### Subject: Summary of additional interagency working comments received on draft rule under EO 12866

review Sent: Friday, November 11, 2011 11:44 AM From: Achanta, Chandana L. 

## To: William Charmley; Jim Tamm james.tamm@dot.gov
Cc: Theroux, Richard P.; Mancini, Dominic J.; Fitzpatr ick, Michael A.; Guzy, Gary S.; Bordoff, Jason E.



### Hello Michael, Katie-

Please find attached additional interagency working comments received on draft NPRM under EO 12866 and EO 13563 review. They are for your consideratio n, and are subject to further policy review.

Thanks. Chandana

Summary of interagency working comments received on draft rule under EO 12866 and EO 13563 review.docx

### Subject: Summary of additional draft interagency working com ments received on draft rule under EO 12866 review

From: "Achanta, Chandana L." [Chandana_L._Achanta@omb.eop .gov] Sent: 11/11/2011 10:53 PM EST To: William Charmley; "'Steve.Wood@dot.gov'" <Steve.Woo d@dot.gov>; "'Neil.Eisner@dot.gov'" <Neil.Eisner@dot.gov>; "''james.tamm@dot.gov' (jame s.tamm@dot.gov)'" <james.tamm@dot.gov>; "'rebecca.yoon@dot.gov'" <rebecca.yoon@dot.gov>



### Please find attached additional draft interagency w orking comments received on draft NPRM under EO 12866 and EO 13563 review. They are for your consid eration and are subject to further policy review.

Thanks. Chandana

Summary of Draft Interagency Working Comments recei ved on draft rule under EO 12866.pdf

### Subject: Summary of additional draft interagency working com ments received on draft rule under EO 12866 review

Sent: 11/12/2011 02:57 PM EST
From: "Achanta, Chandana L." [Chandana_L._Achanta@omb.eop .gov] To: William Charmley; "'Steve.Wood@dot.gov'" <Steve.Woo d@dot.gov>; "'Neil.Eisner@dot.gov'" <Neil.Eisner@dot.gov>; "''james.tamm@dot.gov' (jame s.tamm@dot.gov)'" <james.tamm@dot.gov>; "'rebecca.yoon@dot.gov'" <rebecca.yoon@dot.gov>



### Please find attached additional draft interagency w orking comments received on draft NPRM under EO 12866 and EO 13563 review. They are for your consid eration and are subject to further policy review.

Thanks. Chandana

Summary of interagency working comments received on draft NPRM under EO 12866 and EO 13563 review.pdf

Summary of interagency working comments received on draft NPRM under EO 12866 review.pdfSummary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-1 Below is a summary of interagency working comments received during EO 12866 and EO 13563 review of the draft rule “Joint Rulemaking to Establish Light-Duty Vehicle Greenhouse Gas Emission Standards and Corporate Ave rage Fuel Economy Standards”. They are for your consideration and are subject to furth er policy review.

Interagency commenters recommend that the agencies replace current EPA Chapter 8 with the following working draft language and make consisten t changes throughout the Preamble, NHTSA RIA, and TSD chapters.



## ***

Chapter 8 Vehicle Sales, Employment, and Economy-Wi de Impacts

1.1 Vehicle Sales Impacts

1.1.1 The Effect of Purchase Price and Fuel Savings Chang es on Vehicle Sales

An initial consideration of the Proposed Rule on ve hicle sales impacts must compare two competing effects. On the one hand, as a resul t of this rule, the vehicles will become more expensive, which would, by itself, discourage sales. On the other hand, the vehicles will have improved fuel economy and thus lower operating costs, which makes them more attractive to consumers. The net effect will depen d on the extent to which consumers are willing to pay for fuel economy. As discussed in P reamble III.H of the Proposed Rule, there is considerable uncertainty in the economics litera ture about the extent to which consumers fully value fuel savings from increased fuel econom y. The effect of this proposed regulation on vehicle sales will depend on whether the value p laced on the increased fuel economy is greater or less than the increase in vehicle prices . Of course, there are two possibilities. Consumers will value the fuel economy improvements at amounts that are either greater than or less than the corresponding increase in vehicle price. For the first group of consumers, the standard assumption that producers act to maximize profits implies these vehicles will be produced without a regulation, since consumers woul d be willing to pay the higher price and it would be profitable for the manufacturers to pro duce such vehicles. On the other hand, consumers who value the fuel economy improvements a t less than the corresponding increase in vehicle price would be less likely to buy such v ehicles and a requirement that they be produced nonetheless would generally lead to a decr ease in sales. This is because for these consumers the difference between the value of great er fuel economy and the higher sales prces will be perceived as a pure price increase.

An illustrative example might help. Suppose that a particular improvement in fuel economy causes a vehicle’s production cost to rise by $1,000; and suppose that the auto market were competitive, so that the price rose by the same amount. Consider three scenarios, with different values of fuel savings. First, suppose that consumers valued the Comment [A1]: Interagency commenters note that this may be more complicated than presented in the original example. The original example assumed imperfect competition in the case of high consumer value of fuel savings, but perfect competition in t he case of low consumer value. Interagency commenters suggest that it might be easier to use one market power assumption, and in that case perfect competition might be more intuitive. However, interagency commenters recommend that agencies drop this example.Summary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-2 corresponding fuel savings at moire tha$1,500. In this case, one would expect ordinary market forces to result in these vehicles being pro duced in the absence of regulation, since consumers would pay the price of increase of $1,000 and still be better off than before.In this case, the regulation would have no effect on fuel e conomy or on vehicle sales. In a second scenario, if consumers valued the fuel savings at e xactly $1,000, the regulation might induce manufacturers to build more fuel-efficient cars, bu t it would would have no impact on sales. Because consumer willingness to pay would increase by exactly the amount of the cost, producers could raise prices to just cover their co sts, and the quantity demanded would be the same as before the improvement in fuel economy. Fi nally, if consumers valued the fuel savings at $750, it would not be in manufacturers’ interest to provide them. A requirement that they be produced would lead to cars being prod uced with higher fuel economy. However, while their price would rise by $1,000, th ey would be worth only an additional $750. Consumers would perceive the $250 difference as a pure price increase and sales would decline, with the magnitude of the decline de pending on the price elasticity of vehicle demand. In reality, consumers will vary in their v aluation of fuel savings, for a variety of reasons, including miles driven, local gasoline pri ces, willingness to trade off future savings against initial costs (measured by the rate at whic h consumers discount future fuel savings), and so on. Producer decisions should take such con sumer heterogeneity into account. Nonetheless, the effect of fuel economy standards o n sales will depend on how consumers value future fuel savings relative to the increase in cost.

As noted above and in Preamble III.H, there is cons iderable evidence that consumers undervalue the fuel savings from increased fuel eco nomy. A simple way to capture this is by viewing consumers as applying a high discount rate to future fuel savings [cite literature]. For a consumer with an effective discount rate of 15%, the value of fuel savings – corresponding to the consumer’s willingness to pay for increased fuel economy – would therefore be calculated by discounting the first five years of f uel savings at 15% and summing them. For instance, the 2017 fuel savings per vehicle are the present value in year 2017 of fuel savings estimated for 2017 through 2021, using the assumed discount rate that reflects consumer behavior.

To better understand the factors that can determine the effect of fuel economy standards on vehicle sales, we conduct a simple sal es impact analysis. As a benchmark for our analysis, we maintain the assumption used in th e compliance modeling (discussed in the Preamble XX and in Chapter YY of this DRIA) that ve hicle sales are unaffected by the proposed rule. This approach allows us to ask: What is the effective consumer discount rate for which the increased cost of greater fuel econom y just equals the consumer’s value for fuel savings, so that total vehicle sales are constant?

For the cost of improved fuel economy, we use the i ncrease in cost estimated by the OMEGA model. A

To calculate fuel savings, we start by assuming t hat the consumer holds

A The higher vehicle price is likely to lead to an i ncrease in sales tax, insurance, and vehicle financ ing costs, as well as increases in the resale value of the vehicl e. However, for simplicity we ignore those in this analysis. We point out that to the extent they are included, the y should be discounted using the same effective dis count rateSummary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-3 onto this vehicle for 5 years and then sells it. T his period is consistent with the length of a typical new light-duty vehicle loan, and is similar to the average time that a new vehicle purchaser holds onto the vehicle; it has also been used by NHTSA in previous CAFE rulemakings. B We request comment on whether there are more a ppropriate time periods to consider for this calculation.

We can perform this analysis for an average vehicle in any given model-year. Chapter XX of this DRIA discusses the source of aggregate f uel savings, in dollars, for cars and trucks for each model year by year. These values are divi ded by the total number of the vehicles produced to get per-vehicle savings per year for th e first five years of the vehicle’s life. This method ignores the few vehicles of the new model ye ar that are scrapped. Because incorporating scrappage would reduce the denominato r, and thus increase per-vehicle fuel savings, it underestimates per-vehicle fuel savings by a small amount.

For example, consider model year 2025. In that yea r, the average increase in vehicle cost associated with improved fuel economy is $2100 , while average fuel savings are about $600 per year (Preamble XXX and DRIA Chapter YYY). Under the assumption that consumer consider five years of fuel savings, the “ breakeven discount rate” is 15.5% . In other words, if the entire increased cost of $2100 is passed onto consumer in the form of a higher initial purchase price, consumer willingness to pay for the resulting fuel savings would just balance out the initial cost if they apply a d iscount rate of 15.5% to the annual fuel savings for the first five years. Put yet another way, a discount rate of 15.5% is consistent with the following assumptions: (i) consumers do no t fully value fuel savings; (ii) producers seek to maximize profits; and (iii) fuel economy st andards will change the vehicle mix without affecting total vehicle sales.

We request comment on whether those parameters abov e are representative of current market conditions. For example, what discount rate is appropriate for consumer decision making on durable goods? The agency requests that commenters point to additional studies or data sources that can be used in updated those a ssumptions.

The breakeven discount rate calculated above can se rve as a benchmark in evaluating the effect of the regulation on sales under other a ssumptions about consumer behavior. In theory, if consumers apply a lower effective discou nt rate, so that they are willing to pay more for fuel economy, sales would increase following an improvement in fuel economy.

used to discount fuel savings. That significantly complicates the analysis. These factors weigh agai nst each other: the higher sales tax, insurance, and financ ing costs increase costs to consumers; the higher r esale value allows consumers to recover a portion of these cost s. B As discussed further in Chapter 8.1.2.5, there is not a consensus in the literature on how consumers consider fuel economy in their vehicle purchases. Results a re inconsistent, possibly due to fuel economy not b eing a major focus of many of the studies, and possibly du e to sensitivity of results to modeling and data us ed. A survey by Greene (Greene, David L. “How Consumers V alue Fuel Economy: A Literature Review.” EPA Report EPA-420-R-10-008, March 2010 (Docket EPA-HQ- OAR-2009-0472-11575)) finds that estimates in the literature of the value that consumers place on fue l economy when buying a vehicle range from negative
– consumers would pay to reduce fuel economy – to more than 1000 times the value o f fuel savings. Comment [A2]: Interagency commenters note that it may be preferable to consider another year, e.g., 2017.Summary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-4 However, such an effect should already be reflected in the baseline without regulation (i.e., producers should already be producing the vehicles that consumers desire to purchase); otherwise, such an outcome would be inconsistent wi th the standard assumption that producers maximize profits.

If consumers apply an even higher effective discoun t rate in valuing fuel savings [as some studies of consumer durables suggest], then co nsumer valuation of potential fuel savings would be less than the cost of the increased techno logy, and sales would be expected to decline. The magnitude of this impact would depend on the net cost of improved fuel economy, after accounting for fuel savings, as well as on the elasticity of demand. A standard value for the elasticity of demand for new vehicles of -1: 1 that is, an increase of 1% in the price of a new vehicle will lead to a 1% reduction in new vehicle sales. This elasticity is generally considered to be a short-run elasticity, reflecting the immediate impacts of an immediate price change on vehicle sales. For a dur able good such as an auto, the elasticity may be smaller in the long run: though people may be able to change the timing of their purchase when price changes in the short run, they must eventually make the investment. Using a smaller elasticity would reduce the magnitu de of the estimates presented here for vehicle sales, but it would not change the directio n. A short-run elasticity is more valid for initial responses to changes in price, but, over ti me, a long-run elasticity may better reflect behavior; thus, the results presented for the initi al years of the program may be more appropriate for modeling with the short-run elastic ity than the later years of the program. A search of the literature has not found studies more recent than the 1970s that specifically investigate long-run elasticities. C This change in consumer expenditure as a percent of the average price of a new vehicle, with the elasticity of demand of -1, is the negative of the percent change in vehicle purchases.

Evaluating the impact of the fuel economy rule on v ehicle sales also depends on a number of assumptions that become less certain the further into the future they are applied. For example, consumers are heterogeneous in their b ehavior: some types of consumers may value fuel economy highly, while others give it les s weight. Thus the effect of fuel economy on sales will depend on the distribution of consume r types in the population. For vehicle sales, these include the future path of gasoline pr ices, changes in future cost of fuel-saving technologies, changing market conditions, and other shifts in the U.S. economy that could affect vehicle demand and national driving behavior

.
Adding to the uncertainty is the dynamic effect tha t the proposed rule may have on other relevant aspects of the vehicle sales market aside from purchase price. For example, the proposed rule may induce technological change that would not have occurred otherwise, and introduce consumers to new vehicle attributes that impact vehicle demand in a positive way.

C E.g., Hymans, Saul H. “Consumer Durable Spending: Explanation and Prediction.” Brookings Papers on Economic Activity 1 (1970): 173-206. http://www.brookings.edu/~/media/Files/Programs/ES/ BPEA/1970_2_bpea_papers/1970b_bpea_hymans_ackley _juster.pdf finds a short-run elasticity of auto ex penditures (not sales) with respect to price of 0.7 8 50 1.17, and a long-run elasticity of 0.3 to 0.46.Summary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-5 Similarly, improvements in vehicle economy might ac company other changes in vehicle characteristics that are relevant for purchase deci sions.

The agency requests comment on how future uncertai nty about economic conditions my present unique difficulties in conducting a sale s impact analysis for this rulemaking.

While these factors are always present, they are pa rticularly acute in the current context, in which the rule will not take effect unt il 2017. As a result, we are not seeking to quantify the impacts of this proposed rule on vehic le sales. We welcome comments on all aspects of this discussion, including assumptions o n consumer behavior; how consumers value future fuel savings at the time of purchase; factors that should be taken into account when assessing the impact of fuel economy standard on aggregate vehicle sales; sources of uncertainty in estimating vehicle sales impacts. W e also welcome quantitative estimates of the effects on sales, accompanied by detailed descr iptions of the methodologies used.

1.1.2 Consumer Vehicle Choice Modeling D

The vehicle sales analysis outlined above focuses o n the comparison between the increased purchase price associated with improved f uel economy and the value of the resulting fuel savings. An alternative approach is the use of consumer vehicle choice models. In this section we describe some of the consumer ve hicle choice models EPA has reviewed in the literature, and we describe the models’ results and limitations that we have identified. The evidence from consumer vehicle choice models indica tes a huge range of estimates for consumers’ willingness to pay for additional fuel e conomy. Because consumer surplus estimates from consumer vehicle choice models depen d critically on this value, we would consider any consumer surplus estimates of the effe ct of our rule from such models to be unreliable. In addition, the predictive ability of consumer vehicle choice models may be limited. While vehicle choice models are based on sales of existing vehicles, vehicle models are likely to change, both independently and in res ponse to this rule. The models may not predict well in response to these changes. Instead , we compare the value of the fuel savings associated with this rule with the increase in tech nology costs. EPA will continue its efforts to review the literature, but, given the known limitat ions and uncertainties of vehicle choice models, EPA has not conducted an analysis using the se models for this proposal.

This rule will lead automakers to change characteri stics – in particular, the fuel economy -- of the vehicles they produce. These cha nges will affect the cost of manufacturing the vehicle; as a result, the prices of the vehicle s will also change.

In response to these changes, the number and types of vehicles sold is likely to change. When consumers buy vehicles, they consider both the ir personal characteristics (such as age, family composition, income, and their vehicle needs ) and the characteristics of vehicles (e.g.,

D This section is drawn heavily from Helfand, Gloria , and Ann Wolverton, “Evaluating the Consumer Respo nse to Fuel Economy: A Review of the Literature.” Int ernational Review of Environmental and Resource Economics 5 (2011): 103-146.Summary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-6 vehicle size, fuel economy, and price). In respon se to the changes in vehicle characteristics, consumers will reconsider their purchases. Increas es in fuel economy are likely to be attractive to consumers, but increases in price, as well as any detrimental changes in other vehicle characteristics, may be deterrents to purch ase. As a result, consumers may choose a different vehicle than they would have purchased in the absence of the rule. The changes in prices and vehicle characteristics are likely to in fluence consumers on multiple market scales: the total number of new vehicles sold; the mix of n ew vehicles sold; and the effects of the sales on the used vehicle market.

Consumer vehicle choice modeling (CCM) is a method used to predict what vehicles consumers will purchase based on vehicle characteri stics and prices. In principle, it should produce more accurate estimates of compliance costs compared to models that hold fleet mix constant, since it predicts changes in the fleet mi x that can affect compliance costs. It can also be used to measure changes in consumer surplus, the benefit that consumers perceive from a good over and above the purchase price. (Consumer surplus is the difference between what consumers would be willing to pay for a good, repre sented by the demand curve, and the amount they actually pay. For instance, if a consu mer were willing to pay $30,000 for a new vehicle, but ended up paying $25,000, the $5000 dif ference is consumer surplus.)

A number of consumer vehicle choice models have bee n developed. They vary in the methods used, the data sources, the factors include d in the models, the research questions they are designed to answer, and the results of the mode ls related to the effects of fuel economy on consumer decisions. This section will give some ba ckground on these differences among the models.

1.1.2.1 Methods

Consumer choice models (CCMs) of vehicle purchases typically use a form of discrete choice modeling. Discrete choice models seek to ex plain discrete rather than continuous decisions. An example of a continuous decision is how many pounds of food a farm might grow: the pounds of food can take any numerical va lue. Discrete decisions can take only a limited set of values. The decision to purchase a vehicle, for instance, can only take two values, yes or no. Vehicle purchases are typically modeled as discrete choices, where the choice is whether to purchase a specified vehicle. The result of these models is a prediction of the probability that a consumer will purchase a specified vehicle. A minor variant on discrete choice models estimates the market share ( a continuous variable between 0 and 1) for each vehicle. Because the market share is, essenti ally, the probability that consumers will purchase a specific vehicle, these approaches are s imilar in process; they differ mostly in the kinds of data that they use.

The primary methods used to model vehicle choices a re nested logit and mixed logit. E In a nested logit, the model is structured in layer s. For instance, the first layer may be the

E Logit refers to a statistical analysis method used for analyzing the factors that affect discrete cho ices (i.e., yes/no decisions or the choice among a countable nu mber of options).Summary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-7 choice of whether to buy a new or used vehicle. Gi ven that the person chooses a new vehicle, the second layer may be whether to buy a car or a t ruck. Given that the person chooses a car, the third layer may be the choice among an economy, midsize, or luxury car. Examples of nested logit models include Goldberg, 2 Greene et al., 3 and McManus. 4

In a mixed logit, personal characteristics of consu mers play a larger role than in nested logit. While nested logit can look at the effects of a change in average consumer characteristics, mixed logit allows consideration o f the effects of the distribution of consumer characteristics. As a result, mixed logit can be u sed to examine the distributional effects on various socioeconomic groups, which nested logit is not designed to do. Examples of mixed logit models include Berry, Levinsohn, and Pakes, 5 Bento et al., 6 and Train and Winston. 7

While discrete choice modeling appears to be the pr imary method for consumer choice modeling, others (such as Kleit 8 and Austin and Dinan 9 ) have used a matrix of demand elasticities to estimate the effects of changes in cost. The discrete choice models can produce such elasticities. Kleit as well as Austin and Din an used the elasticities from an internal GM vehicle choice model.

1.1.2.2 Data Sources

The predictions of vehicle purchases from CCMs are based on consumer and vehicle characteristics. The CCMs identify the effects of changing the characteristics on the purchase decisions. These effects are typically called the parameters or coefficients of the models. For instance, the model parameters might predict that a n increase in a person’s income of 10% would increase the probability of her purchasing ve hicle A by 5%, and decrease the probability of her purchasing vehicle B by 10%.

The parameters in CCMs can be developed either from original data sources (estimated models), or using values taken from othe r studies (calibrated models).

Estimated models use datasets on consumer purchase patterns, consumer characteristics, and vehicle characteristics to dev elop their original sets of parameters. The datasets used in these studies sometimes come from surveys of individuals’ behaviors. 10 Because they draw on the behavior of individuals, t hey provide what is sometimes called micro-level data. Other studies, that estimate mar ket shares instead of discrete purchase decisions, use aggregated data that can cover long time periods. 11

Calibrated models rely on existing studies for thei r parameters. Researchers may draw on results from a number of estimated models, or ev en from research other than CCM, to choose the parameters of the models. The Fuel Econ omy Regulatory Analysis Model developed for the Energy Information Administration 12 and the New Vehicle Market Model developed by NERA Economic Consulting 13 are examples of calibrated models.Summary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-8 1.1.2.3 Factors Included in the Models

Consumer choice models vary in their complexity and levels of analysis. Some focus only on the new vehicle market; 14 others consider the choice between new vehicles an d an outside good (possibly including a used vehicle); 15 others explicitly consider the relationship between the new and used vehicle markets. 16 Some models include consideration of vehicle miles traveled, 17 though most do not.

The models vary in their inclusion of both consumer and vehicle information. One model includes only vehicle price and the distribut ion of income in the population influencing choice; 18 others include varying numbers and kinds of vehicl e and consumer attributes.

Some models include only the consumer side of the v ehicle market; 19 others seek to represent both consumer and producer decisions. 20 Models that include only the consumer side are suitable for reflecting consumer choices, but they do not allow for revisions of vehicle characteristics in response to consumer pre ferences. Including producer behavior allows for vehicle characteristics such as price an d fuel economy to be the result of market forces rather than characteristics of the existing fleet. For instance, in the context of “feebates” (subsidizing fuel-efficient cars with re venue collected by taxing fuel-inefficient vehicles), Greene et al. estimated that 95% of the increase in fuel economy was due to addition of technology rather than changes in vehic les sold. 21 Including auto maker response is a complex exercise. Auto makers are commonly co nsidered to have market power; they can influence the prices that consumers pay to incr ease their profits. As a result, the price increases that consumers face may reflect strategic factors that could make them higher or lower than the technology costs. In addition, auto makers may seek to influence consumer preferences through marketing and advertising. 22 Even those vehicle choice models that include a producer model may not include much detai l, due to computational limits: allowing market forces to determine multiple vehicle charact eristics is still under development. 23

1.1.2.4 Research Questions for the Models

Consumer choice models have been developed to analy ze many different research and policy questions. In part, these models have been developed to advance the state of economic modeling. The work of Berry, Levinsohn, and Pakes, 24 for instance, is often cited outside the motor vehicle context for its incorporation of mult iple new modeling issues into its framework. In addition, because the vehicle sector is a major part of the U.S. economy and a stakeholder in many public policy discussions, rese arch questions cover a wide gamut. These topics have included the effects of voluntary expor t restraints on Japanese vehicles compared to tariffs and quotas, 25 the market acceptability of alternative-fuel vehic les, 26 the effects of introduction and exit of vehicles from markets, 27 causes of the decline in market shares of U.S. automakers, 28 and the effects of gasoline taxes 29 and “feebates” 30 (subsidizing fuelefficient cars with revenue collected by taxing fue l-inefficient vehicles).Summary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-9 1.1.2.5 The Effect of Fuel Economy on Consumer Decisions

Consumer vehicle choice models typically consider t he effect of fuel economy on vehicle purchase decisions. It can appear in vario us forms.

Some models 31 incorporate fuel economy through its effects on th e cost of owning a vehicle. With assumptions on the number of miles t raveled per year and the cost of fuel, it is possible to estimate the fuel savings (and perhaps other operating costs) associated with a more fuel-efficient vehicle. Those savings are con sidered to reduce the cost of owning a vehicle: effectively, they reduce the purchase pri ce. This approach relies on the assumption that, when purchasing vehicles, consumers can estim ate the fuel savings that they expect to receive from a more fuel-efficient vehicle and cons ider the savings equivalent to a reduction in purchase price. Turrentine and Kurani 32 question this assumption; they find, in fact, that consumers do not make this calculation when they pu rchase a vehicle. The question remains, then, how or whether consumers take fuel economy in to account when they purchase their vehicles.

Most estimated consumer choice models, instead of m aking assumptions about how consumers incorporate fuel economy into their decis ions, use data on consumer behavior to identify that effect. In some models, miles per ga llon is one of the vehicle characteristics included to explain purchase decisions. Other mode ls use fuel consumption per mile, the inverse of miles per gallon, as a measure: 33 since consumers pay for gallons of fuel, then thi s measure can assess fuel savings relatively directly

. 34 Yet other models multiply fuel consumption per mile by the cost of fuel to get the cost of driving a mile, 35 or they divide fuel economy by fuel cost to get miles per dollar. 36 It is worth noting that these last two measures assume that consumers respond the same way to an in crease in fuel economy as they do to a decrease in the price of fuel when each has the sam e effect on cost per mile driven. F On the one hand, while this assumption does not rely on as complex a calculation as the present value of fuel savings that Turrentine and Kurani examined , it suggests a calculating consumer. On the other hand, using a form of cost per mile is a way to recognize the role of fuel prices in consumers’ purchase of fuel economy: recent resear ch 37 presents results that higher fuel prices play a major role in that decision.

Greene and Liu, 38 in a paper published in 1988, reviewed 10 papers u sing consumer vehicle choice models and estimated for each one ho w much consumers would be willing to pay at time of purchase to reduce vehicle operating costs by $1 per year. They found that people were willing to pay between $0.74 and $25.97 for a $1 decrease in annual operating costs for a vehicle. This is clearly a very wide r ange: while the lowest estimate suggests that people are not willing to pay $1 once to get $1 per year reduced costs of operating their

F Likewise, these measures assume consumers respond the same way to increases and decreases in cost per mile of driving, as well as if those increases and decre ases are large shocks rather than small, gradual ch anges. The issue of potential asymmetric consumer response to increased fuel efficiency compared to other types o f changes to the cost of driving also arises and is discussed in the context of the VMT rebound effect (see Sect ion III.H.4 of the Preamble and Chapter 4.2.5.2 of the TSD).Summary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-10 vehicles, the maximum suggests a willingness to pay 35 times as high. For comparison, the present value of saving $1 per year for 15 years at a 3% discount rate is $11.94, while a 7% discount rate produces a present value of $8.78. W hile this study is quite old, it suggests that, at least as of that time, consumer vehicle choice m odels produced widely varying estimates of the value of reduced vehicle operating costs.

A newer review from David Greene 39 suggests continued lack of convergence on the value of increased fuel economy to consumers. Of 2 7 studies, willingness to pay for fuel economy as a percent of the expected value of fuel savings varied from highly positive to highly negative. Significant numbers of studies fo und that consumers overvalued fuel economy, undervalued fuel economy, or roughly value d fuel economy correctly relative to fuel savings. Part of the difficulty may be, as th ese papers note, that fuel economy may be correlated (either positively or negatively) with o ther vehicle attributes, such as size, power, or quality, not all of which may be included in the analyses; as a result, “fuel economy” may in fact represent several characteristics at the sa me time. Indeed, Gramlich 40 includes both fuel cost (dollars per mile) and miles per gallon i n his analysis, with the argument that miles per gallon measures other undesirable quality attri butes, while fuel cost picks up the consumer’s demand for improved fuel economy. Green e finds that, while some of the variation may be explainable due to issues in some of the studies, the variation shows up in studies that appear to be well conducted. As a res ult, further work needs to be conducted before it is possible to identify one value that re presents the role of fuel economy in consumer purchase decisions.

Some studies 41 argue that automakers could increase profits by in creasing fuel economy because the amount that consumers are willi ng to pay for increased fuel economy outweighs the costs of that improvement. Other stu dies 42 have found that increasing fuel economy standards imposes welfare losses on consume rs and producers, because consumers should already be buying as much fuel economy as th ey want. In the course of reaching this result, though, at least one of these studies 43 notes that its baseline model implies that consumers are willing to buy more fuel economy than producers have provided; they have to adjust their model to eliminate these “negative-cos t” fuel economy improvements.

The models do not appear to yield very consistent r esults on the role of fuel economy in consumer and producer decisions.

1.1.2.6 Modeling Electric Vehicles and Other New Vehicles

Modeling the introduction of new vehicles can be a greater challenge than modeling the existing vehicle market, because the modeler do es not have data on how many of the new vehicles consumers buy. Nevertheless, it can be po ssible to estimate the effects of new vehicle introduction by identifying characteristics for the new vehicles and using those in a vehicle choice model. For instance, as discussed a bove, the models can estimate effects on the vehicle market when vehicles change their fuel economy or price. If the model incorporates other vehicle attributes important to the new vehicles, such as size, performance,Summary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-11 or range, then the effect of the introduction can b e modeled by applying the parameters for those features to the new vehicle characteristics.

As discussed above, some models rely on vehicle pri ce as the primary or only explanatory variable. Even in these models, it is possible, with some additional information, to consider the effects of new vehicle introduction . The first step is to find a vehicle similar on as many dimensions as possible to the new vehicl e. For instance, if the change is to create an electric vehicle (EV) version of an existing mod el, then the existing model serves as the base vehicle. Next, it is necessary to measure the changes in vehicle attributes of interest to potential vehicle buyers. For an EV, changes in ve hicle driving range and cost of fueling may be two such attributes. The next requirement is in formation on the value to consumers of the attributes that change between the new and the base vehicle. Multiplying the value for that attribute by the change in the attribute provides a n estimate of the benefit or cost associated with changing that characteristic. That amount can then be added to or subtracted from the vehicle purchase price to give an adjusted purchase price reflecting the changed characteristic. This procedure is just an extension of the approach , discussed above, used to incorporate fuel economy improvements into vehicle choice models, by calculating future fuel savings and subtracting them (either in whole or a fraction) fr om vehicle purchase price.

Incorporating new vehicles into a vehicle choice mo del, then, requires estimates of the changes in key attributes from conventional vehicle s, and estimates of the value, also called the willingness to pay (WTP), that consumers put on those attributes.

Electric vehicles (EVs) will have a number of chang es in vehicle characteristics from any baseline model. EVs are likely to have a small er driving range between refuelings than conventional vehicles, due to the large battery cap acity needed to increase range. The ability to recharge at home may be a convenient, desirable feature for people who have garages with electric hookups, but not for people who park on th e street. If an infrastructure develops for recharging vehicles with the convenience approachin g that of buying gasoline, range or home recharging may become less of a barrier to purchase . The reduced tailpipe emissions and reduced noise may be attractive features to some co nsumers. G They may have different performance or storage capacity. If sufficient dat a were available, the changes in these attributes, combined with WTP for each of the attri butes, could be used to adjust the purchase price of the baseline vehicle to estimate consumers ’ WTP for the electric version of a vehicle. Greene (2001), for instance, used this approach for a model that simulates choice, not only for EVs, but also for other alternative-fuel vehicles. 44 In that model, he considers only one base vehicle, a passenger car, but considers the effect on WTP of fuel cost per mile, range, acceleration, and several other vehicle attributes.

G For instance, Hidrue et al. (Hidrue, Michael K., G eorge R. Parsons, Willett Kempton, and Meryl P. Gar dner. “Willingness to Pay for Electric Vehicles and their Attributes.” Resource and Energy Economics 33(3) (2011): 686-705) find that some consumers are willing to pa y $5100 more for vehicles with 95% lower emissions than the vehicles they otherwise aim to purchase.Summary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-12 Vehicle driving range has received attention becaus e of the current paucity of recharging infrastructure: if the driver of an EV gets low on fuel, it may be difficult to find a place to recharge. Because range appears to be a m ajor factor in EV acceptability, it is starting to draw attention in the research communit y.

In several studies, researchers have used stated pr eference conjoint analysis to estimate the effect of vehicle range on consumer ve hicle choice. In a conjoint analysis, consumers are given a choice between several vehicl es with different attributes. One choice might be, for instance, between a baseline car and another car with higher range and a higher purchase price. The choices that consumers make (e .g., how much higher does the purchase price have to be for the consumer not to choose mor e range?) provide data that can be used to estimate the role of vehicle attributes in the cons umer’s choice. Stated preference analysis is sometimes considered less reliable than actual mark et behavior, because what people say they will do in hypothetical situations may not match wh at they would do in actual situations. On the other hand, stated preference methods can be us ed to study goods where market data do not exist, such as future market products undergoin g development (marketing studies often use stated preference methods), or environmental go ods. Because electric vehicles are not in widespread enough use for market studies, stated pr eference studies are, at this point, one of the few options to examine consumer behavior relati ng to these vehicles.

Table 1.1-1 summarizes results from several conjoin t studies that include the effects of extending range (in the table, from 150 to 300 mile s, to present standardized results). Variation of results in the table is from income or other demographic factors, not from confidence intervals. The results suggest that the value of additional range varies among consumers, and the amount of that variation is chan ging (perhaps shrinking) in more recent studies.

Table 1.1-1Willingness to Pay for Increasing Range Calculated from Various Studies

Study (Date) Value of extending range from 150 to 300 miles (dollar

year) Value of additional

range in 2009$ a

Bunch et al. (1993) b $7,600 (1991$) $11,100

Kavelek (1996) for California Energy Commission c $2600 - $41,900 (1993$) $3700 - $58,700

Resource Systems Group (2009) for California Energy Commission d $2900 - $7500 (2009$) $2900 - $7500Summary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-13 Hess et al. (2009), using the same data as Resource Systems Group (2009) e $2400 - $8500 (2009$) $2400 - $8500

Hidrue et al. (2011) f $3776 - $10,399 (2009$) $3776 - $10,399

a Values adjusted to 2009$ using the Bureau of Econom ic Analysis GDP deflator.

b Bunch, David S., Mark Bradley, Thomas F. Golob, and Ryuichi Kitamura. “Demand for Clean-Fuel Vehicles in California: A Discrete-Choice Stated Preference Pilot Project.” Transportation Research Part A 27A(3) (1993): 237-253. The value of range was, in their model, assumed to be the same for all people.

c Kavelek, Chris. “CALCARS: The California Conventi onal and Alternative Fuel Response Simulator.” Demand Analysis Office, California Energy Commissio n, April 1996. The variation in values is due to willingness to pay (WTP) varying by income levels a nd for one-car and two-car households. The coeffic ient on range for one-car households was not statistically significantly different from zero (t-statistic = 1. 5), but it was for 2-car households (t-statistic = 3.02). The min ima and maxima presented here represent the values across both ownership and income categories.

d Resource Systems Groups, Inc. “Transportation Fuel Demand Forecast Household and Commercial Fleet Survey Task 8 Report: Logistic Regression Analysis and Results.” Prepared for California Energy Comm ission, June 2009.

e Hess, S., T. Adler, M. Fowler and A. Bahreinian “Th e Use of Cross-nested Logit Models for Multi-Dimens ional Choice Processes: The Case of the Demand for Altern ative Fuel Vehicles,” Proceedings of the 2009 European Transport Conference , Leiden, Netherlands, 2009. This study uses the s ame data as the Resource Systems Group study. The coefficient on range was not stat istically significantly different from zero in thes e regressions: t-statistics varied from 1.29 to 1.52. The variati on in values is due to willingness to pay (WTP) var ying by income levels and statistical specification. The m inima and maxima presented here represent the value s across both income categories and specifications.

f Hidrue, Michael K., George R. Parsons, Willett Kemp ton, and Meryl P. Gardner. “Willingness to Pay for Electric Vehicles and their Attributes.” Resource and Energy Economics 33(3) (2011): 686-705. The range of values is due to the model separating consumers int o “gasoline vehicle-oriented” and “electric vehicle -oriented” groups. The EV-oriented group has higher WTP for a dditional range.

Driving range may be a major factor in consumers’ d ecisions on EVs, but it is not the only attribute that may be important to potential b uyers (e.g., as noted, Hidrue et al. find that some consumers appear willing to pay substantially for reduced tailpipe emissions). A model that does not incorporate the other factors importa nt to consumers’ decisions may not perform well in predicting vehicle purchases. In addition, as mentioned above, and as seen in Table 1.1-1, it is likely that the WTP values for attribu tes of EVs will change over time, particularly if EVs are used more widely, the infrastructure to fuel the vehicles becomes more accessible, and consumers develop more familiarity and understa nding of the vehicles. Thus, challenges associated with predicting market shares for EVs ar e even more serious than those already serious challenges associated with predicting marke t shares for conventional vehicles.

1.1.2.7 EPA Exploration of Vehicle Choice Modeling

In order to develop greater understanding of these models, EPA is in the process of developing a vehicle choice model. In its current form, the model assumes that the vehicleSummary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-14 fleet and all characteristics of each vehicle, exce pt vehicle prices and fuel economy, stay the same. The model will predict changes in the vehicl e fleet, at the individual-configuration level and at more aggregated levels, in response to changes in vehicle fuel economy and price.

The draft EPA model uses a nested logit structure c ommon in the vehicle choice modeling literature, as discussed above in Chapter 1.1.2.1. “Nesting” refers to the decisiontree structure of the model, and “logit” refers to the fact that the choices are discrete (i.e., yes/no decisions about which vehicles to purchase, instead of continuous values).

The nesting involves a hierarchy of choices. In it s current form, at the initial decision node, consumers choose between buying a new vehicle or not. Conditional on choosing a new vehicle, consumers then choose between passenge r vehicles, cargo vehicles, and ultraluxury vehicles. The next set of choices subdivide s each of these categories into vehicle type (e.g., standard car, minivan, SUV, etc.). Next, th e vehicle types are divided into classes (small, medium, and large SUVs, for instance), and then, at the bottom, are the individual vehicle configurations.

At this bottom level, vehicles that are similar to each other (such as standard subcompacts, or prestige large vehicles) end up in the same “nest.” Substitution within a nest is considered much more likely than substitution ac ross nests, because the vehicles within a nest are more similar to each other than vehicles i n different nests. For instance, a person is more likely to substitute between a Chevrolet Aveo and a Toyota Yaris than between an Aveo and a pickup truck. In addition, substitution is g reater at low decision nodes (such as individual configurations) than at higher decision nodes (such as the buy/no buy decision), because there are more choices at lower levels than at higher levels.

Parameters for the model (including demand elastici ties and the value of fuel economy in purchase decisions) are being selected based on a review of values found in the literature on vehicle choice modeling. As discussed above, a number of studies have estimated these parameters. Those estimates, combined with some th eoretical requirements, H assist in assigning values for the parameters. The model wil l allow individual users to change those parameters.

The fuel economy of a vehicle is used to adjust the price of the vehicle, using a version of the procedure discussed in Chapter 1.1.2 .6: the value that the consumer places on fuel economy is multiplied by the change in fuel ec onomy and incorporated into the “effective price” of the vehicle. In practice, implementing t his calculation involves calculating the change in expenditures on fuel based on schedules o f VMT, vehicle survival, and fuel prices in the future consistent with those in OMEGA. As d iscussed in Chapter 1.1.2.5, there is no consensus value for consumers’ willingness to pay f or improved fuel economy: estimates

H The theory of nested logit requires that the price slopes (the change in utility as vehicle full pric e changes, a measure of consumer responsiveness to price changes ) must be higher in absolute value for lower nests. This condition reflects the point, discussed above, that substitution is greater at lower decision notes th an at higher

ones.Summary of interagency working comments received on draft rule under EO 12866 and EO

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2-15 vary tremendously. The model assumes that consumer s will use some years of discounted fuel savings, with the modeler able to input both t he number of years and the discount rate to be used in the analysis.

The vehicle choice model will take as inputs from O MEGA the initial fleet of vehicles (including the initial sales and fuel economy), the cost of technologies added to each vehicle, and the change in fuel economy. With the initial s ales mix, for each vehicle, the model calculates a vehicle-specific constant that summari zes the value of all attributes of the vehicle other than price and fuel economy. This constant e nsures that the model will predict the baseline vehicle fleet when the baseline fleet char acteristics are used as inputs. This constant substitutes for estimating the effects of changes i n all other vehicle characteristics; the underlying assumption is that these other vehicle c haracteristics do not change. For instance, it assumes that a Ford Escape will not change in si ze, power, or accessories; the only changes will be to its cost and its fuel economy.

The model assumes that the increase in vehicle co st associated with increased technology is fully passed through as an increase i n price, and some years of fuel savings offset this price increase. It then calculates cha nges in total fleet size and in sales mix, at the individual-configuration level and at the level of vehicle class, due to the changes in fuel economy and vehicle prices. It also calculates cha nges in consumer surplus associated with the changes in fuel economy and vehicle prices.

It is possible that the predicted changes in fleet mix will lead to vehicle sales for auto makers that do not meet the proposed standards. To correct this problem, it would be necessary to feed the new fleet mix into OMEGA (whi ch calculates costs and compliance) and get a new set of output, which could then be fe d back into the vehicle choice model. OMEGA would increase technologies, and thus costs, to improve compliance; those adjustments would then again affect vehicle demand. We expect that this iteration process would converge to a fleet mix that would meet stand ards. Performing this iteration requires development of an interface between the vehicle cho ice model and OMEGA to ensure accurate transmission of data between the models. At this time, the vehicle choice model takes output from OMEGA, but the results of the mod eling do not feed easily back into OMEGA. Building this interface is an expected part of our future modeling work.

The model is still undergoing development; EPA will seek peer review on it before it is utilized. In addition, concerns remain over the ability of any vehicle choice model to make reasonable predictions of the response of the vehic le fleet to changes in prices and vehicle characteristics. EPA seeks comments on the use of vehicle choice modeling for predicting changes in fleet mix due to policies, and on method s to test the ability of a vehicle choice model to produce reasonable estimates of changes in fleet mix.

1.1.2.8 Summary and Additional Considerations

Consumer vehicle choice modeling in principle can p rovide a great deal of useful information for regulatory analysis, helping to ans wer some of the central questions aboutSummary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-16 relevant effects on consumer welfare. In practice, the advantages depend on the success of models in predicting changes in fleet size and mix.

First, consumer vehicle choice modeling has the pot ential to describe more accurately the impact of a policy, by identifying market shift s. More accurate description of the market resulting from a policy can improve other estimates of policy impacts, such as the change in total vehicle emissions or vehicle miles traveled. The predictive ability of models, though, is not proven.

Vehicle choice models can incorporate the effects o n consumer decisions of changes in vehicle characteristics, if there are estimates of the value that consumers put on changes in those characteristics. These willingness-to-pay va lues may, however, be sensitive to the ways they are estimated, as indicated in the discussion of the value that consumers place on fuel economy in their purchase decisions. Especially fo r characteristics associated with advanced technology vehicles, such as EVs, the willingness-t o-pay values may change over time as consumers develop more experience with the vehicles and these characteristics. Models based on current estimates may not predict well for the future.

The modeling may improve estimates of the complianc e costs of a rule. Consumers can either accept the new costs and vehicle charact eristics, or they can change which vehicles they buy. The fact that consumers have additional options suggests that compliance costs are likely to be lower through incorporation of a consu mer choices than through use of a technology-cost model alone.

An additional complication associated with consumer choice modeling is accurate prediction of producers’ responses to the rule. Wh ile it is possible to include auto makers’ decisions (for instance, on setting prices) into ve hicle choices, computational limits affect the richness of these models. Technology costs, while an accurate measure of the opportunity cost of resources to society, may overestimate or u nderestimate the effect on the prices that consumers face.

Consumer choice models can be used to calculate con sumer surplus impacts on vehicle purchase decisions. Because these values a re based on the estimates of changes in vehicle sales and fleet mix, consumer surplus measu res may not be accurate if the changes in vehicle sales and fleet mix are not well estimated.

Principles of welfare analysis can be useful for un derstanding the role of consumer vehicle choice models in benefit-cost analysis. In particular, except for EVs, the technology cost estimates developed in this proposal take into account the costs to hold other vehicle attributes, such as size and performance, constant. In addition, the analysis assumes that the full technology costs are passed along to vehicle b uyers. With these assumptions, because welfare losses are monetary estimates of how much b uyers would have to be compensated toSummary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-17 be made as well off as in the absence of the change

, I the price increase measures the loss to the buyer. J Assuming that the full technology cost gets passe d along to the buyer as an increase in price, the technology cost thus measure s the welfare loss to the buyer. Increasing fuel economy would have to lead to other changes in the vehicles that buyers find undesirable for there to be additional losses not included in t he technology costs.

Given the current limitations in modeling the role of fuel economy in vehicle purchase decisions, and limitations in modeling market respo nses to the new regulations, in this proposal EPA holds constant the vehicle fleet size and mix in its calculations of the impacts of this rule, and compares the fuel and other savings that consumers will receive with the technology costs of the vehicles. EPA continues to explore options for including consumer and producer choice in modeling the impacts of fuel economy-related regulations. This effort includes further review of existing consumer vehicl e choice models, the estimates of consumers’ willingness to pay for increased fuel ec onomy, and overall effects on consumer welfare, as well as EPA’s exploration of a vehicle choice model for use in the future.

1.2 Employment Impacts

1.2.1 Introduction

Although analysis of employment impacts is not part of a cost-benefit analysis (except to the extent that labor costs contribute to costs) , employment impacts of federal rules are of particular concern in the current economic climate of sizeable unemployment. When President Obama requested that the agencies develop this program, he sought a program that would “strenghten the [auto] industry and enhance j ob creation in the United States.” 45,K The recently issued Executive Order 13563, “Improving R egulation and Regulatory Review” (January 18, 2011), states, “Our regulatory system must protect public health, welfare, safety, and our environment while promoting economic growth, innovation, compe titiveness, and job creation ” (emphasis added). EPA is accordingly providing e stimates of the effects of this proposal on domestic employment.

I This approach describes the economic concept of co mpensating variation, a payment of money after a ch ange that would make a consumer as well off after the ch ange as before it. A related concept, equivalent v ariation, estimates the income change that would be an altern ative to the change taking place. The difference b etween them is whether the consumer’s point of reference i s her welfare before the change (compensating varia tion) or after the change (equivalent variation). In practi ce, these two measures are typically very close tog ether.

J Indeed, it is likely to be an overestimate of the loss to the buyer, because the buyer has choices ot her than buying the same vehicle with a higher price; she co uld choose a different vehicle, or decide not to bu y a new vehicle. The buyer would choose one of those optio ns only if the alternative involves less loss than paying the higher price. Thus, the increase in price that the buyer faces would be the upper bound of loss of co nsumer welfare, unless there are other changes to the vehi cle due to the fuel economy improvements that make the vehicle less desirable to buyers.

K The May 21, 2010 Presidential Memorandum also requ ested that EPA and NHTSA, in developing the technical assessment to inform the rulemaking proce ss (which was issued by the agencies and CARB on September 30, 2010), include, among other things, t he “impacts on jobs and the automotive manufacturin g base in the United States.”Summary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-18 This proposal could affect employment in the United States through the regulated sector – the auto manufacturing industry – and thro ugh several related sectors, specifically, industries that supply the auto manufacturing indus try (e.g., vehicle parts), auto dealers, the fuel refining and supply sectors, and the general r etail sector. According to the U.S. Bureau of Labor Statistics, in 2010, about 677,000 people in the U.S. were employed in Motor Vehicle and Parts Manufacturing Sector (NAICS 3361, 3362, and 3363). About 129,000 people in the U.S. were employed in the Automobile and Light Truck Manufacturing Sector (NAICS 33611) in December 2010; this is the directl y regulated sector, since it encompasses the auto manufacturers that are responsible for com plying with the proposed standards. 46 Changes in light duty vehicle sales, discussed in C hapter Error! Reference source not found. , could affect employment for auto dealers. The em ployment effects of this rule could also expand beyond the regulated sector. Though s ome of the parts used to achieve the proposed standards are likely to be built by auto m anufacturers themselves, the auto parts manufacturing sector also plays a significant role in providing those parts. As discussed in Chapter 5.3 of the RIA, this proposal is expected t o reduce the amount of fuel these vehicles use, and thus affect the petroleum refinery and sup ply industries. Finally, since the net reduction in cost associated with this proposal is expected to lead to lower household expenditures on fuel net of vehicle costs, consumer s then will have additional discretionary income that can be spent on other goods and service s.

When the economy is at full employment, an environm ental regulation is unlikely to have much impact on net overall U.S. employment; in stead, labor would primarily be shifted from one sector to another. These shifts in employm ent impose an opportunity cost on society, approximated by the wages of the employees , as regulation diverts workers from other activities in the economy. In this situatio n, any effects on net employment are likely to be transitory as workers change jobs (e.g., some wo rkers may need to be retrained or require time to search for new jobs, while shortages in som e sectors or regions could bid up wages to attract workers).

On the other hand, if a regulation comes into effec t during a period of high unemployment, a change in labor demand due to regul ation may affect net overall U.S. employment because the labor market is not in equil ibrium. Schmalansee and Stavins point out that net positive employment effects are possib le in the near term when the economy is at less than full employment due to the potential hiri ng of idle labor resources by the regulated sector to meet new requirements (e.g., to install n ew equipment) and new economic activity in sectors related to the regulated sector. 47 In the longer run, the net effect on employment i s more difficult to predict and will depend on the wa y in which the related industries respond to the regulatory requirements. As Schmalansee and Sta vins note, it is possible that the magnitude of the effect on employment could vary ov er time, region, and sector, and positive effects on employment in some regions or sectors co uld be offset by negative effects in other regions or sectors. For this reason, they urge cau tion in reporting partial employment effects since it can “paint an inaccurate picture of net em ployment impacts if not placed in the broader economic context.”Summary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-19 Given the time frame of this proposed rule, we adop t the default presumption that the unemployment rate will have declined to 5.3 percent by the time by the time this rule takes effect (using official government forecasts), so th at the effect of the regulation on labor will be to shift workers from one sector to another. 48 For example, to the extent that regulation increases the number of workers in the regulated se ctor (e.g., because of higher costs of producing vehicles with higher fuel economy), the o pportunity cost associated with those shifts in employment will be captured in labor cost s, as regulation diverts workers from other activities in the economy. In this situation, any effects on net employment are likely to be transitory as workers change jobs (e.g., some worke rs may need to be retrained or require time to search for new jobs, while shortages in som e sectors or regions could bid up wages to attract workers).

Nonetheless, it may be of interest to consider the qualitative impacts of the proposed rule on employment in various sectors. A number of different approaches have been used in published literature to conduct employment analysis . This section describes some of the common methods, as well as some of their limitation s.

1.2.2 Approaches to Quantitative Employment Analysis

Measuring the employment impacts of a policy depend on a number of inputs and assumptions. For instance, as discussed, assumptio ns about the overall state of unemployment in the economy play a major role in me asured job impacts. The inputs to the models commonly are the changes in quantities or ex penditures in the affected sectors; model results may vary in different studies depending on the assumptions about the levels of those inputs, and which sectors receive those changes. W hich sectors are included in the study can also affect the results. For instance, a study of this program that looks only at employment impacts in the refinery sector may find negative ef fects, because consumers will purchase less gasoline; a study that looks only at the auto parts sector, on the other hand, may find positive impacts, because the program will require redesigne d or additional parts for vehicles. In both instances, these would only be partial perspectives on the overall change in national employment due to Federal regulation.

1.2.2.1 Conceptual Framework for Employment Impacts in the Regulated Sector

One study by Morgenstern, Pizer, and Shih 49 provides a retrospective look at the impacts of regulation in employment in the regulate d sectors. The paper provides a theoretical framework that can be useful for examin ing the impacts of a regulatory change on the regulated sector in the medium to longer term. In particular, it identifies three separate ways that employment levels may change in the regul ated industry in response to a new (or more stringent) regulation.

• Demand effect : higher production costs due to the regulation wi ll lead to higher market prices; higher prices in turn reduce demand for the good, reducing the demand for labor to make that good. In the authors ’ words, the “extent of thisSummary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-20 effect depends on the cost increase passed on to co nsumers as well as the demand elasticity of industry output.”

• Cost effect : as costs go up, plants add more capital and labo r (holding other factors constant), with potentially positive effect s on employment. In the authors’ words, as “production costs rise, more inputs, incl uding labor, are used to produce the same amount of output.”

• Factor shift effect : post-regulation production technologies may be m ore or less labor-intensive (i.e., more/less labor is required per dollar of output). In the authors’ words, “environmental activities may be mo re labor intensive than conventional production,” meaning that “the amount of labor per dollar of output will rise,” though it is also possible that “cleane r operations could involve automation and less employment, for example.”

According to the authors, the “demand effect” is ex pected to have a negative effect on employment, L

the “cost effect” to have a positive effect on emp loyment, and the “factor shift effect” to have an ambiguous effect on employment. Without more information with respect to the magnitudes of these competing effects, it is not possible to predict the total effect environmental regulation will have on employment le vels in a regulated sector.

Morgenstern et al. estimated the effects on employm ent of spending on pollution abatement for four highly polluting/regulated U.S. industries (pulp and paper, plastics, steel, and petroleum refining) using data for six years be tween 1979 and 1991. The authors conclude that increased abatement expenditures gene rally have not caused a significant change in employment in those sectors. More specif ically, their results show that, on average across the industries studied, each additional $1 m illion spent on pollution abatement results in a (statistically insignificant) net increase of 1.5 jobs.

This approach to employment analysis has the advant age of carefully controlling for many possibly confounding effects in order to separ ate the effect of changes in regulatory costs on employment. It was, however, conducted fo r only four sectors. It could also be very difficult to update the study for other sectors, be cause one of the databases on which it relies, the Pollution Abatement Cost and Expenditure survey , has been conducted infrequently since 1994, with the last survey conducted in 2005. In a ddition, it does not examine the effects of regulation on employment in sectors related to but outside of the regulated sector.

In addition, the empirical estimates provided by Mo rgenstern et al. are not relevant to the case of fuel economy standards, which are very different from the pollution control

L As will be discussed below, the demand effect in t his proposal is potentially an exception to this ru le. While the vehicles become more expensive, they also produ ce reduced fuel expenditures; the reduced fuel cost s provide a countervailing impact on vehicle sales. As discu ssed in Preamble Section III.H.1, this possibility that vehicles may become more attractive to consumers after the p rogram poses a conundrum: why have interactions be tween vehicle buyers and producers not provided these ben efits without government intervention?Summary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-21 standards on industrial facilities that were consid ered in that study. Nevertheless, the theory that Morgenstern et al. developed continues to be u seful in this context.

The following discussion of additional methodologie s draws from Berck and Hoffmann’s review of employment models. 50

1.2.2.2 Computable General Equilibrium (CGE) Models

Computable general equilibrium (CGE) models are oft en used to assess the impacts of policy. These models include a stylized representa tion of supply and demand curves for all major markets in the economy. The labor market is commonly included. CGE models are very useful for looking at interaction effects of m arkets: “they allow for substitution among inputs in production and goods in consumption.” Thu s, if one market experiences a change, such as a new regulation, then the effects can be o bserved in all other markets. As a result, they can measure the employment changes in the econ omy due to a regulation. Because they usually assume equilibrium in all markets, though, they typically lack involuntary unemployment. If the total amount of labor changes , it is due to people voluntarily entering or leaving the workforce. As a result, these model s may not be appropriate for measuring effects of a policy on unemployment, because of the assumption that there is no involuntary unemployment. In addition, because of the assumpti ons of equilibrium in all markets and forward-looking consumers and firms, they are desig ned for examining the long-run effects of a policy but may offer little insight into its shor t-run effects.

1.2.2.3 Input-Output (IO) Models

Input-output models represent the economy through a matrix of coefficients that describe the connections between supplying and cons uming sectors. In that sense, like CGE models, they describe the interconnections of the e conomy. These interconnections look at how changes in one sector ripple through the rest o f the economy. For instance, a requirement for additional technology for vehicles requires additional steel, which requires more workers in both the auto and steel sectors; th e additional workers in those sectors then have more money to spend, which leads to more emplo yment in retail sectors. These are known as “multiplier” effects, because an initial i mpact in one sector gets multiplied through the economy. Unlike CGE models, input-output model s have fixed, linear relationships among the sectors (e.g., substitution among inputs or goods is not allowed), and quantity supplied need not equal quantity demanded. In part icular, these models do not allow for price changes – an increase in the demand for labor or ca pital does not result in a change in its price to help reallocate it to its best use. As a result , these models cannot capture opportunity costs from using resources in one area of the economy ove r another. The multipliers take an initial impact and can increase it substantially.

IO models are commonly used for regional analysis o f projects. In a regional analysis, the markets are commonly considered small enough th at wages and prices are determined outside the region, and any excess supply or demand is due to exports and imports (or, in the case of labor, emigration or immigration). For nat ional-level employment analysis, the use ofSummary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-22 input-output models requires the assumption that wo rkers flow into or out of the labor market perfectly freely. Wages do not adjust; instead, pe ople join into or depart from the labor pool as production requires them. For other markets as well, there is no substitution of less expensive inputs for more expensive ones. As a res ult, IO models provide an upper bound on employment impacts. As Berck and Hoffmann note, “F or the same reason, they can be thought of as simulating very short-run adjustment, ” in contrast to the CGE’s implicit assumption of long-run adjustment. Changes in prod uction processes, introductions of new technologies, or learning over time due to new regu latory requirements are also generally not captured by IO models, as they are calibrated to al ready established relationships between inputs and outputs.

1.2.2.4 Hybrid Models

As Berck and Hoffmann note, input-output models and CGE models “represent a continuum of closely related models.” Though not s eparately discussed by Berck and Hoffmann, some hybrid models combine some of the fe atures of CGE models (e.g., prices that can change) with input-output relationships. For instance, a hybrid model may include the ability to examine disequilibrium phenomena, su ch as labor being at less than full employment. Hybrid models depend on assumptions ab out how adjustments in the economy occur. CGE models characterize equilibria but say little about the pathway between them, while IO models assume that adjustments are largely constrained by previously defined relationships; the effectiveness of hybrid models d epends on their success in overcoming the limitations of each of these approaches. Hybrid mo dels could potentially be used to model labor market impacts of various vehicle policy opti ons although a number of judgments need to be made about the appropriate assumptions underl ying the model as well the empirical basis for the modeling results.

1.2.2.5 Single Sectors

It is possible to conduct a bottom-up analysis of t he partial effect of regulation on employment in a single sector by estimating the cha nge in output or expenditures in a sector and multiplying it by an estimate of the number of workers per unit of output or expenditures, under the assumption that labor demand is proportio nal to output or expenditures. As Berck and Hoffmann note, though, “Compliance with regulat ions may create additional jobs that are not accounted for.” While such an analysis can app roximate the effects in that one sector in a simple way, it also may miss important connections to related sectors.

1.2.2.6 Ex-Post Econometric Studies

A number of ex-post econometric analyses examine th e net effect of regulation on employment in regulated sectors. Morgenstern, Pizer , and Shih (2002), discussed above, and Berman and Bui (2001) are two notable examples that rely on highly disaggregated establishment-level time series data to estimate lo nger-run employment effects. 51 While often a sophisticated treatment of the issues analy zed, these studies commonly analyze specific scenarios or sectors in the past; care nee ds to be taken in extrapolating their results toSummary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-23 other scenarios and to the future. For instance, ne ither of these two studies examines the auto industry and are therefore of limited applicability in this context.

1.2.2.7 Summary

All methods of estimating employment impacts of a r egulation have advantages and limitations. CGE models may be most appropriate fo r long-term impacts, but the usual assumption of equilibrium in the employment market means that it is not useful for looking at changes in overall employment: overall levels are likely to be premised on full employment. IO models, on the other hand, may be most appropria te for small-scale, short-term effects, because they assume fixed relationships across sect ors and do not require market equilibria. Hybrid models, which combine some features of CGEs with IO models, depend upon key assumptions and economic relationships that are bui lt into them. Single-sector models are simple and straightforward, but they are often base d on the assumptions that labor demand is proportional to output, and that other sectors are not affected. Finally, econometric models have been developed to evaluate the longer-run net effects of regulation on sector employment, though these are ex-post analyses commo nly of specific sectors or situations, and the results may not have direct bearing for the regulation being reviewed.

1.2.3 Employment analysis of this proposal

As mentioned above, this program is expected to aff ect employment in the regulated sector (auto manufacturing) and other sectors direc tly affected by the proposal: auto parts suppliers, auto dealers, the fuel supply market (wh ich will face reduced petroleum production due to reduced fuel demand but which may see additi onal demand for electricity or other fuels), and consumers (who will face higher vehicle costs and lower fuel expenditures). In addition, as the discussion above suggests, each of these sectors could potentially have ripple effects in the rest of the economy. These ripple e ffects depend much more heavily on the state of the macroeconomy than do the direct effect s. At the national level, employment may increase in one industry or region and decrease in another, with the net effect being smaller than either individual-sector effect. EPA does not attempt to quantify the net effects of the regulation on overall national employment.

The discussion that follows provides a partial, bot tom-up quantitative estimate of the effects of this proposal on the regulated sector (t he auto industry; for reasons discussed below, we include some quantitative assessment of effects on suppliers to the industry although they are not regulated directly). It also includes quali tative discussion of the effects of the proposal on other sectors. Focusing quantification of emplo yment impacts on the regulated sector has some advantages over quantifying all impacts. Firs t, the analysis relies on data generated as part of the rulemaking process, which focuses on th e regulated sector; as a result, what is presented here is based on internally consistent as sumptions and estimates made in this proposal. Secondly, as discussed above, net effect s on employment in the economy as a whole depend heavily on the overall state of the ec onomy when this rule has its effects. Focusing on the regulated sector provides insight i nto employment effects in that sectorSummary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-24 without having to make assumptions about the state of the economy when this rule has its impacts. We include a qualitative discussion of em ployment effects on other sectors to provide a broader perspective on the impacts of thi s rule.

As noted above, in a full-employment economy, any c hanges in employment will result from people changing jobs or voluntarily ent ering or exiting the workforce. In a fullemployment economy, employment impacts of this prop osal will change employment in specific sectors, but it will have small, if any, e ffect on aggregate employment. This rule would take effect in 2017 through 2025; by then, th e current high unemployment may be moderated or ended. For that reason, this analysis does not include multiplier effects, but instead focuses on employment impacts in the most d irectly affected industries. Those sectors are likely to face the most concentrated employment impacts. The agencies seek comment on other sectors that are likely to be significantly a ffected and thus warrant further analysis in the final rulemaking analysis.

1.2.3.1 Employment Impacts in the Auto Industry

Following the Morgenstern et al. conceptual framewo rk for the impacts of regulation on employment in the regulated sector, we consider three effects for the auto sector: the demand effect, the cost effect, and the factor shif t effect. However, we are only able to offer quantitative estimates for the demand and cost effe cts. We note that these estimates, based on extrapolations from current data, become more uncer tain as time goes on.

1.2.3.1.1 The Demand Effect

The demand effect depends on the effects of this pr oposal on vehicle sales. If vehicle sales increase, then more people will be required t o assemble vehicles and their components. If vehicle sales decrease, employment associated wi th these activities will unambiguously decrease. Unlike in Morgenstern et al.’s study, wh ere the demand effect decreased employment, there are countervailing effects in the vehicle market due to the fuel savings resulting from this program. On one hand, this pro posal will increase vehicle costs; by itself, this effect would reduce vehicle sales. On the oth er hand, this proposal will reduce the fuel costs of operating the vehicle; by itself, this eff ect would increase vehicle sales, especially if potential buyers have an expectation of higher fuel prices. As noted earlier in this chapter, the assumption that consumer willingness-to-pay tend to undervalue improved fuel economy, along with standard assumptions about producer beha vior, would suggest that vehicle sales will decrease, but the magnitude of any such effect is highly uncertain. For that reason, we are also not seeking to quantify the demand effect.

1.2.3.1.2 The Cost Effect

The demand effect, discussed above, measures employ ment changes due to new vehicle sales only. The cost effect measures emplo yment impacts due to the new or additional technologies needed for vehicles to comp ly with the proposed standards.Summary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-25 One way to estimate the cost effect, given the cost estimates for complying with the rule, is to use the ratio of workers to each $1 mil lion of expenditures in that sector. The use of these ratios has both advantages and limitations. It is often possible to estimate these ratios for quite specific sectors of the economy: for ins tance, it is possible to estimate the average number of workers in the light-duty vehicle manufac turing sector per $1 million spent in the sector, rather than use the ratio from another, mor e aggregated sector, such as motor vehicle manufacturing. As a result, it is not necessary to extrapolate employment ratios from possibly unrelated sectors. On the other hand, these estima tes are averages for the sectors, covering all the activities in those sectors; they may not be re presentative of the labor required when expenditures are required on specific activities, a s the factor shift effect (discussed below) indicates. For instance, the ratio for the motor v ehicle manufacturing sector represents the ratio for all vehicle manufacturing, not just for f uel efficiency improvements. In addition, these estimates do not include changes in sectors t hat supply these sectors, such as steel or electronics producers. They thus may best be viewe d as the effects on employment in the auto sector due to the changes in expenditures in t hat sector, rather than as an assessment of all employment changes due to these changes in expe nditures.

Some of the costs of this proposal will be spent di rectly in the auto manufacturing sector, but some of the costs will be spent in the auto parts manufacturing sector. Because we do not have information on the proportion of expend itures in each sector, we separately present the ratios for both the auto manufacturing sector and the auto parts manufacturing sector. These are not additive, but should instead be considered as a range of estimates for the cost effect, depending on which sector adds technol ogies to the vehicles to comply with the regulation.

We use several public sources for estimates of empl oyment per $1 million expenditures. The U.S. Bureau of Labor Statistics (BLS) provides its Employment Requirements Matrix (ERM), 52 which provides direct estimates of the employment per $1 million in sales of goods in 202 sectors. The most recent estimates, used here, are from 2008 (adjusted to 2009$). The tables used here are adju sted to remove the employment effects of imports through use of the ratio of domestic produc tion to domestic sales, described above, of 0.667. The values reported are for Motor Vehicle M anufacturing (NAICS 3361) and Motor Vehicle Parts Manufacturing (NAICS 3363).

The Annual Survey of Manufactures 53 (ASM) provides another source of estimates based on a sample of 50,000 establishments out of a universe of 346,000 manufacturing establishments. It includes more sectoral detail t han the BLS ERM: for instance, while the ERM includes the Motor Vehicle Manufacturing sector , the ASM has detail at the 6-digit NAICS code level (e.g., automobile manufacturing vs . light truck and utility vehicle manufacturing). While the ERM provides direct esti mates of employees/$1 million in expenditures, the ASM separately provides number of employees and value shipments; the direct employment estimates here are the ratio of t hose values. The data in the ASM are updated annually, except for years when the full Ec onomic Census occurs. The tables presented here use data from 2009. As with the ERM , we adjust for the ratio of domesticSummary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-26 production to domestic sales. The values reported are for Motor Vehicle Manufacturing (NAICS 3361), Automobile and Light Duty Motor Vehic le Manufacturing (NAICS 33611), and Motor Vehicle Parts Manufacturing (NAICS 3363).

The Economic Census includes all large companies an d a sample of smaller ones. The ASM is a subset of the Economic Census; though the Census itself is more complete, it is conducted only every 5 years, while the ASM is annu al. The values presented here use data from 2007 (adjusted to 2009$), with the domestic pr oduction-to-sales adjustment. The values reported are for Motor Vehicle Manufacturing (NAICS 3361), Automobile and Light Duty Motor Vehicle Manufacturing (NAICS 33611), and Moto r Vehicle Parts Manufacturing (NAICS 3363).

Table 1.2-1 provides the values, either given (BLS) or calculate d (ASM, Economic Census) for employment per $1 million of expenditures, all based on 2009 dollars, though the underlying data come from different years (which may account for some of the differences). The different data sources provide sim ilar magnitudes for the estimates for the sectors. Parts manufacturing appears to be more labor-intensive than vehicle manufacturing; light-duty vehicle manufacturing appear s to be slightly less labor-intensive than motor vehicle manufacturing as a whole.

Table 1.2-1 Employment per $1 Million Expenditures (2009$) in the Motor Vehicle Manufacturing Sector*

Source Sector Ratio of workers per $1 million expenditures Ratio of workers per $1

million expenditures, adjusted for domestic vs. foreign production BLS ERM Motor Vehicle Mfg 0.834 0.556

ASM Motor Vehicle Mfg 0.824 0.549

ASM Light Duty Vehicle Mfg 0.757 0.505

Economic Census Motor Vehicle Mfg 0.674 0.449

Economic Census Light Duty Vehicle Mfg 0.610 0.407

BLS ERM Motor Vehicle Parts Mfg 3.073 2.049

ASM Motor Vehicle Parts Mfg 3.093 2.063Summary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-27 Economic Census Motor Vehicle Parts Mfg 2.749 1.833

BLS ERM refers to the U.S. Bureau of Labor Statisti cs’ Employment Requirement Matrix. ASM refers to t he U.S. Census Bureau’s Annual Survey of Manufactures. Economic Census refers to the U.S. Census Bureau’ s Economic Census.

Over time, the amount of labor needed in the auto indust ry has changed: automation and improved methods have led to significant productivity increases. The BLS ERM, for instance, provided estimates that, in 1993, 1.52 workers were needed per $1 million of 2000$, but only 0.83 workers by 2008 (in 20 00$). 54 Because the ERM is available annually for 1993-2008, we used these data to estim ate productivity improvements over time. We regressed logged ERM values on year (to es timate percent change per year) for both the Motor Vehicle Manufacturing and Motor Vehicle Parts Manufacturing sectors. The results suggest a 4.4 percent per year productiv ity improvement in the Motor Vehicle Manufacturing Sector, and a 3.6 percent per year imp rovement in the Motor Vehicle Parts Manufacturing Sector. We then used the regression re lationship to project the ERM through 2025. In the results presented below, these p rojected values (adjusted to 2009$) were used directly for the BLS ERM estimates. For the ASM, we used the ratio of the projected value in the future to the projected value in 2 009 (the base year for the ASM); for the Economic Census estimates, we used the ratio of the projected value in the future to the projected value in 2007 (the base year for that estim ate). As noted above, we adjusted the estimate of workers per vehicle for the demand effec t in Chapter 1.2.3.1.1, above, using the productivity improvement for the Motor Vehicle Manufa cturing sector; because the estimate of workers per vehicle for the demand effec t was based on data from 2001 to 2010, we used the projected value of the ERM in 2005 as the denominator of the ratio.

Table 1.2-2 shows the cost estimates developed for this rule, discussed in Chapter 5. The maximum value in Table 1.2-2 for employment impacts per $1 million expenditures (after accounting for the share of domestic production ) is 2.049 in 2009 if all the additional costs are in the parts sector; the minimum v alue is 0.407 in 2009, if all the additional costs are in the light-duty vehicle manufact uring sector: that is, the range of employment impacts is between 0.4 and 2 additional jobs per $1 million expenditures in
the sector in 2009. The results in Table 1.2-2 include the productivity adjustment described
above.

Table 1.2-2 Employment per $1 Million in the Motor Vehicle Manufact uring Sector

Year Costs (before

adjustment for domestic proportion of production) ($Millions) Minimum

employment effect (if all expenditures are in the parts sector) Maximum

employment effect (if all expenditures are in the light duty vehicle mfg sector)Summary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-28 2017 $ 1,997 500 3,100
2018 $ 4,179 1,000 6,200
2019 $ 6,255 1,500 9,000
2020 $ 8,369 1,900 11,600
2021 $ 11,875 2,600 15,900
2022 $ 17,374 3,700 22,500
2023 $ 22,690 4,600 28,300
2024 $ 28,151 5,400 33,900
2025 $ 33,566 6,200 39,000

1.2.3.1.3 The Factor Shift Effect

The factor shift effect looks at the effects on empl oyment due to changes in labor intensity associated with a regulation. As noted abov e, the estimates of the cost effect assume constant labor per $1 million in expenditures, t hough the new technologies may be either more or less labor-intensive than the existing ones. An estimate of the factor shift effect would either increase or decrease the estimat e used for the cost effect.

We are not quantifying the factor shift effect here, for lack of data on the labor intensity of all the possible technologies that manuf acturers could use to comply with the proposed standards. For a subset of the technologie s, though, EPA-sponsored research (discussed in Chapter 3.2.1.1 of the Joint TSD) whic h compared new technologies to existing ones at the level of individual components pr ovides some insights into the factor shift effect.

The comparison involved tearing down the selected tech nologies to their individual components and looking at the differences in materials and labor needs in moving from the conventional to the new technologies. 55 For instance, the analysis compared all the parts and labor associated with an 8-speed automatic trans mission to those needed for a 6-speed
automatic transmission.

Because labor cost was one of the sources of differ ences between the technologies, it is possible, for those technologies, to see whether labor needs increase or decrease with the switch to technologies that might contribute to compl iance with the proposed standards. An increase in labor cost for the new technology indicate s an increase in the labor needed for the new technology compared to the baseline techn ology. For instance, an 8-speed transmission requires $15.11 more in labor costs tha n a 6-speed transmission. Dividing the labor cost by a wage per hour estimate provides an es timate of the additional hours (and thus the additional labor) needed for the new techn ology compared to the baseline technology. As with labor cost, an increase in labor hours per technology indicates greater employment needs for the new technologies. For this c onversion, a weighted average wage rate (90 percent of the average wage in the Motor Veh icle Parts Manufacturing sector, and 10 percent of the average wage in the Motor Vehicle Manufacturing Sector) of $46.36/hourSummary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-29 in 2015, using 2008 dollars (the unit of analysis for t he FEV study). For the change from a 6-speed to an 8-speed transmission, we thus estimate an additional 0.33 hours of labor per
transmission.

Table 1.2-3 shows the changes in labor hours in moving from basel ine to new fuelsaving technologies for technologies in the FEV study. It indicates that, in switching from the baseline to the new technologies, labor use per technology increased: the fuel-saving technologies use more labor than the baseline technol ogies. For a subset of the technologies likely to be used to meet the standards in this proposal, then, the factor shift effect increases labor demand, at least in the short run; in the long run, as with all technologies, the cost structure is likely to change due to learning, economies of scale, etc. The technologies examined in this research are, how ever, only a subset of the technologies that auto makers may use to comply with the standar ds proposed in this program. As a result, these results cannot be considered definitive evide nce that the factor shift effect increases employment for this rule. We therefore do not quan tify the factor shift effect for this proposal.

Table 1.2-3 Estimated Change in Labor for Selected Compliance Technologies

Technology FEV

Case Study Vehicle Class Labor Costs Total

Costs Hours/

Technology

Downsized Turbo GDI 4 0101 Compact C $72.58 $537.70 1.57

Downsized Turbo GDI V6 0102 Mid/Large C $25.76 $87.38 0.56

Downsized Turbo GDI V6 0104 SUV/Trucks $84.19 $789.53 1.82

Electric A/C

compressor 0602 $4.68 $167.54 0.10

Power split hybrid 0502 Mid/Large C $395.85 $3,435.01 8.54

6- to 8-speed transmission 0803 Mid/Large C $15.11 $61.84 0.33

1.2.4 Effects on Employment for Auto Dealers

The effects of the proposed standards on employment for auto dealers depend principally on the effects of the standards on ligh t duty vehicle sales.

In addition, auto dealers may be affected by change s in maintenance and service costs. Increases in those costs are likely to increase lab or demand in dealerships.Summary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-30 Although this proposal predicts very small penetrat ion of advanced technology vehicles, the uncertainty on consumer acceptance of such technology vehicles is even greater. As discussed in Chapter 1.1.2.6, consumers may find some characteristics of electric vehicles and plug-in hybrid electric vehicles, such as the a bility to fuel with electricity rather than gasoline, attractive; they may find other character istics, such as the limited range for electric vehicles, undesirable. Auto dealers may play a maj or role in explaining the merits and disadvantages of these new technologies to vehicle buyers. There may be a temporary need for increased employment to train sales staff in th e new technologies as the new technologies become available.

1.2.5 Effects on Employment in the Auto Parts Sector

As discussed in the context of employment in the au to industry, some vehicle parts are made in-house by auto manufacturers; others are mad e by independent suppliers who are not directly regulated, but who will be affected by the proposed standards as well. The additional expenditures on technologies are expected to have a positive effect on employment in the parts sector as well as the manufacturing sector; t he breakdown in employment between the two sectors is difficult to predict. The effects o n the parts sector also depend on the effects of the proposed standards on vehicle sales and on the labor intensity of the new technologies, qualitatively in the same ways as for the auto manu facturing sector.

1.2.6 Effects on Employment for Fuel Suppliers

In addition to the effects on the auto manufacturin g and parts sectors, these rules will result in changes in fuel use that lower GHG emissi ons. Fuel saving, principally reductions in liquid fuels such as gasoline and diesel, will affe ct employment in the fuel suppliers industry sectors throughout the supply chain, from refinerie s to gasoline stations. To the extent that the proposed standards result in increased use of e lectricity or other new fuels, employment effects will result from providing these fuels and developing the infrastructure to supply them

to consumers.

Expected petroleum fuel consumption reductions can be found in Chapter 5.3. While this reduced consumption represents fuel savings fo r purchasers of fuel, it represents a loss in value of output for the petroleum refinery industry , fuel distributors, and gasoline stations. The loss of expenditures to petroleum fuel supplier s throughout the petroleum fuel supply chain, from the petroleum refiners to the gasoline stations, is likely to result in reduced employment in these sectors.

This rule is also expected to lead to increases in electricity consumption by vehicles, as discussed in Chapter 5.3. This new fuel may req uire additional infrastructure, such as electricity charging locations. Providing this inf rastructure will require some increased employment. In addition, the generation of electri city is likely also to require some additional labor. We have insufficient information at this ti me to predict whether the increases in labor associated with increased infrastructure provision and generation for electricity will be greater or less than the employment reductions associated w ith reduced demand for petroleum fuels.Summary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-31 1.2.7 Effects on Employment due to Impacts on Consumer Ex penditures

As a result of these proposed standards, consumers will pay a higher up-front cost for the vehicles, but they will recover those costs in a fairly short payback period (see Preamble Section III.H.10.b); indeed, people who finance the ir vehicles are expected to find that their fuel savings per month exceed the increase in the l oan cost. As a result, consumers will have additional money to spend on other goods and servic es, though, for those who do not finance their vehicles, it will occur after the initial pay back period. These increased expenditures will support employment in those sectors where consumers spend their savings.

These increased expenditures will occur in 2017 and beyond. If the economy returns to full employment by that time, any change in cons umer expenditures (as discussed in the economy-wide impact analysis in section 8.3) would primarily represent a shift in employment among sectors. If, on the other hand, t he economy still has substantial unemployment, these expenditures would contribute t o employment through increased consumer demand.

1.2.8 Summary

The primary employment effects of this proposal are expected to be found throughout several key sectors: auto manufacturers, auto deale rs, auto parts manufacturing, fuel production and supply, and consumers. We emphasize that the discussion here is a partial view of these effects. Whether the economy is in fu ll employment will determine whether the discussed changes in employment in these sectors is offset in other sectors of the economy. The extent to which employment in the sectors discu ssed above responds to this program will be influenced by how consumers consider fuel saving s in their vehicle purchase decisions, changes in vehicle manufacturing technologies and l ocations, and other factors.

This rule initially takes effect in model year 2017 , a time period sufficiently far in the future that the current sustained high unemployment at the national level may be moderated or ended. In an economy with full employment, the pri mary employment effect of a rulemaking is likely to be to move employment from one sector to another, rather than to increase or decrease employment. For that reason, we focus our limited quantitative analysis on employment in the regulated sector, to examine the impacts on that sector directly. We discuss the likely direction of impacts in directly related sectors, but we do not quantify those impacts, because employment impacts outside the reg ulated sector are more difficult to quantify with reasonable accuracy, particularly so far into the future.

For the regulated sector, the cost effect is expect ed to increase employment by 500 – 2,900 workers in 2017, depending on the share of th at employment that is in the auto manufacturing sector compared to the auto parts man ufacturing sector. Though we do not have estimates of the factor shift effect for all p otential compliance technologies, the evidence which we do have for some technologies suggests tha t many of the technologies will have increased labor needs.Summary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

2-32 Increased vehicle sales are expected to lead to inc reased labor needs in auto dealerships. Increased vehicle sales and increased expenditures for auto parts are expected to require increased labor to build parts, though this effect also depends on any changes in the labor intensity of production; as noted, the subset of potential compliance technologies for which data are available show increased labor requi rements. Reduced fuel production implies less employment in the fuel provision sectors. Fin ally, net cost savings to consumers are expected to increase employment through their incre ased expenditures in general retail

sectors.

ReferencesSummary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

33 

## 2 Small Business Flexibility Analysis

1 Kleit A.N., 1990, “The Effect of Annual Changes in Automobile Fuel Economy Standards,” Journal of Regulatory Economics 2: 151-172 (Docket EPA-HQ-OAR-2009-0472-0015); McCarthy, Patrick S., 1996. “Market Price and Incom e Elasticities of New Vehicle Demands.” Review of Economics and Statistics 78: 543-547 (Doc ket EPA-HQ-OAR-2009-0472-0016); Goldberg, Pinelopi K., 1998. “The Effects of the Co rporate Average Fuel Efficiency Standards in the US,” Journal of Industrial Economics 46(1): 1-33 (Docket EPA-HQ-OAR-2009-0472- 0017); Greene, David L., “Feebates, Footprints and Highway Safety,” Transportation Research
Part D 14 (2009): 375-384 (Docket EPA-HQ-OAR-2009-0472-0 019).

2 Goldberg, Pinelopi Koujianou, “Product Differentia tion and Oligopoly in International Markets: The Case of the U.S. Automobile Industry, ” Econometrica 63(4) (July 1995): 891-951 (Docket EPA-HQ-OAR-2009-0472-0021); Goldberg, Pinel opi Koujianou, “The Effects of the Corporate Average Fuel Efficiency Standards in the US,” Journal of Industrial Economics 46(1) (March 1998): 1-33 (Docket EPA-HQ-OAR-2009-0472-00 17).

3 Greene, David L., K.G. Duleep, Doug Elliott, and S anjana Ahmad, “A Fuel Economy Regulatory Analysis Model (FERAM) For the Energy In formation Administration,” prepared by the Oak Ridge National Laboratory for the U.S. Depa rtment of Energy under contract No. DEAC0500OR22725, 2005 (Docket EPA-HQ-OAR-2009-0472-00 22); Greene, David L., Philip D. Patterson, Margaret Singh, and Jia Li, “Feebates, R ebates, and Gas-Guzzler Taxes: A Study of Incentives for Increased Fuel Economy,” Energy Poli cy33 (2005): 757-775 (Docket EPA-HQOAR-2009-0472-0023).

4 McManus, Walter M., “Can Proactive Fuel Economy St rategies Help Automakers Mitigate Fuel-Price Risks?” University of Michigan Transpor tation Research Institute, September 14, 2006 (Docket EPA-HQ-OAR-2009-0472-0024).

5 Berry, Steven, James Levinsohn, and Ariel Pakes, “ Automobile Prices in Market Equilibrium,” Econometrica 63(4) (July 1995): 841-940 (Docket EPA-HQ-OAR-200 9-0472-0025); Berry, Steven, James Levinsohn, and Ariel Pakes, “Differen tiated Products Demand Systems from a Combination of Micro and Macro Data: The New Car M arket,” Journal of Political Economy 112(1) (2004): 68-105 (Docket EPA-HQ-OAR-2009-0472 -0026).

6 Bento, Antonio M., Lawrence H. Goulder, Emeric Hen ry, Mark R. Jacobsen, and Roger H. von Haefen, “Distributional and Efficiency Impacts of G asoline Taxes: An Econometrically Based Multi-Market Study,” American Economic Review 95(2) (May 2005): 282-287 (Docket EPAHQ-OAR-2009-0472-0029).Summary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

34 7 Train, Kenneth E., and Clifford Winston, “Vehicle Choice Behavior and the Declining Market Share of U.S. Automakers,” International Economic R eview 48(4) (November 2007): 1469- 1496 (Docket EPA-HQ-OAR-2009-0472-0030).

8 Kleit, Andrew N., “Impacts of Long-Range Increases in the Fuel Economy (CAFE) Standard,” Economic Inquiry

42(2) (April 2004): 279-294 (Docket EPA-HQ-OAR-20 09-0472-0031).

9 Austin, David, and Terry Dinan, “Clearing the Air: The Costs and Consequences of Higher CAFE Standards and Increased Gasoline Taxes,” Journ al of Environmental Economics and Management 50 (2005): 562-582 (Docket EPA-HQ-OAR-2009-0472-0 032).

10 E.g., Bento, Antonio M., Lawrence H. Goulder, Emer ic Henry, Mark R. Jacobsen, and Roger H. von Haefen, “Distributional and Efficiency Impac ts of Gasoline Taxes: An Econometrically Based Multi-Market Study,” American Economic Review 95(2) (May 2005): 282-287 (Docket EPA-HQ-OAR-2009-0472-0029); Train, Kenneth E., and Clifford Winston, “Vehicle Choice Behavior and the Declining Market Share of U.S. Aut omakers,” International Economic Review 48(4) (November 2007): 1469-1496 (Docket EPA-HQ-OA R-2009-0472-0030).

11 E.g., Berry, Steven, James Levinsohn, and Ariel Pa kes, “Automobile Prices in Market Equilibrium,” Econometrica 63(4) (July 1995): 841-940 (Docket EPA-HQ-OAR-200 9-0472- 0025).

12 Greene, David L., K.G. Duleep, Doug Elliott, and S anjana Ahmad, “A Fuel Economy Regulatory Analysis Model (FERAM) For the Energy In formation Administration,” prepared by the Oak Ridge National Laboratory for the U.S. Depa rtment of Energy under contract No. DEAC0500OR22725, 2005 (Docket EPA-HQ-OAR-2009-0472-00 22).

13 NERA Economic Consulting, “Evaluation of NHTSA’s B enefit-Cost Analysis of 2011-2015 CAFE Standards,” 2008, available at http://www.heartland.org/policybot/results/23495/Ev aluation_of_NHTSAs_BenefitCost_Analysi s_Of_20112015_CAFE_Standards.html (Docket EPA-HQ-OA R-2009-0472-0033).

14 E.g., Train, Kenneth E., and Clifford Winston, “Ve hicle Choice Behavior and the Declining Market Share of U.S. Automakers,” International Eco nomic Review 48(4) (November 2007): 1469-1496 (Docket EPA-HQ-OAR-2009-0472-0030).

15 E.g., Berry, Steven, James Levinsohn, and Ariel Pa kes, “Automobile Prices in Market Equilibrium,” Econometrica 63(4) (July 1995): 841-940 (Docket EPA-HQ-OAR-200 9-0472- 0025).

16 E.g., Bento, Antonio M., Lawrence H. Goulder, Emer ic Henry, Mark R. Jacobsen, and Roger H. von Haefen, “Distributional and Efficiency Impac ts of Gasoline Taxes: An Econometrically Based Multi-Market Study,” American Economic Review 95(2) (May 2005): 282-287 (Docket EPA-HQ-OAR-2009-0472-0029).Summary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

35 17 Bento, Antonio M., Lawrence H. Goulder, Emeric Hen ry, Mark R. Jacobsen, and Roger H. von Haefen, “Distributional and Efficiency Impacts of Gasoline Taxes: An Econometrically Based Multi-Market Study,” American Economic Review 95(2) (May 2005): 282-287 (Docket EPA-HQ-OAR-2009-0472-0029); Feng, Yi, Don Fullerton , and Li Gan, “Vehicle Choices, Miles Driven and Pollution Policies,” National Bureau of Economic Analysis Working Paper 11553, available at http://econweb.tamu.edu/gan/w11553.pdf, accessed 5/12/09 (Docket EPA-HQOAR-2009-0472-0034).

18 NERA Economic Consulting, “Appendix B: New Vehicl e Market Model,” “Impacts of the California Greenhouse Gas Emission Standards on Mot or Vehicle Sales,” comments submitted to the U.S. Environmental Protection Agency at Regu lations.gov, document number EPA-HQOAR-2006-0173-9053.1 (Docket EPA-HQ-OAR-2009-0472-0 035).

19 E.g., Train, Kenneth E., and Clifford Winston, “Ve hicle Choice Behavior and the Declining Market Share of U.S. Automakers,” International Eco nomic Review 48(4) (November 2007): 1469-1496 (Docket EPA-HQ-OAR-2009-0472-0030).

20 E.g., Berry, Steven, James Levinsohn, and Ariel Pa kes, “Automobile Prices in Market Equilibrium,” Econometrica 63(4) (July 1995): 841-940 (Docket EPA-HQ-OAR-200 9-0472- 0025).

21 Greene, David L., Philip D. Patterson, Margaret Si ngh, and Jia Li, “Feebates, Rebates, and Gas-Guzzler Taxes: A Study of Incentives for Incre ased Fuel Economy,” Energy Policy 33 (2005): 757-775 (Docket EPA-HQ-OAR-2009-0472-0023)

.

22 Rex, Emma, and Henrikke Baumann (2007). “Beyond e colabels: what green marketing can learn from conventional marketing.” Journal of Cle aner Production 15: 567-576.

23 Whitefoot, Kate, Meredith Fowlie, and Steven Skerl os, “Product Design Responses to Industrial Policy: Evaluating Fuel Economy Standar ds Using an Engineering Model of Endogenous Product Design,” Energy Institute at Haa s Working Paper 214, University of California Energy Institute, February 2011.

24 Berry, Steven, James Levinsohn, and Ariel Pakes, “ Automobile Prices in Market Equilibrium,” Econometrica 63(4) (July 1995): 841-940 (Docket EPA-HQ-OAR-200 9-0472- 0025).

25 Goldberg, Pinelopi Koujianou, “Product Differentia tion and Oligopoly in International Markets: The Case of the U.S. Automobile Industry, ” Econometrica 63(4) (July 1995): 891-951 (Docket EPA-HQ-OAR-2009-0472-0021).

26 Brownstone, David, and Kenneth Train, “Forecasting New Product Penetration with Flexible Substitution Patterns,” Journal of Econometrics 89 (1999): 109-129 (Docket EPA-HQ-OAR2009-0472-0036); Brownstone, David, David S. Bunch, and Kenneth Train, “Joint Mixed LogitSummary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

36 Models of Stated and Revealed Preferences for Alter native-Fuel Vehicles,” Transportation Research Part B 34 (2000): 315-338 (Docket EPA-HQ-OAR-2009-0472-0 0357); Greene David L., “TAFV Alternative Fuels and Vehicles Choice Mod el Documentation,” prepared by the Oak Ridge National Laboratory for the U.S. Department o f Energy, July 2001 (Docket EPA-HQOAR-2009-0472-0038); Greene, David L., K. G. Duleep , and Walter McManus, “Future Potential of Hybrid and Diesel Powertrains in the U .S. Light-Duty Vehicle Market,” prepared by the Oak Ridge National Laboratory for the U.S. Depa rtment of Energy, August 2004 (Docket EPA-HQ-OAR-2009-0472-0039).

27 Petrin, Amil, “Quantifying the Benefits of New Pro ducts: The Case of the Minivan,” Journal of Political Economy 110 (2002): 705-729 (Docket EPA-HQ-OAR-2009-0472- 0040); Berry, Steven, James Levinsohn, and Ariel Pakes, “Differen tiated Products Demand Systems from a Combination of Micro and Macro Data: The New Car M arket,” Journal of Political Economy 112 (2004): 68-105 (Docket EPA-HQ-OAR-2009-0472-00 26).

28 Train, Kenneth E., and Clifford Winston, “Vehicle Choice Behavior and the Declining Market Share of U.S. Automakers,” International Economic R eview 48 (November 2007): 1469-1496 (Docket EPA-HQ-OAR-2009-0472-0030).

29 Bento, Antonio M., Lawrence H. Goulder, Emeric Hen ry, Mark R. Jacobsen, and Roger H. von Haefen, “Distributional and Efficiency Impacts of Gasoline Taxes: An Econometrically Based Multi-Market Study,” American Economic Review 95(2) (May 2005): 282-287 (Docket EPA-HQ-OAR-2009-0472-0029); Feng, Yi, Don Fullerton , and Li Gan, “Vehicle Choices, Miles Driven and Pollution Policies,” National Bureau of Economic Analysis Working Paper 11553, available at http://econweb.tamu.edu/gan/w11553.pdf, accessed 5/12/09 (Docket EPA-HQOAR-2009-0472-0034).

30 Greene, David L., Philip D. Patterson, Margaret Si ngh, and Jia Li, “Feebates, Rebates, and Gas-Guzzler Taxes: A Study of Incentives for Incre ased Fuel Economy,” Energy Policy 33 (2005): 757-775 (Docket EPA-HQ-OAR-2009-0472-0023) ; Feng, Yi, Don Fullerton, and Li Gan, “Vehicle Choices, Miles Driven and Pollution P olicies,” National Bureau of Economic Analysis Working Paper 11553, available at http://e conweb.tamu.edu/gan/w11553.pdf , accessed 5/12/09 (Docket EPA-HQ-OAR-2009-0472-0034); Greene, David L., “Feebates, Footprints and Highway Safety,” Transportation Research Part D (2009) (in press) (Docket EPA-HQ-OAR2009-0472-0019).

31 E.g., Austin, David, and Terry Dinan, “Clearing th e Air: The Costs and Consequences of Higher CAFE Standards and Increased Gasoline Taxes, ” Journal of Environmental Economics and Management

50 (2005): 562-582 (Docket EPA-HQ-OAR-2009-0472-0 032).

32 Turrentine, Thomas S., and Kenneth S. Kurani, “Car Buyers and Fuel Economy?” Energy Policy 35 (2007): 1213-1223 (Docket EPA-HQ-OAR-2009-0472 -0041).Summary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

37 33 E.g., Espey, Molly, and Santosh Nair, 2005. “Autom obile Fuel Economy: What Is It Worth?” Contemporary Economic Policy 23: 317-323 (Docket EP A-HQ-OAR-2009-0472-0042).

34 Larrick, Richard P., and Jack B. Soll, 2008. “The MPG Illusion,” Science 320(5883): 1593- 1594 (Docket EPA-HQ-OAR-2009-0472-0043).

35 E.g., Goldberg, Pinelopi Koujianou, “Product Diffe rentiation and Oligopoly in International Markets: The Case of the U.S. Automobile Industry, ” Econometrica 63(4) (July 1995): 891-951 (Docket EPA-HQ-OAR-2009-0472-0021).

36 E.g., Berry, Steven, James Levinsohn, and Ariel Pa kes, “Automobile Prices in Market Equilibrium,” Econometrica 63(4) (July 1995): 841-940 (Docket EPA-HQ-OAR-200 9-0472- 0025).

37 Busse, Meghan, Christopher R. Knittel, and Florian Zettelmeyer, 2009. “Pain at the Pump: How Gasoline Prices Affect Automobile Purchasing in New and Used Markets,” working paper, http://www.econ.ucdavis.edu/faculty/knittel/papers/ gaspaper_latest.pdf (accessed 6/16/09) (Docket EPA-HQ-OAR-2009-0472-0044); Li, Shanjun, Ch ristopher Timmins, and Roger H. von Haefen, 2009. “How Do Gasoline Prices Affect Fleet Fuel Economy?” American Economic Journal: Economic Policy 1(2): 113-137; Congressional Budget Office (2008) . Effects of Gasoline Prices on Driving Behavior and Vehicle Mar kets . The Congress of the United States, Pub. No. 2883; West. Sarah (2007). “The Effect of Gasoline Prices on the Demand for Sport Utility Vehicles.” Working Paper. Macalester Coll ege, http://www.macalester.edu/~wests/SarahWestMEA2007.p df, accessed 1/25/10.

38 Greene, David L., and Jin-Tan Liu, 1988. “Automot ive Fuel Economy Improvements and Consumers’ Surplus,” Transportation Research Part A 22A (3): 203-218 (Docket EPA-HQOAR-2009-0472-0045).

39 Greene, David L. (2010). “How Consumers Value Fue l Economy: A Literature Review.” EPA Report EPA-420-R-10-008. (Docket EPA-HQ-OAR-20 09-0472-11575).

40 Gramlich, Jacob, “Gas Prices and Endogenous Produc t Selection in the U.S. Automobile Industry,” http://www.econ.yale.edu/seminars/apmicr o/am08/gramlich-081216.pdf , accessed 5/11/09 (Docket EPA-HQ-OAR-2009-0472-0046).

41 Gramlich, Jacob, “Gas Prices and Endogenous Produc t Selection in the U.S. Automobile Industry,” http://www.econ.yale.edu/seminars/apmicr o/am08/gramlich-081216.pdf , accessed 5/11/09 (Docket EPA-HQ-OAR-2009-0472-0046); McManus , Walter, 2007. “The Impact of Attribute-Based Corporate Average Fuel Economy (CAF E) Standards: Preliminary Results.” Ann Arbor, MI: University of Michigan Transportati on Research Institute, Report No. UMTRI2007-31 (Docket EPA-HQ-OAR-2009-0472-0054).Summary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

38 42 For instance, Kleit, Andrew N., “Impacts of Long-R ange Increases in the Fuel Economy (CAFE) Standard,” Economic Inquiry42(2) (April 2004): 279-294 (Docket EPA-HQ-OAR2009-0472-0031); Austin, David, and Terry Dinan, “C learing the Air: The Costs and Consequences of Higher CAFE Standards and Increased Gasoline Taxes,” Journal of Environmental Economics and Management 50 (2005): 562-582 (Docket EPA-HQ-OAR-2009- 0472-0032); Klier, Thomas, and Joshua Linn, 2008. “New Vehicle Characteristics and the Cost of the Corporate Average Fuel Economy Standard,” Fe deral Reserve Bank of Chicago WP 2008- 13, at http://www.chicagofed.org/publications/worki ngpapers/wp2008_13.pdf (accessed 5/6/09) (Docket EPA-HQ-OAR-2009-0472-0047); Jacobsen, Mark, 2008. “Evaluating U.S. Fuel Economy Standards in a Model with Producer and Hous ehold Heterogeneity,” working paper, at http://econ.ucsd.edu/~m3jacobs/Jacobsen_CAFE.pdf (a ccessed 5/6/09) (Docket EPA-HQ-OAR2009-0472-0048).

43 Austin, David, and Terry Dinan, “Clearing the Air: The Costs and Consequences of Higher CAFE Standards and Increased Gasoline Taxes,” Journ al of Environmental Economics and Management 50 (2005): 562-582 (Docket EPA-HQ-OAR-2009-0472-0 032).

44 Greene David L., “TAFV Alternative Fuels and Vehic les Choice Model Documentation,” prepared by the Oak Ridge National Laboratory for t he U.S. Department of Energy, July 2001 (Docket EPA-HQ-OAR-2009-0472-0038).

45 President Barack Obama. “Presidential Memorandum Regarding Fuel Efficiency Standards. The White House, Office of the Press Secretary, May21, 2010. http://www.whitehouse.gov/thepress-office/presidential-memorandum-regarding-fuel -efficiency-standards

46 U.S. Bureau of Labor Statistics, Quarterly Census of Employment and Wages, as accessed on August 9, 2011.

47 Schmalensee, Richard, and Robert N. Stavins. “A G uide to Economic and Policy Analysis of EPA’s Transport Rule.” White paper commissioned by Excelon Corporation, March 2011.

48 Fiscal Year 2012 Mid-Session Review, available at http://www.whitehouse.gov/sites/default/files/omb/b udget/fy2012/assets/12msr.pdf

49 Morgenstern, Richard D., William A. Pizer, and Jhi h-Shyang Shih. “Jobs Versus the Environment: An Industry-Level Perspective.” Jour nal of Environmental Economics and Management 43 (2002): 412-436.

50 Berck, Peter, and Sandra Hoffman. “Assessing the Employment Impacts of Environmental and Natural Resource Policy.” Environmental and Re source Economics 22 (2002): 133-156.

51 Berman, Eli, and Linda T. Bui, (2001) “Environmenta l Regulation and Labor Demand: Evidence from the So uth Coast Air Basin,” Journal of Public Economics , 79, 265 – 295.Summary of interagency working comments received on draft rule under EO 12866 and EO

13563 review. These are for your consideration and are subject to further policy review.

39 52 http://www.bls.gov/emp/ep_data_emp_requirements.ht m

53 http://www.census.gov/manufacturing/asm/index.html

54 http://www.bls.gov/emp/ep_data_emp_requirements.ht m; this analysis used data for sectors 88 (Motor Vehicle Manufacturing) and 90 (Motor Vehicle Parts Manufacturing) from “Chainweighted (2000 dollars) real domestic employment re quirements table. . . adjusted to remove imports.”

55 FOOTNOTE FOR FEV TEARDOWN WORK

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## Below is a summary of interagency working comments received duri ng EO 12866 and EO 13563 review of the draft rule “Joint Rulemaking to Establish Light-Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average Fu el Economy Standards”. They are for your consideration and are subject to further policy review.

1) Interagency commenters thank agencies for the following responses. Commenters recommend that the agencies incorporate a summary of the following responses that the agencies provided into the Preamble so that public commenters can benefit from these
clarifications:

“ EPA Response: The Department of Energy Tran sportation Energy Data Book 1 

## estimates that 15.4% of the total cost per mile for a vehi cle is gas and oil. Between 1985 and 2010, the percentage has varied from a low of 9.4% to a high of 19.9%.

This issue ties into the salience of fuel expenditu res at the time of vehi cle purchase, one of the hypotheses raised in this section. To keep the di scussion of manageable size, we have raised a number of hypotheses in the DRIA without going into depth on any of them. In the Preamble, we have added, in a short discussion of salience, the following footnote: “U.S. Department of Energy, 2011. “Transportation and the Economy,” Ch apter 10 in “Transportation Energy Data Book,” http://cta.ornl.gov/data/te db30/Edition30_Chapter 10.pdf, Table 10.13 , estimates that gas and oil costs were 15.4% of ve hicle costs per mile in 2010.”

“EPA Response: Our gasoline engine technology cost a nd effectiveness estimates are based on the use of regular unleaded gasoline fuel. We do not project that premium fuel will be required to achieve the proposed standards.”

“EPA Response: EPA has not conducted any sensitivity on towing. The vast majority of all of the technology packages which we have added to vehicles maintain towing capability. All full size pickup trucks have been modeled to mainta in towing (gasoline, diesel, and hybrids). All gasoline and diesel vehicles are modeled to main tain towing. For HEV vehicles (other than full size pickup trucks, where we have not utilized Atkinson-cycle engines) , we have utilized Atkinson-cycle engines, but with no downsizing of the engine. Thus, when combined with the electric motor on the vehicle, towing capability is maintained, except for those instances where a vehicle is at or near the maxi mum towing load and operation is on a sustained grade (e.g., going uphill for a long period of time) – and it is possible OEMs may reduce the rated maximum towing limit for such vehicles. Given the relati vely small number of HEVs we project (which are not full size pickups), this impact is modest . It is not clear what part of our analysis

1 

### U.S. Department of Energy, 2011. “Transportation and the Economy,” Chapter 10 in “Transportation Energy Data Book,” http://cta.ornl.gov/data/tedb30/Edition30_Chapter10.pdf, Table 10.13.

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## regarding towing would be a basis for a towing sensitivity assessment, and what type of sensitivity would be performed.”

2) Refueling benefits. Interagency comments r ecommend that the agencies include language seeking public comment from manufacturer s on whether all improvements to fuel economy will translate directly into driving ra nge or if manufacturer s will alternatively
reduce tank size to some extent to maintain driving range.

3) Interagency commenters recommend that the agencies include a discussion in the
Preamble about substitution between new and ol der vehicles in light of increases in vehicle prices. Commenters sugg est that the agencies seek co mment on the effect of rule
on scrappage rates.

1) Interagency commenters recommend that the ag encies insert the fo llowing language in the Preamble on page 61 towards the end of “Section C. Summary of Costs and Benefits for the Proposed National Program”:

“In the RIAs and TSD chapters, the agencies project that some advanced technologies, such as 8-speed automatic transmissions, ha ve negative costs. In other words, these technologies reduce both fuel consumption and vehicle production cost s at the same time. One might expect that auto manufacturers would be able to iden tify such technologies with negative costs and incorporate them into their designs absent regulation. However, for reasons x and y [please insert agency explanation], auto manufacturers will not incorporate these technologies into their designs absent re gulation. For that reason, these negative cost technologies do not belong in the baseline. We seek comment on the estimates of costs of all the technologi es projected to ha ve negative costs.”

2) Interagency commenters recommend that the ag encies insert the fo llowing language in the Preamble on page 61 towards the end of “Section C. Summary of Costs and Benefits for the Proposed National Program”:

“EPA and NHTSA included discussion of lear ning cost assumptions in the RIAs and TSD Chapter X. Since the agencies had to project how learning will occur with new technologies over a long period of time, we request comments on the assumptions of learning costs and methodology. In particular , we are interested in input on the assumptions for certain advanced technologies not expected to be available until 2017,

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## but for which we assume that learning (and th e associated cost reduc tions) begin as early as 2012. We seek comment on the appropriate ness of these pre-produ ction applications of learning.”

3) Interagency commenters recommend that the ag encies insert the fo llowing language in the Preamble section of energy security benefits:

“The calculation of energy securi ty benefits does not include en ergy security costs associated with reliance on foreign sources of lithium and rare earth metals for HEVs and EVs. The agencies intend to quantify this impact for th e final rule stage and seek public input on information that would enable agencies to deve lop this analysis. EPA and DOT also seek public input on the projections that energy securi ty benefits will grow rapidly through 2025.”

4) Interagency commenters recommend that the agencies include the following language in the Preamble on page 61 towards the end of “Section C. Summary of Costs and Benefits for the Proposed National Program”:

“Due to time constraints, the analysis accompanying this joint rule did not include additional costs that may be associated with adoption of certain technologies included in the packages such as:

‐ EV/HEV/PHEV battery disposal costs

‐ Infrastructure costs associated with building new charging stations for EVs

‐ Changes in vehicle maintenance and repair costs

‐ Premium fuel requirements for certain advanced technologies

The agencies intend to quantify these additiona l costs for the final rule stage. DOT and
EPA seek comment on other costs or cost savings that are unaccounted for in this analysis, and agencies seek information on how to quantify impacts of these additional cost and savings categories for the final rule stage.”

5) Interagency commenters recommend that the agencies include the following language in the Preamble on page 61 towards the end of “Section C. Summary of Costs and Benefits

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## for the Proposed National Program”. Interagency comments recommend that agencies title this section “Uncertainty Analysis and Additional Sensitivity Cases”

“Uncertainty Analysis and Additional Sensitivity Cases”

“Due to the uncertainty and difficulty in projecting costs and benefits through 2025, the agencies relied on a combination of methods to project costs and costeffectiveness of technologies. For example, for most advanced technologies, EPA
and DOT relied on new studies and resear ch conducted by EPA, and contracted work with FEV and Ricardo. For other technologies, EPA and DOT relied on cost
and cost-effectiveness estimates de veloped in the 2012-2016 rulemaking by applying learning to those estimates appropriate for the 2017-2025 time period.

DOT conducted a full uncertainty analysis , which is included in the RIA section x. Results of the uncertainty analysis are summarized below:

Total Benefits at 7% discount rate ____

Total Benefits at 3% discount rate ____

Total Costs and 7% discount rate ____

Total Costs at 3% discount rate _____

DOT also conducted sensitivity cases that are very close to the costs and costeffectiveness estimates used by the Nationa l Academy of Sciences in their report titled, “PLEASE INCLUDE CORRECT TITLE.” As the agencies indicated in both RIAs, the NAS did not project costs and cost-effectiveness for technologies beyond 2015. NHTSA applied learning and di scounting similar to the learning and discounting applied to current agency projections of certain technologies to derive alternative sensitivity ca ses for 2017-2025. NHTSA estimated the following impacts on the costs and benefits of the rule when using the NAS-like
sensitivities:

Total Benefits at 7% discount rate ____

Total Benefits at 3% discount rate ____

Total Costs and 7% discount rate ____

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## Total Costs at 3% discount rate _____

The agencies seek comment on the methods used to conduct the uncertainty analysis and on the results from the additional sensitivity cases. The agencies also seek comment on whether the agencies shoul d use any of the sensitivity cases as part of the primary case for the final rule.”

6) Interagency commenters recommend that the ag encies remove this statement that first appears of pages 9-10 of the Preamble and ev erywhere else in the Preamble, both RIAs, and TSD chapters where this stat ement is repeated/summarized:

“The agencies have designed the proposed standards to preserve consumer choice -- that is, the proposed standards should not affect consumers’ opportunity to purchase the size of vehicle w ith the performance, utility and safety features that
meets their needs.”

7) Interagency commenters note th at Table X-10 on page 459 might be confusing because it
looks like the “market driven baseline” was much higher than it actually is. Interagency commenters recommend that the agencies clar ify what methodology was used to develop
the table and estimates.

8) Interagency commenters thank the agencies fo r their response on the model’s inability to accurately project PHEV penetration. As a follow-up, commenters recommend that agencies include a caveat with each table th at details the limitations of modeling PHEVs versus EVs and the fact that the analysis doe s not consider the imp act of the advanced vehicle incentives. Interagency commenters also request clarity from agencies on why agencies chose not to combine EV/PHEV proj ections in a single column as had been
done for the TAR?

Other Follow-up Interagency comments on Preamble:

9) Page 39 – “EPA is proposing that EVs and FC Vs start with a multiplier value of 2.0 in MY 2017, phasing down to a value of 1.5 in MY 2021. PHEVs would start at a multiplier value of 1.6 in MY 2017 and phase down to a value of 1.3 in MY 2021. 2 

## The multiplier would be 1.0 for MYs 2022-2025.” Interagency commenters note that the multipliers appear to be related to the hybrid ization degree of the powertrain (I.e., BEVs have a higher multiplier than PHEVs). If so, perhaps the multiplier should be

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## proportional to the hybridization degree. This would allow differe ntiating PHEVs with different EV ranges. Otherwise, a PHEV with a small battery (i.e., 4kWh) gets the same credit as a PHEV with a larger one (i.e., 16kWh).

10) Page 40 – “EPA is proposing that mild HEV pickup trucks would be eligible for a per vehicle credit of 10 g/mi 3 

## during MYs 2017-2021 if the technology is used on a minimum percentage of a company’s full size pickups...” Interagency commenters request clarity
on whether there is a credit for othe r technologies, such as PHEVs?

11) Page 61, Table I-21: Interagency comenters not e that the 7% discount rate Car Sum of Present Values may be incorrect. Commenters sugge st that agencies to double this table.

12) Page 84, Table II-2: Interagency commenter re commends that agencies define the term “MAV (Multi-Activity Vehicle)”.

13) Page 100 – “The agencies excluded diesels and dedicated AFVs because the agencies anticipate that advanced gaso line-fueled vehicles are li kely to be dominant through MY2025.” Interagency commenters request cl arity on how agencies arrived at this
conclusion.

14) Page 112 – “ Shift optimization is a strategy whereby the engine and/or transmission controller(s) emulates a CVT by continuously evaluating all possible gear options that would provide the necessary tractive power and select the best gear ratio that lets the engine run in the most efficient operating zo ne.” Interagency comme nters request agency views on whether the trade-off between drive qu ality and fuel consumption benefits with respect to CVT controls could be an issue, and if this has le d OEMs to scale back development of CVTs. Commenters would lik e to understand if drive quality suffers when fuel consumption benefits are ma ximized through CVT operation. Commenters also request clarity on whether drive-quality has been taken into acc ount with respect to the shift optimization strategy that emulates a CVT.

15) Page 113 – “ Mass Reduction can be achieved in many ways, such as material substitution, design optimization, part cons olidation, improving ma nufacturing process, etc. The agencies applied ma ss reduction of up to 20 percen t relative to MY 2008 levels in this NPRM compared to only 10 per cent in 2012-2016 final rule.” Interagency commenter recommends that agencies incl ude language to clarify what the 20% reduction includes (if this is for the en tire vehicle or just the glider).

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## 16) Page 182 – Interagency commenters note th at the table lists the incentives for EV/PHEV/FCV multipliers in the same colum n. Interagency commenters note that this seems to be different than the statement on page 39 that mentions that EVs and FCVs
start with 2 and PHEVs with 1.6 in 2017. The same values ar e also in Table III-14 on page 263.

17) Page 271 – Interagency commenters find the CNG vehicle utility factor discussion for dual fuel CNG confusing in the second para graph of this page of the preamble. Interagency commenters request clarity in the text on how agencies derived the 95% CNG operation.

18) Page 314 – Table III – Interagency commenters note that it seems unusual that GM and Hyundai are shown as having 0% penetration of HEVs (and Ford at only 2%) in 2025 while they all have already HEVs in the mark et. Also, commenters no te that Toyota, the current market leader, has a lower percenta ge (12%) than BMW and Tata, who have no HEVs on the market. Interagency commneter s request clarity be hind these numbers.

19) Page 344 – Table III-50. Commenters suggest that agencies include a table comparing the current technology costs with the va lues in 2025 along with a percentage improvement per year to reach these values. Commenters suggest a similar table for Page
673 Table IV.G.4-1A

20) Page 324 – Table III-31 – Interagency comme nters request clarity on why idle-stop systems and mild HEVs are not considered in any of the analysis of this section. Commenters request clarity on whether these technologies are being considered in large production by auto manufacturers now.

21) Page 570 – “NHTSA notes that, in deve loping technology cost and effectiveness estimates, the agencies have made every e ffort to hold constant aspects of vehicle performance and utility typically valued by consumers, such as horsepower, carrying capacity, drivability, durability, noise, vibr ation and harshness (NVH) and towing and hauling capacity.” Interagency commenters request clarity on th e criteria used for durability, noise, vibration, and harshness.

22) Page 576 – Commenters suggest that agencies include language to describe the necessity to use two separate tools (VOLPE and OME GA) and provide further explanations about how the difference in the tool methodologi es and assumptions influence the overall
results.

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further policy review.

8 

## 23) Page 620 – “NHTSA notes that the Volpe model not only has been formally peerreviewed and tested and revi ewed through three rulemakings, but also has some features especially important for the analysis of CAFE standards under EPCA/EISA. Among these are the ability to perform year-by-year analysis, and the ab ility to account for engineering differences between specific vehicle models.“ Interagency commenters recommend that agencies include language a nd information elaborat ing about the impact
of these features and how it would affect results if they did not have them.

24) Page 620 – “By combining technologies incr ementally and on a model-by-model basis,
the CAFE model is able to account for important engineeri ng differences between vehicle models and avoid unlikely technology combin ations.” Interagency commenters suggest that agencies to add additional text elaborat ing on the impact of addressing technologies individually vs. packages.

25) Page 681/682 – Interagency commenters suggest that agencies include an explanation of why Table IV.G.4-4 shows that almost no HEVs are required when EPA states that as much as 15% would be necessary (Table III-23 page 314)?

26) Page 5-71: Commenters request clarity on whether it is likely or unlikely that the g/mi values shown for automobiles for start-stop technology and solar roofs would be so close (2.9 vs. 3.0, respectively). Interagency co mmenters note that the value of these technologies depends to a large part on climate or time of da y. Commenters also note that in particular, the value of start-stop might be much larger compared to solar since it is not dependent on weather (sunny in Dallas vs. rai ny in Seattle vs. snowy in Vermont) or time of day (daylight vs. night). Commenters note that the same argument could apply to solar control. Commenters request clarity on whet her agencies considered these potential
differences.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 1 of 768 Below is a summary of interagency working comments received during EO 12866 and
EO 13563 review of the draft rule “Joint Rulemaking to Establish Light-Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average Fuel Economy Standards”. They are for your consideration and are subject to further policy review.

****

ENVIRONMENTAL PROTECTION AGENCY

40 CFR Parts 86 and 600

DEPARTMENT OF TRANSPORTATION

National Highway Traffic Safety Administration

49 CFR Parts 523, 531, 533, 536, 537, and 538

[EPA–HQ–OAR–2010–0799; FRL_XXXX-X; NHTSA-2010-0131]

RIN 2060-AQ54; RIN 2127-AK79

2017 and Later Model Year Light-Duty Vehicle Greenhouse Gas Emissions and Corporate Average Fuel Economy Standards

AGENCIES: Environmental Protection Agency (EPA) and National Highway Traffic Safety Administration (NHTSA).

ACTION: Proposed Rule.

SUMMARY: EPA and NHTSA, on behalf of the Department of Transportation, are issuing thisjoint proposal to further reduce greenhouse gas emissions and improve fuel economy for lightduty vehicles for model years 2017-2025. This proposal extends the National Program beyond the greenhouse gas and corporate average fuel economy standards set for model years 2012- 2016. On May 21, 2010, President Obama issued a Presidential Memorandum requesting that NHTSA and EPA develop through notice and comment rulemaking a coordinated National Program to reduce greenhouse gas emissions of light-duty vehicles for model years 2017-2025. This proposal, consistent with the President’s requ est, responds to the country’s critical need to address global climate change and to reduce oil consumption

. NHTSA is proposing Corporate Average Fuel Economy standards under the Energy Policy and Conservation Act, as amended by the Energy Independence and Security Act, and EPA is proposing greenhouse gas emissionsSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 2 of 768 standards under the Clean Air Act. These standards apply to passenger cars, light-duty trucks, and medium-duty passenger vehicles, and repr esent a continued harmonized and consistent National Program. Under the National Program for model years 2017-2025, automobile manufacturers would be able to continue building a single light-duty national fleet that satisfies all requirements under both programs while ensuring that consumers still have a full range of vehicle choices. EPA is also proposing a minor chan ge to the regulations applicable to MY 2012- 2016, with respect to air conditioner performance and measurement of nitrous oxides.

DATES : Comments : Comments must be received on or before [Insert date 60 days after publication in the Federal Register]

, sixty days after date of publication in the Federal Register . 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 [Insert date 30 days after publication in the Federal Register], thirty days after date of publication in the Federal Register . See the SUPPLEMENTARY INFORMATION section on “Public Participation” for more information about written comments.

Public Hearings: NHTSA and EPA will jointly hold xx public hearings on the following dates: [Insert Dates] , in [Insert Locations] . The hearings will start at 9 a.m. local time and continue until everyone has had a chance to speak. See the SUPPLEMENTARY INFORMATION section on “Public Participation.” for more information about the public hearings.

ADDRESSES : Submit your comments, identified by Docket ID No. EPA-HQ-OAR-2010-0799 and/or NHTSA-2010-0131, by one of the following methods:

 Online: www.regulations.gov: Follow the on-line instructi ons for submitting comments.

 Email: a-and-r-Docket@epa.gov

 Fax: EPA: (202) 566–9744; NHTSA: (202) 493-2251.

 Mail:

o 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-2010-0799. In addition, please mail a copy of your comments on the information collection provisions to the Office of Informatio n and Regulatory Affairs, Office of Management and Budget (OMB), Attn: Desk Officer for EPA, 725 17th St., NW., Washington, DC 20503.

o 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:

o EPA: Docket Center, (EPA/DC) EPA West, Room B102, 1301 Constitution Ave., NW., Washington, DC, Attention Docket ID No. EPA-HQ-OAR-2010- 0799. Such deliveries are only accepted during the Docket’s normal hours of operation, and special arrangements should be made for deliveries of boxed information.

o 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.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 3 of 768 Instructions : Direct your comments to Docket ID No. EPA-HQ-OAR-2010-0799 and/or
NHTSA-2010-0131

. See the SUPPLEMENTARY INFORMATION section on “Public Participation” for more informatio n about submitting written comments.

Public Hearing : NHTSA and EPA will jointly hold xx public hearings at the following locations: [Insert Date, Location, & Address] . See the SUPPLEMENTARY INFORMATION section on “Public Participation” for more information about the public hearings.

Docket : All documents in the dockets are listed in the www.regulations.gov index. Although listed in the index, some information is not publicly available, e.g., confidential business information (CBI) or other information whos e disclosure is restricted by statute. Certain other material, such as copyrighted material, wi ll be publicly availabl e only in hard copy. Publicly available docket materials are available either electronically in www.regulations.gov or in hard copy at the following locations: EPA: EPA Docket Center, EPA/DC, EPA West, Room 3334, 1301 Constitution Ave., NW ., Washington, DC. 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

. NHTSA: Docket Management Facility, M-30, U.S. Department of Transportation, West Bu ilding, Ground Floor, Rm. W12-140, 1200 New Jersey Avenue, SE, Washington, DC 20590. The Docket Management Facility is open between 9 a.m. and 5 p.m. Eastern Time, Monday through Friday, except Federal holidays.

FOR FURTHER INFORMATION CONTACT: EPA: Christopher Lieske, Office of Transportation and Air Quality, Assessment a nd 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; e-mail address: ot aqpublicweb@epa.gov. NHTSA: Rebecca Yoon, Office of the Chief Counsel, National Highway Tr affic Safety Administration, 1200 New Jersey Avenue, SE, Washington, DC 20590. Telephone: (202) 366-2992.

SUPPLEMENTARY INFORMATION:

A. Does this Action Apply to Me?

This action affects companies that manufacture or sell new light-duty vehicles, light-duty trucks, and medium-duty passenger vehicles, as defined under EPA’s CAA regulations, 1 and passenger automobiles (passenger cars) and non-passenger automobiles (light trucks) as defined under NHTSA’s CAFE regulations. 2 Regulated categories and entities include:

1 “Light-duty vehicle,” “light-duty truck,” and “medium-dut y passenger vehicle” are defined in 40 CFR 86.1803-01. Generally, the term “light-duty vehicle” means a passenger car, the term “light-duty truck” means a pick-up truck, sport-utility vehicle, or minivan of up to 8,500 lb s gross vehicle weight rating, and “medium-duty passenger vehicle” means a sport-utility vehicle or passenger van fr om 8,500 to 10,000 lbs gross vehicle weight rating. Medium-duty passenger vehicles do not include pick-up trucks.

2 “Passenger car” and “light truck” are defined in 49 CFR Part 523.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 4 of 768 Category NAICS Codes A Examples of Potentially Regulated Entities

Industry 336111
336112 Motor Vehicle Manufacturers

Industry 811111
811112 811198 423110 Commercial Importers of Vehicles and Vehicle Components

Industry 335312
336312 336399 811198 Alternative Fuel Vehicle Converters

A North American Industry Classification System (NAICS)

This list is not intended to be exhaustive, bu t rather provides a guide regarding entities likely to be regulated by this action. To dete rmine whether particular activities may be regulated by this action, you should carefully examine the regulations. You may direct questions regarding the applicability of this action to the person listed in FOR FURTHER INFORMATION CONTACT

. B. Public Participation

NHTSA and EPA request comment on all aspects of this joint proposed rule. This section describes how you can participate in this process.

How Do I Prepare and Submit Comments?

In this joint proposal, there are many issues common to both EPA’s and NHTSA’s proposals. For the convenience of all parties, comments submitted to the EPA docket will be considered comments submitted to the NHTSA docket, and vice versa. An exception is that comments submitted to the NHTSA docket on NHTS A’s Draft Environmenta l Impact Statement (EIS) will not be considered submitted to the EPA docket. Therefore, the public only needs to submit comments to either one of the two agency dockets, although they may submit comments to both if they so choose. Comments that ar e submitted for consideration by one agency should be identified as such, and comments that are submitted for consideration by both agencies should be identified as such. Absent such identificatio n, each agency will exercise its best judgment to determine whether a comment is submitted on its proposal.

Further instructions for submitting comments to either the EPA or NHTSA docket are described below.

EPA: Direct your comments to Docket ID No EPA-HQ-OAR-2010-0799. EPA’s policy is that all comments received will be included in the public docket wit hout change and may be made available online at www.regulations.gov , including any personal information provided, unless the comment includes information claimed to be Confidential Business Information (CBI)Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 5 of 768 or other information whose disclosure is restricted by statute. Do not submit information that you consider to be CBI or otherwise protected through www.regulations.gov or e-mail. The www.regulations.gov Web site is an ‘‘anonymous access’’ system, which means EPA will not know your identity or contact information unless you provide it in the body of your comment. If you send an e-mail comment directly to EPA without going through www.regulations.gov your e-mail address will be automatically captured and included as part of the comment that is placed in the public docket and made available on the Internet. If you submit an electronic comment, EPA recommends that you include your name and other contact information in the body of your comment and with any disk or CD–ROM you submit. If EPA cannot read your comment due to technical difficulties and cannot contact you for cl arification, EPA may not be able to consider your comment. Electronic files should avoid the use of special characters, any form of encryption, and be free of any defects or viruses. For additional information about EPA’s public docket visit the EPA Docket Center homepage at http:// www.epa.gov/epahome/dockets.htm

.

NHTSA: Your comments must be written and in English. To ensure that your comments are correctly filed in the Docket, please include the Docket number NHTSA-2010-0131 in your comments. Your comments must not be more than 15 pages long. 3 NHTSA established this limit to encourage you to write your primary comments in a concise fashion. However, you may attach necessary additional documents to your comments, and there is no limit on the length of the attachments. If you are submitting comments electronically as a PDF (Adobe) file, we ask that the documents submitted be scanned us ing the Optical Character Recognition (OCR) process, thus allowing the agencies to search and copy certain portions of your submissions. 4 Please note that pursuant to the Data Quality Act, in order for the substantive data to be relied upon and used by the agencies, it must meet the information quality standards set forth in the OMB and Department of Transportation (DOT) Data Quality Act guidelines. Accordingly, we encourage you to consult the guidelines in preparing your comments. OMB’s guidelines may be accessed at http://www.whitehouse.gov/omb/fedreg/reproducible.html. DOT’s guidelines may be accessed at http://www.dot.gov/dataquality.htm.

Tips for Preparing Your Comments

When submitting comments, please remember to:

• Identify the rulemaking by docket number and other identifying information (subject heading, Federal Register date and page number).

• Explain why you agree or disagree, suggest alternatives, and substitute language for your requested changes.

• Describe any assumptions and provide any technical information and/or data that you used.

• If you estimate potential costs or burde ns, explain how you arrived at your estimate in sufficient detail to allow for it to be reproduced.

• Provide specific examples to illustrate your concerns, and suggest alternatives.

• Explain your views as clearly as possible, avoiding the use of profanity or personal threats.

3 See 49 CFR 553.21.

4 Optical character recognition (OCR) is the process of converting an image of text, such as a scanned paper document or electronic fax file, into computer-editable text.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 6 of 768 • Make sure to submit your comments by the comment period deadline identified in the DATES section above.

How Can I Be Sure That My Comments Were Received?

NHTSA: If you submit your comments by mail and wish Docket Management to notify you upon its receipt of your comments, enclose a self-addressed, stamped postcard in the envelope containing your comments. Upon recei ving your comments, Docket Management will return the postcard by mail.

How Do I Submit Confidential Business Information?

Any confidential business informa tion (CBI) submitted to one of the agencies will also be available to the other agency. However, as with all public comments, any CBI information only needs to be submitted to either one of the agenci es’ dockets and it will be available to the other. Following are specific instructions for submitting CBI to either agency.

EPA: Do not submit CBI to EPA through www.regulations.gov or e-mail. Clearly mark the part or all of the information that you claim to be CBI. For CBI information in a disk or CD ROM that you mail to EPA, mark the outside of the disk or CD ROM as CBI and then identify electronically within the disk or CD ROM the sp ecific information that is claimed as CBI. In addition to one complete version of the comment that includes information claimed as CBI, a copy of the comment that does not contain the information claimed as CBI must be submitted for inclusion in the public docket. Information so marked will not be disclosed except in accordance with procedures set forth in 40 CFR Part 2.

NHTSA: If you wish to submit any information under a claim of confidentiality, you should submit three copies of your complete submission, including the information you claim to be confidential business information, to the Chief Counsel, NHTSA, at the address given above under FOR FURTHER INFORMATION CONTACT . When you send a comment containing confidential business information, you should include a cover letter setting forth the information specified in our confidential business information regulation. 5

In addition, you should submit a copy from which you have deleted the claimed confidential business information to the Docket by one of the methods set forth above.

Will the Agencies Consider Late Comments?

NHTSA and EPA will consider all comments received before the close of business on the comment closing date indicated above under DATES . To the extent practicable, we will also consider comments received after that date. If interested persons believe that any new information the agency places in the docket affects their comments, they may submit comments after the closing date concerning how the agency should consider that information for the final rule. However, the agencies’ ability to consider any such late comments in this rulemaking will be limited due to the time frame for issuing a final rule.

5 See 49 CFR Part 512.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 7 of 768 If a comment is received too late for us to practicably consider in developing a final rule, we will consider that comment as an inform al suggestion for future rulemaking action.

How Can I Read the Comments Submitted By Other People?

You may read the materials placed in the docket for this document (e.g

. , the comments submitted in response to this document by other interested persons) at any time by going to http://www.regulations.gov. Follow the online instructions for accessing the dockets. You may also read the materials at the EPA Docket Ce nter or NHTSA Docket Management Facility by going to the street addresses given above under ADDRESSES

. How Do I Participate in the Public Hearings?

NHTSA and EPA will jointly host xx public hearings on the dates and locations described in the DATES and ADDRESSES sections above.

If you would like to present testimony at the public hearings, we ask that you notify the EPA and NHTSA contact persons listed under FOR FURTHER INFORMATION CONTACT at least ten days before the hearing. Once EPA and NHTSA learn how many people have registered to speak at the public hearing, we w ill allocate an appropriate amount of time to each participant, allowing time for lunch and necessary breaks throughout the day. For planning purposes, each speaker should anticipate speaking for approximately ten minutes, although we may need to adjust the time for each speaker if there is a large turnout. We suggest that you bring copies of your statement or other material for the EPA and NHTSA panels.. It would also be helpful if you send us a copy of your statement or other materials before the hearing. To accommodate as many speakers as possible, we pref er that speakers not use technological aids (e.g., audio-visuals, computer slideshows). However, if you plan to do so, you must notify the contact persons in the FOR FURTHER INFORMATION CONTACT section above. You also must make arrangements to provide your presentation or any other aids to NHTSA and EPA in advance of the hearing in order to facilitate set-up. In addition, we will reserve a block of time for anyone else in the audience who wants to give testimony.

The hearing will be held at a site accessible to individuals with disabilities. Individuals who require accommodations such as sign language interpreters should contact the persons listed under FOR FURTHER INFORMATION CONTACT section above no later than ten days before the date of the hearing.

NHTSA and EPA will conduct the hearing informally, and technical rules of evidence will not apply. We will arrange for a written transcript of the hearing and keep the official record of the hearing open for 30 days to allow you to submit supplementary information. You may make arrangements for copies of the transcript directly with the court reporter.

Table of Contents

[Placeholder]Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 8 of 768 I. Overview of Joint EPA/NHTSA Proposed 2017-2025 National Program

Executive Summary

EPA and NHTSA are each announcing proposed rules that call for strong and coordinated Federal greenhouse gas and fuel economy standards for passenger cars, light-duty trucks, and medium-duty passenger vehicles (hereaf ter light-duty vehicles or LDVs). Together, these vehicle categories, which include passenge r cars, sport utility vehicles, crossover utility vehicles, minivans, and pickup trucks, among others, are presently responsible for approximately 60 percent of all U.S. transportation-related greenhouse gas (GHG) emissions and fuel consumption. This proposal would extend the National Program of Federal light-duty vehicle GHG emissions and corporate average fuel economy (CAFE) standards to model years (MYs) 2017-2025. This proposed coordinated program would achieve important reductions in GHG emissions and fuel consumption from the light-d uty vehicle part of the transportation sector, based on technologies that either are commercially available or that the agencies project will be commercially available in the rulemaking timeframe and that can be incorporated at a reasonable cost. These higher initial vehicle costs will be mo re than offset by significant fuel savings for
consumers over time.

This proposal builds on the success of the fi rst phase of the National Program to regulate fuel economy and GHG emissions from U.S. light-duty vehicles, which established strong and coordinated standards for model years (MY) 2012-2016. As with the first phase of the National Program, collaboration with California Air Re sources Board (CARB) and with automobile manufacturers and other stakeholders has been a key element in developing the agencies’ proposed rules. Continuing the National Program would ensure that all manufacturers can build a single fleet of U.S. vehicles that would satisfy all requirements under both programs as well as under California’s program, helping to reduce costs and regulatory complexity while providing significant energy security and environmental benefits.

Combined with the standards already in effect for MYs 2012-2016, as well as the MY 2011 CAFE standards, the proposed standards woul d result in MY 2025 light-duty vehicles with nearly double the fuel economy, and approximately one-half of the GHG emissions compared to MY 2010 vehicles -- representing the most signi ficant federal action ever taken to reduce GHG emissions and improve fuel economy in the U.S. EPA is proposing standards that are projected to require, on an average industry fleet wide basis, 163 grams/mile of carbon dioxide (CO 2 ) in model year 2025, which is equivalent to 54.5 mpg if this level was achieved solely through improvements in fuel efficiency. 6 NHTSA is proposing two phases of passenger car and light

6 Real-world CO 2 is typically 25 percent higher and real-world fuel economy is typically 20 percent lower than the CO2 and CAFE values discussed here. The reference to CO 2 here refers to CO 2 equivalent reductions, as thisSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 9 of 768 truck standards. The first phase, from MYs 2017-2021, includes proposed standards that are projected to require, on an average industry fleet wide basis, 40.9 mpg in MY 2021. The second phase of the CAFE program, from MYs 2022-2025, represents conditional 7 proposed standards that are projected to require, on an average indu stry fleet wide basis, 49.6 mpg in model year 2025. Both the EPA and NHTSA standards are projected to be achieved through a range of technologies, including improvements in air co nditioning efficiency, which reduces both GHG emissions and fuel consumption; the EPA standard s also are projected to be achieved with the use of air conditioning refrigerants with a lowe r global warming potential (GWP), which reduce GHGs (i.e., hydrofluorocarbons) but do not improve fuel economy. The agencies are proposing separate standards for passenger cars and trucks, based on a vehicle’s size or “footprint.” For the MYs 2022-2025 standards, EPA and NHTSA are proposing a comprehensive mid-term evaluation and agency decision-making process, given both the long time frame and NHTSA’s obligation to conduct a separate rulemaking in or der to establish final standards for vehicles for those model years,

From a societal standpoint, this second phase of the National Program is projected to save
over 4 billion barrels of oil and over 2 billion metr ic tons of GHG emission s over the lifetimes of
those vehicles sold in MY 2017- 2025. The agencies estimate that fuel savings will far outweigh higher vehicle costs, and that the net benefits to society of the MYs 2017-2025 National Program will be in the range of $348 billion to $468 billion (7 and 3 percent discount rates, respectively)
over the lifetimes of those vehicles sold in MY 2017-2025.

These proposed standards would have signifi cant savings for consumers at the pump. Higher costs for new vehicle technology will add, on average, about $ 2000 for consumers who buy a new vehicle in MY 2025. Those consumer s who drive their MY 2025 vehicle for its entire lifetime will save, on average, $5200 to $6600 (7 and 3 percent discount rates, respectively) in fuel savings, for a net lifetime savings of $3000 to 4400. For those consumers who purchase their new MY 2025 vehicle with cash, the discounted fuel savings will offset the higher vehicle cost in about 4 years, and fuel savings will co ntinue for as long as the consumer owns the vehicle. Those consumers that buy a new vehicle with a typical 5-year loan will benefit from an average monthly cash flow savings of about $11 during the loan period, or about $130 per year, on average, as the monthly fuel savings more than offsets the higher monthly payment due to the higher incremental vehicle cost.

The agencies have designed the proposed stan dards to preserve consumer choice -- that is, the proposed standards should not affect c onsumers’ opportunity to purchase the size of

included some degree of reductions in greenhouse gases other than CO 2 , as one part of the air conditioning related reductions.

7 By ”conditional,” NHTSA means to say that the proposed standards for MYs 2022-2025 represent the agency’s current best estimate of what levels of stringency would be maximum feasible in those model years, but in order for the standards for those model years to be legally review able a subsequent rulemaking must be undertaken by the agency at a later time. See Section IV for more information.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 10 of 768 vehicle with the performance, u tility and safety features that meets their needs. The standards are based on a vehicle’s size, or footprint – that is, larger vehicles have relatively less stringent fuel economy/GHG emissions targets and sma ller vehicles have more stringent fuel economy/GHG emissions targets. Thus, consumers will be able to continue to choose from the same mix of vehicles that are currently in the marketplace.

The agencies’ believe there is a wide range of technologies available for manufacturers to consider in reducing GHG emissions and improvi ng fuel economy. The proposals allow for longterm planning by manufacturers and suppliers for the continued development and deployment across their fleets of fuel saving and emissions-reduc ing technologies. The agencies believe that advances in gasoline engines and transmissions w ill continue for the fores eeable future, and that there will be continual improvement in other tec hnologies, including vehi cle weight reduction, lower tire rolling resistance, improvements in ve hicle aerodynamics, diesel engines, and more efficient vehicle accessories. The agencies also e xpect to see increased electrification of the fleet through the expanded production of stop/start, hybrid, plug-in hybrid and electric vehicles. Finally, the agencies expect that vehicle air c onditioners will continue to improve by becoming more efficient and by increasing the use of alternative refrigerants. Many of these technologies are already available today, and manufacturers will be able to meet the standards through significant efficiency improvements in these tech nologies, as well as a significant penetration of these and other technologies across the fleet. Auto manufacturers may also introduce new technologies that we have not considered for this rulemaking analysis, which could make possible alternative, more cost-e ffective paths to compliance.

A. Introduction

1. Continuation of the National Program

EPA and NHTSA are each announcing proposed rules that call for strong and coordinated Federal greenhouse gas and fuel economy standards for passenger cars, light-duty trucks, and medium-duty passenger vehicles (hereaf ter light-duty vehicles or LDVs). Together, these vehicle categories, which include passenge r cars, sport utility vehicles, crossover utility vehicles, minivans, and pickup trucks, are presentl y responsible for approximately 60 percent of all U.S. transportation-related greenhouse gas emissions and fuel consumption. The proposal would extend the National Program of Federal light-duty vehicle greenhouse gas (GHG) emissions and corporate average fuel economy (CAFE) standards to model years (MYs) 2017- 2025. The coordinated program being proposed would achieve important reductions of greenhouse gas (GHG) emissions and fuel consumption from the light-duty vehicle part of the transportation sector, based on technologies that either are commercially available or that the agencies project will be commercially availabl e in the rulemaking timeframe and that can be incorporated at a reasonable cost.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 11 of 768 In working together to develop the next round of standards for MYs 2017-2025, NHTSA and EPA are building on the success of the first pha se of the National Progr am to regulate fuel economy and GHG emissions from U.S. light-duty vehicles, which established the strong and coordinated standards for model years (MY) 2012-2016. As for the MYs 2012-2016 rulemaking, collaboration with California Air Resources Board (CARB) and with industry and other stakeholders has been a key element in developing the agencies’ proposed rules. Continuing the National Program would ensure that all manufacturers can build a single fleet of U.S. vehicles that would satisfy all requirements under both programs as well as under California’s program, helping to reduce costs and regulatory complexity while providing significant energy security
and environmental benefits.

The agencies have been developing the basis for these joint proposed standards almost since the conclusion of the rulemaking establis hing the first phase of the National Program. After much research and deliberation by the agen cies, along with CARB and other stakeholders, President Obama announced plans for these proposed rules on July 29, 2011 and NHTSA and EPA issued a Supplemental Notice of Intent (N OI) outlining the agencies’ plans for proposing the MY 2017-2025 standards and program. 8 The State of California and thirteen auto manufacturers representing over 90 percent of U.S. vehicle sales provided letters of support for the program concurrent with the Supplemental NOI. 9 The United Auto Workers (UAW) also supported the announcement. 10 As envisioned in the Presidential announcement and Supplemental NOI, this proposal sets forth proposed MYs 2017-2025 standards as well as detailed supporting analysis for those standards an d regulatory alternatives for public review and comment. The program that the agencies are proposing will spur the development of a new generation of clean cars and truc ks through innovative technologies and manufacturing that will, in turn, spur economic growth and create high-quality domestic jobs, enhance our energy security, and improve our environment. Consistent with Executive Order 13563, this proposal was developed with early consultation with stakeholders, employs flexible regulatory approaches to reduce burdens, maintains freedom of choice for the public, and helps to harmonize federal and state regulations.

As described below, NHTSA and EPA are proposing a continuation of the National Program that the agencies believe represents the appropriate levels of fuel economy and GHG emissions standards for model years 2017-2025, given the technologies that the agencies anticipate will be available for use on these vehi cles and the agencies’ understanding of the cost and manufacturers’ ability to apply these technol ogies during that time frame, and consideration of other relevant factors. Under this joint rulemaking, EPA is proposing GHG emissions

8 76 FR 48758 (August 9, 2011).

9 Commitment letters are available at http://www.epa.gov/otaq/climate/regulations.htm and at http://www.nhtsa.gov/fuel-economy (last accessed Aug. 24, 2011).

10 The UAW’s support was expressed in a statement on July 29, 2011, which can be found at http://www.uaw.org/articles/ua w-supports-administration- proposal-light-duty-vehicl e-cafe-and-greenhouse-gasemissions-r (last accessed September 19, 2011)Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 12 of 768 standards under the Clean Air Act (CAA), and NHTSA is proposing CAFE standards under EPCA, as amended by the Energy Independence and Security Act of 2007 (EISA). This joint rulemaking proposal reflects a carefully coordina ted and harmonized approach to implementing these two statutes, in accordance with all substa ntive and procedural requirements imposed by
law. 11

The proposed approach allows for long-term planning by manufacturers and suppliers forthe continued development and deployment across their fleets of fuel saving and emissionsreducing technologies. NHTSA’s and EPA’s tech nology assessment indicates there is a wide range of technologies available for manufacturer s to consider in reducing GHG emissions and improving fuel economy. The agencies believe that advances in gasoline engines and
transmissions will continue for the foreseeable futu re, which is a view that is supported in the literature and amongst the vehicle manufacturers and suppliers. 12 The agencies also believe that there will be continual improvement in other te chnologies including re ductions in vehicle weight, lower tire rolling resistance, improvements in vehicle aerodynamics, diesel engines, and more efficient vehicle accessories. The agencies also expect to see incr eased electrification of the fleet through the expanded production of st op/start, hybrid, plug-in hybrid and electric
vehicles. 13 Finally, the agencies expect that vehicl e air conditioners will continue to improve by becoming more efficient and by increasing the us e of alternative refrigerants. Many of these technologies are already available today, and EPA’s and NHTSA’s assessments are that
manufacturers will be able to meet the standards through significant efficiency improvements in these technologies as well as a significant penetr ation of these and other technologies across the fleet. We project that these potential comp liance pathways for manufacturers will result in significant benefits to consumers and to society, as quantified below. Manufacturers may also introduce new technologies that we have not considered for this rulemaking analysis, which could make possible alternative, more cost-effective paths to compliance.

As discussed further below, as with the standards for MYs 2012-2016, the agencies believe that the proposed standards would continue to preserve consumer choice, that is, the proposed standards should not affect consumers’ opp ortunity to purchase the size of vehicle that meets their needs. NHTSA and EPA are proposing to continue standards based on vehicle footprint, where smaller vehicles have relatively more stringent standards, and larger vehicles

11 For NHTSA, this includes the requirements of the National Environmental Policy Act (NEPA).

12 There are a number of competing engine technologies, with one in particular that the agencies project will be common beyond 2016. This is the gasoline direct inject ion and downsized engines equipped with turbochargers and cooled exhaust gas recirculation, which has performance char acteristics similar to that of larger, less efficient engines. Paired with these engines, the agencies project that advanced transmissions (such as automatic and dual clutch transmissions with eight forward speeds) and higher efficiency gearboxes will provide significant improvements. Transmissions with eight or more speeds can be found in the fleet today in very limited production, and while they are expected to penetrate further by 2016, we anticipate that by 2025 these will be the dominant transmissions in new vehicle sales.

13 For example, while today less than th ree percent of annual vehicle sales are strong hybrids, plug-in hybrids and all electric vehicles, by 2025 we estimate these technologies could represent nearly 15 percent of new sales.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 13 of 768 have less stringent standards, so there shoul d not be a significant effect on the relative availability of different size vehicles in the fleet . Additionally, as with the standards for MYs 2012-2016, the agencies believe that the proposed standards should not have a negative effect on vehicle safety.

We note that as part of this rulemaking, given the long time frame at issue in setting standards for MY 2022-2025 light-duty vehicles, the agencies are discussing a comprehensive mid-term evaluation and agency decision-making process. NHTSA has a statutory obligation to conduct a separate de novo rulemaking in order to establish final standards for vehicles for the 2022-2025 model years, and EPA is proposing regulations that address the mid-term evaluation The mid-term evaluation will assess the appropriateness of the MY 2022-2025 standards considered in this rulemaking, based on an updated assessment of all the factors considered in setting the standards and the impacts of those fact ors on the manufacturers’ ability to comply. NHTSA and EPA fully expect to conduct this mid-term evaluation in coordination with the California Air Resources Board, given our inte rest in a maintaining a National Program to address GHGs and fuel economy. Further discussion of the mid-term evaluation is found later in this section, as well as in Sections III and IV.

Based on the agencies’ analysis, the National Program standards being proposed are currently projected to reduce GHGs by approxim ately 2 billion metric to ns and save 4 billion
barrels of oil over the lifetime of MYs 2017-2 025 vehicles relative to the MY 2016 standard

curves 14 already in place. The average cost for a MY 2025 vehicle to meet the standards is estimated to be about $2,000 compared to a vehicle that would meet the level of the MY 2016 standards in MY 2025. However, fuel savings for consumers are expected to more than offset the higher vehicle costs. The typical driver woul d save a total of $6,600 in fuel costs over the lifetime of a MY 2025 vehicle and, even after accounting for the higher vehicle cost, consumers would save a net $4,400 in fuel costs over the vehicle’s lifetime. Further, consumers who buy new vehicles with cash would save enough in lower fuel costs after about 4 years of owning a MY 2025 vehicle to offset the higher upfront ve hicle costs, while consumers who buy with a 5- year loan would save more each month on fuel than they would spend on the higher monthly loan payment.

Continuing the National Program has both energy security and climate change benefits. Climate change is widely viewed as a significant long-term threat to the global environment. EPA has found that elevated atmospheric con centrations of six greenhouse gases– carbon dioxide, methane, nitrous oxide, hydrofluorocarbons, perflurocarbons, and sulfur hexafluoride -- taken in combination endanger both the public health and the public welfare of current and future generations. EPA further found that the combined emissions of these greenhouse gases from new motor vehicles and new motor vehicle engines contribute to the greenhouse gas air pollution

14 The calculation of GHG reductions and oil savings is rela tive to a future in which the MY 2016 standards remain in place for MYs 2017-2025 and manufacturer s comply on average at those levels.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 14 of 768 that endangers public health and welfare. 74 FR 66496 (Dec. 15, 2009). As summarized in EPA's Endangerment and Cause or Contribute Findings under Section 202(a) of the Clear Air Act, anthropogenic emissions of GHGs are very likely (90 to 99 percent probability) the cause of most of the observed global warming over the last 50 years. 15 Mobile sources emitted 31 percent of all U.S. GHGs in 2007 (transportation sources, which do not include certain off-highway sources, account for 28 percent) and have been the fastest-growing source of U.S. GHGs since

1990. 16 Mobile sources addressed in the endang erment and contribution findings under CAA section 202(a)--light-duty vehicles, heavy-duty trucks, buses, and motorcycles--accounted for 23 percent of all U.S. GHG in 2007. 17 Light-duty vehicles emit CO 2 , methane, nitrous oxide, and hydrofluorocarbons and are responsible for nearly 60 percent of all mobile source GHGs and over 70 percent of Section 202(a) mobile source GHGs. For light-duty vehicles in 2007, CO 2 emissions represent about 94 percent of all greenhouse emissions (including HFCs), and the CO 2 emissions measured over the EPA tests used for fuel economy compliance represent about 90 percent of total light-du ty vehicle GHG emissions. 18,19

Improving our energy and national security by reducing our dependence on foreign oil has been a national objective since the first oil price shocks in the 1970s. Net petroleum imports accounted for approximately 51 percent of U.S. petroleum consumption in 2009. 20 World crude oil production is highly concentrated, exacerbating the risks of supply disruptions and price
shocks as the recent unrest in North Afri ca and the Persian Gulf highlights . Recent tight global oil markets led to prices over $100 per barrel, with gasoline reaching as high as $4 per gallon in many parts of the U.S., causing financial hardship for many families and businesses. The export of U.S. assets for oil imports continues to be an important component of the historically unprecedented U.S. trade deficits. Transportation accounted for about 71 percent of U.S. petroleum consumption in 2009. 21 Light-duty vehicles account for about 60 percent of

15 74 FR 66,496, - 66,518, December 18, 2009; “Technical Support Document for Endangerment and Cause orContribute Findings for Greenhouse Gases Under Section 202(a) of the Clean Air Act” Docket: EPA-HQ-OAR2009-0472-11292, http://epa.gov/climatechange/endangerment.html.

16 U.S. Environmental Protection Agency. 2009. Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-
2007. EPA 430-R-09-004. Available at http://epa.gov/climatechange/emissions/downloads09/GHG2007entire_report-508.pdf

17 U.S. EPA. 2009 Technical Support Document for Endangerment and Cause or Contribute Findings for Greenhouse Gases under Section 202(a) of the Clean Air Act. Washington, DC. pp. 180-194. Available at http://epa.gov/climatechange/endangerment/downloads/Endangerment%20TSD.pdf

18 U.S. Environmental Protection Agency. 2009. Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-
2007. EPA 430-R-09-004. Available at http://epa.gov/climatechange/emissions/downloads09/GHG2007entire_report-508.pdf

19 U.S. Environmental Protection Agency. RIA, Chapter 2

20 Energy Information Administration, “How dependent are we on foreign oil?” Available at http://www.eia.gov/energy_in_brief/foreign_oil_de pendence.cfm (last accessed August 28, 2011).

21 Energy Information Administration, Annual Energy Outlook 2011, “Oil/Liquids.” Available at http://www.eia.gov/forecasts/aeo/MT_liquidfuels.cfm (last accessed August 28, 2011).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 15 of 768 transportation oil use, which means that they alone account for about 40 percent of all U.S. oil consumption.

2. Additional Background on the National Program

Following the successful adoption of a National Program of federal standards for greenhouse gas emissions (GHG) and fuel economy standards for model years (MY) 2012-2016 light duty vehicles, President Obama issued a Memorandum on May 21, 2010 requesting that the National Highway Traffic Safety Administration (NHTSA), on behalf of the Department of Transportation, and the Environmental Protection Agency (EPA) work together to develop a national program for model years 2017-2025. Specifically, he requested that the agencies develop “ ...a coordinated national program under the CAA [Clean Air Act] and the EISA [Energy Independence and Security Act of 20 07] to improve fuel efficiency and to reduce greenhouse gas emissions of passenger cars and light-duty trucks of model years 2017-2025.” 22
The President recognized that our country could take a leadership role in addressing the global challenges of improving energy security and re ducing greenhouse gas pollution, stating that “America has the opportunity to lead the world in the development of a new generation of clean cars and trucks through innovat ive technologies and manufactur ing that will spur economic growth and create high-quality domestic jobs, enhance our energy secu rity, and improve our

environment.”

The Presidential Memorandum stated “ The program should also seek to achieve substantial annual progress in reducing trans portation sector greenhouse gas emissions and fossil fuel consumption, consistent with my Admi nistration's overall energy and climate security goals, through the increased domestic production and use of existing, advanced, and emerging technologies, and should strengthen the industry and enhance job creation in the United States.” Among other things, the agencies were tasked with researching and then developing standards for MYs 2017 through 2025 that would be appropriate and consistent with EPA’s and NHTSA’s respective statutory authorities, in order to contin ue to guide the automotive sector along the road to reducing its fuel consumption and GHG emissions, thereby ensuring corresponding energy security and environmental benefits. During the public comment period for the MY 2012-2016 proposed rulemaking, many stakeholders encouraged NHTSA and EPA to begin working toward standards for MY 2017 and beyond in order to maintain a single nationwide program. Several major automobile manufacturers and CARB sent letters to EPA and NHTSA in support of a

22 The Presidential Memorandum is found at: http ://www.whitehouse.gov/the-pre ss-office/presidentialmemorandum-regarding-fuel-efficiency-standards. For the reader’s reference, the President also requested the Administrators of EPA and NHTSA to issue joint rules und er the CAA and EISA to establish fuel efficiency and greenhouse gas emissions standards for commercial medium -and heavy-duty on-highway vehicles and work trucks beginning with the 2014 model year. The agencies recentl y promulgated final GHG and fuel efficiency standards for heavy duty vehicles and engines for MYs 2014-2018. 76 FR 57106 (September 15, 2011).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 16 of 768 MYs 2017 to 2025 rulemaking initiative as outlined in the President’s May 21, 2010

announcement. 23

As a first step in responding to the President’s request, the agencies collaborated with CARB to prepare an Interim Joint Technical Asse ssment Report (TAR) to inform the rulemaking process and provide an initial technical assessment for that work. NHTSA, EPA, and CARB issued the joint Technical Assessment Report cons istent with Section 2(a) of the Presidential
Memorandum. 24 In developing the technical assessment, EPA, NHTSA, and CARB held numerous meetings with a wide variety of stak eholders including the automobile original equipment manufacturers (OEMs), automotive supp liers, non-governmental organizations, states and local governments, infrastructure providers, and labor unions. The Interim Joint TAR provided an overview of key stakeholder input, ad dressed other topics noted in the Presidential memorandum, and EPA’s and NHTSA’ s initial assessment of benefi ts and costs of a range of stringencies of future standards.

In accordance with the Presidential Memorandum, NHTSA and EPA also issued a joint Notice of Intent to Issue a Proposed Rulemaking (NOI). 25 The September 2010 NOI highlighted the results of the analyses contained in the Interim Joint TAR, provided an overview of key program design elements, and announced plans for initiating the joint rulemaking to improve the fuel efficiency and reduce the GHG emissions of passenger cars and light-duty trucks built in MYs 2017-2025. The agencies requested comments on the September NOI and accompanying
Interim Joint TAR.

The Interim Joint TAR contained an initial fleet -wide analysis of improvements in overall average GHG emissions and equivalent fuel economy levels. For purposes of an initial assessment, this range was intended to represent a reasonably broad range of stringency increases for potential future GHG emissions standards, and was also consistent with the increases suggested by CARB in its letter of commitment in response to the President’s memorandum. 26,27

23 These letters of support in response to the May 21, 2010 Presidential Memorandum are available at http://www.epa.gov/otaq/climate/regulations.htm#prez and http://www.nhtsa.gov/Laws+&+Regulations/CAFE+- +Fuel+Economy/Stakeholder+Commitment+Le tters (last accessed August 28, 2011).

24 This Interim Joint Technical Assessment Report (TAR) is available at http://www.epa.gov/otaq/climate/re gulations/ldv-ghg-tar.pdf and http://www.nhtsa.gov/staticfiles/rulemaking/ pdf/cafe/2017+CAFE-GHG_Interim_TAR2.pdf Section 2(a) of the Presidential Memorandum requested that EPA and NHTSA “Work with the State of California to develop by September 1, 2010, a technical assessment to in form the rulemaking process, reflecting input from an array of stakeholders on relevant factors, including viable technologies, costs, benefits, lead time to develop and deploy new and emerging technologies, incentives and othe r flexibilities to encourage development and deployment of new and emerging technologies, impacts on jobs and the automotive manufacturing base in the United States, and infrastructure for advanced vehicle technologies.”

25 75 FR 62739, October 13, 2010.

26 75 FR at 62744-45

27 Statement of the California Air Resources Board Regard ing Future Passenger Vehicle Greenhouse Gas Emissions Standards, California Air Resources Board, May 21, 2010. Available at: http://www.epa.gov/otaq/climate/regulations.htmSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 17 of 768 The TAR evaluated a range of potential stringency scenarios through model year 2025, representing a 3, 4, 5, and 6 percent per year estimated decrease in GHG levels from a model year 2016 fleet-wide average of 250 gram/mile (g/mi). Thus, the model year 2025 scenarios analyzed in the Interim Joint TAR ranged from 190 g/mi on an estimated fleet-wide average (calculated to be equivalent to 47 miles per gallon, mpg, if all improvements were made with fuel economy-improving technologies) under the 3 percent per year reduction scenario, to 143 g/mi on an estimated fleet-wide average (calculated to be equivalent to 62 mpg, if all improvements were made with fuel economy-improving technologies) under the 6 percent per year scenario. 28 For each of these scenarios, the TAR also evaluated four pre-defined “technological pathways” by which these levels could be attained. These pathways were meant to represent ways that the industry as a whole could increase fuel economy and reduce greenhouse gas emissions, and did not represent ways that individual manufacturers would be required to or necessarily would employ in responding to future standards. Each defined technology pathway emphasized a different mix of advanced technologies, by assuming various degrees of penetration of advanced gasoline technologies, mass reduction, hybrid electric vehicles (HEVs), plug-in hybrids (PHE Vs), and electric vehicles (EVs).

Manufacturers and others commented extensivel y on the NOI and Interim Joint TAR on a variety of topics, including the stringency of the standards, program design elements, the effect of potential standards on vehicle safety, an d the TAR’s discussion of technology costs, effectiveness, and feasibility. In response, the agencies and CARB spent the next several months continuing to gather information from the industry and others in response to the agencies’ initial analytical efforts. To aid the public’s understanding of some of the key issues facing the agencies in developing the proposed rule , EPA and NHTSA also issued a follow-on Supplemental NOI in November 2010. 29 The Supplemental NOI highlighted many of the key comments the agencies received in response to the September NOI and Interim Joint TAR, and summarized some of the key them es from the comments and the additional stakeholder meetings. We note, as highlighted in the November Supplemental NOI, that there continued to be widespread stakeholder support for continuing the National Program for improved fuel economy and greenhouse gas standards for model years 2017-2025. The November Supplemental NOI also provided an overview of many of the key technical analyses the agencies planned in support the proposed rule.

After issuing the November 2010 Supplemental NOI, EPA, NHTSA and CARB continued studies on technology cost and effectiveness and more in-depth and comprehensive analysis of the issues. In addition to this work, the agencies continued meeting with

28 These levels correspond to on-road values of 37 to 50 mpg, respectively, recognizing that on-road fuel economy tends to be about 20 percent worse than calculated mpg valu es based on the CAFE test cycle. We note, however, that because these mpg values are translated from CO 2 e values that include reductions in hydrofluorocarbon (HFC) leakage due to use of advanced refrigerants and leak age improvements, therefore these numbers are not as representative of either CAFE te st cycle or real-world mpg.

29 75 FR 76337, December 8, 2010Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 18 of 768 stakeholders, including with manufacturers, ma nufacturer organizations , automotive suppliers, a labor union, environmental groups, consumer inte rest groups, and investment organizations. As discussed above, on July 29, 2011 President Obama announced plans for these proposed rules and NHTSA and EPA issued a Supplemental Notice of Intent (NOI) outlining the agencies’ plans for proposing the MY 2017-2025 standards and program.

3. California’s Greenhouse Gas Program

In 2004, the California Air Resources Board (CARB) approved standards for new lightduty vehicles, regulating the emission of CO 2 and other GHGs. Thirteen states and the District of Columbia, comprising approximately 40 percent of the light-duty vehicle market, adopted California’s standards. On June 30, 2009, EPA granted California’s request for a waiver of preemption under the CAA with respect to these standards. 30 The granting of the waiver permits California and the other states to proceed with implementing the California emission standards for MYs 2009-2016. After EPA and NHTSA issued their MYs 2012-2016 standards, CARB revised its program such that compliance with the EPA greenhouse gas st andards will be deemed to be compliance with California’s GHG standards. 31 This facilitates the National Program by allowing manufacturers to meet all of the standards with a single national fleet.

As requested by the President and in th e interest of maximizing regulatory harmonization, NHTSA and EPA have worked closely with CARB throughout the development of this proposal. CARB is releasing a propos al for MY 2017-2025 GHG emissions standards which are consistent with the standards being proposed by EPA and NHTSA. CARB recognizes the benefit for the country of continuing the National Program and plans an approach similar to
the one taken for MYs 2012-2016. CARB has committed to propose to revise its GHG emissions standards for MY 2017 and later such that compliance with EPA GHG emissions standards shall be deemed compliance with the Ca lifornia GHG emissions standards, as long as EPA’s final GHG standards are substantially as described in the July 2011 Supplemental NOI. 32

4. Stakeholder Engagement

On July 29, 2011, President Obama announced with the support of thirteen major automakers for the next phase in the Administration’s national vehicle program, increasing fuel economy and reducing GHG emissions for passenger cars and light trucks built in MYs 2017-

30 74 FR 32744 (July 8, 2009). See also Chamber of Commerce v. EPA , 642 F.3d 192 (D.C. Cir. 2011) (dismissing petitions for review challenging EPA’s grant of the waiver).

31 See “California Exhaust Emission Standards and Test Pro cedures for 2001 and Subsequent Model Passenger Cars, Light-Duty Trucks, and Medium-Duty Vehicles as approved by OAL,” March 29, 2010. Available at http://www.arb.ca.gov/regact/2010/ghgpv10/oa ltp.pdf (last accessed August 28, 2011).

32 See State of California July 28, 2011 letter availa ble at: http://www.epa.gov/otaq/climate/regulations.htmSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 19 of 768 2025. 33 The President was joined by Ford, GM, Chrysler, BMW, Honda, Hyundai, Jaguar/Land Rover, Kia, Mazda, Mitsubishi, Nissan, Toyota and Volvo, which together account for over 90 percent of all vehicles sold in the United Stat es. The California Air Resources Board (CARB), the United Auto Workers (UAW) and a number of environmental and consumer groups, also were integral to developing this agreement.

On the same day as the President’s announcement, the agencies released a second SNOI (published in the Federal Register on August 9, 2011) generally describing the joint proposal that the EPA and NHTSA expected to issue to establish the National Program for model years 2017– 2025, and which is set forth in this NPRM. Th e agencies explained that the proposal would be developed based on extensive technical analyses, an examination of the factors required under their respective statutes and discussions with and input from individual motor vehicle manufacturers and other stakeholders (including ce rtain members of the United States Congress). The input of stakeholders, which is encouraged by Executive Order 13563, has been invaluable to the agencies in developing today’s NPRM.

For background, as discussed above, after publishing the Supplemental NOI on December 8, 2010 (the December 8 SNOI), NHTSA, EPA and CARB continued studies and conducted more in-depth and comprehensive rulemaking analyses related to technology cost and effectiveness, technological feasibility, reas onable timing for manufacturers to implement technologies, and economic factors, and other re levant considerations. In addition to this ongoing and more in-depth work, the agencies continued meeting with stakeholders and received additional input and feedback to help inform th e rulemaking. Meetings were held with and
relevant information was obtained from manufactu rers, manufacturer organizations, suppliers, a labor union, environmental groups, consumer inte rest groups, and investment organizations.

This section summarizes NHTSA stakeholde r engagement between December 2010 and July 29, 2011, the date on which President Obama announced the agencies’ plans for proposing standards for MY2017-2025, and the support of thirteen major automakers and other stakeholders for these plans. A complete list of stakeholder meeting dates and participants can
be found in a memorandum to the docket. 34 Information that the agencies presented to stakeholders is posted in the docket and refere nced in multiple places in this section.

The agencies’ engagement with the large an d diverse group of stakeholders described above between December 2010 and July 29, 2011 shared the single aim of ensuring that the agencies possessed the most complete and compre hensive set of information possible to inform the proposed rulemaking.

33 The President’s remarks are available at http://www.whitehouse.gov/the-press-office/2011/07/29/remarkspresident-fuel-efficiency-standards; s ee also http://www.nhtsa.gov/fuel-eco nomy for more information from the agency about the announcement.

34 [Memo Name], at NHTSA-2010-0131.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 20 of 768 Throughout this period, the stakeholders repeated many of the broad concerns and suggestions described in the TAR, NOI, and December 8 SNOI. For example, stakeholders uniformly expressed interest in maintaining a harmonized and coordinated national program that would be supported by CARB and allow auto make rs to build one fleet and preserve consumer
choice. The stakeholders also raised concerns about potential stringency levels, consumer acceptance of some advanced technologies and th e potential structure of compliance flexibilities available under EPCA (as amended by EISA) an d the CAA. In addition, most of the
stakeholders wanted to discuss issues concerni ng technology availability, cost and effectiveness and economic practicability. The auto manufacturers, in particular, sought to provide the agencies with a better understanding of their re spective strategies (and associated costs) for improving fuel economy while satisfying consumer demand in the coming years. Additionally, some stakeholders expressed concern about potential safety impacts associated with the standards, consumer costs and consumer acceptan ce, and potential disparate treatment of cars
and trucks. Some stakeholders also stressed th e importance of investing in infrastructure to support more widespread deployment of alternativ e vehicles and fuels. Many stakeholders also asked the agencies to acknowledge prevailing economic uncertainties in developing proposed standards. In addition, many stakeholders shared on the number of years to be covered by the program and what they considered to be important features of a mid-term review of any standards set or proposed for MY 2022-2025. In all of these meetings, NHTSA and EPA sought
additional data and information from the stakeholde rs that would allow them to refine their initial analyses and determine proposed standards that are consistent with the agencies’ respective statutory and regulatory requirements. The gene ral issues raised by those stakeholders are addressed in the sections of this NPRM discussing the topics to which the issues pertain ( e.g. , the form of the standards, technology cost and effec tiveness, safety impacts, impact on U.S. vehicle sales and other economic considerations, costs and benefits).

The first stage of the meetings occurred between December 2010 and June 20, 2011. These meetings covered topics that were generally similar to the meetings th at were held prior to the publication of the December 8 Supplemental NOI and that were summarized in the Supplemental NOI. The manufacturers provided the agencies with additional information related to their product plans for vehicle models an d fuel efficiency improving technologies and associated cost estimates. Detailed product plans generally extend only five or six model years into the future. Manufacturers also provided estimates of the amount of improvement in CAFE
and CO 2 emissions they could reasonably achieve in model MYs 2017-2025; feedback on the shape of MY 2012-2016 regulatory stringency cu rves and curve cut points, regulatory program flexibilities; recommendations for and on the structure of one or more mid-term reviews of the later model year standards; estimates of the cost, effectiveness and availability of some fuel efficiency improving technologies; and feedback on some of the cost and effectiveness assumptions used in the TAR analysis. In addition, manufacturers provided input on manufacturer experience with consumer acceptance of some advanced technologies and raisedSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 21 of 768 concerns over consumer acceptance if higher penetration of these technologies were needed in the future, consumer’s willingness to pay for improved fuel economy, and ideas on enablers and incentives that would increase consumer acceptance. Many manufacturers stated that technology is available to significantly improve fuel economy and CO 2 emissions; however, they maintained that the biggest challenges relate to the cost of the technologies, consumer willingness to pay and
consumer acceptance.

During this first phase NHTSA and EPA conti nued to meet with other stakeholders, who provided their own perspectives on issues of importance to them. They also provided data to the
extent available to them. Information obtained from stakeholders during this phase is contained
in the docket.

The second stage of meetings occurred between June 21, 2011 and July 14, 2011, during which time EPA, NHTSA, CARB and several Wh ite House Offices kicked-off an intensive series of meetings, primarily with manufacturers, to share tentative regulatory concepts developed by the agencies, which included concept stringency curves and program flexibilities based on the analyses completed by the agencies as of June 21, 35 and requested feedback. 36 In particular, the agencies requested that the manufacturers provide detailed and reliable information on how they might comply with the concepts and, if they projected they could not comply, information supporting their belief that they would be unable to comply. Additionally, EPA and NHTSA sought detailed input from the manufacturers regarding potential changes to the concept stringency levels and program flexibilities available under EPA’s and NHTSA’s respective authority that might reduce the cost s of compliance. In addition, manufacturers provided input related to consumer acceptance and adoption of some advanced technologies and program costs based on their independent assessments or information previously submitted to the agencies.

In these second stage meetings, the agencies received considerable input from the manufacturers. The agencies carefully considered the manufacturer information along with information from the agencies’ independent analyses. The agencies used all available information to refine their assessment of the range of program concept stringencies and provisions that the agencies determined were consistent with their statutory mandates.

The third stage of meetings occurred between July 15, 2011 and July 28, 2011. During this time period the agencies continued to refine concept stringencies and compliance flexibilities

35 The agencies consider a range of standards that may sa tisfy applicable legal criteria, taking into account the complete record before them The initia l concepts shared with stakeholders we re within the range the agencies were considering, based on the information then available to the agencies.

36 The agencies prepared materials prior to the meetings to present to the manufacturers which are included in a memo to docket. [add reference]Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 22 of 768 based on further consideration of the informa tion available to them. They also met with manufacturers who expressed ongoing interest in engaging with the agencies. 37

Throughout all three stages, EPA and NHTSA continued to engage other stakeholders to ensure that the agencies were obtaining the most comprehensive and reliable information possible to guide the agencies in developing proposed standards for MY 2017-2025. Many of these stakeholders reiterated comments previous ly presented to the agencies. For instance, environmental organizations consistently stat ed that stringent standards are technically achievable and critical to important national interests, such as improving energy independence, reducing climate change, and enabling the domestic automobile industry to remain competitive in the global market. Labor interests stressed the need to carefully consider economic impacts and the opportunity to create and support new jobs, and consumer advocates emphasized the economic and practical benefits to consumers of improved fuel economy and the need to

preserve consumer c hoice. In addition, a number of stakehol ders stated that the standards under development should not have an adverse impact on safety.

On July 29, 2011, EPA and NHTSA the agencies issued a new SNOI with concept stringency curves and program provisions based on refined analyses and further consideration of the record before the agencies. The agencies have received letters of support for the concepts laid out in the SNOI from BMW, Chrysler, Ford , General Motors, Globa l Automakers, Honda, Hyundai, Jaguar Land Rover, Kia, Mazda, Mi tsubishi, Nissan, Toyota, Volvo and CARB. Numerous other stakeholders, including labor, environmental and consumer groups, have expressed their support for the agencies’ plans to move forward.

The agencies have considered all of this stakeholder input in developing this proposal, and look forward to continuing the productive dialogue through the comment period following this proposal.

B. Summary of the Proposed 2017-2025 National Program

1. Joint Analytical Approach

This proposed rulemaking continues the collaborative analytical effort between NHTSA and EPA, which began with the MYs 2012-2016 rulemaking. NHTSA and EPA have worked together, and in close coordination with CARB, on nearly every aspect of the technical analysis supporting these joint proposed rules. The results of this collaboration are reflected in the elements of the respective NHTSA and EPA proposed rules, as well as in the analytical work
contained in the Draft Joint NHTSA and EPA T echnical Support Document (Joint TSD). The agencies have continued to develop and refine supporting analyses since issuing the NOI and Interim Joint TAR last September. The Joint TSD, in particular, describes important details of

37 The agencies prepared materials prior to the meetings to present to the manufacturers which are included in a memo to docket. [add reference]Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 23 of 768 the analytical work that are common, as well as highlighting any key differences in approach. The joint analyses include the build-up of the baseline and reference fleets, the derivation of the shape of the footprint-based attribute curves that define the agencies’ respective standards, a detailed description of the estimated costs and eff ectiveness of the technologies that are available to vehicle manufacturers, the economic inputs used to calculate the costs and benefits of the proposed rules, a description of air conditioner and other off-cycle technologies, and the agencies’ assessment of the effects of the proposed standards on vehicle safety. This comprehensive joint analytical approach has provided a sound and consistent technical basis for both agencies in developing their proposed standards, which are summarized in the sections
below.

2. Level of the Standards

EPA and NHTSA are each proposing two separate sets of standards, each under its respective statutory authorities. Both the proposed CO 2 and CAFE standards for passenger cars and light trucks would be footprint-based, simila r to the standards currently in effect through model year 2016, and would become more stringent on average in each model year from 2017 through 2025. The basis for measuring performance relative to standards would continue to be based predominantly on the EPA city and highway test cycles (2-cycle test). However, EPA is proposing optional air conditioning and off-cycle credits for the GHG program and adjustments to calculated fuel economy for the CAFE programs that would be based on test procedures other than the 2-cycle tests.

EPA is proposing standards that are projected to require, on an average industry fleet wide basis, 163 grams/mile of CO 2 in model year 2025. This is projected to be achieved through improvements in fuel efficiency with some additional reductions achieved through reductions in

non-CO 2 GHG emissions from reduced AC system leakage and the use of lower global warming potential (GWP) refrigerants. The level of 163 grams/mile CO 2 would be equivalent on a mpg basis to 54.5 mpg, if this level was achieved solely through improvements in fuel efficiency. 38

For passenger cars, the CO 2 compliance values associated with the footprint curves would be reduced on average by 5 percent per year from the model year 2016 projected passenger car industry-wide compliance level through model year 2025. In recognition ofmanufacturers’ unique challenges in improving the fuel economy and GHG emissions of fullsize pickup trucks as we transition from the MY 2016 standards to MY 2017 and later, while preserving the utility (e.g., to wing and payload capabilities) of those vehicles, EPA is proposing a lower annual rate of improvement for light-duty trucks in the early years of the program. For light-duty trucks, the proposed average annual rate of CO 2 emissions reduction in model years 2017 through 2021 is 3.5 percent per year. EPA is also proposing to change the slopes of the

38 Real-world CO 2 is typically 25 percent higher and real-world fuel economy is typically 20 percent lower than the CO2 and CAFE values discussed here. The reference to CO 2 here refers to CO 2 equivalent reductions, as this included some degree of reductions in greenhouse gases other than CO 2 , as one part of the AC related reductions.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 24 of 768 CO 2 -footprint curves for light-duty trucks from those in the 2012-2016 rule, in a manner that effectively means that the annual rate of impr ovement for smaller light-duty trucks in model years 2017 through 2021 would be higher than 3.5 percent, and the annual rate of improvement for larger light-duty trucks over the same time period would be lower than 3.5 percent. For model years 2022 through 2025, EPA is proposing an average annual rate of CO 2 emissions reduction for light-duty trucks of 5 percent per year.

NHTSA is proposing two phases of passenger car and light truck standards in this NPRM. The first phase runs from MYs 2017-2021, with proposed standards that are projected to require, on an average industry fleet wide basis, 40.9 mpg in MY 2021. For passenger cars, the annual increase in the stringency of the target curves between model years 2017 to 2021 is expected to average 4.1 percent. In recognition of manufacturers’ unique challenges in improving the fuel economy and GHG emissions of full-size pickup trucks as we transition from the MY 2016 standards to MY 2017 and later, wh ile preserving the utility (e.g., towing and payload capabilities) of those vehicles, NHTSA is also proposing a slower annual rate of improvement for light trucks in the first phase of the program. For light trucks, the proposed annual increase in the stringency of the target curves in model years 2017 through 2021 would be 2.9 percent per year. NHTSA is proposing to change the slopes of the fuel economy footprint curves for light trucks from those in the MYs 2012-2016 final rule, which would effectively make the annual rate of improvement for smaller light trucks in MYs 2017-2021 higher than 2.9 percent, and the annual rate of improvement for larger light trucks over that time period lower than 2.9 percent.

The second phase of the CAFE program runs from MYs 2022-2025 and represents
conditional 39 proposed standards that are projected to require, on an average industry fleet wide basis, 49.6 mpg in model year 2025. For passenger cars, the annual increase in the stringency of the target curves between model years 2022 and 2025 is expected to average 4.3 percent, and for light trucks, the annual increase during those model years is expected to average 4.7 percent. For the first time, NHTSA is proposing to increase the stringency of standards by the amount (in mpg terms) that industry is expected to improve air conditioning system efficiency, and EPA is proposing, under EPCA, to allow manufacturers to include air conditioning system efficiency improvements in the calculation of fuel economy for CAFE compliance. NHTSA notes that the proposed rates of increase in stringency for CAFE standards are lower than EPA’s proposed rates of increase in stringency for GHG standards. As in the MYs 2012-2016 rulemaking, this is for purposes of harmonization and in reflection of seve ral statutory constraints in EPCA/EISA. As a primary example, NHTSA’s proposed standards, unlik e EPA’s, do not reflect the inclusion of air conditioning system refrigerant and leakage impr ovements, but EPA’s proposed standards would

39 By ”conditional,” NHTSA means to say that the proposed standards for MYs 2022-2025 represent the agency’s current best estimate of what levels of stringency would be maximum feasible in those model years, but in order for the standards for those model years to be legally reviewab le a subsequent rulemaking must be undertaken by the agency at a later time. See Section IV for more information.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 25 of 768 allow consideration of such A/C refrigerant im provements which reduce GHGs but do not affect fuel economy.

As with the MYs 2012-2016 standards, NHTSA and EPA’s proposed MYs 2017-2025 passenger car and light truck standards are expressed as mathematical functions depending on vehicle footprint. 40 Footprint is one measure of vehicle size, and is determined by multiplying the vehicle’s wheelbase by the vehicle’s average track width. The standards that must be met by each manufacturer's fleet would be determined by computing the production-weighted average of the targets applicable to each of the manufact urer’s fleet of passenger cars and light trucks. 41
Under these footprint-based standards, the average levels required of individual manufacturers will depend, as noted above, on the mix and volume of vehicles the manufacturer produces. The values in the tables below reflect the agenci es’ projection of the corresponding average fleet
levels that will result from these attribute-base d curves given the agencies’ current assumptions about the mix of vehicles that will be sold in the model years covered by the proposed standards.

As shown in Table I-1, NHTSA’s fleet-wide required CAFE levels for passenger cars under the proposed standards are estimated to increase from 40.0 to 56.0 mpg between MY 2017 and MY 2025. Fleet-wide required CAFE levels for light trucks, in tu rn, are estimated to increase from 29.4 to 56.0 mpg. For the reader’s reference, Table I-1 also provides the estimated average fleet-wide required levels for the combined car and truck fleets, culminating in an estimated overall fleet average required CAFE level of 49.6 mpg in MY 2025. Considering these combined car and truck increases, the proposed standards together represent approximately a 4.0 percent annual rate of increase, 42 on average, relative to the MY 2016 required CAFE
levels.

Table I-1 Estimated Average Required Fleet-Wide Fuel Economy (mpg) under Proposed Footprint-Based CAFE Standards

2016
base 2017 2018 2019 2020 2021 2022 2023 2024 2025

Passenger Cars 37.8 40.0 41.4 443.0 444.7 446.6 448.8 551.0 53.5 56.0 Light Trucks 28.8 29.4 330.0 330.6 331.2 333.3 334.9 336.6 38.5 40.3 Combined Cars & Trucks 34.1 35.3 336.4 337.5 338.8 440.9 442.9 445.0 47.3 49.6

The estimated average required mpg levels for cars and trucks under the proposed standards shown in Table I-1 above include the use of A/C efficiency improvements, as

40 NHTSA is required to set attribute-based CAFE sta ndards for passenger cars and light trucks. 49 U.S.C. 32902(b)(3).

41 For CAFE calculations, a harmonic average is used.

42 This estimated average percentage increase includes the e ffect of changes in standard stringency and changes in the forecast fleet sales mix.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 26 of 768 discussed above, but do not reflect a numbe r of proposed flexibilities and credits that manufacturers could use for compliance that NHTS A cannot consider in establishing standards
based on EPCA/EISA constraints. These flexib ilities would cause the actual achieved fuel economy to be lower than the required levels in th e table above. The flexibilities and credits that NHTSA cannot consider include the ability of manufacturers to pay civil penalties rather than achieving required CAFE levels, the ability to use FFV credits, the ability to count electric vehicles for compliance, the operation of plug-in hybrid electric vehicles on electricity for compliance prior to MY 2020, and the ability to transfer and carry-forward credits. When accounting for these flexibilities and credits, NHTSA estimates that the proposed CAFE standards would lead to the following average achieved fuel economy levels, based on the projections of what each manufacturer’s fleet will comprise in each year of the program: 43

Table I-2 Estimated Average Achieved Fleet-Wide Fuel Economy (mpg) under Proposed Footprint-Based CAFE Standards

2016 base 2017 2018 2019 2020 2021 2022 2023 2024 2025

Passenger Cars 36.2 39.5 41.7 43.5 45.3 47.1 48.2 49.4 51.3 52.6 Light Trucks 27.5 29.6 30.7 32.5 33.7 35.6 36.5 37.5 38.5 39.5 Combined Cars & Trucks 32.7 35.2 36.9 38.8 40.4 42.3 43.4 44.6 46.1 47.4

NHTSA is also required by EISA to set a minimum fuel economy standard for domestically manufactured passenger cars in addition to the attribute-based passenger car standard. The minimum standard “shall be the greater of (A) 27.5 miles per gallon; or (B) 92 percent of the average fuel economy projected by the Secretary for the combined domestic and non-domestic passenger automobile fleets manufactured for sale in the United States by all manufacturers in the model year....”

Based on NHTSA’s current market forecast, the agency’s estimates of these proposed minimum standards for domestic passenger cars for MYs 2017-2025 are presented below in
Table I-3.

Table I-3 Estimated Minimum Standard for Domestically Manufactured Passenger Cars (mpg)

43 The proposed CAFE program includes incentives for full size pick-up trucks that have mild HEV or strong HEV systems, and for full size pick-up trucks that have fuel economy performance that is be tter than the target curve by more than proposed levels. To receive these incenti ves, manufacturers must produce vehicles with these technologies or performance levels at volumes that meet or exceed proposed penetration levels (percentage of full size pick-up truck volume). This incentive is described in detail in Section IV.1. The NHTSA estimates in Table I2 do not account for the reduction in estim ated average achieved fleet-wide CAFE fuel economy that would occur if manufacturers use this incentive. NHTSA has conducte d a sensitivity study that estimates the effects for manufacturers’ potential use of this fl exibility in Chapter X of the PRIA.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 27 of 768

2017 2018 2019 2020 2021 2022 2023 2024 2025
36.8 38.1 39.6 41.1 42.9 44.9 47.0 49.2 51.5

EPA is proposing GHG emissions standards, and Table I-4 provides estimates of the projected overall fleet-wide CO 2 emission compliance target levels. The values reflected in Table I-4 are those that correspond to the manufacturers’ projected CO2 compliance target levels from the car and truck footprint curves, but do not account for EPA’s projection of how manufactures will implement two of the proposed incentive pr ograms (advanced technology vehicle multipliers, and hybrid and performance-based incentives for full-size pickup trucks). EPA’s projection of fleet-wide emissions levels that do reflect these incentives is shown in Table
I-5 below.

Table I-4 Projected Fleet-Wide CO 2 Compliance Targets under the Proposed Footprint-Based CO 2 Standards (g/mi)

2016 base 2017 2018 2019 2020 2021 2022 2023 2024 2025

Passenger Cars 225 213 202 192 182 173 165 158 151 144

Light Trucks 297 295 285 277 270 250 237 225 214 203
Combined Cars and Trucks 252 44 243 232 223 213 200 190 181 172 163

As shown in Table I-4, projected fleet-wide CO 2 emission compliance targets for cars increase in stringency from 213 to 144 g/mi between MY 2017 and MY 2025. Similarly, projected fleet-wide CO 2 equivalent emission compliance targets for trucks increase in stringency from 295 to 203 g/mi. As shown, the overall fleet average CO 2 level targets are projected to increase in stringency from 243 g/mi in MY 2017 to 163 g/mi in MY 2025, which is equivalent to 54.5 mpg if all reductions were made with fuel economy improvements.

EPA anticipates that manufacturers would take advantage of proposed program credits and incentives, such as car/truck credit transfers, air conditioning credits, off-cycle credits, advanced technology vehicle multipliers, and hybrid and performance-based incentives for full size pick-up trucks. Two of these flexibi lity provisions – advanced technology vehicle multipliers and the full size pick-up hybrid/perfo rmance incentives – are expected to have an

44 The projected fleet compliance levels for 2016 are differen t for trucks and the fleet th an were projected in the 2012-2016 rule (298 and 250 g/mi respectively). That is because the standards are footprint based and the fleet projections, hence the footprint distributions, change sli ghtly with each update of our projections, as described below. In addition, the actual target levels for any mode l year will not be known until the end of that model year based on actual vehicle sales.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 28 of 768 impact on the fleet-wide emissions levels that manufacturers will actually achieve. Therefore, Table I-5 shows EPA’s projection of the achieved emission levels of the fleet for MY 2017 through 2025. The differences between the emissions levels shown in Tables I-4 and I-5 reflect the impact on stringency due to the advanced technology vehicle multipliers and the full size pick-up hybrid/performance incentives, but do not reflect car-truck trad ing, air conditioning credits, or off-cycle credits, because, while those credit provisions should help reduce manufacturers’ costs of the program, EPA believe s that they will result in real-world emission
reductions that will not affect the achieved level of emission reductions. These estimates are more fully discussed in III.B

Table I-5 Projected Fleet-Wide Achieved CO 2 -equivalent Emission Levels under the Proposed Footprint-Based CO2 Standards (g/mi)

2016 base 2017 2018 2019 2020 2021 2022 2023 2024 2025

Passenger Cars 225 215 205 194 184 174 165 158 151 144

Light Trucks 297 295 285 278 271 251 238 226 214 204 Combined Cars and Trucks 252 245 234 224 214 201 190 181 172 163.6

A more detailed description of how the agencies arrived at the year by year progression of the stringency of the proposed standards can be found in Sections III and IV of this preamble.

Both agencies also considered other alternative standards as part of their respective Regulatory Impacts Analyses that span a reasonable range of alternative stringencies both more and less stringent than the standards being proposed. EPA’s and NHTSA’s analyses of these regulatory alternatives (and explanation of why we are proposing the standards proposed and not the regulatory alternatives) are contained in Sections III and IV of this preamble, respectively, as
well as in EPA’s DRIA and NHTSA’s PRIA.

3. Form of the Standards

As noted, NHTSA and EPA are proposing to continue attribute-based standards for passenger cars and light trucks, as required by EISA and as allowed by the CAA, and continue to use vehicle footprint as the attrib ute. Footprint is defined as a vehicle’s wheelbase multiplied by its track width -- in other words, the area enclosed by the points at which the wheels meet the ground. NHTSA and EPA adopted an attribute-based approach based on vehicle footprint for MYs 2012-2016 light-duty vehicle standards. 45 The agencies continue to believe that footprint

45 NHTSA also uses the footprint attribute in its Re formed CAFE program for light trucks for model years 2008- 2011 and passenger car CAFE standards for MY 2011.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 29 of 768 is the most appropriate attribute on which to base the proposed standards, as discussed later in this notice and in Chapter 2 of the Joint TSD.

Under the footprint-based standards, the curve defines a GHG or fuel economy performance target for each separate car or truck footprint. Using the curves, each manufacturer thus will have a GHG and CAFE average standard that is unique to each of its fleets, depending on the footprints and production volumes of the ve hicle models produced by that manufacturer. A manufacturer will have separate footprint-based standards for cars and for trucks. The curves are mostly sloped, so that generally, larger vehicles ( i.e. , vehicles with larger footprints) will be subject to less stringent targets ( i.e. , higher CO 2 grams/mile targets and lower CAFE mpg targets) than smaller vehicles. This is because , generally speaking, smaller vehicles are more capable of achieving lower levels of CO 2 and higher levels of fuel economy than larger vehicles. Although a manufacturer’s fleet average standards could be estimated throughout the model year based on projected production volume of its vehicle fleet, the standards to which the manufacturer must comply will be based on its final model year production figures. A manufacturer’s calculation of their fleet averag e standards as well as their fleets’ average performance at the end of the model year will thus be based on the production-weighted average target and performance of each model in its fleet. 46

While the concept is the same, the proposed curve shapes for MYs 2017-2025 are
somewhat different from the MYs 2012-2016 foot print curves. The passenger car curves are similar in shape to the car curves for MYs 2012-2016. However, the agencies are proposing more significant changes to the light trucks curves for MYs 2017-2025 compared to the light truck curves for MYs 2012-2016. The agencies are proposing changes to the light-truck curve to increase the slope and to extend the large-footprint cutpoint over time to larger footprints, which we believe represent an appropriate balance of both technical and policy issues, as discussed in Section II below and Chapter 2 of the draft Joint TSD.

NHTSA is proposing the attribute curves below for assigning a fuel economy target level to an individual car or truck’s footprint value, for model years 2017 through 2025. These mpg values will be production weighted to determine each manu facturer’s fleet average standard for cars and trucks. Although the general model of the target curve equation is the same for each vehicle category and each year, the parameters of the curve equation differ for cars and trucks. Each parameter also changes on a model year basis, resulting in the yearly increases in stringency. Figure I-1 below illustrates the passenger car CAFE standard curves for model years 2017 through 2025 while Figure I-2 below illustrates the light truck CAFE standard curves for model years 2017 through 2025.

46 As in the MYs 2012-2016 rule, a manufacturer may have so me models that exceed their target, and some that are below their target. Compliance with a fl eet average standard is determined by comparing the fleet average standard (based on the sales weighted average of the target levels for each model) with fleet average performance (based on the sales weighted average of th e performance for each model).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 30 of 768 EPA is proposing the attribute curves shown in Figure I-3 and Figure I-4 below for assigning a CO 2 target level to an individual vehicle’s footprint value, for model years 2017 through 2025. These CO 2 values would be production weighted to determine each manufacturer’s fleet average standard for cars and trucks. As with the CAFE curves, the general form of the equation is the same for each vehicle category and each year, but the parameters of the equation differ for cars and trucks. Again, each parameter also changes on a model year basis, resulting in the yearly increases in stringency. Figure I-3 below illustrates the CO 2 car standard curves for model years 2017 through 2025 while Figure I-4 shows the CO 2 truck standard curves for model years 2017-2025.Summary of Interagency Working Comments Received on Draftrule under EO 12866 review. Subject to further policyreview.Page31of768Figure I-1 CAFE Target Curves for Passenger CarsSummary of Interagency Working Comments Received on Draftrule under EO 12866 review. Subject to further policyreview.Page32of768Figure I-2 CAFE Target Curves for Light Trucks2030405060708030 35 40 45 50 55 60 65 70 75 80

Fuel Economy Target (mpg)Footprint(sf)20252024202320222021202020192018201720162015201420132012Summary of Interagency Working Comments Received on Draftrule under EO 12866 review. Subject to further policyreview.Page33of768Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policyreview.Page34of768Figure I-3 CO2 (g/mile) Car Standards CurvesSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policyreview.Page35of768Figure I-4 CO2(g/mile) Truck Standard CurvesSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 36 of 768 NHTSA and EPA are proposing to use the same vehicle category definitions for determining which vehicles are subject to the car curve standards versus the truck curve standards as were
used for MYs 2012-2016 standards. As in the MYs 2012-2016 rulemaking, a vehicle classified as a car under the NHTSA CAFE program will al so be classified as a car under the EPA GHG program, and likewise for trucks. 47 This approach of using CAFE definitions allows the CO 2 standards and the CAFE standards to continue to be harmonized across all vehicles for the National Program.

As just explained, generally speaking, a smaller footprint vehicle will tend to have higher fuel economy and lower CO 2 emissions relative to a larger footprint vehicle when both have the same level of fuel efficiency improvement technology. Since the proposed standards apply to a manufacturer’s overall fleet, not to an individual ve hicle, if a manufacturer’s fleet is dominated by small footprint vehicles, then that fleet w ill have a higher fuel economy requirement and a
lower CO 2 requirement than a manufacturer whose fleet is dominated by large footprint vehicles. All vehicles, whether smaller or larger, must make improvements to reduce CO 2 emissions or improve fuel economy, and therefore all vehicles will be relatively more ex pensive. With this footprint-based standard appro ach, EPA and NHTSA continue to believe that the rules will not create significant incentives to produce vehicles of particular sizes, and thus there should be no significant effect on the relative availability of different vehicle sizes in the fleet due to the proposed standards, which will help to maintain consumer choice during the rulemaking timeframe. Consumers should still be able to purchase the size of vehicle that meets their needs. Table I-6 helps to illustrate the varying CO 2 emissions and fuel economy targets under the proposed standards that different vehicle sizes will have, although we emphasize again that these targets are not actual standards – the proposed standards are manufacturer-specific, rather than vehicle-specific.

Table I-6 Model Year 2025 CO 2 and Fuel Economy Targets for Various MY 2008 Vehicle Types

Vehicle

Type Example Models Example Model Footprint (sq. ft.) CO 2 Emissions Target (g/mi) Fuel Economy Target (mpg)

Example Passenger Cars Compact

car Honda Fit 40 131 67.8

Midsize

car Ford Fusion 46 147 60.5

Fullsize

car Chrysler 300 53 170 52.3

47 See 49 CFR 523 for NHTSA’s definitions for passenger car and light truck under the CAFE program.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 37 of 768 Example Light-duty Trucks

Small SUV 4WD Ford Escape 44 170 52.3

Midsize

crossover Nissan Murano 49 188 47.3

Minivan Toyota Sienna 55 209 42.5 Large pickup truck Chevy Silverado 67 252 35.3

4. Program Flexibilities for Achieving Compliance

a. CO 2 /CAFE Credits Generated Based on Fleet Average Over-Compliance

The MYs 2012-2016 rules contain several provisions which provide flexibility to manufacturers in meeting standards, many of whic h the agencies are not proposing to change for MYs 2017 and later. For example, the agencies are proposing to continue allowing manufacturers to generate credits for over-compliance with the CO 2 and CAFE standards. 48
Under the agencies’ footprint-based approach to the standards, a manufacturer’s ultimate compliance obligations are determined at the end of each model year, when production of the model year is complete. Since the fleet average standards that apply to a manufacturer’s car and truck fleets are based on the applicable footprint-based curves, a production volume-weighted fleet average requirement will be calculated for each averaging set (cars and trucks) based on the mix and volumes of the models manufactured for sale by the manufacturer. If a manufacturer’s car and/or truck fleet achieves a fleet average CO 2 /CAFE level better than the car and/or truck standards, then the manufacturer generates credits. Conversely, if the fleet average CO 2 /CAFE level does not meet the standard, the fleet would incur debits (also referred to as a shortfall). Asin the MY 2011 CAFE program under EPCA/EISA, and also in MYs 2012-2016 for the lightduty vehicle GHG and CAFE program, a manufacturer whose fleet generates credits in a given model year would have several options for using those credits, including credit carry-back, credit carry-forward, credit transfers, and credit trading.

Credit “carry-back” means that manufacturers are able to use credits to offset a deficit that had accrued in a prior model year, while credit “carry-forward” means that manufacturers can bank credits and use them toward compliance in future model years. EPCA, as amended by EISA, requires NHTSA to allow manufacturers to carry-back credits for up to three model years, and to carry-forward credits for up to five model years. EPA’s MYs 2012-2016 light duty vehicle GHG program includes the same limitati ons and EPA is proposing to continue this limitation in the MY 2017-2025 program. To facilitate the transition to the increasingly more

48 This credit flexibility is required by EPCA/EISA, see 49 U.S.C. 32903, and allowed by the CAA.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 38 of 768 stringent standards, EPA is proposing under its CAA authority a one-time CO 2 carry-forward beyond 5 years, such that any credits generate d from MY 2010 through 2016 will be able to be used any time through MY 2021. This provision would not apply to early credits generated in MY 2009. NHTSA’s program will continue the 5-year carry-forward and 3-year carry-back, as required by statute.

Credit “transfer” means the ability of manufacturers to move credits from their passenger car fleet to their light truck fleet, or vice versa. EISA required NHTSA to establish by regulation a CAFE credits transferring program, now codified at 49 CFR Part 536, to allow a manufacturer
to transfer credits between its car and truck fleet s to achieve compliance with the standards. For example, credits earned by over-compliance with a manufacturer’s car fleet average standard
could be used to offset debits incurred due to that manufacturer’s not meeting the truck fleet average standard in a given year. However, EISA imposed a cap on the amount by which a manufacturer could raise its CAFE through transf erred credits: 1 mpg for MYs 2011-2013; 1.5 mpg for MYs 2014-2017; and 2 mpg for MYs 2018 and beyond. 49 Under section 202 (a) of the CAA, in contrast, there is no statutory limitati on on car-truck credit transfers, and EPA’s GHG program allows unlimited credit transfers across a manufacturer’s car-truck fleet to meet the GHG standard. This is based on the expectatio n that this flexibility will facilitate setting appropriate GHG standards that manufacturers' can comply with in the lead time provided, and will allow the required GHG emissions reductions to be achieved in the most cost effective way. Therefore, EPA did not constrain car-truck cr edit transfers, as doing so would reduce the flexibility for lead time, and would increase cost s with no corresponding environmental benefit. EISA also prohibits the use of transferred credits to meet the minimum domestic passenger car
fleet CAFE standard. 50 These statutory limits will necessarily continue to apply to the determination of compliance with the CAFE standards.

Credit “trading” means the ability of manufactur ers to sell credits to, or purchase credits from, one another. EISA allowed NHTSA to establish by regulation a CAFE credit trading program, also now codified at 49 CFR Part 536, to allow credits to be traded between vehicle
manufacturers. EPA also allows credit tradi ng in the light-duty vehicle GHG program. These sorts of exchanges between averaging sets are typically allowed under EPA’s current mobile source emission credit programs (as well as EPA’s and NHTSA’s recently promulgated GHG and fuel efficiency standards for heavy-duty vehi cles and engines), although manufacturers have in the past seldom made such exchanges. EISA also prohibits manufacturers from using traded credits to meet the minimum domestic passenger car CAFE standard. 51

49 49 U.S.C. 32903(g)(3).

50 49 U.S.C. 32903(g)(4).

51 49 U.S.C. 32903(f)(2).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 39 of 768 b. Air Conditioning Improvement Cred its/Fuel Economy Value Increases

Air conditioning (A/C) systems contribut e to GHG emissions in two ways. Hydrofluorocarbon (HFC) refrigerants, which are powerful GHGs, can leak from the A/C system (direct A/C emissions). In addition, operation of the A/C system places an additional load on the engine which increases fuel consumption and thus results in additional CO2 tailpipe emissions (indirect A/C related emissions). In the MYs 2012-2016 program, EPA allows manufacturers to generate credits by reducing either or both types of GHG emissions related to A/C systems. The expected generation of A/C credits is accounted for in setting the level of the overall CO2 standard. For the current proposal, as with the MYs 2012-2016 program, manufacturers will be able to generate CO 2 -equivalent credits to use in complying with the CO 2 standards for improvements in air conditioning (A/C) systems, both for efficiency improvements (reduces tailpipe CO2 and improves fuel consumption) and for leakage or alterna tive, lower GWP (global warming potential) refrigerant use (reduces hydrofluorocarbon (HFC) emissions). EPA is proposing that the maximum A/C credit available fo r cars is 18.8 grams/mile CO2 and for trucks is 24.4 grams/mile CO2. The proposed test meth ods used to calculate these direct and indirect A/C credits are very similar to those of the MYs 2012-2016 program, though EPA is seeking comment on a revised idle test as well as a new test procedure.

For the first time in the current proposal , the agencies are proposing provisions that would account for improvements in air conditioner efficiency in the CAFE program. Improving A/C efficiency leads to real-world fuel econom y benefits, because as explained above, A/C operation represents an additional load on the e ngine, so more efficient A/C operation imposes less of a load and allows the vehicle to go farther on a gallon of gas. Under EPCA, EPA has authority to adopt procedures to measure fuel economy and calculate CAFE. Under this authority EPA is proposing that manufacturers c ould generate fuel consumption improvement values for purposes of CAFE compliance based on air conditioning system efficiency improvements for cars and trucks. This increase in fuel economy would be allowed up to a maximum based on 0.000563 gallon/mile for cars and 0.000810 gallon/mile for trucks. This is equivalent to the A/C efficiency CO2 credit allowed by EPA under the GHG program. The same methods would be used in the CAFE program to calculate the values for air conditioning efficiency improvements for cars and trucks as are used in EPA’s GHG program. NHTSA is including in its proposed passenger car and light truck CAFE standards an increase in stringency in each model year from 2017-2025 by the amount industry is expected to improve air conditioning system efficiency in those year s, in a manner consistent with EPA’s GHG standards. EPA is not proposing to allow generation of fuel consumption improvement values for CAFE purposes, nor is NHTSA proposing to increase stringency of the CAFE standard, for the use of A/C systems that reduce leakage or employ alternative, lower GWP refrigerant, because those changes do not improve fuel economy.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 40 of 768 c. Off- cycle Credits/Fuel Economy Value Increases

For MYs 2012-2016, EPA provided an option for manufacturers to generate credits for employing new and innovative technologies that achieve CO 2 reductions that are not reflected on current test procedures. EPA noted in the MYs 2012-2016 rulemaking that examples of such “off-cycle” technologies might include solar panels on hybrids, adaptive cruise control, and active aerodynamics, among other technologies. See generally 75 FR at 25438-39. EPA’s current program allows off-cycle credits to be generated through MY 2016.

EPA is proposing that manufacturers may con tinue to use off-cycle credits for MY 2017 and later for the GHG program. As with A/C efficiency, improving efficiency through the use of off-cycle technologies leads to real-world fuel economy benefits and allows the vehicle to go farther on a gallon of gas. Thus, under its EPCA authority EPA is proposing to allow manufacturers to generate fuel consumption improvement values for purposes of CAFE compliance based on the use of off-cycle techno logies. Increases in fuel economy under the CAFE program based on off-cycle technology will be equivalent to the off-cycle credit allowed by EPA under the GHG program, and these amounts will be determined using the same procedures and test methods as are used in EPA’s GHG program. For the reasons discussed in sections III and IV of this proposal, the ability to generate off-cycle credits and increases in fuel economy for use in compliance will not affect or change the level of the GHG or CAFE standards proposed by each agency.

Many automakers indicated that they had a strong interest in pursuing off-cycle technologies, and encouraged the agencies to refine and simplify the evaluation process to provide more certainty as to the types of technologies the agencies would approve for credit generation. For 2017 and later, EPA is proposing to expand and streamline the MYs 2012-2016 off-cycle credit provisions, including an approach by which the agencies would provide specified amounts of credit and fuel consumption improvement values for a subset of off-cycle technologies whose benefits are readily quantifiabl e. EPA is proposing a list of technologies and credit values, where sufficient data is availabl e, that manufacturers could use without going through an advance approval process that would otherwise be required to generate credits. EPA believes that our assessment of off-cycle tec hnologies and associated credit values on this proposed list is conservative, and automakers may apply for additional off-cycle credits beyond the minimum credit value if they have sufficient supporting data. Further, manufacturers may also apply for off-cycle technologies beyond those listed, again, if they have sufficient data.

In addition, EPA is providing additional detail on the process and timing for the credit/fuel consumption improvement values ap plication and approval process. EPA is proposing a timeline for the approval process, including a 60-day EPA decision process from the time a manufacturer submits a complete application. EPA is also proposing a detailed, common, step-by-step process, including a specification of the data that manufacturers must submit. ForSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 41 of 768 off-cycle technologies that ar e both not covered by the pre-approved off-cycle credit/fuel consumption improvement values list and that are not quantifiable based on the 5-cycle test cycle option provided in the 2012-2016 rulemaking, EPA is proposing to retain the public comment process from the MYs 2012-2016 rule.

d. Incentives for Electric Vehicles, Plug-in Hybrid Electric Vehicles, and Fuel Cell
Vehicles

To facilitate market penetration of the most advanced vehicle techno logies as rapidly as possible, EPA is proposing an incentive multiplier for compliance purposes for all electric vehicles (EVs), plug-in hybrid el ectric vehicles (PHEVs), and fuel cell vehicles (FCVs) sold in MYs 2017 through 2021. This multiplier ap proach means that each EV/PHEV/FCV would
count as more than one vehicle in the manufactur er’s compliance calculation. EPA is proposing that EVs and FCVs start with a multiplier value of 2.0 in MY 2017, phasing down to a value of 1.5 in MY 2021. PHEVs would start at a multiplier value of 1.6 in MY 2017 and phase down to
a value of 1.3 in MY 2021. 52 The multiplier would be 1.0 for MYs 2022-2025.

NHTSA currently interprets EPCA and EISA as precluding the agency from offering incentives for EVs, FCVs and PHEVs, except as sp ecified by statute, and thus is not proposing incentive multipliers comparable to the EPA incentive multipliers described above.

For EVs, PHEVs and FCVs, EPA is proposing to set a value of 0 g/mile for the tailpipe compliance value for EVs, PHEVs (electricity usage) and FCVs for MY 2017-2021, with no limit on the quantity of vehicles eligible for 0 g/mi tailpipe emissions accounting. For MY 2022- 2025, EPA is proposing that 0 g/mi only be allowed up to a per-company cumulative sales cap, tiered as follows: 1) 600,000 vehicles for companies that sell 300,000 EV/PHEV/FCVs in MYs 2019-2021; 2) 200,000 vehicles for all other manufacturers. EPA believes the industry-wide impact of such a tiered cap will be approximately 2 million vehicles. EPA proposes to phase-in the change in compliance value, from 0 grams per mile to net upstream accounting, for any manufacturer that might exceed its cumulativ e production cap for EV/PHEV/FCVs. EPA proposes that, through MY 2025, the compliance value for EVs, FCVs, and the electric portion of PHEVs in excess of individual automaker cumulative production caps would be one-half of the value based on net upstream accounting.

For EVs and other dedicated alternative fuel vehicles, EPA is proposing to calculate fuel economy for the CAFE program using the same methodology as in the MYs 2012-2016 rulemaking, which aligns with EP CA/EISA statutory requirements. For liquid alternative fuels,this methodology generally counts 15 percent of the volume of fuel used in determine the mpgequivalent fuel economy. For gaseous alternative fuels, the methodology generally determines a

52 The multipliers for EV/FCV would be: 2017-2019 – 2.0, 2020 - 1.75, 2021 – 1.5; for PHEV: 2017-2019 – 1.6, 2020 – 1.45, 2021 – 1.3.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 42 of 768 gasoline equivalent mpg based on the energy content of the gaseous fuel consumed using a petroleum equivalency factor (PEF), and then adjusts the fuel consumption by effectively only counting 15 percent of the actual energy consumed. For electricity, the methodology generally determines a gasoline equivalent mpg by measuring the electrical energy consumed, and then using a petroleum equivalency factor (PEF) to convert to an mpg-equivalent value. The PEF for electricity includes an adjustment that effectively only counts 15 percent of the actual energy consumed. Counting 15 percent of the volume or energy provides an incentive for alternative fuels in the CAFE program.

The methodology that EPA is proposing to use to calculate fuel economy for the CAFE program for dual fueled vehicle is discussed below in subsection I.B.7.a.

e. Incentives for “Game Changing” Technologies Performance for Full-Size Pickup Truck including Hybridization

The agencies recognize that the standards under consideration for MYs 2017-2025 will be challenging for large trucks, including full size pickup trucks. In order to incentivize the penetration into the marketplace of “game changing” technologies for these pickups, including their hybridization, EPA is proposing a CO2 credit in the GHG program and an equivalent fuel consumption improvement value in the CAFE progr am for manufacturers that employ significant quantities of hybridization on full size pickup trucks, by including a per-vehicle CO2 credit and fuel consumption improvement value available fo r mild and strong hybrid electric vehicles (HEVs). EPA would provide the incentive for the GHG program under EPA’s CAA authority and the incentive for the CAFE program unde r EPA’s EPCA authority. EPA’s GHG and NHTSA’s CAFE proposed standards are set at levels that take into account this flexibility as an incentive for the introduction of advanced technology. This provides the opportunity to begin to transform the most challenging category of vehicl es in terms of the penetration of advanced technologies, which, if successful at incentivizing these “game changing technologies,” should allow additional opportunities to successfully achiev e the higher levels of truck stringencies in

MYs 2022-2025.

EPA is proposing that access to this credit and fuel consumption improvement value be conditioned on a minimum penetration of the tec hnology in a manufacturer’s full size pickup truck fleet, and is proposing criteria for a full size pickup truck ( e.g. , minimum bed size and minimum towing or payload capability). EPA is pr oposing that mild HEV pickup trucks would be eligible for a per vehicle credit of 10 g/mi 53 during MYs 2017-2021 if the technology is used on a minimum percentage of a company’s full size pickups, beginning with at least 30% of a company’s full size pickup production in 2017 and ramping up to at least 80% in MY 2021. Strong HEV pickup trucks would be eligible for a 20 g/mi per 54 vehicle credit during MYs 2017-

53 0.001125 gallon/mile.

54 0.00225 gallon/mileSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 43 of 768 2025 if the technology is used on at least 10% of the company’s full size pickups. These volume thresholds are being proposed in order to encour age rapid penetration of these technologies in this vehicle segment. EPA and NHTSA are proposing specific definitions of mild and strong HEV pickup trucks.

In addition to the specific hybridization credits, EPA is also proposing a performancebased incentive CO 2 emissions credit and equivalent fuel consumption improvement value for full size pickup trucks that achieve a significant CO 2 reduction below/fuel economy improvement above the applicable target. This would be available for vehicles achieving significant CO 2 reductions/fuel economy improvements through the use of technologies other than hybrid drive systems. EPA is proposing that eligible pickup trucks achieving 15 percent below their applicable CO2 target would receive a 10 g/mi credit, and those achieving 20 percent below their target would receive a 20 g/mi cred it. The 10 g/ mi performance-based credit would be available for MYs 2017 to 2021 and a vehicle meeting the requirements would receive the
credit until MY 2021 unless its CO 2 level increases. The 20 g/mi performance-based credit would be available for a maximum of 5 years within the model years of 2017 to 2025, provided the CO2 level does not increase for those vehicles earning the credit. The credits would begin in the MYof the eligible vehicle’s introduction, and could not extend past MY 2021 for the 10 g/mi credit and MY 2025 for the 20 g/mi credit.

To avoid double-counting, the same vehi cle would not receive credit under both the HEV and the performance based approaches.

5. Mid-Term Evaluation

Given the long time frame at issue in se tting standards for MYs 2022-2025, and given NHTSA’s obligation to conduct a separate rulemaki ng in order to establish final standards for vehicles for those model years, EPA and NHTSA are proposing a comprehensive mid-term evaluation and agency decision-making process. As part of this undertaking, both NHTSA and EPA will develop and compile up-to-date informatio n for the evaluation, through a collaborative, robust and transparent process, including public notice and comment. The evaluation will be based on (1) a holistic assessment of all of the factors considered by the agencies in setting standards, including those set forth in the rule and other relevant factors, and (2) the expected impact of those factors on the manufacturers’ abil ity to comply, without placing decisive weight on any particular factor or proj ection. The comprehensive evaluation process will lead to final agency action by both agencies.

Consistent with the agencies’ commitment to maintaining a single national framework forregulation of vehicle emissions and fuel economy, the agencies fully expect to conduct the midterm evaluation in close coordination with the California Air Resources Board (CARB). Moreover, the agencies fully expect that any adjustments to the GHG standards will be madeSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 44 of 768 with the participation of CARB and in a manner that ensures continued harmonization of state
and federal vehicle standards.

Further discussion of the mid-term evaluation can be found in section III and IV of the proposal.

6. Coordinated Compliance

The MYs 2012-2016 final rules established detailed and comprehensive regulatory provisions for compliance and enforcement under the GHG and CAFE programs. These provisions remain in place for model years beyond MY 2016 without additional action by the agencies and EPA and NHTSA are not proposing an y significant modifications to them. In the MYs 2012-2016 final rule, NHTSA and EPA established a program that recognizes, and replicates as closely as possible, the compliance protocols associated with the existing CAA Tier 2 vehicle emission standards, and with earlier m odel year CAFE standards. The certification, testing, reporting, and associ ated compliance activities establis hed for the GHG program closely track those in previously existing programs and ar e thus familiar to manuf acturers. EPA already oversees testing, collects and processes test data, and performs calculations to determine compliance with both CAFE and CAA standards. Under this coordinated approach, the compliance mechanisms for both programs are consis tent and non-duplicative. EPA also applies the CAA authorities applicable to its separa te in-use requirements in this program.

The compliance approach allows manufacturers to satisfy the GHG program requirements in the same genera l way they comply with previously existing applicable CAA and CAFE requirements. Manufacturers will demonstr ate compliance on a fleet-average basis at the end of each model year, allowing model-level testing to continue throughout the year as is the current practice for CAFE determinations. The compliance program design includes a single set of manufacturer reporting requirements and relies on a single set of underlying data. This approach still allows each agency to assess compliance with its respective program under its respective statutory authority. The program also addresses EPA enforcement in cases of noncompliance.

7. Additional Program Elements

a. Treatment of Compressed Natural Gas (CNG), Plug-in Hybrid Electric Vehicles (PHEVs), and Flexible Fuel Vehicles (FFVs)

EPA is proposing that CO 2 credits for plug-in hybrid electric vehicles (PHEVs) and bifuel compressed natural gas (CNG) vehicles will be based on the recognition that, once a consumer has paid several thousand dollars to be ab le to use a fuel that is considerably cheaper than gasoline, it is very likely that the consumer will seek to use the cheaper fuel as much as possible. Accordingly, for CO 2 emissions compliance, EPA is proposing to use the Society ofSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 45 of 768 Automotive Engineers “utility factor” methodology (based on vehicle range on the alternative fuel and typical daily travel mileage) to de termine the assumed percentage of operation on gasoline and percentage of operation on the alternative fuel for both PHEVs and bi-fuel CNG vehicles, along with the CO2 emissions test va lues on the alternative fuel and gasoline.

EPA is not proposing to extend this method to flexible fueled vehicles (FFVs) using E-85 and gasoline, since there is not a significant cost differential between an FFV and a conventional gasoline vehicle and historically consumers have only fueled these vehicles with E85 a very small percentage of the time. Therefore, accoun ting for E85 FFVs will continue as in the MY 2016 program, based on actual usage of E85 which represents a real-world reduction attributed
to alternative fuels.

In the CAFE program for MYs 2017-2019, EPA is proposing that the fuel economy of dual fuel vehicles will be determined in the same manner as specified in the MY 2012-2016 rule, and as defined by EISA. Beginning in MY 2020, EISA does not specify how to measure the fuel economy of dual fuel vehicles, and EPA is proposing under its EPACA authority to use the EPA “utility factor” methodology for PHEV and CNG ve hicles to determine how to proportion the fuel economy when operating on gasoline or diesel fuel and the fuel economy when operating on the alternative fuel. For FFVs, EPA is proposing to use the same methodology as it uses for the GHG program to determine how to proportion the fuel economy, which would be based on actual usage of E85. EPA is proposing to continue to use Petroleum Equivalency Factors and the 0.15 divisor used in the MY 2012-2016 rule for the alternative fuels, however with no cap on the amount of fuel economy increase allowed. This issue is discussed further in Section III.B.10.

b. Exclusion of Emergency and Police Vehicles

Under EPCA, manufacturers are allowed to exclude emergency vehicles from their
CAFE fleet 55 and all manufacturers have historically done so. In the MYs 2012-2016 program, EPA’s GHG program applies to these vehicles. Ho wever, after further consideration of this issue, EPA is proposing the same type of exclus ion provision for these vehicles for MY 2017 and later because of the unique features of vehicles designed specifically for law enforcement and emergency purposes, which have the effect of raising their GHG emissions and calling into question whether the footprint attribute is suitable.

c. Small Businesses and Small Volume Manufacturers

EPA is proposing provisions to address two categories of smaller manufacturers. The first category is small businesses as defined by the Small Business Administration (SBA). For vehicle manufacturers, SBA’s definition of small business is any firm with less than 1,000 employees. As with the MYs 2012-2016 program, EPA is proposing to continue to exempt small

55 49 U.S.C. 32902(e)Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 46 of 768 businesses from the GHG standards, for any comp any that meets the SBA’s definition of a small business. EPA believes this exemption is appropriate given the unique challenges small businesses would face in meeting the GHG standards, and since these businesses make up less than 0.1% of total U.S. vehicle sales, and there is no significant impact on emission reductions. The second category of small manufacturers addressed in EPA’s proposal are small volume manufacturers, which EPA defines as manufactur ers with U.S. annual sales of less than 5,000 vehicles. Under the MYs 2012-2016 program, these small volume manufacturers are eligible for an exemption from the CO 2 standards. EPA is proposing to bring small volume
manufacturers into the CO 2 program for the first time starting in MY 2017, and allow them to petition EPA for alternative standards.

EPCA provides NHTSA with the authority to exempt from the generally applicable CAFE standards manufacturers that produce fewer than 10,000 passenger cars worldwide in the model year each of the two years prior to the year in which they seek an exemption. 56 If NHTSA exempts a manufacturer, it must establish an alte rnate standard for that manufacturer for that model year, at the level that the agency decides is maximum feasible for that manufacturer. The exemption and alternative standard apply only if the exempted manufacturer also produces fewer than 10,000 passenger cars worldwide in the year for which the exemption was granted.

Further, the Temporary Lead-time Alternative Standards (TLAAS) provisions included in EPA’s MYs 2012-2016 program for manufacturers with MY 2009 U.S. sales of less than 400,000 vehicles ends after MY 2015 for most eligible manufacturers. 57 EPA is not proposing to extend or otherwise replace the TLAAS provisions for the proposed MYs 2017-2025 program. With the exception of the small businesses and sm all volume manufacturers discussed above, the proposed MYs 2017-2025 standards would apply to all manufacturers.

C. Summary of Costs and Benefits for the Proposed National Program

This section summarizes the projected cost s and benefits of the proposed CAFE and GHG emissions standards. These projections he lped inform the agencies’ choices among the alternatives considered and provide further confirmation that the proposed standards are appropriate under their respective statutory authorities. The costs and benefits projected by NHTSA to result from these CAFE standards are presented first, followed by those from EPA’s analysis of the GHG emissions standards.

The agencies recognize that there are uncertainties regarding the benefit and cost values presented in this proposal. Some benefits and costs are not quantified. The value of other benefits and costs could be too low or too high.

56 49 U.S.C. 32902(d). Implementing regulations may be found in 49 CFR Part 525.

57 TLAAS ends after MY 2016 for manufacturers with MY 2009 U.S. sales of less than 50,000 vehiclesSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 47 of 768 For several reasons, the estimates for costs and benefits presented by NHTSA and EPA, while consistent, are not directly comparable, and thus should not be expected to be identical. Most important, NHTSA and EPA’s standards would require slightly different fuel efficiency improvements. EPA’s proposed GHG standard is more stringent in part due to its assumptions about manufacturers’ use of air conditioning leakage credits, which result from reductions in air conditioning-related emissions of HFCs. NHTSA is proposing standards at levels of stringency that assume improvements in the efficiency of air conditioning systems, but that do not account for reductions in HFCs, which are not related to fuel economy or energy conservation. In addition, the CAFE and GHG st andards offer somewhat different program flexibilities and provisions, and the agencies’ analyses differ in their accounting for these flexibilities (examples include the treatment of EVs, dual-fueled ve hicles, and civil penalties), primarily because NHTSA is statutorily prohibited from consideri ng some flexibilities when establishing CAFE standards, 58 while EPA is not. These differences c ontribute to differences in the agencies’ respective estimates of costs and benefits resultin g from the new standards. Nevertheless, it is important to note that NHTSA and EPA have harmonized the programs as much as possible, and this proposal to continue the National Progra m would result in significant cost and other advantages for the automobile industry by allowing them to manufacture one fleet of vehicles across the U.S., rather than comply with potentia lly multiple state standard s that may occur in the absence of the National Program.

In summary, the projected costs and benefits presented by NHTSA and EPA are not directly comparable, because the levels being proposed by EPA include air conditioning-related improvements in HFC reductions, and because of the projection by EPA of complete compliance with the proposed GHG standards, whereas NHTSA projects some manufacturers will pay civil penalties as part of their compliance strategy, as allowed by EPCA. It should also be expected that overall EPA’s estimates of GHG reductions and fuel savings achieved by the proposed GHG standards will be slightly higher than those projected by NHTSA only for the CAFE standards because of the same reasons described above. For the same reasons, EPA’s estimates of manufacturers’ costs for complying with the proposed passenger car and light truck GHG standards are slightly higher than NHTSA’s es timates for complying with the proposed CAFE
standards.

1. Summary of Costs and Benefits for the Proposed NHTSA CAFE Standards

In reading the following section, we note that tables are identified as reflecting “estimated required” values and “estimated achieved” values . When establishing standards, EPCA allows NHTSA to only consider the fuel economy of dual-fuel vehicles (for example, FFVs and PHEVs) when operating on gasoline, and prohibits NHTSA from considering the use of dedicated alternative fuel vehicle credits (including for example EVs), credit carry-forward and

58 See 49 U.S.C. 32902(h).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 48 of 768 carry-back, and credit transfer and trading. NHTSA’s primary analysis of costs, fuel savings, and related benefits from imposing higher CAFE standards does not include them. However, EPCA does not prohibit NHTSA from co nsidering the fact that manuf acturers may pay civil penalties rather than comply with CAFE standards, and NHTSA’s primary analysis accounts for some manufacturers’ tendency to do so. The primary analysis is generally identified in tables throughout this document by the term “ estimated required CAFE levels.”

To illustrate the effects of the flexibilities and technologies that NHTSA is prohibited from including in its primary analysis, NHTSA performed a supplemental analysis of these effects on benefits and costs of the proposed CAFE standards that helps to demonstrate the realworld impacts. As an example of one of the e ffects, including the use of FFV credits reduces estimated per-vehicle compliance costs of the program, but does not significantly change the projected fuel savings and CO 2 reductions, because FFV credits reduce the fuel economy levels that manufacturers achieve not only under the proposed standards, but also under the baseline MY 2016 CAFE standards. As another example, including the operation of PHEV vehicles on both electricity and gasoline, and the expected use of EVs for compliance may raise the fuel economy levels that manufacturers achieve under the proposed standards. The supplemental analysis is generally identified in tables throughout this document by the term “ estimated
achieved CAFE levels.”

Thus, NHTSA’s primary analysis shows the estimates the agency considered for purposes of establishing new CAFE standards, and its s upplemental analysis including manufacturer use
of flexibilities and advanced t echnologies currently reflects the agency’s best estimate of the potential real-world effects of the proposed CAFE standards.

Without accounting for the compliance flexib ilities and advanced technologies that NHTSA is prohibited from considering when determining the maximum feasible level of new CAFE standards, since manufacturers’ decisions to use those flexibilities and technologies are voluntary, NHTSA estimates that the required fuel economy increases would lead to fuel savings totaling 161 billion gallons throughout the lives of vehicles sold in MYs 2017-2025. At a 3 percent discount rate, the present value of the economic benefits resulting from those fuel savings is $420 billion; at a 7 percent private discount rate, the present value of the economic benefits resulting from those fuel savings is $334 billion.

The agency further estimates that these new CAFE standards would lead to corresponding reductions in CO 2 emissions totaling 2.0 billion metric tons during the lives of vehicles sold in MYs 2017-2025. The present value of the economic benefits from avoiding those emissions is $46 billion, based on a global soci al cost of carbon value of $22 per metric tonSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 49 of 768 (in 2010, and growing thereafter). 59 It is important to note that NHTSA’s CAFE standards and EPA’s GHG standards will both be in effect, and each will lead to increases in average fuel economy and CO 2 reductions. The two agencies standards together comprise the National Program, and this discussion of the costs and benefits of NHTSA’s CAFE standards does not change the fact that both the CAFE and GHG standards, jointly, are the source of the benefits and costs of the National Program.

Table I-7 NHTSA’s Estimated MYs 2017-2025 Costs, Benefits, and Net Benefits ($Billion) under the CAFE Standards (Estimated Required)

3% discount rate 7% discount rate
Lifetime present value Annualized value Lifetime present value Annualized value
Costs 158 158 Benefits 496 403 Net benefits 338 246

59 NHTSA also estimated the benefits associated with thr ee more estimates of a one ton GHG reduction in 2009 ($5, $36, and $67), which will likewise grow thereafter. See Section II for a more detailed discussion of the social cost of carbon.Summary of Interagency Working Comments Received on Draftrule under EO 12866 review. Subject to further policyreview.Page50of768Table I-8 NHTSA’s Estimated Fuel Saved (Billion Gallons and Barrels) and CO2Emissions Avoided (mmt) under theCAFE Standards (Estimated Required)Earlier60201720182019202020212022202320242025TotalPassengerCarsFuel (billion gallons) 3 2 5 7 9 11 12 14 16 18 98Fuel (billion barrels)CO2(mmt) 37 23 57 83 111 135 154 179 208 243 1230LightTrucksFuel (billion gallons) 1 1 2 4 6 8 9 10 11 12 63Fuel (billion barrels)CO2(mmt) 6 7 22 53 72 96 107 119 128 149 759CombinedFuel (billion gallons) 4 3 7 11 15 19 21 24 27 30 161Fuel (billion barrels)CO2(mmt) 44 29 79 137 183 231 261 297 337 392 198960The “Earlier” column shows benefits that NHTSA forecasts manufacturers will implement in model years prior to 2017 that are inresponse to the proposedMY 2017-2025 standards. The CAFE model forecasts that manufactures will implement some technologies, and achieve benefits during vehicle redesigns thatoccur prior to MY 2017 in order to comply with MY 2017 and later standards in a cost effective manner.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 51 of 768 Considering manufact urers’ ability to employ comp liance flexibilities and advanced technologies for meeting the standards, NHTSA estimates the following for fuel savings and
avoided CO 2 emissions, assuming FFV credits would be used toward both the baseline and final
standards:Summary of Interagency Working Comments Received on Draftrule under EO 12866 review. Subject to further policyreview.Page52of768Table I-9 NHTSA’s Estimated Fuel Saved (Billion Gallons and Barrels) and CO2Emissions Avoided (mmt) under theCAFE Standards (Estimated Achieved)Earlier201720182019202020212022202320242025TotalPassengerCarsFuel (billion gallons) 4 2 4 6 8 10 11 14 16 19 94Fuel (billion barrels) 2.2CO2(mmt) 39 23 42 69 93 130 150 183 217 258 1,205LightTrucksFuel (billion gallons) 1 1 2 4 6 8 8 9 10 11 59Fuel (billion barrels) 1.4CO2(mmt) 6 7 20 44 60 84 94 106 115 123 659CombinedFuel (billion gallons) 4 3 6 10 14 18 20 23 26 30 153Fuel (billion barrels) 3.6CO2(mmt) 45 30 62 113 153 215 245 289 332 381 1,864Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 53 of 768 NHTSA estimates that the fuel economy increases resulting from the proposed standards would produce other benefits both to drivers ( e.g. , reduced time spent refueling) and to the U.S. as a whole ( e.g. , reductions in the costs of petroleum imports beyond the direct savings from reduced oil purchases), as well as some disbenefits ( e.g. , increased traffic congestion) caused by drivers’ tendency to travel more when the cost of driving declines (as it does when fuel economy increases). NHTSA has estimated the total mone tary value to society of these benefits and disbenefits, and estimates that the proposed standards will prod uce significant net benefits to society. Using a 3 percent discount rate, NHTSA estimates that the present value of these benefits would total more than $496 billion ove r the lives of the vehicles sold during MYs 2017- 2025; using a 7 percent discount rate, more th an $403 billion. More discussion regarding
monetized benefits can be found in Section IV of this notice and in NHTSA’s PRIA. Note that the benefit calculation in the following tables includes the benefits of reducing CO 2 emissions, 61
but not the benefits of reducing other GHG emissions.

61 CO 2 benefits for purposes of these tables are calculated using the $22/ton SCC values. Note that the net present value of reduced GHG emissions is calculated differently from other benefits. The same discount rate used to discount the value of damages from future emissions (SCC at 5, 3, and 2.5 percent) is used to calculate net present value of SCC for internal consistency.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 54 of 768 Table I-10 NHTSA’s Discounted Benefits ($Billion) under the CAFE Standards Using a 3 and 7 Percent Discount Rate (Estimated Required)

Earlier 2017 2018 2019 2020 2021 2022 2023 2024 2025 Total
3% discount rate Passenger cars 10 6 14 20 27 34 38 44 52 58 302

Light trucks 2 2 6 13 17 24 28 31 34 38 193

Combined 11 8 20 33 44 58 66 75 86 95 496

7% discount rate Passenger cars 8 5 11 16 22 28 32 36 42 47 248

Light trucks 1 1 5 10 14 19 22 25 27 30 155

Combined 9 6 16 27 36 47 54 61 70 78 403

Considering manufact urers’ ability to employ comp liance flexibilities and advanced technologies for meeting the standards, NHTSA estimates the present va lue of these benefits would be reduced by about [XX] percent:

Table I-11 NHTSA’s Discounted Benefits ($Billion) under the CAFE Standards Using a 3 and 7 Percent Discount Rate (Estimated Achieved)

Earlier 2017 2018 2019 2020 2021 2022 2023 2024 2025 Total
3% discount rate Passenger cars 10 6 11 18 25 31 35 42 49 58 287

Light trucks 1 2 5 12 17 23 26 29 32 35 184

Combined 12 8 17 31 42 54 61 72 82 93 471

7% discount rate Passenger cars 8 5 9 15 20 25 29 35 40 48 235

Light trucks 1 1 4 10 13 19 21 24 26 28 148

Combined 10 7 14 25 34 44 50 58 67 76 383

NHTSA attributes most of these benefits (abo ut $399 billion at a 3 percent discount rate, or about $317 billion at a 7 percent discount rate, excluding consideration of compliance flexibilities and advanced technologies for meeting the standards) to reductions in fuel consumption, valuing fuel (for societal purposes) at the future pre-tax prices projected in the Energy Information Administration’s (EIA) reference case forecast from the Annual Energy Outlook (AEO) 2011. NHTSA’s PRIA accompanying this proposal presents a detailed analysis of specific benefits of the rule.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 55 of 768 Table I-12 Summary of NHTSA’s Fuel Savings and CO 2 Emissions Reduction under the CAFE Standards (Estimated Required)

Amount 3% discount rate 7% discount rate Fuel savings 161 420 334
CO 2 emissions reductions 1,989 46 46

NHTSA estimates that the increases in tech nology application necessary to achieve the projected improvements in fuel economy will entail considerable monetary outlays. The agency estimates that the incremental costs for achieving the proposed CAFE standards – that is, outlays by vehicle manufacturers over and above those required to comply with the MY 2016 CAFE standards – will total about $158 billion ( i.e. , during MYs 2017-2025).

Table I-13 NHTSA’s Incremental Technology Outlays ($Billion) under the CAFE Standards (Estimated Required)

Earlier 2017 2018 2019 2020 2021 2022 2023 2024 2025 Total Passenger

cars 3 2 5 7 9 12 14 17 22 23 115

Light trucks 0 0 1 2 4 5 6 7 8 9 43

Combined 4 3 6 9 13 17 20 24 30 32 158

However, NHTSA estimates that manufacturers employing compliance flexibilities and advanced technologies to meet the standards could significantly reduce these outlays:

Table I-14 NHTSA’s Incremental Technology Outlays ($Billion) under the CAFE Standards (Estimated Achieved)

Earlier 2017 2018 2019 2020 2021 2022 2023 2024 2025 Total Passenger

cars 1 2 3 6 8 11 12 16 19 22 100

Light trucks 0 0 1 2 3 5 5 6 7 7 37

Combined 2 2 4 8 11 15 17 22 26 29 137

NHTSA projects that manufacturers will rec over most or all of these additional costs through higher selling prices for new cars and light trucks. To allow manufacturers to recover these increased outlays (and, to a much less ex tent, the civil penalties that some manufacturers are expected to pay for non-compliance), the agency estimates that the standards would lead toSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 56 of 768 increase in average new vehicle prices rangi ng from $175 per vehicle in MY 2017 to $1975 per
vehicle in MY 2025:

Table I-15 NHTSA’s Incremental Increases in Average New Vehicle Costs ($) under the CAFE Standards (Estimated Required)

2017 2018 2019 2020 2021 2022 2023 2024 2025 Passenger cars 236 492 690 931 1,237 1,407 1,682 2,062 2,170

Light trucks 70 208 426 671 924 1,056 1,239 1,399 1,581

Combined 175 389 596 840 1,127 1,285 1,531 1,840 1,975

And as before, NHTSA estimates that manuf acturers employing compliance flexibilities and advanced technologies to meet the standa rds could significantly reduce these increases.

Table I-16 NHTSA’s Incremental Increases in Average New Vehicle Costs ($) under the CAFE Standards (Estimated Achieved)

2017 2018 2019 2020 2021 2022 2023 2024 2025 Passenger cars 180 366 589 831 1,072 1,217 1,568 1,826 2,049

Light trucks 62 186 389 580 832 935 1,092 1,220 1,277

Combined 136 300 517 743 988 1,119 1,406 1,623 1,793

NHTSA estimates, therefore, that the tota l benefits of these proposed CAFE standards will be more than 2.5 times the magnitude of the corresponding costs. As a consequence, the proposed CAFE standards would produce net benefits of $338 billion at a 3 percent discount rate (with compliance flexibilities, $334 billion), or $246 billion at a 7 percent discount rate (with compliance flexibilities, $246 billion), over the useful lives of the vehicles sold during MYs

2017-2025.

2. Summary of Costs and Benefits for the Proposed EPA GHG Standards

EPA has analyzed in detail the costs and benefits of the proposed GHG standards. Table I-17 shows EPA’s estimated lifetime discounted cost, fuel savings, and benefits for all vehiclesprojected to be sold in model years 2017-2025. The benefits include impacts such as climaterelated economic benefits from reducing emissions of CO 2 (but not other GHGs), reductions in energy security externalities caused by U.S. petroleum consumption and imports, the value of certain health benefits, the value of additional dr iving attributed to the rebound effect, the value of reduced refueling time needed to fill up a more fuel efficien t vehicle. The analysis also includes economic impacts stemming from additional vehicle use, such as the economic damages caused by accidents, congestion and noise. Note that benefits depend on estimated values for the social cost of carbon (SCC), as described in Section III.H.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 57 of 768 Table I-17 EPA’s Estimated 2017-2025 Model Year Lifetime Discounted Costs, Benefits, and Net Benefits assuming the 3% discount rate SCC Value a,b (Billions of 2009 dollars)

Lifetime Present Value c – 3% Discount Rate Program Costs $133 Fuel Savings $468
Benefits $133

Net Benefits d $468

Annualized Value e – 3% Discount Rate
Annualized costs $5.89 Annualized fuel savings $20.8
Annualized benefits $5.94
Net benefits $20.9

Lifetime Present Value c - 7% Discount Rate Program Costs $130 Fuel Savings $363
Benefits $115

Net Benefits d $348

Annualized Value e – 7% Discount Rate
Annualized costs $9.86 Annualized fuel savings $27.5
Annualized benefits $7.19
Net benefits $24.9

Notes:

a The agencies estimated the benefits associated with four different values of a one ton CO 2 reduction (model average at 2.5% discount rate, 3%, and 5%; 95 th percentile at 3%), which each increase over time. For the purposes of this overview presentation of estimated costs and benefits, however, we are showing the benefits associated wi th the marginal value deemed to be central by the interagency working group on this topic: the model average at 3% discount rate, in 2009 dollars. Section III.H provides a complete list of values for the 4 estimates.

b Note that net present value of reduced GHG emissions is calculated differently than other benefits. The same discount rate used to disc ount the value of damages from future emissions (SCC at 5, 3, and 2.5 percent) is used to cal culate net present value of SCC for internal consistency. Refer to Section III.H for more detail

c Present value is the total, aggregated amount that a series of monetized costs or benefits that occur over time is worth in a given year. For th is analysis, lifetime present values are calculated for the first year of each model year for MYs 201 7-2025 (in year 2009 dollar terms). The lifetime present values shown here are the present values of each MY in its first year summed across MYs.

d Net benefits reflect the fuel savings plus benefits minus costs.

e The annualized value is the constant annual valu e through a given time period (the lifetime of each MY in this analysis) whose summed present va lue equals the present value from which it was derived. Annualized SCC values are calculated usin g the same rate as that used to determine the SCC value while all other costs and benef its are annualized at either 3% or 7%.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 58 of 768 Table I-18 shows EPA’s estimated lifetime fuel savings and CO 2 equivalent emission reductions for all vehicles sold in the model years 2017-2025. The values in Table I-18 are projected lifetime totals for each model year and are not discounted. As documented in EPA’s draft RIA, the potential credit transfer between cars and trucks may change the distribution of the fuel savings and GHG emission impacts betwee n cars and trucks. As discussed above with respect to NHTSA’s CAFE standards, it is important to note that NHTSA’s CAFE standards and EPA’s GHG standards will both be in effect, and each will lead to increases in average fuel economy and reductions in CO 2 emissions. The two agencies’ standards together comprise the National Program, and this discussion of costs and benefits of EPA’s proposed GHG standards does not change the fact that both the proposed CAFE and GHG standards, jointly, are the source of the benefits and costs of the National Program . In general though, in addition to the added GHG benefit of HFC reductions from the EPA program, the fuel savings benefit are also somewhat higher than that from CAFE, primaril y because of the possibility of paying civil penalties in lieu of applying technology in NHTSA ’s program, which is required by EPCA.Summary of Interagency Working Comments Received on Draftrule under EO 12866 review. Subject to further policyreview.Page59of768Table I-18 EPA’s Estimated 2017-2025 Model Year Lifetime Fuel Saved and GHGEmissions Avoided2017MY2018MY2019MY2020MY2021MY2022MY2023MY2024MY2025MYTotalCarsFuel (billion gallons) 1.4 3.7 6.1 8.7 11.4 14.2 16.9 19.7 22.5 104.5Fuel (billion barrels) 0.03 0.09 0.14 0.21 0.27 0.34 0.40 0.47 0.54 2.49CO2EQ (mmt) 18.6 46.9 75.5 107 140 171 199 229 259 1,246LightTrucksFuel (billion gallons) 1.1 2.2 3.04.0 7.4 9.8 12.0 14.1 16.3 69.7Fuel (billion barrels) 0.03 0.05 0.07 0.10 0.18 0.23 0.28 0.34 0.39 1.66CO2EQ (mmt) 12.2 27.7 39.5 53 92 118 141 164 186 833CombinedFuel (billion gallons) 2.5 5.9 9.1 12.7 18.7 24.0 28.8 33.8 38.8 174.2Fuel (billion barrels) 0.06 0.14 0.22 0.30 0.45 0.57 0.69 0.80 0.92 4.15CO2EQ (mmt) 30.8 74.6 115 160 233 289 340 392 445 2,079Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 60 of 768 Table I-19 shows EPA’s estimated lifetime discounted benefits for all vehicles sold in model years 2017-2025. Although EPA estimated the benefits associated with four different values of a one ton GHG reduction ($5, $22 $36, $67 in CY 2010 and in 2009 dollars), for the purposes of this overview presentation of estimated benefits EPA is showing the benefits associated with one of these marginal values, $22 per ton of CO 2 , in 2009 dollars and 2010 emissions. Table I-19 presents benefits based on the $22 value. Section III.H presents the four marginal values used to estimate monetized benefits of GHG reductions and Section III.H presents the program benefits using each of the four marginal values, which represent only a partial accounting of total benefits due to omitte d climate change impacts and other factors that are not readily monetized. The values in the table are discounted values for each model year of vehicles throughout their projected lifetimes. Th e benefits include all benefits considered by EPA such as GHG reductions, PM benefits, ener gy security and other externalities such as reduced refueling time and accidents, congestion and noise. The lifetime discounted benefits are
shown for one of four different social cost of carbon (SCC) values considered by EPA. The
values in Table I-19 do not include costs associ ated with new technology required to meet the GHG standard and they do not include the fuel savings expected from that technology.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 61 of 768 Table I-19 EPA’s Estimated 2017-2025 Mode l Year Lifetime Discounted Benefits Assuming the $22/ton SCC Value a,b,c,d (billions of 2009 dollars)

Discount

Rate Model Year

2017 2018 2019 2020 2021 2022 2023 2024 2025 Sum of
Present Values 3% $1.67 $4.06 $6.47 $9.32 $14.1 $18.2 $22.1 $26.3 $30.6 $133
7% $1.44 $3.50 $5.57 $8.04 $12.1 $15.7 $19.1 $22.7 $26.4 $115

a The benefits include all benefits considered by EPA savings in refueling time, climate-related economic benefits from reducing emissions of CO 2 (but not other GHGs), economic benefits from reducing emissions of PM and other air pollutants th at contribute to its formation, and reductions in energy security externalities caused by U.S. petroleum consumption and imports. The analysis also includes disbenefits stemming from additional ve hicle use, such as the economic damages caused by accidents, congestion and noise.

b Note that net present value of reduced GHG emissi ons is calculated differently than other benefits. The same discount rate used to discount the value of damages from future emissions (SCC at 5, 3, and 2.5 percent) is used to calculate net present value of SCC for internal consistency. Refer to
Section III.H for more detail.

c Monetized GHG benefits exclude the value of reductions in non-CO 2 GHG emissions (HFC, CH 4 and N 2 O) expected under this final rule. Alt hough EPA has not monetized the benefits of reductions in these non-CO 2 emissions, the value of these reductions should not be interpreted as zero. Rather, the reductions in non-CO 2 GHGs will contribute to this rule’s climate benefits, as explained in Section III.F.2. The SCC TSD notes the difference between the social cost of non-CO 2 emissions and CO 2 emissions, and specifies a goal to develop methods to value non-CO 2 emissions in future analyses. Also, as noted in Section III.H, SCC increases over time. The $22/ton (2009$) value applies to 2010 emissions and grows larger over time.

d Model year values are discounted to the first year of each model year; the “Sum” represents those discounted values summed across model years.

Table I-20 shows EPA’s estimated lifetime fuel savings, lifetime CO 2 emission reductions, and the monetized net present values of those fuel savings and CO 2 emission reductions. The fuel savings and CO 2 emission reductions are projected lifetime values for all vehicles sold in the model years 2017-2025. The estimated fuel savings in billions of gallons
and the GHG reductions in million metric tons of CO 2 shown in Table I-20 are totals for the nine model years throughout their projected lifetime and are not discounted. The monetized values shown in Table I-20 are the summed values of the discounted monetized fuel savings and
monetized CO 2 reductions for the model years 2017-2025 vehicles throughout their lifetimes. The monetized values in Table I-20 reflect both a 3 percent and a 7 percent discount rate as
noted.

Table I-20 EPA’s Estimated 2017-2025 Model Year Lifetime Fuel Savings, CO 2 Emission Reductions, and Discounted Monetized SCC Benefits using the $22/ton SCC Value (monetized values in 2009 dollars)

Amount $ valueSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 62 of 768 (billions)

Fuel savings (3% discount rate) 174 billion gallons (4.1 billion barrels) $468

Fuel savings (7% discount rate) 174 billion gallons (4.1 billion barrels) $363

CO 2 e emission reductions (CO 2 portion valued assuming $22/ton
CO 2 in 2010) 2,079 MMT CO 2 e $49.1 a,b

a $49.1 billion for 1,848 MMT of reduced CO 2 emissions. As noted in Section III.H, the $22/ton (2009$) value applies to 2010 emissions and grows larger over time. M onetized GHG benefits exclude the value of reductions in

non-CO 2 GHG emissions (HFC, CH 4 and N 2 O) expected under this proposed rule. Although EPA has not
monetized the benefits of reductions in these non-CO 2 GHG emissions, the value of these reductions should not be interpreted as zero. Rather, the reductions in non-CO 2 GHGs will contribute to this rule’s climate benefits, as explained in Section III.F.2. The SCC TSD notes the difference between the social cost of non-CO 2 emissions and

CO 2 emissions, and specifies a goal to develop methods to value non-CO 2 emissions in future analyses.

b Note that net present value of reduced CO 2 emissions is calculated differently than other benefits. The same discount rate used to discount the value of damages from fu ture emissions (SCC at 5, 3, and 2.5 percent) is used to calculate net present value of SCC for internal consis tency. Refer to Section III.H for more detail.

Table I-21 shows EPA’s estimated incremental and total technology outlays for cars and trucks for each of the model years 2017-2025. The technology outlays shown in Table I-21 are for the industry as a whole and do not account for fuel savings associated with the program. Table I-22 shows EPA’s estimated incremental cost increase of the average new vehicle for each model year 2017-2025. The values shown are incremental to a baseline vehicle and are not cumulative. In other words, the estimated increase for 2017 model year cars is $172 relative to a 2017 model year car meeting the MY 2016 standards. The estimated increase for a 2018 model year car is $319 relative to a 2018 model year car meeting the MY 2016 standards (not $172 plus $319).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 63 of 768 Table I-21 EPA’s Estimated Incremental Technology Outlays (billions of 2009 dollars)

2017
MY 2018
MY 2019
MY 2020
MY 2021
MY 2022
MY 2023
MY 2024
MY 2025
MY Sum of
Present Values
3% discount

rate Cars $1.69 $3.11 $4.56 $6.00 $7.48 $11.1 $14.7 $18.4 $22.1 $89.2 Trucks $0.28 $1.00 $1.61 $2.25 $4.22 $6.00 $7.69 $9.34 $10.9 $43.3 Combined $1.97 $4.12 $6.16 $8.25 $11.7 $17.1 $22.4 $27.7 $33.1 $133
7% discount

rate Cars $1.66 $3.06 $4.48 $5.89 $7.35 $10.9 $14.4 $18.1 $21.7 $42.9 Trucks $0.27 $0.99 $1.58 $2.21 $4.14 $5.89 $7.55 $9.17 $10.7 $42.5 Combined $1.93 $4.04 $6.05 $8.10 $11.5 $16.8 $21.9 $27.2 $32.5 $130 Model year values are discounted to the fi rst year of each model year; the “Sum” repr esents those discounted values summed acro ss model years.

Table I-22 EPA’s Estimated Incremental Increase in Average New Vehicle Cost (2009 dollars per unit)

2017
MY 2018
MY 2019
MY 2020
MY 2021
MY 2022
MY 2023
MY 2024
MY 2025
MY Cars $172 $319 $463 $591 $723 $1,051 $1,357 $1,658 $1,947 Trucks $49 $180 $292 $407 $753 $1,068 $1,373 $1,670 $1,944 Combined $126 $268 $402 $527 $734 $1,057 $1,362 $1,662 $1,946Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 64 of 768 D. Background and Comparison of NHTSA and EPA Statutory Authority

This section provides the agencies’ resp ective statutory authorities under which CAFE
and GHG standards are established.

1. NHTSA Statutory Authority

NHTSA establishes CAFE standards for passenger cars and light trucks for each model year under EPCA, as amended by EISA. EPCA mandates a motor vehicle fuel economy regulatory program to meet the various facets of the need to conserve energy, including the environmental and foreign policy implications of petroleum use by motor vehicles. EPCA allocates the responsibility for implementing the program between NHTSA and EPA as follows: NHTSA sets CAFE standards for passenger cars and light trucks; EPA establishes the procedures for testing, tests vehicles, collects and analyzes manufacturers’ data, and calculates the individual and average fuel economy of each manufacturer’s passenger cars and light trucks; and NHTSA
enforces the standards based on EPA’s calculations.

a. Standard Setting

We have summarized below the most importa nt aspects of standard setting under EPCA, as amended by EISA. For each future model year, EPCA requires that NHTSA establish separate passenger car and light truck standards at “the maximum feasible average fuel economy level that it decides the manufacturers can achieve in that model year,” based on the agency’s consideration of four statutory factors: techno logical feasibility, economic practicability, the effect of other standards of the Government on fuel economy, and the need of the nation to conserve energy. EPCA does not define these terms or specify what weight to give each concern in balancing them; thus, NHTSA defines them a nd determines the appropriate weighting that leads to the maximum feasible standards given the circumstances in each CAFE standard rulemaking. 62 For MYs 2011–2020, EPCA further requires that separate standards for passengercars and for light trucks be set at levels high enough to ensure that the CAFE of the industrywide combined fleet of new passenger cars and ligh t trucks reaches at least 35 mpg not later than MY 2020. For model years after 2020, standards need simply be set at the maximum feasible
level.

62 See Center for Biological Diversity v. NHTSA , 538 F.3d. 1172, 1195 (9th Cir. 2008) (“The EPCA clearly requires the agency to consider these four factors, but it gives NHTSA discretion to decide how to balance the statutory factors—as long as NHTSA’s balancing does not undermine the fundamental purpose of the EPCA: energy conservation.”)Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 65 of 768 Because EPCA states that standards must be set for “...automobiles manufactured by manufacturers,” and because Congress provid ed specific direction on how small-volume manufacturers could obtain exemptions from the passenger car standards, NHTSA has long interpreted its authority as pertaining to setting st andards for the industry as a whole. Prior to this NPRM, some manufacturers raised with NHTSA the possibility of NHTSA and EPA setting alternate standards for part of the industry that me t certain (relatively low) sales volume criteria – specifically, that separate standards be set so that “intermediate-size,” limited-line manufacturers do not have to meet the same levels of stringen cy that larger manufactur ers have to meet until several years later. NHTSA seeks comment on whether or how EPCA, as amended by EISA, could be interpreted to allow such alternate standards for certain parts of the industry.

i. Factors That Must Be Considered in Deciding the Appropriate Stringency of
CAFE Standards

(1) Technological Feasibility

“Technological feasibility” refers to whet her a particular method of improving fuel economy can be available for commercial application in the model year for which a standard is being established. Thus, the agency is not lim ited in determining the level of new standards to technology that is already being commercially applied at the time of the rulemaking, a consideration which is particularly relevant fo r a rulemaking with a timeframe as long as the present one. For this rulemaking, NHTSA has cons idered all types of technologies that improve real-world fuel economy, including air-conditione r efficiency, due to EP A’s proposal to allow generation of fuel consumption improvement values for CAFE purposes based on improvements to air-conditioner efficiency that improves fuel efficiency.

(2) Economic Practicability

“Economic practicability” refers to whether a standard is one “within the financial capability of the industry, but not so stringent as to” lead to “adverse economic consequences, such as a significant loss of jobs or the unreasonable elimination of consumer choice.” 63 The agency has explained in the past that this factor can be especially important during rulemakings in which the automobile industry is facing significantly adverse economic conditions (with corresponding risks to jobs). Consumer acceptability is also an element of economic practicability, one which is particularly difficult to gauge during times of uncertain fuel prices. 64 In a rulemaking such as the present one, looking out into the more distant future, economic practicability is a way to consider the uncertainty surrounding future market conditions and

63 67 FR 77015, 77021 (Dec. 16, 2002).

64 See

, e.g., Center for Auto Safety v. NHTSA (CAS) , 793 F.2d 1322 (D.C. Cir. 1986) (Administrator’s consideration of market demand as component of economic practicability found to be reasonable); Public Citizen v. NHTSA , 848 F.2d 256 (Congress established broad guidelines in the fuel economy statute; agency’s decision to set lower standard was a reasonable accommodation of conflicting policies).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 66 of 768 consumer demand for fuel economy in addition to other vehicle attributes. In an attempt to ensure the economic practicability of attribute-based standards, NHTSA considers a variety of factors, including the annual rate at which manufacturers can increase the percentage of their fleet that employ a particular type of fuel-savin g technology, the specific fleet mixes of different manufacturers, and assumptions about the cost of the standards to consumers and consumers’ valuation of fuel economy, among other things.

It is important to note, however, that the law does not preclude a CAFE standard that poses considerable challenges to any individu al manufacturer. The Conference Report for EPCA, as enacted in 1975, makes clear, and the case law affirms, “a determination of maximum feasible average fuel economy should not be keyed to the single manufacturer which might have the most difficulty achieving a given level of average fuel economy.” 65 Instead, NHTSA is compelled “to weigh the benefits to the nation of a higher fuel economy standard against the
difficulties of individual automobile manufacturers.” 66 The law permits CAFE standards exceeding the projected capability of any particular manufacturer as long as the standard is economically practicable for the industry as a whole. Thus, while a particular CAFE standard may pose difficulties for one manufacturer, it may also present opportunities for another. NHTSA has long held that the CAFE program is not necessarily intended to maintain the competitive positioning of each particular company. Rather, it is intended to enhance the fuel economy of the vehicle fleet on American roads, while protecting motor vehicle safety and being mindful of the risk to the overall United States economy.

(3) The Effect of Other Motor Vehicle Standards of the Government on Fuel Economy

“The effect of other motor vehicle standards of the Government on fuel economy,” involves an analysis of the effects of compliance with emission, safety, noise, or damageability standards on fuel economy capability and thus on average fuel economy. In previous CAFE rulemakings, the agency has said that pursuant to this provision, it considers the adverse effects of other motor vehicle standards on fuel economy. It said so because, from the CAFE program’s earliest years 67 until present, the effects of such compliance on fuel economy capability over the history of the CAFE program have been negative ones. For example, safety standards that have the effect of increasing vehicle weight lower vehicle fuel economy capability and thus decrease the level of average fuel economy that the agency can determine to be feasible.

In the wake of Massachusetts v. EPA and of EPA’s endangerment finding, granting of a
waiver to California for its motor vehicle GHG standards, and its own establishment of GHG standards, NHTSA is confronted with the issue of how to treat those standards under

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

66 Id

. 67 42 FR 63184, 63188 (Dec. 15, 1977). See also 42 FR 33534, 33537 (Jun. 30, 1977).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 67 of 768 EPCA/EISA, such as in the context of the “oth er motor vehicle standards” provision. To the extent the GHG standards result in increases in fuel economy, they would do so almost exclusively as a result of inducing manufacturers to install the same types of technologies used by manufacturers in complying with the CAFE standards.

Comment is requested on whether and in what way the effects of the California and EPA standards should be considered under EPCA/EISA, e.g. , under the “other motor vehicle standards” provision, consistent with NHTSA’s independent obligation under EPCA/EISA to issue CAFE standards. The agency has already considered EPA’s proposal and the harmonization benefits of the National Program in developing its own proposal.

(4) The Need of the United States To Conserve Energy

“The need of the United States to conserve energy” means “the consumer cost, national balance of payments, environmental, and foreign policy implications of our need for large quantities of petroleum, especially imported petroleum.” 68 Environmental implications principally include reductions in emissions of carbon dioxide and criteria pollutants and air toxics. Prime examples of foreign policy implications are energy independence and security

concerns.

(5) Fuel Prices and the Value of Saving Fuel

Projected future fuel prices are a critical input into the preliminary economic analysis of alternative CAFE standards, because they determine the value of fuel savings both to new vehicle buyers and to society, which is related to the consumer cost (or rather, benefit) of our need for large quantities of petroleum. In this rule, NHTSA relies on fuel price projections from the U.S. Energy Information Administration’s (EIA) most recent Annual Energy Outlook (AEO) for this analysis. Federal government agencies generally use EIA’s projections in their assessments of future energy-related policies.

(6) Petroleum Consumption and Import Externalities

U.S. consumption and imports of petroleum products impose costs on the domestic economy that are not reflected in the market price for crude petroleum, or in the prices paid by consumers of petroleum products such as gasoline . These costs include (1) higher prices for petroleum products resulting from the effect of U.S. oil import demand on the world oil price; (2) the risk of disruptions to the U.S. economy caused by sudden reductions in the supply of imported oil to the U.S.; and (3) expenses for maintaining a U.S. military presence to secure imported oil supplies from unstable regions, and for maintaining the strategic petroleum reserve (SPR) to provide a response option should a disr uption in commercial oil supplies threaten the

68 42 FR 63184, 63188 (1977).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 68 of 768 U.S. economy, to allow the United States to me et part of its Intern ational Energy Agency obligation to maintain emergency oil stocks, and to provide a national defense fuel reserve. Higher U.S. imports of crude oil or refined petroleum products increase the magnitude of these external economic costs, thus increasing the true economic cost of supplying transportation fuels above the resource costs of producing them. Conversely, reducing U.S. imports of crude petroleum or refined fuels or reducing fuel consumption can reduce these external costs.

(7) Air Pollutant Emissions

While reductions in domestic fuel refining an d distribution that result from lower fuel consumption will reduce U.S. emissions of variou s pollutants, additional vehicle use associated
with the rebound effect 69 from higher fuel economy will increase emissions of these pollutants. Thus, the net effect of stricter CAFE standards on emissions of each pollutant depends on the relative magnitudes of its reduced emissions in fu el refining and distribution, and increases in its emissions from vehicle use. Fuel savings from stricter CAFE standards also result in lower
emissions of CO 2 , the main greenhouse gas emitted as a result of refining, distribution, and use of transportation fuels. Reducing fuel consum ption reduces carbon dioxide emissions directly, because the primary source of transportation-related CO 2 emissions is fuel combustion in internal combustion engines.

NHTSA has considered environmental issues, both within the context of EPCA and the National Environmental Policy Act, in making decisions about the setting of standards from the earliest days of the CAFE program. As courts of appeal have noted in three decisions stretching over the last 20 years, 70 NHTSA defined the “need of the Nation to conserve energy” in the late 1970s as including “the consumer cost, national balance of payments, environmental, and foreign policy implications of our need for large quantities of petroleum, especially imported petroleum.” 71 In 1988, NHTSA included climate change concepts in its CAFE notices and prepared its first environmental assessment addressing that subject. 72 It cited concerns about climate change as one of its reasons for limiting the extent of its reduction of the CAFE standard for MY 1989 passenger cars. 73 Since then, NHTSA has considered the benefits of reducing tailpipe carbon dioxide emissions in its fuel eco nomy rulemakings pursuant to the statutory requirement to consider the nation’s need to conserve energy by reducing fuel consumption.

69 The “rebound effect” refers to the tendency of drivers to drive their vehicles more as the cost of doing so goes down, as when fuel economy improves.

70 Center for Auto Safety v. NHTSA , 793 F.2d 1322, 1325 n. 12 (D.C. Cir. 1986); Public Citizen v. NHTSA , 848 F.2d 256, 262–3 n. 27 (D.C. Cir. 1988) (noting that “NHTSA itsel f has interpreted the factors it must consider in setting CAFE standards as including environmental effects”); and Center for Biological Diversity v. NHTSA , 538 F.3d 1172 (9 th Cir. 2007).

71 42 FR 63184, 63188 (Dec. 15, 1977) (emphasis added).

72 53 FR 33080, 33096 (Aug. 29, 1988).

73 53 FR 39275, 39302 (Oct. 6, 1988).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 69 of 768 ii. Other Factors Considered by NHTSA

NHTSA considers the potential for adverse safety consequences when establishing CAFE standards. This practice is recognized approvingly in case law. 74 Under the universal or “flat” CAFE standards that NHTSA was previously authori zed to establish, the pr imary risk to safety came from the possibility that manufacturers woul d respond to higher standards by building smaller, less safe vehicles in order to “balan ce out” the larger, safer vehicles that the public generally preferred to buy. Under the attribute-based standards being proposed in this action, that risk is reduced because building smaller vehicles tends to raise a manufacturer’s overall CAFE obligation, rather than only raising its fleet average CAFE. However, even under attribute-based standards, there is still risk th at manufacturers will rely on down-weighting to improve their fuel economy (for a given vehicle at a given footprint target) in ways that may reduce safety. 75

iii. Factors That NHTSA Is Statutorily Prohibited From Considering in Setting
Standards

EPCA provides that in determining the level at which it should set CAFE standards for a particular model year, NHTSA may not consider the ability of manufacturers to take advantage of several EPCA provisions that facilitate co mpliance with the CAFE standards and thereby reduce the costs of compliance. Specifically, in determining the maximum feasible level of fuel economy for passenger cars and light trucks, NHTSA cannot consider the fuel economy benefits of “dedicated” alternative fuel vehicles (like ba ttery electric vehicles or natural gas vehicles), must consider dual-fueled automobiles to be operated only on gasoline or diesel fuel, and may not consider the ability of manufacturers to use, trade, or transfer credits. 76 This provision limits, to some extent, the fuel economy levels that NHTSA can find to be “maximum feasible” – if NHTSA cannot consider the fuel economy of electric vehicles, for example, NHTSA cannot set a standards predicated on manufacturers’ usage of electric vehicles to meet the standards.

74 As the United States Court of Appeals pointed out in upholding NHTSA’s exercise of judgment in setting the 1987–1989 passenger car standards, “NHT SA has always examined the safety consequences of the CAFE standards in its overall consideration of relevant factors since its earliest rulemaking under the CAFE program.” Competitive Enterprise Institute v. NHTSA (CEI I) , 901 F.2d 107, 120 at n.11 (D.C. Cir. 1990).

75 For example, by reducing the mass of the smallest vehi cles rather than the largest, or by reducing vehicle overhang outside the space measured as “foot print,” which results in less crush space.

76 49 U.S.C. 32902(h). We note, as discussed in greater de tail in Section [XX], that NHTSA interprets 32902(h) as reflecting Congress’ intent that statutorily-mandated co mpliance flexibilities remain flexibilities. When a compliance flexibility is not statutorily mandated, therefore, or when it ceases to be available under the statute, we interpret 32902(h) as no longer binding the agency’s determin ation of the maximum feasible levels of fuel economy. For example, when the manufacturing incentive for dual-fueled automobiles under 49 U.S.C. 32905 and 32906 expires in MY 2019, there is no longer a flexibility left to protect per 32902(h), so NHTSA considers the calculated fuel economy of plug-in hybrid electric vehicles for purpo ses of determining the maximum feasible standards in MYs 2020 and beyond.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 70 of 768 iv. Weighing and Balancing of Factors

NHTSA has broad discretion in balancing the above factors in determining the average fuel economy level that the manufacturers can ach ieve. Congress “specifically delegated the process of setting * * * fuel economy standards with broad guidelines concerning the factors that the agency must consider.” The breadth of those guidelines, the absence of any statutorily prescribed formula for balancing the factors, the f act that the relative weight to be given to the various factors may change from rulemaking to rulemaking as the underlying facts change, and the fact that the factors may often be conflicting with respect to whether they militate toward higher or lower standards give NHTSA discretion to decide what weight to give each of the competing policies and concerns and then determine how to balance them—as long as NHTSA’s balancing does not undermine the fundamental purpose of the EPCA, energy conservation, and as long as that balancing reasonably accommodates “conflicting policies that were committed to the agency’s care by the statute.” Thus, EPCA does not mandate that any particular number be adopted when NHTSA determines the level of CAFE standards.

v. Other Requirements Related to Standard Setting

The standards for passenger cars and for light trucks must increase ratably each year through MY 2020. 77 This statutory requirement is in terpreted, in combination with the requirement to set the standards for each model y ear at the level determined to be the maximum feasible level that manufacturers can achieve for that model year, to mean that the annual increases should not be disproportionately large or small in relation to each other. 78 Standards after 2020 must simply be set at the maximum feasible level. 79

The standards for passenger cars and light trucks must also be based on one or more vehicle attributes, like size or weight, which corr elate with fuel economy and must be expressed
in terms of a mathematical function. 80 Fuel economy targets are set for individual vehicles and
increase as the attribute decreases and vice versa. For example, footprint-based standards assignhigher fuel economy targets to smaller-footprint vehicles and lower ones to larger footprintvehicles. The fleetwide average fuel economy th at a particular manufacturer is required to achieve depends on the footprint mix of its fleet, i.e., the proportion of the fleet that is small-, medium- or large-footprint.

This approach can be used to require virtua lly all manufacturers to increase significantly the fuel economy of a broad range of both passenger cars and light trucks, i.e., the manufacturer must improve the fuel economy of all the vehicles in its fleet. Further, this approach can do so

77 49 U.S.C. 32902(b)(2)(C).

78 See 74 Fed. Reg. 14196, 14375-76 (Mar. 30, 2009).

79 49 U.S.C. 32902(b)(2)(B).

80 49 U.S.C. 32902(b)(3).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 71 of 768 without creating an incentive for manufacturers to make small vehicles smaller or large vehicles larger, with attendant im plications for safety.

b. Test Procedures for Measuring Fuel Economy

EPCA provides EPA with the responsibility fo r establishing procedures to measure fuel economy and to calculate CAFE. Current test procedures measure the effects of nearly all fuel saving technologies. EPA is considering revi sing the procedures for measuring fuel economy and calculating average fuel economy for the CAFE program, however, to account for four impacts on fuel economy not currently included in these procedures – increases in fuel economy because of increases in efficiency of the ai r conditioning system; increases in fuel economy because of technology improvements that achieve “off-cycle” benefits; incentives for use of certain hybrid technologies in a significant percentage of pick-up trucks; and incentives for achieving fuel economy levels in a significant per centage pick-up trucks that exceeds the target curve by specified amounts, in the form of increased values assigned for fuel economy. NHTSA has taken these proposed changes into account in determining the proposed fuel economy standards. These changes would be the same as program elements that are part of EPA’s greenhouse gas performance standards, discussed in Section III.B.10. As discussed below, these three elements would be implemented in the same manner as in the EPA’s greenhouse gas program – a vehicle manufacturer would have the option to generate these fuel economy values
for vehicle models that meet the criteria for thes e elements and to use these values in calculating their fleet average fuel economy. This proposed revision to CAFE calculation is discussed in
more detail in Sections III and IV below.

c. Enforcement and Compliance Flexibility

NHTSA determines compliance with the CAFE standards based on measurements of automobile manufacturers’ CAFE from EPA. If a manufacturer’s passenger car or light truck CAFE level exceeds the applicable standard for that model year, the manufacturer earns credits for over-compliance. The amount of credit earned is determined by multiplying the number of tenths of a mpg by which a manufacturer exceeds a standard for a particular category of automobiles by the total volume of automob iles of that category manufactured by the manufacturer for a given model year. As discussed in more detail in Section IV.I, credits can be carried forward for 5 model years or back for 3, and can also be transferred between a
manufacturer’s fleets or traded to another manufacturer.

If a manufacturer’s passenger car or light truck CAFE level does not meet the applicable standard for that model year, NHTSA notifies the manufacturer. The manufacturer may use “banked” credits to make up the shortfall, but if there are no (or not enough) credits available, then the manufacturer has the option to submit a “carry back plan” to NHTSA. A carry back plan describes what the manufacturer plans to do in the following three model years to earnSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 72 of 768 enough credits to make up for the shortfall through future over-compliance. NHTSA must examine and determine whether to approve the plan.

In the event that a manufacturer does not comply with a CAFE standard, even after the consideration of credits, EPCA provides for the assessing of civil penalties. 81 The Act specifies a precise formula for determining the amount of civil penalties for such a noncompliance. The penalty, as adjusted for inflation by law, is $5.50 for each tenth of a mpg that a manufacturer’s average fuel economy falls short of the standard for a given model year multiplied by the total volume of those vehicles in the affected fleet ( i.e., import or domestic passenger car, or light truck), manufactured for that model year. The amount of the penalty may not be reduced except under the unusual or extreme circumstances speci fied in the statute, which have never been exercised by NHTSA in the history of the CAFE program.

Unlike the National Traffic and Motor Vehicl e Safety Act, EPCA does not provide for recall and remedy in the event of a noncompliance. The presence of recall and remedy provisions 82 in the Safety Act and their absence in EP CA is believed to arise from the difference in the application of the safety standards and CAFE standards. A safety standard applies to individual vehicles; that is, each vehicle must possess the requisite equipment or feature that must provide the requisite type and level of performance. If a vehicle does not, it is noncompliant. Typically, a vehicle does not entirely lack an item or equipment or feature. Instead, the equipment or features fails to perform adequately. Recalling the vehicle to repair or replace the noncompliant equipment or feature can usually be readily accomplished.

In contrast, a CAFE standard applies to a manufacturer’s entire fleet for a model year. It does not require that a particular individual vehicle be equipped with any particular equipment or feature or meet a particular level of fuel economy. It does require that the manufacturer’s fleet, as a whole, comply. Further, although under th e attribute-based approach to setting CAFE standards fuel economy targets are established for individual vehicles based on their footprints, the individual vehicles are not required to meet or exceed those targets. However, as a practical matter, if a manufacturer chooses to design some ve hicles that fall below their target levels of fuel economy, it will need to design other vehicles that exceed their targets if the manufacturer’s overall fleet average is to meet the applicable standard.

Thus, under EPCA, there is no such thi ng as a noncompliant vehicle, only a noncompliant fleet. No particular vehicle in a noncompliant fleet is any more, or less, noncompliant than any other vehicle in the fleet.

81 EPCA does not provide authority for seeking to enjoin violations of the CAFE standards.

82 49 U.S.C. 30120, Remedies for defects and noncompliance.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 73 of 768 2. EPA Statutory Authority

Title II of the Clean Air Act (CAA) provides for comprehensive regulation of mobile sources, authorizing EPA to regulate emission s of air pollutants from all mobile source categories. Pursuant to these sweeping grants of authority, EPA considers such issues as technology effectiveness, its cost (both per vehicle, per manufacturer, and per consumer), the lead time necessary to implement the tec hnology, and based on this the feasibility and practicability of potential standards; the impacts of potential standards on emissions reductions of both GHGs and non-GHGs; the impacts of standards on oil conservation and energy security; the impacts of standards on fuel savings by consumers; the impacts of standards on the auto industry; other energy impacts; as well as othe r relevant factors such as impacts on safety

Pursuant to Title II of the Clean Air Act, EPA has taken a comprehensive, integrated approach to mobile source emission control that has produced benefits well in excess of the costs of regulation. In developing the Title II progra m, the Agency’s historic, initial focus was on personal vehicles since that category represented the largest source of mobile source emissions.Over time, EPA has established stringent emissions standards for large truck and other heavyduty engines, nonroad engines, and marine and locomotive engines, as well. The Agency’s initial focus on personal vehicles has resulted in significant control of emissions from these vehicles, and also led to technology transfer to the other mobile source categories that made possible the stringent standards for these other categories.

As a result of Title II requirements, new car s and SUVs sold today have emissions levels of hydrocarbons, oxides of nitrogen, and carbon monoxide that are 98-99% lower than new vehicles sold in the 1960s, on a per mile basis. Similarly, standards established for heavy-duty highway and nonroad sources require emissions rate reductions on the order of 90% or more for particulate matter and oxides of nitrogen. Overall ambient levels of automotive-related pollutants are lower now than in 1970, even as economic growth and vehicle miles traveled have nearly tripled. These programs have resulted in millions of tons of pollution reduction and major reductions in pollution-related deat hs (estimated in the tens of th ousands per year) and illnesses. The net societal benefits of the mobile source programs are large. In its annual reports on federal regulations, the Office of Management and Budget reports that many of EPA’s mobile source emissions standards typically have projected be nefit-to-cost ratios of 5:1 to 10:1 or more. Follow-up studies show that long-term compliance costs to the industry are typically lower than the cost projected by EPA at the time of regulation, which result in even more favorable real world benefit-to-cost ratios. 83 Pollution reductions attributable to Title II mobile source controls are critical components to attainment of primary National Ambient Air Quality Standards, significantly reducing the national inventory and ambient concentrations of criteria pollutants,especially PM2.5 and ozone. See e.g. 69 FR 38958, 38967-68 (June 29, 2004) (controls on nonroad diesel engines expected to reduce entire nati onal inventory of PM2.5 by 3.3% (86,000 tons)

83 OMB, 2011. 2011 Report to Congress on the Benefits and Costs of Federal Regulations and Unfunded Mandates on State, Local, and Tribal Entities. Office of Information and Regulatory Affairs. June. http://www.whitehouse.gov/sites/default/files/omb/info reg/2011_cb/2011_cba_report.pdf. Website accessed on October 11, 2011.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 74 of 768 by 2020). Title II controls have also made enor mous reductions in air toxics emitted by mobile sources. For example, as a result of EPA’s 2007 mobile source air toxics standards, the cancer risk attributable to total mobile source air toxi cs will be reduced by 30% in 2030 and the risk from mobile source benzene (a leukemogen) will be reduced by 37% in 2030. (reflecting reductions of over three hundred thousand tons of mobile source air toxic emissions) 72 FR 8428, 8430 (Feb. 26, 2007).

Title II emission standards have also stimulated the development of a much broader set of advanced automotive technologies, such as on-board computers and fuel injection systems, which are the building blocks of today’s automotive designs and have yielded not only lower pollutant emissions, but improved vehicle pe rformance, reliability, and durability.

This proposal implements a specific provision from Title II, section 202(a). 84 Section 202(a)(1) of the Clean Air Act (CAA) states that “the Administrator sha ll by regulation prescribe (and from time to time revise)...standards appli cable to the emission of any air pollutant from any class or classes of new motor vehicles ..., wh ich in his judgment cause, or contribute to, air pollution which may reasonably be anticipated to endanger public health or welfare.” If EPA makes the appropriate endangerment and cause or contribute findings, then section 202(a) authorizes EPA to issue standards applicab le to emissions of those pollutants.

Any standards under CAA section 202(a)(1) “shall be applicable to such vehicles ... for their useful life.” Emission standards set by the EPA under CAA section 202(a)(1) are technology-based, as the levels chosen must be premised on a finding of technological feasibility. Thus, standards promulgated under CA A section 202(a) are to take effect only “after providing such period as the Administrator finds necessary to permit the development and application of the requisite technology, giving appropriate consideration to the cost of compliance within such period” (section 202 (a)(2); see also NRDC v. EPA , 655 F. 2d 318, 322 (D.C. Cir. 1981)). EPA is afforded considerable discretion under section 202(a) when assessing issues of technical feasibility and availability of lead time to implement new technology. Such determinations are “subject to the restraints of reasonableness”, which “does not open the door to ‘crystal ball’ inquiry.” NRDC , 655 F. 2d at 328, quoting International Harvester Co. v.
Ruckelshaus , 478 F. 2d 615, 629 (D.C. Cir. 1973). However, “EPA is not obliged to provide detailed solutions to every engineering problem posed in the perfection of the trap-oxidizer. In the absence of theoretical objections to the technology, the agency need only identify the major steps necessary for development of the device, and give plausible reasons for its belief that the industry will be able to solve th ose problems in the time remainin g. The EPA is not required to rebut all speculation that unspecified factors may hinder ‘real world’ emission control.” NRDC, 655 F. 2d at 333-34. In developing such technology-based standards, EPA has the discretion to consider different standards for appropriate groupi ngs of vehicles (“class or classes of new motor

84 42 U.S.C. 7521 (a)Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 75 of 768 vehicles”), or a single standard for a larger grou ping of motor vehicles (NRDC, 655 F. 2d at 338).

Although standards under CAA section 202(a)(1) are technology-based, they are not based exclusively on technological capability. EPA has the discretion to consider and weigh various factors along with technological feasibility, such as the cost of compliance (see section 202(a) (2)), lead time necessary for compliance (section 202(a)(2)), safety (see NRDC , 655 F. 2d at 336 n. 31) and other impacts on consumers, 85 and energy impacts associated with use of the technology. 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).

In addition, EPA has clear authority to set standards under CAA section 202(a) that are technology forcing when EPA consid ers that to be appropriate, but is not required to do so (as compared to standards set under provisions such as section 202(a)(3) and section 213(a)(3)). EPA has interpreted a similar statutory pr ovision, CAA section 231, as follows:

While the statutory language of section 231 is not identical to other provisions in title II
of the CAA that direct EPA to establish tec hnology-based standards for various types of engines, EPA interprets its authority under s ection 231 to be somewhat similar to those provisions that require us to identify a reasonable balance of specified emissions reduction, cost, safety, noise, and other factors. See, e.g., Husqvarna AB v. EPA

, 254 F.3d 195 (DC Cir. 2001) (upholding EPA’s promulgation of technology-based standards for small non-road engines under section 213(a)(3) of the CAA). However, EPA is not compelled under section 231 to obtain the ‘‘greatest degree of emission reduction achievable’’ as per sections 213 and 202 of the CAA, and so EPA does not interpret the Act as requiring the agency to give subordinate status to factors such as cost, safety, and noise in determining what standards are reasonable for aircraft engines. Rather, EPA has greater flexibility under section 231 in determining what standard is most reasonable for aircraft engines, and is not required to achieve a ‘‘technology forcing’’ result. 86

This interpretation was upheld as reasonable in NACAA v. EPA , (489 F.3d 1221, 1230 (D.C. Cir. 2007)). CAA section 202(a) does not specify the degree of weight to apply to each factor, and EPA accordingly has discretion in choosing an appropriate balance among factors.
See Sierra Club v. EPA , 325 F.3d 374, 378 (D.C. Cir. 2003) (even where a provision is technology-forcing, the provision “does not resolve how the Administrator should weigh all [the statutory] factors in the process of finding the 'greatest emission reduction achievable’”). Also see Husqvarna AB v. EPA , 254 F. 3d 195, 200 (D.C. Cir. 2001) (great discretion to balance

85 Since its earliest Title II regulations, EPA has considered the safety of pollution control technologies. See 45 Fed.Reg. 14,496, 14,503 (1980).("EPA would not require a pa rticulate control technology that was known to involve serious safety problems. If during the development of the trap-oxidizer safety problems are discovered, EPA would reconsider the control requirements implemented by this rulemaking").

86 70 FR 69664, 69676, November 17, 2005.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 76 of 768 statutory factors in considering level of technol ogy-based standard, and statutory requirement “to [give appropriate] consideration to the cost of applying ... technology” does not mandate a specific method of cost analysis); see also Hercules Inc. v. EPA , 598 F. 2d 91, 106 (D.C. Cir. 1978) (“In reviewing a numerical standard we mu st ask whether the agency’s numbers are within a zone of reasonableness, not whether its numbers are precisely right”); Permian Basin Area Rate

Cases , 390 U.S. 747, 797 (1968) (same); Federal Power Commission v. Conway Corp. , 426 U.S. 271, 278 (1976) (same); Exxon Mobil Gas Marketing Co. v. FERC , 297 F. 3d 1071, 1084 (D.C. Cir. 2002) (same).

a. EPA’s Testing Authority

Under section 203 of the CAA, sales of vehicles are prohibited unless the vehicle is covered by a certificate of conformity. EPA issues certificates of conformity pursuant to section 206 of the Act, based on (necessarily) pre-sale testing conducted either by EPA or by the manufacturer. The Federal Test Procedure (FTP or ‘‘city’’ test) and the Highway Fuel Economy Test (HFET or ‘‘highway’’ test ) are used for this purpose. Compliance with standards is required not only at certification but throughout a vehicle’s useful life, so that testing requirements may continue post-certification. Useful life standards may apply an adjustment
factor to account for vehicle emission control deteri oration or variability in use (section 206(a)).

Pursuant to EPCA, EPA is required to measure fuel economy for each model and to calculate each manufacturer’s average fuel economy. 87 EPA uses the same tests – the FTP and HFET – for fuel economy testing. EPA established the FTP for emissions measurement in the early 1970s. In 1976, in response to the Energy Policy and Conservation Act (EPCA) statute, EPA extended the use of the FTP to fuel economy measurement and added the HFET. 88 The provisions in the 1976 regulation, effective with the 1977 model year, established procedures to calculate fuel economy values both for labeling and for CAFE purposes. Under EPCA, EPA is required to use these procedures (or procedures which yield comparable results) for measuring fuel economy for cars for CAFE purposes, but not for labeling purposes. 89 EPCA does not pose this restriction on CAFE test procedures for li ght trucks, but EPA does use the FTP and HFET for this purpose. EPA determines fuel economy by measuring the amount of CO 2 and all other carbon compounds (e.g. total hydrocarbons (THC) and carbon monoxide (CO)), and then, by mass balance, calculating the amount of fuel consumed. EPA’s proposed changes to the procedures for measuring fuel economy and calcu lating average fuel economy are discussed in
section III.B.10.

87 See 49 U.S.C. 32904(c).

88 See 41 FR 38674 (Sept. 10, 1976), which is codified at 40 CFR Part 600.

89 See 49 U.S.C. 32904(c).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 77 of 768 b. EPA Enforcement Authority

Section 207 of the CAA grants EPA broad authority to require manufacturers to remedy vehicles if EPA determines there are a substantial number of noncomplying vehicles. In addition, section 205 of the CAA authorizes EPA to assess penalties of up to $37,500 per vehicle for violations of various prohibited acts specified in the CAA. In determining the appropriate penalty, EPA must consider a variety of factors such as the gravity of the violation, the economic impact of the violation, the violator’s history of compliance, and “such other matters as justice may require.” Unlike EPCA, the CAA does not authorize vehicle manufacturers to pay fines in lieu of meeting emission standards.

c. Compliance

EPA oversees testing, collects and processes test data, and performs calculations to determine compliance with both CAA and CAFE standards. CAA standards apply not only at the time of certification but also throughout the vehicle’s useful life, and EPA is accordingly is proposing in-use standards as well as standards based on testing performed at time of production. See section III.E. Both the CAA and EPCA provide for penalties should manufacturers fail to comply with their fleet average standards, but, unlike EPCA, there is no option for manufacturers to pay fines in lieu of compliance with the st andards. Under the CAA, penalties are typically determined on a vehicle-specific basis by determining the number of a manufacturer’s highest emitting vehicles that cause the fleet average standard violation. Penalties under Title II of the CAA are capped at $25,000 per day of violation and apply on a per vehicle basis. CAA section 205 (a).

d. Test Procedures

EPA establishes the test procedures under which compliance with both the CAA GHG standards and the EPCA fuel economy standards are measured. EPA’s testing authority under the CAA is flexible, but testing for fuel economy for passenger cars is by statute is limited to the Federal Test procedure (FTP) or test procedures which provide results which are equivalent to the FTP. 49 USC section 32904 and section III.B, below. EPA developed and established the FTP in the early 1970s and, after enactment of EPCA in 1976, added the Highway Fuel Economy Test to be used in conjunction with the FTP for fuel economy testing. EPA has also developed tests with additional cycles (the so-calle d 5-cycle test) which test is used for purposes of fuel economy labeling and is also used in the EPA program for extending off-cycle credits under both the light-duty and (along with NHTSA) heavy-duty vehicle GHG programs. See 75 FR at 25439; 76 FR at 57252. In this rule, EPA is proposing to retain the FTP and HFET for purposes of testing the fleetwide average standards, and is further proposing modifications to the N2O measurement test pr ocedures and the A/C CO2 efficien cy test procedures EPA initially adopted in the 2012-2016 rule.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 78 of 768 3. Comparing the Agencies’ Authority

As the above discussion makes clear, there are both important differences between the statutes under which each agency is acting as well as several important areas of similarity. One important difference is that EPA’s authority addresses various GHGs, while NHTSA’s authority addresses fuel economy as measured under specifi ed test procedures and calculated by EPA. This difference is reflected in this rulemaking in the scope of the two standards: EPA’s proposal takes into account reductions of direct air cond itioning emissions, as well as proposed standards for methane and N 2 O, but NHTSA’s does not, because these things do not relate to fuel economy. A second important difference is that EPA is proposing certain compliance flexibilities, such as the multipli er for advanced technology vehi cles, and takes those flexibilities into account in its technical analysis and modeling supporting its proposal. EPCA specifies a number of particular compliance flexibilities fo r CAFE, and expressly prohibits NHTSA from considering the impacts of those statutory compli ance flexibilities in setting the CAFE standard so that the manufacturers’ election to avail th emselves of the permitted flexibilities remains strictly voluntary. 90 The Clean Air Act, on the other hand, contains no such prohibition. These considerations result in some differences in the technical analysis and modeling used to support EPA’s and NHTSA’s proposed standards.

Another important area where the two agencies’ authorities are similar but not identical involves the transfer of credits between a single firm’s car and truck fleets. EISA revised EPCA to allow for such credit transfers, but placed a cap on the amount of CAFE credits which can be transferred between the car and truck fleets. 49 U.S.C. 32903(g)(3). Under CAA section 202(a), EPA is proposing to continue to allow CO2 credit transfers between a single manufacturer’s car and truck fleets, with no corresponding limits on such transfers. In general, the EISA limit on CAFE credit transfers is not expected to have the practical effect of limiting the amount of CO2 emission credits manufacturers may be able to transfer under the CAA program, recognizing that manufacturers must comply with both the pr oposed CAFE standards and the proposed EPA standards. However, it is possible that in so me specific circumstances the EPCA limit on CAFE credit transfers could c onstrain the ability of a manufacturer to achieve cost savings through unlimited use of GHG emissions credit transfers under the CAA program.

These differences, however, do not change the fact that in many critical ways the two agencies are charged with addressing the same basic issue of reducing GHG emissions and improving fuel economy. Given the dir ect relationship between emissions of CO 2 and fuel economy levels, both agencies are looking at the same set of control technologies (with the exception of the air conditioning leakage-relate d technologies). The standards set by each agency will drive the kind and degree of penetratio n of this set of technologies across the vehicle fleet. As a result, each agency is trying to answer the same basic question – what kind and degree of technology penetration is necessary to achieve the agencies’ objectives in the rulemaking time frame, given the agenci es’ respective statutory authorities?Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 79 of 768 In making the determination of what standards are appropriate under the CAA and EPCA, each agency is to exercise its judgment and balance many similar factors. NHTSA’s factors are provided by EPCA: technological fe asibility, economic practicability, the effect of other motor vehicle standards of the Government on fuel economy, and the need of the United States to conserve energy. EPA has the discretion under the CAA to consider many related factors, such as the availability of technologi es, the appropriate lead time for introduction of technology, and based on this the feasibility and pr acticability of their standards; the impacts of their standards on emissions reductions (of both GHGs and non-GHGs); the impacts of their standards on oil conservation; the impacts of their standards on fuel savings by consumers; the impacts of their standards on the auto industry; as well as other relevant factors such as impacts on safety. Conceptually, therefore, each agency is considering and balancing many of the same concerns, and each agency is making a decision that at its core is answering the same basic question of what kind and degree of technology penetration is it appropriate to call for in light of all of the relevant factors in a given rulemaking, for the model years concerned. Finally, each agency has the authority to take into consideration impacts of the standards of the other agency. EPCA calls for NHTSA to take into considerati on the effects of EPA’s emissions standards on fuel economy capability (see 49 U.S.C. 32902 (f)), and EPA has the discretion to take into consideration NHTSA’s CAFE standards in determ ining appropriate action under section 202(a). This is consistent with the S upreme Court’s statement that EPA’s mandate to protect public health and welfare is wholly independent from NHTSA’s mandate to promote energy efficiency, but there is no reason to think the two agencies cannot both administer their obligations and yet avoid inconsistency. Massachusetts v. EPA , 549 U.S. 497, 532 (2007).

In this context, it is in the Nation’s interest for the two agencies to continue to work together in developing their respective proposed standards, and they have done so. For example, the agencies have committed considerable effort to develop a joint Technical Support Document that provides a technical basis underlying each agency’s analyses. The agencies also have worked closely together in developing and revi ewing their respective modeling, to develop the best analysis and to promote technical consistency. The agencies have developed a common set of attribute-based curves that each agency su pports as appropriate both technically and from a policy perspective. The agencies have also worked closely to ensure that their respective programs will work in a coordi nated fashion, and will provide regulatory compatibility that allows auto manufacturers to build a single natio nal light-duty fleet that would comply with both the GHG and the CAFE standards. The resulting overall close coordination of the proposed GHG and CAFE standards should not be surprising, however, as each agency is using a jointly developed technical basis to address the closely intertwined challenges of energy security and climate change.

As set out in detail in Sections III and IV of this notice, both EPA and NHTSA believe the agencies’ proposals are fully justified under their respective statutory criteria. The proposed standards are feasible in each model year within the lead time provided, based on the agencies’ projected increased use of various technologies wh ich in most cases are already in commercial application in the fleet to varying degrees. Detailed modeling of the technologies that could be employed by each manufacturer supports this in itial conclusion. The agencies also carefully assessed the costs of the proposed rules, both for the industry as a whole and per manufacturer, as well as the costs per vehicle, and consider these costs to be reasonable during the rulemaking time frame and recoverable (from fuel savings). The agencies recogni ze the significant increaseSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 80 of 768 in the application of technology that the pr oposed standards would require across a high percentage of vehicles, which will require the manufacturers to devote co nsiderable engineering and development resources before 2017 laying the critical foundation for the widespread deployment of upgraded technology across a hi gh percentage of the 2017-2025 fleet. This clearly will be challenging for au tomotive manufacturers and thei r suppliers, especially in the current economic climate, and given the stringency of the recently-established MYs 2012-2016 standards. However, based on all of the analyses performed by the agencies, our judgment is that it is a challenge that can reasonably be met.

The agencies also evaluated the impacts of th ese standards with respect to the expected reductions in GHGs and oil consumption and, fou nd them to be very significant in magnitude. The agencies considered other factors such as the impacts on noise, energy, and vehicular congestion. The impact on safety was also given careful consideration. Moreover, the agencies quantified the various costs and benefits of the pro posed standards, to the extent practicable. The agencies’ analyses to date indicate that the over all quantified benefits of the proposed standards far outweigh the projected costs. All of these f actors support the reasonableness of the proposed standards. See section III (proposed GHG standard s) and section IV (proposed CAFE standards) for a detailed discussion of each agency’s basis for its selection of its proposed standards.

The fact that the benefits are estimated to considerably exceed their costs supports the view that the proposed standards represent an appropriate balance of the relevant statutory factors. In drawing this conclusion, the agencies acknowledge the uncertainties and limitations of the analyses. For example, the analysis of the benefits is highly dependent on the estimated price of fuel projected out many years into the fu ture. There is also significant uncertainty in the potential range of values that could be assigned to the social cost of carbon. There are a variety of impacts that the agencies are unable to quantify, such as non-market damages, extreme weather, socially contingent effects, or the potential for longer-term catastrophic events, or the impact on consumer choice. The cost-benefit analyses are one of the important things the agencies consider in making a judgment as to the appropriate standards to propose under their respective statutes. Consideration of the results of the cost-benefit analyses by the agencies, however, includes careful consideration of the limitations discussed above.

II. Joint Technical Work Completed for This Proposal

E. Introduction

In this section, NHTSA and EPA discuss several aspects of their joint technical analyses. These analyses are common to the development of each agency’s standards. Specifically we discuss: the development of the vehicle market forecast used by each agency for assessing costs, benefits, and effects, the development of the attribute-based standard curve shapes, the technologies the agencies evaluated and their co sts and effectiveness, the economic assumptions the agencies included in their analyses, a desc ription of the air conditioning and off-cycle technology (credit) programs, as well as the effects of the proposed standards on vehicle safety. The Joint Technical Support Document (TSD) discusses the agencies’ joint technical work in
more detail.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 81 of 768 The agencies have based today’s proposal on a very significant body of data and analysis that is the best information currently available on th e full range of technical inputs utilized in our respective analyses. As noted in various places throughout this preamble, the draft Joint TSD, the NHTSA preliminary RIA, and the EPA draft RIA we expect new information will become available between the proposal and final rulemaki ng. This new information will come from a range of sources: some is based on work the agencies have underway (e.g., work on technology costs and effectiveness, potentially updating our baseline year from model year 2008 to model year 2010); other sources are those we expect to be released by others (e.g., the Energy Information Agency’s Annual Energy Outlook, which is published each year, and which we expect to use the most recent available for the final rule); and other information will likely come from the public comment process. The agencies intend to evaluate all such new information as it becomes available, and where appropriate to update their analysis for purposes of the final rule. In addition, new information or analyses may be made available in the agencies’ respective public dockets for this rulemaking prior to the final rule, where that is appropriate. We encourage all stakeholders to periodically check the two agencies’ dockets between the proposal and final rules for any potential new docket submissions.

F. Developing the Future Fleet for Assessing Costs, Benefits, and Effects

1. Why Did the Agencies Establish a Baseline and Reference Vehicle Fleet?

In order to calculate the impacts of the EPA and NHTSA regulations, it is necessary to estimate the composition of th e future vehicle fleet absent these regulations, to provide a reference point relative to which costs, benefits, and effects of the regulations are assessed. As in the 2012-2016 light duty vehicle rulemaking, EPA and NHTSA have developed this comparison fleet in two parts. The first step was to develop a baseline fleet based on model year
2008 data. This baseline 2008-based fleet includes vehicle sales volumes, GHG/fuel economy performance, and contains a listing of the base technologies on every 2008 vehicle sold. The second step was to project that baseline 2008-based fleet volume into model years 2017-2025. The vehicle volumes projected out to MY 2025 is referred to as the reference fleet volumes. The third step was to modify that MY 2017-2025 refe rence fleet such that it reflects technology manufacturers could apply if MY 2016 standards are extended without change through MY

2025. 91 The agencies assume that without adoption of the proposed rule that during the 2017 to 2025 period, manufacturers will not improve fuel economy levels beyond th e levels required in the MY 2016 standards. However, it is possible that manufacturers may be driven by market changes to adopt higher fuel economy. The recently adopted fuel economy labels may consumers more aware of the benefits of higher fuel economy and they may demand more fuel

91 EPA’s MY 2016 GHG standards under the CAA continue into the future until they are changed. While NHTSA must actively promulgate standards in order for CAFE sta ndards to extend past MY 2016, the agency has, as in all recent CAFE rulemakings, defined a no-action ( i.e. , baseline) regulatory alternative as an indefinite extension of the last-promulgated CAFE standards for purposes of the main analysis of the sta ndards in this preamble.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 82 of 768 efficient vehicles. Also, the agencies’ analysis indicates that some fuel-saving technologies may save money for manufacturers. In Section X of its RIA, NHTSA examines the impact of an alternative “market-driven” baseline, which allows for some fuel economy beyond the MY 2016 levels. The agencies seek comment on what assumptions about fuel economy are most likely to accurately predict what would happen in the absence of the proposed rule.

Each agency used its modeling system to develop a modified or final reference fleet, or adjusted baseline, for use in its analysis of regul atory alternatives, as di scussed below in Chapter 1 of the EPA draft RIA and [insert reference to DOT section], and in the agencies’ respective preliminary regulatory impact analyses. All of the agencies’ estimates of emission reductions, fuel economy improvements, costs, and societal impacts are developed in relation to the respective reference fleets. This section discusses the first two steps, development of the
baseline fleet and the reference fleet.

EPA and NHTSA used a transparent approach to developing the baseline and reference fleets, largely working from publicly available data. Because both input and output sheets from our modeling are public, stakeholders can verify and check EPA’s and NHTSA’s modeling, and perform their own analyses with these datasets. 92 However, the agencies also compared their predictions with manufacturers’ confidential business plans to ensure that they are consistent.

2. How Did the Agencies Develop the Baseline Vehicle Fleet?

NHTSA and EPA developed a baseline fleet comprised of model year 2008 data gathered from EPA’s emission and fuel economy database. This baseline fleet was originally developed by EPA and NHTSA for the 2012-2016 final rule, and was updated for this proposal. 93 The new fleet has the model year 2008 vehicle’s volumes and attributes along with the addition of projected volumes from 2017 to 2025. It also has some expanded footprint data for pickup trucks that was needed for a more detailed analysis of the truck curve.

In this proposed rulemaking, the agencies are again choosing to use model year 2008 vehicle data to be the basis of the baseline fleet, but for different reasons than in the 2012-2016 final rule. Model year 2008 is now the most recent model year for wh ich the industry had normal sales. Model year 2009 data is available, but the agencies believe that model year was disrupted by the economic downturn and the bankruptcies of both General Motors and Chrysler resulting in a significant reduction in the number of vehicles sold by both companies and the industry as a whole. These abnormalities led th e agencies to conclude that 2009 data was not representative for projecting the future fleet. Model Year 2010 data was not complete because

92 EPA’s Omega Model and input sheets are available at http://www.epa.gov/oms/climate/models.htm ; DOT/NHTSA’s CAFE Compliance and Effects Modeling Sy stem (commonly known as the “Volpe Model”) and input and output sheets are available at http://www.nhtsa.gov/fuel-economy [we’ll have a more specific cite once we get the website settled, making changes right now].

93 Further discussion of the development of the 2008 baseline fleet for the MY2012-2016 rule can be found at 75 Fed. Reg. 25324, 25349 (May 7, 2010). Comment [A1]: Interaegncy commenters request clarity on whether agencies did this?Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 83 of 768 not all manufacturers have yet submitted it to EPA, and was thus not available in time for it to be used for this proposal. Therefore, the agencies chose to use model year 2008 again as the baseline since it was the latest complete repres entative and transparent data set available. However, the agencies will consider using Model Year 2010 for the final rule, based on availability and an analysis of the data representativeness. To the extent the MY 2010 data becomes available during the comment period the ag encies will place a copy of this data in our respective dockets. We request comments on the relative merits of using MY 2008 and MY 2010 data, and whether one provides a better foundation than the other for purposes of using such data as the foundation for a market forecast extending through MY 2025.

The baseline fleet reflects all fuel economy technologies in use on MY 2008 light duty vehicles. The 2008 emission and fuel economy database included data on vehicle production volume, fuel economy, engine size, number of engine cylinders, transmission type, fuel type, etc., however it did not contain complete informa tion on technologies. Thus, the agencies relied on publicly available data like the more complete technology descriptions from Ward’s Automotive Group. 94 In a few instances when required vehicle information (such as vehicle footprint) was not available from these two sour ces, the agencies obtained this information from publicly accessible internet sites such as Motortrend.com and Edmunds.com. 95 A description of all of the technologies used in modeling the 2008 vehicle fleet and how it was constructed are available in Chapter 1 of the Joint Draft TSD.

Footprint data for the baseline fleet came mainly from internet searches, though detailed information about the pickup truck footprints with volumes was not available online. Where this information was lacking, the agencies used manufacturer product plan data for 2008 model year to find out the correct number footprint and dist ribution of footprints. The footprint data for pickup trucks was expanded from the original data used in the previous rulemaking. The agencies obtained this footprint data from MY 2008 product plans submitted by the various manufacturers, which can be made public at this time because by now all MY 2008 vehicle models are already in production, which makes footprint data about them essentially public information. A description of exactly how the agen cies obtained all the footprints is available in Chapter 1 of the TSD.

3. How Did the Agencies Develop the Projected MY 2017-2025 Vehicle Reference
Fleet?

As in the 2012-2016 light duty vehicle rulemaking, EPA and NHTSA have based the projection of total car and total light truck sales for MYs 2017-2025 on projections made by the Department of Energy’s Energy Information Administration (EIA). See 75 FR at 25349. EIA publishes a mid-term projection of national energy use called the Annual Energy Outlook

94 Note that WardsAuto.com is a fee-based service, but all information is public to subscribers.

95 Motortrend.com and Edmunds.com are free, no-fee internet sites.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 84 of 768 (AEO). This projection utilizes a number of technical and econometric models which are designed to reflect both economic and regulatory conditions expected to exist in the future. In support of its projection of fuel use by light- duty vehicles, EIA projects sales of new cars and light trucks. EIA published its Early Annual Energy Outlook for 2011 in December 2010. EIA released updated data to NHTSA in February (In terim AEO). The final release of AEO for 2011 came out in May 2011, but by that time EPA/NHTSA had already prepared modeling runs for potential 2017-2025 standards using the interim data release to NHTSA. EPA and NHTSA are using the interim data release for this proposal , but intend to use the newest version of AEO
available for the FRM.

The agencies used the Energy Informati on Administration’s (EIA’s) National Energy Modeling System (NEMS) to estimate the future relative market shares of passenger cars and light trucks. However, NEMS methodology include s shifting vehicle sales volume, starting after 2007, away from fleets with lower fuel economy (the light-truck fleet) towards vehicles with higher fuel economies (the passenger car fleet) in order to facilitate projected compliance with
CAFE and GHG standards. Because we use our ma rket projection as a baseline relative to which
we measure the effects of new st andards, and we attempt to estimate the industry’s ability to comply with new standards without changing product mix ( i.e. , we analyze the effects of the proposed rules assuming manufacturers will not change fleet composition as a compliance strategy, as opposed to changes that might happen due to market forces), the Interim AEO 2011- projected shift in passenger car market share as a result of required fuel economy improvements creates a circularity. Therefore, for the current analysis, the agencies developed a new projection of passenger car and light truck sales shares by running scenarios from the Interim AEO 2011
reference case that first deactivate the above -mentioned sales-volume shifting methodology and then hold post-2017 CAFE standards constant at MY 2016 levels. As discussed in Chapter 1 of the agencies’ joint Technical Support Document, incorporating these changes reduced the NEMS-projected passenger car share of the ligh t vehicle market by an average of about 5% during 2017-2025.

In the AEO 2011 Interim data, EIA projects that total light-duty vehicle sales will gradually recover from their currently depressed levels by around 2013. In 2017, car sales are projected to be 8.4 million (53 percent) and truck sales are projected to be 7.3 million (47 percent). Although the total level of sales of 15.8 million units is similar to pre-2008 levels, the fraction of car sales is projected to be higher than that existing in the 2000-2007 timeframe. This projection reflects the impact of assumed higher fu el prices. Sales projections of cars and trucks for future model years can be found in Chapter 1 of the joint TSD.

In addition to a shift towards more car sales, sales of segm ents within both the car and truck markets have been changing and are expected to continue to change. Manufacturers are introducing more crossover models which offer much of the utility of SUVs but use more carlike designs. The AEO 2011 report does not, howev er, distinguish such changes within the carSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 85 of 768 and truck classes. In order to reflect these changes in fleet makeup, EPA and NHTSA used CSM Worldwide (CSM) as they did in the 2012-2016 rulemaking analysis. EPA and NHTSA believe that CSM is the best source available for a long range forecast for 2017-2025, though when EPA and NHTSA contacted several forecasting firms none of them offered comparably-detailed forecasting for that time frame. NHTSA and EPA decided to use the forecast from CSM for several reasons presented in the Joint TSD chapter I.

The long range forecast from CSM Worldwide is a custom forecast covering the years 2017-2025 which the agencies purchased from CSM in December of 2009. CSM provides quarterly sales forecasts for the automotive industry, and updates their data on the industry quarter. For the public’s reference, a copy of CSM’s long range forecast has been placed in the docket for this rulemaking. 96 EPA and NHTSA hope to purchase and use an updated forecast, whether from CSM or other appropriate sources, before the final rulemaking. To the extent that such a forecast becomes available during the comment period the agencies will place a copy in our respective dockets.

The next step was to project the CSM forecasts for relative sales of cars and trucks by manufacturer and by market segment onto the total sales estimates of AEO 2011. Table 0-1 and Table 0-2 show the resulting projections for the reference 2025 model year and compare these to actual sales that occurred in the baseline 2008 model year. Both tables show sales using the traditional definition of cars and light trucks.

Table 0-1 Annual Sales of Light-Duty Vehicles by Manufacturer in 2008 and Estimated for 2025

Cars Light Trucks Total

2008 MY 2025 MY 2008 MY 2025 MY 2008 MY 2025 MY
Aston Martin 1,370 1,182 0 0 1,370 1,182

BMW 291,796 405,256 61,324 145,409 353,120 550,665 Chrysler/Fiat 703,158 436,479 956,792 331,762 1,659,950 768,241 Daimler 208,195 340,719 79,135 101,067 287,330 441,786 Ferrari 1,450 7,658 0 0 1,450 7,658 Ford 956,699 1,540,109 814,194 684,476 1,770,893 2,224,586 Geely/Volvo 65,649 101,107 32,748 42,588 98,397 143,696
GM 1,587,391 1,673,936 1,507,797 1,524,008 3,095,188 3,197,943 Honda 1,006,639 1,340,321 505,140 557,697 1,511,779 1,898,018 Hyundai 337,869 677,250 53,158 168,136 391,027 845,386

96 The CSM Sales Forecast Excel file (“CSM North Amer ica Sales Forecasts 2017-2025 for the Docket”) is available in the docket (Docket EPA-HQ-OAR-2010-0799).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 86 of 768 Kia 221,980 362,783 59,472 97,653 281,452 460,436

Lotus 252 316 0 0 252 316 Mazda 246,661 306,804 55,885 61,368 302,546 368,172 Mitsubishi 85,358 73,305 15,371 36,387 100,729 109,692 Nissan 717,869 1,014,775 305,546 426,454 1,023,415 1,441,229 Porsche 18,909 40,696 18,797 11,219 37,706 51,915 Spyker/Saab 21,706 23,130 4,250 3,475 25,956 26,605 Subaru 116,035 256,970 82,546 74,722 198,581 331,692 Suzuki 79,339 103,154 35,319 21,374 114,658 124,528 Tata/JLR 9,596 65,418 55,584 56,805 65,180 122,223 Tesla 800 31,974 0 0 800 31,974 Toyota 1,260,364 2,108,053 951,136 1,210,016 2,211,500 3,318,069 Volkswagen 291,483 630,163 26,999 154,284 318,482 784,447 Total 8,230,568 11,541,560 5,621,193 5,708,899 13,851,761 17,250,459

Table 0-2 Annual Sales of Light-Duty Vehicles by Market Segment in 2008 and Estimated for 2025

Cars Light Trucks

2008 MY 2025 MY 2008 MY 2025 MY Full-Size Car 829,896 245,355 Full-Size Pickup 1,332,335 1,002,806 Luxury Car 1,048,341 1,637,410 Mid-Size Pickup 452,013 431,272 Mid-Size Car 2,103,108 2,713,078 Full-Size Van 33,384 88,572 Mini Car 617,902 1,606,114 Mid-Size Van 719,529 839,452 Small Car 1,912,736 2,826,190 Mid-Size MAV* 110,353 548,457 Specialty Car 469,324 808,183 Small MAV 231,265 239,065 Full-Size SUV* 559,160 46,978 Mid-Size SUV 436,080 338,849 Small SUV 196,424 71,827 Full-Size CUV* 264,717 671,665 Mid-Size CUV 923,165 1,259,483 Small CUV 1,612,029 1,875,703 Total Sales** 6,981,307 9,836,330 6,870,454 7,414,129
* MAV – Multi-Activity Vehicle, SUV – Sport Utility Vehicle, CUV – Crossover Utility Vehicle **Total Sales are based on the classic Car/Truck definition.

As mentioned previously, NHTSA has changed the definition of a truck for 2011 model year and beyond. The new definition has moved some 2 wheel drive SUVs and CUVs to the car category. Table 0-3 shows the different volumes for car and trucks based on the new and oldSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 87 of 768 NHTSA definition. The table shows the difference in 2008, 2021, and 2025 to give a feel for how the change in definition changes the car/truck split.

Table 0-3 New and Old Car and Truck definition in 2008, 2016, 2021, and 2025

Vehicle Type 2008 2016 2021 2025
Old Cars Definition 6,981,307 8,576,717 8,911,173 9,836,330 New Cars Definition 8,230,568 7,618,459 10,505,165 11,541,560

Old Truck Definition 6,870,454 10,140,463 7,277,894 7,414,129
New Truck Definition 5,621,193 6,054,713 5,683,902 5,708,899

The CSM forecast provides estimates of car and truck sales by segment and by manufacturer separately. The forecast was broken up into two tables. One table with manufacturer volumes by year and the other with vehicle segments percentages by year. Table 0-4 and Table 0-5 are examples of the data received from CSM. The task of estimating future sales using these tables is complex. We used the same methodology as in the previous rulemaking. A detailed description of how the projection process was done is found in Chapter 1
of the TSD.

Table 0-4 CSM Manufacturer Volumes in 2016, 2021, and 2025

2016 2021 2025

BMW 328,220 325,231 317,178 Chrysler/Fiat 391,165 346,960 316,043

Daimler 298,676 272,049 271,539

Ford* 971,617 893,528 858,215

Subaru 205,486 185,281 181,062

General Motors 1,309,246 1,192,641 1,135,305

Honda 1,088,449 993,318 984,401 Hyundai 429,926 389,368 377,500

Kia 234,246 213,252 205,473

Mazda 215,117 200,003 199,193

Mitsubishi 47,414 42,693 42,227 Spyker/Saab 66 6

Tesla 800 800 800

Aston Martin 1,370 1,370 1,370Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 88 of 768 Lotus 252 252 252

Porsche 12 12 12

Nissan 803,177 729,723 707,361

Suzuki 88,142 81,042 76,873

Tata/JLR 58,594 53,143 52,069 Toyota 1,751,661 1,576,499 1,564,975 Volkswagen 578,420 530,378 494,596

*Ford volumes include Volvo in this table.

Table 0-5 CSM Segment Percentages in 2016, 2021, and 2025

2016 2021 2025

Full-Size CUV 3.66% 8.34% 9.06% Full-Size Pickup 19.39% 15.42% 13.53%
Full-Size SUV 3.27% 0.90% 0.63%
Full-Size Van 0.92% 1.29% 1.19%
Mid-Size CUV 19.29% 16.88% 16.99%
Mid-Size MAV 1.63% 5.93% 7.40% Mid-Size Pickup 4.67% 5.74% 5.82%
Mid-Size SUV 2.28% 4.73% 4.57%
Mid-Size Van 11.80% 11.63% 11.32%
Small CUV 30.67% 25.06% 25.30%
Small MAV 0.88% 2.98% 3.22% Small Pickup 0.00% 0.00% 0.00%
Small SUV 1.53% 1.12% 0.97%

The overall result was a projection of car and truck sales for model years 2017-2025--the reference fleet--which matched the total sales projections of the AEO forecast and the manufacturer and segment splits of the CSM forecast. These sales splits are shown in Table 0-6
below.

Table 0-6 Car and Truck Volumes and Split Based on NHTSA New Truck Definition

2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

Car Volume* 10,140 9,988 9,905 9,996 10,292 10,505 10,736 10,968 11,258 11,542

Truck Volume* 6,054 5,819 5,671 5,583 5,604 5,684 5,704 5,687 5,676 5,709 Car Split 62.6% 63.2% 63.6% 64.2% 64.7% 64.9% 65.3% 65.9% 66.5% 66.9% Truck Split 37.4% 36.8% 36.4% 35.8% 35.3% 35.1% 34.7% 34.1% 33.5% 33.1%

*in thousandsSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 89 of 768 Given publicly- and commercially-available sources that can be made equally transparent to all reviewers, the forecast described above re presents the agencies’ best technical judgment regarding the likely composition direction of th e fleet. EPA and NHTSA recognize that it is impossible to predict with certainty how manufac turers’ product offering s and sales volumes will evolve through MY 2025 under baseline cond itions—that is, without further changes in standards after MY 2016. The agencies have not developed alternative market forecasts to examine corresponding sensitivity of analytical results discussed below, and have not varied the market forecast when conducting probabilistic uncertainty analysis discussed in NHTSA’s preliminary Regulatory Impact Analysis. The agencies invite comment regarding alternative methods or projections to inform forecasts of th e future fleet at the level of specificity and technical completeness required by the agencies’ respective modeling systems.

The final step in the construction of the final reference fleet involves applying additional technology to individual vehicle models—that is, technology beyond that already present in MY 2008——reflecting already-promulgated standards through MY 2016, and reflecting the assumption that MY 2016 standards would apply through MY 2025. A description of the agencies’ modeling work to develop their respective final reference (or adjusted baseline) fleets appear below in Sections III and IV of this preamble.

C. Development of Attribute-Based Curve Shapes

1. Why are standards attribute-based and defined by a mathematical function?

As in the MYs 2012-2016 CAFE/GHG rules, and as NHTSA did in the MY 2011 CAFE rule, NHTSA and EPA are proposing to set attribute-based CAFE and CO 2 standards that are defined by a mathematical function. EPCA, as am ended 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. 97 The CAA has no such requirement, although such an approach is permissible under section 202 (a) and EPA has used the attribute-based approach in issuing stan dards under analogous provisions of the CAA ( e.g. , criteria pollutant standards for non-road diesel engines using engine size as the attribute, 98 in the recent GHG standards for heavy duty pickups and vans using a work factor attribute, 99 and in the MYs 2012-2016 GHG rule itself which used vehicle footprint as the attribute). Public comments on the MYs 2012-2016 rulemaking widely supported attribute-based standards for both agencies’
standards.

Under an attribute-based standard, every ve hicle model has a performance target (fuel economy and CO 2 emissions for CAFE and CO 2 emissions standards, respectively), the level of

97 49 U.S.C. 32902(a)(3)(A).

98 69 FR 38958 (June 29, 2004).

99 76 FR 57106, 57162-64, (Sept. 15, 2011).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 90 of 768 which depends on the vehicle’s attribute (for this proposal, footprint, as discussed below). The manufacturers’ fleet average performance is determined by the production-weighted 100 average (for CAFE, harmonic average) of those targets.

The agencies believe that an attribute-based standard is preferable to a single-industrywide average standard in the context of CAFE and CO 2 standards for several reasons. First, if the shape is chosen properly, every manufacturer is more likely to be required to continue adding more fuel efficient technology each year across their fleet, because the stringency of the compliance obligation will depend on the part icular product mix of each manufacturer.
Therefore a maximum feasible attr ibute-based standard will tend to require greater fuel savings
and CO 2 emissions reductions overall than would a maximum feasible flat standard (that is, a single mpg or CO 2 level applicable to every manufacturer).

Second, depending on the attribute, attribute-based standards reduce the incentive for
manufacturers to respond to CAFE and CO 2 standards in ways harmful to safety



## . 101 Because each vehicle model has its own target (based on the attribute chosen), properly fitted attributebased standards provide little, if any, incentive to build smaller vehicles simply to meet a fleetwide average, because the smaller vehicles will be subject to more stringent compliance
targets. 102

Third, attribute-based standards provide a more equitable regulatory framework for
different vehicle manufacturers. 103 A single industry-wide average standard imposes disproportionate cost burdens and compliance diffi culties on the manufacturers that need to change their product plans to meet the standard s, and puts no obligation on those manufacturers that have no need to change their plans. As discussed above, attribute-based standards help to spread the regulatory cost burden for fuel economy more broadly across all of the vehicle manufacturers within the industry.

Fourth, attribute-based standards better respect economic conditions and consumer choice, as compared to single-value standards. A flat, or single value standard, encourages a certain vehicle size fleet mix by creating incenti ves for manufacturers to use vehicle downsizing as a compliance strategy. Under a footprint-base d standard, manufacturers are required to invest in technologies that improve the fuel economy of the vehicles they sell rather than shifting the

100 Production for sale in the United States.

101 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 2002 NAS Report at 5, finding 12. Ensuing analyses, including by NHTSA, sup port 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.

102 Assuming that the attribute is related to vehicle size.

103 Id . at 4-5, finding 10.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 91 of 768 product mix, because reducing the size of the vehicle is generally a less viable compliance strategy given that smaller vehicles have more stringent regulatory targets.

2. What attribute are the agencies proposing to use, and why?

As in the MYs 2012-2016 CAFE/GHG rules, and as NHTSA did in the MY 2011 CAFE rule, NHTSA and EPA are proposing to set CAFE and CO 2 standards that are based on vehicle footprint, which has an observable correlation to fuel economy and emissions. There are several policy and technical reasons why NHTSA and EPA be lieve that footprint is the most appropriate attribute on which to base the standards, even th ough some other vehicle attributes (notably curb weight) are better correlated to fuel economy and emissions.

First, in the agencies’ judgment, from the sta ndpoint of vehicle safety, it is important that
the CAFE and CO 2 standards be set in a way that does not encourage manufacturers to respond by selling vehicles that are in any way less safe . While NHTSA’s research of historical crash
data also indicates that reductions in vehicle mass that are accompanied by reductions in vehicle footprint tend to compromise vehicle safety, footprint-based standards provide an incentive to use advanced lightweight materials and structures that would be discouraged by weight-based standards, because manufacturers can use them to improve a vehicle’s fuel economy and CO 2 emissions without their use necessarily resulting in a change in the vehicle’s fuel economy and emissions targets.

Further, although we recognize that weight is better correlated with fuel economy and

CO 2 emissions than is footprint, we continue to believe that there is less risk of “gaming” (changing the attribute(s) to achieve a more favorable target) by increasing footprint under footprint-based standards than 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 compar ed to increasing vehicle footprint. We also continue to agree with concerns raised in 2008 by some commenters on the MY 2011 CAFE rulemaking 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. The agencies agree with the assessment first presented in NHTSA’s MY 2011 CAFE final rule 104
that the possibility of gaming is lowest with footprint-based standards, as opposed to weightbased 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 fre edom with respect to more easily-adjusted attributes, they could make it less certain that the future fleet would actually achieve the average fuel economy and CO 2 reduction levels projected by the agencies.

104 See 74 FR at 14359 (Mar. 30, 2009).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 92 of 768 The agencies recognize that based on economic and consumer demand factors that are external to this rule, the distribution of footprints in the future may be different (either smaller or larger) than what is projected in this rule. Howe ver, the agencies continue to believe that there will not be significant shifts in this distributi on as a direct consequence of this proposed rule. The agencies also recognize that some internationa l attribute-based standard s use attributes other than footprint and that there could be benefits for a number of manufacturers if there was greater international harmonization of fuel economy and GHG standards for light-duty vehicles, but this is largely a question of how stringent standards are and how they are tested and enforced. It is entirely possible that footprint-based and weig ht-based systems can coexist internationally and not present an undue burden for manufacturers if th ey are carefully crafted. Different countries or regions may find different attributes appropriate for basing standards, depending on the particular challenges they face—from fuel prices, to family size and land use, to safety concerns, to fleet composition and consumer preference, to other environmental challenges besides climate change. The agencies anticipate working more cl osely with other countries and regions in the
future to consider how to address these issues in a way that least burdens manufacturers while respecting each country’s need to meet its own particular challenges.

The agencies continue to find that footprint is the most appropriate attribute upon which to base the proposed standards, but recognizing st rong public interest in this issue, we seek comment on whether the agencies should consider setting standards for the final rule based on
another attribute or another combination of attrib utes. If commenters suggest that the agencies
should consider another attribute or another comb ination of attributes, the agencies specifically request that the commenters address the concerns raised in the paragraphs above regarding the use of other attributes, and explain how standards should be developed using the other attribute(s) in a way that contributes more to fuel savings and CO 2 reductions than the footprintbased standards, without compromising safety.

3. What mathematical functions have the agencies previously used, and why?

a. NHTSA in MY 2008 and MY 2011 CAFE (constrained logistic)

For the MY 2011 CAFE rule, NHTSA estimated fuel economy levels after normalization for differences in technology, but did not make adjustments to reflect other vehicle attributes ( e.g. , power-to-weight ratios). 105 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 poin t 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 gpm basis, uniformly downward) to produce the promulgated standards. In the

105 See 74 FR 14196, 14363-14370 (Mar. 30, 2009) for NHTSA discussion of curve fitting in the MY 2011 CAFE final rule.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 93 of 768 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. 106

b. MYs 2012-2016 Light Duty GHG/CAFE (constrained/piecewise linear)

For the MYs 2012-2016 rules, NHTSA and EPA re-evaluated potential methods for specifying mathematical functions to define fuel economy and GHG standards. The agencies concluded that 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. 107 The agencies judged that a range of methods to fit the curves would be reasonable, and used a minimum absolute deviation (MAD) regression without sales weighting on a technology-adjusted car and light truck fleet to fit a linear equation. This equation was used as a starting point to develop mathematical functions defining the standards as discussed above. The agencies then identified footprints at which to apply minimum and maximum values (rather than letting the standa rds extend without limit) and transposed these constrained/piecewise linear functions vertically ( i.e ., on a gpm or CO 2 basis, uniformly downward) to produce the fleetwide fuel economy and CO 2 emission levels for cars and light
trucks described in the final rule. 108

4. How have the agencies changed the mathematical functions for the proposed MYs 2017-2025 standards, and why?

By requiring NHTSA to set CAFE standards that are attribute-based and defined by amathematical function, Congress appears to have wanted the post-EISA standards to be datadriven – a mathematical function defining the standards, in order to be “attribute-based,” should reflect the observed relationship in the data between the attribute chosen and fuel economy. 109
EPA is also proposing to set attribute-based CO 2 standards defined by similar mathematical functions, for the reasonable technical and policy grounds discussed below and in section II of the preamble to the proposed rule, and which supp orts a harmonization with the CAFE standards.

106 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 disp roportionally large change in stringency.

107 75 FR at 25362

108 See generally 74 FR at 49491-96; 75 FR at 25357-62.

109 A mathematical function can be defined, of course, that has nothing to do with the relationship between fuel economy and the chosen attribute – the most basic example is an industry-wide standard defined as the mathematical
function average required fuel economy = X , where X is the single mpg level set by the agency. Yet a standard that is simply defined as a mathematical function that is not tied to the attribute(s) would not meet the requirement of

EISA.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 94 of 768 The relationship between fuel economy (and GHG emissions) and footprint, though directionally clear ( i.e. , fuel economy tends to decrease and CO 2 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. 110 There is thus a range of legitimate options open to the agencies in developing curve shapes. The agencies may of course consider statutory objectives in choosing among the many reasonable alternatives. For example, curve shapes that might have some theoretical basis c ould lead to perverse outcomes contrary to the intent of the statutes to conserve energy and protect human health and the environment. 111 Thus, the decision of how to set the target curves ca nnot always be just about most “clearly” using a mathematical function to define the relationship between fuel economy and the attribute; it often has to have a normative aspect, where the agencies adjust the function that would define the relationship in order to avoid perverse results, improve equity of burden across manufacturers, preserve consumer choice, etc. This is true both for the decisions that guide the mathematical function defining the sloped portion of the target curves, and for the separate decisions that guide the agencies’ choice of “cutpoints” (if any) that define the fuel economy/CO 2 levels and footprints at each end of the curves where the curves become flat. Data informs these decisions, but how the agencies define and interpret the relevant data, and then the choice of methodology for fitting a curve to the data, must include a consideration of both technical data and policy goals.

The next sections examine the policy concerns that the agencies considered in developing the proposed target curves that define the proposed MYs 2017-2025 CAFE and CO 2 standards, new technical work (expanding on similar analyses performed by NHTSA when the agency proposed MY 2011-2015 standards, and by both agencies during consideration of options for MY 2012-2016 CAFE and GHG standards) that was completed in the process of reexamining potential mathematical functions, how the agencies have defined the data, and how the agencies explored statistical curve-fitting methodologies in order to arrive at proposed curves.

5. What are the agencies proposing for the MYs 2017-2025 curves?

The proposed mathematical functions for the proposed MYs 2017-2025 standards are somewhat changed from the functions for the MYs 2012-2016 standards, in response to comments received from stakeholders and in order to address technical concerns and policy goals that the agencies judge more significant in this 9-year rulemaking than in the prior one,

110 In fact, numerous manufacturers have confidentially shar ed with the agencies what they describe as “physics based” curves, with each OEM showing significantly differen t shapes, and footprint relationships. The sheer variety of curves shown to the agencies furthe r confirm the lack of an underlying principle of “fundamental physics” driving the relationship between CO 2 emission or fuel consumption and footprint, and the lack of an underlying principle to dictate any outcome of the agencies’ establishment of footprint-based standards.

111 For example, if the agencies set weight-based sta ndards defined by a steep function, the standards might encourage manufacturers to keep adding weight to thei r vehicles to obtain less stringent targets.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 95 of 768 which only included 5 years. This section discusses the methodology the agencies selected as, at this time, best addressing those technical con cerns and policy goals, given the various technical inputs to the agencies’ current analyses. Below the agencies discusses how the agencies determined the cutpoints and the flat portions of the MYs 2017-2025 target curves. We also note that both of these sections address only how the target curves were fit to fuel consumption and

CO 2 emission values determined using the city and highway test procedures, and that in determining respective regulatory alternatives, the agencies made further adjustments to the resultant curves in order to account for adjustme nts for improvements to mobile air conditioners.

Thus, recognizing that there are many reasonable statistical methods for fitting curves to data points that define vehicles in terms of foot print and fuel economy, the agencies have chosen for this proposed rule to fit curves using an ordi nary least-squares formulation, on sales-weighted data, using a fleet that has had technology applied, and after adjusting the data for the effects of weight-to-footprint, as described below. This represents a departure from the statistical approach for fitting the curves in MYs 2012-2016, as explained in the next section. The agencies considered a wide variety of reasonable statis tical methods in order to better understand the range of uncertainty regarding the relationship between fuel consumption (the inverse of fuel economy), CO 2 emission rates, and footprint, thereby providing a range within which decisions about standards would be potentially supportable.

a. What concerns were the agencies looking to address that led them to change from the approach used for the MYs 2012-2016 curves?

During the year and a half since the MYs 2012-2016 final rule was issued, NHTSA and
EPA have received a number of comments from stakeholders on how curves should be fitted to the passenger car and light truck fleets. Some limited-line manufacturers have argued that curves should generally be flatter in order to a void discouraging small vehicles, because steeper curves tend to result in more stringent targets fo r smaller vehicles. Most full-line manufacturers have argued that a passenger car curve similar in slope to the MY 2016 passenger car curve would be appropriate for future model years, but that the light truck curve should be revised to be less difficult for manufacturers selling the larges t full-size pickup trucks. These manufacturers argued that the MY 2016 light truck curve was not “physics-based,” and that in order for future tightening of standards to be feasible for full- line manufacturers, the truck curve for later model years should be steeper and extended further (i.e., made less stringent) into the larger footprints. The agencies also do not agree that the MY 2016 light truck curve was somehow deficient in lacking a “physics basis,” or that it was somehow overly stringent for manufacturers selling large pickups—manufacturers making these arguments pr esented no “physics-based” model to explain how fuel economy should depend on footprint. 112 The same manufacturers indicated that they believed that the light truck standard should be somewhat steeper after MY 2016, primarily because, after more than ten years of progressive increases in the stringency of applicable CAFE

112 See footnote 110Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 96 of 768 standards, large pickups would be less capable of achieving further improvements without compromising load carrying and towing capacity.

In developing the curve shapes for this proposed rule, the agencies were aware of the current and prior technical concerns raised by OEMs concerning the effects of the stringency on individual manufacturers and their ability to me et the standards with available technologies, while producing vehicles at a cost that allowed them to recover the additional costs of the technologies being applied. Although we con tinue to believe that the methodology for fitting curves for the MY2012-2016 standards was technically sound, we recognize manufacturers’ technical concerns regarding their abilities to comply with a similarly shallow curve after MY2016 given the anticipated mix of light trucks in MYs 2017-2025. As in the MYs 2012-2016 rules, the agencies considered these concerns in the analysis of potential curve shapes. The agencies also considered safety concerns which could be raised by curve shapes creating an incentive for vehicle downsizing, as well as the potential loss to consumer welfare should vehicle upsizing be unduly disincentivized. In addition, the agencies sought to improve the balance of compliance burdens among manufacturers. Among the technical concerns and resultant policy trade-offs the agencies considered were the following:

 Flatter standards ( i.e. , curves) increase the risk that both the weight and size of vehicles will be reduced, compromising highway safety.

 Flatter standards potentially impact the utility of vehicles by providing an incentive for vehicle downsizing.

 Steeper footprint-based standards may incentivize vehicle upsizing, thus increasing the risk that fuel economy and gr eenhouse gas reduction benefits will be less than expected.

 Given the same industry-wide average required fuel economy or CO 2 standard, flatter standards tend to place greater compliance burdens on full-line manufacturers

 Given the same industry-wide average required fuel economy or CO 2 standard, 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 2 emissions) discourages the introduction of small vehicles, and reduces the incentive to downsize small vehicles in ways that would compromise 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 2 emissions) better accommodates the unique design requirements of larger vehicles—especially large pickups—and extends the size range over which downsizing is discouraged.

All of these were policy goals th at required trade-offs, and in determining the curves they also required balance against the comments from the OEM comments discussed in theSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 97 of 768 introduction to this section. Ultimately, the agencies do not agree that the MY 2017 target curves for this proposal, on a relative basis, s hould be made significantly flatter than the MY 2016 curve, 113 as we believe that this would undo some of the safety-related incentives and balancing of compliance burdens among manufact urers—effects that attribute-based standards are intended to provide.

Nonetheless, the agencies recognize full-line OEM concerns and have tentatively concluded that further increases in the stringe ncy of the light truck standards will be more feasible if the light truck curve is made steeper than the MY 2016 truck curve and the right (large footprint) cut-point is extended over time to larger footprints. This conclusion is supported by the agencies’ technical analyses of regulatory alte rnatives defined using the curves developed in
the manner described below.

b. What methodologies and data did the agencies consider in developing the 2017-

2025 curves?

In considering how to address the various po licy concerns discussed in the previous sections, the agencies revisited the data and performed a number of analyses using different combinations of the various statistical methods, weighting schemes, adjust ments to the data and the addition of technologies to make the fleets less technologically heterogeneous. As discussed above, in the agencies’ judgment, there is no single “correct” way to estimate the relationship
between CO 2 or fuel consumption and footprint – rather, each statistical result is based on the underlying assumptions about the particular func tional form, weightings and error structures embodied in the representational approach. These assumptions are the subject of the following discussion. This process of performing many an alyses using combinations of statistical methods generates many possible outcomes, each embodying different potentially reasonable combinations of assumptions and each thus reflective of the data as viewed through a particular lens. The choice of a standard developed by a gi ven combination of these statistical methods is consequently a decision based upon the agencies’ determination of how, given the policy objectives for this rulemaking and the agencies’ MY 2008-based forecast of the market through MY 2025, to appropriately reflect the current understanding of the evolution of automotive technology and costs, the future prospects for the vehicle market, and thereby establish curves (i.e., standards) for cars and light trucks.

c. What information did the agencies use to estimate a relationship between fuel economy, CO 2 and footprint?

For each fleet, the agencies began with the MY 2008-based market forecast developed to support this proposal ( i.e. , the baseline fleet), with vehicles’ fuel economy levels and

113 While “significantly” flatter is subjective, the year over ye ar change in curve shapes is discussed in greater detail in Section I.C.7.a.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 98 of 768 technological characteristics at MY 2008 levels. 114 The development, scope, and content of this market forecast is discussed in detail in Chap ter 1 of the joint Technical Support Document supporting this rulemaking.

d. What adjustments did the agencies evaluate?

The agencies believe one possible approach is to fit curves to the minimally adjusted data shown above (the approach still includes sales mi x adjustments, which influence results of salesweighted regressions), much as DOT did when it first began evaluating potential attribute-based
standards in 2003. 115 However, the agencies have found, as in prior rulemakings, that the data are so widely spread ( i.e. , when graphed, they fall in a loose “cloud” rather than tightly around an obvious line) that they indicate a relationship between footprint and CO 2 and fuel consumption that is real but not particularly stro ng. Therefore, as discussed below, the agencies also explored possible adjustments that could help to explain and/or reduce the ambiguity of this relationship, or could help to produce policy outcomes the agencies judged to be more desirable.

i. Adjustment to reflect di fferences in technology

As in prior rulemakings, the agencies cons ider technology differences between vehicle models to be a significant factor producing un certainty regarding the relationship between

CO 2 /fuel consumption and footprint. Noting that attribute-based standards are intended to encourage the applicatio n of additional technology to impr ove fuel efficiency and reduce CO 2 emissions, the agencies, in addition to cons idering approaches based on the unadjusted engineering characteristics of MY 2008 vehicle m odels, therefore also considered approaches in which, as for previous rulemakings, technology is added to vehicles for purposes of the curve fitting analysis in order to produce fleets that are less varied in technology content.

The agencies adjusted the baseline fleet for technology by adding all technologies considered, except for the most advanced high-BMEP (brake mean effective pressure) gasoline engines, diesel engines, strong HEVs, PHEVs, EVs, and FCVs. The agencies included 15 percent mass reduction on all vehicles.

ii. Adjustments reflecting differences in performance and “density”

As discussed in above, during stakeholder meet ings the agencies held while developing this NPRM, some manufacturers indicated that th ey believed that the light truck standard should be somewhat steeper after MY 2016. As a means to produce a steeper light truck curve, the agencies considered adjustments for othe r differences between vehicle models ( i.e. , inflating or deflating the fuel economy of each vehicle model based on the extent to which one of the

114 While the agencies jointly conducted th is analysis, the coefficients ultimately used in the slope setting analysis are from the CAFE model.

115 68 FR 74920-74926.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 99 of 768 vehicle’s attributes, such as power, is higher or lower than average). Previously, NHTSA had rejected such adjustments because they imply that a multi-attribute standard may be necessary, and the agencies judged multi-attribute standard to be more subject to gaming than a footprintonly standard. 116,117 Having considered this issue again for purposes of this rulemaking, NHTSA and EPA conclude the need to accommodate in the target curves the challenges faced by manufacturers of large pickups currently outweighs these prior concerns. Therefore, the agencies also evaluated curve fitting approaches through which fuel consumption and CO 2 levels were adjusted with respect to weight-to-footprint alone, and in combination with power-toweight. While the agencies examined these adjustments for purposes of fitting curves, the agencies are not proposing a multi-attribute standard; the proposed fuel economy and CO 2 targets for each vehicle are still f unctions of footprint alone. No adjustment would be used in the compliance process. The agencies also examined some differences between the technology-adjusted car and truck fleets in order to better understand the relationship between footprint and CO 2 /fuel consumption in the agencies’ MY 2008 based forecast. The agencies investigated the relationship between HP/WT and footprint in the agencies’ MY2008-based market forecast. On a sales weighted basis, cars tend to become proportionally more powerful as they get larger. In contrast, there is a minimally positive relationship between HP/WT and footprint for light trucks, indicating that light trucks become only sligh tly more powerful as they get larger.

This analysis, presented in chapter 2.4.1.2 of the agencies’ joint TSD, indicated that vehicle performance (power-to-weight ratio) and “d ensity” (curb weight divided by footprint) are both correlated to fuel consumption (and CO 2 emission rate), and that these vehicle attributes are also both related to vehicle footprint. Based on these relationships, the agencies explored adjusting the fuel economy and CO 2 emission rates of individual vehicle models based on deviations from “expected” performance or weight /footprint at a given footprint; the agencies inflated fuel economy levels of vehicle models with higher performance and/or weight/footprint than the average of the fleet would indicate at th at footprint, and deflated fuel economy levels with lower performance and/or weight. Previously, NHTSA had rejected such adjustments because they imply that a multi-attribute standard may be necessary, and the agency judged multi-attribute standard to be more subject to gaming than a footprint-only standard. 118,119

116 For example, in comments on NHTSA’s 2008 NPRM regarding MY 2011-2015 CAFE standards, Porsche recommended that standards be defined in terms of a “Summed Weighted Attribute”, wherein the fuel economy target would calculated as follows: target = f(SWA) , where target is the fuel economy target applicable to a given vehicle model and SWA = footprint + torque 1/1.5 + weight 1/2.5 . (NHTSA-2008-0089-0174). While the standards the agencies are proposing for MY 2017-2025 are not multi-attributes, that is the ta rget is only a function of footprint, we are proposing curve shapes that were developed considering more than one attribute.

117 74 FR 14359.

118 For example, in comments on NHTSA’s 2008 NPRM regarding MY 2011-2015 CAFE standards, Porsche recommended that standards be defined in terms of a “Summed Weighted Attribute”, wherein the fuel economy target would calculated as follows: target = f(SWA) , where target is the fuel economy target applicable to a given vehicle model and SWA = footprint + torque 1/1.5 + weight 1/2.5 . (NHTSA-2008-0089-0174). While the standards theSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 100 of 768 While the agencies considered this technique for purposes of fitting curves, the agencies are not proposing a multi-attribute standard, as the proposed fuel economy and CO 2 targets for each
vehicle are still functions of foot print alone. No adjustment would be used in the compliance

process.

The agencies seek comment on the appropriateness of the adjustments as described in Chapter 2 of the joint TSD, particularly regarding whether these adjustments suggest that standards should be defined in terms of other attributes in addition to footprint, and whether they may encourage changes other than encouraging the application of technology to improve fuel economy and reduce CO 2 emissions. The agencies also seek comment regarding whether these adjustments effectively “lock in” through MY 20 25 relationships that were observed in MY

2008.

e. What statistical methods did the agencies evaluate?

The above approaches resulted in three data sets each for (a) vehicles without added technology and (b) vehicles with technology added to reduce technology differences, any of which may provide a reasonable basis for fitting mathematical functions upon which to base the slope of the standard curves: (1) vehicles with out any further adjustments; (2) vehicles with adjustments reflecting differences in “density” (weight/footprint); and (3) vehicles with adjustments reflecting differences in “density ,” and adjustments reflecting differences in performance (power/weight). Using these data se ts, the agencies tested a range of regression methodologies, each judged to be possibly reasonable for application to at least some of these
data sets.

i. Regression Approach

In the MYs 2012-2016 final rules, the agencies employed a robust regression approach (minimum absolute deviation, or MAD), rath er than an ordinary least squares (OLS) regression. 120 MAD is generally applied to mitigate the effect of outliers in a dataset, and thus was employed in that rulemaking as part of our interest in attempting to best represent the underlying technology. NHTSA had used OLS in early development of attribute-based CAFE standards, but NHTSA (and then NHTSA and EPA) subsequently chose MAD instead of OLS for both the MY 2011 and the MYs 2012-2016 rulemakings. These decisions on regression technique were made both because OLS gives additional emphasis to outliers 121 and because the MAD approach helped achieve the agencies’ policy goals with regard to curve slope in those

agencies are proposing for MY 2017-2025 are not multi-attribute standards, that is the target is only a function of footprint, we are proposing curve shapes that were developed considering more than one attribute.

119 74 FR 14359.

120 See 75 FR at 25359.

121 Id

. at 25362-63.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 101 of 768 rulemakings. 122 In the interest of taking a fresh look at appropriate regression methodologies as promised in the 2012-2016 light duty rulemaking, in developing this proposal, the agencies gave full consideration to both OLS and MAD. The OLS representation, as described, uses squared errors, while MAD employs absolute errors and thus weights outliers less.

As noted, one of the reasons stated for choosing MAD over least square regression in the MYs 2012-2016 rulemaking was that MAD reduced the weight placed on outliers in the data. However, the agencies have further considered whet her it is appropriate to classify these vehicles as outliers. Unlike in traditional datasets, these ve hicles’ performance is not mischaracterized due to errors in their measurement, a common reason for outlier classification. Being certification data, the chances of large measurement errors s hould be near zero, particularly towards high CO 2 or fuel consumption. Thus, they can only be outliers in the sense that the vehicle designs are
unlike those of other vehicles. These outlier vehicles may include performance vehicles, vehicles with high ground clearance, 4WD, or boxy designs. Given that these are equally legitimate on-road vehicle designs, the agenci es concluded that it would appropriate to
reconsider the treatment of these vehi cles in the regression techniques.

Based on these considerations as well as the adjustments discussed above, the agencies concluded it was not meaningful to run MAD regressions on gpm data that had already been adjusted in the manner described above. Normalizing already reduced the variation in the data, and brought outliers towards aver age values. This was the inte nded effect, so the agencies deemed it unnecessary to apply an additional remedy to resolve an issue that had already been addressed, but we seek comment on the use of robust regression techniques under such
circumstances.

ii. Sales Weighting

Likewise, the agencies reconsidered employing sales-weighting to represent the data. As explained below, the decision to sales weight or not is ultimately based upon a choice about how to represent the data, and not by an underlying statistical concern. Sales weighting is used if the decision is made to treat each (mass produced) un it sold as a unique physical observation. Doing so thereby changes the extent to which different vehicle model types are emphasized as compared to a non-sales weighted regression. For example, while total General Motors Silverado (332,000) and Ford F-150 (322,000) sales differ by less than 10,000 in MY 2021 market forecast, 62 F-150s models and 38 Silverado models are reported in the agencies baselines. Without sales-weighting, the F-150 models, because there are more of them, are given 63 percent more weight in the regression despite comprising a similar portion of the marketplace and a relatively homogenous set of vehicle technologies.

122 Id

. at 25363.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 102 of 768 The agencies did not use sales weighting in the 2012-2016 rulemaking analysis of the curve shapes. A decision to not perform sale s weighting reflects judgment that each vehicle model provides an equal amount of information concerning the underlying relationship between footprint and fuel economy. Sales-weighted regression gives the highest sales vehicle model types vastly more emphasis than the lowest-sales vehicle model types thus driving the regression toward the sales-weighted fleet norm. For unweig hted regression, vehicle sales do not matter. The agencies note that the light truck market fo recast shows MY 2025 sales of 218,000 units for Toyota’s 2WD Sienna, and shows 66 model config urations with MY 2025 sales of fewer than 100 units. Similarly, the agencies’ market forecast shows MY 2025 sales of 267,000 for the Toyota Prius, and shows 40 model configurations with MY2025 sales of fewer than 100 units. Sales-weighted analysis would give the Toyota Si enna and Prius more than a thousand times the consideration of many vehicle model configuratio ns. Sales-weighted analysis would, therefore, cause a large number of vehicle model configurations to be virtually ignored in the regressions. 123

However, the agencies did note in the MYs 2012-2016 final rules that, “sales weighted regression would allow the difference between othe r vehicle attributes to be reflected in the analysis, and also would reflect consumer demand.” 124 In reexamining the sales-weighting for this analysis, the agencies note that there are low-volume model types account for many of the passenger car model types (50 percent of passenger car model types account for 3.3 percent of sales), and it is unclear whether the engineering characteristics of these model types should equally determine the standard for the remainder of the market.

In the interest of taking a fresh look at appropriate methodologies as promised in the lastfinal rule, in developing this proposal, the agencies gave full consideration to both salesweighted and unweighted regressions.

iii. Analyses Performed

We performed regressions describing the re lationship between a vehicle’s CO2/fuel consumption and its footprint, in terms of various combinations of factors: initial (raw) fleets with no technology, versus after technology is applied; sales-weighted versus non-sales weighted; and with and without two sets of normalizing factors applied to the observations. The agencies excluded diesels and dedicated AFVs because the agencies anticipate that advanced gasoline-fueled vehicles are likely to be dominant through MY2025.

Thus, the basic OLS regression on the initial data (with no technology applied) and no sales-weighting represents one perspective on the relation between footprint and fuel economy. Adding sales weighting changes the interpretation to include the influence of sales volumes, and thus steps away from representing vehicle techno logy alone. Likewise, MAD is an attempt to

123 75 FR at 25362 and n. 64

124 75 FR at 25632/3.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 103 of 768 reduce the impact of outliers, but reducing the impact of outliers might perhaps be less representative of technical relationships between the variables, although that relationship may change over time in reality. Each combination of methods and data reflects a perspective, and the regression results simply reflect that persp ective in a simple quantifiable manner, expressed as the coefficients determining the line through the average (for OLS) or the median (for MAD) of the data. It is left to policy makers to dete rmine an appropriate perspective and to interpret the consequences of the various alternatives.

We invite comments on the application of the weights as described above, and the implications for interpreting the relationship between fuel efficiency (or CO 2 ) and footprint.

f. What results did the agencies obtain, which methodology did the agencies choose for this proposal, and why is it reasonable?

Both agencies analyzed the same statistical approaches. For regressions against data including technology normalization, NHTSA used the CAFE modeling system, and EPA used EPA’s OMEGA model. The agencies obtained similar regression results, and have based today’s joint proposal on those ob tained by NHTSA. The draft Joint TSD Chapter 2 contains a large set of illustrative of figures which show the range of curves determined by the possible combinations of regression technique, with a nd without sales weighting, with and without the application of technology, and with various adjustments to the gpm variable prior to running a regression. The choice among the alternatives presented in the draft Joint TSD Chapter 2 was to use the OLS formulation, on sales-weighted data, using a fleet that has had technology applied, and after adjusting the data for the effect of weight-to-footprint, as described above. The agencies believe that this represents a technically reasonable approach for purposes of developing target curves to define the proposed standards, and that it represents a reasonable trade-off among various considerations balancing statistical, t echnical, and policy matters, which include the statistical representativeness of the curves considered and the steepness of the curve chosen. The agencies judge the application of technology pr ior to curve fitting to provide a reasonable means—one consistent with the rule’s objective of encouraging manufacturers to add technology in order to increase fuel economy—of reducing variation in the data and thereby helping to estimate a relationship between fuel consumption/CO 2 and footprint.

Similarly, for the agencies’ current MY 2008-based market-forecast and the agencies’ current estimates of future technology effectivene ss, the inclusion of the weight-to-footprint data adjustment prior to running the regression also helps to improve the fit of the curves by reducing the variation in the data, and the agencies believe that the benefits of this adjustment for this proposed rule likely outweigh the potential that resultant curves might somehow encourage reduced load carrying capability or vehicle performance (note that the we are not suggesting thatSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 104 of 768 we believe these adjustments will reduce load carrying capability or vehicle performance). In addition to reducing the variability, the truck curve is also steepened, and the car curve flattened compared to curves fitted to sales weighted data that do not include these normalizations. The agencies agree with manufacturers of full-size pick -up trucks that in order to maintain towing and hauling utility, the engines on pick-up trucks must be more powerful, than their low “density” nature would statistically suggest based on the agencies’ current MY2008-based market forecast and the agencies’ current estimates of the effectiveness of different fuel-saving technologies. Therefore, it may be more equitable ( i.e. , in terms of relative compliance challenges faced by different light truck manufacturer s) to adjust the slope of the curve defining fuel economy and CO 2 targets.

As described above, however, other approaches are also technically reasonable, and also represent a way of expressing the underlying relationships. The agencies plan to revisit the analysis for the final rule, after updating th e underlying market forecast and estimates of technology effectiveness, and based on relevant public comments received. In addition, the agencies intend to update the technology cost estimates, which could alter the NPRM analysis results and consequently alter the balance of the trade-offs being weighed to determine the final

curves.

g. Implications of the proposed slope compared to MY 2012-2016

The proposed slope has several implications relative to the MY 2016 curves, with the majority of changes on the truck curve. With the agencies’ current MY2008-based market forecast and the agencies’ current estimates of technology effectiveness, the combination of sales weighting and WT/FP normalization produced a car curve slope similar to that finalized in the MY 2012-2016 final rulemaking (4.7 g/mile in MY 2016, vs. 4.5 g/mile proposed in MY 2017). By contrast, the truck curve is steeper in MY 2017 than in MY 2016 (4.0 g/mile in MY 2016 vs. 4.9 g/mile in MY 2017). As discussed previous ly, a steeper slope relaxes the stringency of targets for larger vehicles re lative to those for smaller vehi cles, thereby shifting relative compliance burdens among manufacturers based on their respective product mix.

6. Once the agencies determined the appropriate slope for the sloped part, how did the agencies determine the rest of the mathematical function?

The agencies continue to believe that wit hout a limit at the sma llest footprints, the function—whether logistic or linear—can reach va lues that would be unfairly burdensome for a
manufacturer that elects to focus on the market for small vehicles; depending on the underlying data, an unconstrained form could result in stringency levels that are technologically infeasible and/or economically impracticable for those manufacturers that may elect to focus on the
smallest vehicles. On the other side of the func tion, without a limit at th e largest footprints, the function may provide no floor on required fuel economy. Also, the safety considerations that support the provision of a disincentive for downsizi ng as a compliance strategy apply weakly, ifSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 105 of 768 at all, to the very largest vehicles. Limiting the function’s value for the largest vehicles thus leads to a function with an inherent absolute minimum level of performance, while remaining consistent with safety considerations.

Just as for slope, in determining the appropriate footprint and fuel economy values for the “cutpoints,” the places along the curve where the sloped portion becomes flat, the agencies took a fresh look for purposes of this proposal, taking into account the updated market forecast and new assumptions about the availability of technologies. The next two sections discuss the agencies’ approach to cutpoints for the passenger car and light truck curves separately, as the policy considerations for each vary somewhat.

a. Cutpoints for PC curve

The passenger car fleet upon which the agencies have based the target curves for MYs 2017-2025 is derived from MY 2008 data, as discussed above. In MY 2008, passenger car footprints ranged from 36.7 square feet, the Lotus Exige 5, to 69.3 square feet, the Daimler Maybach 62. In that fleet, several manufacturers offer small, sporty coupes below 41 square feet, such as the BMW Z4 and Mini, Honda S2000, Mazda MX-5 Miata, Porsche Carrera and 911, and Volkswagen New Beetle. Because such ve hicles represent a small portion (less than 10 percent) of the passenger car ma rket, yet often have performance, utility, and/or structural characteristics that could make it technologically infeasible and/or economically impracticable for manufacturers focusing on such vehicles to achieve the very challenging average requirements that could apply in the absence of a constraint, EPA and NHTSA are again proposing to cut off the sloped portion of the passenger car function at 41 square feet, consistent with the MYs 2012-2016 rulemaking. The agenci es recognize that for manufacturers who make small vehicles in this size range, putting the cutpoint at 41 square feet creates some incentive to downsize ( i.e. , further reduce the size, and/or increase the production of models currently smaller than 41 square feet) to make it easier to meet the target. Putting the cutpoint here may also create the incentive for manufacturers who do not currently offer such models to do so in the future. However, at the same time, the agencies believe that there is a limit to the market for cars smaller than 41 square feet -- most consumers likely have some minimum expectation about interior volume, among other things. The agenci es thus believe that the number of consumers who will want vehicles smaller than 41 square feet (regardless of how they are priced) is small, and that the incentive to downsize to less than 41 square feet in response to this proposal, if present, will be at best minimal. On the othe r hand, the agencies note that some manufacturers are introducing mini cars not reflected in the agen cies MY 2008-based market forecast, such as the Fiat 500, to the U.S. market, and that the footprint at which the curve is limited may affect
the incentive for manufacturers to do so.

Above 56 square feet, the only passenger car models present in the MY 2008 fleet were four luxury vehicles with extremely low sales volumes—the Bentley Arnage and three versionsSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 106 of 768 of the Rolls Royce Phantom. As in the MYs 2012-2016 rulemaking, NHTSA and EPA therefore are proposing again to cut off the sloped portion of the passenger car function at 56 square feet.

While meeting with manufacturers prior to issuing the proposal, the agencies received comments from some manufacturers that, combined with slope and overall stringency, using 41 square feet as the footprint at which to cap the target for small cars would result in unduly challenging targets for small cars. The agencies do not agree. No specific vehicle need meet its target (because standards apply to fleet average performance), and maintaining a sloped function toward the smaller end of the passenger car market is important to discourage unsafe downsizing, the agencies are thus proposing to again “cut off” the passenger car curve at 41 square feet, notwithstanding these comments.

The agencies seek comment on setting cutpoints for the MYs 2017-2025 passenger car curves at 41 square feet and 56 square feet.

b. Cutpoints for LT curve

The light truck fleet upon which the agencies have based the target curves for MYs 2017- 2025, like the passenger car fleet, is derived from MY 2008 data, as discussed in Section 2.4 above. In MY 2008, light truck footprints ranged from 41.0 square feet, the Jeep Wrangler, to 77.5 square feet, the Toyota Tundra. For consistency with the curve for passenger cars, the agencies are proposing to cut off the sloped po rtion of the light truck function at the same footprint, 41 square feet, although we recognize that no light trucks are currently offered below 41 square feet. With regard to the upper cutpoint, the agencies heard from a number of manufacturers during the discussions leading up to th is proposal that the location of the cutpoint in the MYs 2012-2016 rules, 66 square feet, meant that the same standard applied to all light trucks with footprints of 66 square feet or greater , and that in fact the ta rgets for the largest light trucks in the later years of that rulemaking were extremely challenging. Those manufacturers requested that the agencies extend the cutpoint to a larger footprint, to reduce targets for the largest light trucks which represent a significant percentage of those manufacturers light truck sales. At the same time, in re-examining the light truck fleet data, the agencies concluded that aggregating pickup truck models in the MYs 2012-2016 rule had led the agencies to underestimate the impact of the different pickup truck model configurations above 66 square feet on manufacturers’ fleet average fuel economy and CO2 levels (as discussed immediately below). In disaggregating the pickup truck model data, the im pact of setting the cut point at 66 square feet after model year 2016 became clearer to the agencies.

In the agencies’ view, there is legitimate basi s for these comments. The agencies’ market forecast includes about 24 vehicle configurations above 74 square feet with a total volume of about 50,000 vehicles or less during any MY in the 2017-2025 time frame. While a relatively small portion of the overall truck fleet, for so me manufacturers, these vehicles are non-trivialSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 107 of 768 portion of sales. As noted above, the very larges t light trucks have significant load-carrying and towing capabilities that make it particularly cha llenging for manufacturers to add fuel economyimproving/CO 2 -reducing technologies in a way that ma intains the full functionality of those capabilities.

Considering manufacturer CBI and our estimates of the impact of the 66 square foot cutpoint for future model years, the agencies have initially determined to adopt curves that transition to a different cut point. While noting that no specific vehicle need meet its target (because standards apply to fleet average performance), we believe that the information provided to us by manufacturers and our own analysis supports the gradual extension of the cutpoint for large light trucks in this proposa l from 66 square feet in MY 2016 out to a larger footprint square
feet before MY 2025.

Figure 0-1 Footprint Distribution by Car and Truck*

*Proposed truck cutpoints for MY 2025 shown in red, car cutpoints shown in green

The agencies are proposing to phase in the higher cutpoint for the truck curve in order to avoid any backsliding from the MY 2016 standard. A target that is feasible in one model year should never become less feasible in a subsequent model year—manufacturers should have no reason to remove fuel economy-improving/CO 2 -reducing technology from a vehicle once it hasSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 108 of 768 been applied. Put another way, the agencies are proposing to not allow “curve crossing” from one model year to the next. In proposing MYs 2011-2015 CAFE standards and promulgating MY 2011 standards, NHTSA proposed and requested comment on avoiding curve crossing, as an “anti-backsliding measure.” 125 The MY 2016 2 cycle test curves are therefore a floor for the MYs 2017-2025 curves. For passenger cars, which have minimal change in slope from the MY 2012-2016 rulemakings and no change in cut points, there are no curve crossing issues in the proposed standards.

The minimum stringency determination was done using the two cycle curves. Stringency adjustments for air conditioning and other credits were calculated after curves that did not cross were determined in two cycle space. The year over year increase in these adjustments cause neither the GHG nor CAFE curves (with A/C) to contact the 2016 curves when charted.

7. Once the agencies determined the complete mathematical function shape, how did the agencies adjust the curves to develop the proposed standards and regulatory alternatives?

The curves discussed above all reflect the addition of technology to individual vehicle models to reduce technology differences between vehicle models before fitting curves. This application of technology was conducted not to directly determine the proposed standards, but rather for purposes of technology adjustments, and set aside consideratio ns regarding potential rates of application ( i.e. , phase-in caps), and considerations regarding economic implications of applying specific technologies to specific vehicle models. The following sections describe further adjustments to the curves discussed above, that affect both the shape of the curve, and the location of the curve, that helped the agencies determine curves that defined the proposed
standards.

a. Adjusting for Year over Year Stringency

As in the MYs 2012-2016 rules, the agencies developed curves defining regulatory alternatives for consideration by “shifting” these curves. For the MYs 2012-2016 rules, the agencies did so on an absolute basis, offsettin g the fitted curve by the same value (in gpm or g/mi) at all footprints. In developing this proposal , the agencies have reconsidered the use of this approach, and have concluded that after MY 2016, curves should be offset on a relative basis— that is, by adjusting the entire gpm-based curve (and, equivalently, the CO 2 curve) by the same percentage rather than the same absolute value. The agencies’ estimates of the effectiveness of these technologies are all expressed in relative terms—that is, each technology (with the exception of A/C) is estimated to reduce fuel consumption (the inverse of fuel economy) and

CO 2 emissions by a specific percentage of fuel consumption without the technology. It is, therefore, more consistent with the agencies’ estimates of technology effectiveness to develop

125 74 Fed. Reg. at 14370 (Mar. 30, 2009).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 109 of 768 the proposed standards and regulatory alternatives by applying a proportional offset to curves expressing fuel consumption or emissions as a function of footprint. In addition, extended indefinitely (and without other compensating adju stments), an absolute offset would eventually ( i.e. , at very high average stringencies) produce ne gative (gpm or g/mi) targets. Relative offsets avoid this potential outcome. Relative offsets do cause curves to become, on a fuel consumption
and CO 2 basis, flatter at greater average stringencies; however, as discussed above, this outcome remains consistent with the agencies’ estimates of technology effectiveness. In other words, given a relative decrease in average required fuel consumption or CO 2 emissions, a curve that is flatter by the same relative amou nt should be equally challengi ng in terms of the potential to achieve compliance through the addition of fuel-saving technology.

On this basis, and considering that the “fla ttening” occurs gradually for the regulatory alternatives the agencies have evaluated, the agen cies tentatively conclude that this approach to offsetting the curves to develop year-by-year regulatory alternatives neither re-creates a situation in which manufacturers are likely to respond to standards in ways that compromise highway safety, nor undoes the attribute-based standard’s more equitable balancing of compliance burdens among disparate manufacturers. The agen cies invite comment on these conclusions, and on any other means that might avoid the potential outcomes—in particular, negative fuel consumption and CO 2 targets—discussed above.

b. Adjusting for anticipated improvements to mobile air conditioning systems

The fuel economy values in the agencies’ market forecast are based on the 2-cycle ( i.e.

, city and highway) fuel economy test and calculati on procedures that do not reflect potential improvements in air conditioning system efficien cy, refrigerant leakage, or refrigerant Global Warming Potential (GWP). Recognizing that there are significant and cost effective potential air conditioning system improvements available in the rulemaking timeframe (discussed in detail in Chapter 5 of the draft joint TSD), the agencies ar e increasing the stringency of the target curves based on the agencies’ assessment of the capability of manufacturers to implement these changes. For the proposed CAFE standards and alternatives, an offset is included based on air conditioning system efficiency improvements, as these improvements are the only improvements that effect vehicle fuel economy. For the proposed GHG standards and alternatives, a stringency increase is included based on air conditioning system efficiency, leakage and refrigerant improvements. As discussed above in Chapter 5 of the join TSD, the air conditioning system improvements affect a vehicle’s fuel efficiency or CO 2 emissions performance as an additive stringency increase, as compared to other fuel efficiency improving technologies which are multiplicative. Therefore, in adjusting target curves for improvements in the air conditioning system performance, the agencies are adjusting th e target curves by additive stringency increases (or vertical shifts) in the curves.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 110 of 768 For the GHG target curves, the offset for air conditioning system performance is being handled in the same manner as for the MY 2012-2016 rules. For the CAFE target curves, NHTSA for the first time is proposing to account for potential improvements in air conditioning system performance. Using this methodology, the agencies first use a multiplicative stringency adjustment for the sloped portion of the curves to reflect the effectiveness on technologies other that air conditioning system technologies, creating a series of curve shapes that are “fanned” based on two-cycle performance. Then the curves are offset vertically by the air conditioning improvement by an equal amount at every point.

D. Joint Vehicle Technology Assumptions

For the past four to five years, the agencies have been working together closely to follow the development of fuel consumption and GHG reducing technologies. Two major analyses have been published jointly by EPA and NHTSA: the Technical Support Document to support the MYs 2012-2016 final rule and the 2010 Technical Analysis Report (which supported the 2010 Notice of Intent). The latter of these analyses was also done in conjunction with CARB. Both of these analyses have both been published within the past 18 months. As a result, much of the work is still relevant and we continue to re ly heavily on these references. However, some technologies -- and what we know about them -- are changing so rapidly that the analysis supporting this proposal contains a considerab le amount of new work on technologies included in this rule, some of which were included in prior rulemakings, and others that were not.

Notably, we have updated our battery costing methodology significantly since the MYs 2012-2016 final rule and even relative to the 2010 TAR. We are now using a peer reviewed model developed by Argonne National Laboratory for the Department of Energy which provides us with more rigorous estimates for battery costs and allows us to estimate future costs specific to hybrids, plug-in hybrids and electric vehicles all of which have different battery design characteristics.

We also have new cost data from more recently completed tear down and other cost studies by FEV which were not available in either the MYs 2012-2016 final rule or the 2010 TAR. These new studies analyzed a 8-speed automatic transmission replacing 6-speed automatic transmission, a 8-speed dual clutch transmission replacing 6-speed dual clutch transmission, a power-split hybrid powertrain with an I4 engine replacing a conventional engine powertrain with V6 engine, a mild hybrid with stop-start technology and an I4 engine replacing a conventional I4 engine, and the Fiat Multi-Air engine technology. We discuss the new tear down studies in Section II.D.2 of this preamble. Based on this, we have updated some of the FEV-developed costs relative to what we used in the 2012-2 016 final rule, although these costs are consistent with those used in the 2010 TAR. Furthermore, we have completely re-worked our estimated costs associated with mass reduction relative to both the MYs 2012-2016 final rule and the 2010
TAR.

As would be expected given that some of our cost estimates were developed several years ago, we have also updated all of our base direct manufacturing costs to put them in terms of more recent dollars (2009 dollars for this proposal). We have also updated our methodology for calculating indirect costs associ ated with new technologies since both the MYs 2012-2016 finalSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 111 of 768 rule and the TAR. We continue to use the indir ect cost multiplier (ICM) approach used in those analyses, but have made important changes to the calculation methodology – changes done in response to ongoing staff evaluation and public input.

Lastly, we have updated many of the technologies’ effectiveness estimates largely based on new vehicle simulation work conducted by Ricardo Engineering. This simulation work provides the effectiveness estimates for a number of the technologies most heavily relied on in the agencies’ analysis of potential standards for MYs 2017-2025.

The agencies have also reviewed the findings and recommendations in the updated NAS report “Assessment of Fuel Economy Technologies for Light-Duty Vehicles” that was completed after the MYs 2012-2016 final rule was issued, 126 and NHTSA has performed a sensitivity analysis (contained in its PRIA) to examine the impact of using some of the NAS cost and effectiveness estimates on the proposed standards.

Each of these changes is discussed briefly in the remainder of this section and in much greater detail in Chapter 3 of the draft joint TSD. First we provide a brief summary of the technologies we have considered in this prop osal before highlighting the above-mentioned items that are new for this proposal. We request comment on all aspects of our analysis as discussed here and detailed in the draft joint TSD.

1. What Technologies did the Agencies Consider?

For this proposal, the agencies project that manufacturers can add a variety of technologies to each of their vehicle models and or platforms in order to improve the vehicles’ fuel economy and GHG performance. In order to analyze a variety of regulatory alternative scenarios, it is essential to have a thorough und erstanding of the technologies available to the manufacturers. This analysis includes an assessment of the cost, effectiveness, availability, development time, and manufacturability of vari ous technologies within the normal redesign and refresh periods of a vehicle line (or in the design of a new vehicle). As we describe in the draft Joint TSD, when a technology can be applied can affect the cost as well as the technology penetration rates (or phase-in caps) that are projected in the analysis.

The agencies considered dozens of vehicle t echnologies that manufacturers could use to improve the fuel economy and reduce CO 2 emissions of their vehicles during the MYs 2017- 2025 timeframe. Many of the technologies considered are available today, are well known, and could be incorporated into vehicles once pro duct development decisions are made. These are “near-term” technologies and are identical or very similar to those anticipated in the agencies’ analyses of compliance strategies for the MYs 2012-2016 final rule. For this rulemaking, given its time frame, other technologies are also consid ered that are not currently in production, but that are beyond the initial research phase, and are under development and expected to be in production in the next 5-10 years. Examples of these technologies are downsized and turbocharged engines operating at combustion pressures even higher than today’s turbocharged

126 “Assessment of Fuel Economy Technologies for Light -Duty Vehicles”, National Research Council of the National Academies, June 2010.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 112 of 768 engines, and an emerging hybrid architecture comb ined with an 8 speed dual clutch transmission, a combination that is not available today. These are technologies which the agencies believe can, for the most part, be applied both to cars and trucks, and which are expected to achieve significant improvements in fuel economy and reductions in CO 2 emissions at reasonable costs in the MYs 2017 to 2025 timeframe. The agencies did not consider technologies that are currently in an initial stage of research because of the uncertainty involved in the availability and feasibility of implementing these t echnologies with significant penetration rates for this analysis. The agencies recognize that due to the relatively long time frame between the date of this proposal and 2025, it is very possible that new and innovative technologies will make their way into the fleet, perhaps even in significant numbers, that we have not considered in this analysis. We expect to reconsider such technologies as pa rt of the mid-term evaluation, as appropriate, and possibly could be used to generate credits under a number of the proposed flexibility and incentive programs provided in the proposed rules.

The technologies considered can be grouped into four broad categories: engine technologies; transmission technologies; vehicle t echnologies (such as mass reduction, tires and aerodynamic treatments); and electrification technol ogies (including hybridization and changing to full electric drive). 127 The specific technologies within each broad group are discussed below. The list of technologies presented below is nearly identical to that presented in both the MYs 2012-2016 final rule and the 2010 TAR, with th e following new technologies added to the list since the last final rule: the P2 hybrid, a newl y emerging hybridization technology that was also considered in the 2010 TAR; continued improvements in gasoline engines, with greater efficiencies and downsizing; continued signifi cant efficiency improvements in transmissions; and ongoing levels of improvement to some of the seemingly more basic technologies such as lower rolling resistance tires and aerodynamic treatments, which are among the most cost effective technologies available for reducing fu el consumption and GHGs. Not included in the list below are technologies specific to air conditioning system improvements and off-cycle controls, which are presented in Section II.F of this NPRM and in Chapter 5 of the draft Joint
TSD.

a. Types of Engine Technologies Considered

Low-friction lubricants including low viscosity and advanced low friction lubricant oils are now available with improved performance. If manufacturers choose to make use of these lubricants, they may need to make engine changes and conduct durability testing to accommodate the lubricants. The costs in our analysis consider these engine changes and testing requirements. This level of low friction lubricants is expected to exceed 85 percent penetration by the 2017 MY.

Reduction of engine friction losses can be achieved through low-tension piston rings, roller cam followers, improved material coatings, more optimal thermal management, piston surface treatments, and other improvements in the design of engine components

127 NHTSA’s analysis considers these technologies in five gr oups rather than four – hybridization is one category, and “electrification/accessories” is another.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 113 of 768 and subsystems that improve efficient engine operation. This level of engine friction reduction is expected to exceed 85 percent penetration by the 2017 MY.

Advanced Low Friction Lubricant and Second Level of Engine Friction Reduction are new for this analysis. As technologies advance between now and the rulemaking timeframe, there will be further development in low friction lubricants and engine friction reductions. The agencies grouped the development in these two areas into a single technology and applied them for MY 2017 and beyond.

Cylinder deactivation disables the intake and exhaust valves and prevents fuel injection into some cylinders during light-load operation. The engine runs temporarily as though it were a smaller engine which substantially reduces pumping losses.

Variable valve timing alters the timing of the intake valves, exhaust valves, or both, primarily to reduce pumping losses, increase specific power, and control residual gases.

Discrete variable valve lift increases efficiency by optimizing air flow over a broader range of engine operation which reduces pumping losses. This is accomplished by controlled switching between two or more cam profile lobe heights.

Continuous variable valve lift is an electromechanical or electrohydraulic system in which valve timing is changed as lift height is controlled. This yields a wide range of performance optimization and volumetric efficien cy, including enabling the engine to be valve throttled.

Stoichiometric gasoline direct-injection technology injects fuel at high pressure directly into the combustion chamber to improve cooling of the air/fuel charge as well as combustion quality within the cylinder, which allows for higher compression ratios and increased thermodynamic efficiency.

Turbo charging and downsizing increases the available airflow and specific power level, allowing a reduced engine size while maintaining performance. Engines of this type use gasoline direct injection (GDI) and dual cam phasing. This reduces pumping losses at lighter loads in comparison to a larger engine. We continue to include an 18 bar brake mean effective pressure (BMEP) technology (as in the MYs 2012-2016 final rule) and are also including both 24 bar BMEP and 27 bar BMEP technologies. The 24 bar BMEP technology would use a single-stage, variable geometry turbocharger which would provide a higher intake boost pressure available across a broader range of engine operation than conventional 18 bar BMEP engines. The 27 bar BMEP technology requires additional boost and thus would us e a two-stage turbocharger necessitating use of cooled exhaust gas recirculation (EGR) as described below. The18 bar BMEP technology is applied with 33 percent engine downsizing, 24 bar BMEP is applied with 50 percent engine downsizing, and 27 bar BMEP is applied with 56 percent engine downsizing.

Cooled exhaust-gas recirculation (EGR) reduces the incidence of knocking combustion with additional charge dilution and obviates th e need for fuel enrichment at high engine power. This allows for higher boost pressure and/or compression ratio and furtherSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 114 of 768 reduction in engine displacement and both pumping and friction losses while maintaining performance. Engines of this type use GDI and both dual cam phasing and discretevariable valve lift. The EGR systems considered in this assessment would use a dualloop system with both high and low pressure EGR loops and dual EGR coolers. For this proposal, cooled EGR is considered to be a technology that can be added to a 24 bar BMEP engine and is an enabling technology for 27 bar BMEP engines.

Diesel engines have several characteristics that give superior fuel efficiency, including reduced pumping losses due to lack of (or great ly reduced) throttling, high pressure direct injection of fuel, a combustion cycle that operates at a higher compression ratio, and a very lean air/fuel mixture relative to an equivalent-performance gasoline engine. This technology requires additional enablers, such as a NOx adsorption catalyst system or a urea/ammonia selective catalytic reduction sy stem for control of NOx emissions during lean (excess air) operation.

b. Types of Transmission Technologies Considered

Improved automatic transmission controls optimize the shift schedule to maximize fuel efficiency under wide ranging conditions and minimizes losses associated with torque converter slip through lock-up or modulation. The first level of controls is expected to exceed 85 percent penetration by the 2017 MY.

Shift optimization is a strategy whereby the engine and/or transmission controller(s) emulates a CVT by continuously evaluating all possible gear options that would provide the necessary tractive power and select the best gear ratio that lets the engine run in the most efficient operating zone.

Six-, seven-, and eight-speed automatic transmissions are optimized by changing the gear ratio span to enable the engine to operate in a more efficient operating range over a broader range of vehicle operating conditions. While a six speed transmission application was most prevalent for the MYs 2012-2016 final rule, eight speed transmissions are expected to be readily available and applied in the MYs 2017 through 2025 timeframe.

Dual clutch or automated shift manual transmissions are similar to manual transmissions, but the vehicle controls shifting and launch functions. A dual-clutch automated shift manual transmission (DCT) uses separate clutches for even-numbered and odd-numbered gears, so the next expected gear is pre-se lected, which allows for faster and smoother shifting. The 2012-2016 final rule limited DCT applications to a maximum of 6-speeds. For this proposal we have considered both 6-speed and 8-speed DCT transmissions.

Continuously variable transmission commonly uses V-shaped pulleys connected by a metal belt rather than gears to provide ratios for operation. Unlike manual and automatic transmissions with fixed transmission ratios, continuously variable transmissions can provide fully variable and an infinite number of transmission ratios th at enable the engine to operate in a more efficient operating range over a broader range of vehicle operating conditions. The CVT is maintained for existing baseline vehicles and not considered forSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 115 of 768 future vehicles in this proposal due to the av ailability of more cost effective transmission technologies.

Manual 6-speed transmission offers an additional gear ratio, often with a higher overdrive gear ratio, than a 5-speed manual transmission.

High Efficiency Gearbox (automatic, DCT or manual) – continuous improvement in seals, bearings and clutches, super finishing of gearbox parts, and development in the area of lubrication, all aimed at reducing frictional and other parasitic load in the system for an automatic or DCT type transmission.

c. Types of Vehicle Technologies Considered

Lower-rolling-resistance tires have characteristics that reduce frictional losses associated with the energy dissipated mainly in the deformation of the tires under load, thereby improving fuel economy and reducing CO 2 emissions. New for this proposal (and also marking an advance over low rolling resistance tires considered during the heavy duty greenhouse gas rulemaking, see 76 FR at 57207, 57229) is a second level of lower rolling resistance tires that reduce frictional losses ev en further. The first level of low rolling resistance tires will have 10 percent rolling resistance reduction while the 2 nd level would have 20 percent rolling resistance reduction compared to 2008 baseline vehicle. The first level of lower rolling resistance tires is expected to exceed 85 percent penetration by the
2017 MY.

Low-drag brakes reduce the sliding friction of disc brake pads on rotors when the brakes are not engaged because the brake pads are pulled away from the rotors.

Front or secondary axle disconnect for four-wheel drive systems provides a torque distribution disconnect between front and rear axles when torque is not required for the non-driving axle. This results in the reduction of associated parasitic energy losses.

Aerodynamic drag reduction can be achieved via two approaches, either reducing the drag coefficients or reducing vehicle frontal ar ea. To reduce the drag coefficient, skirts, air dams, underbody covers, and more aerodynamic side view mirrors can be applied. In addition to the standard aerodynamic treatment s, the agencies have included a second level of aerodynamic technologies which coul d include active grill shutters, rear visors, and larger under body panels. The first level of aero dynamic drag improvement is estimated to reduce aerodynamic drag by 10 percent relative to the baseline 2008 vehicle while the second level would reduce aero dynamic drag by 20 percent relative to 2008 baseline vehicles. The second level of aerodynamic technologies was not considered in the MYs 2012-2016 final rule.

Mass Reduction can be achieved in many ways, such as material substitution, design optimization, part consolidation, improving manufacturing process, etc. The agencies applied mass reduction of up to 20 percent re lative to MY 2008 levels in this NPRM compared to only 10 percent in 2012-2016 final rule. The agencies also determined effectiveness values for hybrid, plug-in and el ectric vehicles based on net mass reduction, or the delta between the applied mass reduction (capped at 20 percent) and the addedSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 116 of 768 mass of electrification components. In asse ssing compliance strategies and in structuring the standards, the agencies only considered amounts of vehicle mass reduction that would result in what we estimated to be no adverse effect on overall fleet safety. The agencies have an extensive discussion of mass reduction technologies as well as the cost of mass reduction in chapter 3 of the draft joint TSD.

d. Types of Electrification/Accessory a nd Hybrid Technologies Considered

Electric power steering (EPS)/ Elect ro-hydraulic power steering (EHPS) is an electrically-assisted steering system that has advantages over traditional hydraulic power steering because it replaces a continuously operated hydraulic pump, thereby reducing parasitic losses from the accessory drive. Manufacturers have informed the agencies that full EPS systems are being developed for all light-duty vehicles, including large trucks. However, the agencies have applied the EHPS technology to large trucks and the EPS technology to all other light-duty vehicles.

Improved accessories (IACC) may include high efficiency al ternators, electrically driven (i.e., on-demand) water pumps and cooling fans. This excludes other electrical accessories such as electric oil pumps and elect rically driven air conditioner compressors. New for this proposal is a second level of IACC (IACC2) which consists of the IACC technologies and the addition of a mild rege neration strategy and a higher efficiency alternator. The first level of IACC improvements is expected to be at more than 85 percent penetration by the 2017MY.

12-volt Stop-Start

, sometimes referred to as idle-stop or 12-volt micro hybrid is the most basic hybrid system that facilitates idle-stop capability. These systems typically incorporate an enhanced performance battery and other features such as electric transmission and cooling pumps to maintain vehicle systems during idle-stop.

Higher Voltage Stop-Start/Belt Integrated Starter Generator (BISG) sometimes referred to as a mild hybrid, provides idle-stop capab ility and uses a higher voltage battery with increased energy capacity over typical automotive batteries. The higher system voltage allows the use of a smaller, more powerful electric motor. This system replaces a standard alternator with an enhanced power , higher voltage, higher efficiency starteralternator, that is belt driven and that can recover braking energy while the vehicle slows down (regenerative braking). This mild hybrid technology is not included by either agency as an enabling technology in the analysis supporting this proposal, although some automakers have expressed interest in possibly using the technology during the rulemaking time frame. EPA and NHTSA are providing incentives to encourage this and similar hybrid technologies on pick-up trucks in particular, as described in Section II.F, and the agencies are in the process of including this technology for the final rule analysis as we expand our understanding of the associated costs and limitations.

Integrated Motor Assist (IMA)/Crank integrated starter generator (CISG) provides idlestop capability and uses a high voltage battery with increased energy capacity over typical automotive batteries. The higher system voltage allows the use of a smaller, more powerful electric motor and reduces the weight of the wiring harness. This systemSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 117 of 768 replaces a standard alternator with an enhan ced power, higher voltage, higher efficiency starter-alternator that is crankshaft mounted and can recover braking energy while the vehicle slows down (regenerative braking). The IMA technology is not included by either agency as an enabling technology in the analysis supporting this proposal, although it is included as a baseline technology because it exists in our 2008 baseline fleet.

P2 Hybrid is a newly emerging hybrid technology that uses a transmission integrated electric motor placed between the engine and a gearbox or CVT, much like the IMA system described above except with a wet or dry separation clutch which is used to decouple the motor/transmission from the e ngine. In addition, a P2 hybrid wouldtypically be equipped with a larger electric machine. Disengaging the clutch allows allelectric operation and more efficient brake-energy recovery. Engaging the clutch allows efficient coupling of the engine and electric motor and, when combined with a DCT transmission, reduces gear-train losses relative to power-split or 2-mode hybrid systems.

2-Mode Hybrid is a hybrid electric drive system that uses an adaptation of a conventional stepped-ratio automatic transmission by replaci ng some of the transmission clutches with two electric motors that control the ratio of engine speed to vehicle speed, while clutches allow the motors to be bypassed. This impr oves both the transmission torque capacity for heavy-duty applications and reduces fuel consumption and CO 2 emissions at highway speeds relative to other types of hybrid electric drive systems. The 2-mode hybrid technology is not included by either agency as an enabling technology in the analysis supporting this proposal, although it is included as a baseline technology because it exists
in our 2008 baseline fleet.

Power-split Hybrid is a hybrid electric drive system that replaces the traditional transmission with a single planetary gearset and a motor/generator. This motor/generator uses the engine to either charge the battery or supply additional power to the drive motor. A second, more powerful motor/generator is pe rmanently connected to the vehicle’s final drive and always turns with the wheels. Th e planetary gear splits engine power between the first motor/generator and the drive motor to either charge the battery or supply power to the wheels. The power-split hybrid technology is not included by e ither agency as an enabling technology in the analysis supporting this proposal, (the agencies evaluate the P2 hybrid technology discussed above wher e power-split hybrids might otherwise have been appropriate) although it is included as a baseline technology because it exists in our 2008 baseline fleet.

Plug-in hybrid electric vehicles (PHEV) are hybrid electric vehicles with the means to charge their battery packs from an outside source of electricity (usually the electric grid). These vehicles have larger battery packs with more energy storage and a greater capability to be discharged th an other hybrid electric vehicles. They also use a control system that allows the battery pack to be substantially depleted under electric-only or blended mechanical/electric operation and batteries that can be cycled in charge sustaining operation at a lower state of charge than is typical of other hybrid electric vehicles. These vehicles are sometimes referr ed to as Range Extended Electric VehiclesSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 118 of 768 (REEV). In this MYs 2017-2025 analysis, PH EVs with several all-electric ranges—both a 20 mile and a 40 mile all-electric range—have been included as potential technologies.

Electric vehicles (EV) are equipped with all-electric drive and with systems powered by energy-optimized batteries charged primarily from grid electricity. EVs with several ranges—75 mile, 100 mile and 150 mile range—have been included as potential technologies.

e. Technologies Considered but Deemed “Not Ready” in the MYs 2017-2025 Timeframe

Fuel cell electric vehicles (FCEVs) utilize a full electric drive platform but consume electricity generated by an on-board fuel cel l and hydrogen fuel. Fuel cells are electrochemical devices that direct ly convert reactants (hydrogen and oxygen via air) into electricity, with the potential of achieving more than twice the efficiency of conventional internal combustion engines. High pressure gaseous hydrogen storage tanks are used by most automakers for FCEVs that are currently under development. The high pressure tanks are similar to those used for compressed gas storage in more than 10 million CNG vehicles worldwide, except that they are designed to operate at a higher pressure (350 bar or 700 bar vs. 250 bar for CNG). While we expect there will be some limited introduction of FCEVs into the market place in the time frame of this rule, we expect this introduction to be relatively small, and thus FCEVs are not considered in the modeling analysis conducted for this proposal.

There are a number of other technologies that the agencies have not considered in their analysis, but may be considered for the final rule. These include HCCI, “multi-air”, and camless valve actuation, and other advanced engines currently under development.

2. How did the Agencies Determine the Costs of Each of these Technologies?

As noted in the introduction to this sectio n, most of the direct cost estimates for technologies carried over from the MYs 2012-2016 final rule and subsequently used in this proposal are fundamentally unchanged since the MYs 2012-2016 final rule analysis and/or the 2010 TAR. We say “fundamentally” unchanged sin ce the basis of the direct manufacturing cost estimates have not changed; however, the costs ha ve been updated to more recent dollars, the learning effects have resulted in further cost reduc tions for some technologies, the indirect costs are calculated using a modified methodology and the impact of long-term ICMs is now present during the rulemaking timeframe. Besides these changes, there are also some other notable changes to the costs used in previous analyses. We highlight these changes in Section II.D.2.a, below. We highlight the changes to the indirect cost methodology and adjustments to more recent dollars in Sections II.D.2.b and c. Lastly, we present some updated terminology used for our approach to estimating learning effects in an effort to eliminate confusion with our past terminology. This is discussed in Section II.D.2.d, below.

The agencies note that the technology costs included in this proposal take into account only those associated with the initial build of th e vehicle. Although comments were received to the MYs 2012-2016 rulemaking that suggested there could be additional maintenance requiredSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 119 of 768 with some new technologies (e.g., turbocharging, hybrids, etc.), and that additional maintenance costs could occur as a result, the agencies belie ve that it is equally possible that maintenance costs could decrease for some vehicles, especially when considering full electric vehicles (which lack routine engine maintenance) or the replace ment of automatic transmissions with simpler dual-clutch transmissions. The agencies requ est comment on the possible maintenance cost impacts associated with this proposal, remindi ng potential commenters that increased warranty costs are already considered as part of the ICMs.

a. Direct Manufacturing Costs (DMC)

For direct manufacturing costs (DMC) relate d to turbocharging, downsizing, gasoline direct injection, transmissions, as well as non- battery-related costs on hybrid, plug-in hybrid and electric vehicles, the agencies have relied on costs derived from teardown studies. For battery related DMC for HEVs, PHEVs and EVs, the agencies have relied on the BatPaC model developed by Argonne National Laboratory for the Department of Energy. For mass reduction DMC, the agencies have relied on several studies as described in detail in the draft Joint TSD. We discuss each of these briefly here and in more detail in the draft joint TSD. For the majority of the other technologies considered in this pr oposal and described above, the agencies have relied on the 2012-2016 final rule and sources described there for estimates of DMC.

i. Costs from Tear-down Studies

As a general matter, the agencies believe that the best method to derive technology cost estimates is to conduct studies involving tear- down and analysis of actual vehicle components. A “tear-down” involves breaking down a technology into its fundamental parts and manufacturing processes by completely disassembling actual vehicles and vehicle subsystems and precisely determining what is required for its production. The result of the tear-down is a “bill of materials” for each and every part of the relevant vehicle systems. This tear-down method of costing technologies is often used by manufacturers to benchmark their products against competitive products. Historically, ve hicle and vehicle component tear-down has not been done on a large scale by researchers and regulators due to the expense required for such studies. While tear-down studies are highly accurate at costing technologies for the year in which the study is intended, their accuracy, like that of all cost projections, may diminish over time as costs are extrapolated further into th e future because of uncertainties in predicting commodities (and raw material) prices, labor rate s, and manufacturing practices. The projected costs may be higher or lower than predicted.

Over the past several years, EPA has contracted with FEV, Inc. and its subcontractor Munro & Associates, to conduct tear-down cost studies for a number of key technologies evaluated by the agencies in assessing the feasib ility of future GHG and CAFE standards. The analysis methodology included procedures to scale the tear-down results to smaller and larger vehicles, and also to different technology conf igurations. FEV’s methodology was documented in a report published as part of the MY 2012-2 016 rulemaking, detailing the costing of the firstSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 120 of 768 tear-down conducted in this work (#1 in the below list). 128 This report was peer reviewed by experts in the industry and revised by FEV in response to the peer review comments. 129
Subsequent tear-down studies (#2-5 in the below list) were documented in follow-up FEV reports made available in the public docket for the MY 2012-2016 rulemaking. 130

Since then, FEV’s work under th is contract work assignment has continued. Additional cost studies have been completed and are available for public review. 131 The most extensive study, performed after the MY 2012-2016 Final Rule, involved whole-vehicle tear-downs of a 2010 Ford Fusion powersplit hybrid and a conventional 2010 Ford Fu sion. (The latter served as a baseline vehicle for comparison.) In addition to providing powersplit HEV costs, the results for individual components in these vehicles we re subsequently used by FEV/Munro to cost another hybrid technology, the P2 hybrid, which employs similar hardware. This approach to costing P2 hybrids was undertaken because P2 HEVs were not yet in volume production at the time of hardware procurement for tear-down. Finally, an automotive lithium-polymer battery was torn down and costed to provide supplemental battery costing information to that associated with the NiMH battery in the Fusion. This HEV cost work, including the extension of results to P2 HEVs, has been extensively documented in a new report prepared by FEV. 132 Because of the complexity and comprehensive scope of this HEV analysis, EPA commissioned a separate peer review focused exclusively on it. Reviewer comments generally supported FEV’s methodology and results, while including a number of suggestions for improvement many of which were subsequently incorporated into FEV’s analysis an d final report. The peer review comments and responses are available in the rulemaking docket. 133, 134

Over the course of this work assignment, teardown-based studies have been performed thus far on the technologies listed below. These completed studies provide a thorough evaluation of the new technologies’ costs relative to their baseline (or replaced) technologies.

1. Stoichiometric gasoline direct injectio n (SGDI) and turbocharging with engine downsizing (T-DS) on a DOHC (dual overhead cam) I4 engine, replacing a conventional DOHC I4 engine.
2. SGDI and T-DS on a SOHC (single overhead cam) on a V6 engine, replacing a conventional 3-valve/cylinder SOHC V8 engine.
3. SGDI and T-DS on a DOHC I4 engine, replacing a DOHC V6 engine.

128 U.S. EPA, “Light-Duty Technology Cost Analysis Pilo t Study,” Contract No. EP-C-07-069, Work Assignment 1- 3, December 2009, EPA-420-R-09-020, Docket EPA-HQ-OAR-2009-0472- 11282

129 FEV pilot study response to peer review document November 6, 2009, is at EPA-HQ-OAR-2009-0472-11285

130 U.S. EPA, “Light-duty Technology Cost Analysis – Report on Additional Case Studies,” EPA-HQ-OAR-2009- 0472-11604

131 [Compilation of FEV study reports for 8spAT, 8spDCT, mild HEV, and Multi-Air]

132 FEV, Inc., “Light-Duty Technology Cost Analys is, Power-split and P2 HEV Case Studies”,

133 ICF, “Peer Review of FEV Inc. Report “Light Duty Technology Cost Analysis, Power-Split and P2 Hybrid Electric Vehicle Case Studies”, March 31, 2011.

134 FEV and EPA, Peer Review Report - Response to Comments Document for “Light Duty Technology Cost Analysis, Power-Split and P2 Hybrid Electri c Vehicle Case Studies”, October 3, 2011.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 121 of 768 4. 6-speed automatic transmission (AT), replacing a 5-speed AT.
5. 6-speed wet dual clutch transmission (DCT) replacing a 6-speed AT.
6. 8-speed AT replacing a 6-speed AT.
7. 8-speed DCT replacing a 6-speed DCT.
8. Power-split hybrid (Ford Fusion with I4 engine) compared to a conventional vehicle (Ford Fusion with V6). The results from th is tear-down were extended to address P2 hybrids. In addition, costs from individual components in this tear-down study were used by the agencies in developing cost estimates for PHEVs and EVs.
9. Mild hybrid with stop-start technology (S aturn Vue with I4 engine), replacing a conventional I4 engine. (Although results from this cost study are included in the rulemaking docket, they were not used by the agencies in this rulemaking’s technical analyses.)
10. Fiat Multi-Air engine technology. (Although results from this cost study are included in the rulemaking docket, th ey were not used by the agencies in this rulemaking’s technical analyses.)

Items 6 through 10 in the list above are new since the 2012-2016 final rule.

In addition, FEV and EPA extrapolated the engine downsizing costs for the following scenarios that were based on the above study cases:

1. Downsizing a SOHC 2 valve/cylinder V8 engine to a DOHC V6.
2. Downsizing a DOHC V8 to a DOHC V6.
3. Downsizing a SOHC V6 engine to a DOHC 4 cylinder engine.
4. Downsizing a DOHC 4 cylinder engine to a DOHC 3 cylinder engine.

The agencies have relied on the findings of FEV for estimating the cost of the technologies covered by the tear-down studies.

ii. Costs of HEV, EV & PHEV

The agencies have also reevaluated the co sts for HEVs, PHEVs, and EVs since both the 2012-2016 final rule and the 2010 TAR. First, electrified vehicle technologies are developing rapidly and the agencies sought to capture results from the most recent analysis. Second, the 2012-2016 rule employed a single $/kWhr estimate and did not consider the specific vehicle and technology application for the battery when we estimated the cost of the battery. Specifically, batteries used in HEVs (high power density ap plications) versus EVs (high energy density applications) need to be considered appropriatel y to reflect the design differences, the chemical material usage differences and differences in $/kWhr as the power to energy ratio of the battery changes for different applications.

To address these issues for this proposal, the agencies have done two things. First, EPA has developed a spreadsheet tool that was used to size the motor and battery based on the
different road load of various ve hicle classes. Second, the agencies have used a battery cost model developed by Argonne National Laboratory (ANL) for the Vehicle Technologies ProgramSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 122 of 768 of the U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy. 135
The model developed by ANL allows users to estimate unique battery pack costs using user customized input sets for different hybridizati on applications, such as strong hybrid, PHEV and EV. The DOE has established long term industry goals and targets for advanced battery systems as it does for many energy efficient technologies. ANL was funded by DOE to provide an independent assessment of Li-ion battery costs because of ANL’s expertise in the field as one of the primary DOE National Laboratories responsible for basic and applied battery energy storage technologies for future HEV, PHEV and EV app lications. Since publication of the 2010 TAR, ANL’s battery cost model has been peer-reviewed and ANL has updated the model and documentation to incorporate suggestions from peer-reviewers, such as including a battery management system, a battery disconnect unit, a thermal management system, etc. 136 In this proposal, NHTSA and EPA have used the recently revised version of this updated model.

The agencies are using the ANL model as the basis for estimating large-format lithiumion batteries for this assessment for the following reasons. The model was developed by scientists at ANL who have significant experience in this area. The model uses a bill of materials methodology for developing cost estimates. The ANL model appropriately considers the vehicle application’s power and energy requirements, which are two of the fundamental parameters when designing a lithium-ion batter y for an HEV, PHEV, or EV. The ANL model can estimate production costs based on user defined inputs for a range of production volumes. The ANL model’s cost estimates, while generally lower than the estimates we received from the OEMs, are consistent with some of the supplier cost estimates that EPA received from largeformat lithium-ion battery pack manufacturers. This includes data which was received from onsite visits done by the EPA in the 2008-2011 time frame. Finally, the ANL model has been described and presented in the public domain and does not rely upon confidential business information (which could not be reviewed by the public).

The potential for future reductions in battery cost and improvements in battery performance relative to current batteries will pl ay a major role in determining the overall cost and performance of future PHEVs and EVs. The U.S. Department of Energy manages major battery-related R&D programs and partnerships, and has done so for many years, including the ANL model utilized in this report. DOE has re viewed the battery cost projections underlying this proposal and supports the use of the ANL model for the purposes of this rulemaking. 137

We have also estimated cost associated with in-home chargers and installation of in-home chargers expected to be necessary for PHEVs and EVs. Charger costs are covered in more detail in chapter 3 of the draft Joint TSD.

135 Insert cite to ANL BatPac model, if we can.

136 Cite ANL BatPaC peer review report.

137 Cite a DOE memo or email that documents this support?Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 123 of 768 iii. Mass Reduction Costs

The agencies have revised the costs for mass reduction from the MYs 2012-2016 rule and the 2010 Technical Assessment Report. For this proposal, the agencies are relying on a wide
assortment of sources from the literature as we ll as data provided from a number of OEMs. Based on this review, the agencies have estimated a new cost curve such that the costs increase
as the levels of mass reduction increase. For th e final rule the agencies will consider any new studies that become available, including two stud ies that the agencies are sponsoring and expect will be completed in time to inform the final rule. These studies are discussed in TSD chapter 3.

b. Indirect Costs (IC)

i. Markup Factors to Estimate Indirect Costs

For this analysis, indirect costs are estimate d by applying indirect cost multipliers (ICM)
to direct cost estimates. ICMs were derive d by EPA as a basis for estimating the impact on indirect costs of individual vehicle technology ch anges that would result from regulatory actions. Separate ICMs were derived for low, medium, and high complexity technologies, thus enabling
estimates of indirect costs that reflect the variat ion in research, overhead, and other indirect costs that can occur among different technologies. ICMs were also applied in the MYs 2012-2016 rulemaking.

Prior to developing the ICM methodology, 138 EPA and NHTSA both applied a retail price equivalent (RPE) factor to estimate indirect co sts. RPEs are estimated by dividing the total revenue of a manufacturer by the direct manufacturing costs. As such, it includes all forms of
indirect costs for a manufacturer and assumes that the ratio applies equally for all technologies.
ICMs are based on RPE estimates that are then modified to reflect only those elements of indirect costs that would be expected to change in response to a regulatory-induced technology change. For example, warranty costs would be reflected in both RPE and ICM estimates, while marketing costs might only be reflected in an RPE estimate but not an ICM estimate for a particular technology, if the new regulatory-induced technology change is not one expected to be
marketed to consumers. Because ICMs calcula ted by EPA are for individual technologies, many of which are small in scale, they often reflect a subset of RPE costs; as a result, for low complexity technologies, the RPE is typically higher than the ICM. This is not always the case, as ICM estimates for particularly complex tec hnologies, specifically hybrid technologies (for near term ICMs), and plug-in hybrid battery and full electric vehicle techno logies ( for near term and long term ICMs), reflect higher than average indirect costs, with the resulting ICMs for those technologies equaling or exceeding the averaged RPE for the industry.

138 The ICM methodology was developed by RTI International, under contract to EPA. The results of the RTI report were published in Alex Rogozhin, Michael Gallaher, Glor ia Helfand, and Walter McManus, “Using Indirect Cost Multipliers to Estimate the Total Cost of Adding New Technology in the Automobile Industry.” International Journal of Production Economics 124 (2010): 360-368. [Docket item #]Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 124 of 768 There is some level of uncertainty surrounding both the ICM and RPE markup factors. The ICM estimates used in this proposed action group all technologies into four broad categories and treat them as if individual technologies within each of the categories (“low”, “medium”, “high1” and “high2” complexity) will have the same ratio of indirect costs to direct costs. This simplification means it is likely that the direct co st for some technologies within a category will be higher and some lower than the estimate for the category in general. More importantly, the ICM estimates have not been validated through a direct accounting of actual indirect costs for individual technologies. Rather, the ICM esti mates were developed using adjustment factors developed in two separate occasions: the first, a consensus process, was reported in the RTI report; the second, a modified Delphi method, was conducted separately and reported in an EPA

memo. 139 Both these panels were composed of EPA staff members with previous background in the automobile industry; the memberships of the two panels overlapped but were not identical. 140
The panels evaluated each element of the industry’s RPE estimates and estimated the degree to which those elements would be expected to change in proportion to changes in direct manufacturing costs. The method and estimates in the RTI report were peer reviewed by three industry experts and subsequently by reviewers for the International Journal of Production Economics. RPEs themselves are inherently difficult to estimate because the accounting statements of manufacturers do not neatly categorize al l cost elements as either direct or indirect costs. Hence, each researcher developing an RPE estimate must apply a certain amount of judgment to the allocation of the costs. Since em pirical estimates of ICMs are ultimately derived from the same data used to measure RPEs, this affects both measures. However, the value of RPE has not been measured for specific technologi es, or for groups of specific technologies. Thus applying a single average RPE to any give n technology by definition overstates costs for very simple technologies, or understates them for advanced technologies.

In every recent GHG and fuel economy rulemaking proposal, we have requested
comment on our ICM factors and whether it is most appropriate to use ICMs or RPEs. We have generally received little to no co mment on the issue specifically, other than basic comments that the ICM values are too low. In addition, in the June 2010 NAS report, NAS noted that the under the initial ICMs, no technology would be assumed to have indirect costs as high as the average RPE. NRC found that “RPE factors certainly do vary depending on the complexity of the task of integrating a component into a vehicle system, the extent of the required changes to other components, the novelty of the technology, and other factors. However, until empirical data derived by means of rigorous estimation methods are available, the committee prefers to use average markup factors.” 141 The committee also stated that “The EPA (Rogozhin et al., 2009),

139 Helfand, Gloria, and Sherwood, Todd. “Documentation of the Development of Indirect Cost Multipliers for Three Automotive Technologies.” Memorandum, Assessme nt and Standards Division, Office of Transportation and Air Quality, U.S. Environmental Protection Agency, August 2009. [Docket item #]

140 NHTSA staff participated in the development of the proc ess for the second, modified Delphi panel, and reviewed the results as they were developed, but did not serve on the panel.

141 NRC, Finding 3-2 at page 3-23.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 125 of 768 however, has taken the first steps in attempting to analyze this problem in a way that could lead to a practical method of estimating technology-specific markup factors” where “this problem” spoke to the issue of estimating technology-s pecific markup factors and indirect cost multipliers. 142

The agencies note that, since the committee completed their work, EPA has published its
work in the Journal of Production Economics 143 and has also published a memorandum furthering the development of ICMs, 144 neither of which the committee had at their disposal. Further, having published two final rulemakings—the 2012-2016 light-duty rule (see 75 FR 25324) and the more recent heavy-duty GHG rule (see 76 FR 57106)—as well as the 2010 TAR
where ICMs served as the basis for all or most of the indirect costs, EPA believes that ICMs are indeed fully developed for regulatory purposes. As thinking has matured, we have adjusted our ICM factors such that they are slightly higher and, importantly, we have changed the way in which the factors are applied.

The first change—increased ICM factors—has been done as a result of further thought among EPA and NHTSA that the ICM factors presented in the original RTI report for low and medium complexity technologies should no longer be used and that we should rely solely on the modified-Delphi values for these complexity levels. For that reason, we have eliminated the averaging of original RTI values with modified -Delphi values and instead are relying solely on the modified-Delphi values for low and medium complexity technologies. The second change— the way the factors are applied—results in the warranty portion of the indirect costs being applied as a multiplicative factor (thereby d ecreasing going forward as direct manufacturing costs decrease due to learning), and the remainder of the indirect costs being applied as an additive factor (thereby remaining constant year-over-year and not being reduced due to learning). This second change has a comparatively large impact on the resultant technology costs and, we believe, more appropriately estimates costs over time. In addition to these changes, a secondary-level change was also made as part of this ICM recalculation to ICMs. That change was to revise upward the RPE level reported in the original RTI report from an original value of 1.46 to 1.5, to reflect the long term average RPE. The original RTI study was based on 2008 data. However, an analysis of hist orical RPE data indicates that, although there is year to year variation, the average RPE has rema ined roughly constant at 1.5. ICMs will be applied to future years’ data and, therefore, NHTSA and EPA staffs believe that it would be appropriate to base ICMs on the historical average rather than a single year’s result. Therefore,

142 NRC at page 3-19.

143 Alex Rogozhin, Michael Gallaher, Gloria Helfand, a nd Walter McManus, “Using Indirect Cost Multipliers to Estimate the Total Cost of Adding New Technology in the Automobile Industry.” International Journal of Production Economics 124 (2010): 360-368 (Docket item #XX).

144 Helfand, Gloria, and Sherwood, Todd. “Documentation of the Development of Indirect Cost Multipliers for Three Automotive Technologies.” Memorandum, Assessme nt and Standards Division, Office of Transportation and Air Quality, U.S. Environmental Protection Agency, August 2009 (Docket item #XX).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 126 of 768 ICMs have been adjusted to reflect this aver age level. These changes to the ICMs and the methodology are described in greater detail in Chapter 3 of the draft Joint TSD.

ii. Stranded Capital

Because the production of automotive components is capital-intensive, it is possible for substantial capital investments in manufacturing equipment and facilities to become “stranded” (where their value is lost, or diminished). This would occur when the capital is rendered useless (or less useful) by some factor that forces a majo r change in vehicle design, plant operations, or manufacturer’s product mix, such as a shift in cons umer demand for certain vehicle types. It can also be caused by new standards that phase-in at a rate too rapid to accommodate planned replacement or redisposition of existing capital to other activities. The lost value of capital equipment is then amortized in some way over production of the new technology components.

It is difficult to quantify accurately any capital stranding associated with new technology phase-ins under the proposed standards because of the iterative dynamic involved – that is, the new technology phase-in rate strongly affects th e potential for additional cost due to stranded capital, but that additional cost in turn affects the degree and rate of phase-in for other individual competing technologies. In addition, such an analysis is very company-, factory-, and manufacturing process-specific, particularly in re gard to finding alternative uses for equipment and facilities. Nevertheless, in order to account for the possibility of stranded capital costs, the agencies asked FEV to perform a separate bound ing analysis of potential stranded capital costs associated with rapid phase-in of technologies due to new standards, using data from FEV’s primary teardown-based cost analyses. 145

The assumptions made in FEV’s stranded cap ital analysis with potential for major impacts on results are:

• All manufacturing equipment was bought brand new when the old technology started production (no carryover of equipment used to make the previous components that the old technology itself replaced). • 10-year normal production runs: Manufacturing equipment used to make old technology components is straight-line depreciated over a 10-year life. • Factory managers do not optimize capital equipment phase-outs (that is, they are assumed to routinely repair and replace equipment without regard to whether or not it will soon be scrapped due to adoption of new vehicle technology). • Estimated stranded capital is amortized over 5 years of annual production at 450,000 units (of the new technology components). This annual production is identical to that assumed in FEV’s primary teardown-based cost analyses. The 5-year recovery period

145 FEV stranded capital report [update with actual title, etc] [xx Kopinski, Docket item #]Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 127 of 768 is chosen to help ensure a conservative analysis; the actual recovery would of course vary greatly with market conditions.

The stranded capital analysis was performed for three transmission technology scenarios, two engine technology scenarios, and one hybrid technology scenario. The methodology used by EPA in applying the results to the technology costs is described in EPA’s draft RIA section [DRIA xx.xx]. The methodology used by NHTSA in applying the results to the technology costs is described in NHTSA’s preliminary RIA section V.

c. Cost Adjustment to 2009 Dollars

This simple change is to update any costs presented in earlier analyses to 2009 dollars using the GDP price deflator as reported by the Bureau of Economic Analysis on January 27, 2011. The factors used to update costs from 2007 and 2008 dollars to 2009 dollars are shown below. For the final rule, we are considering moving to 2010 dollars but, for this analysis, given the timing of conducting modeling runs and developing inputs to those runs, the factors for converting to 2010 dollars were not yet available.

Table 0-7 GDP Price Deflators Used in this Proposal

2007 2008 2009
Price Index for Gross Domestic Product 106.3 108.6 109.6 Factor applied to convert to 2009 dollars 1.031 1.009 1.00 Source: Bureau of Economic Analysis, Table 1.1.4. Price Indexes for Gross Domestic Product, downloaded 1/27/2011, last revised 12/22/2010.

d. Cost Effects Due to Learning

The agencies continue to apply learning effects in the same way as we did in both the MYs 2012-2016 final rule and in the 2010 TAR. However, we have employed some new terminology in an effort to eliminate some confus ion that existed with our old terminology. This new terminology was described in the recent heavy-duty GHG final rule (see 76 FR 57320). Our old terminology suggested we were accounting for two completely different learning effects— one based on volume production and the other based on time. This was not the case since, in fact, we were actually relying on just one lear ning phenomenon, that being the learning-by-doing phenomenon that results from cumulative production volumes.

As a result, the agencies have also considered the impacts of manufacturer learning on the technology cost estimates by reflecting the phenomenon of volume-based learning curve cost reductions in our modeling using two algorithms depending on where in the learning cycle (i.e., on what portion of the learning curve) we cons ider a technology to be – “steep” portion of the curve for newer technologies and “flat” portion of the curve for more mature technologies. The observed phenomenon in the economic literature which supports manufacturer learning cost reductions are based on reductions in costs as production volumes increase with the highest absolute cost reduction occurring with the first doubling of production. The agencies use theSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 128 of 768 terminology “steep” and “flat” portion of the cu rve to distinguish among newer technologies and more mature technologies, respectively, and how learning cost reductions are applied in cost analyses.

Learning impacts have been considered on most but not all of the technologies expected to be used because some of the expected technologies are already used rather widely in the industry and, presumably, quantifiable learning impacts have already occurred. The agencies have applied the steep learning algorithm for only a handful of technologies considered to be new or emerging technologies such as PHEV an d EV batteries which are experiencing heavy development and, presumably, rapid cost declines in coming years. For most technologies, the agencies have considered them to be more established and, hence, the agencies have applied the lower flat learning algorithm. For more discussion of the learning approach and the technologies to which each type of learning has been applied the reader is directed to Chapter 3 of the draft Joint TSD.

3. How Did the Agencies Determine the Effectiveness of Each of these Technologies?

In 2007 EPA conducted a detailed vehicle simulation project to quantify the effectiveness of a multitude of technologies for the MYs 2012-2016 rule (as well as the 2010 NOI). This technical work was conducted by the global engineering consulting firm, Ricardo, Inc. and was peer reviewed and then published in 2008. For this current rule, EPA has conducted another peer reviewed study with Ricardo to broaden the scope of the original project in order to expand the range of vehicle classes and technologies considered, consistent with a longer-term outlook through model years MYs 2017-2025. The extent of the project was vast, including hundreds of thousands of vehicle simulation runs. The results were, in turn, employed to calibrate and update EPA’s lump ed parameter model, which is used to quantify the synergies and dis-synergies associated with combining tec hnologies together for the purposes of generating inputs for the agencies respective OMEGA and CAFE modeling.

Additionally, there were a number of technolo gies that Ricardo did not model explicitly. For these, the agencies relied on a variety of sources in the literature. A few of the values are identical to those presented in the MYs 2012-2016 final rule, while others were updated based on the newer version of the lumped parameter model. More details on the Ricardo simulation, lumped parameter model, as well as the effectiveness for supplemental technologies are described in Chapter 3 of the draft Joint TSD.

The agencies note that the effectiveness values estimated for the technologies considered in the modeling analyses may represent average values, and do not reflect the virtually unlimited spectrum of possible values that could result fro m adding the technology to different vehicles. For example, while the agencies have estimated an effectiveness of 0.6 to 0.8 percent, depending on the vehicle subclass for low friction lubricants, each vehicle could have a unique effectiveness estimate depending on the baseline vehicle’s oil viscosity rating. Similarly, the reduction in rolling resistance (and thus the improvement in fuel economy and the reduction in CO 2 emissions) due to the application of low rolling resistance tires depends not only on the unique characteristics of the tires originally on the vehi cle, but on the unique characteristics of the tires being applied, characteristics which must be balanced between fuel efficiency, safety, and performance. Aerodynamic drag reduction is much the same—it can improve fuel economy andSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 129 of 768 reduce CO 2 emissions, but it is also highly depend ent on vehicle-specific functional objectives. For purposes of the proposal, NHTSA and EPA believe that employing average values for technology effectiveness estimates, as adjusted depending on vehicle subclass, is an appropriate way of recognizing the potential variation in the specific benefits that individual manufacturers (and individual vehicles) might obtain from adding a fuel-saving technology.

E. Joint Economic and Other Assumptions

The agencies’ analysis of CAFE and GHG standards for the model years covered by this proposed rulemaking rely on a range of forecast information, estimates of economic variables, and input parameters. This section briefly describes the agencies’ proposed estimates of each of these values. These values play a significant role in assessing the benefits of both CAFE and GHG standards.

In reviewing these variables and the agencies’ estimates of their values for purposes of this NPRM, NHTSA and EPA reconsidered comments that the agencies previously received on both the Interim Joint TAR and during the MYs 2012-2016 light duty vehicle rulemaking and also reviewed newly available literature. As a consequence, for today’s proposal, the agencies are proposing to update some economic assumptions and parameter estimates, while retaining a majority of values consistent with the Interi m Joint TAR and the MYs 2012-2016 final rule. To review the parameters and assumptions the agen cies used in the 2012-2016 final rule, please refer to 75 FR 25378 and Chapter 4 of the Joint Technical Support Document that accompanied the final rule. 146 The proposed values summarized below are discussed in greater detail in Chapter 4 of the joint TSD that accompanies this proposal and elsewhere in the preamble and respective RIAs. The agencies seek comment on all of the assumptions discussed below.

• Costs of fuel economy-improving technologies —These inputs are discussed in summary form above and in more detail in the agencies’ respective sections of this preamble, in Chapter 3 of the draft joint TSD, and in the agencies’ respective RIAs. The technology direct manufacturing cost estimates used in this analysis are intended to represent manufacturers’ direct costs for high-volume production of vehicles with these technologies in the year for which we state the cost is considered “valid.” Technology direct manufacturing cost estimates are fundamentally unchanged from those employed by the agencies in the 2012-2016 final rule, the heavy-duty truck rule (to the extent relevant), and TAR for most technologies, although revised costs are used for batteries, mass reduction, transmissions, and a few other technologies. Indirect costs are accounted for by applying near-term indirect cost multipliers ranging from 1.24 to 1.77 to the estimates of vehicle manufacturers’ direct costs for producing or acquiring each technology, depending on the complexity of the technology and the time frame over which costs are estimated. These values are reduced to 1.19 to 1.50 over the long run as some aspects of indirect costs decline. Indirect cost markup factors have been revised from previous rulemakings and the Interim Joint TAR to reflect the agencies current thinking regarding a number of issues. These changes are discussed in detail in Section II.D.2 of this preamble and in Chapter 3 of the draft joint TSD. Details of the agencies’ technology cost

146 See http://www.epa.gov/otaq/climate/regulations/420r10901.pdf.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 130 of 768 assumptions and how they were derived can be found in Chapter 3 of the draft joint TSD.

• Potential opportunity costs of improved fuel economy —This issue addresses the possibility that achieving the fuel econom y improvements required by alternative CAFE or GHG standards would require manufacturers to compromise the performance, carrying capacity, safety, or comfort of their vehicle models. If it did so, the resulting sacrifice in the value of these attributes to consumers would represent an additional cost of achieving the required im provements, and thus of manufacturers’ compliance with stricter standards. Curren tly the agencies project that these vehicle attributes will not change as a result of this rule. Section II.C above and Chapter 2 of the draft joint TSD describes how the agency carefully selected an attribute-based standard to minimize manufacturers’ incentive to reduce vehicle capabilities. While manufacturers may choose to do this for other reasons, the agencies continue to believe that the rule itself will not result in such changes. Additionally, EPA and NHTSA have sought to include the cost of maintaining these attributes as part of the cost estimates for technologies that are included in the cost analysis for the proposal. For example, downsized engines are assumed to be turbocharged, so that they provide the same performance and utility even though they are smaller. 147 Nonetheless, it is possible that in some cases, the technology cost estimates may not include adequate allowance for the necessary efforts by manufacturers to maintain vehicle acceleration performance, payload, or utility while improving fuel econom y and reducing GHG emissions. As described in Section III.D. 3 and Section IV.G, there are two possible exceptions in cases where some vehicle types are converted to hybrid or full electric vehicles (EVs), but, in such cases, we believe that sufficient options would exist for consumers concerned about the possible loss of utility (e.g., they would purchase the non-hybridized version of the vehicle or no t buy an EV) that welfare loss should not necessarily be assumed. Although consumer vehicle demand models can measure these effects, past analyses using such models have not produced consistent estimates of buyers’ willingness-to-pay for higher fuel economy, and it is difficult to decide whether one data source, model specification, or estimation procedure is clearly preferred over another. Thus, the agencies seek comment on how to estimate explicitly the changes in vehicle buyers’ choices and welfare from the combination of higher prices for new vehicle models, increases in their fuel economy, and any accompanying changes in vehicle attributes such as performance, passenger- and cargo-carrying capacity, or other dimensions of utility.

• The on-road fuel economy “gap” –Actual fuel economy levels achieved by lightduty vehicles in on-road driving fall somewhat short of their levels measured under the laboratory test conditions used by EPA to establish compliance with the proposed CAFE and GHG standards. The modeling approach in this proposal follows the 2012-2016 final rule and the Interim Joint TAR. In calculating benefits of the program, the agencies estimate that actual on-road fuel economy attained by light-

147 The agencies do not believe that adding fuel-savi ng technology should preclude future improvements in performance, safety, or other attributes, though it is possibl e that the costs of these additions may be affected by the presence of fuel-saving technology.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 131 of 768 duty vehicles that operate on liquid fuels will be 20 percent lower than published fuel economy ratings for vehicles that operate on liquid fuels. For example, if the measured CAFE fuel economy value of a light truck is 20 mpg, the on-road fuel economy actually achieved by a typical driver of that vehicle is expected to be 16 mpg (20*.80). 148 Based on manufacturer confidential business information, as well as data derived from the 2006 EPA fuel economy label rule, the agencies use a 30 percent gap for consumption of wall electricity for electric vehicles and plug-in hybrid electric vehicles. 149

• Fuel prices and the value of saving fuel – Projected future fuel prices are a critical input into the preliminary economic analysis of alternative standards, because they determine the value of fuel savings both to new vehicle buyers and to society, and fuel savings account for the majority of the proposed rule’s estimated benefits. For this proposed rule, the agencies are using the most recent fuel price projections from the U.S. Energy Information Administrati on’s (EIA) Annual Energy Outlook (AEO) 2011 reference case forecast. The forecasts of fuel prices reported in EIA’s AEO 2011 extend through 2035. Fuel prices beyond the time frame of AEO’s forecast were estimated using an average growth rate for the years 2017-2035 to each year after 2035. This is the same methodology used by the agencies in the 2012-2016 rulemaking, in the heavy duty truck and engine rule (76 FR 57106), and in the Interim Joint TAR. For example, these forecasts of gasoline fuel prices in 2009$ include $3.25 per gallon in 2017, $3.39 in 2021 and $3.71 in 2035. Extrapolating as described above, retail gasoline prices reach $4.16 per gallon in 2050 (measured in constant 2009 dollars). As discussed in Ch apter 4 of the draft Joint TSD, while the agencies believe that EIA’s AEO reference case generally represents a reasonable forecast of future fuel prices for purposes of use in our analysis of the benefits of this rule, we recognize that there is a great deal of uncertainty in any such forecast that could affect our estimates. The agencies request comment on how best to account for uncertainty in future fuel prices.

• Consumer valuation of fuel economy and payback period —In estimating the value of fuel economy improvements to potential vehicle buyers that would result from alternative CAFE and GHG standards, the agencies assume that buyers value the resulting fuel savings over only part of the expected lifetimes of the vehicles they purchase. Specifically, we assume that buyers value fuel savings over the first five years of a new vehicle’s lifetime, and that buyers discount the value of these future fuel savings. The five-year figure represents the current average term of consumer loans to finance the purchase of new vehicles.

148 U.S. Environmental Protection Agency, Final Techni cal Support Document, Fuel Economy Labeling of Motor Vehicle Revisions to Improve Calculation of Fuel Economy Estimates, EPA420-R-06-017, December 2006.

149 See 71 FR at 77887, and U.S. Environmental Protect ion Agency, Final Technical Support Document, Fuel Economy Labeling of Motor Vehicle Revisions to Improve Calculation of Fuel Economy Estimates, EPA420-R-06- 017, December 2006 for general background on the anal ysis. See also EPA’s Response to Comments ( EPA-420-R11-005) to the 2011 labeling rule, page 189, first paragraph, specifically the discussion of the derived five cycle equation and the non-linear adjustment with increasing MPG.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 132 of 768 • Vehicle sales assumptions— The first step in estimating lifetime fuel consumption by vehicles produced during a model year is to calculate the number that are expected to be produced and sold. The agencies relied on the AEO 2011 Reference Case for forecasts of total vehicle sales, while th e baseline market forecast developed by the agencies (discussed in Section II.B and in Chapter 1 of the TSD) divided total projected sales into sales of cars and light trucks.

• Vehicle lifetimes and survival rates – As in the 2012-2016 final rule and Interim Joint TAR, we apply updated values of age-specific survival rates for cars and light trucks to adjusted forecasts of passenger car and light truck sales to determine the number of these vehicles expected to remain in use du ring each year of their lifetimes. These values remain unchanged from prior analyses.

• Vehicle miles traveled – We calculated the total number of miles that cars and light trucks produced in each model year will be driven during each year of their lifetimes using estimates of annual vehicle use by age tabulated from the Federal Highway Administration’s 2001 National Household Travel Survey (NHTS), 150 adjusted to account for the effects on vehicle use of subseq uent increases in fuel prices. In order to insure that the resulting mileage schedules imply reasonable estimates of future growth in total car and light truck use, we calculated the rate of future growth in annual mileage at each age that would be necessary for total car and light truck travel to increase at the rates forecast in the AEO 2011 Reference Case. The growth rate in average annual car and light truck use produced by this calculation is approximately 1 percent per year through 2030 and 0.5 percent thereafter. We applied these growth rates applied to the mileage figures derived from the 2001 NHTS to estimate annual mileage by vehicle age during each year of the expected lifetimes of MY 2017-2025 vehicles. A similar approach to estimating future vehicle use was used in the 2012- 2016 final rule and Interim Joint TAR, but th e future growth rates in average vehicle use have been revised for this proposal.

• Accounting for the rebound effect of higher fuel economy – The rebound effect refers to the increase in vehicle use that results if an increase in fuel efficiency lowers the cost of driving. For purposes of this NPRM , the agencies elected to continue to use a 10 percent rebound effect in their analyses of fuel savings and other benefits from higher standards, consistent with the 2012- 2016 light-duty vehicle rulemaking and the Interim Joint TAR. That is, we assume a 10 percent decrease in fuel cost per mile resulting from our proposed standards would result in a 1 percent increase in the annual number of miles driven at each age over a vehicle’s lifetime. In Chapter 4 of the joint TSD, we provide a detailed explanation of the basis for our rebound estimate, including a summary of new literature published since the 2012-2016 rulemaking that lends further support to the 10 percent rebound estimate. We also refer the reader to Chapters X and XII of NHTSA’s PRIA that accompanies this preamble for sensitivity and uncertainty analyses of alternative rebound assumptions.

150 For a description of the Survey, see http://www.b ts.gov/programs/national_household_travel_survey/ (last accessed Sept. 9, 2011).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 133 of 768 • Benefits from increased vehicle use – The increase in vehicle use from the rebound effect provides additional benefits to driv ers, who may make more frequent trips or travel farther to reach more desirable des tinations. This additional travel provides benefits to drivers and their passengers by improving their access to social and economic opportunities away from home. The analysis estimates the economic benefits from increased rebound-effect driving as the sum of the fuel costs they incur in that additional travel plus the consumer surplus drivers receive from the improved accessibility their travel provides. As in the 2012-2016 final rule we estimate the economic value of this consumer surplus using the conventional approximation,which is one half of the product of the decline in vehicle operating costs per vehiclemile and the resulting increase in the annual number of miles driven.

• Added costs from congestion, accidents, and noise – Although it provides benefits to drivers as described above, increased vehicle use associated with the rebound effect also contributes to increased traffic congestion, motor vehicle accidents, and highway noise. Depending on how the additional travel is distributed over the day and where it takes place, additional vehicle use can contribute to traffic congestion and delays by increasing traffic volumes on facilities that are already heavily traveled. These added delays impose higher costs on drivers and other vehicle occupants in the form of increased travel time and operating expenses. At the same time, this travel also increases costs associated with traffic acci dents, and increased traffic noise. The agencies rely on estimates of congestion, accident, and noise costs caused by automobiles and light trucks developed by the Federal Highway Administration to estimate these increased external costs caused by added driving. 151 This method is consistent with the 2012-2016 final rule.

• Petroleum consumption and import externalities – U.S. consumption of imported petroleum products also impose costs on the domestic economy that are not reflected in the market price for crude petroleum, or in the prices paid by consumers of petroleum products such as gasoline. These costs include (1) higher prices for petroleum products resulting from the effect of increased U.S. demand for imported oil on the world oil price (“monopsony costs”); (2) the expected costs associated with the risk of disruptions to the U.S. economy caused by sudden reductions in the supply of imported oil to the U.S.; and (3) expenses for maintaining a U.S. military presence to secure imported oil supplies from unst able regions, and for maintaining the strategic petroleum reserve (SPR) to cushion the U.S. economy against the effects of oil supply disruptions. 152 Although the reduction in the global price of petroleum and refined products due to decreased demand for fuel in the U.S. resulting from this rule represents a benefit to the U.S. economy, it simultaneously represents an economic

151 These estimates were developed by FHWA for use in its 1997 Federal Highway Cost Allocation Study ; http://www.fhwa.dot.gov/policy/hcas/final/i ndex.htm (last accessed Sept. 9, 2011).

152 See, e.g., Bohi, Douglas R. and W. David Montgomery (1 982). Oil Prices, Energy Security, and Import Policy Washington, DC: Resources for the Future, Johns Hopkins University Press; Bohi, D. R., and M. A. Toman (1993). "Energy and Security: Externalities and Policies," Ener gy Policy 21:1093-1109; and Toman, M. A. (1993). "The Economics of Energy Security: Theory, Evidence, Policy, " in A. V. Kneese and J. L. Sweeney, eds. (1993). Handbook of Natural Resource and Energy Economics, Vol. III. Amsterdam: North-Holland, pp. 1167-1218.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 134 of 768 loss to other countries that produce and sell oil or petroleum products to the U.S. Recognizing the redistributive nature of this “monopsony effect” when viewed from a global perspective (which is consistent with the agencies’ use of a global estimate for the social cost of carbon to value reductions in CO 2 emissions, the energy security benefits estimated to result from this program exclude the value of this monopsony effect. In contrast, the macroeconomic di sruption and adjustment costs that arise from sudden reductions in the supply of imported oil to the U.S. do not have offsetting impacts outside of the U.S., so the estimated reduction in their expected value stemming from reduced U.S. petroleum imports is included in the energy security benefits estimated for this program. U.S. military costs are excluded from the analysis because their attribution to par ticular missions or activities is difficult. Also, historical variation in U.S. military co sts have not been associated with changes in U.S. petroleum imports, although we recognize that more broadly, there may be significant (if unquantifiable) benefits in improving national security by reducing oil imports. Similarly, since the size or other factors affecting the cost of maintaining the SPR historically have not varied in response to changes in U.S. oil import levels, changes in the costs of the SPR are excluded from the estimates of the energy security benefits of the program. To summarize, the agencies have included only the macroeconomic disruption and adjustment costs portion of the energy security benefits to estimate the monetary value of the total energy securi ty benefits of this program. Based on a recent update of an earlier peer-reviewed Oak Ridge National Laboratory study that was used in support of the both the 2012-2016 light duty vehicle and the 2014-2018 medium- and heavy-duty vehicle rulemaking, we estimate that each gallon of fuel saved will reduce the expected macroeconomic disruption and adjustment costs of sudden reductions in the supply of imported oil to the U.S. economy by $0.185 (2009$) in 2025. Each gallon of fuel saved as a consequence of higher standards is anticipated to reduce total U.S. imports of crude petroleum or refined fuel by 0.95 gallons. 153 The energy security analysis conducted for this proposal also estimates that the world pri ce of oil will fall modestly in response to lower U.S. demand for refined fuel. 154,155 The energy security methodology used in this proposal is the same as that used by the agencies in both the 2012-2016 light duty vehicle and 2014-2018 medium- and heavy-duty vehicle rulemakings. In those rulemakings, the agencies addressed comments about the magnitude of their energy security estimates and methodological i ssues such as whether to include the monopsony benefits in energy security calculations.

• Air pollutant emissions –

153 Each gallon of fuel saved is assumed to reduce imports of refined fuel by 0.5 gallons, and the volume of fuel refined domestically by 0.5 gallons. Domestic fuel re fining is assumed to utilize 90 percent imported crude petroleum and 10 percent domestically-produced crude petrol eum as feedstocks. Together, these assumptions imply that each gallon of fuel saved will reduce imports of refined fuel and crude petr oleum by 0.50 gallons + 0.50 gallons*90 percent = 0.50 gallons + 0.45 gallons = 0.95 gallons.

154 Leiby, Paul. Oak Ridge National Laborat ory. “Approach to Estimating the Oil Import Security Premium for the MY 2017 -2025 Light Duty Vehicle Proposal” 2011.

155 Note that this change in world oil price is not reflected in the AEO projections described earlier in this section.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 135 of 768 o Impacts on criteria air pollutant emissions – Criteria air pollutants emitted by vehicles and during fuel production a nd distribution include carbon monoxide (CO), hydrocarbon compou nds (usually referred to as “volatile organic compounds,” or VOC), nitrogen oxides (NO X ), fine particulate matter (PM 2.5 ), and sulfur oxides (SO X ). Although reductions in domestic fuel refining and distribution that result from lower fuel cons umption will reduce U.S. emissions of these pollutants, additional vehicle use associated with the rebound effect will increase emissions. Thus the net effect of stricter standards on emissions of each criteria pollutant depends on the relative magnitudes of reduced emissions from fuel refining and distribution, and increases in emissions resulting from added vehicle use. The agencies’ analysis assumes that the per-mile emission rates for cars and light trucks produced during the model years affected by the proposed rule will remain constant at the levels resulting from EPA’s Tier 2 light duty vehicle emissions standards. The agencies’ approach to estimating criteria air pollutant emissions is consistent with the method used in the 2012-2016 final rule (where the agencies received no signif icant adverse comments), although the agencies employ a more recent version of the EPA’s MOVES (Motor Vehicle Emissions Simulator) model.

. o Economic value of reductions in criteria pollutant emissions - For the purpose of the joint technical analysis, EPA and NHTSA estimate the economic value of the human health benefits associated with reducing population exposure to PM 2.5 using a “benefit-per-ton” method. These PM 2.5 -related benefit-per-ton estimates provide the total monetized benefits to human health (the sum of reductions in premature mortality and premature morbidity) that result from eliminating one ton of directly emitted PM 2.5 , or one ton of other pollutants that contribute to atmospheric levels of PM 2.5 (such as NO X , SO X , and VOCs), from a specified source. These unit values remain unchanged from the 2012-2016 final rule, and the agencies received no significant adverse comment on the analysis. Note that the agencies’ analysis includes no estimates of the direct health or other benefits associated with reductions in emissions of criteria pollutants other than PM 2.5

.

o Impacts on greenhouse gas (GHG) emissions - NHTSA estimates reductions in emissions of carbon dioxide (CO 2 ) from passenger car and light truck use by multiplying the estimated reduction in consumption of fuel (gasoline and diesel) by the quantity or mass of CO 2 emissions released per gallon of fuel consumed. EPA directly calculates reductions in total CO 2 emissions from the projected reductions in CO 2 emissions by each vehicle subject to the proposed rule. 156 Both agencies also calculate the impact on CO 2 emissions that occur during fuel production and distribution resulting from lo wer fuel consumption, as well as the emission impacts due to changes in electricity production. Although CO 2 emissions account for nearly 95 percent of total GHG emissions that result from fuel combustion during vehicle use, emissions of other GHGs are potentially significant as well because of their hi gher “potency” as GHGs than that of CO 2

156 The weighted average CO 2 content of certification gasoline is estimate d to be 8,887 grams per gallon, while that of diesel fuel is estimated to be a pproximately 10,200 grams per gallon.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 136 of 768 itself. EPA and NHTSA therefore also estimate the change in upstream and downstream emissions of non-CO 2 GHGs that occur during the aforementioned processes due to their respective standards. 157 The agencies approach to estimating GHG emissions is consistent with the method used in the 2012-2016 final rule and the Interim Joint TAR.

o Economic value of reductions in CO 2 emissions – EPA and NHTSA assigned a dollar value to reductions in CO 2 emissions using recent estimates of the “social cost of carbon” (SCC) developed by a federal interagency group that included the two agencies. As that group’s report obse rved, “The SCC is an estimate of the monetized damages associated with an incremental increase in carbon emissions in a given year. It is intended to include (but is not limited to) changes in net agricultural productivity, human health, property damages from increased flood risk, and the value of ecosystem services due to climate change.” 158 Published estimates of the SCC vary widely as a result of uncertainties about future economic growth, climate sensitivity to GHG emissions, pro cedures used to model the economic impacts of climate change, and the choice of discount

rates. 159 The SCC estimates used in this analysis were developed through an interagency process that included EPA, DOT/NHTSA, and other executive branch entities, and concluded in February 2010. We first used these SCC estimates in the benefits analysis for the 2012-2016 light-duty vehicle rulemaking. We have continued to use these estimates in other rulemaking analyses, including theGreenhouse Gas Emission Standards and Fuel Efficiency Standards for Mediumand Heavy-Duty Engines and Vehicles (76 FR 57106, p. 57332)

. The SCC Technical Support Document (SCC TSD) provides a complete discussion of the methods used to develop these SCC estimates.

• The value of changes in driving range – By reducing the frequency with which drivers typically refuel their vehicles, and by extending the upper limit of the range they can travel before requiring refueling, improving fuel economy and reducing GHG emissions provides additional benefits to their owners. The primary benefits from the reduction in the number of required refueling cycles are the value of time saved to drivers and other adult vehicle occupants, as well as the savings to owners in terms of the cost of the fuel that would have otherwise been consumed in transit during those (now no longer required) refueling trips. Using recent data on vehicle owners’ refueling patterns gathered from a survey conducted by the National

157 There is, however, an exception. NHTSA does not and cannot claim benefit from reductions in downstream emissions of HFCs because they do not relate to fuel economy, while EPA does because all GHGs are relevant for purposes of EPA’s Clean Air Act standards.

158 SCC TSD, see page 2. Docket ID EPA-HQ-OAR-2009-0472-114577, Technical Support Document: Social Cost of Carbon for Regulatory Impact Analysis Under Executi ve Order 12866, Interagency Working Group on Social Cost of Carbon , with participation by Council of Economic Advisers, Council on Environmental Quality, Department of Agriculture, Department of Commerce, Department of Energy, Department of Transportation, Environmental Protection Agency, National Economic Council, Office of Energy and Climate Change, Office of Management and Budget, Office of Science and Technology Policy, and Department of Treasury (February 2010). Also available at http://epa.gov/otaq/climate/regulations.htm

159 SCC TSD, see pages 6-7.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 137 of 768 Automotive Sampling System (NASS), NHTSA was able to better estimate parameters associated with refueling trips. NASS data provided NHTSA with the ability to estimate the average time required for a refueling trip, the average time and distance drivers typically travel out of thei r way to reach fueling stations, the average number of adult vehicle occupants, the average quantity of fuel purchased, and the distribution of reasons given by drivers for refueling. From these estimates, NHTSA constructed an updated set of economic assumptions to update those used in the 2012- 2016 FRM in calculating refueling-related benefits. The 2012-2016 FRM discusses NHTSA’s intent to utilize the NASS data on refueling trip characteristics in future rulemakings. While the NASS data improve the precision of the inputs used in the analysis of the benefits resulting from fe wer refueling cycles, the framework of the analysis remains essentially the same as in the 2012-2016 final rule. Note that this topic and associated benefits were not covered in the Interim Joint TAR. Detailed discussion and examples of the agencies’ approach are provided in Chapter VIII of NHTSA’s PRIA and Chapter 8 of EPA’s DRIA.

• Discounting future benefits and costs – Discounting future fuel savings and other benefits is intended to account for the redu ction in their value to society when they are deferred until some future date, rather than received immediately. 160 The discount rate expresses the percent decline in the value of these future fuel-savings and other benefits—as viewed from today’s perspective—for each year they are deferred into the future. In evaluating the non-climate related benefits of the final standards, the agencies have employed discount rates of both 3 percent and 7 percent, consistent with the 2012-2016 final rule and OMB Circular A-4 guidance.

For the reader’s reference, Table 0-8 and Table 0-9 below summarize the values used to calculate the impacts of each proposed standard. The values presented in this table are summaries of the inputs used for the models; spec ific values used in the agencies’ respective analyses may be aggregated, expanded, or have other relevant adjustments. See Joint TSD 4 and each agency’s respective RIA for details. The agencies seek comment on the economic assumptions presented in the table.

In addition, the agencies analyzed the sensitiv ity of their estimates of the benefits and costs associated with this proposed rule to va riation in the values of many of these economic assumptions and other inputs. The values used in these sensitivity analyses and their results are presented their agencies’ respective RIAs. A wide range of estimates is available for many of the primary inputs that are used in the agencies’ CAFE and GHG emissions models. The agencies recognize that each of these values has some degree of uncertainty, which the agencies further discuss in the draft Joint TSD. The agenci es have tested the sensitivity of their estimates of costs and benefits to a range of assumptions about each of these inputs, and present these sensitivity analyses in their respective RIAs. For example, NHTSA conducted separate sensitivity analyses for, among other things, discount rates, fuel prices, the social cost of carbon,

160 Because all costs associated with improving vehicles’ fuel economy and reducing CO2 emissions are assumed to be incurred at the time they are produ ced, these costs are already expressed in their present values as of each model year affected by the proposed rule, and require discounting only for the purpose of expressing them as present values as of a common year.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 138 of 768 the rebound effect, consumers’ valuation of fuel economy benefits, battery costs, mass reduction costs, the value of a statistical life, and the indir ect cost markup factor. This list is similar in scope to the list that was examined in the MY 2012-2016 final rule, but includes battery costs and mass reduction costs, while dropping military security and monopsony costs. NHTSA’s sensitivity analyses are contained in Chapte r X of NHTSA’s PRIA. In addition, NHTSA performs a probabilistic uncertainty analysis examining simultaneous variation in the major model inputs including technology costs, technolo gy benefits, fuel prices, the rebound effect, and military security costs. This information is provided in Chapter XII of NHTSA’s PRIA. These uncertainty parameters are consistent with those used in the MY 2012-2016 final rule. The agencies will consider conducting additional sensitivity and uncertainty analyses for the final rule as appropriate.

Table 0-8 Economic Values for Benefits Computations (2009$)

Fuel Economy Rebound Effect 10%"Gap" between test and on-road MPG for liquidfueled vehicles 20% “Gap” between test and on-road wall electricity consumption for electric and plug-in hybrid electric vehicles 30%

Value of refueling time per ($ per vehicle-hour) $21.27 Cars

$21.62 Truck Average tank volume refille d during refueling stop 65% Annual growth in average vehicle use 1% through 2030, 0.5% thereafter Fuel Prices (2017-50 average, $/gallon) Retail gasoline price $3.71 Pre-tax gasoline price $3.35 Economic Benefits from Reducing Oil Imports ($/gallon) "Monopsony" Component $ 0.00 Price Shock Component $ 0.185 in 2025 Military Security Component $ 0.00 Total Economic Costs ($/gallon) $ 0.185 in 2025 Emission Damage Costs (2020, $/short ton) Carbon monoxide $ 0 Volatile organic compounds (VOC) $ 1,300 Nitrogen oxides (NO X ) – vehicle use $ 5,500 Nitrogen oxides (NO X ) – fuel production and distribution $ 5,300

Particulate matter (PM 2.5 ) – vehicle use $ 300,000Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 139 of 768 Particulate matter (PM 2.5 ) – fuel production and distribution $ 250,000

Sulfur dioxide (SO 2 ) $ 32,000

Annual CO 2 Damage Cost (per metric ton) Variable, depending on discount rate and year (see Table 0-9 for 2017 estimate)
External Costs from Additional Automobile Use ($/vehicle-mile) Congestion $ 0.056 Accidents $ 0.024 Noise $ 0.001 Total External Costs $ 0.080 External Costs from Additional Light Truck Use ($/vehicle-mile) Congestion $0.049 Accidents $0.027 Noise $0.001 Total External Costs $0.077 Discount Rates Applied to Future Benefits 3%, 7%

Table 0-9 Social Cost of CO 2 ($/metric ton), 2017 (2009$)

Discount Rate 5% 3% 2.5% 3%
Source of Estimate Mean of Estimated Values 95 t h percentile estimate 2017 Estimate $6 $26 $41 $78

F. Air Conditioning Efficiency CO 2 Credits and Fuel Consumption Improvement Values, Off-cycle Reductions, and Full-size Pickup Trucks

For MYs 2012-2016, EPA provided an option for manufacturers to generate credits for complying with GHG standards by incorporating efficiency improving vehicle technologies that
would reduce CO 2 and fuel consumption from air conditioning (A/C) operation or from other vehicle operation that is not captured by the Federal Test Procedure (FTP) and Highway Fuel Economy Test (HFET), also collectively known as the “two-cycle” test procedure. EPA referred to these credits as “off-cycle credits.”

For this proposal, EPA, in coordination with NHTSA, is proposing under their EPCA
authorities to allow manufacturers to generate fuel consumption improvement values for purposes of CAFE compliance based on the use of A/C efficiency and off-cycle technologies. This proposed expansion is a change from the 2012-16 final rule where EPA only provided theSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 140 of 768 A/C efficiency and off-cycle credits for the GHG program. EPA is not proposing to allow these increases for compliance with the CAFE pr ogram for MYs 2012-2016, nor to allow any compliance with the CAFE program as a result of reductions in direct A/C emissions resulting from leakage of HFCs from air conditioning systems, which remains a flexibility unique to the GHG program.

The agencies believe that because of the significant amount of credits and fuel consumption improvement values offered under the A/C program (up to 5.0 g/mi for cars and 7.2 g/mi for trucks which is equivalent to a fuel consumption improvement value of 0.000563 gal/mi for cars and 0.000586 gal/mi for trucks) that manufacturers will maximize the benefits these credits and fuel consumption improvement values afford. Consistent with the 2012-2016 final rule, EPA will continue to adjust the st ringency of the two-cycle tailpipe CO 2 standards in order to account for this projected widespread penetration of A/C credits (as described more fully in Section III.C), and NHTSA has al so accounted for expected A/C efficiency improvements in determining the maximum feasible CAFE standards. The agencies discuss these proposed CO 2 credits/fuel consumption improvement values be low and in more detail in the Joint TSD (Chapter 5). EPA discusses add itional proposed GHG A/C leakage credits that are unrelated to

CO 2 and fuel consumption (though they are part of EPA’s CO 2 equivalent calculation) in Section
III.C below.

EPA, in coordination with NHTSA, is also proposing to add for MYs 2017-2025 a new incentive for Advanced Technology for Full Sized Pickup Trucks. Under its EPCA authority for CAFE and under its CAA authority for GHGs, EPA is proposing GHG credits and fuel economy improvement values for manufacturers that hybridize a significant quantity of their full size pickup trucks, or that use other technologies that significantly reduce CO 2 emissions and fuelconsumption. Further discussions of the A/C, off-cycle, and the advanced technology for pickup truck incentive programs are provided below.

1. Proposed Air Conditioning CO 2 Credits and Fuel Consumption Improvement Values

The credits/fuel consumption improvement values for higher-efficiency air conditioning technologies are very similar to those EPA included in the 2012-2016 GHG final rule. The proposed credits/fuel consumption improvement values represent an improved understanding of the relationships between A/C technologies and CO 2 emissions and fuel consumption. Much of this understanding results from a new vehicle simulation tool that EPA has developed and the agencies are using for this proposal. EPA designed this model to simulate in an integrated way the dynamic behavior of the several key system s that affect vehicle efficiency: the engine, electrical, transmission, and vehi cle systems. The simulation model is supported by data from a wide range of sources; the Draft Regulatory Impact Analysis discusses its development in more
detail.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 141 of 768 The agencies have identified several technologies that are key to the amount of fuel a
vehicle consumes and thus the amount of CO 2 it emits. Most of thes e technologies already exist on current vehicles, but manufacturers can improve the energy efficiency of the technology designs and operation. For example, most of the additional air conditioning related load on an engine is due to the compressor which pumps the refrigerant around the system loop. The less the compressor operates, the less load the compressor places on the engine resulting in less fuel consumption and CO 2 emissions. Thus, optimizing compressor operation with cabin demand using more sophisticated sensors, controls and control strategies, is one path to improving the overall efficiency of the A/C system. Additional components or control strategies are available to manufacturers to reduce the air conditioning load on the engine which are discussed in more detail in Chapter 5 of the joint TSD. Overall, the agencies have concluded that these improved technologies could together reduce A/C-related CO 2 and fuel consumption of today’s typical air conditioning systems by 42%. The agencies propose to use this level of improvement to represent the maximum efficiency credit available to a manufacturer.

Demonstrating the degree of efficiency improvement that a manufacturer’s air conditioning systems achieve – thus quantifying the appropriate amount of GHG credit and CAFE fuel consumption improvement value the manufacturer is eligible for -- would ideally involve a performance test. That is, a test that would directly measure CO 2 (and thus allow calculation of fuel consumption) before and after the incorporation of the improved technologies. Progress toward such a test continues. As me ntioned in the introduction to this section, the primary vehicle emissions and fuel consumption te st, the Federal Test Procedure (FTP) or “twocycle” testing, does not require or simulate air conditioning usage through the test cycle. The SC03 test is designed to identify any effect the air conditioning system has on other emissions when it is operating under extreme conditions, but is not designed to measure the small
differences in CO 2 due to different A/C technologies. In order to correct the shortcomings of the available tests, EPA has developed a four-par t performance test, called the AC17. The testincludes the SC03 driving cycle, the fuel economy highway cycle, in addition to a preconditioning cycle, and a solar soak period. EPA is proposing that manufacturers may use this test to demonstrate that A/C technologies re sult in efficiency improvements. Since the appropriateness of the test to measure the amount of reduction achieved is still being evaluated, EPA proposes that manufacturers continue to use a technology lookup table (“menu”) to determine credits and fuel consumption improvement values for the GHG and CAFE programs. This was also the approach that EPA used for efficiency credits in the MY2012-2016 GHG rule. The design approach would assign CO2 credit an d fuel consumption improvement value to each efficiency-improving air conditioning technology that the manufacturer incorporates in a vehicle model. The sum of these values for all technologies would be the amount of CO 2 credit generated and fuel consumption reduction achieved by that vehicle, up to a maximum of 5.0 g/mi for car and 7.2 g/mi for trucks. As stated above, this is equivalent to a fuel consumption value of 0.000563 gallons /mi for cars and 0.000586 gallons /mi for trucks. EPA will consult withSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 142 of 768 NHTSA on the amount of fuel consumption improvement value manufacturers may factor into their CAFE calculations if there are adjustments that may be required in the future. Table 0-10 presents the proposed CO 2 credit and CAFE fuel consumption improvement values for each of the efficiency-reducing air conditioning technologies considered in this rule. More detail is provided on the calculation of i ndirect A/C CAFE fuel consum ption improvement values in chapter 5 of the TSD. EPA is proposing very spec ific definitions of each of the technologies in the table below which are discussed in Chapter 5 of the draft joint TSD to ensure that the air conditioner technology used by manufacturers seeking these credits corresponds with the technology used to derive the credit/fuel consumption improvement values.

Table 0-10 A/C Efficiency Credits and Fuel Consumption Improvement Values

Technology Description Estimated reduction in A/C CO 2 Emissions

and Fuel Consumption Car A/C Efficiency

Credit (g/mi CO 2 ) Truck A/C Efficiency

Credit (g/mi CO 2 ) Car A/C Efficiency

Fuel Consumption Improvement ( g allon / mi) Truck A/C Efficiency

Fuel Consumption Improvement ( g allon / mi)Reduced reheat, with externallycontrolled, variable-displacement

compressor 30% 1.5 2.2 0.000169 0.000248

Reduced reheat, with externallycontrolled, fixed-displacement or pneumatic variable displacement

compressor 20% 1.0 1.4 0.000113 0.000158

Default to recirculated air with closedloop control of the air supply (sensor feedback to control interior air quality) whenever the outside ambient temperature is 75 °F or higher (although deviations from this temperature are allowed based on additional analysis) 30% 1.5 2.2 0.000169 0.000248

Default to recirculated air with openloop control of the air supply (no sensor feedback) whenever the outside ambient temperature is 75 °F or higher (although deviations from this temperature are allowed if accompanied by an engineering analysis) 20% 1.0 1.4 0.000113 0.000158

Blower motor control which limit wasted electrical energy (e.g. pulsewidth modulated power controller) 15% 0.8 1.1 0.000090 0.000124

Internal heat exchanger (or suction line heat exchanger) 20% 1.0 1.4 0.000113 0.000158

Improved evaporators and condensers (with engineering analysis on each component indicating a COP improvement greater than 10%, when compared to previous design) 20% 1.0 1.4 0.000113 0.000158

Oil Separator (internal or external to compressor) 10% 0.8 0.7 0.000090 0.000079Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 143 of 768 At the time of the final rule for the 2012-2016 GHG program, EPA concluded that a practical, performance-based test procedure capable of quantifying efficiency credits was not yet available. However, EPA introduced a specialized new procedure that it believed would be appropriate for the more limited purpose of demonstrating that the design improvements a manufacturer was earning credits for produced actual efficiency improvements. EPA’s test is a fairly simple test, performed while the vehicle is at idle. Beginning with the 2014 model year, the A/C Idle Test was to be used to qualify a manufacturer to be able to use the “menu” approach to quantify credits. That is, a manufacturer would need to achieve a certain CO 2 level in order to use the “menu” and generate efficiency credits.

Since that final rule was published, several manufacturers have provided data that raises questions about the ability of the Idle Test to fulfill its intended purpose. Especially for small, lower-powered vehicles, the data also shows that it is difficult to achieve reasonable test-to-test repeatability. The manufacturers have also info rmed EPA (in meetings subsequent to the 2012- 2016 final rule) that the Idle Test does not accurately capture the improvements from many of the technologies listed in the menu. EPA has been aware of all of these issues, and proposing to modify the Idle Test such that the threshold is now a function of engine displacement in contrast to the flat threshold from the previous rule. EPA continues to consider this Idle Test to be a
reasonable measure of some A/C CO 2 emissions as there is significant real-world driving activity at idle, and the Idle Test significantly exerci ses a number of the A/C technologies from the menu

As mentioned above, EPA, working with manufacturers and CARB, has made significant progress in developing a more robust test that may be capable of measuring differences in A/C efficiency. While EPA believes that more testin g and development will be necessary before the new test could be used directly to quantify ef ficiency credits and fuel consumption improvement values, EPA is proposing the test be used to demonstrate that A/C technologies result in reductions in GHG emissions and fuel consumption. EPA is proposing the AC17 test as an alternative to the Idle Test as a prerequisite for generating Efficiency Credits and fuel consumption improvement values. To demonstrate that a vehicle’s A/C system is delivering the efficiency benefits of the new technologies, manufacturers would run the AC17 test procedure on a vehicle that incorporates the new technologies, with the A/C system off and then on, and then compare that result to the result from a previous model year or baseline vehicle with similar vehicle characteristics, except that the comparison vehicle would not have the new technologies. If the test result with the new technology demons trated an emission reduction that is greater than or equal to the menu-based credit potential of those technologies, the manufacturer would generate the appropriate credit based on the menu. However, if the test result did not demonstrate the full menu-based potential of the t echnology, partial credit could still be earned, in proportion to how far away the result was from the mean value.

EPA discusses the new test in more detail in Section III.C below and in Chapter 5 of the joint TSD. Due to the length of time to conduct the test procedure, EPA is also proposing thatSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 144 of 768 required testing be limited to a subset of vehicles. The agencies request comment on this approach to establishing A/C efficiency credits and fuel consumption improvement values and
the use of the new A/C test.

2. Off-Cycle CO 2 Credits

For MYs 2012-2016, EPA provided an option for manufacturers to generate adjustments (credits) for employing new and innovative technologies that achieve CO 2 reductions which are not reflected on current 2-cycle test procedures. For this proposal, EPA, in coordination with NHTSA, is proposing to apply the off-cycle credits and equivalent fuel consumption improvement values to both the CAFE and GHG pr ograms. This proposed expansion is a change from the 2012-16 final rule where only EPA provided the off-cycle credits for the GHG program. For MY 2017 and later, EPA is proposing that manufacturers may continue to use off-cycle credits for GHG compliance and begin to use fuel consumption improvement values for CAFE compliance. In addition, EPA is proposing a set of defined (e.g. default) values for identified off-cycle technologies that would apply unless th e manufacturer demonstrates to EPA that a different value for its technology is appropriate.

Starting with MY2008, EPA started employing a “five-cycle” test methodology to measure fuel economy for the fuel economy label. However, for GHG and CAFE compliance, EPA continues to use the established “two-cycle” (city and highway test cycles, also known as the FTP and HFET) test methodology. As learned through development of the “five-cycle” methodology and researching this proposal, EPA and NHTSA recognize that there are technologies that provide real-world GHG emis sions and fuel consumption improvements, but those improvements are not fully reflected on the “two-cycle” test.

During meetings with vehicle manufacturers, EPA received comments that the approval process for generating off-cycle credits was comp licated and did not provide sufficient certainty on the amount of credits that might be approved. Commenters also maintained that it is impractical to measure small incremental improvements on top of a large tailpipe measurement, similar to comments received related to quantifying air conditioner improvements. These same manufacturers believed that such a process could st ifle innovation and fuel efficient technologies from penetrating into the vehicle fleet.

In response to these concerns, EPA is proposing a menu with a number of technologies that the agency believes will show real-world CO 2 and fuel consumption benefits which can be reasonably quantified by the agencies at this time. This list of pre-approved technologies includes a quantified default value that would ap ply unless the manufacturer demonstrates to EPA that a different value for a technology is appropriate. This list is similar to the menu driven approach described in the previous section on A/C efficiency credits. The estimates of these credits were largely determined from research, analysis and simulations, rather from full vehicle testing, which would have been cost and time prohibitive. These predefined estimates areSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 145 of 768 somewhat conservative to avoid the potential for windfall. If manufactures believe their specific off-cycle technology achieves larger improvement, they may apply for greater credits and fuel consumption improvement values with supporting data. For technologies not listed, EPA is proposing a case-by-case approach for approval of off-cycle credits and fuel consumption improvement values, similar to the approach in the 2012-2016 rule but with important modifications to streamline the approval process. EPA will also consult with NHTSA during thereview process. See section III.C below; technologies for which EPA is proposing default offcycle credit values and fuel consumption improvement values are shown in Table II -2 below. Fuel consumption improvement values under th e CAFE program based on off-cycle technology would be equivalent to the off-cycle credit a llowed by EPA under the GHG program, and these amounts would be determined using the same procedures and test methods as are proposed for use in EPA’s GHG program.

EPA and NHTSA are not proposing to adjust the stringency of the standards based on the availability of off-cycle credits and fuel consumption improvement values. There are a number of reasons for this. First, the agencies have limited technical information on the cost, development time necessary, and manufacturability of many of these technologies. The analysis presented below (and in greater detail in Chapter 5 of the joint TSD) is limited to quantifying the effectiveness of the technology (for the purposes of quantifying credits and fuel consumption improvement values). It is based on a combination of data and engineering analysis for each technology. Second, for most of these technologies the agencies have no data on what the rates of penetration of these technologies would be during the rule timeframe. Thus, with the exception of active grill shutters and stop start technology, the agencies do not have adequate information available to consider the technolog ies on the list when determining the appropriate GHG emissions or CAFE standards. The agen cies expect to continue to improve their understanding of these technologies over time. If further information is obtained during the comment period that supports consideration of th ese technologies in setting the standards, EPA and NHTSA will reevaluate their positions. Ho wever, given the current lack of detailed information about these technologies, the agencies do not expect that it will be able to do more for the final rule than estimate some general amount of reasonable projected cost savings from generation of off-cycle credits and fuel consumpt ion improvement values. Therefore, effectively the off-cycle credits and fuel consumption impr ovement values allow manufacturers additional flexibility in selecting technologies that may be used to comply with GHG emission and CAFE
standards.

Two technologies on the list - active grill shutters and stop start – are in a different position than the other technologies on the list. Both of these technologies are included in the agencies’ modeling analysis of technologies proj ected to be available for use in achieving the reductions needed for the standards. We have information on their effectiveness, cost, and availability for purposes of considering them along with the various other technologies we
consider in determin ing the appropriate CO 2 emissions standard. These technologies are amongSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 146 of 768 those listed in Chapter 3 of the joint TSD and have measureable benefit on the 2-cycle test. However, in the context of off-cycle credits and fuel consumption improvement values, stop start is any technology which enables a vehicle to automatically turn off the engine when the vehicle comes to a rest and restart the engine when the driver applies pressure to the accelerator or
releases the brake. This includes HEVs and PH EVs (but not EVs). In addition, active grill shutters is just one of variou s technologies that can be used as part of aerodynamic design improvements (as part of the “aero2” technology). The modeling and other analysis developed for determining the appropriate emissions standard includes these technologies, using the effectiveness values on the 2-cycle test. This is consistent with our consideration of all of the other technologies included in these analyses. Including them on the list for off-cycle credit and fuel consumption improvement value generation, for purposes of compliance with the standards, would recognize that these technologies have a higher degree of effectiveness than reflected in their 2-cycle effectiveness. As discussed in S ections III.C and Chapter 5 of the joint TSD, the agencies have taken into account the generation of off-cycle credits and fuel consumption improvement values by these two technologies in determining the appropriateness of the proposed standards, considering the amount of credit and fuel consumption improvement value, the projected degree of penetration of these t echnologies, and other factors. The proposed standards are appropriate recognizing that thes e technologies would also generate off-cycle credits and fuel consumption improvement values. Section III.D has a more detailed discussion on the feasibility of the standards within the cont ext of the flexibilities (such as off-cycle credits and fuel consumption improvement values) proposed in this rule.

For these technologies that provide a benefit on five-cycle testing, but show less benefit on two cycle testing, in order to quantify the emissions impacts of these technologies, EPA will simply subtract the two-cycle benefit from the fi ve-cycle benefit for the purposes of assigning credit and fuel consumption improvement values fo r this pre-approved list. Other technologies, such as more efficient lighting show no benefit over any test cycle. In these cases, EPA will estimate the average amount of usage using MOVES 161 data if possible and use this to calculate a duty-cycle-weighted benefit (or credit and fuel consumption improvement value). In the 2012- 2016 rule, EPA stated a technology must have “real world GHG reductions not significantly captured on the current 2-cycle tests...” For this proposal, EPA is proposing to modify this requirement to allow technologies as long as the incremental benefit in the real-world is significantly better than on the 2-cycle test. There are environmental benefits to encouraging these kinds of technologies that might not othe rwise be employed, beyond the level that the 2- cycle standards already do, thus we are now allo wing credits and fuel consumption improvement values to be generated where the technology achie ves an incremental benefit that is significantly better than on the 2-cycle test, as is the case for the technologies on the list.

161 MOVES is EPA’s MOtor Vehicle Emissions Simulator. Th is model contains (in its database) a wide variety of fleet and activity data as well as na tional ambient temperature conditions.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 147 of 768 EPA and NHTSA evaluated many more technologies for off-cycle credits and fuel consumption improvement values and decided that the following technologies should be eligible for off-cycle credits and fuel consumption improvement values. These eleven technologies eligible for credits and fuel consumption improvement values are shown in Table 0-11 below.

Table 0-11 Off-cycle Technologies and Proposed Credits and Fuel Consumption Improvement Values for Cars and Light Trucks

Technology Cars Light Trucks g/mi gallons/mi g/mi gallons/mi High Efficiency Exterior Lighting 1.1 0.000124 1.1 0.000124 Engine Heat Recovery 0.7 0.000778 0.7 0.000778
Solar Roof Panels 3.0 0.000338 3.0 0.000338
Active Grill Shutters and Active Aerodynamics 0.6 0.0000675 1.0 0.000113

Engine Start-Stop 2.9 0.000326 4.5 0.000506
Electric Heater Circulation Pump 1.0 0.000123 1.5 0.000169 Active Transmission Warm-Up 1.8 0.000203 1.8 0.000203 Active Engine Warm-Up 1.8 0.000203 1.8 0.000203

Solar Control Up to 3.0 Up to 0.000338 Up to 4.3 Up to 0.000484

Table 0-11 shows the proposed list of off-cy cle technologies and credits and fuel consumption improvement values for cars and trucks. The credits and fuel consumption improvement values for engine heat recovery and solar roof panels are scalable, depending on the amount of energy these systems can generate for the vehicle. The Solar/Thermal control technologies are varied and are limited to 3 and 4.3 g/mi (car and truck respectively) total.

To ensure that the off cycle technology used by manufacturers seeking these credits and fuel consumption improvement values corresponds with the technology used to derive the credit and fuel consumption improvement values, EPA is proposing very specific definitions of each of the technologies in the table of the list of technol ogies in Chapter 5 of the draft joint TSD. The agencies are requesting comment on all aspects of the off-cycle credit and fuel consumption improvement value program, and would welcome any data to support an adjustment to this table, whether it is to adjust the values or to add or remove technologies.

Vehicle Simulation Tool

Chapter 2 of the RIA provides a detailed desc ription of the vehicle simulation tool that EPA has been developing. This tool is capable of simulating a wide range of conventional and advanced engines, transmissions, and vehicle technologies over various driving cycles. It evaluates technology package effectiveness while taking into account synergy (and dis-synergy)Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 148 of 768 effects among vehicle components and estimates GHG emissions for various combinations of technologies. For the 2017 to 2025 GHG proposal, this simulation tool was used to assist estimating the amount of GHG credits for improved A/C systems and off-cycle technologies.EPA seeks public comments on this approach of using the tool for directly generating and finetuning some of the credits in order to capture the amount of GHG reductions provided by primarily off-cycle technologies.

There are a number of technologies that c ould bring additional GHG reductions over the 5-cycle drive test (or in the real world) compar ed to the combined FTP/Highway (or two) cycle test. These are called off-cycle technologies and are described in chapter 5 of the Joint TSD in detail. Among them are technologies related to reducing vehicle’s electrical loads, such as High Efficiency Exterior Lights, Engine Heat Recovery, and Solar Roof Panels. In an effort to streamline the process for approving off-cycle cr edits, we have set a relatively conservative estimate of the credit based on our efficacy analysis. EPA seeks comment on utilizing the model in order to quantify the credits more accurately, if actual data of electrical load reduction and/or on-board electricity generation by one or more of these technologies is available through data submission from manufacturers. Similarly, there are technologies that would provide additional GHG reduction benefits in the 5-cycle test by actively reducing the vehicle’s aerodynamic drag forces. These are referred to as active aerodynamic technologies, which include but are not limited to Active Grill Shutters and Active Susp ension Lowering. Like the electrical load reduction technologies, the vehicle simulation tool can be used to more accurately estimate the additional GHG reductions (therefore the credits) provided by these active aerodynamic technologies over the 5-cycle drive test. EPA seeks comment on using the simulation tool in order to quantify these credits. In order to do this properly, manufacturers would be expected to submit two sets of coast-down coefficients (with and without the active aerodynamic technologies). Or, they could submit two sets of aerodynamic drag coefficient (with and without the active aerodynamic technologies) as a function of vehicle speed.

There are other technologies that would resu lt in additional GHG reduction benefits that cannot be fully captured on the combined FTP/High way cycle test. These technologies typically reduce engine loads by utilizing advanced engine controls, and they range from enabling the vehicle to turn off the engine at idle, to reducing cabin temperature and thus A/C compressor loading when the vehicle is restarted. Exampl es include Engine Start-Stop, Electric Heater Circulation Pump, Active Engine/Transmission Warm-Up, and Solar Control. For these types of technologies, the overall GHG re duction largely depends on the control and calibration strategies of individual manufacturers and vehicle types. Also, the current vehicle simulation tool does not have the capability to properly simulate the vehicle behaviors that depend on thermal conditions of the vehicle and its surroundings, such as Active Engine/Transmission Warm-Up and Solar Control. Therefore, the vehicle simulation may not provide full benefits of the technologies on the GHG reductions. For this reason, the agency is not proposing to use the simulation tool toSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 149 of 768 generate the GHG credits for these technologies at this time, though future versions of the model may be more capable of quantifying the efficacy of these off-cycle technologies as well.

3. Advanced Technology Incentives for Full Sized Pickup Trucks

The agencies recognize that the standards under consideration for MY 2017-2025 will be most challenging to large trucks, including full size pickup trucks that are often used for commercial purposes and have generally higher payload and towing capabilities, and cargo volumes than other light-duty vehicles . In Section II.C and Chapter 2 of the joint TSD, EPA and NHTSA describe the proposal to adjust the slope of the truck curve compared to the 2012-2016 rule. In Sections III.B and IV.x, EPA and NHTSA describe the progression of the truck standards. In this section, the agencies describe a credit and fuel consumption improvement value for full size pickup trucks to incentivize advanced technologies on this class of vehicles.

The agencies’ goal is to incentivize the penetration into the marketplace of “game changing” technologies for these pickups, including th eir hybridization. For that reason, EPA ,in coordination with NHTSA, is proposing credits and fuel consumption improvement values for manufacturers that hybridize a significant quantity of their full size pickup trucks, or use other technologies that significantly reduce CO 2 emissions and fuel consumption. This proposed credit fuel consumption improvement value would be available on a per-vehicle basis for mild and strong HEVs, as well as other technologies th at significantly improve the efficiency of the full sized pickup class. The credits and fuel consumption improvement values would apply for purposes of compliance with both the GHG emissions standards and the CAFE standards. This provides the incentive to begin transforming this most challenging category of vehicles toward use of the most advanced technologies.

Access to this credit and fuel consumptio n improvement value is conditioned on a minimum penetration of the technologies in a manu facturer’s full size pickup truck fleet. To ensure its use for only full sized pickup trucks, EPA is proposing a very specific definition for a full sized pickup truck based on minimum bed size and minimum towing capability. The specifics of this proposed definition can be found in Chapter 5 of the draft joint TSD (see Section 5.3.1). This proposed definition is meant to ensure that smaller pickup trucks, which are not used as often for commercial purposes, such as the Ford Ranger or the Honda Ridgeline do not qualify 162 . For this proposal, a full sized pickup truck would be defined as meeting requirements 1 and 2, below, as well as either requirement 3 or 4, below:

1. The vehicle must have an open cargo box with a minimum width between the
wheelhouses of 48 inches measured as the minimum lateral distance between the limiting interferences (pass-through) of the wheelhouses. The measurement would exclude the transitional arc, local prot rusions, and depressions or pockets, if

162 As discussed in TSD Section 5.3.1, EPA is seeking co mment on expanding the scope of this credit to somewhat smaller pickups, provided they have the towing and/or hauling capabilities of the larger full-size trucks.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 150 of 768 present. 163 An open cargo box means a vehicle where the cargo bed does not have a permanent roof or cover. Vehicles sold with detachable covers are considered “open” for the purposes of these criteria.

2. Minimum open cargo box length of 60 inches defined by the lesser of the pickup bed length at the top of the body (defined as the longitudinal distance from the inside front of the pickup bed to the inside of the closed endgate; this would be measured at the height of the top of the open pickup bed along vehicle centerline and the pickup bed length at the floor) and the pickup bed length at the floor (defined as the longitudinal distance from the inside front of the pickup bed to the inside of the closed endgate; this would be measured at the cargo floor surface along vehicle centerline). 164

3. Minimum Towing Capability – the vehicle must have a GCWR (gross combined weight rating) minus GVWR (gross vehicle weight rating) value of at least 5,000 pounds. 165

4. Minimum Payload Capability – the vehicle must have a GVWR (gross vehicle weight rating) minus curb weight value of at least 1,700 pounds.

The technical basis for these proposed defin itions is found in Section III.C below and Chapter 5 of the joint TSD. EPA is proposing that mild HEV pickup trucks would be eligible for a per-truck 10 g/mi CO 2 credit (equal to a 0.001125 gal/mi fuel consumption improvement value) during MYs 2017-2021 if the mild HEV te chnology is used on a minimum percentage of a company’s full sized pickups. 166 That minimum percentage would be 30 percent of a company’s full sized pickup production in MY 2017 with a ramp up to at least 80 percent of production in MY 2021.

EPA is also proposing that strong HEV pickup trucks would be eligible for a per-truck 20 g/mi CO 2 credit (equal to a 0.002250 gal/mi fuel consumption improvement value) during MYs 2017-2025 if the strong HEV technology is used on a minimum percentage of a company’s full sized pickups. That minimum percentage would be 10 percent of a company’s full sized pickup production in each year over the model years 2017-2025.

163 This dimension is also known as dimension W202 as defined in Society of Automotive Engineers Procedure
J1100.

164 The pickup body length at the top of the body is al so known as dimension L506 in Society of Automotive Engineers Procedure J1100. The pickup body length at th e floor is also known as dimension L505 in Society of Automotive Engineers Procedure J1100.

165 Gross combined weight rating means the value specified by the vehicle manufacturer as the maximum weight of a loaded vehicle and trailer, consistent with good engi neering judgment. Gross vehicle weight rating means the value specified by the vehicle manufacturer as the maximum design loaded weight of a single vehicle, consistent with good engineering judgment. Curb weight is define d in 40 CFR 86.1803, consistent with the provisions of 40 CFR 1037.140.

166 The corresponding credit for purposes of compliance with CAFE is discussed at XXXXX.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 151 of 768 To ensure that the hybridization technology used by manufacturers seeking one of these credits and fuel consumption improvement values meets the intent behind the incentives, EPA is proposing very specific definitions of what qu alifies as a mild and a strong HEV. These definitions are described in detail in Chapter 5 of the draft joint TSD (see section 5.3.3).

For similar reasons, EPA is also proposing a performance-based incentive credit and fuel consumption improvement value for full size pickup trucks that achieve an emission level significantly below the applicable target and/ or fuel consumption performance significantly above the CAFE target for that footprint. EPA, in coordination with NHTSA, is proposes this credit to be either 10 g/mi CO 2 (equivalent to 0.001125 gal/mi for the CAFE program) or 20 g/mi

CO 2 (equivalent to 0.002250 gal/mi for the CAFE program) for pickups achieving 15 percent or 20 percent, respectively, better CO 2 or fuel consumption than their footprint based target in a given model year. Further details on this performance-based incentive are in Section III.C below and in Chapter 5 of the draft joint TSD (see Section 5.3.4). The 10 g/ mi (equivalent to 0.001125 gal/mi) performance-based credit and fuel consumption improvement value would be available for MYs 2017 to 2021 and a vehicle meeting the requirements would receive the credit and fuel consumption improvement value until MY 2021 unless its CO 2 level increases or fuel economy decreases. The 20 g/mi CO 2 (equivalent to 0.0023 gal/mi fuel consumption improvement value) performance-based credit would be available for a maximum of 5 years within the model years of 2017 to 2025, provided its CO 2 level and fuel consumption does not increase. The rationale for these limits is because of the year over year progression of the stringency of the truck target curves. The credits and fuel consumption improvement values would begin in the model year of introduction, and could not extend past MY 2021 for the 10 g/mi credit (equivalent to 0.001125 gal/mi) and MY 2025 for the 20 g/mi credit (equivalent to 0.002250 gal/mi).

As with the HEV-based credit and fuel consumption improvement value, the performance-based credit and fuel consumption improvement value requires that the technology be used on a minimum percentage of a manufactur er’s full-size pickup trucks. That minimum percentage for the 10 g/mi GHG credit (equivalent to 0.001125 gal/mi fuel consumption improvement value) would be 15 percent of a company’s full sized pickup production in MY 2017 with a ramp up to at least 40 percent of production in MY 2021. The minimum percentage for the 20 g/mi credit (equivalent to 0.002250 ga l/mi fuel consumption improvement value) would be 10 percent of a company’s full sized pickup production in each year over the model years 2017-2025.

Importantly, the same vehicle could not receive credit and fuel consumption improvement under both the HEV and the performance-based approaches. EPA and NHTSA request comment on all aspects of this proposed pickup truck incentive credit and fuel consumption improvement value, including the pr oposed definitions for full sized pickup truck and mild and strong HEV.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 152 of 768 G. Safety Considerations in Establishing CAFE/GHG Standards

1. Why do the agencies consider safety?

The primary goals of the proposed CAFE and GHG standards are to reduce fuel consumption and GHG emissions from the on-road light-duty vehicle fleet, but in addition to these intended effects, the agencies also consider the potential of the sta ndards to affect vehicle safety. 167 As a safety agency, NHTSA has long considered the potential for adverse safety consequences when establishing CAFE standards, 168 and under the CAA, EPA considers factors related to public health and human welfare, and safety, in regulating emissions of air pollutants
from mobile sources. 169 Safety trade-offs associated with fuel economy increases have occurred in the past (particularly before NHTSA CAFE st andards were attribute-based), and the agencies must be mindful of the possibility of future ones. These past safety trade-offs may have occurred because manufacturers chose, at the time, to build smaller and lighter vehicles—partly in response to CAFE standards—rather than adding more expensive fuel-saving technologies (and maintaining vehicle size and safety), and the smaller and lighter vehicles did not fare as well in crashes as larger and heavier vehicles. Histor ically, as shown in FARS data analyzed by NHTSA, the safest cars have been heavy and large, while the cars with the highest fatal-crash rates have been light and small. The question, then, is whether past is necessarily prologue when it comes to potential changes in vehicle size (both footprint and “overhang”) and mass in response to these proposed future CAFE and GHG standards. Manufacturers have stated that they will reduce vehicle mass as one of the cost-effective means of increasing fuel economy and reducing CO 2 emissions in order to meet the proposed standards, and the agencies have incorporated this expectation into our modeling analysis supporting the proposed standards. Because the agencies discern a historical rela tionship between vehicle mass and safety, it is
reasonable to assume that there will also be relationships between vehicle mass and safety in the future, although it may have been in the past and possibly the future partially or fully mitigated by improvements in vehicle design and advances in vehicle safety features. The question of whether vehicle design can mitigate the adverse effects of mass reduction is discussed below.

Manufacturers are less likely than they were in the past to reduce vehicle footprint in order to reduce mass for increased fuel economy. The primary mechanism in this rulemaking for mitigating the potential negative effects on safety is the application of footprint-based standards,
which create a disincentive for manufacturers to produce smaller-footprint vehicles. See section

167 In this rulemaking document, “vehicle safety” is define d as societal fatality rates which include fatalities to occupants of all the vehicles involved in the collisions, plus any pedestrians.

168 This practice is recognized approvingly in case law. As the United States Court of Appeals for the D.C. Circuit stated in upholding NHTSA’s exercise of judgment in se tting the 1987-1989 passenger car standards, “NHTSA has always examined the safety consequences of the CAFE st andards in its overall consideration of relevant factors since its earliest rulemaking under the CAFE program.” Competitive Enterprise Institute v. NHTSA (“CEI I”) , 901 F.2d 107, 120 at n. 11 (D.C. Cir. 1990).

169 See NRDC v. EPA, 655 F. 2d 318, 332 n. 31 (D.C. Cir. 1981).(EPA may consider safety in developing standards under section 202 (a) and did so appropriately in the given instance).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 153 of 768 II. C.1, above. This is because, as footprint decreases, the corresponding fuel economy/GHG emission target becomes more stringent. We also believe that the shape of the footprint curves themselves is approximately “footprint-neutral, ” that is, that it should neither encourage manufacturers to increase the footprint of their fleet s, nor to decrease it. Upsizing footprint is also discouraged through the curve “cut-off” at larger footprints. 170 However, the footprintbased standards do not discourage downsizing the portions of a vehicle in front of the front axle and to the rear of the rear axle, or of other ar eas of the vehicle outside the wheels. The crush space provided by those portions of a vehicle can make important contributions to managing crash energy. Additionally, simply because fo otprint-based standards create no incentive to
downsize vehicles does not mean that manufact urers will not downsize if doing so makes it easier to meet the overall CAFE/GHG standard, as for example if the smaller vehicles are so much lighter that they exceed their targets by much greater amounts. On balance, however, we believe the target curves and the incentives th ey provide generally will not encourage downsizing (or up-sizing) in terms of footprint reductions (or increases). 171

Given that we expect manufacturers to reduce vehicle mass in response to the proposed standards, and do not expect manufacturers to reduce vehicle footprint in response to the proposed standards, the agencies must attempt to predict the safety effects, if any, of the proposed standards based on the best information currently available. This section explained why the agencies consider safety; the following section discusses how the agencies consider safety.

2. How do the agencies consider safety?

Assessing the effects of vehicle mass reduction and size on societal safety is a complex issue. One part of estimating potential safety effects involves trying to understand better the relationship between mass and vehicle design. Th e extent of mass reduction that manufacturers may be considering to meet more stringent fuel economy and GHG standards may raise different safety concerns from what the industry has previously faced. The principal difference between the heavier vehicles, especially truck-based LTVs , and the lighter vehicles, especially passenger

170 The agencies recognize that at the other end of the cu rve, manufacturers who make small cars and trucks below 41 square feet (the small footprint cut-off point) have some incentive to downsize their vehicles to make it easier to meet the constant target. That cut-off may also create some incentive for manufacturers who do not currently offer models that size to do so in the future . However, at the same time, the agencies believe that there is a limit to the market for cars and trucks smaller than 41 square feet: most consumers likely have some minimum expectation about interior volume, for example, among other things. A dditionally, vehicles in this segment are the lowest price point for the light-duty automotive market, with several models in the $10,000-$15,000 range. Manufacturers who find themselves incentivized by the cut-off will also find themselves adding technology to the lowest price segment vehicles, which could make it challenging to retain the pri ce advantage. Because of these two reasons, the agencies believe that the incentive to in crease the sales of vehicles smaller than 41 sq uare feet due to this rulemaking, if any, is small. See Section II.C.1 above and Chapter 1 of the draf t Joint TSD for more information on the agencies’ choice of “cut-off” points for the footprint-based target curves.

171 This statement makes no prediction of how consumer choices of vehicle size w ill change in the future, independent of this proposal.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 154 of 768 cars, is that mass reduction has a different effect in collisions with another car or LTV. When two vehicles of unequal mass collide, the change in velocity (delta V) is higher in the lighter vehicle, similar to the mass ratio proportion. As a result of the higher change in velocity, the fatality risk may also increase. Removing more mass from the heavier vehicle than in the lighter vehicle by amounts that bring the mass ratio closer to 1.0 reduces the delta V in the lighter vehicle, possibly resulting to a net societal benefit.

Another complexity is that if a vehicle is made lighter, it may also n eed to be made stiffer to protect its occupants in a crash to manage th e total energy of the crash. A stiffer vehicle affects the forces on the vehicle’s occupants in a crash – because the vehicle manages crash energy differently, the occupants may have to “ride down” greater crash forces themselves, putting more burden on the restraint systems to protect the occupants. Matching the restraint system to the vehicle stiffness may help mitigat e the effects of increased vehicle stiffness.
Another factor is that a stiffer vehicle also affects the forces that the stiffer vehicle exerts on the vehicles it crashes into – stiffer vehicles can be more aggressive in crashes due to the crash energy transfer.

The agencies must attempt to estimate now, based on the best information currently before us, how the assume d levels of mass reduction without additional changes (i.e. footprint, performance, functionality) might affect the safe ty of vehicles, and how lighter vehicles might affect the safety of drivers and passengers in the entire on-road fleet, as we are analyzing potential future CAFE and GHG standards. The agencies seek to ensure that the standards aredesigned to encourage manufacturers to pursue a path toward compliance that is both costeffective and safe.

To estimate the possible safety effects of the MY 2017-2025 standards, then, the agencies have undertaken research that approaches this qu estion from several angles. First, we are using a statistical approach to study the effect of ve hicle mass reduction on safety historically, as discussed in greater detail in section C below. Statistical analysis is performed using the most recent historical crash data available, and is cons idered as the agencies’ best estimate of potential mass-safety effects. The agencies recognize that negative safety effects estimated based on the historical relationships could a dditionally be potentially tempered with safety technology advances in the future, and may not represent the current or future fleet. Second, we are using an engineering approach to investigate what amount of mass reduction is affordable and feasible while maintaining vehicle safety and other major functionalities such as NVH and acceleration performance. Third, we are also studying the ne w challenges these lighter vehicles might bring to vehicle safety and potential countermeasures available to manage those challenges effectively.

The sections below discuss more specifically th e state of the research on the mass-safety relationship, and how the agencies integrate that research into our assessment of the potential safety effects of the MY 2017-2025 CAFE and GHG standards.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 155 of 768 3. What is the current state of the research on statistical analysis of historical crash
data?

a. Background

Researchers have been using statistical analysis to examine the relationship of vehicle mass and safety in historical crash data for many years, and continue to refine their techniques over time. In the MY 2012-2016 final rule, the agencies stated that we would conduct further study and research into the interaction of mass, si ze and safety to assist future rulemakings, and start to work collaboratively by developing an interagency working group between NHTSA, EPA, DOE, and CARB to evaluate all aspects of mass, size and safety. The team would seek to coordinate government supported studies and i ndependent research, to the greatest extent possible, to help ensure the work is complementary to previous and ongoing research and to guide further research in this area.

The agencies also identified three specific areas to direct research in preparation for future CAFE/GHG rulemaking in regards to statistical analysis of historical data.

First, NHTSA would contract wi th an independent institution to review the statistical methods that NHTSA and DRI have used to analyze historical data related to mass, size and safety, and to provide recommendation on whether the existing methods or other methods should be used for future statistical analysis of histori cal data. This study will include a consideration of potential near multicollinearity in the historical da ta and how best to address it in a regression analysis. The 2010 NHTSA report was also peer reviewed by two other experts in the safety field - Charles Farmer (Insurance Institute fo r Highway Safety) and Anders Lie (Swedish Transport Administration). 172

Second, NHTSA and EPA, in consultation with DOE, would update the MYs 1991–1999 database on which the safety analyses in the NPRM and final rule are based with newer vehicle data, and create a common database that could be made publicly available to help address concerns that differences in data were leading to different results in statistical analyses by
different researchers.

And third, in order to assess if the design of recent model year vehicles that incorporate various mass reduction methods affect the relationships among vehicle mass, size and safety, the agencies sought to identify vehi cles that are using material su bstitution and smart design, and to try to assess if there is sufficient crash data invo lving those vehicles for statistical analysis. If sufficient data exists, statistical analysis would be conducted to compare the relationship among

172 All three of the peer reviews are in docket, NHTSA-2010-0152. You can access the docket at http://www.regulations.gov/#!home by typing ‘NHTSA-2010-0152’ where it says “enter keyword or ID” and then clicking on “Search.”Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 156 of 768 mass, size and safety of these smart design vehicl es to vehicles of similar size and mass with more traditional designs.

Significant progress has been made on thes e tasks since the MY 2012-2016 final rule, as follows: The independent review of recent and upd ated statistical analyses of the relationship between vehicle mass, size, and crash fatality rates has been completed. NHTSA contracted with the University of Michigan Tran sportation Research Institute (U MTRI) to conduct this review, and the UMTRI team led by Paul Green evaluated over 20 papers, including studies done by NHTSA’s Charles Kahane, Tom Wenzel of Lawrence Berkeley National Laboratories, Dynamic Research, Inc., and others. UMTRI’s basic findi ngs will be discussed below. Some commenters in recent CAFE rulemakings, including some vehi cle manufacturers, suggested that the designs and materials of more recent model year vehicles may have weakened the historical statistical relationships between mass, size, and safety. Th e agencies agree that the statistical analysis would be improved by using an updated database that reflects more recent safety technologies, vehicle designs and materials, and reflects changes in the overall vehicle fleet. The agencies also believe, as UMTRI also found, that part of the r eason that different past statistical analyses may have come up with different results could be due to the lack of a single comprehensive database
of crash information. In order to try to mitigate this po ssibility and to su pport the current rulemaking, NHTSA has created a common, updated database for statistical analysis that consists of crash data of model years 2000-2007 vehicles in calendar years 2002-2008, as compared to the database used in prior NHTSA analyses which was based on model years 1991–1999 vehicles in calendar years 1995-2000. The new database is the most up-to-date possible, given the processing lead time for crash data and the n eed for enough crash cases to permit statistically meaningful analyses. NHTSA has made the new databases available to the public, 173 enabling other researchers to analyze the same data and hopefully minimizing discrepancies in the results
that would have been due to inconsistencies across databases. 174 The agencies recognize, however, that the updated database may not represent the future fleet, because vehicles have continued and will continue to change.

The agencies are aware that several studies have b een initiated by using NHTSA’s 2011 newly established safety database. In addition to a new Kahane study, which is discussed in section II.G.4, other on-going studies include one from Wenzel at Lawrence Berkeley National Laboratory (LBNL) under contract with the U.S. DOE, and Dynamic Research, Inc. (DRI) contracted by the International Council on Clean Transportation (ICCT). These studies may take somewhat different approaches to examine the statistical relationship between fatality risk, vehicle mass and size. Wenzel’s dual approach is expected to consider the casualty risk effect associated with mass reduction, in addition to a detailed assessment of the NHTSA 2011 report. Casualty risk includes both fatality risk and seri ous injuries. DRI’s is expected to investigate a

173 The new databases are available at http://www.nhtsa. gov/fuel-economy (look for “Download Crash Databases for Statistical Analysis of Relationships Between Vehicles’ Fatality Risk, Mass, and Footprint.”

174 75 Fed. Reg. 25324 (May 7, 2010); the discussion of planned statistical analyses is on pp. 25395-25396.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 157 of 768 two-stage approach to separate the fatality risk effect between crash avoidance and crash worthiness explicitly due to mass reduction. The LBNL-Wenzel report on detailed assessment of the NHTSA 2011 report will be avai lable in the docket this NPRM. 175 The casualty risk effect study was not available in time to inform this NPRM. The completed final peer reviewed-report on both assessments will be available prior to th e final rule. DRI has also indicated that it expects its study to be publicly available prior to the final rule. The agencies will consider these studies and any others that become available, and the results may influence the safety analysis
for the final rule.

Other researchers are free to download the database from NHTSA’s website, and we expect to see additional papers in the coming months and as co mments to the rulemaking that may also inform our consideration of these issues for the final rule. Kahane’s updated study for 2011 is currently undergoing peer-review, and is available in the docket for this rulemaking for review by commenters.

And finally, EPA and NHTSA with DOT’s Volpe Center, part of the Research and Innovative Technology Administration (RITA), attempted to investigate the implications of “Smart Design,” by identifying and describing the types of “Smart Design” and methods for using “Smart Design” to result in vehicle mass reduction, selecting analytical pairs of vehicles, and using the appropriate crash database to analy ze vehicle crash data. The analysis identified
several one-vehicle and two-vehicle crash datasets with the potential to shed light on the issue, but the available data for specific crash scenarios was insufficient to produce consistent results that could be used to support conclusions regardi ng historical performance of “smart designs.”

Undertaking these tasks has helped the agencies come closer to resolving some of the ongoing debates in statistical analysis research of historical crash data. We intend to apply these conclusions going forward, and we believe that the public discussion of the issues will be facilitated by the research conducted. The following sections discuss the findings from these studies and others in greater detail, to present a more nuanced picture of the current state of the
statistical research.

b. NHTSA workshop on vehicle mass, size and safety

On February 25, 2011, NHTSA hosted a workshop on mass reduction, vehicle size, and fleet safety at the Headquarters of the U.S. De partment of Transportation in Washington, DC. 176
The purpose of the workshop was to provide the agencies with a broad understanding of current research in the field and provide stakeholders an d the public with an opportunity to weigh in on

175 Need reference to LBNL study -EPA

176 A video recording, transcript, and the presentations from the NHTSA workshop on mass reduction, vehicle size and fleet safety is available at http://www.nhtsa.gov/fuel-economy (look for “NHTSA Workshop on Vehicle MassSize-Safety on Feb. 25”)Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 158 of 768 this issue. NHTSA also created a public docket to receive comments from interested parties that
were unable to attend.

The speakers included Charles Kahane of NHTSA, Thomas Wenzel of Lawrence Berkeley National Library, R. Michael Van Auken of Dynamic Research Inc. (DRI), Jeya Padmanaban of JP Research, Inc., Adrian Lund of the Insurance Institute for Highway Safety, Paul Green of the University of Michigan Transportation Research Institute (UMTRI), Stephen Summers of NHTSA, Gregg Peterson of Lotus Engineering, Koichi Kamiji of Honda, John
German of the International Council on Clean Transportation (ICCT), Scott Schmidt of the Alliance of Automobile Manufacturers, Guy Nusholtz of Chrysler, and Frank Field of the Massachusetts Institute of Technology.

The wide participation of the workshop allowed the agencies to hear from a broad range of experts and stakeholders. The contributions were particularly relevant to the agencies’ analysis of the effects of weight reduction for this proposed rule. The presentations were divided
into two sessions that addresse d the two expansive sets of issues – statistical evidence of the roles of mass and size on safety, and engineering r ealities – structural crashworthiness, occupant injury and advanced vehicle design.

The first session focused on previous and ongoi ng statistical studies of crash data that attempt to identify the relative effects of vehicle mass and size on fleet safety. There was consensus that there is a complicated relationship with many confounding influences in the data. Wenzel identified qualitatively similar trends in results for various classes of vehicles (e.g., nonsports car passenger cars, vans, SUVs, crossove r SUVs, pickups) regardless of what risk was being measured (fatality or casualty) or what exposure metric was used (e.g., registration years, police-reported crashes, etc.). In general, most showed trends demonstrated lower risk for heavier vehicles. Due to varying reporting criteria in different component databases, results were sometimes off by a discernible but consistent factor. Several participants pointed out that analyses must control for individual technologies with significant safety effects (e.g., Electronic Stability Control, airbags).It was not always conc lusive whether a specialty vehicle group (e.g., sports cars, two-door cars, early crossover SUVs) were outliers that confound the trend or unique datasets that isolate specific vehicle characteristi cs. Unfortunately, specialty vehicle groups are usually adopted by specific driver groups, often with outlying vehicle usage or driver behavior patterns. Green, who is conducting an independen t review of the current statistical analyses, suggested that evaluating residuals will give an i ndication of whether or not a data subset can be legitimately removed.

It was recognized that the physics of a two- vehicle crash require that the lighter vehicle experience a greater change in velocity and often l eads to disproportionately more injury risk. Lund noted persistent historical trends that, in any time period, occupants of the smallest and lightest vehicles had fatality rates approximately twice those of occupants of the largest and heaviest vehicles but predicted the sky will not fall as the fleet downsizes, we will not see anSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 159 of 768 increase in absolute injury risk because smaller cars will become increasingly protective of their occupants. Padmanaban also noted in her research of the historical trends that mass ratio and vehicle stiffness are significant predictors with mass ratio consistently the dominant parameter when correlating harm. Reducing the mass of a ny vehicle may have competing societal effects as it increases the injury risk in the lightened vehicle and decreases them in the partner vehicle.

The separation of key parameters was also discussed as a challenge to the analyses, as vehicle size is highly correlated with vehicle mass in the previous historical databases. Presenters had varying approaches for acknowledging the importance of and dealing with the effects of this variable multicollinearity. Van A uken of DRI stated that there was latitude in the value of Variance Inflation Factor (VIF, a measur e of multicollinearity) that would call results into question and suggested that the large value of VIF for curb weight might imply “perhaps the effect of weight is too small in comparison to other factors.” Green, of UMTRI, stated that highly correlated variables may not be appropriate for use in a predictive model and that “match[ing] on footprint” (i.e., conducting multiple analyses for data subsets with similar footprint values) may be the most effective way to resolve the issue.

There was no consensus on the overall effect of the maneuverability of smaller, lighter vehicles. German noted that lighter vehicles should have improved handling and braking characteristics and “may be more likely to avoi d collisions”. Lund presented crash involvement data that implied that, among vehicles of similar function and use rates, crash risk does not go down for more “nimble” vehicles. Several presen ters noted the difficulties of projecting past
data into the future as new tec hnologies will be used that were not available when the data were collected. The advances in technology through the decades have dramatically improved safety for all weight and size classes. A video of IIHS’s 50 th anniversary crash test of a 1959 Chevrolet Bel Air and 2009 Chevrolet Malibu graphically demo nstrated that stark differences in design and technology that can possibly mask the discrete mass effects, while videos of compatibility crash tests between smaller, lighter vehicles and cont emporary larger, heavier vehicles graphically showed the significance of vehicle mass and size.

Kahane’s presented results from his 2010 report 177 that found that foreseeable mass reductions, which took so me mass out of heavier vehicles but little or no mass out of the lightest vehicles, did not impact safety in absolute terms. Kahane noted that if the analyses were able to consider the mass of both light vehicles in a two-car crash, the results may be more indicative of future crashes. There is apparent consistency with other presentations (e.g., Padmanaban, Nusholtz) that reducing the overall ranges of masses and mass ratios seems to reduce overall societal harm. That is, the eff ect of mass reduction exclusively does not appear to be a “zero sumSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 160 of 768 game” in which any increase in harm to occupants of the lightened vehicle is precisely offset by a decrease in harm to the occupants of the partner vehicle. If the mass of the heavier vehicle is reduced by a larger percentage, the changes in velocity from the collision are more nearly equal and the injuries suffered in the lighter vehicle are likely to be reduced more than the injuries in the heavier vehicle are increased. Alternatively, a fixed mass reduction (say, 100 lbs) in all
vehicles could increase societal harm whereas a fixed percentage mass reduction is more likely
to be neutral.

Padmanaban described a series of studies conducted in recent years. She included numerous vehicle parameters including bumper height and several measures of vehicle size and stiffness and also commented on previous histor ic analysis that using weight and wheelbase together in a logistic model distorts the estimates , resulting in inflated variance with wrong signs and magnitudes in the results. Her results consistently showed that vehicle mass ratio was a more important parameter than those describing vehicle geometry or stiffness. Her ultimate conclusion was that removing mass (e.g., 100 lbs.) from all passenger cars would cause an overall increase in fatalities in truck-to-car crashes while removing the same amount from light
trucks would cause an overall decrease in fatalities.

c. Report by Green et al., UMTRI – “Independent Review: Statistical Analyses of Relationship Between Vehicle Curb Weight, Track Width, Wheelbase and Fatality Rates,” April 2011.

As explained above, NHTSA contracted with the University of Michigan Transportation Research Institute (UMTRI) to conduct an independent review 178 of a set of statistical analyses of relationships between vehicle curb weight, th e footprint variables (track width, wheelbase) and fatality rates from vehicle crashes. The purpose of this review was to examine analysis methods, data sources, and assumptions in a set of previous statistical studi es, with the objective of identifying the reasons for the differences in results. Another objective was to examine the suitability of the various methods for estimating the fatality risks of future vehicles.

UMTRI reviewed a set of papers, reports, and manuscripts provided by NHTSA (listed in Appendix A of UMTRI’s report, which is available in the docket to this rulemaking) and examined the statistical analyses of relations hips between crash or fatality rates and vehicle properties such as curb weight, track width, wheelbase and other variables.

It is difficult to summarize a study of that length and complexity for purposes of this discussion, but fundamentally, the UMTRI team concluded the following:

 Differences in data may have complicated comparisons of earlier analyses, but if the methodology is robust, and the methods were applied in a similar way, small changes in

178 The review is independent in the sense that it was conduc ted by an outside third party without any interest in the reported outcome.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 161 of 768 data should not lead to different conclusions. The main conclusions and findings should be reproducible. The data base created by Kahane appears to be an impressive collection of files from appropriate sources and the best ones available for answering the research questions considered in this study.

 In general, for statistical analysis of histori cal crash data, simpler models generally lead to improved inference, assuming the data and model assumptions are appropriate, and in that regard, the disaggregate logistic regression model used by NHTSA in the 2003 report 179 seems to be the most appropriate model, and valid for the analysis of rates in the context that it was used – finding general associations between fatality risk and mass – and the general directions of the reported associations are correct.

 The two-stage logistic regression model in combination with the two-step aggregate regression used by DRI seems to be more comp licated than is necessary based on the data being analyzed, and summing regression coefficients from two separate models to arrive at conclusions about the effects of reductions in weight or size on fatality rates seems to add unneeded complexity to the problem.

 Discussion of multicollinearity – UMTRI states that one of the biggest issues regarding this work is the historical correlation between curb weight, wheelbase, and track width. Including three variables that are highly correlated in the same model can have adverse effects on the fit of the model, especially with respect to the parameter estimates, as discussed by Kahane. UMTRI makes no conclusions about multicollinearity, other than to say that inferences made in the presence of multicollinearity should be judged with great concern. At the NHTSA workshop on size safety and mass, Paul Green suggested that a matched analysis (designed to control confounders) based on footprint could be undertaken to make the model more efficient. Kahane has combined wheelbase and track width into one variable (footprint) to compar e to curb weight. NHTSA believes that the 2011 Kahane analysis has done all it can to lessen concerns about multicollinearity, but a concern still exists. In considering other studies provided by NHTSA for evaluation by the UMTRI team:

o Papers by Wenzel and Wenzel and Ross addressing associations between crash risk, weight, and size, mostly focused on certain passenger car and light truck model types, contribute to understanding some of the relationships between risk, weight, and size, and some describe findings that are generally in the right direction. However, least squares linear regression models, without modification, are not exposure-based risk models and inference drawn from these models tends to be weak since they do not account for differences in exposure measures in the denominators of the rates.

o A 2009 J.P. Research paper focused on the difficulties associated with separating out the contributions of weight and size variables when analyzing fatality risk properly recognized the problem arising from multicollinearity and included a clear explanation of why fatality risk is expected to increase with increasing mass ratio. UMTRI concluded that the positive fatality rate increases associated with aSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 162 of 768 100-pound weight reduction in vehicle weight estimated by Kahane and JP Research are broadly more convincing than the 6.7 percent reduction of fatalities reported by DRI.

o A paper by Nusholtz et al. focused on the question of whether vehicle size can reasonably be the dominant vehicle factor for fatality risk, and finding that changing the mean mass of the vehicle population (leaving variability unchanged) has a stronger influence on fatality risk than corresponding (feasible) changes in mean vehicle dimensions, concluded une quivocally that reducing vehicle mass while maintaining constant vehicle dimensions will increase fatality risk. UMTRI concluded that if one accepts the methodology, this conclusion is robust against realistic changes that may be made in the force vs. deflection characteristics of the impacting vehicles.

o Two papers by Robertson, one a commentary paper, and the other a peerreviewed journal paper were reviewed. The commentary paper did not fit separate models according to crash type, and included passenger cars, vans, and SUVs in the same model. UMTRI conclu ded that some of the claims in the commentary paper appear to be overstated, and intermediate results and more documentation would help the reader determine if these claims are valid. The second paper focused largely on the effects of electronic stability control (ESC), but generally followed on from the first paper except that curb weight is not fit and fuel economy is used as a surrogate.

The UMTRI study provided a number of useful suggestions that Kahane considered in updating his 2011 analysis, and that have been incorporated into the safety effects estimates for the current rulemaking.

d. Report by Dr. Charles Kahane, NHTSA – “Relationships Between Fatality Risk, Mass, and Footprint in Model Year 2000-2007 Passenger Cars and LTVs,” 2011

The relationship between a vehicle’s mass, size, and fatality risk is complex, and it varies in different types of crashes. NHTSA, along with others, has been examining this relationship for over a decade. The safety chapter of NHTSA’s April 2010 final regulatory impact analysis (FRIA) of CAFE standards for MY 2012-2016 passenger cars and light trucks included a statistical analysis of relationships between fa tality risk, mass, and footprint in MY 1991-1999 passenger cars and LTVs (light trucks and vans), based on calendar year (CY) 1995-2000 crash and vehicle-registration data. 180

The principal findings and conclusions of NHTSA’s 2010 report were that mass reduction in the lighter cars, ev en while holding footprint constant would significantly increase

180 Kahane, C. J. (2010). “Relationships Between Fatality Risk, Mass, and Footprint in Model Year 1991-1999 and Other Passenger Cars and LTVs,” Final Regulatory Impact Analysis: Corporate Average Fuel Economy for MY 2012-MY 2016 Passenger Cars and Light Trucks . Washington, DC: National Highway Traffic Safety Administration, pp. 464-542, available at http://www.nhtsa.gov/staticfiles/rulemaking/pdf/cafe/CAFE_2012- 2016_FRIA_04012010.pdf

.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 163 of 768 fatality risk, whereas mass re duction in the heavier LTVs would significantly reduce societal fatality risk, because it would reduce the fatality ri sk of occupants of lighter vehicles colliding with those heavier LTVs. NHTSA concluded that, as a result, any reasonable combination of mass reductions that held footprint constant in MY 2012-2016 vehicles – concentrated, at least to some extent, in the heavier LTVs and limited in the lighter cars – would likely be approximately safety-neutral; it would not significantly increase fatalities and might well decrease them.

NHTSA’s 2010 report partially agreed and partially disagreed with analyses published during 2003-2005 by Dynamic Research, Inc. (DRI ). NHTSA and DRI both found a significant protective effect for footprint and that reducing mass and footprint together (downsizing) on smaller vehicles was harmful. DRI’s analyses estimated significant overall benefits for mass reduction in all passenger cars and LTVs if wheel base and track width were maintained, whereas NHTSA’s report showed an overall benefit only in the heavier LTVs, but for other classes of vehicles, benefits only in some types of crashes. Much of NHTSA’s 2010 report as well as recent work by DRI involved sensitivity tests on the databases and models and generated a range
of estimates somewhere between the initial DRI and NHTSA results. 181

Immediately after issuing the final rule for MYs 2012-2016 CAFE and GHG standards in May 2010, NHTSA and EPA began work on the next joint rulemaking to develop CAFE and GHG standards for MYs 2017 and beyond. The preamble to the 2012-2016 final rule stated that NHTSA, working closely with EPA and the Department of Energy (DOE), would perform a new statistical analysis of the relationships between fatality rates, mass and footprint, updating the crash and exposure databases to the latest available model years, refining the methodology in response to peer reviews of the 2010 report and taking into account changes in vehicle technologies. The previous databases of MY 1991-1999 vehicles in CY 1995-2000 crashes has become outdated as new safety technologies, ve hicle designs and materials were introduced. The new databases comprising MY 2000-2007 vehicles in CY 2002-2008 crashes with the most up-to-date possible, given the processing lead time for crash data and the need for enough crash cases to permit statistically meaningful analyses . NHTSA has made the new databases available

181 Van Auken, R. M., and Ze llner, J. W. (2003). A Further Assessment of the Eff ects of Vehicle Weight and Size Parameters on Fatality Risk in Model Year 1985-98 Passenger Cars and 1986-97 Light Trucks . Report No. DRITR-03-01. Torrance, CA: Dynamic Research, Inc.; Van Auken, R. M., and Zellner, J. W. (2005a). An Assessment of the Effects of Vehicle Weight and Size on Fatality Risk in 1985 to 1998 Model Year Passenger Cars and 1985 to 1997 Model Year Light Trucks and Vans . Paper No. 2005-01-1354. Warrendale, PA: Society of Automotive Engineers; Van Auken, R. M., and Zellner, J. W. (2005b). Supplemental Results on the Independent Effects of Curb Weight, Wheelbase, and Track on Fatality Risk in 1985-19 98 Model Year Passenger Cars and 1986-97 Model Year
LTVs . Report No. DRI-TR-05-01. Torrance, CA: Dynamic Research, Inc.; Van Auken, R.M., and Zellner, J. W. (2011). “Updated Analysis of the Effects of Pa ssenger Vehicle Size and Weight on Safety,” NHTSA Workshop on Vehicle Mass-Size-Safety , Washington, February 25, 2011, http://www.nhtsa.gov/staticfiles/rulemak ing/pdf/MSS/MSSworks hop_VanAuken.pdfSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 164 of 768 to the public 182 , enabling other researchers to analyze the same data and hopefully minimizing discrepancies in the results that would have been due to inconsistencies across databases. 183

One way to estimate these effects is via statistical analyses of societal fatality rates per vehicle miles traveled (VMT), by vehicles’ mass and footprint, for the current on-road vehicle fleet. The basic analytical method used for the 2011 NHTSA report is the same as in NHTSA’s 2010 report: cross-sectional analyses of the societal fatality rate per billion vehicle miles of travel (VMT) by mass and footprint, while controlling for driver age, gender, and other factors, in separate logistic regressions by vehicle class an d crash type. Societal fatality rates include occupants of all vehicles in the crash as well as pedestrians. NHTSA’s 2011 Report 184 analyzes MY 2000-2007 cars and LTVs in CY 2002-2008 crashes. Fatality rates were derived from FARS data, 13 State crash files, and registration and mileage data from R.L. Polk.

The most noticeable change in MY 2000-2007 vehicles from MY 1991-1999 has been the increase in crossover utility vehicles (CUV), which are SUVs of unibody construction, often but not always built upon a platform shared with passenger cars. CUVs have blurred the
distinction between cars and trucks. The new anal ysis treats CUVs and minivans as a separate vehicle class, because they differ in some respects from pickup-truck-based LTVs and in other respects from passenger cars. In the 2010 report, the many different types of LTVs were combined into a single analysis and NHTSA believes that this may have made the analyses too complex and might have contributed to so me of the uncertainty in the results.

The new data has accurate VMT estimates, derived from a file of odometer readings by make, model, and model year recently developed by R.L. Polk and purchased by NHTSA. 185 For the 2011 report, the relative distribution of crash types has been changed to reflect projected future crash types during the period from 2017 to 2025 based on the effectiveness of electronic stability control (ESC). For exam ple, the percent of rollover cr ashes has been reduced and two vehicle crashes increased. The annual target population of fatalities or the annual fatality
distribution baseline 186 was not decreased in the period between 2017 and 2025 for the safety statistics analysis, but is taken into account later in the Volpe model analysis, since all vehicles in the future will be equipped with ESC 187

.

182 http://www.nhtsa.gov/fuel-economy

183 75 Fed. Reg. 25324 (May 7, 2010); the discussion of planned statistical analyses is on pp. 25395-25396.

184 Kahane, C. J. (2011). “Relationships Between Fatal ity Risk, Mass, and Footprint in Model Year 2000-2007 Passenger Cars and LTVs,”, July 2011. The report is available in the NHTSA docket, NHTSA-2010-0152. You can access the docket at http://www.regulations.gov/#!home by typing ‘NHTSA-2010-0152’ where it says “enter keyword or ID” and then clicking on “Search.”

185 In the 1991-1999 data base, VMT was estimated onl y by vehicle class, based on NASS CDS data.

186 MY 2004 -2007 vehicles with fatal crashes occurred in CY 2004-2008 are selected as the annual fatality distribution baseline in the Kahane analysis.

187 In the Volpe model, NHTSA assumed that the safety trend would result in 12.6 percent reduction between 2007 and 2020 in the combination of ESC, new safety standard, and behavior changes anticipated.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 165 of 768 For the 2011 report, vehicles are now grouped into five classes rather than four: passenger cars (including both 2-door and 4-door car s) are split in half by median weight; CUVs and minivans; and truck-based LTVs, which are also split in half by median weight of the model year 2000-2007 vehicles. Table 0-12 presents the estimated percent increase in societal fatality rates per 100-pound mass reduction while holding footprint constant for five classes of vehicles.

Table 0-12 Results of 2011 NHTSA report Fatality Increase (%) per 100-Pound Mass Reduction While Hold ing Footprint Constant

MY 2000-2007 CY 2002-2008 Fatality Increase (%) Per 100-Pound Mass Reduction While Holding Footprint Constant

Point Estimate 95% Confidence Bounds

Cars < 3,106 pounds 1.44 + .29 to +2.59
Cars > 3,106 pounds .47 - .58 to +1.52
CUVs and minivans - .46 -1.75 to + .83 Truck-based LTVs < 4,594 pounds .52 - .43 to +1.46 Truck-based LTVs > 4,594 pounds - .39 -1.06 to + .27

Only the 1.44 percent risk increase in the lighter cars is statistically significant. There are non-significant increases in the heavier car s and the lighter truck-based LTVs and nonsignificant societal benefits for mass reduction in CUVs, minivans, and the heavier truck-based LTVs. Based on these results, potential combinations of mass reductions that maintain footprint and are proportionately somewhat higher for the heavier vehicles may be safety-neutral or better as point estimates and, in any case, unlikely to significantly increase fatalities. The primarily non-significant results are not due to a paucity of data, but because the societal effect of mass
reduction while mainta ining footprint, if any, is small.

MY 2000-2007 vehicles of all types are heavier and larger than their MY 1991-1999 counterparts. The average mass of passenger cars increased by 5 percent from 2000 to 2007 and the average mass of pickup trucks increased by 19 percent. Other types of vehicles became heavier, on the average, by intermediate amounts. There are several reasons for these increases: during this time frame, some of the lighter make-models were discontinued; many models were redesigned to be heavier and larger; and consumers more often selected stretched versions such as crew cabs in their new-vehicle purchases.

It is interesting to compare the new result s to NHTSA’s 2010 analysis of MY 1991-1999 vehicles in CY 1995-2000, especially the new po int estimate to the “actual regression result scenario” in the 2010 report:

Table 0-13 2010 Report: MY 1991-1999, CY 1995-2000 Fatality Increase (%) per 100-Pound Mass Reduction While Holding Footprint ConstantSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 166 of 768 Actual Regression Result Scenario Upper-Estimate Scenario Lower-Estimate Scenario Cars < 2,950 pounds 2.21 2.21 1.02
Cars > 2,950 pounds 0.90 0.90 0.44 LTVs < 3,870 pounds 0.17 0.55 0.41
LTVs > 3,870 pounds -1.90 -0.62 -0.73

Table 0-14 Fatality Increase (%) per 100-Pound Mass Reduction While Holding Footprint Constant

NHTSA (2010) NHTSA (2011)

Lighter cars 2.21% 1.43%

Heavier cars 0.89% 0.48% Lighter LTVs 0.17%* 0.52%

Heavier LTVs -1.90%* -0.40%

CUV/ minivan -0.47%

*Includes CUV/minivan

The new results are directionally the same as in 2010: fatality increase in the lighter cars, safety benefit in the heavier LTVs, but the effects may have become weaker at both ends. (The agencies do not consider this conclusion to be definitive because of the relatively wide confidence bounds of the estimates.) The fatality increase in the lighter cars tapered off from 2.21 percent to 1.44 percent while the societal benefit of mass reduction in the heaviest LTVs diminished from 1.90 percent to 0.39 percent a nd is no longer statistically significant.

The agencies believe that the changes may be due to a combination of “real” factors (characteristics of the newer vehicles) and revisi ons to the analysis. NHTSA believes, above all, many cars with poor safety performance, which were often light, small cars, were discontinued by 2000 or during 2000-2007. The tendency of light, small vehicles to be driven poorly, while still there, is not as strong as it used to be – perhaps in part because safety improvements in lighter and smaller vehicles have made some good drivers more willing to buy them. Both agencies believe that at the other end of the spectrum, blocker beams and other voluntary compatibility improvements in LTVs as we ll as compatibility-related self-protection improvements to cars have made the heavier LTVs somewhat less aggressive in collisions with lighter vehicles (although the effect of mass dispar ity remains). This report’s analysis of CUVs and minivans as a separate class of vehicles may have relieved some inaccuracies in the 2010 regression results for LTVs. Interestingly, the ne w actual-regression results are quite close to the previous report’s “lower-estimate scenario,” which was an attempt to adjust for supposed inaccuracies in some regressions and for a seemin gly excessive trend toward higher crash rates in smaller and lighter cars.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 167 of 768 The principal difference between the heavier vehicles, especially truck-based LTVs, and the lighter vehicles, especially passenger cars, is that mass reduction has a different effect in
collisions with another car or LTV. When two ve hicles of unequal mass collide, the delta V is higher in the lighter vehicle, in the same propor tion as the mass ratio. As a result, the fatality risk is also higher. Removing some mass from the heavy vehicle reduces delta V in the lighter vehicle, where fatality risk is high, resulting in a large benefit, offset by a small penalty because delta V increases in the heavy vehicle, where fatality risk is low – adding up to a net societal benefit. Removing some mass from the lighter vehicle results in a large penalty offset by a small benefit – adding up to net harm. These considerations drive the overall result: fatality increase in the lighter cars, redu ction in the heavier LTVs, and little effect in the intermediate groups. However, in some types of crashes th at do not involve collisions between cars and LTVs, especially 1 st -event rollovers and impacts with fixed objects, mass reduction is usually not harmful and often beneficial, because the lighter vehicles respond more quickly to braking and steering and are often more stable because their center of gravity is lower. Offsetting that benefit is the continuing historical tendency of lighter and smaller vehicles to be driven less well – although it continues to be unknown why that is so, and to what extent, if any, the lightness or smallness of the vehicle contributes to people driving it less safely.

The estimates of the model are formulated for 100-pound mass reductions. According to the regression results, if risk increases or decreases by 1 percent for 100 pounds, it would increase or decrease by 2 percent for 200 pounds and 3 percent for 300 pounds (more exactly, 2.01 percent and 3.03 percent, because the effects work like compound interest). Confidence bounds will grow wider by the same proportions.

The regression results are best suited to predict the effect of a small change in mass, leaving all other factors the same as the model was developed (MY 2000-2007 in CY 2002- 2008), including performance, wheelbase and track wi dth. With each additional change from the current environment, the model may become somewh at less accurate and it is difficult to assess the sensitivity to additional mass reduction greater than 100 pounds. The agencies recognize that the light duty vehicle fleet in the 2017-2025 ti meframe will be different than the 2000-2007 fleet analyzed for this study. Nevertheless, one consideration provides some basis for confidence. This is NHTSA’s fourth evaluation of the effects of mass reduction and/or downsizing, comprising databases ranging from MY 1985 to 2007. The results of the four studies are not identical, but they have been consistent up to a point. During this time period, many makes and models have increased substantially in ma ss, sometimes as much as 30-40 percent. 188 If the statistical analysis has, over the past years, been able to accommodate mass increases of this

188 For example, one of the most popular models of small 4-door sedans increased in curb weight from 1,939 pounds in MY 1985 to 2,766 pounds in MY 2007, a 43 percent increase. A high-sales mid-size sedan grew from 2,385 to 3,354 pounds (41%); a best-selling pickup truck from 3,390 to 4,742 pounds (40%) in the basic model with 2-door cab and rear-wheel drive; and a popular minivan from 2,940 to 3,862 pounds (31%).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 168 of 768 magnitude, perhaps it will also succeed in modelin g the effects of mass reductions on the order of 10-20 percent, if they occur in the future.

e. Based on this information, what do the agencies consider to be the current state of statistical research on vehicle mass and safety?

The agencies believe that statistical analysis of historical crash data continues to be an informative and important tool in assessing the potential safety impacts of the proposed standards. The effect of mass reduction (while maintaining footprint) is a complicated topic and there are open questions whether future designs ma y offset the findings of statistical analysis of historical data. It is important to note that while the updated database represents more current vehicles with technologies more representative of vehicles on the road today, they still do not fully represent what vehicles will be on the road in the 2017-2025 timeframe. The vehicles
manufactured in the 2000-2007 timeframe were not subject to footprint-based fuel economy standards. The agencies expect that the attri bute-based standards will likely facilitate the design of vehicles such that manufacturers may reduce ma ss while maintaining footprint. Therefore, it is possible that the analysis for 2000-2007 vehicles may not be fully representative of the vehicles
that interact with the exis ting fleet in 2017 and beyond.

While we recognize that statistical analysis of historical crash data may not be the only way to think about the future relationship between vehicle mass and safety, we also recognize that other assessment methods are also subject to uncertainties, which makes statistical analysis of historical data an important starting point if employed mindfully and recognized for how it can be useful and what its limitations may be.

NHTSA undertook the independent review of st atistical studies and held the mass-safety workshop in February 2011 in order to help the agencies sort through the ongoing debates over what statistical analysis of historical data is actually telling us. Previously, the agencies have
assumed that differences in results were due in part to inconsistent databases; by creating the updated common database and making it publicly av ailable, we are hopeful that that aspect of the problem has been solved, and moreover, the UMTRI review suggested that differences in data were probably less significant than the agencies may have thought. The agencies also more recently concluded, in the MY 2012-2016 fina l rule, that multicollinearity was likely a significant risk in statistical analys is of historical crash data, that could lead to different results. The agencies will continue to monitor issues with multicollinearity in our analyses, and hope that
outside researchers will do the same. And finall y, based on the findings of the independent review, the agencies continue to be confident that Kahane’s analysis is the one of the best for purposes of analyzing potential safety effects of future CAFE and GHG standards. UMTRI concluded that Kahane’s approach is valid, and Kahane has continued and refined that approach for the current analysis. The NHTSA 2011 statistical fatality report finds directionally similar but less statistically significant relationships between vehicle mass, size, and footprint, as discussedSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 169 of 768 above. Based on these findings, the agencies believe that in the future, fatalities due to mass
reduction will be best reduced if mass reduction is concentrated in the heaviest vehicles. NHTSA considers part of the reason that more recen t historical data shows a dampened effect in the relationship between mass reduction and safety is that all vehicles, including traditionally lighter ones, grew heavier during that timeframe (2000s). As lighter vehicles become more prevalent in the fleet again over the next decade, it is possible (although certainly not inevitable) that the trend could strengthen again and that future updates to the common database may show that. Both agencies agree that there are several identifiable safety trends already in place or expected to occur in the foreseeable futures that are not accounted for in the study, since they
were not in effect at the time that the vehicles in question were built. For example, there are two important new safety standards that have alread y been issued and will be phasing in after MY 2008. Federal Motor Vehicle Safety Standa rd No. 126 (49 CFR § 571.126) will require electronic stability control in all new vehicles by MY 2012, and the upgrade to Federal Motor Vehicle Safety Standard No. 214 (Side Impact Protection, 49 CFR § 571.214) will likely result in all new vehicles being equipped with head-cur tain air bags by MY 2014. Additionally, we anticipate continued improvements in driver (and passenger) behavior, such as higher safety belt use rates. All of these may tend to reduce the ab solute number of fatalities. On the other hand, as crash avoidance technology improves, statistical analysis of (future) historical data may be complicated by a lower population of crashes, and different crash effects that may begin to trend as those technologies become more widespread in the fleet. In summary, the agencies have relied on the coefficients in the Kahane 2011 study for estimating the potential safety effects of the proposed CAFE and GHG standards for MYs 2017-2025, based on our assumptions regarding the amount mass reduction could be used to meet the standards in a cost-effective way. Section E below discusses the methodology used by the agen cies in more detail; while the results of the safety effects analysis are less significant than the results in the MY 2012-2016 final rule, the agencies still believe that any statistically signi ficant results warrant caref ul consideration of the assumptions about appropriate levels of mass reduction on which to base future CAFE and GHG standards, and have acted accordingly in developing the proposed standards.

4. How do the agencies think technological solutions might affect the safety estimates indicated by the statistical analysis?

As mass reduction becomes a more important technology option for manufacturers in meeting future CAFE and GHG standards, manufacturers will invest more and more resources in developing increasingly lightweight vehicle design s that meet their needs for manufacturability and the public’s need for vehicles that are safe, useful, affordable, and enjoyable to drive. There are many different ways to reduce mass, as discussed in Chapter 3 of this TSD and in Sections II, III, and IV of the preamble, and a considerable amount of information is available today on lightweight vehicle designs currently in production and that may be able to be put into production in the rulemaking timeframe. Discussion of lightweight material designs from NHTSA’s workshop is presented below.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 170 of 768 Besides “lightweighting” technologies themselves, though, there are a number of considerations when attempting to evaluate how future technological developments might affect the safety estimates indicated by the statistical analysis. As discussed in the first part of this chapter, for example, if reducing mass makes a vehicle less able to protect itself and its occupants in crashes, there are ways to redesign the vehicle to help it protect itself better – through improved distribution of crash pulse ener gy, through making the vehicle stiffer, etc. – but these techniques can sometimes cause other problems, such as increased crash forces on vehicle occupants that have to be mitigated, or greater aggressivity against other vehicles in crashes. Manufacturers may develop new and better restraints – air bags, seat belts, etc. – to protect occupants in lighter vehicles in crashes, but NHTSA’s current safety standards for restraint systems are designed based on the current fleet, not the yet-unknown future fleet. The agency will need to monitor trends in the crash data to see whether changes to the safety standards (or new safety standards) become necessary. Manufacturers are also increasingly employing a variety of crash avoidance technologi es – ABS, electronic stability control (ESC), lane departure warnings, vehicle-to-vehicle (“V2V”) communications – that, as they become more prevalent in the fleet, are expected to reduce the overall population of crashes. Until these vehicles are present in the fleet in greater number s, however, it will be difficult to assess whether these technologies can mitigate the observed relationship between vehicle mass and safety in the historical data, or whether for the crashes that remain and the relationship also persists.

The agencies and independent researchers have several vehicle level projects to determine the maximum potential for mass reduction in the MY 2017-2021 timeframe by using
advanced materials and improved designs while continuing to meeting safety regulations and maintaining functionality of vehi cles, and one study that will inve stigate the effects of resultant designs on fleet safety:

A. NHTSA has awarded a contract to Electricore, with EDAG and George Washington University (GWU) as subcontractors, to study the maximum feasible amount mass reduction for a mid-size car – specifically, a Honda Accord. The study tears down a MY 2011 Honda Accord, studies each component and sub-system, and then redesigns each component and sub-system trying to maximize the amount of mass reduction with technologies that are considered feasible for 200,000 units per year production volume during the time frame of this rulemaking. Electricore and its sub-contractors are consulting industry leaders and experts for each component and sub-system when deciding which technologies are feasible. Electricore and its sub-contractors are also building detailed CAD/CAE/powertrain models to validate vehicle safety, stiffness, NVH, durability, drivability and powertrain performance. For OEM-supplied parts, a detailed cost model is being built based on a Technical Cost Modeling (TCM) approach developed by the Massachusetts Institute of Technolo gy (MIT) Materials Systems Laboratory’s research 189 for estimating the manufacturing costs of OEM parts. The cost will be broken

189 Frank Field, Randolph Kirchain and Richard Roth, Pr ocess cost modeling: Strategic engineering and economic evaluation of materials technologies, JOM Journal of th e Minerals, Metals and Materials Society, Volume 59,Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 171 of 768 down into each of the operations involved in the manufacturing, such as for a sheet metal part production by starting from blanking the steel coil, until the final operation to fabricate the component. Total costs are then categorized into fixed cost, such as tooling, equipment, and facilities; and variable co sts such as labor, material, energy, and maintenance. These costs will be assessed th rough an interactive process between the product designer, manufacturing engineers and cost analysts. For OEM-purchased parts, the cost will be estimated by consultation with experienced cost analysts and Tier 1 system suppliers. This study will help to info rm the agencies about the feasible amount of mass reduction and the cost associated with it. NHTSA intends to have this study completed and peer reviewed before July 2012, in time for it to play an integral role in informing the final rule.

B. EPA has awarded a contract to FEV, with EDAG and Monroe & Associates, Inc. as subcontractors, to study the maximum feasible amount of mass reduction for a mid-size CUV (cross over vehicle) specifically, a Toyota Venza. The study tears down a MY 2010 vehicle, studies each component and sub-system, and then redesigns each component and sub-system trying to maximize the amount of mass reduction with technologies that are considered feasible for high volume production for a 2017 MY vehicle. FEV in coordination with EDAG is building detailed CAD/CAE/powertrain models to validate vehicle safety, stiffness, NVH, durability, drivability and powertrain performance to assess the safety of this new design. This study builds upon the low development (20% mass reduction) design in the 2010 Lotus En gineering study “An Assessment of Mass Reduction Opportunities for a 2017-2020 Model Year Vehicle Program”. This study will undergo a peer review. EPA intends to have this study completed and peer reviewed before July 2012, in time for it to play an integral role in informing the final rule.

C. California Air Resources Board (CARB) has awarded a contract to Lotus Engineering, to study the maximum feasible amount mass reduction for a mid-size CUV (cross over vehicle) specifically, a Toyota Venza. Th e study will concentrate on the Body-in-White and closures in the high development design (40% mass reduction) in the Lotus Engineering study cited above. The study wi ll provide an updated design with crash simulation, detailed costing and manufacturin g feasibility of these two systems for a MY2020 high volume production vehicle. Th is study will undergo a peer review. CARB intends to have this study completed and peer reviewed before July 2012, in time for it to play an integral role in informing the final rule.

D. NHTSA has contracted with GWU to build a fleet simulation model to study the impact and relationship of light-weighted vehicle design and injuries and fatalities. This study will also include an evaluation of potential c ountermeasures to reduce any safety concerns associated with lightweight vehicles. NHTS A will include three light-weighted vehicle designs in this study: the one from Electricore/EDAG/GWU mentioned above, one from Lotus Engineering funded by California Air Resource Board for the second phase of the study, evaluating mass reduction levels around 35 percent of total vehicle mass, and two funded by EPA and the International Council on Clean Transportation (ICCT). This study

Number 10, 21-32. Available at http://msl.mit.edu/pubs/docs/Field_Kirch ainCM_StratEvalMatls.pdf (last accessed Aug. 22, 2011).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 172 of 768 will help to inform th e agencies about the possible safe ty implications for light-weighted vehicle designs and the appropriate counter-measures, 190 if applicable, for these designs, as well as the feasible amounts of mass reduction. All of these analyses are expected to be finished and peer-reviewed before July 2012, in time to inform the final rule.

a. NHTSA workshop on vehicle mass, size and safety

As stated above, in section C.2, on February 25, 2011, NHTSA hosted a workshop on mass reduction, vehicle size, and fleet safety at the Headquarters of the US Department of Transportation in Washington, DC. The purpose of the workshop was to provide the agencies with a broad understanding of current research in the field and provide stakeholders and the public with an opportunity to weigh in on this issue. The agencies also created a public docket to receive comments from interested parties that were unable to attend. The presentations were divided into two sessions that addressed the two expansive sets of issues. The first session explored statistical evidence of the roles of mass and size on safety, and is summarized in section C.2. The second session explored the engineer ing realities of structural crashworthiness, occupant injury and advanced vehicle design, and is summarized here. The speakers in the second session included Stephen Summers of NHTSA, Gregg Peterson of Lotus Engineering, Koichi Kamiji of Honda, John German of the International Council on Clean Transportation (ICCT), Scott Schmidt of the Alli ance of Automobile Manufacturer s, Guy Nusholtz of Chrysler, and Frank Field of the Massachusetts Institute of Technology.

The second session explored what degree of we ight reduction and occupant protection are feasible from technical, economic, and engineerin g perspectives. Field em phasized that technical feasibility alone does not constitute feasibility in the context of vehicle mass reduction. Sufficient material production capacity and viable manufacturing processes are essential to economic feasibility. Both Kamiji and German noted that both good mate rials and good designs will be necessary to reduce fatalities. For exampl e, German cited the examples of hexagonally
structured aluminum columns such as used in th e Honda Insight can improve crash absorption at lower mass and of high-strength steel componen ts can both reduce weight and improve safety. Kamiji made the point that widespread mass reduction will reduce the kinetic energy of all crashes which should produce some beneficial effect.

Summers described NHTSA’s plans for a model to estimate fleet wide safety effects based on an array of vehicle-to-vehicle computational crash simulations of current and anticipated vehicle designs. In particular, three computational models of lightweight vehicles are under development. They are based on current vehicles that have been modified by significant mass reduction methodologies. The most ambitious was the “high development” derivative of a Toyota Venza developed by Lotus Engineering and discussed by Mr. Peterson. Its structure currently contains about 75% aluminum, 12% magnesium, 8% steel, and 5% advanced

190 Countermeasures could potentially involve improved front end structure, knee bags, seat ramps, buckle pretensioners, and others.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 173 of 768 composites. Peterson expressed confidence that the design had the pote ntial to meet federal safety standards. Nusholtz emphasized that computational crash simulations involving more advanced materials were less reliable than those involving traditional metals such as aluminum
and steel.

Nusholtz presented a revised data-based fleet safety model in which important vehicle parameters were modeled based on trends from current NCAP crash tests. For example, crash pulses and potential intrusion for a particular size vehicle were based on existing distributions. Average occupant deceleration was used to estimate injury risk. Through a range of simulations of modified vehicle fleets, he was able to estima te the net effects of various design strategies for lighter weight vehicles, such as various scaling approaches for vehicle stiffness or intrusion. The approaches were selected based on engineering requirements for modified vehicles. Transition from the current fleet was considered. He concluded that protocols resulting in safer transitions (e.g., removing more mass from heavier vehicles with appropriate stiffness scaling according to a 3/2 power law) were not generally consistent wi th those that provide the greatest reduction in GHG production.

German discussed several important points on the future of mass reduction. Similar to
Kahane’s discussion of the difficulties of isolatin g the impact of weight reduction, German stated that other important variables, such as vehicle design and compatibility factors, must be held constant in order for size or weight impacts to be quantified in statistical analyses and presented data that compared to driver, driving influences, and vehicle design influences showing safety impacts of size and weight are small and difficult to quantify. He noted that several scenarios, such as rollovers, greatly favored the occupants of smaller and lighter cars once a crash occurred. He pointed out that if size and design are mainta ined, lower weight should translate into a lower total crash force. He thought that advanced material designs have the potential to “decouple” vehicle size and weight and felt that design efficien cy and driver attributes may start to dominate size and weight issues in future vehicle models to the point “that neither size nor weight [will have] a whole lot of impact on the overall safety of the overall fleet when you consider all the different type of crashes involved.”

Other presenters noted industry’s perspective of the effect of incentivizing weight reduction. Field highlighted the complexity of institutional changes that may be necessitated by weight reduction, including redesign of ma terial and component supply chains and manufacturing infrastructure. Schmidt described an industry perspective on the complicated decisions that must be made in the face of regul atory change, such as evaluating goals, gains, and timing.

Field and Schmidt noted that the introduction of technical innovations is generally an innate development process involv ing both tactical and strategic considerations that balance
desired vehicle attributes with economic and t echnical risk. In the absence of challenging regulatory requirements, a substantial technology change is often implemented in stages, startingSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 174 of 768 with lower volume pilot production before a commitment is made to the infrastructure and supply chain modifications necessary for inclusi on on a high-volume production model. Joining, damage characterization, durability, repair, and significant uncertainty in final component costs are also concerns. Thus, for example, the wide spread implementation of high-volume composite or magnesium structures might be problematic in the short or medium term when compared to relatively transparent aluminum or high strength steel implemen tations. Regulatory changes will affect how these tradeoffs are made and these risks are managed.

Koichi Kamiji presented data showing in in creased use of high strength steel in their Honda product line to reduced vehicle mass and increase vehicle safety. He stated that mass reduction is clearly a benefit for 42% of all fatal crashes because absolute energy is reduced. He followed up with slides showi ng the application of intelligent design can improve safety even when controlling for weight and size.

A philosophical theme developed that explor ed the ethics of consciously allowing the
total societal harm associated with mass reduc tion to approach the anticipated benefits of enhanced safety technolog ies. Lund conceded that there may eventually be specific fatalities that would not have occurred without downsizing, bu t asserted “Those of us whose mission is highway safety will have to adapt our strategies to the reality cr eated by consumer choices,” but
that “We will be ok if we let data on what work s – not wishful thinking – guide our strategies.”

5. How have the agencies estimated safety effects for the proposed standards?

a. What was the agencies’ methodology for estimating safety effects for the proposed standards?

As explained above, the agencies consider the 2011 statistical analysis of historical crash data by Kahane of NHTSA to represent our best estimates of the potential relationship between mass reduction and fatality increases in the future fleet. This section discusses how the agencies used NHTSA’s 2011 analysis to calculate specific estimates of safety effects of the proposed standards, based on the analysis of how much mass reduction manufacturers might use to meet the proposed standards.

Neither the proposed CAFE/GHG standards nor the agencies’ analysis mandates mass reduction, or mandates that mass reduction occur in any specific manner. However, mass reduction is one of the technology applications available to the manufacturers and a degree of mass reduction is used by the both agencies ’ models to determine the capabilities of manufacturers and to predict both cost and fuel consumption/emissions impacts of improved CAFE/GHG standards. We note that the mass reduction amounts in the agencies’ analysis for this rulemaking were chosen based both on our assumptions about how much is technologicallyfeasible, and to find a way by which manufacturers could comply with the standards in a safetyneutral manner. While we are confident that manufacturers will build safe vehicles, we cannotSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 175 of 768 predict with certainty that they will choose to re duce mass in exactly the ways that the agencies have analyzed in response to the standards. In the event that manufacturers ultimately choose to reduce mass and/or footprint in ways not analyzed by the agencies, the safety effects of the rulemaking may likely differ from the agencies’ estimates.

NHTSA utilized the study relationships between weight and safety, expressed as percentage increases in fatalities per 100-pound weight reduction, and examined the weight effects assumed in this rulemaking analysis. However, as mentioned previously, there are several identifiable safety trends already in place or expected to occur in the foreseeable future that are not accounted for in the study. For example, the two important new safety standards that were discussed above for electronic stability contro l and head curtain airbags, have already been issued and will be phasing in after MY 20 08. Additionally, we anticipate continued improvements in driver (and passenger) behavior, such as higher safety belt use rates. All of
these will tend to reduce the absolute number of fatalities. The agency estimated the overall change in calculated fatalities by calendar year after adjusting for ESC, Side Impact Protection, and other Federal safety standards and behavioral changes projected through this time period. Thus, while the percentage increases in NHTSA (2011) were applied, the reduced base has
resulted in smaller absolute in creases than those that were predicted in the 2010 report.

NHTSA examined the impacts of identifiable safety trends over the lifetime of the vehicles produced in each model year. An estimate of these impacts was contained in a previous
agency report. 191 The impacts were estimated on a year-by-year basis, but could be examined in
a combined fashion. NHTSA assumed that the safety trends will resu lt in a reduction in the target population of fatalities from which the weight impacts are derived. Using this method, we found a 12.6 percent reduction in fatality levels between 2007 and 2020 for the combination of safety standards and behavioral changes anticipated (ESC, head-curtain air bags, and increase belt use). Since the same safety standards are taking effect in the same years, the estimates derived from applying NHTSA fatality percentage s to a baseline of 2007 fatalities were thus multiplied by 0.874 to account for changes that NHTSA believes will take place in passenger car and light truck safety between the 2007 baseline on-road fleet used for this particular safety analysis and year 2025.

After applying these percentage increases to the estimated weight reductions per vehicle size by model year assumed in the Volpe model, Table 0-15 shows the results of NHTSA’s

ls technologies, JOM Journal of the Minerals, Metals and Materials Society, Volume 59, Number 10, 21-32. Available at http://msl.mit.edu/pubs/docs/Field_KirchainCM_St ratEvalMatls.pdf (last accessed Aug. 22, 2011).

191 Countermeasures could potentially involve improved front end structure, knee bags, seat ramps, buckle pretensioners, and others.

191 Blincoe, L. and Shankar, U, “The Impact of Safety Standards and Behavioral Trends on Motor Vehicle Fatality Rates,” DOT HS 810 777, January 2007. See Table 4 comparing 2020 to 2007 (37,906/43,363 = 12.6% reduction (1-.126 = .874). Since 2008 was a recession year, it does not seem appropriate to use that as a baseline. We believe this same ratio should hold for this analysis which should compare 2025 to 2008. Thus, we are inclined to continue to use the same ration.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 176 of 768 safety analysis separately for each model year. 192 These are estimated increases or decreases in fatalities over the lifetime of the model year fleet. A positive number means that fatalities are projected to increase, a negative number ( ) means that fatalities are projected to decrease. The results are significantly affected by the assump tions put into the Volpe model to take more weight out of the heavy LTVs, CUVs, and minivans than out of other vehicles. As the negative coefficients only appear for LTVs greater than 4, 594 lbs., CUVs, and minivans, a statistically improvement in safety can only occur if more weight is taken out of these vehicles than passenger cars or smaller light trucks. Combining passenger car and light truck safety estimates for the proposed standards results in an increase in fatalities over the lifetime of the nine model years of MY 2017-2025 of 76 fatalities, broken up into an increase of 193 fatalities in passenger cars and 117 decrease in fatalities in light trucks . NHTSA also analyzed the results for different regulatory alternatives in Chapter IX of its PRIA; the differ ence in the results by alternative depends upon how much weight reduction is used in that alternative and the types and sizes of vehicles that the weight reduction applies to.

Table 0-15 NHTSA Calculated Mass-Safety-Related Fatality Impacts of the Proposed Standards over the Lifetime of the Vehicles Produced in each Model Year

MY 2017 MY 2018 MY 2019 MY 2020 MY 2021 MY 2022 MY 2023 MY 2024 MY 2025 Total

Passenger

cars 6 11 29 27 26 25 25 21 22 193

Light trucks (5) (14) 2 (23) (17) (22) (18) (13) (7) (117)

Total 1 (3) 31 (4) 9 3 7 8 15 76

Using the same coefficients from the 2011 Kahane study, EPA used the OMEGA model to conduct a similar analysis. After applying these percentage increases to the estimated weight reductions per vehicle size by model year assumed in the Omega model, Table 0-16 shows the results of EPA’s safety analysis separately for each model year. These are estimated increases or
decreases in fatalities over the lifetime of th e model year fleet. A positive number means that fatalities are projected to incr ease; a negative number means th at fatalities are projected to decrease. For details, see the EPA RIA Chapter 3.

Table 0-16 EPA Calculated Mass-Safety-Related Fatality Impacts of the Proposed Standards over the Lifetime of the Vehicles Produced in each Model Year

192 NHTSA has changed the definitions of a passenger car and light truck for fuel economy purposes between the time of the Kahane 2003 analysis and this final rule. Abou t 1.4 million 2 wheel drive SUVs have been redefined as passenger cars instead of light trucks. The Kahane 2011 anal ysis continues with the definitions used in the Kahane 2003 analysis. Thus, there are different definitions betw een Tables IX-1 and IX-2 (which use the old definitions) and Table IX-3 (which uses the new definitions).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 177 of 768 MY 2017 MY 2018 MY 2019 MY 2020 MY 2021 MY 2022 MY 2023 MY 2024 MY 2025 Total

Passenger

cars -3 -6 -9 -12 -16 7 31 56 83 131

Light trucks 0 -1 -1 -2 -3 -34 -66 -98 -131 -336

Total -3 -7 -10 -14 -18 -27 -35 -42 -48 -204

b. Why might the real-world effects be less than or greater than what the agencies
have calculated?

As discussed above the ways in which future technological advances could potentially mitigate the safety effects estimated for this rule making: lightweight vehicles could be designed to be both stronger and not more aggressive; rest raint systems could be improved to deal with higher crash pulses in lighter vehicles; crash avoidance technologies could reduce the number of overall crashes. As also stated above, however, while we are confident that manufacturers will build safe vehicles, it will be difficult for bo th the agencies and the industry to know with certainty ahead of time how crash trends will change in the future fleet as lightweighted vehicles become more prevalent. We will have to continue to monitor the crash data going forward.

Additionally, we note that the mass reduction amounts in the agencies’ analysis for this rulemaking were chosen based both on our assumptions about how much is technologicallyfeasible, and to find a way by which manufacturers could comply with the standards in a safetyneutral manner. Again, while we are confident that manufacturers will build safe vehicles, we cannot predict with certainty that they will choose to reduce mass in exactly the ways that the agencies have analyzed in response to the standards. In the event that manufacturers ultimately choose to reduce mass and/or footprint in ways not analyzed by the agencies, the safety effects of the rulemaking may likely differ from the agencies’ estimates.

c. Do the agencies plan to make any changes in these estimates for the final rule?

As discussed above, the agencies have based our estimates of safety effects due to the proposed standards on Kahane’s 2011 report. That report is currently undergoing peer review and is docketed for public review; 193 the peer review comments and response to peer review comments, along with any revisions to the repor t in response to that review, will also be docketed there. Depending on the results of the peer review, our calculation of safety effects for

193 Kahane, C. J. (2011). “Relationships Between Fatal ity Risk, Mass, and Footprint in Model Year 2000-2007 Passenger Cars and LTVs,”, July 2011. The report is available in the NHTSA docket, NHTSA-2010-0152. You can
access the docket at http://www.regulations.gov/#!home by typing ‘NHTSA-2010-0152’ where it says “enter keyword or ID” and then clicking on “Search.”Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 178 of 768 the final rule will also be revised accordingly. The agencies will also consider any comments received to the proposed rule, and determine at that time whether and how our estimates should be changed in response to those comments. Additional studies published by the agencies or other independent researchers as previously di scussed will also be considered, along with any
other relevant information.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 179 of 768 III. EPA Proposal for MYs 2017-2025 Greenhouse Gas Vehicle Standards

A. Overview of EPA Rule

1. Introduction

Soon after the completion of the successful MY 2012-2016 rulemaking in May 2010, the President, with support from the auto manufacturers, requested that EPA and NHTSA work to extend the National Program to MY 2017-2025 light duty vehicles. The agencies were requested to develop “a coordinated national program under the CAA (Clean Air Act) and the EISA (Energy Independence and Security Act of 2007) to improve fuel efficiency and to reduce greenhouse gas emissions of passenger cars and light-duty trucks of model years 2017-2025.” 194
EPA’s proposal grows directly out of our work with NHTSA and CARB in developing such a continuation of the National Program. This prop osal provides important benefits to society and
consumers in the form of reduced emissions of greenhouse gases (GHGs), reduced consumption of oil, and fuel savings for consumers, all at reasonable costs. It provides industry with the important certainty and leadtime needed to implement the technology changes that will achieve these benefits, as part of a harmonized set of federal requirements. Acting now to address the
standards for MYs 2017-2025 will allow for the im portant continuation of the National Program that started with the 2012-2016 model years.

EPA is proposing GHG emissions standards for light-duty vehicles, light-duty trucks, and medium-duty passenger vehicles (hereafter light vehicles) for model years (MYs) 2017 through 2025. These vehicle categories, which include car s, sport utility vehicles, minivans, and pickup trucks used for personal transportation, are resp onsible for almost 60% of all U.S. transportation related greenhouse gas (GHG) emissions.

If finalized, this proposal would be the sec ond EPA rule to regulate light vehicle GHG emissions under the Clean Air Act (CAA), build ing upon the GHG emissions standards for MY 2012-2016 that were established in 2010, 195 and the third rule to regulate GHG emissions from the transportation sector. 196 Combined with the standards already in effect for MY 2012-2016, the proposed standards would result in MY 2025 light vehicles emitting approximately one-half
of the GHG emissions of MY 2011 vehicles and would represent the most significant federal action ever taken to reduce GHG emissions (and improve fuel economy) in the U.S.

From a societal standpoint, the proposed GHG emissions standards are projected to save
over 2 billion metric tons of GHG emissions and ove r 4 billion barrels of oil over the lifetimes of

194 The Presidential Memorandum is found at: http ://www.whitehouse.gov/the-press-office/presidentialmemorandum-regarding-fuel-efficiency-standards.

195 75 FR 25324 (May 7, 2010).

196 76 FR 57106 (September 15, 2011) established GHG emis sion standards for heavy-duty vehicles and engines for model years 2014-2018.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 180 of 768 those vehicles sold in MY 2017-2025. EPA estimates that fuel savings will far outweigh higher vehicle costs, and that the net benefits to soci ety will be in the range of $348 billion (at 7% discount rate) to $468 billion (3% discount) over the lifetimes of those vehicles sold in MY 2017-2025. Just in calendar year 2040 alone, after the on-road vehicle fleet has largely turned over to vehicles sold in MY 2025 and later, EP A projects GHG emissions savings of 486 million metric tons, oil savings of 2.77 million barrel s per day, and net benefits of $158 billion.

EPA estimates that these proposed standards will save consumers money. Higher costs for new technology, sales taxes, and insurance w ill add, on average in the first year, about $2100 for consumers who buy a new vehicle in MY 2025. But those consumers who drive their MY 2025 vehicle for its entire lifetime will save, on average, $4800 (7% discount rate) to $6200 (3% discount) in fuel savings, for a net lifetime savings of $2800-$4100. For those consumers who purchase their new MY 2025 vehicle with cash, the discounted fuel savings will offset the higher vehicle cost in 4.0-4.4 years, and fuel savings will continue for as long as the consumer owns the vehicle. Those consumers that buy a new vehicle with a 5-year loan will benefit from a monthly cash flow savings of $12 (or about $140 per year), on average, as the monthly fuel savings more than offsets the higher monthly payment due to the higher incremental vehicle cost.

The proposed standards are designed to allow full consumer choice, in that they are footprint-based, i.e., larger vehicles have higher absolute GHG emissions targets and smaller
vehicles have lower absolute GHG emissions ta rgets. While the GHG emissions targets do become more stringent each year, the emissions targets have been selected to allow compliance by vehicles of all sizes and with current levels of vehicle attributes such as utility, size, safety, and performance. Accordingly, these proposed standards are projected to allow consumers to choose from the same mix of vehicles that are currently in the marketplace.

Section I above provides a comprehensive overview of the joint EPA/NHTSA proposal, including the history and rationale for a National Program that allows manufacturers to build a single fleet of light vehicles that can satisfy a ll federal and state requirements for GHG emissions and fuel economy, the level and structure of the proposed GHG emissions and corporate average fuel economy (CAFE) standards, the compliance flexibilities proposed to be available to manufacturers, the mid-term technology review, a nd a summary of the costs and benefits of the GHG and CAFE standards based on a “model year lifetime analysis.”

In this Section III, EPA provides more deta iled information about EPA’s proposed GHG emissions standards. After providing an overvie w of key information in this section (III.A), EPA discusses the proposed standards (III.B); the vehicles covered by the standards, various compliance flexibilities available to manufacturers, and a mid-term review (III.C); the feasibility of the proposed standards (III.D); provisions for certification, compliance, and enforcement (III.E); the reductions in GHG emissions projected for the proposed standards and the associated effects of these reductions (III.F); the impact of the proposal on non-GHG emissions and theirSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 181 of 768 associated effects (III.G); the estimated cost , economic, and other impacts of the proposal (III.H); and various statutory and executive order issues (III.I).

2. Why is EPA Proposing this Rule?

a. Light Duty Vehicle Emissions Contribute to Greenhouse Gases and the Threat of Climate Change

Greenhouse gases (GHGs) are gases in the atmosphere that effectively trap some of the Earth’s heat that would otherwise escape to sp ace. GHGs are both naturally occurring and anthropogenic. The primary GHGs of concern that are directly emitted by human activities include carbon dioxide, methane, nitrous oxide, hydrofluorocarbons, perfluorocarbons, and
sulfur hexafluoride.

These gases, once emitted, remain in the atmosphere for decades to centuries. They become well mixed globally in the atmosphere and their concentrations accumulate when emissions exceed the rate at which natural processes remove GHGs from the atmosphere. The heating effect caused by the human-induced buildup of GHGs in the atmosphere is very likely the cause of most of the observed global warming over the last 50 years. The key effects of climate change observed to date and projected to occur in the future include, but are not limited to, more frequent and intense heat waves, more severe wildfires, degraded air quality, heavier and more frequent downpours and flooding, increased drought, greater sea level rise, more intense storms, harm to water resources, continued ocean acidification, harm to agriculture, and harm to wildlife and ecosystems. A more in depth explanation of observed and projected changes in GHGs and climate change, and the impact of climate change on health, society, and the
environment is included in Section III.F below.

Mobile sources represent a large and growi ng share of U.S. GHG emissions and include light-duty vehicles, light-duty trucks, medium duty passenger vehicles, heavy duty trucks, airplanes, railroads, marine vessels and a variety of other sources. In 2007, all mobile sources emitted 30% of all U.S. GHGs, and have been the source of the largest absolute increase in U.S. GHGs since 1990. Transportation sources, which do not include certain off highway sources such as farm and construction equipment, account for 27% of U.S. GHG emissions, and motor vehicles (CAA section 202(a)), which include light-duty vehicles, light-duty trucks, mediumduty passenger vehicles, heavy-duty trucks, buses, and motorcycles account for 23% of total U.S.

GHGs.

Light duty vehicles emit carbon dioxide, methane, nitrous oxide and hydrofluorocarbons. Carbon dioxide (CO2) is the end product of fossi l fuel combustion. During combustion, the
carbon stored in the fuels is oxidized and emitte d as CO2 and smaller amounts of other carbon compounds. Methane (CH4) emissions are a function of the methane content of the motor fuel, the amount of hydrocarbons passing uncombusted through the engine, and any post-combustionSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 182 of 768 control of hydrocarbon emissions (such as catal ytic converters). Nitrous oxide (N2O) (and nitrogen oxide (NOX)) emissions from vehicles an d their engines are closely related to air-fuel ratios, combustion temperatures, and the use of pollution control equipment. For example, some types of catalytic converters installed to reduce motor vehicle NOX, carbon monoxide (CO) and hydrocarbon (HC) emissions can promote the form ation of N2O. Hydrofluorocarbons (HFC) are progressively replacing chlorofluorocarbons (CFC ) and hydrochlorofluorocarbons (HCFC) in these vehicles’ cooling and refrigeration syst ems as CFCs and HCFCs are being phased out
under the Montreal Protocol and Title VI of the CAA. There are multiple emissions pathways for HFCs with emissions occurring during charging of cooling and refrigeration systems, during operations, and during decommissioning and disposal.

b. Basis for Action Under the Clean Air Act

Section 202(a)(1) of the Clean Air Act (CAA) states that ‘‘the Administrator shall by regulation prescribe (and from time to time revise) * * * standards applicable to the emission of any air pollutant from any class or classes of new motor vehicles * * *, which in his judgment cause, or contribute to, air pollution which may reasonably be anticipated to endanger public health or welfare.’’ The Administrator has found that the elevated concentrations of a group of six GHGs in the atmosphere may reasonably be anticipated to endanger public health and welfare, and that emissions of GHGs from new motor vehicles and new motor vehicle engines contribute to this air pollution.

As a result of these findings, section 202(a) requires EPA to issue standards applicable to emissions of that air pollutant, and authorizes EP A to revise them from time to time. This preamble describes the proposed revisions to the current standards to control emissions of CO2 and HFCs from new light-duty motor vehicles. 197 For further discussion of EPA’s authority under section 202(a), see Section I.D. of the preamble.

c. EPA’s Endangerment and Cause or Contribute Findings for Greenhouse Gases Under Section 202(a) of the Clean Air Act

On December 15, 2009, EPA published its findings that elevated atmospheric concentrations of GHGs are reasonably anticipated to endanger the public health and welfare of current and future generations, and that emissions of GHGs from new motor vehicles contribute to this air pollution. Further information on these findings may be found at 74 FR 66496 (December 15, 2009) and 75 FR 49566 (Aug. 13, 2010).

197 EPA is not proposing to amend the substantive standa rds adopted in the 2012-2016 light-duty vehicle rule for N2O and CH4, but is proposing revisions to the options that manufacturers have in meeting the N2O and CH4 standards, and to the timeframe for manufacturers to be gin measuring N2O emissions. See Section III.B below.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 183 of 768 3. What is EPA Proposing?

a. Light-Duty Vehicle, Light-Duty Truc k, and Medium-Duty Passenger Vehicle Greenhouse Gas Emission Standards and Projected Emissions Levels

EPA is proposing tailpipe carbon dioxide (CO2) standards for cars and light trucks based on the CO2 emissions-footprint curves for cars and light trucks that are shown above in Section
I.B.3 and below in Section III.B. These curves establish different CO 2 emissions targets for each unique car and truck footprint value. Generally, the larger the vehicle footprint, the higher the corresponding vehicle CO 2 emissions target. Generally, vehicle CO 2 emissions will be measured over the EPA city and highway tests. Under this proposal, various incentives and
credits are available for manufacturers to dem onstrate compliance with the standards. See Section I.B for a comprehensive overview of both the EPA CO2 emissions-footprint standard curves and the various compliance flexibilities that are proposed to be available to the manufacturers in meeting the EPA tailpipe CO2 standards.

EPA projects that the proposed tailpipe CO2 emissions-footprint curves would yield a fleetwide average light vehicle CO 2 emissions compliance target level in MY 2025 of 163 grams per mile, which would represent an average reduction of 35 percent relative to the projected average light vehicle CO 2 level in MY 2016. On average, car CO2 emissions would be reduced by about 5 percent per year, while light truck CO2 emissions would be reduced by about 3.5 percent per year from MY 2017 through 2021, and by about 5 percent per year from MY 2022 through 2025.

The following three tables, Table III-1 through Table III-3, summarize EPA’s projections of what the proposed standards would mean in terms of projected CO2 emissions reductions for passenger cars, light trucks, and the overall fleet combining passenger cars and light trucks for MY 2017-2025. It is important to emphasize that these projections are based on technical assumptions by EPA about various matters, including the mix of cars and trucks, as well as the mix of vehicle footprint values, in the fleet in varying years. It is possible that the actual CO2 emissions values will be either highe r or lower than the EPA projections.

In each of these tables, the column “Projected CO 2 Compliance Target” represents our projected fleetwide average CO 2 compliance target value based on the proposed CO 2 -footprint curve standards as well as the projected mixes of cars and trucks and vehicle footprint levels. This Compliance Target represents the projected fleetwide average of the projected standards for
the various manufacturers.

The column(s) under “Incentives” represents the emissions impact of the proposed multiplier incentive for EV/PHEV/FCVs and the proposed pickup truck incentives. These incentives allow manufacturers to meet their Compliance Targets with CO2 emissions levels slightly higher than they would otherwise have to be, but do not reflect actual real-world CO2Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 184 of 768 emissions reductions. As such they reduce the emissions reductions that the CO2 standards would be expected to achieve.

The column “Projected Achieved CO2” is the sum of the CO2 Compliance Target and the value(s) in the “Incentive” columns. This Achieved CO2 value is a better reflection of the CO2 emissions benefits of the standards, since it accounts for the incentive programs. One incentive that is not reflected in these tables is the 0 gram per mile compliance value for EV/PHEV/FCVs. The 0 gram per mile value accura tely reflects the tailpipe CO2 gram per mile achieved by these vehicles; however, the use of this fuel does impact the overall GHG reductions associated with the proposed standards due to fuel production and distri bution-related upstream GHG emissions which are projected to be greater than the upstream GHG emissions associated with gasoline from oil. The combined impact of the 0 gram per mile and multiplier incentive for EV/PHEV/FCVs on overall program GHG emissions is discussed in more detail below in
Section III.C.2.

The columns under “Credits” quantify the projected CO2 emissions credits that we project manufacturers will achieve through improvements in air conditioner refrigerants and efficiency. These credits reflect real world emissions reductions, so they do not raise the levels of the Achieved CO2 values, but they do allow manufacturers to comply with their compliance targets with 2-cycle test CO2 emissions values hi gher than otherwise. One other credit program that could similarly affect the 2-cycle CO2 values is the off-cycle credit program, but it is not included in this table due to the uncertainty in herent in projecting the future use of these technologies. The off-cycle credits, like A/C credits, reflect real world reductions, so they would not change the CO2 Achieved values.

The column “Projected 2-cycle CO2” is th e projected fleetwide 2-cycle CO2 emissions
values that manufacturers would have to achieve in order to be able to comply with the proposed standards. This value is the sum of the projected fleetwide credit, incentive, and Compliance Target values. 198

198 For MY 2016, the Temporary Leadtime Allowance Alternative Standards are available to manufacturers. In the MY 2012-2016 rule, we estimated the impact of this credit in MY 2016 to be 0.1 gram/mile. Due to the small magnitude, we have not included this in the following tables for the MY 2016 base year.Summary of Interagency Working Comments Received on Draftrule under EO 12866 review. Subject to further policyreview.Page185of768Table III-1 EPA Projections for Fleetwide Tailpipe Emissions Compliance with Proposed CO2Standards – PassengerCars (Grams per mile)Incentives (1)ProjectedAchievedCO2Credits (2)ModelYearProjectedCO2ComplianceTargetEV/PHEV/FCVMultiplierA/CRefrigerantA/CEfficiencyProjected2-cycleCO2(3)2016(base)225 -- 225 5.4 4.8 2352017 213 2.2 215 7.8 5.0 2282018 202 2.1 205 9.3 5.0 2192019 192 2.0 194 10.8 5.0 2102020 182 1.5 184 12.3 5.0 2012021 173 1.0 174 13.8 5.0 1932022 165 -- 165 13.8 5.0 1842023 158 -- 158 13.8 5.0 1772024 151 -- 151 13.8 5.0 1692025 144 -- 144 13.8 5.0 163(1)The one incentive not reflected in this table is the 0 gram per mile compliance value for EV/PHEV/FCVs. See text for explanation.(2)The one credit not reflected in this table is the off-cycle credit. See text for explanation.(3)For a projected 2-cycle fuel economy value, divide 8887 grams of CO2per gallon by the projected 2-cycle CO2emission value. EPA projects thatfleetwide real world CO2 emissions are approximately 25 percent higher, and fleetwide real world fuel economy is about 20 percent lower, than the 2-cycle values reflected in this table.Summary of Interagency Working Comments Received on Draftrule under EO 12866 review. Subject to further policyreview.Page186of768Table III-2EPA Projections for Fleetwide Tailpipe Emissions Compliance with Proposed CO2Standards – LightTrucks (Grams per mile)(1)The one incentive not reflected in this table is the 0 gram per mile compliance value for EV/PHEV/FCVs. See text for explanation.(2)The one credit not reflected in this table is the off-cycle credit. See text for explanation.(3)For a projected 2-cycle fuel economy value, divide 8887 grams of CO2per gallon by the projected 2-cycle CO2emission value. EPA projects thatfleetwide real world CO2 emissions are approximately 25 percent higher, and fleetwide real world fuel economy is about 20 percent lower, than the 2-cycle values reflected in this table.Incentives (1)ProjectedAchievedCO2Credits (2)ModelYearProjectedCO2ComplianceTargetEV/PHEV/FCVMultiplierPickupMildHEV + PerfPickupStrongHEV + PerfA/CRefrigerantA/CEfficiencyProjected2-cycleCO2(3)2016(base)297 -- -- -- 297 6.6 4.8 3092017 295 0.0 0.3 0.0 295 7.0 5.0 3072018 285 0.0 0.4 0.1 285 11.0 6.5 3032019 277 0.1 0.6 0.2 278 13.4 7.2 2992020 270 0.1 0.7 0.2 271 15.3 7.2 2932021 250 0.0 0.8 0.4 251 17.2 7.2 2752022 237 -- -- 0.5 238 17.2 7.2 2622023 225 -- -- 0.6 226 17.2 7.2 2502024 214 -- -- 0.6 214 17.2 7.2 2392025 203 -- -- 0.7 204 17.2 7.2 228Summary of Interagency Working Comments Received on Draftrule under EO 12866 review. Subject to further policyreview.Page187of768Table III-3 EPA Projections for Fleetwide Tailpipe Emissions Compliance with Proposed CO2Standards –Combined Cars and Trucks (Grams per mile)Incentives (1)ProjectedAchievedCO2Credits (2)ModelYearProjectedCO2ComplianceTargetEV/PHEV/FCVMultiplierPickupMildHEV + PerfPickupStrongHEV + PerfA/CRefrigerantA/CEfficiencyProjected2-cycleCO2(3)2016(base)252 -- -- -- 252 5.8 4.8 2632017 243 1.4 0.1 0.0 245 7.5 5.02572018 232 1.3 0.2 0.0 234 9.9 5.52492019 223 1.3 0.2 0.1 224 11.7 5.82422020 213 1.0 0.3 0.1 214 13.4 5.82342021 200 0.6 0.3 0.1 201 15.0 5.82222022 190 -- -- 0.2 190 15.0 5.82112023 181 -- -- 0.2 181 15.0 5.82022024 172 -- -- 0.2 172 14.9 5.71932025 163 -- -- 0.2 163.6 14.9 5.7184(1)The one incentive not reflected in this table is the 0 gramper mile compliance value for EV/PHEV/FCVs. See text forexplanation.(2)The one credit not reflected in this table is the off-cycle credit. See text for explanation.(3)For a projected 2-cycle fuel economyvalue, divide 8887 grams of CO2per gallon by the projected 2-cycle CO2emission value.EPA projects that fleetwide real world CO2 emissions are approximately 25 percent higher, and fleetwide real world fueleconomy is about 20 percentlower, than the 2-cycle values reflected in this table.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 188 of 768 As discussed both in Section I and later in this Section III, EPA either already has adopted or is proposing provisions for averaging, banking, and trading of credits, that allow annual credits for a manufacturer’s over-complia nce with its unique fleet-wide average standard, carry-forward and carry-backward of credits, the ability to transfer credits between a manufacturer’s car and truck fleets, and credit tr ading between manufacturers. EPA is proposing a one-time carry-forward of any credits such that any credits generated in MY 2010-2016 can be used through MY 2021. These provisions are not expected to change the emissions reductions achieved by the standards, but should significantly reduce the cost of achieving those reductions. The Tables above do not reflect the year to year impact of these provisions. For example, EPA expects that many manufacturers may generate credits by over complying with the standards for cars, and transfer such credits to its truck fleet. Table III-1 (cars) and Table III-2 (trucks) do not reflect such transfers. If on an industry wide basis more credits are transferred from cars to trucks than vice versa, you would expect to achie ve greater reductions from cars than reflected in Table III-1 (lower CO2 gm/miles values) and less re ductions from trucks than reflected in Table III-2 (higher CO2 gm/mile values). Credit transfers between cars and trucks would not be expected to change the results for the combined fleet, reflected in Table III-3.

The proposed rule would also exclude from coverage a limited set of vehicles: emergency and police vehicles, and vehicles manufactured by small businesses. As discussed in Section III.B below, these exclusions have very limited impact on the total GHG emissions reductions from the light-duty vehicle fleet. We also do not anticipate significant impacts on total GHG emissions reductions from the proposed provisions allowing small volume manufacturers to petition EPA for alternative standa rds. See Section III.B below.

b. Environmental and Economic Benefits and Costs of EPA’s Standards

i. Model Year Lifetime Analysis

Section I.C provides a comprehensive discussion of the projected benefits and costs associated with the proposed MY 2017-2025 GHG and CAFE standards based on a “model year lifetime” analysis, i.e., the benefits and costs a ssociated with the lifetime operation of the new vehicles sold in these nine model years. It is important to note that while the incremental vehicle
costs associated with MY 2017 vehicles will in fact occur in calendar year 2017, the benefits associated with MY 2017 vehicles will be sp lit among all the calendar years from 2017 through the calendar year during which the last MY 2017 vehicle would be retired.

Table III-4 provides a summary of the GHG emi ssions and oil savings associated with the lifetime operation of all the vehicles sold in each model year. Cumulatively, for the nine model years from 2017 through 2025, the proposed standards are projected to save over 2 billion metric
tons of GHG emissions and over 4 billion barrels of oil.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 189 of 768 Table III-5 provides a summary of the most important projected economic impacts of the proposed GHG emissions standards based on this model year lifetime analytical approach. These monetized dollar values are all discounted to the first year of each model year, then summed up across all model years. With a 3% discount rate, cumulative incremental vehicle technology cost for MY 2017-2025 vehicles is $1 33 billion, fuel savings is $468 billion, other monetized benefits are $133 billion, and program net benefits are projected to be $468 billion. Using a 7% discount rate, the projected program net benefits are $348 billion.

As discussed previously, EPA recognizes that some of these same benefits and costs are also attributable to the CAFE standard contained in this joint proposal, although the GHG program achieves greater reductions of both GHG emissions and petroleum. More details associated with this model year lifetime analysis of the proposed GHG standards are presented in
Sections III.F and III.H.Summary of Interagency Working Comments Received on Draftrule under EO 12866 review. Subject to further policyreview.Page190of768Table III-4 Summary of GHG Emissions and Oil Savings for Proposed CO2Standard Model YearLifetime AnalysisMY2017MY2018MY2019MY2020MY2021MY2022MY2023MY2024MY2025CumulativeMY 2017-2025GHG Savings (MMT) 31 75 115 160 233 289 340392 445 2,079Oil Savings (Billion Barrels) 0.06 0.14 0.22 0.30 0.45 0.57 0.69 0.80 0.92 4.15Table III-5 Summary of Key Projected Economic Impacts,on a Lifetime Present Value Basis, for Proposed CO2Standard (1) Model Year LifetimeAnalysis (Billions of 2009 dollars)3% Discount Rate 7% Discount RateIncremental Vehicle Technology Cost $133 $130Societal Fuel Savings (2) $468 $363Other Benefits $133 $115Program Net Benefits $468 $348(1)Present value discounts all values to the first year of each MY, then sums those present values across MYs, in 2009 dollars.(2)All fuel impacts are calculated with pre-tax fuel prices of $2.85 per gallon in calendar year 2017, rising to $3.18 per gallonin calendar year 2025, and $3.49 per gallon in calendar year2040, and electricity prices of $0.10 per kWh in 2017 and2025, and $0.11 per kWh in 2040, all in 2009 dollars.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 191 of 768 ii. Calendar Year Analysis

In addition to the model year lifetime analysis projections summarized above, EPA also performs a “calendar year” analysis that projects the environmental and economic impacts associated with the proposed tailpipe CO 2 standards during specific calendar years out to 2050. This calendar year approach reflects the timeframe when the benefits would be achieved and the costs incurred. Because the EPA tailpipe CO 2 emissions standards will remain in effect unless and until they are changed, the projected impacts in this calendar year analysis beyond calendar year 2025 reflect vehicles sold in model years after 2025 (e.g., most of the benefits in calendar year 2040 would be due to vehicles sold after MY 2025).

Table III-6 provides a summary of the most important projected benefits and costs of the proposed EPA GHG emissions standards based on this calendar year analysis. In calendar year 2025, EPA projects GHG savings of 152 million me tric tons and oil savings of 0.83 million barrels per day. These would grow to 580 million metric tons of GHG savings and 3.31 million barrels of oil per day by calendar year 2050. Program net benefits are projected to be $19.6 billion in calendar year 2025, growing to $218 billion in calendar year 2050. Program net benefits over the 34-year period from 2017 through 2050 are projected to have a net present value in 2012 of $654 billion (7% discount ra te) to $1.5 trillion (3% discount rate).

More details associated with this calendar y ear analysis of the proposed GHG standards are presented in Sections III.F and III.H.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 192 of 768 Table III-6 Summary of Key Projected Impacts for Proposed CO 2 Standard – Calendar Year (CY) Analysis (1)

CY 2017 CY 2020 CY 2025 CY 2030 CY 2040 CY 2050 CY 2017-2050 Net Present Value in 2012 GHG Savings (MMT per Year) 2.3 28 152 306 486 580 -- --

Oil Savings (Million Barrels per Year) 4.5 53.1 304 627 1,010 1,208 -- --

Oil Savings (Million Barrels per Day) 0.012 0.15 0.83 1.72 2.77 3.31 -- --

Incremental Vehicle Technology Cost (billions of 2009$) $2.0 $8.4 $34 $36 $40 $45 $545 $239

Societal Fuel Savings (billions of 2009$) (2) $0.56 $6.9 $42 $88 $151 $198 $1570 $601

Other Benefits (billions of 2009$) $0.15 $1.9 $12 $26 $47 $65 $485 $292

Program Net Benefits (billions of 2009$) (2) (3) -$1.29 $0.40 $20 $78 $158 $218 $1510 $654

(1) Values in columns 2 through 7 are undiscounted annual values, values in columns 8 and 9 are discounted to a net present value in 2012. (2) All fuel impacts are calculated with pre-tax fuel prices of $2.85 per gallon in calendar year 2017, rising to $3.18 per gallon in calendar year 2025, and $3.49 per gallon in calendar year 2040, and electricity prices of $0.10 per kWh in 2017 and 2025, and $0.11 per kWh in 2040, all in 2009 dollars. (3) Assuming the 3% average SCC value and other benefits of the proposed program not presented in this table.

iii. Consumer Analysis

The model year lifetime and calendar year analytical approaches discussed above aggregate the environmental and economic impacts across the nationwide light vehicle fleet. EPA has also projected the average impact of the proposed GHG standards on individual consumers who own and drive MY 2025 light vehicles over their lifetimes.

Table III-7 shows, on average, several key consumer impacts associated with the proposed tailpipe CO2 standard for MY 2025 vehicles. Some of these factors are dependent on the assumed discount factors, and this table uses the same 3% and 7% discount factors usedSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 193 of 768 throughout this preamble. EPA uses AEO2011 fuel price projections of $3.25 per gallon in calendar year 2017, rising to $3.54 per gallon in calendar year 2025 and $3.85 per gallon in calendar year 2040.

EPA projects that the new technology necessary to meet the proposed MY 2025 standard would add, on average, an extra $1950 to the st icker price of a new MY 2025 light-duty vehicle. Including higher vehicle sales taxes and first-year insurance costs, the projected incremental first-year cost to the consumer is about $2100 on average. The projected incremental lifetime vehicle cost to the consumer, reflecting higher insurance premiums over the life of the vehicle, is, on average, about $2200. For all of the consumers who drive MY 2025 light-duty vehicles, the proposed standards are projected to yield a net savings of $3000 (7% discount rate) to $4400 (3% discount) over the lifetime of the vehicle, as the discounted lifetime fuel savings of $5200- $6600 is 2.4 to 3 times greater than the $2200 incremental lifetime vehicle cost to the consumer.

Of course, many vehicles are owned by more than one consumer. The payback period and monthly cash flow approaches are two ways to evaluate the economic impact of the MY 2025 standard on those new car buyers who do not own the vehicle for its entire lifetime. Projected payback periods of 3.8-4.0 years means that, for a consumer that buys a new vehicle with cash, the discounted fuel savings for that consumer would more than offset the incremental lifetime vehicle cost in 4 years. If the consumer owns the vehicle beyond this payback period, the vehicle will save money for the consumer. Fo r a consumer that buys a new vehicle with a 5- year loan, the monthly cash flow savings of $15 (or about $180 per year) shows that the consumer would benefit immediately as the mont hly fuel savings more than offsets the higher monthly payment due to the higher incremental first-year vehicle cost.

The final entries in Table III-7 show the CO2 and oil savings that would be associated with the MY 2025 vehicles on average, both on a lifetime basis and in the first full year of operation. On average, a consumer who owns a MY 2025 vehicle for its entire lifetime is projected to emit 20 fewer metric tons of CO2 and consume 2200 fewer gallons of gasoline due to the proposed standards.Summary of Interagency Working Comments Received on Draftrule under EO 12866 review. Subject to further policyreview.Page194of768Table III-7 Summary of Key Projected Consumer Impacts for Proposed MY 2025 CO2Standard (1) (2)3% Discount Rate 7% Discount RateIncremental Vehicle Technology Cost $1950Incremental First-Year Vehicle Cost to Consumer (3) $2100Incremental Lifetime Vehicle Cost to Consumer (4) $2200 $2200Lifetime Consumer Fuel Savings (5) $6600 $5200Lifetime Consumer Net Savings (6) $4400 $3000Payback Period for Cash Purchase (years) 3.8 4.0Monthly Cash Flow Savings Based on 5-Year Loan $11Annual Cash Flow Savings Based on 5-Year Loan $130First Year CO2Savings (Metric Tons) (7) 1.6Lifetime CO2Savings (Metric Tons) (7) 20First Year Gasoline/Oil Savings (Gallons) (7) 180Lifetime Gasoline/Oil Savings (Gallons) (7) 2200(1)Average impact of all MY 2025 light vehicles, excluding rebound effect.(2)Most values have been rounded to two significant digits in this summary table and therefore may be slightly different thantables elsewhere that report valuesto three or four significant digits.(3)Incremental First-Year Vehicle Cost to Consumer includesthe incremental vehicle technology cost, a 5.3% averagenationwide sales tax, and a 1.85% increase in first-year insurance premiums.(4)Incremental Lifetime Vehicle Cost to Consumer includesthe incremental vehicle technology cost, a 5.3% averagenationwide sales tax, and the discounted cost associated with incremental lifetime insurance premiums.(5)All fuel impacts are calculated with fuel prices, including fueltaxes, of $3.25 per gallon in calendar year 2017, rising to$3.54 per gallon in calendar year 2025, and $3.85 per gallon incalendar year 2040, and electricity prices of $0.10 per kWhin 2017 and 2025, and $0.11 per kWh in 2040, all in 2009 dollars.Summary of Interagency Working Comments Received on Draftrule under EO 12866 review. Subject to further policyreview.Page195of768(6)Lifetime Consumer Fuel Savings minus Incremental Lifetime Vehicle Cost to Consumer.(7)CO2and gasoline savings reflect vehicletailpipe-only and do not include CO2and oil savings associated with fuelproduction and distribution.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 196 of 768 4. Basis for the GHG Standards under Section 202(a)

EPA has significant discretion under section 202(a) of the Act in how to structure the standards that apply to the emission of the air pollutant at issue here, the aggregate group of six GHGs, as well as to the content of such standards. See generally 74 FR at 49464-65. EPA statutory authority under section 202(a) (1) of the Clean Air Act (CAA) is discussed in more detail in Section I.D of the preamble. In this rulemaking, EPA is proposing a CO 2 tailpipe emissions standard that provides for credits based on reductions of HFCs, as the appropriate way to issue standards applicable to emissions of the single air pollutant, the aggregate group of six GHGs. EPA is not proposing to change the methane and nitrous oxide standards already in place (although EPA is proposing certain changes to the compliance mechanisms for these standards as explained in Section III.B below). EPA is no t setting any standards for perfluorocarbons or sulfur hexafluoride, as they are not emitted by motor vehicles. The following is a summary of the basis for the proposed GHG standards under s ection 202(a), which is discussed in more detail in the following portions of Section III.

With respect to CO 2 and HFCs, EPA is proposing attribute-based light-duty car and truck standards that achieve large and important emissions reductions of GHGs. EPA has evaluated the technological feasibility of the standards, and the information and analysis performed by
EPA indicates that these standards are feasible in the lead time provided. EPA and NHTSA have carefully evaluated the effectiveness of individual technologies as well as the interactions when technologies are combined. EPA projects that ma nufacturers will be able to meet the standards by employing a wide variety of technologies that are already commercially available. EPA’s analysis also takes into account certain flexibilities that will facilitate compliance. These flexibilities include averaging, banking, and trading of various types of credits. For a few very small volume manufacturers, EPA is proposing to allow manufacturers to petition for alternative
standards.

EPA, as a part of its joint technology an alysis with NHTSA, has performed what we believe is the most comprehensive federal vehicle technology analysis in history. We carefully
considered the cost to manufacturers of meetin g the standards, estimating piece costs for all candidate technologies, direct manufacturing cost s, cost markups to account for manufacturers’ indirect costs, and manufacturer cost reductio ns attributable to learning. In estimating manufacturer costs, EPA took into account manuf acturers’ own practices such as making major changes to vehicle technology packages during a planned redesign cycle. EPA then projectedthe average cost across the industry to employ this technology, as well as manufacturer-bymanufacturer costs. EPA considers the per vehicle co sts estimated by this analysis to be within a reasonable range in light of the emissions reductions and benefits achieved. EPA projects, for example, that the fuel savings over the life of th e vehicles will more than offset the increase in cost associated with the technology used to meet the standards. As explained in Section III.D.6 below, EPA has also investigated potential sta ndards both more and less stringent than thoseSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 197 of 768 being proposed and has rejected them. Less stringent standards would forego emission reductions which are feasible, cost effective, and cost feasible, with short consumer payback periods. More stringent standards would not on ly be more costly, but would force technology penetration rates of certain technologies (such as strong hybrids for vehicles that tow) past a point where the technology is feasible in the available lead time (in the early years of the standard) or acceptable to consumers.

EPA has also evaluated the impacts of these standards with respect to reductions in GHGs and reductions in oil usage. For the lifetime of the model year 2017-2025 vehicles we estimate GHG reductions of approximately 2 billio n metric tons and fuel reductions of about 4 billion barrels of oil. These are important and significant reductions. EPA has also analyzed a variety of other impacts of the standards, ranging from the standards’ effects on emissions of non-GHG pollutants, impacts on noise, energy, sa fety and congestion. EPA has also quantified the cost and benefits of the standards, to the ex tent practicable. Our analysis to date indicates that the overall quantified benefits of the standards far outweigh the projected costs. We estimate the total net social benefits (lifetime pr esent value discounted to the first year of the model year) over the life of MY 2017-2025 vehicles to be $468 billion with a 3% discount rate and $348 billion with a 7% discount rate.

Under section 202(a), EPA is called upon to set standards that provide adequate lead-time for the development and application of technology to meet the standards. EPA’s standards satisfy this requirement given the present existence of the technologies on which the proposed rule is predicated and the substantial lead ti mes afforded under the proposal (which by MY2025 allow for multiple vehicle redesign cycles and so affords opportunities for adding technologies in the most cost efficient manner, see 75 FR at 25407) . In setting the standards, EPA is called upon to weigh and balance various factors, and to exercise judgment in setting standards that are a reasonable balance of the relevant factors. In this case, EPA has considered many factors, such as cost, impacts on emissions (both GHG and non-GHG), impacts on oil conservation, impacts on noise, energy, safety, and other factors, and has where practicable quantified the costs and benefits of the proposed rule. In summary, given the technical feasibility of the standard, the cost per vehicle in light of the savings in fuel costs over the lifetime of the vehicle, the very significant reductions in emissions and in oil us age, and the significantly greater quantified benefits compared to quantified costs, EPA is confident that the standards are an appropriate and reasonable balance of the factors to consider under section 202(a). See Husqvarna AB v. EPA

, 254 F. 3d 195, 200 (D.C. Cir. 2001) (great discreti on to balance statutory factors in considering level of technology-based standard, and statutory requirement “to [give appropriate] consideration to the cost of applying ... technol ogy” does not mandate a specific method of cost analysis); see also Hercules Inc. v. EPA , 598 F. 2d 91, 106 (D.C. Cir. 1978) (“In reviewing a numerical standard we must ask whether the agency’s numbers are within a zone of reasonableness, not whether its numbers are precisely right”); Permian Basin Area Rate Cases

, 390 U.S. 747, 797 (1968) (same); Federal Power Commission v. Conway Corp. , 426 U.S. 271,Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 198 of 768 278 (1976) (same); Exxon Mobil Gas Marketing Co. v. FERC , 297 F. 3d 1071, 1084 (D.C. Cir. 2002) (same).

EPA recognizes that most of the technologies that we are considering for purposes of setting standards under section 202( a) are commercially available and already being utilized to a limited extent across the fleet, or will soon be commercialized by one or more major manufacturers. The vast majority of the emission reductions that would result from this rule
would result from the increased use of these tec hnologies. EPA also recognizes that this rule would enhance the development and commercialization of more advanced technologies, such as PHEVs and EVs and strong hybrids as well. In th is technological context, there is no clear cut line that indicates that only one projection of technology penetration could potentially be considered feasible for purposes of section 202(a), or only one standard that could potentially be considered a reasonable balancing of the factors relevant under section 202(a). EPA therefore evaluated several alternative standards, some more stringent than the promulgated standards and some less stringent.

See Section III.D.6 for EPA’s analysis of alternative GHG emissions standards.

5. Other Related EPA Motor Vehicle Regulations

a. EPA’s Recent Heavy-Duty GHG Emissions Rulemaking

EPA and NHTSA recently conducted a joint rulemaking to establish a comprehensive Heavy-Duty National Program that will reduce gr eenhouse gas emissions and fuel consumption for on-road heavy-duty vehicles beginning in MY 2014 (76 FR 57106 (September 15, 2011)). EPA’s final carbon dioxide (CO 2 ), nitrous oxide (N 2 O), and methane (CH 4 ) emissions standards, along with NHTSA’s final fuel consumption standards, are tailored to each of three regulatory categories of heavy-duty vehicles: (1) Combina tion Tractors; (2) Heavy-duty Pickup Trucks and Vans; and (3) Vocational Vehicles. The rules include separate standards for the engines that power combination tractors and vocational vehicl es. EPA also set hydrofluorocarbon standards to control leakage from air conditioning systems in combination tractors and heavy-duty pickup
trucks and vans.

The agencies estimate that the combined standards will reduce CO 2 emissions by approximately 270 million metric tons and save 530 million barrels of oil over the life of vehicles sold during the 2014 through 2018 model years, providing $49 billion in net societal benefits when private fuel savings are considered. See 76 FR at 57125-27.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 199 of 768 b. EPA’s Plans for Further Standards for Light Vehicle Criteria Pollutants and Gasoline Fuel Quality

In the May 21, 2010 Presidential Memorandum, in addition to addressing GHGs and fuel economy, the President also requested that EPA examine its broader motor vehicle air pollution control program. The President requested that ‘‘ [t]he Administrator of the EPA review for adequacy the current nongreenhouse gas emissions regulations for new motor vehicles, new motor vehicle engines, and motor vehicle fuels, including tailpipe emissions standards for nitrogen oxides and air toxics, and sulfur standards for gasoline. If the Administrator of the EPA finds that new emissions regulations are required, then I request that the Administrator of the EPA promulgate such regulations as part of a comprehensive approach toward regulating motor
vehicles. ’’ 199 EPA is currently in the process of conducting an assessment of the potential need for additional controls on light -duty vehicle non-GHG emissions and gasoline fuel quality. EPA has been actively engaging in technical conversations with the automobile industry, the oil industry, nongovernmental organizations, the states, and other stakeholders on the potential need for new regulatory action, including the areas that are specifically mentioned in the Presidential
Memorandum. EPA will coordinate all future actions in this area with the State of California.

Based on this assessment, in the near future, EPA expects to propose a separate but related program that would, in general, affect the same set of new vehicles on the same timeline as would the proposed light-duty GHG emissions sta ndards. It would be designed to address air quality problems with ozone and PM, which continue to be serious problems in many parts of the country, and light-duty vehicles co ntinue to play a significant role.

EPA expects that this related program, called “Tier 3” vehicle and fuel standards, would among other things propose tailpipe and evaporative standards to reduce non-GHG pollutants from light-duty vehicles, incl uding volatile organic compounds, nitrogen oxides, particulate matter, and air toxics. EPA’s intent, based on exte nsive interaction to date with the automobile manufacturers and other stakeholders, is to propose a Tier 3 program that would allow manufacturers to proceed with coordinated future product development plans with a full understanding of the major regulatory requirements th ey will be facing over the long term. This coordinated regulatory approach would allow manuf acturers to design their future vehicles so that any technological challenges associated w ith meeting both the GHG and Tier 3 standards could be efficiently addressed.

It should be noted that under EPA’s curr ent regulations, GHG emissions and CAFE compliance testing for gasoline vehicles is conducted using a defined fuel that does not include

199 The Presidential Memorandum is found at: http://www.whitehouse.gov/the-press-office/presidentialmemorandum-regarding-fuelefficiency-standards.[Need to update WH web link, or use EPA’s]Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 200 of 768 any amount of ethanol. 200 If the certification test fuel is changed to some ethanol-based fuel through a future rulemaking, EPA would be required under EPCA to address the need for a test procedure adjustment to preserve the level of stringency of the CAFE standards. 201 EPA is committed to doing so in a timely manner to ensure that any change in cer tification fuel will not affect the stringency of future GHG emission standards.

B. Proposed Model Year 2017-2025 GHG Standards for Light-duty Vehicles, Lightduty Trucks, and Medium duty Passenger Vehicles

EPA is proposing new emissions standards to control greenhouse gases (GHGs) from MY 2017 and later light-duty vehicles. EPA is proposing new emission standards for carbon dioxide (CO 2 ) on a gram per mile (g/mile) basis that wi ll apply to a manufacturer’s fleet of cars, and a separate standard that will apply to a manufacturer’s fleet of trucks. CO 2 is the primary greenhouse gas resulting from the combustion of vehicular fuels, and the amount of CO 2 emitted is directly correlated to the amount of fuel consumed. EPA is proposing to conduct a mid-term review of the GHG standards and other requireme nts for MYs 2022-2025, as further discussed in
Section III.B.3 below.

EPA is not proposing changes to the CH 4 and N 2 0 emissions standards, but is proposing revisions to the options that manufacturers have in meeting the CH 4 and N 2 O standards, and to the timeframe for manufacturers to begin measuring N 2 O emissions. These proposed changes are not intended to change the stringency of the CH 4 and N 2 O standards, but are aimed at addressing implementation concerns regarding the standards.

The opportunity to earn credits toward the fleet-wide average CO 2 standards for improvements to air conditioning systems remains in place for MY 2017 and later, including improvements to address both hydrofluorocarbon (HFC) refrigerant losses (i.e., system leakage)
and indirect CO 2 emissions related to the air conditioning efficiency and load on the engine.
The CO 2 standards proposed for cars and trucks take into account EPA’s projection of the average amount of credits expected to be generated across the industry. EPA is proposing several revisions to the air conditioning credits pr ovisions, as discussed in Section III.C.1.

The MY 2012-2016 Final Rule established several program elements that remain in place, where EPA is not proposing significant changes. The proposed standards described below would apply to passenger cars, light-duty trucks, and medium-duty passenger vehicles (MDPVs). As an overall group, they are referred to in this preamble as light-duty vehicles or simply as

200 See 40 CFR § 86.113-94(a).

201 EPCA requires that CAFE tests be determined from the EP A test procedures in place as of 1975, or procedures that give comparable results. 49 USC 32904(c).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 201 of 768vehicles. In this preamble section, passenger cars may be referred to simply as “cars”, and lightduty trucks and MDPVs as “light trucks” or “trucks.” 202

EPA is not proposing changes to the averaging, banking, and trading program elements, as discussed in Section III.B.4, with the excep tion of our proposal for a one-time carry-forward of any credits generated in MY 2010-2016 to be used anytime through MY2021. The previous rulemaking also established provisions for MY 2 016 and later FFVs, where the emissions levels of these vehicles are based on tailpipe emissions performance and the amount of alternative fuel used. These provisions remain in place without change.

Several provisions are being proposed that allow manufacturer’s to generate credits for use in complying with the standards or that provide additional incentives for use of advanced technology. These include credits for technology that reduces CO 2 emissions during off-cycle operation that is not reasonably accounted for by the 2-cycle tests used for compliance purposes. EPA is proposing various changes to this program to streamline its use compared to the MYs 2012-2016 program. These provisions are discusse d in section III.C. In addition, EPA is proposing the use of multipliers to provide an incentive for the use of EVs, PHEVs, and FCVs, as well as a specified gram/mile credit for full si ze pick-up trucks that meet various efficiency performance criteria and/or include hybrid technology at a minimum level of production volumes. These provisions are also discussed in Section III.C. As discussed in those sections, while these additional credit provisions do not ch ange the level of the standards proposed for cars and trucks, unlike the provisions for AC credits, they all support the reasonableness of the standards proposed for MYs 2017-2025.

1. What Fleet-wide Emissions Levels Correspond to the CO 2 Standards?

EPA is proposing standards that are projected to require, on an average industry fleet wide basis, 163 grams/mile of CO 2 in model year 2025. The level of 163 grams/mile CO 2 would be equivalent on a mpg basis to 54.5 mpg, if this level was achieved solely through improvements in fuel efficiency.. 203,204 For passenger cars, the proposed footprint curves call for reducing CO2 by 5 percent per year on average from the model year 2016 passenger car standard through model year 2025. In recognition of manufacturers’ unique challenges in improving the GHG emissions of full-size pickup trucks as we transition from the MY 2016 standards to MY 2017 and later, while preserving the utility (e.g., towing and payload capabilities) of those

202 GHG emissions standards would use the same vehicle category definitions used for MYs 2012-2016 and as are used in the CAFE program.

203 In comparison, the MY 2016 CO 2 standard is projected to achieve a na tional fleet-wide average, covering both cars and trucks, of 250 g/mile

204 Real-world CO 2 is typically 25 percent higher and real-world fu el economy is typically 20 percent lower than the CO2 and CAFE values discussed here. The reference to CO 2 here refers to CO 2 equivalent reductions, as this level includes some reductions in emissions of greenhouse gases other than CO 2 , from refrigerant leakage, as one part of the AC related reductions.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 202 of 768 vehicles, EPA is proposing a lower annual rate of improvement for light-duty trucks in the early years of the program. For light-duty trucks, the footprint curves call for reducing CO2 by 3.5 percent per year on average from the model year 2016 truck standard through model year 2021. EPA is also proposing to change the slopes of the CO 2 -footprint curves for light-duty trucks from those in the 2012-2016 rule, in a manner that effectively means that the annual rate of improvement for smaller light-duty trucks in model years 2017 through 2021 would be higher than 3.5 percent, and the annual rate of improvement for larger light-duty trucks over the same time period would be lower than 3.5 percent. For model years 2022 through 2025, EPA is proposing a reduction of CO 2 for light-duty trucks of 5 percent per year on average starting from the model year 2021 truck standard.

EPA’s proposed standards include EPA’s projection of average industry wide CO 2 - equivalent emission reductions from A/C improv ements, where the proposed footprint curve is made more stringent by an amount equivalent to this projection of A/C credits. This projection of A/C credits builds on the projections from MYs 2012-2016, with the increases in credits mainly due to the full penetration of low GWP alternative refrigerant by MY 2021. The proposed car standards would begin with MY 2017, with a generally linear increase in stringency from MY 2017 through MY 2025 for cars. The truck standards have a more gradual increase for the early years (2017-2020) and is “backloaded” to MY 2021 (i.e the CO 2 standards decrease more slowly at first, then more rapidly in later years approaching MY 2021). For MYs 2021- 2025, the truck standards increase in stringency generally in a linear fashion. EPA proposes to continue to have separate standards for cars and li ght trucks, and to have identical definitions of cars and trucks as NHTSA, in order to harmonize with CAFE standards. The tables in this section below provide overall fleet average levels that are projected for both cars and light trucks over the phase-in period which is estimated to correspond with the proposed standards. The actual fleet-wide average g/mi leve l that would be achieved in an y year for cars and trucks will depend on the actual production for that year, as well as the use of the various credit and averaging, banking, and trading provisions. For example, in any year, manufacturers would be able to generate credits from cars and use them for compliance with the truck standard, or vice
versa. Such transfer of credits between cars and trucks is not reflected in the table below. In Section III.F, EPA discusses the year-by-year estim ate of emissions reductions that are projected to be achieved by the standards.

In general, the proposed schedule of standards acts as a phase-in to the MY 2025 standards, and reflects consideration of the appr opriate lead-time and engineering redesign cycles for each manufacturer to implement the requisite emission reductions technology across its product line. Note that MY 2025 is the final model year in which the standards become more stringent. The MY 2025 CO 2 standards would remain in place for MY 2025 and later modelyears, until revised by EPA in a future rulemaking. EPA estimates that, on a combined fleetwide national basis, the 2025 MY proposed standards would require a level of 163 g/mile CO 2. The derivation of the 163 g/mile estimate is desc ribed in Section III.B.2. EPA has estimated theSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 203 of 768 overall fleet-wide CO 2 -equivalent emission (target) levels that correspond with the proposed attribute-based standards, based on the projecti ons of the composition of each manufacturer’s fleet in each year of the program. Tables III-8 and

III-9 provides these target estimates for each manufacturer.

III-8 Estimated Fleet CO 2 -equivalent Levels Corresponding to the Proposed Standards (Targets) for Cars (g/mile)

2017 2018 2019 2020 2021 2022 2023 2024 2025

Aston Martin 210 200 190 180 171 163 156 149 142

BMW 216 205 195 185 175 168 160 153 146 Chrysler/Fiat 218 207 196 187 176 168 161 153 146
Daimler 226 215 205 194 184 176 168 161 153
Ferrari 222 211 201 191 181 173 165 158 150
Ford 218 207 196 187 177 169 162 154 147 Geely 220 209 198 188 178 170 163 155 148
General Motors 217 206 196 186 176 168 161 153 146
Honda 210 200 189 180 170 163 155 148 142 Hyundai 211 201 190 181 171 163 156 149 142
Kia 213 202 192 182 172 165 157 150 143

Lotus 195 185 175 166 157 150 143 137 131
Mazda 210 200 190 180 171 163 156 149 142
Mitsubishi 207 197 187 177 168 160 153 146 139
Nissan 214 204 193 184 174 166 159 152 145

PORSCHE 195 185 175 166 157 150 143 137 131 Spyker 210 199 189 180 170 162 155 148 141
Subaru 204 194 184 174 165 158 151 144 137
Suzuki 196 186 177 167 158 151 144 138 132

Tata 237 225 214 203 193 184 176 168 161
Tesla 195 185 175 166 157 150 143 137 131 Toyota 209 199 189 179 169 162 155 148 141 Volkswagen 207 196 186 177 167 160 153 146 139

III-9 Estimated Fleet CO 2 -equivelent Levels Corresponding to the Proposed Standards (Targets) for Light Trucks (g/mile)

2017 2018 2019 2020 2021 2022 2023 2024 2025

Aston Martin N/A N/A N/A N/A N/A N/A N/A N/A N/ASummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 204 of 768 BMW 283 272 264 255 236 225 214 204 194 Chrysler/Fiat 293 283 275 266 246 234 223 212 201
Daimler 299 289 280 272 253 241 229 218 208
Ferrari N/A N/A N/A N/A N/A N/A N/A N/A N/A

Ford 305 296 288 282 262 250 237 224 213 Geely 278 266 258 250 231 220 209 199 189
General Motors 309 299 291 283 262 249 236 224 213
Honda 279 269 261 252 233 222 211 201 191 Hyundai 277 266 258 249 231 219 209 198 188
Kia 289 279 271 262 243 231 220 209 199
Lotus N/A N/A N/A N/A N/A N/A N/A N/A N/A

Mazda 272 259 252 244 226 216 206 195 186
Mitsubishi 266 254 246 238 220 209 199 189 180
Nissan 293 282 274 266 248 236 224 212 202
PORSCHE 286 274 266 257 238 226 215 205 195 Spyker 278 265 258 249 230 219 208 198 188
Subaru 263 251 243 235 217 206 196 186 177
Suzuki 269 257 249 240 222 211 201 191 181

Tata 270 258 250 241 223 212 202 191 182
Tesla N/A N/A N/A N/A N/A N/A N/A N/A N/A Toyota 292 281 273 266 246 234 222 211 200 Volkswagen 295 284 276 267 248 236 225 214 203 Companies with “N/A” do not presently have trucks in their fleet.

These estimates were aggregated based on projected production volumes into the fleetwide averages for cars, trucks, and the entire fleet, shown in Table III-10. 205 The combined fleet estimates are based on the assumption of a fleet mix of cars and trucks that vary over the MY 2017-2025 timeframe. This fleet mix distribution can be found in Chapter 1 of the join TSD.

III-10 Estimated Fleet-wide CO 2 -equivalent Levels Corresponding to the Proposed Standards

205 Due to rounding during calculations, the estimated fleet-wide CO 2 -equivalent levels may vary by plus or minus 1

gram.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 205 of 768 Cars Trucks Fleet
Model Year CO 2 (g/mi) CO 2 (g/mi) CO 2 (g/mi)
2017 213 295 243
2018 202 285 232
2019 192 277 223
2020 182 270 213
2021 173 250 200
2022 165 237 190
2023 158 225 181
2024 151 214 172 2025 and later 144 203 163

As shown in Table III-10, fleet-wide CO 2 -equivalent emission levels for cars under the approach are projected to decrease from 213 to 144 grams per mile between MY 2017 and MY 2025. Similarly, fleet-wide CO 2 -equivalent emission levels for trucks are projected to decrease from 295 to 203 grams per mile. These numbers do not include the effects of other flexibilities and credits in the program 206 . The estimated achieved values can be found in Chapter x of the Regulatory Impact Analysis (RIA).

As noted above, EPA is proposing standards that would result in increasingly stringent
levels of CO 2 control from MY 2017 though MY 2025. Applying the CO 2 footprint curves applicable in each model year to the vehicles (and their footprint distributions) expected to be sold in each model year produces progressive ly more stringent estimates of fleet-wide CO 2 emission targets. The standards achieve important CO 2 emissions reductions through the application of feasible control technology at r easonable cost, considering the needed lead time for this program and with proper consideration of manufacturer product redesign cycles. EPA has analyzed the feasibility of achieving the proposed CO 2 standards, based on projections of the adoption of technology to reduce emissions of CO 2 , during the normal redesign process for cars and trucks, taking into account the effectiveness and cost of the technology. The results of the analysis are discussed in detail in Section III.D below and in the draft RIA. EPA also presents the overall estimated costs and benefits of the car and truck proposed CO 2 standards in Section III.H. In developing the proposal, EPA has eval uated the kinds of technologies that could be utilized by the automobile industry, as well as the associated costs for the industry and fuel savings for the consumer, the magnitude of the GHG and oil reductions that may be achieved,
and other factors relevant under the CAA.

With respect to the lead time and cost of incorporating technology improvements that reduce GHG emissions, EPA places important weight on the fact that the proposed rule provides a long planning horizon to achieve the very challenging emissions standards being proposed, and provides manufacturers with certain ty when planning fu ture products. The time-frame and levels

206 Nor do they reflect ABTSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 206 of 768 for the standards are expected to provide manufacturers the time needed to develop and incorporate technology that will achieve GHG reductions, and to do this as part of the normal vehicle redesign process. Further discussing of lead time, redesigns and feasibility can be found in Section III-D and Chapter 3 of the joint TSD.

In the MY 2012-2016 Final Rule, EPA establis hed several provisions which will continue to apply for the proposed MY2017-2025 standards. Consistent with the requirement of CAA section 202(a)(1) that standards be applicable to vehicles “for their useful life,” CO 2 vehicle standards would apply for the useful life of the ve hicle. Under section 202(i) of the Act, which authorized the Tier 2 standards, EPA establishe d a useful life period of 10 years or 120,000 miles, whichever first occurs, for all light-duty vehicles and light-duty trucks. 207 This useful life was applied to the MY 2012-2016 GHG standards and EPA is not proposing any changes to the useful life for MYs 2017-2025. Also, as with MYs 2012-2016, EPA proposes that the in-use emission standard would be 10% higher for a model than the emission levels used for certification and compliance with the fleet average th at is based on the footprint curves. As with the MY2012-2016 standards, this will address issu es of production variability and test-to-test variability. The in-use standard is discussed in Section III.E. Finally, EPA is not proposing any changes to the test procedures over which emissions are measured and weighted to determine compliance with the standards. These procedures are the Federal Test Procedure (FTP or ‘‘city’’ test) and the Highway Fuel Economy Te st (HFET or ‘‘highway’’ test).

2. What Are the Proposed CO2 At tribute-based Standards?

As with the MY 2012-2016 standards, EPA is proposing separate car and truck standards, that is, vehicles defined as cars have one set of footprint-based curves for MY 2017-2025 and vehicles defined as trucks have a different set for MY 2017-2025. In general, for a given footprint the CO 2 g/mi target for trucks would be less stringent than for a car with the same footprint. EPA’s approach for establishing the footprint curves for model years 2017 and later, including changes from the approach used for th e MY2012-2016 footprint curves, is discussed in Section II.C and Chapter 2 of the joint TSD. The curves are described mathematically by a family of piecewise linear functions (with respect to vehicle footprint) that gradually and continually ramp down from the MY 2016 curve established in the previous rule. As Section II.C describes, EPA has modified the curves from 2016, particularly for trucks. To make this modification, we wanted to ensure that starting from the 2016 curve, there is a gradual transition to the new slopes and cut point (out to 74 sq ft from 66 sq ft). The transition is also designed to prevent the curve from one year from crossing the previous year’s curve.

Written in mathematic notation, the form of the proposed function is as follows: 208

207 See 65 FR 6698 (February 10, 2000).

208 See proposed Regs xxxx, which are the official coefficien ts and equation. The information proposed here is a summary version.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 207 of 768 Passenger Car Target = min (b,max(a, c * footprint+d))

Coefficient 2017 2018 2019 2020 2021 2022 2023 2024 2025

a 194.7 184.9 175.3 166.1 157.2 150.2 143.3 136.8 130.5
b 262.7 250.1 238.0 226.2 214.9 205.5 196.5 187.8 179.5
c 4.53 4.35 4.17 4.01 3.84 3.69 3.54 3.40 3.26
d 8.9 6.5 4.2 1.9 -0.4 -1.1 -1.8 -2.5 -3.2

Light Truck Target = min(min (b,max(a, c * footprint+d)),min(f,max(e, g*footprint+h)

Coefficient 2017 2018 2019 2020 2021 2022 2023 2024 2025

a 238.1 226.8 219.5 211.9 195.4 185.7 176.4 167.6 159.1

b 347.2 341.7 338.6 336.7 334.8 320.8 305.6 291.0 277.1

c 4.87 4.76 4.68 4.57 4.28 4.09 3.91 3.74 3.58

d 38.3 31.6 27.7 24.6 19.8 17.8 16.0 14.2 12.5

e 246.4 240.9 237.8 235.9 234.0 234.0 234.0 234.0 234.0
f 347.4 341.9 338.8 336.9 335.0 335.0 335.0 335.0 335.0 g 4.04 4.04 4.04 4.04 4.04 4.04 4.04 4.04 4.04
h 80.5 75.0 71.9 70.0 68.1 68.1 68.1 68.1 68.1Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 208 of 768 Figure 2 - Car CurvesSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 209 of 768 Figure 3 –Truck CurvesSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 210 of 768 The car curves are largely similar to 2016 curve in slope. By contrast, the MY 2017 and later truck curves are steeper relative to the MY 2016 curve, but gradually flatten as a result of the multiplicative increase of the standards. As a further change from the MYs 2012-2016 rule, the truck curve does not reach the ultimate cutpoi nt of 74 sq ft until 2022. The gap between the 2020 curve and the 2021 curve is indicative of design of the truck standards described earlier, where a significant proportion of the increased stringency over the first five years occurs between MY 2020 and MY 2021. Finally, the gradual flattening of both the car and the trucks curves is noticeable. For further discussion of these topics, please see Section II.C and Chapter 2 of the joint TSD.

3. Mid-Term Technology Review

Given the long time frame at issue in setting standards for MY2022–2025 light-duty vehicles, and given NHTSA’s obligation to conduct a separate rulemaking in order to establish
final standards for vehicles for those mo del years, EPA and NHTSA will conduct a comprehensive mid-term evaluation and agency decision-making as described below. Up to date information will be developed and compiled for the evaluation, through a collaborative, robust and transparent process, including public notice and comment. The evaluation will be based on (1) A holistic assessment of all of the factors co nsidered by the agencies in setting standards, including those set forth in the rule and other re levant factors, and (2) the expected impact of those factors on the manufacturers’ ability to comply, without placing decisive weight on any particular factor or projection. The comprehensive evaluation process will lead to final agency action by both agencies.

Consistent with the agencies’ commitment to maintaining a single national framework forregulation of vehicle emissions and fuel economy, the agencies fully expect to conduct the midterm evaluation in close coordination with the California Air Resources Board (CARB). Moreover, the agencies fully expect that any adjustments to the standards will be made with the participation of CARB and in a manner that ensures continued harmonization of state and
Federal vehicle standards.

EPA will conduct a mid-term evaluation of the later model year light-duty GHG standards (MY2022–2025). The evaluation will determine whether those standards are appropriate under section 202(a) of the Act. Under the regulations proposed today, EPA would be legally bound to make a final decision, by April 1, 2018, on whether the MY 2022–2025 GHG standards are appropriate under section 202(a), in light of the record then before the

agency.

EPA, NHTSA and CARB will jointly prep are a draft Technical Assessment Report (TAR) to inform EPA’s determination on the ap propriateness of the GHG standards and toSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 211 of 768 inform NHTSA’s rulemaking for the CAFE standards for MYs 2022–2025. The TAR will examine the same issues and underlying analyses and projections considered in the original rulemaking, including technical and other analyses and projections relevant to each agency’s authority to set standards as well as any relevant new issues that may present themselves. There will be an opportunity for public comment on the draft TAR, and appropriate peer review will be performed of underlying analyses in the TAR. The assumptions and modeling underlying the TAR will be available to the public, to the extent consistent with law.

EPA will also seek public comment on whet her the standards are appropriate under section 202(a), e.g. comments to affirm or change the GHG standards (either more or less stringent). The agencies will carefully consider comments and information received and respond to comments in their respective subsequent final actions.

EPA and NHTSA will consult and coordinate in developing EPA’s determination on whether the MY 2022–2025 GHG standards are ap propriate under section 202(a) and NHTSA’s

NPRM.

In making its determination, EPA will evaluate and determine whether the MY2022– 2025 GHG standards are appropriate under section 202(a) of the CAA based on a comprehensive, integrated assessment of all of the results of the review, as well as any public comments received during the evaluation, taken as a whole. The decision making required of the Administrator in making that determination is inte nded to be as robust and comprehensive as that in the original setting of the MY2017–2025 standards.

In making this determination, EPA will consider information on a range of relevant factors, including but not limited to those listed in the proposed rule and below:

1. Development of powertrain improvements to gasoline and diesel powered vehicles.

2. Impacts on employment, including the auto sector.

3. Availability and implementation of met hods to reduce weight, including any impacts on safety.

4. Actual and projected availability of public and private charging infrastructure for electric vehicles, and fueling infrastructure for alternative fueled vehicles.

5. Costs, availability, and consumer acceptance of technologies to ensure compliance with the standards, such as vehicle batteri es and power electronics, mass reduction, and anticipated trends in these costs.

6. Payback periods for any incremental vehicle costs associated with meeting the
standards.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 212 of 768 7. Costs for gasoline, diesel fuel, and alternative fuels.

8. Total light-duty vehicle sales and projected fleet mix.

9. Market penetration across the fleet of fuel efficient technologies.

10. Any other factors that may be deemed relevant to the review.

If, based on the evaluation, EPA decides that the GHG standards are appropriate under section 202(a), then EPA will announce that final decision and the basis for EPA’s decision. The decision will be final agency action which also w ill be subject to judicial review on its merits. EPA will develop an administrative record for that review that will be no less robust than that developed for the initial determination to establis h the standards. In the midterm evaluation, EPA will develop a robust record for judicial review that is the same kind of record that would be developed and before a court for judicial review of the adoption of standards.

Where EPA decides that the standards are not appropriate, EPA will initiate a rulemaking to adopt standards that are appropriate under section 202(a), which could result in standards that are either less or more stringent. In this ru lemaking EPA will evaluate a range of alternative standards that are potentially effective and reasonably feasible, and the Administrator will propose the alternative that in her judgment is the best choice for a standard that is appropriate under section 202(a). In the 2017–2025 rulemaking EPA will formally adopt the interpretation that the provisions of section 202(b)(1)(C) are not applicable to any revisions of the greenhouse standards adopted in this later rulemaking based on the mid-term evaluation. If EPA initiates a rulemaking, it will be a joint rulemaking with NHT SA. Any final action taken by EPA at the end of that rulemaking is also judicially reviewable.

The MY 2022–2025 GHG standards will remain in effect unless and until EPA changes them by rulemaking.

NHTSA intends to issue conditional standards for MYs 2022–2025 in the LDV rulemaking being initiated this fall for MY2017 and later model years. The CAFE standards for MYs 2022–2025 will be determined with finality in a subsequent, de novo notice and comment rulemaking conducted in full co mpliance with section 32902 of title 49 U.S.C. and other applicable law. Accordingly, NHTSA’s development of its proposal in that later rulemaking will include the making of economic and technology analyses and estimates that are appropriate for those model years and based on then-current information.

Any rulemaking conducted jointly by the agencies or by NHTSA alone will be timed to provide sufficient lead time for industry to make whatever changes to their products that the rulemaking analysis deems feasible based on the new information available. At the very latest, the three agencies will complete the mid-term ev aluation process and subsequent rulemaking onSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 213 of 768 the standards that may occur in sufficient time to promulgate final standards for MYs 2022–2025 with at least 18 months lead time, but additional lead time may be provided.

EPA understands that California intends to propose a mid-term evaluation in its program
that is coordinated with EPA and NHTSA and is ba sed on a similar set of factors as outlined in this Appendix A. The rules submitted to EPA for a waiver under the CAA will include such a mid-term evaluation. EPA understands that California intends to continue promoting harmonized
state and federal vehicle standards. EPA further understands that California’s 2017–2025
standards to be submitted to EPA for a waiver under the Clean Air Act will deem compliance with EPA greenhouse gas emission standards, even if amended after 2012, as compliant with California’s. Therefore, if EPA revises it standards in response to the mid-term review, California may need to amend one or more of its 2022–2025 MY standards and would submit such amendments to EPA with a request for a waiver, or for confirmation that said amendments fall within the scope of an existing waiver, as appropriate.

4. Averaging, Banking, and Trading Provisions for CO2 Standards

In the MY 2012-2016 rule, EPA adopted credit provisions for credit carry-back, credit carry-forward, credit transfers, and credit trading. For EPA’s purposes, these kinds of provisions are collectively termed Averaging, Banking, and Trading (ABT), and have been an important part of many mobile source programs under CAA Title II, both for fuels programs as well as for engine and vehicle programs. 209 As in the MY2012-2016 program, EPA is proposing basically the same comprehensive program for averaging, banking, and trading of credits which together will help manufacturers in planning and implementing the orderly phase-in of emissions control technology in their production, consistent with their typical redesign schedules. ABT is important because it can help to address many issues of technological feasibility and lead-time,
as well as considerations of cost. ABT is an inte gral part of the standard setting itself, and is not just an add-on to help reduce costs. In many cases, ABT resolves issues of cost or technical feasibility, allowing EPA to set a standard that is numerically more stringent. The ABT provisions are integral to the fleet averaging approach established in the MY 2012-2016 rule. EPA is proposing to change the credit carry-forward provisions as described below, but the program otherwise would remain in place unchanged for model years 2017 and later.

As noted above, the ABT provisions consist primarily of credit carry-back, credit carryforward, credit transfers, and credit trading. A manufacturer may have a deficit at the end of a model year after averaging across its fleet using credit transfers between cars and trucks – that is, a manufacturer’s fleet average level may fail to meet the required fleet average standard. Credit carry-back refers to using credits to offset any de ficit in meeting the fleet average standards that had accrued in a prior model year. A deficit must be offset within 3 model years using credit carry-back provisions. After satisfying any needs to offset pre-existing debits within a vehicle

209 See 75 FR at 25412-413.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 214 of 768 category, remaining credits may be banked, or saved for use in future years. This is referred to as credit carry-forward. The EPCA/EISA statutory framework for the CAFE program includes a 5-year credit carry-forward provision and a 3-year credit carry-back provision. In the MYs2012-2016 program, EPA chose to adopt 5-year credit carry-forward and 3-year credit carryback provisions as a reasonable approach that maintained consistency between the agencies’ provisions. EPA is proposing to continue with this approach in this rulemaking. (A further discussion of the ABT provisions can be found at 75 FR 25412-14 May 7, 2010).

Although the credit carry-forward and carry-back provisions would generally remain in place for MY 2017 and later, EPA is proposing to allow all unused credits generated in MY2010-2016 to be carried forward through MY 2021. This amounts to the normal 5 year carryforward for MY 2016 and later credits but provid es additional carry-forward years for credits earned in MYs 2010-2015. Extending the life for MY 2010-2015 credits would provide greater flexibility for manufacturers in using the credits they have generated. These credits would help manufacturers resolve lead-time issues they might face in the model years prior to 2021 as they transition from the 2016 standards to the progressively more stringent standards for 2017 and later. It also provides an additional incentive to generate credits earlier, for example in MYs 2014 and 2015, because those credits may be used through 2021, thereby encouraging the earlier
use of additional CO 2 reducing technology.

While this provision provides greater flexib ility in how manufacturers use credits they have generated, it would not change the overall CO 2 benefits of the National Program, as EPA does not expect that any of the credits would have expired as they would be used or traded to other manufacturers. EPA believes the prop osed approach provides important additional flexibility in the early years of the new MY2017 and later standards. EPA requests comments on the proposed approach for carrying over MY 2016 and earlier vintage credits into the MY 2017 and later model years.

EPA is not proposing to allow MY 2009 early credits to be carried forward beyond the normal 5 years due to concerns expressed during the 2012-2016 rulemaking that there may be the potential for large numbers of credits that could be generated in MY 2009 for companies that are over-achieving on CAFE and that some of these credits could represent windfall credits. 210
In response to these concerns, EPA placed restrictions the use of MY 2009 credits (for example, MY 2009 credits may not be traded) and does not believe expanding the use of MY 2009 credits would be appropriate. Under th e MY 2012-2016 early credits pr ogram, manufacturers have until the end of MY 2011 (reports must be submitted by April 2012), when the early credits program ends, to submit early credit reports. Therefore, EPA does not yet have information on the amount of early MY2009 credits actually generated by manufacturers to assess whether or not

210 75 FR at 25442. Moreover, as pointed out in the earlier rulemaking, there can be no legitimate expectation that these 2009 MY credits could be used as part of a compliance strategy in model years after 2014, and thus no reason to carry forward the credits past 5 years due to action in reliance by manufacturers.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 215 of 768 they could be viewed as windfall. Nevertheless, because these concerns continue, EPA is proposing not to extend the MY 2009 credit transfers past the existing 5-years limit .

Transferring credits refers to exchanging credits between the two averaging sets,passenger cars and trucks, within a manufacturer. For example, credits accrued by overcompliance with a manufacturer’s car fleet average standard could be used to offset debits accrued due to that manufacturer not meeting the truck fleet average standard in a given year. Finally, accumulated credits may be traded to another manufacturer. In EPA’s CO 2 program, there are no limits on the amount of credits that may be transferred or traded.

The averaging, banking, and trading provisi ons are generally consistent with those included in the CAFE program, with a few notable exceptions. As with EPA’s approach (except for the proposal discussed above for a one-time extended carry-forward of MY2010-2016 credits), CAFE allows five year carry-forward of credits and three year carry-back. CAFE
transfers of credits across a manufacturer’s car a nd truck averaging sets are also allowed, but with limits established by EISA on the use of transferred credits. The amount of transferred credits that can be used in a year is limited under CAFE, and transferred credits may not be used to meet the CAFE minimum domestic passenger car standard. CAFE allows credit trading, but again, traded credits cannot be used to meet the minimum domestic passenger car standard.

5. Small Volume Manufacturer Standards

In adopting the CO 2 standards for MY 2012-2016, EPA recognized that for very small volume manufacturers, the CO 2 standards adopted for MY 2012-2016 would be extremely challenging and potentially infeasible absent credits from other manufacturers. EPA therefore deferred small volume manufacturers (SVMs) with annual U.S. sales less than 5,000 vehicles from having to meet CO 2 standards until EPA is able to esta blish appropriate SVM standards. As part of establishing eligibility for the exemption, manufacturers must make a good faith effort to secure credits from other manufacturers, if they are reasonably available, to cover the emissions reductions they would have otherwise had to achieve under applicable standards.

These small volume manufacturers face a greater challenge in meeting CO 2 standards compared to large manufacturers because they only produce a few vehicle models, mostly focusing on high performance sports cars and luxury vehicles. These manufacturers have limited product lines across which to average emissions, and the few models they produce often have very high CO 2 levels. As SVMs noted in discussions, SVMs only produce one or two vehicle types but must compete directly with brands that ar e part of larger manufacturer groups that have
more resources available to them. There is often a time lag in the availability of technologies from suppliers between when the technology is supplied to large manufacturers and when it is
available to small volume manufacturers. Also , incorporating new technologies into vehicle designs costs the same or more for small volume manufacturers, yet the costs are spread over significantly smaller volumes. Therefore, SVMs ty pically have longer model life cycles in orderSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 216 of 768 to recover their investments. SVMs further note d that despite constraints facing them, SVMs
need to innovate in order to differentiate themselv es in the market and ofte n lead in incorporating technological innovations, particularly lightweight materials.

In the MY 2012-2016 Final Rule, EPA noted that it intended to conduct a follow-on rulemaking to establish appropriate standards for these manufacturers. In developing this proposal, the agencies held detailed technical di scussions with the manufacturers eligible for the exemption under the MY 2012-2016 program and reviewed detailed product plans of each
manufacturer. EPA continues to believe that SVMs would face great difficulty meeting the primary CO 2 standards and that establishing challengi ng but less stringen t SVM standards is appropriate given the limited products offering of SVMs. EPA believes it is important to establish standards that will require SVMs to continue to innovate to reduce emissions and do their “fair share” under the GHG program. However, selecting a single set of standards that would apply to all SVMs is difficult because each manufacturer’s product lines vary significantly. EPA is concerned that a standard that would be appropriate for one manufacturer may not be feasible for another, potentiall y driving them from the domestic market. Alternatively, a less stringent standard ma y only cap emissions for some manufacturers, providing little incentive to reduce emissions.

Based on this, rather than conducting a separate rulemaking, as part of this MY 2017- 2025 rulemaking EPA is proposing to allow SVMs to petition EPA for an alternative CO 2 standard for these model years. The proposed approach for SVM standards and eligibility requirements are described below. EPA is also requesting comments on extending eligibility for the proposed SVM standards to very small manufacturers that are owned by large manufacturers
but are able to establish that th ey are operationally independent.

EPA considered a variety of approaches and believes a case-by-case approach for establishing SVM standards would be appropriate. EPA is proposing to allow eligible SVMs the option to petition EPA for alternative standards. An SVM utilizing this option would be required to submit data and information that the agency would use in addition to other available
information to establish CO 2 standards for that specific manufacturer. EPA requests comments on all aspects of the proposed approach described in detail below.

a. Overview of Existing Case-by-Case Approaches

A case-by-case approach for establishing standards for SVMs has been adopted by NHTSA for CAFE, CARB in their 2009-2016 GHG program, and the European Union (EU) for European CO 2 standards. For the CAFE program, EPCA allows manufacturers making less than 10,000 vehicles per year worldwide to petition the ag ency to have an alternative standard set forSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 217 of 768 them. 211 NHTSA has adopted alternative standards for some small volume manufacturers under these CAFE provisions and continually revi ews applications as they are submitted. 212 Under the CAFE program, petitioners must include projections of the most fuel efficient production mix of vehicle configurations for a model year and a discussion demonstrating that the projections are reasonable. Petitioners must include, among other items, annual production data, efforts to comply with applicable fuel economy sta ndards, and detailed information on vehicle technologies and specifications. The petitione r must explain why they have not pursued additional means that would allow them to achieve higher average fuel economy. NHTSA publishes a proposed decision in the Federal Register and accepts public comments. Petitions may be granted for up to three years. Manufacturers are not required to pay fines for the model years covered by the petition while th eir petition is under NHTSA review.

For the California GHG standards for MYs 2 009-2016, CARB established a process that would start at the beginning of MY2013, where small volume manufacturers would identify all MY 2012 vehicle models certified by large volume manufacturers that are comparable to the SVM’s planned MY 2016 vehicle models. 213 The comparison vehicles were to be selected on the basis of horsepower and power to weight ra tio. The SVM was required to demonstrate the appropriateness of the comparison models sel ected. CARB would then provide a target CO 2 value based on the emissions performance of the comparison vehicles to the SVM for each of their vehicle models to be used to calculate a fleet average standard for each test group for MY2016 and later. Since CARB provides that compliance with the National Program for MYs 2012-2016 will be deemed compliance with the CARB program, it has not taken action to set unique SVM standards, but its program nevertheless was a useful model to consider.

The EU process allows small manufacturers to apply for a derogation from the primary CO 2 emissions reduction targets. 214 Applications for 2012 were required to be submitted by manufacturers no later than March 31, 2011, an d the Commission will assess the application within 9 months of the receipt of a complete ap plication. Applications for derogations for 2012 have been submitted by several manufacturers and non confidential versions are currently available to the public. 215 In the EU process, the SVM proposes an alternative emissions target supported by detailed information on the applic ant’s economic activities and technological potential to reduce CO 2 emissions. The application also requires information on individual vehicle models such as mass and specific CO 2 emissions of the vehicles, and information on the

211 See 49 U.S.C. 32902(d) and 49 CFR Part 525. Under the CAFE program, manufacturers who manufacture less than 10,000 passenger cars worldwide annually may petiti on for an exemption from generally-applicable CAFE standards, in which case NHTSA will determine what level of CAFE would be maximum feasible for that particular manufacturer if the agency determines that doing so is appropriate.

212 Alternative CAFE standards are provided in 49 CFR 531.5 (e).

213 13 CCR 1961.1(D).

214 Article 11 of Regulation (EC) No 443/2009 and EU No 63/2011. See also “Frequently asked questions on application for derogation pursuant to Aticle 11 of Regulation (EC) 443/2009.”

215 http://ec.europa.eu/clima/documenta tion/transport/vehicles/cars_en.htmSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 218 of 768 characteristics of the market for the types of ve hicles manufactured. The proposed alternative emissions standards may be the same numeric standard for multiple years or a declining standard, and the alternative standards may be established for a maximum period of five years. Where the European Commission is satisfied that the specific emissions target proposed by the manufacturer is consistent with its reduction po tential, including the economic and technological potential to reduce its specific emissions of CO 2 , and taking into account the characteristics of the market for the type of car manufactured, the Co mmission will grant a derogation to the manufacturer.

b. EPA’s Proposed Framework for Case-by-Case SVM Standards

EPA proposes that SVMs will become subject to the GHG program beginning with MY 2017. Starting in MY 2017, an SVM would be required to meet the primary program standards unless EPA establishes alternative standards for the manufacturer. EPA proposes that eligible manufacturers seeking alternative standards must petition EPA for alternative standards by July 30, 2013, providing the information described below. If EPA finds that the application is incomplete, EPA would notify the manufacturer and provide an additional 30 days for the manufacturer to provide all necessary information. EPA would then publish a notice in the Federal Register of the manufacturer’s petition and recommendations for an alternative standard, as well as EPA’s proposed alternative standard . Non confidential busin ess information portions of the petition would be available to the public for review in the docket. After a period for public comment, EPA would make a determination on an alternative standard for the manufacturer and publish final notice of the determination in the Fede ral Register for the general public as well as the applicant. EPA expects the process to estab lish the alternative standa rd to take about 12 months once a complete application is submitted by the manufacturer.

EPA proposes that manufacturers would petition for alternative standards for up to 5 model years (i.e., MYs 2017 – 2021) as long as sufficient information is available on which to
base the alternative standards (see application discussion be low). This initial round of establishing case-by-case standards would be followed by one or more additional rounds until
standards are established for the SVM for all mode l years up to and including MY 2025. For the later round(s) of standard setting, EPA proposes that the SVM must submit their petition 36 months prior to the start of the first model year for which the standards would apply in order to provide sufficient time for EPA to evaluate and set alternative standards (e.g., January 1, 2018 for MY 2022). The subsequent case-by-case standard setting would follow the same notice and comment process as outlined above.

EPA also proposes that if EPA does not es tablish SVM standards for a manufacturer at least 12 months prior to the start of the model year in cases where the manufacturer provided all required information by the established deadline, the manufacturer may request an extension of the alternative standards currently in place, on a model year by model year basis. This wouldSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 219 of 768 provide assurance to manufacturers that they would have at least 12 months lead time to prepare for the upcoming model year.

EPA requests comments on allowing SVMs to comply early with the MY 2017 SVM standards established for them. Manufacturers may want to certify to the MY 2017 standards in earlier model years (e.g., MY 2015 or MY 2016). Under the MY 2012-2016 program, SVMs are eligible for an exemption from the standards as long as they have made a good faith effort to purchase credits. By certifying to the SVM st andard early in lieu of this exemption, manufacturers could avoid having to seek out credits to purchase In order to maintain this exemption. EPA would not allow certification for vehicles already produced by the manufacturer, so the applicability of this provision would be limited due to the timing of establishing the SVM standards. Manufacturers in terested in the possibility of early compliance would be able to apply for SVM standards earlier than the required July 30, 2013 deadline proposed above. An early compliance option also may be beneficial for new manufacturers entering the market that qualify as SVMs.

c. Petition Data and Information Requirements

As described in detail in section I.D.2, EPA establishes motor vehicle standards under section 202(a) that are based on technological feas ibility, and considering lead time, safety, costs and other impacts on consumers, and other factors such as energy impacts associated with use of the technology. EPA proposes to require that SVMs submit the data and information listed below which EPA would use, in addition to other relevant information, in determining an appropriate alternative standard for the SVM. EPA would also consider data and information provided by commenters during the comment process in determining the final level of the SVM’s standards. As noted above, other case- by-case standard setting ap proaches have been adopted by NHTSA, the European Union, and CARB and EPA has considered the data requirements of those programs in developing the proposed data and information requirements detailed below. EPA requests comments on the following proposed data requirements.

EPA proposes that SVMs would provide the following information as part of their petition for SVM standards:

Vehicle Model and Fleet Information

• MYs that the application covers – up to 5 MY s. Sufficient information must be provided to establish alternative standards for each year

• Vehicle models and sales projections by model for each MY

• Description of models (vehicle type, mass, power, footprint, expected pricing)

• Description of powertrainSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 220 of 768 • Production cycle for each model including new vehicle model introductions

• Vehicle footprint based targets and project ed fleet average standard under primary program by model year

Technology Evaluation

• CO 2 reduction technologies employed or expected to be on the vehicle model(s) for the applicable model years, including effectiveness and cost information

– Including A/C and potential off-cycle technologies

• Evaluation of similar vehicles certified in MYs 2012-2013 (or latest 2 MYs for later applications) for each vehicle model including CO 2 results and any A/C credits generated by the models

– Must be selected based on vehicle ty pe, horsepower, mass, power-to-weight, vehicle footprint, vehicle price range and other relevant factors as explained by
the SVM

• Discussion of CO 2 reducing technologies employed on vehicles offered by the
manufacturer outside of the U.S. market but not in the U.S., including why those vehicles/technologies are not being introduced in the U.S. market as a way of reducing
overall fleet CO 2 levels

• Evaluation of technologies projected by EPA as technologies likely to be used to meet the 2012-2016 and 2017-2025 standards that are not projected to be fully utilized by manufacturer and explanation of reasons for not using the technologies, including
relevant cost information

SVM Projected Standards

• The most stringent CO 2 level estimated by the SVM to be feasible and appropriate by model and MY and the technological and other basis for the estimate

• For each MY, projection of the lowest fleet average CO 2 production mix of vehicle models and discussion demonstrating that these projections are reasonable

– EPA expects fleet standards would track product plan/projected changes in product mix for the individual manufacturers

• A copy of any applications submitted to NHTSA for MY 2012 and later alternative
standards

EligibilitySummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 221 of 768  U.S. sales for previous three model years and projections for production volumes over the time period covered by the application

 Complete information on ownership structure in cases where SVM has ties to other
manufacturers with U.S. vehicle sales

EPA proposes to weigh several factors in determining what CO 2 standards are appropriate for a given SVMs fleet. These factors would include the level of technology applied to date by the manufacturer, the manufacturer’s projections for the application of additional technology, CO 2 reducing technologies being employed by other manufacturers including on vehicles with which the SVM competes directly and the CO 2 levels of those vehicles, and the technological feasibility and reasonableness of employing additional technology not projected by the manufacturer in the time-frame for which standards are being established. EPA would also consider opportunities to generate A/C and o ff-cycle credits that are available to the manufacturer. Lead time would be a key consideration both for the initial years of the SVM standard, where lead time would be shorter due to the timing of the notice and comment process to establish the standards, and for the later years where manufacturers would have more time to
achieve additional CO 2 reductions.

d. SVM Credits Provisions

As discussed in Section III.B.4, EPA’s progra m includes a variety of credit averaging, banking, and trading provisions. EPA proposes that these provisions would generally apply to SVM standards as well, with the exception that SVMs would not be allowed to trade credits to other manufacturers. Because SVMs would be meeting alternative, less stringent standards compared to manufacturers in the primary program, EPA proposes that SVM would not be allowed to trade (i.e., sell or otherwise provide) CO 2 credits that the SVM generates against the
SVM standards to other manufacturers. SVMs woul d be able to use credits purchased from other manufacturers generated in the primary program . Although EPA does not expect significant credits to be generated by SVMs due to the manufacturer-specific st andard setting approach being proposed, SVMs would be able to generate and use credits internally, under the credit carry-forward and carry-back provisions. Under a case-by-case approach, EPA would not view
such credits as windfall credits and not allo wing internal banking could stifle potential innovative approaches for SVMs. SVMs would also be able to transfer credits between the car and light trucks categories.

e. SVM Standards Eligibility

i. Current SVMs

The MY 2012-2016 rulemaking limited eligibility for the SVM deferment to manufacturers in the U.S. market in MY 2008 or MY 2009 with U.S. sales of less than 5,000 vehicles per year. After initial eligibility has b een established, the SVM remains eligible for theSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 222 of 768 exemption if the rolling average of three consecutive model years of sales remains below 5,000 vehicles. Manufacturers going over the 5,000 vehicle rolling average limit would have two additional model years to transition to having to meet applicable CO 2 standards. Based on these eligibility criteria, there are three companies that qualify currently as SVMs under the MY2012- 2016 standards: Aston Martin, Lotus, and McLaren. 216 These manufacturers make up much less than one percent of total U.S. vehicles sales, so the environmental impact of these alternative standards would be very small. EPA continues to believe that the 5,000 vehicle cut-point and rolling three year average approach is appropriate and proposes to retain it as a primary criterion for SVMs to remain eligible for SVM standards. The 5,000 vehicle threshold allows for some sales growth by SVMs, as the SV Ms in the market today typical ly have annual sales of below 2,000 vehicles. However, EPA wants to ensure that standards for as few vehicles as possible are included in the SVM standards to minimize the environmental impact, and therefore believes it is appropriate that manufacturers with U.S. sales growing to above 5,000 vehicles per year be required to comply with the primary standards. Manufacturers with unusually strong sales in a given year would still likely remain eligible, base d on the three year rolling average. However, if a manufacturer takes steps to expand in the U.S. market on a permanent basis such that they consistently sell more than 5,000 vehicles per year, they would no longer be eligible. EPA
believes a manufacturer will be able to consider these provisions, along with other factors, in its planning to significantly expand in the U.S. mark et. As discussed below, EPA is not proposing to continue to tie eligibility to having been in the market in MY 2008 or MY 2009, or any other year and is instead proposing eligibility criteria for new SVMs newly entering the U.S. market.

ii. New SVMs (New Entrants to the U.S. Market)

As noted above, the SVM deferment under the MY 2012-2016 program included a requirement that a manufacturer had to have been in the U.S. vehicle market in MY 2008 or MY 2009. This provision ensured that a known universe of manufacturers would be eligible for the exemption in the short term and manufacturers would not be driven from the market as EPA proceeded to develop appropriate SVM standards. EPA is not proposing to include such a provision for the SVM standards eligibility criteria for MY 2017-2025. EPA believes that with SVM standards in place, tying eligibility to bein g in the market in a prior year is no longer necessary because SVMs will be required to achieve appropriate levels of emissions control. Also, it could serve as a potential market barrier to competition by hindering new SVMs from entering the U.S. market.

For new market entrants, EPA proposes that a manufacturer seeking an alternative standard for MY2017-2025 must apply and that standards would be established through the process described above. The new SVM would not be able to certify their vehicles until the
standards are established and therefore EPA wo uld expect the manufacturer to submit an

216 Under the MY 2012-2016 program, manufacturers must also make a good faith effort to purchase CO 2 credits in order to maintain eligibility for SVM status.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 223 of 768 application as early as possible but at least 30 months prior to when they expect to begin producing vehicles in order to provide enough time for EPA to evaluate standards and to follow the notice and comment process to establish the sta ndards and for certification. In addition to the information and data described below, EPA proposes to require new market entrants to provide evidence that the company intends to enter the U.S. market within the time frame of the
MY2017-2025 SVM standards. Such evidence w ould include documentation of work underway to establish a dealer network, appropriate financing and marketing plans, and evidence the company is working to meet other federal vehicle requirements such as other EPA emissions standards and NHTSA vehicle safety standards. EPA is concerned about the administrative burden that could be created for the agency by companies with no firm plans to enter the U.S. market submitting applicatio ns in order to see what standard might be established for them. This information, in addition to a complete application with the information and data outlined above, would provide evidence of the seriousness of the a pplicant. As part of this review, EPA reserves the right to not undertake its SVM standards development process for companies that do not
exhibit a serious and documented effort to enter the U.S. market.

EPA remains concerned about th e potential for gaming by a manufacturer that sells less than 5,000 vehicles in the first year, but with plans for significantly larger sales volumes in the following years. EPA believes that it would not be appropriate to establish SVM standards for a new market entrant that plans a steep ramp-up in U.S. vehicle sales. Therefore, EPA proposes that for new entrants, U.S. vehicle sales must remain below 5,000 vehicles for the first three years in the market, after which the manufacturer must maintain a three year rolling average below 5,000 vehicles. If a new market entrant does not comply with these provisions for the first five years in the market, vehicles sold above the 5,000 vehicle threshold would be found not to be covered by the alternative standards, and EPA expects the fleet average is therefore not in compliance with the standards and would be subject to enforcement action and also, the manufacturer would lose eligibility for the SV M standards until it has reestablished three consecutive years of sales below 5,000 vehicles.

By not tying the 5,000 vehicle eligibility criteri a to a particular model year, it would be possible for a manufacturer already in the market to drop below the 5,000 vehicle threshold in a future year and attempt to establish eligibility. EPA proposes to treat such manufacturers as new entrants to the market for purposes of determin ing eligibility for SVM standards. However, the requirements to demonstrate that the manufacturer intends to enter the U.S. market obviously would not be relevant in this case, and therefore would not apply.

iii. Aggregation Requirements and an Operational Independence Concept

In determining eligibility for the MY 2012-2016 exemption, sales volumes must be aggregated across manufacturers according to the provisions of 40 CFR 86.1838-01(b)(3), which requires the sales of different firms to be aggregated in various situations, including where oneSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 224 of 768 firm has a 10% or more equity ownership of a nother firm, or where a third party has a 10% or more equity ownership of two or more firms. These are the same aggregation requirements used in other EPA small volume manufacturer provisions, such as those for other light-duty emissions
standards. 217 EPA proposes to retain these aggregation provisions as part of the eligibility criteria for the SVM standards for MYs 2017-2025. Manufacturers also retain, no matter their size, the option to meet the full set of GHG requirements on their own, and do not necessarily need to demonstrate compliance as part of a corporate parent company fleet. However, as discussed below, EPA is seeking comments on allowing manufacturers that otherwise would not be eligible for the SVM standards due to these aggregation provisions, to demonstrate to the Administrator that they are “operationally independent” based on the criteria described below. Under such a concept, if the Administrator were to determine that a manufacturer was operationally independent, that manufacturer would be eligible for SVM standards.

During the 2012-2016 rule comment period, EPA received comments from Ferrari requesting that EPA allow a manufacturer to apply to EPA to establish SVM status based on the independence of its research, development, test ing, design, and manufacturing from another firm that has ownership interest in that manufacturer. Ferrari is majority owned by Fiat and would be aggregated with other Fiat brands, including Ch rysler, Maserati, and Alfa Romeo, for purposes of determining eligibilit y for SVM standards; therefore Ferrari does not meet the eligibility criteria for SVM status. However, Ferrari believes that it would qualify for such an “operational independence” concept, if such an option were provided. In the MY 2012-2016 Final Rule, EPA noted that it would further consider the issue of operational independence and seek public comments on this concept (see 75 FR 25420). In this proposal, EPA is requesting comment on the concept of operational independence. Specifically, we are seeking comment on expanding eligibility for the SVM standards to manufacturers who would have U.S. annual sales of less than 5,000 vehicles and based on a demonstration that they are “operationally independent” of other companies. Under such an approach, EPA would be amending the limitation for SVM corporate aggregation provisions such that a manufacturer that is more than 10 percent owned by a large manufacturer would be allowed to qualify for SVM standards on the basis of its own sales, because it operates its research, design, production, and manufacturing independently from the parent company.

In seeking public comment on this concept of operational independence, EPA particularly is interested in comments regarding the degree to which this concept could unnecessarily open up the SVM standards to several sm aller manufacturers that are inte grated into large companies – smaller companies that may be capable of and planning to meet the CO 2 standards as part of the larger manufacturer’s fleet. EPA also seeks co mment on the concern that manufacturers could change their corporate structure to take advantage of such provisions (that is, gaming). EPA is therefore requesting comment on approaches, described below, to narrowly define the

217 For other programs, the eligibility cut point for SVM flexibility is 15,000 vehicles rather than 5,000 vehicles.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 225 of 768 operational independence criteria to ensure that qualifying companies are truly independent and to avoid gaming to meet the criteria. EPA also requests comments on the possible implications of this approach on market competition, which we believe should be fully explored through the public comment process. EPA acknowledges that regardless of the criteria for operational independence, a small manufacturer under the umbrella of a large manufacturer is fundamentally different from other SVMs because the large manufacturer has several options under the GHG program to bring the smaller subsidiary into compliance, including the use of averaging or credit transfer provisions, purchasing credits from another manufacturer, or providing technical and financial assistance to the smaller subsidiary. Tr uly independent SVMs do not have the potential access to these options, with the exception of buying credits from another manufacturer. EPA requests comments on the need for and appropriateness of allowing companies to apply for less stringent SVM standards based on sales that are not aggregated with other companies because of operational independence.

EPA is considering and requesting comments on the operational independence criteria listed below. These criteria are meant to establish that a company, though owned by another manufacturer, does not benefit operationally or financially from this relationship, and should therefore be considered independent for purposes of calculating the sales volume for the SVM program. Manufacturers would need to demonstrat e compliance with all of these criteria in order to be found to be operationally independent. By “related manufacturers” below, EPA means all manufacturers that would be aggregated together under the 10 percent ownership provisions contained in EPA’s current small volume manufacturer definition (i.e., the parent company and all subsidiaries where there is 10 percent or greater ownership).

EPA would need to determine, based on the info rmation provided by the manufacturer in its application, that the manufacturer currently meets the following criteria and has met them for at least 24 months preceding the application submittal:

1. No financial or other support of economic value was provided by related manufacturers for purposes of design, parts procurement, R&D and production facilities and operation. Any other transactions with related manufacturers must be conducted under normal commercial arrangements like those conducted with other parties. Any such transactions shall be at competitive pricin g rates to the manufacturer.

2. Maintains separate and independent research and development, testing, and production
facilities.

3. Does not use any vehicle powertrains or platforms developed or produced by related
manufacturers.

4. Patents are not held jointly with related manufacturers.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 226 of 768 5. Maintains separate business administration, legal, purchasing, sales, and marketing departments; maintains autonomous decision making on commercial matters.

6. Overlap of Board of Directors is limited to 25 percent with no sharing of top operational management, including president, chief executive officer (CEO), chief financial officer (CFO), and chief operating officer (COO), a nd provided that no individual overlapping director or combination of overlapping direct ors exercises exclusive management control over either or both companies.

7. Parts or components supply agreements between related companies must be established through open market process and to the extent that manufacturer sells parts/components to non-related auto manufacturers, it does so through the open market at competitive pricing.

In addition to the criteria listed above, EPA also requests comments on the following programmatic elements and framework. EPA requests comments on requiring the manufacturer applying for operational independence to provide an attest engagement from an independent auditor verifying the accuracy of the in formation provided in the application. 218 EPA foresees possible difficulty verifying the information in the application, especially if the company is located oversees. The principal purpose of the attest engagement would be to provide an independent review and verification of the information provided. EPA also would require that the application be signed by the company president or CEO. After EPA approval, the manufacturer would be required to report within 60 days any material changes to the information provided in the application. A manufacturer wo uld lose eligibility automatically after the material change occurs. However, EPA would confirm that the manufacturer no longer meets one or more of the criteria and thus is no longer considered operationally independent, and would notify the manufacturer. EPA would provide two model years lead time for the manufacturer to transition to the primary program. For example, if the manufactur er lost eligibility sometime in calendar year 2018 (based on when the material change occurs), the manufacturer would need to meet primary program standards in MY 2021.

In addition, EPA requests comments on whether or not a manufacturer losing eligibility should be able to re-establish itself as operationa lly independent in a future year and over what period of time they would need to meet the criter ia to again be eligible. EPA requests comments on, for example, whether or not a manufacturer meeting the criteria for three to five consecutive years should be allowed to again be considered operationally independent.

218 EPA has required attest engagements as part of its Reformulated Fuels program. See 40 CFR § 80.1164 and

§ 80.1464.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 227 of 768 6. Nitrous Oxide, Methane, and CO2-equivalent Approaches

a. Standards and Flexibility

For light-duty vehicles, as part of the MY 2012–2016 rulemaking, EPA finalized standards for nitrous oxide (N 2 O) of 0.010 g/mile and methane (CH 4 ) of 0.030 g/mile for MY 2012 and later vehicles. 75 FR at 25421–24. The light-duty vehicle standards for N 2 O and CH 4 were established to cap emissions, where current levels are generally significantly below the cap. The cap would prevent future emissions increases, and were generally not expected to result in the application of new technologie s or significant costs for the manufacturers for current vehicle designs. EPA also finalized an alternative CO 2 equivalent standard option, which manufacturers may choose to use in lieu of complying with the N 2 O and CH 4 cap standards. The CO 2 - equivalent standard option allows manufacturers to fold all 2-cycle weighted N 2 O and CH 4 emissions, on a CO 2 -equivalent basis, along with CO 2 into their CO 2 emissions fleet average compliance level. 219 The applicable CO 2 fleet average standard is not adjusted to account for the
addition of N 2 O and CH 4 . For flexible fueled vehicles, the N 2 O and CH 4 standards must be met on both fuels (e.g., both gasoline and E–85).

After the light-duty standards were finalized, manufacturers raised concerns that for a few of the vehicle models in their existing fleet they were having difficulty meeting the N 2 O
and/or CH 4 standards, in the near-term. In such cas es, manufacturers would still have the option of complying using the CO 2 equivalent alternative. On a CO 2 equivalent basis, folding in all

N 2 O and CH 4 emissions could add up to 3–4 g/mile to a manufacturer’s overall fleet-average

CO 2 emissions level because the alternative standard must be used for the entire fleet, not just for the problem vehicles. The 3-4 gm/mile assumes all emissions are actually at the level of the cap. See 75 FR at 74211. This could be especially challenging in the early years of the program for manufacturers with little compliance margin because there is very limited lead time to develop strategies to address these additional emissions. Some manufacturers believe that the current

CO 2 -equivalent fleet-wide option “penalizes” them by requiring them to fold in both CH 4 and

N 2 O emissions for their entire fleet, even if they have difficulty meeting the cap on only one
vehicle model.

In response to these concerns, as part of the heavy-duty GHG rulemaking, EPA requested comment on and finalized provisions allowing manufacturers to use CO 2 credits, on a CO 2 -

219 The global warming potentials (GWP) used in this rule are consistent with the 100-year time frame values in the 2007 Intergovernmental Panel on Climate Change (IPCC) F ourth Assessment Report (AR4). At this time, the 100- year GWP values from the 1996 IPCC Second Assessment Report (SAR) are used in the official U.S. greenhouse gas inventory submission to the United Nations Framew ork Convention on Climate Change (per the reporting requirements under that international conventi on, which were last updated in 2006) . N 2 O has a 100-year GWP of
298 and CH 4 has a 100-year GWP of 25 according to the 2007 IPCC AR4.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 228 of 768 equivalent basis, to meet the light-duty N 2 O and CH 4 standards. 220 Manufacturers have the option of using CO 2 credits to meet N 2 O and CH 4 standards on a test group basis as needed for MYs 2012-2016. In their public comments to the proposal in the heavy-duty package, manufacturers urged EPA to extend this flexibility indefinitely, as they believed this option was more advantageous than the CO 2 -equivalent fleet wide option (discussed previously) already provided in the light-duty program, because it allowed manufacturers to address N 2 O and CH 4 separately and on a test group basis, rather than across their whole fleet. Further, manufacturers believed that since this option is allowed under the heavy-duty standards, allowing it indefinitely in the light-duty program would make the light- and heavy-duty programs more consistent. In the Final Rule for Heavy-Duty Vehicles, EPA noted that it would consider this issue further in the context of new standards for MYs 2017-2025 in the planned future light-duty vehicle rulemaking. 76 FR at 57194.

EPA has further considered this issue and is proposing to allow the additional option of using CO 2 credits to meet the light-duty vehicle N 2 O and CH 4 standards to extend for all model years beyond MY 2016. EPA understands manufacturer concerns that if they use the CO 2 - equivalent option for meeting the GHG standards, they would be penalized by having to incorporate all N 2 O and CH 4 emissions across their entire fleet into their CO 2 -equivalent fleet
emissions level determination. EPA c ontinues to believe that allowing CO 2 credits to meet CH 4 and N 2 O standards on a CO 2 equivalent basis is a reasonable approach to provide additional flexibility without diminishing overall GHG emissions reductions.

EPA is also requesting comments on making an adjustment to the CO 2 -equivalent standard for manufacturers selecting the CO 2 -equivalent option established in the MY 2012-2016 rulemaking. Manufacturers would continue to be required to fold in all of their CH 4 and N 2 O emissions, along with CO 2 , into their CO 2 -equivalent levels. The purpose of this adjustment would be to ensure manufacturers do not have to offset the typical N 2 O and CH 4 vehicle emissions, while effectively holding manufacturers responsible for higher than average N 2 O and

CH 4 emissions levels. For example, if the adjustment for CH 4 and N 2 O combined was 1 to 2 g/mile CO2 equivalent (takin g into account the GWP of N 2 O and CH 4 ), manufacturers would
determine their CO 2 fleet emissions standard and add the 1 to 2 g/mile adjustment factor to it to
determine their CO 2 -equivalent standard. EPA continues to believe that it would not be appropriate to base the adjustment on the cap standards because such an approach could have the effect of undermining the stringency of the CO 2 standards, as many vehicles would likely have

CH 4 and N 2 O levels much lower than the cap standard s. EPA believes that if an appropriate adjustment could be developed and applied, it would help alleviate manufacturers concerns
discussed above and make the CO 2 -equivalent approach a more viable option.

EPA is not proposing an adjustment, however, due to a current lack of N 2 O test data on which to base the adjustment for N 2 O. As discussed below, EPA and manufacturers are

220 See 76 FR at 57193-94.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 229 of 768 currently evaluating N 2 O measurement equipment and insufficie nt data is available on which to base an appropriate adjustment. For CH 4 , manufacturers currently provide data during certification, and based on current vehicle data an adjustment for CH 4 in the range of 0.14 g/mile appears to be appropriate. 221 EPA requests comments on this concept and requests city and highway cycle N 2 O data on current Tier 2 vehicles which could help serve as the basis for the adjustment.

b. N 2 O Measurement

For the N 2 O standard, EPA finalized provisions in the MY 2012-2016 rule allowing manufacturers to support an application for a ce rtificate by supplying a compliance statement based on good engineering judgment, in lieu of N 2 O test data, through MY 2014. EPA required

N 2 O testing starting with MY 2015. See 75 FR at 25423. This flexibility provided
manufacturers with lead time n eeded to make necessary f acilities changes and install N 2 O measurement equipment.

Since the final rule, manufacturers have raised concerns that the lead-time provided to begin N 2 O measurement is not sufficient, as their research and evaluation of N 2 O measurement instrumentation has involved a greater level of effort than previously expected. There are several analyzers available today for the measurement of N 2 O. Over the last year since the MY 2012- 2016 standards were finalized, EPA has continued to evaluate instruments for N 2 O measurement and now believes instruments not evaluated during the 2012-2016 rulemaking have the potential to provide more precise emissions measurement and believe it would be prudent to provide manufacturers with additional time to evaluate, pr ocure, and install equipment in their test
cells. 222 Therefore, EPA believes that the manufacturer’s concerns about the need for additional lead-time have merit, and is proposing to extend the ability for manufacturers to use compliance statements based on good engineering judgment in lieu of test data through MY 2016. Beginning in MY 2017, manufacturers would be required to measure N 2 O emissions to verify compliance with the standard. This approach, if finalized, will provide the manufacturers with two additional years of lead-time to evaluate, procure, and install N 2 O measurement systems throughout their certification laboratories.

7. Small Entity Exemption (Lieske)

In the MY 2012-2016 rule, EPA exempted entities from the GHG emissions standard, if the entity met the Small Business Administration (SBA) size criteria of a small business as
described in 13 CFR 121.201. 223 This includes both U.S.-based and foreign small entities in

221 Average city/highway cycle CH 4 emissions based on MY2010-2012 gasoline vehicles certification data is about 0.0056 g/mile.

222 “Data from the evaluation of instruments that measure N2O,” Memorandum from Chris Laroo to Docket EPAHQ-OAR-2010-0799.

223 See final regulations at 40 CFR 86.1801-12(j).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 230 of 768 three distinct categories of businesses for light -duty vehicles: small manufacturers, independent commercial importers (ICIs), and alternative fu el vehicle converters. EPA is proposing to continue this exemption for the MY 2017-2025 standards. EPA w ill instead consider appropriate GHG standards for these entities as pa rt of a future regulatory action.

EPA has identified about 17 entities that fit the Small Business Administration (SBA) size criterion of a small business. EPA estimates there currently are approximately four small manufacturers including three electric vehicle small manufacturers that have recently entered the market, eight ICIs, and five alternative fuel vehicl e converters in the light-duty vehicle market. EPA estimates that these small entities comprise less than 0.1 percent of the total light-duty vehicle sales in the U.S., and th erefore the exemption will have a negligible impact on the GHG
emissions reductions from the standards. Furt her detail regarding EPA’s assessment of small businesses is provided in Regulato ry Flexibility Act Section III.J.3.

At least one small business manufacturer, Fisk er Automotive, in discussions with EPA, has suggested that small businesses should have the option of voluntarily opting-in to the GHG
standards. This manufacturer sells electric ve hicles, and sees a potential market for selling
credits to other manufacturers. EPA believes th at there could be several benefits to this approach, as it would allow small businesses an opportunity to generate revenue to offset their technology investments and encourage commercialization of the innovative technology, and it would benefit any manufacturer seeking those cred its to meet their compliance obligations. EPA is proposing to allow small businesses to waive their small entity exemption and opt-in to the GHG standards. Upon opting in, the manufacturer would be subject to all of the requirements that would otherwise be applicable. This wo uld allow small entity manufacturers to earn CO 2 credits under the program, which may be an especially attractive option for the new electric vehicle manufacturers entering the market. EPA proposes to make the opt-in available starting in MY 2014, as the MY 2012, and potentially the MY 2013, certification process will have already occurred by the time this rulemaking is fi nalized. EPA is not proposing to retroactively certify vehicles that have already been produced . However, EPA proposes that manufacturers certifying to the GHG standards for MY 2014 would be eligible to generate credits for vehicles
sold in MY 2012 and MY 2013 based on the number of vehicles sold and the manufacturer’s footprint-based standard under the primary program that would have otherwise applied to the manufacturer if it were a large manufacturer. Th is approach would be similar to that used by EPA for early credits generated in MYs 2009-2011, where manufacturers did not certify vehicles

to CO 2 standards in those years but were able to generate credits. See 75 FR at 25441. EPA believes it is appropriate to provide these credits to small entities, as the credits would be available to large manufacturers producing simila r vehicles, and the credits further encourage manufacturers of advanced technology vehicles such as EVs. In addition to benefiting these small businesses, this option also has the potential to expand the pool of credits available to be purchased by other manufacturers. Note that ma nufacturers waiving their small entity exemptionSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 231 of 768 would be required to meet all aspects of the GHG standards and program requirements across their entire product line.

8. Additional Leadtime Issues

The 2012-2016 GHG vehicle standards include Temporary Leadtime Allowance Alternative Standards (TLAAS) whic h provide alternative standards to certain intermediate sized manufacturers to accommodate two situations: manufacturers which traditionally paid fines instead of complying with CAFE standards, and limited line manufacturers facing special compliance challenges due to less flexibility afforded by averaging, banking and trading. See 75 FR at 25414-416. EPA is not proposing to conti nue this program for MYs 2017-2025. First, the allowance was premised on the need to provide adequate lead time, given the (at the time the rule was finalized) rapidly approaching MY 2012 deadline, and given that manufacturers were transitioning from a CAFE regime that allows fine -paying, to a Clean Air Act regime that does not. That concern is no longer applicable, given that there is ample lead time before the MY 2017 standards. More important, the Temporary Lead Time Allowance was just that – temporary – and EPA provided it to allow manufactur ers to transition to full compliance in later model years. See 75 FR at 25416. EPA is thus not proposing to continue this provision.

In the context of the increasing stringency of standards in the latter phase of the program (e.g., MY 2022-2025), one manufacturer suggested that EPA should consider providing limited line, intermediate volu me manufacturers additional time to phase into the standards. The concern raised is that such limited line manufacturers face unique challenges securing competitive supplier contracts for new technologies, and have fewer vehicle lines to allocate the necessary upfront investment and risk inherent with new technology introduction. This manufacturer believes that as the standards become increasingly stringent in future years requiring the investment of new or advanced technologies, intermediate volume limited line manufacturers may have to pay a premium to gain access to these technologies which would put them at a competitive disadvantage. EPA seeks comment on this issue, and whether there is a need to provide some type of additional leadtime for intermediate volume limited line manufacturers to meet the latter year standards.

9. Police and Emergency Vehicle Exemption from CO 2 Standards

Under EPCA, manufacturers are allowed to ex clude police and other emergency vehicles
from their CAFE fleet and all manufacturers that produce emergency vehicles have historically done so. EPA received comments in the MY 2012-2016 rulemaking that these vehicles should be exempt from the GHG emissi ons standards and EPA committed to further consider the issue in a future rulemaking. 224 After further consideration of this issue in the context of the MY 2017-

224 75 FR 25409Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 232 of 768 2025 standards being proposed, EPA proposes to exempt police and other emergency vehicles
from the CO 2 standards starting in MY 2017. EPA believes it is appropriate to provide an exemption for these vehicles because of the unique features of vehicles designed specifically for law enforcement and emergency response purposes, which have the effect of raising their GHG emissions, as well as for purposes of harmonization with the CAFE program. EPA proposes to exempt vehicles that are excluded under EPCA and NHTSA regulations which define emergency vehicle as “a motor vehicle manufactured primarily for use as an ambulance or combination ambulance-hearse or for use by the United States Government or a State or local government for law enforcement, or for other emergency uses as prescribed by regulation by the Secretary of Transportation.” 225

While these vehicles are covered by the MY 2012-2016 standards, as the CO 2 standards become increasingly more stringent, manufacturer s of these vehicles would likely begin to face significantly greater challenges. The unique featur es of these vehicles result in significant added weight including: heavy-duty suspensions, stabilizer bars, heavy-duty/dual batteries, heavy-duty engine cooling systems, heavier glass, bullet-proof side panels, and high strength sub-frame. Police pursuit vehicles are often equipped w ith specialty steel rims and increased rolling resistance tires designed for high speeds, and un ique engine and transmission calibrations to allow high-power, high-speed chases. Police and emergency vehicles also have features thattend to reduce aerodynamics, such as emergency lights, increased ground clearance, and heavyduty front suspensions.

EPA is concerned that manufacturers may not be able to sufficiently reduce the emissions from these vehicles, and would be faced with a difficult choice of compromising necessary vehicle features or dropping vehicles from their fl eets, as they may not have credits necessary to
cover the excess emissions from these vehicles as standards become more stringent. Without the exemption, there could be situations where a manufacturer is more challenged in meeting the GHG standards simply due to the inclusion of these higher emitting emergency vehicles. Technical feasibility issues go beyond those of other high-performance vehicles and there is a clear public need for law enforcement and emergency vehicles that meet these performance
characteristics as these vehicles must continue to be made available in the market. EPA requests comments on its proposal to exempt emergency vehicles from the 2017-2025 standards.

10. Test Procedures

EPA is considering revising the procedures for measuring fuel economy and calculating average fuel economy for the CAFE program, to account for three impacts on fuel economy not currently included in these procedures – increas es in fuel economy because of increases in efficiency of the air conditioner; increases in fuel economy because of technology improvements that achieve “off-cycle” benefits; and incentives fo r use of certain hybrid technologies in light-

225 49 U.S.C. 32902(e)Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 233 of 768 duty trucks, in the form of increased values assigned for fuel economy. As discussed in section IV. of this proposal, NHTSA would take th ese changes into account in determining the applicable fuel economy standard. In this section, EPA discusses the legal framework for considering these changes, and the mechanisms by which these changes could be implemented. EPA invites comment on all aspects of this concept, and plans to adopt this approach in the final rule if it determines the changes are appropriate after consideration of all comments on these
issues.

These changes would be the same as program elements that are part of EPA’s greenhouse gas performance standards, discussed in sectio n III.B.1 and 2, above. EPA is considering adopting these changes for A/C efficiency and off-cycle technology because they are based on technology improvements that affect real world fuel economy, and the incentives for light-duty trucks will promote greater use of hybrid technology to improve fuel economy in these vehicles. In addition, adoption of these changes would lead to greater coordination between the greenhouse gas program under the CAA and the fuel economy program under EPCA. As discussed below, these three elements would be implemented in the same manner as in the EPA’s greenhouse gas program – a vehicle manufactur er would have the option to generate these fuel economy values for vehicle models that meet the criteria for these “credits,” and to use these values in calculating their fleet average fuel economy.

a. Legal Framework

EPCA provides that:

(c) Testing and calculation procedures. The Administrator [of EPA] shall measure fuel economy for each model and calculate average fuel economy for a manufacturer under testing and calculation procedures prescribed by the Administrator. However ..., the Administrator shall use the same procedures for passenger automobiles the Administrator used for model year 1975 ..., or procedures that give comparable results. 49 USC 32904(c)

Thus, EPA is charged with developing and adopting the procedures used to measure fuel economy for vehicle models and for calculating average fuel economy across a manufacturer's fleet. While this provision provides broad discretion to EPA, it contains an important limitation for the measurement and calculation procedures applicable to passenger automobiles. For passenger automobiles, EPA has to use the same procedures used for model year 1975 automobiles, or procedures that give comparable results. 226 This limitation does not apply to vehicles that are not passenger automobiles. The legislative history explains that:

226 For purposes of this discussion, EPA need not determ ine whether the changes relating to A/C efficiency, offcycle, and light-duty truck hybrids involve changes to pr ocedures that measure fuel economy or procedures for calculating a manufacturer’s average fuel economy. The same provisions apply irrespective of which procedure is atSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 234 of 768 Compliance by a manufacturer with applicable average fuel economy standards is to be determined in accordance with test procedures established by the EPA Administrator. Test procedures so establis hed would be the procedures utilized by the EPA Administrator for model year 1975, or procedures which yield comparable results. The words “or procedures which yield comparable results” are intended to give EPA wide latitude in modifying the 1975 test procedures to achieve procedures that are more accurate or easier to administer, so long as the modified procedure does not have the effect of substantially changing the average fuel economy standards. H. R. REP. No. 94- 340, at 91-92 (1975).

EPA measures fuel economy for the CAFE progr am using two different test procedures – the Federal Test Procedure (FTP) and the Highway Fuel Economy Test (HFET). These procedures originated in the early 1970’s, and were intended to generally represent city and highway driving, respectively. These two tests are commonly referred to as the “2-cycle” test procedures for CAFE. The FTP is also used for measuring compliance with CAA emissions standards for vehicle exhaust. EPA has made various changes to the city and highway fuel economy tests over the years. These have ranged from changes to dynamometers and other mechanical elements of testing, changes in test fuel properties, changes in testing conditions, to changes made in the 1990s when EPA adopted ad ditional test procedures for exhaust emissions testing, called the Supplemental Fe deral Test Procedures (SFTP).

When EPA has made changes to the FTP or HFET, we have evaluated whether it is appropriate to provide for an adjustment to the measured fuel economy results, to comply with the EPCA requirement for passenger cars that the test procedures produce results comparable to the 1975 test procedures. These adjustments are typically referred to as a CAFE or fuel economy test procedure adjustment or adjustment factor. In 1985 EPA evaluated various test procedure changes made since 1975, and applied fuel economy adjustment factors to account for several of the test procedure changes that reduced the measured fuel economy, producing a significant CAFE impact for vehicle manufacturers. 50 FR 27172 (July 1, 1985). EPA defined this significant CAFE impact as any change or group of changes that has at least a one tenth of a mile per gallon impact on CAFE results. Id. at 27173. EPA also concluded in this proceeding that no adjustments would be provided for changes that removed the manufacturer’s ability to take advantage of flexibilities in the test procedure and derive increases in measured fuel economy values which were not the result of design impr ovements or marketing shifts, and which would not result in any improvement in real world fu el economy. EPA likewise concluded that test procedure changes that provided manufacturers with an improved ab ility to achieve increases in measured fuel economy based on real world fuel economy improvements also would not warrant a CAFE adjustment. Id. at 27172, 27174, 27183. EPA adopted retroactive adjustments that had the effect of increasing measured fuel economy (to offset test procedure changes that reduced the

issue. This discussion generally refers to procedures for measuring fuel economy for purposes of convenience, but the same analysis applies whether a measurem ent or calculation procedure is involved.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 235 of 768 measured fuel economy level) but declined to apply retroactive adjustments that reduced fuel

economy.

The D.C. Circuit reviewed two of EPA’s decisi ons on CAFE test procedure adjustments. Center for Auto Safety et al. v. Thomas , 806 F.2d 1071 (1986). First, the Court rejected EPA’s decision to apply only positive retroactive adjust ments, as the appropriate ness of an adjustment did not depend on whether it increased or decreased measured fuel economy results. Second, the Court upheld EPA’s decision to not apply any adju stment for the change in the test setting for road load power. The 1975 test procedure provided a default settin g for road load power, as well as an optional, alternative method that allowed a manufacturer to develop an alternative road load power setting. The road load power setting affected the amount of work that the engine had to perform during the test, hence it affected the amount of fuel consumed during the test and the measured fuel economy. EPA changed the test procedure by replacing the alternative method in the 1975 procedure with a new alternative coast down procedure. Both the original and the replacement alternative procedures were designed to allow manufacturers to obtain the benefit of vehicle changes, such as changes in aerodynamic design, that improved real world fuel economy by reducing the amount of work that the engine needed to perform to move the vehicle. The Center for Auto Safety (CAS) argued that EPA was required to provide a test procedure adjustment for the new alternative coast down procedure as it increased measured fuel economy compared to the values measured for the 1975 fleet. In 1975, almost no manufacturers made use of the then available alternative method, while in later years many manufacturers made use of the option once it was changed to the coast down procedure. CAS argued this amounted to a change in test procedure that did not achieve comparable results, and therefore required a test procedure adjustment. CAS did not contest that the coast down method and the prior alternative method achieved comparable results.

The D.C. Circuit rejected CAS’ arguments, stating that:

The critical fact is that a procedure that credited reductions in a vehicle’s road load power requirements achieved through improved aerodynamic design was available for MY1975 testing, and those manufacturers, however few in number, that found it advantageous to do so, employed that procedure. The manifold intake procedure subsequently became obsolete for other reasons, but its basic function, to measure real improvements in fuel economy through more aerodynamically efficient designs, lived on in the form of the coast down technique for measuring those aerodynamic improvements. We credit the EPA's finding that increases in measured fuel economy because of the lower road load settings obtainable under the coast down method, were increases "likely to be observed on the road," and were not "unrepresentative artifact[s] of the dynamometer test procedure." Such real improvements are exactly what Congress meant to measure when it afforded the EPA flexibility to change testing and calculating procedures. We agree with the EPA that no retroactive adjustment need be made onSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 236 of 768 account of the coast down technique. Center for Auto Safety et al v. EPA, 806 F.2d 1071, 1077 (D.C. Cir. 1986)

Some years later, in 1996, EPA adopted a variety of test procedure changes as part of updating the emissions test procedures to better reflect real world operation and conditions. 61 Fed. Reg. 54852 (October 22, 1996). EPA adopted new test procedures to supplement the FTP,
as well as modifications to the FTP itself. Fo r example, EPA adopted a new supplemental test procedure specifically to address the impact of air conditioner use on exhaust emissions. Since this new test directly addressed the impact of A/C use on emissions, EPA removed the specified A/C horsepower adjustment that had been in the FTP since 1975. Id. at 54864, 54873. Later
EPA determined that there was no need for CA FE adjustments for the overall set of test procedures changes to the FTP, as the net effect of the changes was no significant change in
CAFE results.

As evidenced by this regulatory history, EPA’ s traditional approach is to consider the impact of potential test procedure changes on CAFE results for passenger automobiles and determine if a CAFE adjustment factor is warr anted to meet the requirement that the test procedure produce results comparable to the 1975 test procedure. This involves evaluating the magnitude of the impact on measured fuel economy results. It also involves evaluating whether the change in measured fuel economy reflects real word fuel economy impacts from changes in technology or design, or whether it is an arti fact of the test procedure or test procedure flexibilities such that the change in measured fuel economy does not reflect a real world fuel economy impact.

In this case, allowing credits for improvement s in air conditioner efficiency and off-cycle efficiency for passenger cars would lead to an increase (i.e., improvement) in the fuel economy results for the vehicle model. The impact on fuel economy and CAFE results clearly could be greater than one tenth of a mile per gallon (the le vel that EPA has previously indicated as having a substantial impact). The increase in fuel economy results would reflect real world improvements in fuel economy and not changes that are just artifacts of the test procedure or changes that come from closing a loophole or removing a flexibility in the current test procedure. However, these changes in procedure would not have the “critical fact” that the CAS Court relied upon - the existence of a 1975 test provision that was designed to account for the same kind of fuel economy improvements from changes in A/C or off-cycle efficiency. Under EPA’s traditional approach, these changes would appear to have a significant impact on CAFE results, would reflect real world changes in fuel economy, but would not have a comparable precedent in the 1975 test procedure addressing the impact of these technology changes on fuel economy. EPA’s traditional approach would be expected to lead to a CAFE adjustment factor for passenger cars to account for the impact of these changes.

However, EPA is considering whether a change in approach is appropriate based on the existence of similar EPA provisions for the greenhous e gas emissions procedures and standards.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 237 of 768 In the past, EPA has determined whether a CAFE adjustment factor for passenger cars would be appropriate in a context where manufacturers are subject to a CAFE standard under EPCA and there is no parallel greenhouse gas standard under the CAA. That is not the case here, as MY2017-2025 passenger cars will be subject to both CAFE and greenhouse gas standards. As discussed elsewhere in this Notice, there is a close and direct relationship between the technology to improve fuel economy and the technology to reduce emissions of CO2. The agencies’ joint rulemaking builds upon this technological relationship. As such, EPA is considering whether it is appropriate to consider the impact of a CAFE procedure change in this
broader context standard.

The term “comparable results” is not defined in section 32904(c), and the legislative history indicates that it is intende d to address changes in procedure that result in a substantial change in the average fuel economy standard. As explained above, EPA has considered a change of one-tenth of a mile per gallon as having a substantial impact, based in part on the one tenth of a mile per gallon rounding convention in the statute for CAFE calculations. 48 FR 56526, 56528 fn.14 (December 21, 1983). A change in the procedure that changes fuel economy results to this or a larger degree has the effect of changing the stringency of the CAFE standard, either making it more or less stringent. A change in stringency of the standard changes the burden on the manufacturers, as well as the fuel savings and other benefits to society expected from the standard. A CAFE adjustment factor is designed to account for these impacts.

Here, however, there is a companion EPA standard for greenhouse gas emissions. In this case, the changes would have an impact on the fuel economy results and therefore the stringency of the CAFE standard, but would not appear to have a real world impact on the burden placed on the manufacturers, as the provisions would be the same as provisions in EPA’s greenhouse gas standards. Similarly it would not appear to have a real world impact on the fuel savings and other benefits of the National Program which would remain identical. If that is the case, then it would appear reasonable to interpret section 3 2904(c) in these circumstances as not restricting these changes in procedure for passenger automobiles. The fuel economy results would be considered comparable results to the 1975 procedure as there would not be a substantial impact on real world CAFE stringency and benefits, given the changes in procedure are the same as provisions in EPA’s companion greenhouse gas procedures and standards. EPA invites comment on this approach to interpreting sectio n 32904(c), as well as the view that this would not have a substantial impact on either the burden on manufacturers or the benefits of the National Program.

An alternative interpretation has also been brought to EPA’s attention. Under this interpretation, the change in procedure would be considered within EPA’s broad discretion to prescribe reasonable testing and calculation procedures, as these changes reflect real world improvements in design and accompanying real world improvements in fuel economy. The reference to the 1975 procedures in section 32904(c) would not be seen as a codification of anySummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 238 of 768 specific procedures or fuel economy improvement technologies, but instead is best viewed as a historic reference point. The changes in pr ocedure would reflect real world fuel economy improvements and increase harmonization with EPA’s greenhouse gas program. Since the changes in procedure have an impact on fuel economy results and could have an impact on the stringency of the CAFE standard, EPA could consid er two different approaches to offsetting the change in stringency. In one approach EPA could maintain the stringency of the 2-cycle (FTP and HFET) CAFE standard by adopting a corresponding adjustment factor, ensuring that the stringency in the CAFE standard was not substantially changed by the change in procedure. An
alternative would be for NHTSA to maintain th e stringency of the 2-cycle CAFE standard by increasing that standard’s stringency to offset any reduction in stringency associated with changes that increase fuel economy values. Under this interpretation, this would maintain the level of stringency of the 2-cycle CAFE standard that would be adopted for passenger cars absent the changes in procedure. As with the approach discussed above, this alternative interpretation would be a major change from EPA’s pa st interpretation and practice. In this joint rulemaking the alternative interpretation would apply to changes in procedure that are the same as the companion EPA greenhouse gas program. However, that would not be an important element in this alternative interpretation, which would apply irrespective of the similarity with EPA’s greenhouse gas procedures and standards. EPA invites comment on this alternative interpretation.

The discussion above focuses on the procedures for passenger cars, as section 32904(c) limits changes to the CAFE test and calculation procedures for these automobiles. There is no such limitation on the procedures for light-trucks. The credit provisions for improvements in air conditioner efficiency and off-cy cle performance would apply to light-trucks as well. In addition, the limitation in section 32904(c) does not apply to the provisions for credits for use of hybrids in light-trucks, if certain criteria are me t, as these provisions apply to light-trucks and not passenger automobiles.

b. Implementation of this Approach

As discussed in section IV, NHTSA would take these changes in procedure into account in setting the applicable CAFE standards for pa ssenger cars and light-trucks. As in EPA’s greenhouse gas program, the allowance of AC credits for cars and trucks results in a more stringent CAFE standard than otherwise would apply (although in the CAFE program the AC credits would only be for AC efficiency impr ovements, since refrigerant improvements do not impact fuel economy). The allowance of off-cycle credits has been considered in setting the CAFE standards for passenger car and light-truck s and credits for hybrid use in light pick-up trucks has been considered in setting the CAFE standards for light-trucks, but does not result in any change in the standards.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 239 of 768EPA further discusses the criteria and test procedures for determining AC credits, offcycle technology credits, and hybrid/performance-based credits for full size pickup trucks in
Section III.C below.

C. Additional Manufacturer Compliance Flexibilities

1. Air Conditioning Related Credits

A/C is virtually standard equipment in new cars and trucks today. Over 95% of the new cars and light trucks in the United States are equipped with A/C systems. Given the large number of vehicles with A/C in use in today’s li ght duty vehicle fleet, their impact on the amount of energy consumed and on the amount of refrigerant leakage that occurs due to their use is significant.

EPA proposes that manufacturers be able to comply with their fleetwide average CO 2 standards described above by generating and using credits for improved (A/C) systems. Because such improved A/C technologies tend to be relatively inexpe nsive compared to other GHGreducing technologies, EPA expects that most ma nufacturers would choose to generate and use such A/C compliance credits as a part of their compliance demonstrations. For this reason, EPA has incorporated the projected costs of compliance with A/C related emission reductions into the overall cost analysis for the program. As discussed in section II.F, and III.B.10, EPA, in coordination with NHTSA, is also proposing th at manufacturers be able to include fuel consumption reductions resulting from the use of A/C efficiency improvements in their CAFE compliance calculations. Manufacturers would generate “fuel consumption improvement values” essentially equivalent to EPA CO 2 credits, for use in the CAFE program. The proposed changes to the CAFE program to incorporate A/C efficiency improvements are discussed below
in section III.C.1.b.

As in the 2012-2016 final rule, EPA is structuring the A/C provisions as optional credits for achieving compliance, not as separate standards. That is, unlike standards for N 2 0 and CH 4 , there are no separate GHG standards related to AC related emissions. Instead, EPA provides manufacturers the option to generate A/C GHG emission reductions th at could be used as part of
their CO 2 fleet average compliance demonstrations. As in the 2012-2016 final rule, EPA also included projections of A/C credit generation in determining the appropriate level of the proposed standards. 227

In the time since the analyses supporting the 2012-2016 FRM were completed, EPA has
re-assessed its estimates of overall A/C emission s and the fraction of those emissions that might be controlled by technologi es that are or will be available to manufacturers. 228 As discussed in

227 See Section II.F above and Section IV below for more information on the use of such credits in the CAFE

program. 228 The A/C-related emission inventories presented in this paragraph are discussed in Chapter 4 of the Draft RIA.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 240 of 768 more detail in Chapter 5 of the Joint TSD (see Sec tion 5.1.3.2), the revised estimates remain very
similar to those of the earlier rule. This include s “direct emission” -- the leakage of refrigerant during the vehicle’s useful life, as well as the subsequent leakage associated with maintenance and servicing, and with disposal at the end of th e vehicle’s life. The refrigerant universally used today is HFC-134a with a global warming potential (GWP) of 1,430. 229 Together these leakage emissions are equivalent to CO 2 emissions of 13.8 g/mi for cars and 17.2 g/mi for trucks. (Due to the high GWP of HFC-134a, a small amount of leakage of the refrigerant has a much greater global warming impact than a si milar amount of emissions of CO 2 or other mobile source GHGs.) EPA also estimates that A/C efficien cy-related emissions (also called “indirect” A/C emissions), account for CO 2 –equivalent emissions of 11.9 g/mi for cars and 17.1 g/mi for
trucks. 230 Chapter 5 of the Joint TSD (see Section 5.1.3.2) discusses the derivation of these
estimates.

EPA believes that it is important to addr ess A/C leakage and efficiency emissions because the technologies that manufacturers wo uld otherwise likely employ to reduce vehicle
exhaust CO 2 would have little or no impact on A/C-related emissions. Achieving the reductions from the proposed GHG standards in the most cost-effective ways is a primary goal of the program, and EPA believes that allowing manufacturers to comply by using credits generated from incorporating A/C GHG-reducing technologies is a key factor in meeting that goal. 231 EPA accounts for these reductions in developing the standards (curve targets), and includes these emission reductions in estimating the achieved benefits of the program. See Section II.D above.

Manufacturers can make very feasible improvements to their A/C systems to reduce leakage and increase efficiency. Manufactur ers can reduce A/C leakage emissions by using components that tend to limit or eliminate refrig erant leakage. Also, manufacturers can largely eliminate the global warming impact of leakage emissions by adopting systems that use an alternative, low-GWP refrigerant, acceptable under EPA’s SNAP program, as discussed below, especially if systems are also designed to minimize leakage. 232 Manufacturers can also increase the overall efficiency of the A/C system and thus reduce A/C-related CO 2 emissions. This is because the A/C system contributes to increased CO 2 emissions through the additional work

229 The global warming potentials (GWP) used in this rule are consistent with the 100-year time frame values in the 2007 Intergovernmental Panel on Climate Change (IPCC) F ourth Assessment Report (AR4). At this time, the 1996 IPCC Second Assessment Report (SAR) 100-year GWP values are used in the official U.S. greenhouse gas inventory submission to the United Nations Framework Convention on Climate Change (per the reporting requirements under that international conventi on, which were last updated in 2006) .

230 Indirect emissions are additional CO 2 emitted due to the load of the A/C system on the engine.

231 The recent GHG standards for medium and heavy duty ve hicles included separate standards for A/C leakage, rather than credits. EPA did so because the quantity of these leakage emissions is small relative to CO 2 emissions from driving and moving freight, so that a credit does not create sufficient incentive to adopt leakage controls. 76 FR at 57118; 75 FR at 74211. EPA also did not adopt standards to control A/C leakage from vocational vehicles, and did not adopt standards to control indirect emissi ons from any medium or heavy duty vehicle for reasons explained at 75 FR 74211 and 74212.

232 Refrigerant emissions during service, maintenance, repair, and disposal are also addressed by the CAA Title VI stratospheric ozone program, as described below.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 241 of 768 required to operate the compressor, fans, and blowers. This additional work typically is provided through the engine’s crankshaft, and delivered via belt drive to the alternator (which provides electric energy for powering the fans and blower s) and the A/C compressor (which pressurizes the refrigerant during A/C operation). The additio nal fuel used to supply the power through the crankshaft necessary to operate the A/C system is converted into CO 2 by the engine during
combustion. This incremental CO 2 produced from A/C operation can thus be reduced by increasing the overall efficiency of the vehicl e’s A/C system, which in turn will reduce the additional load on the engine from A/C operation.

As with the earlier GHG rule, EPA is pro posing two separate credit approaches to address leakage reductions and efficiency improvements independently. A leakage reduction credit would take into account the various technologies that could be used to reduce the GHG impact of refrigerant leakage, including the use of an alternative refrigerant with a lower GWP. An efficiency improvement credit would account for the various types of hardware and control of that hardware available to increase the A/C system efficiency. To generate credits toward compliance with the fleet average CO2 standard, ma nufacturers would be required to attest to the durability of the leakage reduction and the efficiency improvement technologies over the full
useful life of the vehicle.

EPA believes that both reducing A/C system leakage and increasing A/C efficiency would be highly cost-effective a nd technologically feasible for light-duty vehicles in the 2017- 2025 timeframe. EPA proposes to maintain mu ch of the existing fram ework for quantifying, generating, and using A/C Leakage Credits and Efficiency Credits. EPA expects that most
manufacturers would choose to use these A/C cr edit provisions, although some may choose not to do so. Consistent with the 2012-2016 final rule, the proposed standard reflects this projected widespread penetration of A/C control technology.

The following table summarizes the maximum credits the EPA proposes to make available in the overall A/C program.

Table III-11 Summary of Maximum Per- Vehicle Credit for A/C (in g/mi)

2012-2016 2017-2025 Direct Max Credit Car Leakage 6.3 6.3 Direct Max Credit Car Alt Refrigerant 13.8 13.8 Direct Max Credit Truck Leakage 7.8 7.8
Direct Max Credit Truck Alt Refrigerant 17.2 17.2

Indirect Max Credit Car 5.7 5
Indirect Max Credit Truck 5.7 7.2Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 242 of 768 The next table shows the credits on a model year basis that EPA projects that manufacturers will generate on average (starting with the ending values from the 2012-2016 final rule). In the 2012-2016 rule, the total average car and total average truck credits accounted for
the difference between the GHG and CAFE standards.

Table III-12 Projected Average Credits

Car Credit leakage

avg Car Credit efficiency

avg Total Car Credit

avg Truck Credit leakage

avg Truck Credit efficiency

avg Total Truck Credit

avg Fleet Avg Combined

Car &
Truck Credit

2016 5.4 4.8 10.2 6.6 4.8 11.5 10.6
2017 7.8 5.0 12.8 7.0 5.0 12.1 12.5
2018 9.3 5.0 14.3 11.0 6.5 17.5 15.5
2019 10.8 5.0 15.8 13.4 7.2 20.6 17.5
2020 12.3 5.0 17.3 15.3 7.2 22.5 19.1
2021 13.8 5.0 18.8 17.2 7.2 24.4 20.7
2022 13.8 5.0 18.8 17.2 7.2 24.4 20.7
2023 13.8 5.0 18.8 17.2 7.2 24.4 20.7
2024 13.8 5.0 18.8 17.2 7.2 24.4 20.7
2025 13.8 5.0 18.8 17.2 7.2 24.4 20.7

The year-on-year progression of credits was determined as follows. The credits are assumed to increase starting from their MY 20 16 value at a rate approximately commensurate with the increasing stringency of the 2017-2025 GHG standards, but never exceeding a 20% penetration rate increase in any given year, un til the maximum credits are achieved by 2021 at the earliest. This 20%/per year limit is consis tent with EPA’s expectation that manufacturers would be changing over to alternative refrigerants only at the time of complete vehicle redesign, which occurs about every 5 years. Given the significant number of credits and benefits of low GWP refrigerants, EPA believes that a total phase in of alternative refrigerants is likely by 2021 (as shown in Table III-12 above). EPA requests comment on our assumptions for the phase-in rate for the alternative refrigerant.

The progression of the average credits (relative to the maximum) also defines the relative year-on-year costs as described in Chapter 3 of the Joint TSD. The costs are proportioned by the ratio of the average credit in any given year to the maximum credit. This is nearly equivalent to proportioning costs to technology penetration rates as is done for all the other technologies. However because the maximum efficiency credits for cars and trucks have changed since theSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 243 of 768 2012-2016 rule, proportioning to the credits provides a more realistic and smoother year-on-year sequencing of costs. 233

EPA seeks comment on all aspects of the A/C credit program, including changes from the current A/C credit program and th e details in the Joint TSD.

a. Air Conditioning Leakage (“Di rect”) Emissions and Credits

i. Quantifying A/C Leakage Credits for Today’s Refrigerant

As previously discussed, EPA proposes to continue the existing leakage credit program, with minor modifications. Although in general EPA continues to prefer performance-based standards whenever possible, A/C leakage is very difficult to accurately measure in a laboratory test, due to the typical slowness of such leaks and the tendency of leakage to develop unexpectedly as vehicles age. At this time, no appropriate performance test for refrigerant leakage is available. Thus, as in the existing MYs 2012-2016 program, EPA would associate each available leakage-reduction technology with associated leakage credit value, which would be added together to qu antify the overall system credit, up to the maximum available credit. EPA’s Leakage Credit method is drawn from the SAE J2727 method (HFC-134a Mobile Air Conditioning System Refrigerant Emission Chart, August 2008 version), which in turn was based on results from the cooperative “IMAC” study. 234 EPA is proposing to incorporate several minor modifications that SAE is making to the J2727 method, but these do not affect the proposed credit values for the technologies. Chap ter 5 of the joint TSD includes a full discussion of why EPA is proposing to continue the design-based “menu” approach to quantifying Leakage Credits, including definitions of e ach of the technologies associated with the values in the menu.

In addition to the above “menu” for vehicles using the current high-GWP refrigerant (HFC-134a), EPA also proposes to continue to pr ovide the leakage credit calculation for vehicles using an alternative, lower-GWP refrigerant. This provision was also a part of the MYs2012- 2016 rule. As with the earlier rule, the agency is including this provision because shifting to lower-GWP alternative refrigeran ts (such as HFO-1234yf, or CO 2 as a refrigerant) would eliminate much of the climate-change concern about HFC-134a refrigerant leakage by reducing the direct climate impacts. Thus, the credit a ma nufacturer could generate is a function of the degree to which the GWP of an alte rnative refrigerant is less than that of the current refrigerant (HFC-134a).

In the earlier GHG rule, a manufacturer using an alternative refrigerant would receive no credit for leakage-reduction technologies. At that time, EPA believed that from the perspective

233 In contrast, the technology penetratio n rates could have anomalous (and unrea listic) discontinuities that would be reflected in the cost progressions. This issue is only specific to A/C credits and costs and not to any other technology analysis in this proposal.

234 [spell out and reference IMAC study.]Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 244 of 768 of primary climate effect, leakage of a very low GWP refrigerant is largely irrelevant. However, there is reason to believe that the need for repeated recharging (top-off) of A/C systems with what would likely be a more costly refrigerant co uld lead some consumers and/or repair facilities to recharge a system designed for use with HFO-1234yf with either HFC-134a or another high GWP refrigerant. Since, as discussed below, EPA believes that systems designed for HFO1234yf could operate feasibly, although not ideally, on HFC-134a, the need for repeated recharging in use could slow the transition away from the high-GWP refrigerant even if such recharging is not authorized under current regulations. 235

Thus, for alternative refrigerant systems, EPA is proposing to add to the existing credit calculation approach for alternative-refriger ant systems a provision that would provide a
disincentive for manufacturers if systems designed to operate with HFO-1234yf incorporated fewer leakage-reduction technologies. A system with higher annual leakage could then be recharged with HFC-134a or another refrigerant with a GWP higher than that of HFO-1234yf.Some stakeholders have suggested that EPA take precautions to address the potential for HFC134a to replace HFO-1234yf in vehicles designed for use with the new refrigerant ( see comment and response section of EPA’s SNAP rule on HFO-1234yf

, 76 FR 17509; March 29, 2011). 236
In EPA’s proposed disincentive provision, manufacturers would avoid some or all of a deduction in their Leakage Credit of about 2 g/mi by main taining the use of low-leak components after a transition to an alternative refrigerant.

ii. Issues Raised by a Potential Broad Tr ansition to an Alternative Refrigerant

As described previously, use of alternative, lower-GWP refrigerants for mobile use reduces the climate effects of leakage or release of refrigerant through the entire life-cycle of the A/C system. Because the impact of direct emissions of such refrigerants on climate is significantly less than for the current refrigerant HFC-134a, release of these refrigerants into the atmosphere through direct leakage, as well as release due to maintenance or vehicle scrappage, is predictably less of a concern than with the current refrigerant. As discussed above, there remainsa concern, even with a low-GWP refrigerant, that some repairs may repeatedly replace the lowerGWP refrigerant from a leaky A/C system with the less-costly high-GWP refrigerant.

For a number of years, the automotive industry has explored lower-GWP refrigerants and the systems required for them to operate effectively and efficiently, taking into account refrigerant costs, toxicity, flammability, envir onmental impacts, and A/C system costs, weight, complexity, and efficiency. European Union regulations require a transition to alternative refrigerants with a GWP of 150 or less for motor vehicle air conditioning. The European

235 See appendix D to 40 CFR part 82, subpart G

236 Regulations in Appendix D to Subpart G of 40 CFR part 82 prohibit topping off the refrigerant in a motor vehicle A/C system with a different refrigerantSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 245 of 768 Union’s Directive on mobile air-co nditioning systems (MAC Directive 237 ) aims at reducing emissions of specific fluorinated greenhouse ga ses in the air-conditioning systems fitted to passenger cars (vehicles under EU category M1) and light commercial vehicles (EU category N1, class 1).

The main objectives of the EU MAC Directive are: to control of leakage of fluorinated greenhouse gases with a global warming potential (GWP) higher than 150 used in this sector; and to prohibit by a specified date the use of higher GWP refrigerants in MACs. The MAC Directive is part of the European Union’s overall objectives to meet commitments made under the UNFCCC’s Kyoto Protocol. This transition starts with new car models in 2011 and continues with a complete transition to manufact uring all new cars with low GWP refrigerant by January 1, 2017.

In recent years, the global industry has given serious attention to HFC-152a and to carbondioxide (R-744) as alternative refrigerants. Work on additional alternatives continues. HFC152a (1,1-difluoroethane) has a GWP of 124 and CO 2 has a GWP of 1. 238 However, vehicle manufacturers have been reluctant to adopt these alternative refrigerants, for several reasons. In the case of HFC-152a, the refrigerant is flammable, listed as A2 by ASHRAE. 239 Air conditioning systems using this refrigerant would require significant redesign or adding complex engineering strategies or devices in order to redu ce flammability risks to acceptable levels (e.g., use of release valves or secondary-loop systems). Air conditioning systems using CO 2 would also require significant redesign due to higher operating pressures required. In confidential meetings EPA has held with manufacturers since the MYs 2012-2016 final rule, no manufacturer has indicated to EPA that they are currently pl anning to introduce either of these alternative refrigerants in vehicles for the U.S. market.

However, one alternative refrigerant has genera ted significant interest in the automobile manufacturing industry and it appears likely to be used broadly in the near future for this application. This refrigerant, called HFO-1234yf (2,3,3,3-tetrafluoropropene) 240 , has a GWP of 4, an ODP of zero, is slightly flammable, and has been assigned an A2L flammability classification by ASHRAE. General Motors announ ced in 2010 its intent to begin manufacturing some car models using HFO-1234yf beginning with model year 2013. 241

237 2006/40/EC

238 IPCC 4 th Assessment Report

239 A wide range of concentrations has been reported for HFC–152a flammability where the gas poses a risk of ignition and fire (3.7%–20% by volume in air) (Wilson, 2002). EPA finalized a rule in 2008 listing HFC-152a as acceptable subject to use conditions in motor vehicle air-conditioning, one of these restricting refrigerant concentrations in the passenger compartment resulting from leaks above the lower flammability limit of 3.7% ( see 71 FR 33304; June 12, 2008).

240 Chemical Abstracts Service Registry Number (CAS Reg. No.) 754-12-1

241 General Motors (2010), GM First to market Greenhouse Gas-friendly Air Conditioning Refrigerant in the U.S. July 23, 2010 press release. A copy can be found at: http://media.gm.com/content/media/us/en/news/news_deta il.brand_gm.html/content/Pages /news/us/en/2010/July/07 23_refrigerantSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 246 of 768 The physical and thermodynamic properties of this refrigerant are similar enough to
HFC-134a that auto manufacturers need to make relatively minor technological changes to their vehicle A/C systems in order to manufacture and market vehicles capable of using HFO-1234yf. Both compounds have similar boiling points and si milar critical points -- boiling points of -29 °C for HFO-1234yf and -26 °C for HFC-134a and critical points 242 of 95°C and 102°C respectively for HFO-1234yf and HFC-134a. 243 The cooling capacity and coefficient of performance of HFO-1234yf is generally within 5% of that of HFC-134a. 244 Although HFO-1234yf is flammable, it requires a high amount of energy to ignite (5,000 mJ to 10,000 mJ), has a low flame speed (1.5 cm/s), and is expected to ha ve flammability risks that are not significantly different from those of HFC-134a or other refrig erants found acceptable subject to use conditions (76 FR 17494-17496, 17507; March 29, 2011).

There are some drawbacks to the use of HFO-1234yf. Some technological changes are necessary to use HFO-1234yf, i.e., addition of an internal heat exchanger in the A/C system. In addition, the anticipated cost of HFO-1234yf is several times that of HFC-134a. At the time that EPA’s Significant New Alternatives Policy (SNAP ) program issued its determination allowing the use of HFO-1234yf in motor vehicle A/C systems, the agency cited estimated costs of $40 to $60 per pound, and stated that this range was confirmed by an automobile manufacturer (76 FR 17491; March 29, 2011) and a component supplier. 245 By comparison, HFC-134a currently costs about $2 to $4 per pound. 246 The higher cost of HFO-1234yf is largely because of limited global production capability at this time. Howeve r, because it is more complicated to produce the molecule for HFO-1234yf, it is unlikely that it will ever be as inexpensive as HFC-134a is currently. In Chapter 5 of the TSD (see Section 5.1.4), the EPA has accounted for this additional cost of both the refrigerant as well as the hardware upgrades.

242 Above the critical point, distinct liquid and gas phases do not exist.

243 Dupont Frequently Asked Questions about OpteonTMyf Refrigerants: http://www2.dupont.com/Refrigerants/en_U S/uses_apps/automotive_ac/SmartAutoA C/faqs.html#char ). The vapor pressure of the two refrigerants is within a few percentage points of each other in the normal range of temperatures for air conditioning (roughly 2% difference at 25 °C-- Dupont Frequently Asked Questions about OpteonTMyf Refrigerants

244 HFO-1234yf Low GWP Refrigerant LCCP Analysis - presentation by Mary Koban, DuPont at SAE 2009 World Congress. Available at http://www.regulations.g ov/#!documentDetail;D=EPA-HQ-OAR-2008-0664-0205

245 Automotive News, April 18,2011.21.

246 Ibid.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 247 of 768 (1) Related EPA Actions to Date and Potential Actions Concerning Alternative Refrigerants

EPA is addressing potential environmental and human health concerns of low-GWP alternative refrigerants through a number of actions. The SNAP program has issued final rules regulating the use of HFC-152a and HFO-1234yf in order to reduce their potential risks (June 12, 2008, 73 FR 33304; March 29, 2010, 76 FR 17488). The SNAP rule for HFC-152a allows its use in new motor vehicle A/C systems where proper engineering strategies and/or safety devices are incorporated into the system. The SNAP rules for both HFC-152a and HFO-1234yf require meeting safety requirements of the industry standard SAE J639. With both refrigerants, EPA expects that manufacturers conduct and keep on file failure mode and effect analysis for the motor vehicle A/C system, as stated in SAE J17 39. EPA has also proposed a rule that would allow use of carbon dioxide as a refrigerant s ubject to use conditions for motor vehicle A/C systems (September 21, 2006; 71 FR 55140). EPA expects to finalize a rule for use of carbon dioxide in motor vehicle A/C systems in 2012, however we are not basing our alternative refrigerant analysis on the availability or feasibility of this specific refrigerant.

Under Section 612(d) of the Clean Air Act, any person may petition EPA to add alternatives to or remove them from the list of acceptable substitutes for ozone depleting substances. The National Resource Defense Council (NRDC) submitted a petition on behalf of NRDC, the Institute for Governance & Sustainable Development (IGSD), and the Environmental Investigation Agency-US (EIA-US) to EPA under Clean Air Act Section 612(d), requesting that the Agency remove HFC-134a from the list of acceptable substitutes and add it to the list of unacceptable (prohibited) substitutes for motor vehicle A/C, among other uses. 247 EPA has found this petition complete specifically for use of HFC-134a in new motor vehicle A/C systems for use in passenger cars and light duty vehicles. EPA intends to initiate a separate notice and comment rulemaking in response to this petition in the future.

EPA has also addressed potential toxicity i ssues with HFO-1234yf through a significant new use rule (SNUR) under the Toxic Substanc es Control Act (TSCA) (October 27, 2010; 75 FR 65987). Under the SNUR, manufacturers, importers and processors of substances subject to a SNUR must notify EPA at least 90 days befo re beginning any designated significant new use through a significant new use notice (SNUN). EPA has 90 days from the date of submission of a SNUN to decide whether the new use ``may present an unreasonable risk'' to human health or the environment. If the Agency does not determine that the new use ``may present an unreasonable risk,'' the submitter would be allowed to engage in the use, with or without certain restrictions. The significant new uses identified in the SNUR for HFO-1234yf are:

247 NRDC et al. Re: Petition to Remove HFC-134a from the List of Acceptable Substitutes under the Significant New Alternatives Policy Program (November 16, 2010)Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 248 of 768 (1) use other than as a refrigerant in motor vehicle air conditioning systems in new passenger cars and vehicles; (2) commercial use other than in new passenger cars and vehicles in which the charging of motor vehicle air conditioning systems with HFO-1234yf was done by the motor vehicle OEM; and (3) distribution in commerce of products intended for use by a consumer for the purposes of servicing, maintenance and disposal involving HFO-1234yf. 248

In summary, the SNUR for HFO-1234yf allows its use as an A/C refrigerant for new passenger cars and vehicles, and found no sign ificant toxicity issues with that use.

One of the manufacturers of HFO-1234yf has petitioned EPA to exempt it from the definition of “volatile orga nic compound” (VOC) under CAA regulations (see 40 CFR 51.100(s)) addressing the development of State Implementation Plans (SIPs) to attain and maintain the national ambient air quality standard s. VOCs are a class of compounds that can contribute to ground level ozone, or smog, in the presence of sunlight. Some organic compounds do not react enough with sunlight to create si gnificant amounts of smog. EPA has alreadydetermined that a number of compounds, including the current automotive refrigerant, HFC134a, are low enough in photochemical reactivity that they do not need to be regulated under SIPs. The manufacturer has provided information to EPA, showing that HFO-1234yf, although more reactive than HFC-134a, is still low enough in reactivity that it is not likely to contribute significantly to local air quality problems from ground-level ozone. EPA has issued a proposed rule, proposing to exempt HFO-1234yf from the definition of VOC for purposes of preparing State implementation plans (SIPs) to attain the national ambient air quality standards for ozone under Title I of the Clean Air Act (insert date, 2011; 76 FR XXXXX).

Further, EPA has considered a peer-reviewed study by Luecken et al. (2010) 249 , in which, among other things, potential air quality impacts from generation of ground-level ozone were modeled using a regional-scale 3-dimensional at mospheric model. This study found that, if 2,3,3,3-tetrafluoropropene (HFO-1234yf) was only emitted from automobiles and degraded in the atmosphere, the incremental amount of ozone formed was only 0.01% of total ozone formed during the simulation. Also, while the modeled concentrations of deposited trifluoroacetic acid, a product of atmospheric degradation, from the use of 2,3,3,3-tetrafluoropropene in automobiles were well below levels of concern for aquatic toxicity, its potential for long-term accumulation
in water bodies is still somewhat uncertain. Thus, the additional information from this study shows that 2,3,3,3-tetrafluoropr opene does produce ozone, but the amount will likely not have a

248 The last of these significant new uses is intended to protect against potentially excessively high exposure levels that could occur if consumers attempt to service their own car’s A/C system.

249 D. Luecken, R. Waterland, S. Papasavva, K. Taddonio, W. Hutzell, J. Rugh, and S. Andersen. Ozone and TFA Impacts in North America from Degradation of 2,3,3,3- Tetrafluoropropene (HFO-1234yf), A Potential Greenhouse Gas Replacement. Environ. Sci. Technol. 44, pp. 343-349.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 249 of 768 significant impact on local air quality under curr ent conditions, although some questions remain about usage trends and effects in the future.

(2) Vehicle Technology Requirements for HFO-1234yf

As described by vehicle manufacturers, A/C systems for use with HFO-1234yf wouldneed a limited amount of additional hardware to maintain cooling efficiency compared to HFC134a. In particular, A/C systems would require a different internal heat exchanger to use HFO1234yf. Because HFO-1234yf would be less effective in A/C systems not designed for its use, and because EPA’s SNAP ruling allows only for its use in new vehicles, we expect that manufacturers will introduce cars using HFO-1234yf only during complete vehicle redesigns or when introducing new models. 250 The same would be true for ot her alternative refrigerants that are potential candidates (e.g., HFC-152a). This need for complete vehicle redesign limits the pace of a transition from HFC-134a to alternative re frigerants. In meetings with the OEMs, the manufacturers have informed EPA that their vehicle manufacturing plants must also upgrade their refrigerant storage facilities and charging stations on the assembly line. During the transition period between the refrigerants, some of these assembly lines may need to have the infrastructure for both refrigera nts simultaneously since many lines produce multiple vehicle models. Moreover, many of these plants may not have the facilities, nor the space for two refrigerant infrastructures, thus likely further increasing necessary lead time. EPA took these factors into account in estimating the penetration of alternative refrigerant, and the resulting estimated average credit rate shown in Table III-12.

Switching to alternative refrig erants in the U.S. market continues to be attractive to automobile manufacturers because vehicles with low GWP refrigerant would qualify for the maximum leakage credit. This compliance option is greatly desired or in some cases may be needed by some manufacturers for compliance with GHG emission standards as the best approach for their fleet in 2017.

(3) Alternative Refrigerant Supply

EPA is aware that another practical factor a ffecting the rate of tr ansition to alternative refrigerants is their supply. In particular, for the alternative of greatest interest to automobile manufacturers, HFO-1234yf, there are currentl y two major producers of HFO-1234yf, DuPont and Honeywell, that are licensed to produce this chemical for the U.S. market. Currently, both companies are providing most of their production from a single overseas facility, as well as some production from small pilot plants. The initial emphasis for these companies is to provide HFO-

250 Some suppliers and manufacturers have informed us that some vehicles may be able to upgrade A/C systems during a refresh of an existing model (between redesign year s). However, this is highly dependent on the vehicle, space constraints behind the dashboard, a nd the manufacturing plant, so an upgrade may be feasible for only a select few models.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 250 of 768 1234yf to the European market, where regulato ry requirements for low GWP refrigerants are already in effect. These same companies have indicated that they plan to construct a new facility in the 2014 timeframe and intend to issue a formal announcement about that facility close to the end of this calendar year. This facility shoul d be designed to provide sufficient production volume for a worldwide market in coming years. EPA expects that the speed of the transition in the U.S. will depend on how rapidly chemical manu facturers are able to provide the amount of alternative refrigerant supply to automobile manufacturers that woul d allow most or all vehicles
sold in the U.S. to be built using alternative refrigerant.

One manufacturer (GM) has announced its intention to begin introducing vehicle models using HFO-1234yf as early as MY 2013. 251 EPA is not aware of other companies that have made a public commitment about early adoption of the new refrigerant. As described above, we expect that in most cases a change-over to systems designed for HFO-1234yf will be limited to vehicle product redesign cycles, typically about every 5 years. Because of this, the pace of introduction is likely to be lim ited to about 20% of a manufacturer’ s fleet per year. In addition, the current uncertainty about the availability of supply of the new refrigerant in the early years of introduction into vehicles in the U.S. vehicles, also discussed above, means that the change-over may not occur at every vehicle redesign point. Thus, even with the announced intention of this one manufacturer to begin early introduction of the new refrigerant, EPA’s analysis of the overall industry trend will assume minimal penetration of the U.S. vehicle market before MY

2017.

Table III-12 shows that, starting from MY 2017, virtually all of the expected increase in generated credits would be due to a gradual increase in penetration of HFO-1234yf. In earlier model years, EPA attributes the expected incr ease in Leakage Credits to improvements in lowleak technologies.

(4) Projected Potential Scenarios for Auto Industry Changeover to HFO1234yf

As discussed above, EPA is planning on issuing a proposed SNAP rulemaking in the future requesting comment on whether to move HFC-134a from the list of acceptable substitutes to the list of unacceptable (prohibited) substitutes. However, the agency has not determined the specific content of that proposal, and the results of any final action are unknowable at this time. EPA recognizes that a major element of that propos al will be the evaluation of the time needed for a transition for automobile manufacturers away from HFC-134a. Thus, there could be multiple scenarios for the timing of a transition c onsidered in that future proposed rulemaking.

251 General Motors Press Release, July 23, 2010. “GM Fi rst to Market Greenhouse Gas-Friendly Air Conditioning Refrigerant in U.S.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 251 of 768 Should EPA finalize a rule under the SNAP program that prohibits the use of HFC-134a in new vehicles, the agency plans to evaluate the impacts of such a SNAP rule to determine whether it would be necessary to consider revisions to the availability and use of the compliance credit for

MY 2017-2025.

For purposes of this proposed GHG rule, EPA is assuming the current status, where there are no U.S. regulatory requirements for manufacturers to eliminate the use of HFC-134a for newly manufactured vehicles. Thus, the agency would expect that the market penetration of alternatives -- presumably HFO-1234yf--will proceed based on supply and demand and the strong incentives in this proposal. Given the combination of a clear interest of manufacturers in switching to an alternative refrigerant, such as HFO-1234yf, and the interest of the manufacturers of the refrigerant to expand their capacity to produce and market the refrigerant,
EPA believes it is reasonable to project that supply would be adequate to support the orderly rate of transition to an alternative refrigerant described above. EPA recognizes that some automobile manufacturers will likely use HFO-1234yf in the next several years. For example (as mentioned earlier) at least one U.S. manufacturer already has plans to introduce models using HFO-1234yf beginning in MY 2013. However, it is not cer tain how widespread the transition to a new refrigerant will be in the U.S ., nor how quickly that transitio n will occur in the absence of requirements or strong incentives.

There are other situations that could lead to an overall fleet changeover from HFC-134a to alternative refrigerants. For example, the governments of the U.S., Canada, and Mexico have proposed to the Parties to the Montreal Protocol on Substances that Deplete the Ozone Layer that production of HFCs be reduced over time. The North American Proposal to amend the Montreal Protocol allows the global community to make near-term progress on climate change by addressing this group of potent greenhouse gases. The proposal, would result in lower emissions in developed and developing countries through the phase-down of the production and consumption of HFCs. If an amendment were ad opted by the Parties, then switching from HFC134a to an alternative refrigerant such as HFO- 1234yf will likely be an attractive option for decreasing the overall use and emissions of high-GWP HFCs. Options for reductions would include transition from HFCs, moving from high to lower GWP HFCs, and reducing charge
sizes.

EPA requests comment on the implications for the program of the refrigerant transition scenario assumed for the analyses supporting this NPRM; that is, where there are no U.S. regulatory requirements for manufacturers to eliminate the use of HFC-134a for newly manufactured vehicles. EPA requests comment on factors that may affect the industry demand for refrigerant and its U.S. and international supply.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 252 of 768 b. Air Conditioning Efficiency (“Indirect”) Emissions and Credits

In addition to the A/C leakage credits discussed above, EPA is proposing credits for improving the efficiency of – and thus reducing the CO 2 emissions from -- A/C systems. Manufacturers have available a number of very co st-effective technology options that can reduce
these A/C-related CO 2 emissions, which EPA estimates be on average 11.9 g/mi for cars and 17.1 for trucks nationally. 252 When manufacturers incorporate these technologies into vehicles that clearly result in reduced CO 2 emissions, EPA believes that A/C Efficiency Credits are warranted. Based on extensive industry testin g and EPA analysis, the agency proposes that eligible efficiency-improving technologies be limited to up to a maximum 42% improvement, 253
which translates into a maximum credit value of 5.0 g/mi for cars and 7.2 g/mi for trucks.

As discussed further in Sec tion III.C.1.b.iii below, under its EPCA authority, EPA is proposing, in coordination with NHTSA, to allo w manufacturers to generate fuel consumption improvement values for purposes of CAFE compliance based on the use of A/C efficiency technologies. EPA is proposing that both the A/ C efficiency credits under EPA’s GHG program and the A/C efficiency fuel consumption improvement values under the CAFE program would be based on the same methodologies and test procedures, as further described below.

i. Quantifying A/C Efficiency Credits

As in the 2012-2016 rule, EPA proposes that A/C Efficiency Credits be calculated based on the efficiency-improving technologies included in the vehicle. The design-based approach, associating each technology with a specific credit value, is a surrogate for a using a performance test to determine credit values. Although EPA generally prefers measuring actual emissions performance to a design-based approach, measuring small differences in A/C CO 2 emissions is very difficult, and an accurate test procedure capable of determining such differences is not currently available.

However, in conjunction with the (menu or) design-based calculation, EPA continues to believe it is important to verify that the technol ogies installed to generate credits are improving the efficiency of the A/C system. In the 2012-2016 rule, EPA required that manufacturers
submit data from an A/C CO 2 Idle Test as a prerequisite to accessing the design-based credit

252 EPA derived these estimates using a sophisticated new ve hicle simulation tool that EPA has developed since the completion of the MYs 2012-2016 final rule. Although resu lts are very similar to thos e in the earlier rule, EPA believes they represent more accurate estimates. Chapter 5 of the Joint TSD presents a detailed discussion of the development of the simulation tool and the resulting emissions estimates.

253 The cooperative IMAC study mentioned above concluded that these emissions can be reduced by as much as 40% through the use of these technologies. In additi on, EPA has concluded that improvements in the control software for the A/C system, including more precise control of such components as the radiator fan and compressor, can add another 2% to the emission reductions. In total, EPA believes that a total maximum improvement of 42% is available for A/C systems.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 253 of 768 calculation method. Beginning in MY 2014, ma nufacturers wishing to generate the A/C Efficiency Credits need to meet a CO 2 emissions threshold on the Idle Test.

As manufacturers have begun to evaluate the Idle Test requirements, they have made EPA aware of an issue with the test’s original design. In the MYs 2012-2016 rule, EPA received comments that the Idle Test did not properly capture the efficiency impact of some of the technologies on the Leakage Credit menu list. EP A also received comments that idle operation is not typical of real-world driv ing. EPA acknowledges that both of these comments have merit. At the time of the MY 2012-2016 rule, we expected that many manufacturers would be able to demonstrate improved efficiency with just a few technologies (e.g. forced cabin air recirculation or electronically-controlled, variable-displaceme nt compressors), but under idle conditions, testing by manufacturers has shown that the benefi ts are difficult to quantify. EPA continues to believe that there are some technologies that do have their effectiveness demonstrated during idle and that idle is a significant fraction of real-world operation. Also, recent data provided by the industry shows that some vehicles that incorp orate higher-efficiency A/C technologies are not able to consistently reach the CO 2 threshold on the current Idle Test. The available data also indicates that meeting the threshold tends to be more difficult for vehicles with smallerdisplacement engines.

Although EPA believes some adjustments in the Idle Test are warranted and is proposing such adjustments, the agency also believes that a reasonable degree of verification is still needed, to demonstrate that that A/C efficien cy-improving technologies for which manufacturers are basing credits are indeed implemented pr operly and are reducing A/C-related fuel consumption. EPA continues to believe that the Idle Test is a reasonable measure of some A/Crelated CO 2 emissions as there is significant real -world driving activity at idle, and it significantly exercises a number of the A/C t echnologies from the menu. Therefore, EPA proposes to maintain the use of Idle Test as a prerequisite for generating Efficiency Credits. However, in order to provide reasonable verification while encouraging the development and use of efficiency-improving technologies, EPA proposes to revise the CO 2 threshold. Specifically, the agency proposes to scale the magnitude of the threshold to the displacement of the vehicle’s engine, with smaller-displacement engines having a higher “grams per minute” threshold than larger-displacement engines. Thus, for vehicles with smaller-displacement engines, the threshold would be less stringent. The revise d threshold would apply beginning with MY 2017, thus replacing at that point the flat gram per minute threshold that applies for MYs 2014, 2015, and 2016, with the option for manufacturers to use the revised threshold as early as MY 2014. 254
In addition to revising the threshold, EPA proposes to relax the average ambient temperature and humidity requirements, due to the difficulty in controlling the year-round humidity in test cells designed for FTP testing. EPA requests comment on the proposed continued use of the Idle Test

254 The Joint TSD describes the available data relevant to testing on the Idle Test and the design of the revised threshold in more detail.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 254 of 768 as a tool to validate the function of a vehicle’ s A/C efficiency-improving technologies, and on
the revised CO 2 threshold and ambient requirements.

In addition to proposing the revised Idle Test, EPA proposes that manufacturers have the option of using a new transient A/C test in place of the Idle Test, beginning as early as MY 2014. In the year since the previous GHG rule was finalized, EPA, CARB, and a consortium of auto manufacturers (USCAR) have developed a new transient test procedure that can measure the effect of the operation of the overall A/C system on CO 2 emissions and fuel economy. The new test, known as “AC17” (for Air Conditioning, 2017) , is essentially a comb ination of the existing SC03 and HWFET test procedures, which, with the proposed modifications, would exercise the A/C system (and new technologies) under conditions representing typical U.S. driving and
climate.

Some aspects of the AC17 test are still be ing developed and impr oved, but the basic procedure is sufficiently complete for EPA to propose it as an alternative to the Idle Test as a prerequisite for generating Efficiency Credits. To demonstrate that a vehicle’s A/C system is delivering the efficiency benefits of the new technologies, manufacturers would run the AC17 test procedure on a vehicle that incorporates the new technologies, with the A/C system off and then on, and then compare that result to the result from a previous model year or baseline vehicle with similar vehicle characteristics, except that it does not have the new tech nologies. If the test result with the new technology demonstrated an emission reduction which is greater than or equal to the menu-based credit potential of thos e technologies, the manufacturer would generate the appropriate credit based on the menu. However, if the test result did not demonstrate the full menu-based potential of the technology, partial cr edit could still be earned, in proportion to how far away the result was fro m the mean value.

The AC17 test requires a significant amount of time for each test (nearly 4 hours) and must be run in expensive SC03-capable facilities. EPA believes that the purpose of the test – to
validate that A/C CO 2 reductions are indeed occurring and hence that the manufacturer is eligible for Efficiency Credits – would be met if the manufacturer performs the new test on a limited
subset of test vehicles. EPA proposes that manufacturers wishing to use the AC17 test to validate a vehicle’s A/C technology be required to test one vehicle from each platform. For this purpose, “platform” would be defined as a group of vehicles with common body floorplan, chassis, engine, and transmission. 255 EPA requests comment on the new test and its use. EPA requests comment on the AC17 test and its proposed use as an optional method of validating the function of A/C efficiency-improving technologi es and in generating A/C Efficiency Credits.
EPA also seeks comment on eliminat ing the idle test in favor of using only the AC17 test for A/C efficiency credits.

255 A single platform may encompass a larger group of fuel economy label classes or car lines (40 CFR §600.002- 93), such as passenger cars, compact utility vehicles, and station wagons The specific vehicle selection requirements for manufacturers using this testing are laid out in the regulations associated with this NPRM.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 255 of 768 ii. Potential Future Use of the New A/ C Test for Credit Quantification

As described above, EPA is proposing to use the AC17 test as a prerequisite to generating A/C Efficiency Credits. The test is well-suited for this purpose since it can accurately measure
the difference in the increased CO 2 emissions that occur when the A/C system is turned on vs. when it is turned off. When the test is done for both a new vehicle and a comparative vehicle with less-effective efficiency-improving technol ogies, this difference in the “off-on” A/C CO 2 increase between the two vehicles is enough to show that the vehicle’s A/C technologies are generally performing well, relative to an average vehicle.

However, the test is limited in its ability to accurately quantify the amount of credit that would be warranted by an improved A/C systems on a particular vehicle. This is because to
determine an absolute – rather than a relative – difference in CO 2 effect for an individual vehicle design would require knowledge of the A/C system CO 2 performance for that exact vehicle, but without those specific A/C efficiency improveme nts installed. This would be difficult and costly, since two test vehicles (or a single ve hicle with the components removed and replaced) would be necessary. Even then, the inherent variablility between such tests on such a small sample in such an approach might not be statistically robust enough to confidently determine a
small absolute CO 2 emissions impact between the two vehicles.

In Chapter 5 of the Joint TSD, EPA discu sses a potential solution to this dilemma, including comparing the efficiencies of indi vidual components outside the vehicles, through “bench” testing of components supplemented by vehicle simulation modeling to relate that component’s performance to the complete vehicle. EPA believes that such approaches may eventually allow the AC17 test to be used as part of a more complicated series of test procedures and simulations, to accurately quantify the A/C CO 2 effect of an individual vehicle’s A/C technology package, but EPA believes that this i ssue is beyond the scope of this proposed rule. However, the agency does encourage comment, including test data, on how the AC17 test couldbe enhanced in order to measure the individual and collective impact of different A/C efficiencyimproving technologies on individual vehicle designs and thus to quantify Efficiency Credits. EPA also seeks comment on a more complex procedure, also discussed in Chapter 5 of the Joint TSD, that uses a combination of bench testing of components, vehicle simulation models, and dynamometer testing to quantify Efficiency Credits.

iii. A/C Efficiency Fuel Consumption Improvement Values in the CAFE Program

As described in section II.F, EPA is proposi ng to continue to use a technology design “menu” approach for quantifying A/C efficiency credits, and EPA is proposing, in coordination with NHTSA, for the first time under its EPCA authority to allow manufacturers to use this same technology design “menu” to generate fuel consumption improvement values for purposes of CAFE compliance based on the use of A/C efficiency technologies. For CAFE, the design approach would assign a fuel consumption impr ovement value to each efficiency-improving airSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 256 of 768 conditioning technology that the manufacturer incor porates in a vehicle model. The sum of these values for all technologies would be the amount of fuel consumption reduction achieved by that vehicle, up to a maximum of 0.000563 gallons/mi fuel consumption improvement value for cars and a 0.000586 gallons/mi fuel consumption improvement value for a truck. The table belowpresents the proposed CAFE fuel consumption improvement values for each of the efficiencyreducing air conditioning technologies considered in this proposal. More detail is provided on the calculation of indirect A/C CAFE fuel consumption improvement values in chapter 5 of the joint TSD. EPA is proposing very specific defini tions of each of the technologies in the table below which are discussed in Chapter 5 of the dr aft joint TSD to ensure that the air conditioner technology used by manufacturers seeking these values corresponds with the technology used to derive the fuel consumption improvement values. EPA is also proposing thresholds based on

CO 2 performance testing for manufacturer wanting to generate CO 2 credits. Manufacturers would also be required to meet the performance thresholds, which are based on CO 2 performance, to be eligible to generate fuel consumption improvement values for CAFE.

Table III-13 Proposed Fuel Consumption Improvement Values for A/C Efficiency

Technology Description Estimated reduction in A/C CO 2 Emissions

and Fuel Consum p tion Car A/C Efficiency Fuel Consumption Improvement ( g allon / mi) Truck A/C Efficiency Fuel Consumption Improvement ( g allon / mi)Reduced reheat, with externallycontrolled, variable-displacement

compressor 30% 0.000169 0.000248

Reduced reheat, with externallycontrolled, fixed-displacement or pneumatic variable displacement

compressor 20% 0.000113 0.000158

Default to recirculated air with closedloop control of the air supply (sensor feedback to control interior air quality) whenever the outside ambient temperature is 75 °F or higher (although deviations from this temperature are allowed based on additional analysis) 30% 0.000169 0.000248

Default to recirculated air with openloop control of the air supply (no sensor feedback) whenever the outside ambient temperature is 75 °F or higher (although deviations from this temperature are allowed if accompanied by an engineering analysis) 20% 0.000113 0.000158

Blower motor control which limit wasted electrical energy (e.g. pulsewidth modulated power controller) 15% 0.000090 0.000124

Internal heat exchanger (or suction line heat exchanger) 20% 0.000113 0.000158

Improved evaporators and condensers (with engineering analysis on each component indicating a COP improvement greater than 10%, when compared to previous design) 20% 0.000113 0.000158Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 257 of 768 Oil Separator (internal or external to compressor) 10% 0.000090 0.000079

2. Incentive for Electric Vehicles, Plug-in Hy brid Electric Vehicles, and Fuel Cell
Vehicles

a. Rationale for Temporary Regulatory Incentives for Electric Vehicles, Plug-in Hybrid Electric Vehicles, and Fuel Cell Vehicles

EPA has identified two vehicle powertrain-fuel pathways that have th e future potential to transform the light-duty vehicle sector by achieving near-zero greenhouse gas (GHG) emissions and oil consumption in the longer term, but which face major near-term market barriers such as vehicle cost, fuel cost, the development of low-GHG fuel production and distribution infrastructure, and/or consumer acceptance.

 Electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs) which would operate exclusively or frequently on grid electricity that could be produced from very low GHG emission feedstocks or processes.

 Fuel cell vehicles (FCVs) which would opera te on hydrogen that could be produced from very low GHG emissions feedstocks or processes.

As in the 2012-2016 rule, EPA is proposing temporary regulatory incentives for the commercialization of EVs, PHEVs, and FCVs. EPA believes that these advanced technologies represent potential game-changers with respect to control of transportation GHG emissions as they can combine an efficient vehicle propulsion system with the potential to use motor fuels produced from low-GHG emissions feedstocks or from fossil feedstocks with carbon capture and sequestration. EPA recognizes that the us e of EVs, PHEVs, and FCVs in the 2017-2025 timeframe, in conjunction with the incentives, will decrease the overall GHG emissions reductions associated with the program as the upstream emissions associated with the generation and distribution of electricity are higher than th e upstream emissions associated with production and distribution of gasoline. EPA accounts for this difference in projections of the overall program’s impacts and benefits (see Section III.F). 256

The tailpipe GHG emissions from EVs, PHEVs operated on grid electricity, and hydrogen-fueled FCVs are zero, and traditionally th e emissions of the vehicle itself are all that EPA takes into account for purposes of compliance with standards set under Clean Air Act section 202(a). Focusing on vehicle tailpipe emissions has not raised any issues for criteria pollutants, as upstream emissions associated with production and distribution of the fuel are

256 Also see the Regulatory Impact Analysis.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 258 of 768 addressed by comprehensive regulatory programs focused on the upstream sources of those emissions. At this time, however, there is no such comprehensive program addressing upstream emissions of GHGs, and the upstream GHG emissions associated with production and distribution of electricity are higher, on a national average basis, than the corresponding upstream GHG emissions of gasoline or other petroleum based fuels. 257 In the future, if there were a program to comprehensively control upstream GHG emissions, then the zero tailpipe levels from these vehicles have the potential to produce very large GHG reductions, and to transform the transportation sector’s contribu tion to nationwide GHG emissions (as well as oil consumption). For a discussion of this issue in the 2012-2016 rule, see 75 FR at 25434-438.

EVs and FCVs also represent some of the most significant changes in automotive technology in the industry’s history. 258 For example, EVs face major consumer barriers such as significantly higher vehicle cost and lower range. EVs also have attributes that could be attractive to some consumers: lower and more predictable fuel price, no need for oil changes or spark plugs, and reducing one’s personal contribution to air pollution, climate change, and oil dependence. 259

Original equipment manufacturers currently offer two EVs and one PHEV in the U.S.
market. 260 Deliveries of the Nissan Leaf EV, which has a list price of about $33,000 and an EPA label range of 73 miles, began in December 2010 in selected areas, and total sales through July 2011 are about 7000. The luxury Tesla Roadster EV, with a list price of $109,000, has been on sale since March 2008 with cumulative sales of approximately 1500. The Chevrolet Volt PHEV, with a list price of about $41,000 and an EPA label all-electric range of 35 miles, has
sold over 4000 vehicles since it entered the market in December 2010 in selected markets. At this time, no original equipment manufacturer offers FCVs to the general public. 261 Currently, combined EV, PHEV, and FCV sales represent about 0.1% of overall light-duty vehicle sales. Additional models, such as the Fo rd Focus EV, the Mitsubishi i EV, and the Toyota Prius PHEV, are expected to enter the U.S. market in the next few months.

The agency remains optimistic about consumer acceptance of EVs, PHEVs, and FCVs in the long run, but we believe that near-term market acceptance is less certain. One of the most successful new automotive powertrain technol ogy—conventional hybrid electric vehicles like the Toyota Prius—illustrates the challenges i nvolved in automotive po wertrain technology changes. Even though conventional hybrids have now been on the U.S. market for over a

257 There is significant regional variation with upstream GHG emissions associated with electricity production and distribution. Based on EPA’s eGRID2010 database, comprised of 26 regions, the average powerplant GHG emissions rates per kilowatt-hour for those regions with the highest GHG emissions rates are about 3 times higher than those with the lowest GHG emissions rates. See http://www.epa.gov/cleanenergy/energyresources/egrid/index.html

. 258 A PHEV is not such a big change since, if the owner so chooses, it can operate on gasoline.

259 PHEVs and FCVs share many of these same challenges and opportunities.

260 Smart has also leased approximately 100 Smart ED vehicles in the U.S.

261 Cite the small number of leases with the Honda Clarity FCV?Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 259 of 768 decade, their market share hovers around 3 percent or so even though they offer higher vehicle range than their traditional gasoline vehicle counterparts, involve no significant consumer tradeoffs (other than cost), and have reduced their incremental cost to a few thousand dollars.
The cost and consumer tradeoffs associated with EVs, PHEVs, and FCVs are more significant than those associated with conventional hybrids. Given the long leadtimes associated with major transportation technology shifts, there is value in promoting these potential game-changing technologies today if we want to retain the possibility of achieving major environmental and energy benefits in the future.

In terms of the relative relationship between tailpipe and upstream fuel production and distribution GHG emissions, EVs, PHEVs, and FCVs are very different than conventional gasoline vehicles. Combining vehicle tailpipe and fuel production/distribution sources, gasoline vehicles emit about 80 percent of these GHG emissi ons at the vehicle tailpipe with the remaining 20 percent associated with “upstream” fuel production and distribution GHG emissions. 262 On the other hand, vehicles using electricity and hy drogen emit no GHG (or other emissions) at the vehicle tailpipe, and therefore all GHG emission s associated with powering the vehicle are due to fuel production and distribution. 263 Depending on how the electricity and hydrogen fuels are produced, these fuels can have very high fuel production/distribution GHG emissions (for example, if coal is used with no GHG emissi ons control) or very low GHG emissions (for example, if renewable processes with minimal fossil energy inputs are used, or if carbon capture and sequestration is used).

For example, as shown in the Regulatory Impact Analysis, today’s Nissan Leaf EV would have an upstream GHG emissions value of 161 grams per mile based on national average electricity, and a value of 84 grams per mile based on the average electricity in California, one of
the initial markets for the Leaf.

Because these upstream GHG emissions values are generally higher than the upstream
GHG emissions values associated with gasoline vehicles, and because there is currently no national program in place to reduce GHG emissions from electric powerplants, EPA believes it is appropriate to consider the incremental upstre am GHG emissions associated with electricity

262 Fuel production and distribution GHG emissions have r eceived much attention because there is the potential for more widespread commercialization of transportation fuel s that have very different GHG emissions characteristics in terms of the relative contribution of GHG emissions from the vehicle tailpipe and those associated with fuel production and distribution. Other GHG emissions source cat egories include vehicle production, including the raw materials used to manufacture vehicle components, and vehi cle disposal. These categories have not been included in EPA motor vehicle emissions regulations for several reasons: these categories are less important from an emissions inventory perspective, they raise complex accoun ting questions that go well beyond vehicle testing and fuel-cycle analysis, and in general there are fewer differences across technologies.

263 The Agency notes that many other fuels currently used in light-duty vehicles, such as diesel from conventional oil, ethanol from corn, and compressed natural gas from conventional natural gas, have tailpipe GHG and fuel production/distribution GHG emissions characteristics fairly si milar to that of gasoline from conventional oil. See 75 FR at 25437. The Agency recognizes that future transportation fuels may be produced from renewable feedstocks with lower fuel production/distribution GHG emissions than gasoline from oil.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 260 of 768 production and distribution. But, we also think it is appropriate to encourage the initial commercialization of EV/PHEV/FCVs as well, in order to retain the pote ntial for game-changing GHG emissions and oil savings in the long term.

Accordingly, EPA proposes to provide temporary regulatory incentives for EVs, PHEVs (when operated on electricity) and FCVs that will be discussed in detail below. EPA recognizes that the use of EVs, PHEVs, and FCVs in the 2017-2025 timeframe, in conjunction with the incentives, will decrease the overall GHG emissions reductions associated with the program as the upstream emissions associated with the gene ration and distribution of electricity are higher than the upstream emissions associated with production and distribution of gasoline. EPA accounts for this difference in projections of the overall program’s impacts and benefits (see Section III.F). EPA believes that the relatively minor impact on GHG emissions reductions in the near term is justified by promoting techno logies that have significant transportation GHG emissions and oil consumption game-changing potential in the longer run, and that also face major market barriers in entering a market that has been dominated by gasoline vehicle technology and infrastructure for over 100 years.

EPA will review all of the issues associated with upstream GHG emissions, including the status of EV/PHEV/FCV commercialization, the status of upstream GHG emissions control programs, and other relevant factors.

b. MY 2012-2016 Light-Duty Vehicle Gr eenhouse Gas Emissions Standards

The light-duty vehicle greenhouse gas emissions standards for model years 2012-2016 provide a regulatory incentive for electric vehicles (EVs), fuel cell vehicles (FCVs), and for the electric portion of operation of pl ug-in hybrid electric vehicles (PHEVs). See generally 75 FR at 25434-438. This is designed to promote advanced technologies that have the potential to provide “game changing” GHG emissions reductions in the future. This incentive is a 0 grams per mile compliance value (i.e., a compliance value based on measured vehicle tail pipe GHG emissions) up to a cumulative EV/PHEV/FCV production cap threshold for individual manufacturers. For manufacturers that exceed the cumulative production cap over MY 2012-2016, compliance values for those vehicles in excess of the cap will be based on a full accounting of the net fuel production and distribution GHG emi ssions associated with those vehicles relative to the fuel production and distribution GHG emissions associat ed with comparable gasoline vehicles. For an electric vehicle, this accounting is based on th e vehicle electricity consumption over the EPA compliance tests, eGRID2007 national averag e powerplant GHG emissions factors, and multiplicative factors to account for electricity grid transmission losses and pre-powerplant
feedstock GHG related emissions. 264 The accounting for a hydrogen fuel cell vehicle would be done in a comparable manner. There is a two-tier cumulative EV/PHEV/FCV production cap for

264 See 40 C.F.R. 600.113-12(m).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 261 of 768 MY 2012-2016: the cap is 300,000 vehicles for those manufacturers that sell at least 25,000 EVs/PHEVs/FCVs in MY 2012, and the cap is 200,000 vehicles for all other manufacturers.

Although EPA also proposed a vehicle incentive multiplier for MY 2012-2016, the agency did not finalize a multiplier. At that time, the Agency believed that combining the 0 gram per mile and multiplier incentives would be excessive.

The 0 grams per mile compliance value decreases the GHG emissions reductions associated with the 2012-2016 standards compared to the same standards and no 0 grams per mile compliance value. It is impossible to know the precise number of vehicles that will take advantage of this incentive in MY 2012-2016. In the preamble to the final rule, EPA projected
the decrease in GHG emissions reductions that would be associated with a scenario of 500,000 EVs certified with a compliance value of 0 grams per mile. This scenario would result in a projected decrease of 25 million metric tons of GHG emissions reductions, or less than 3 percent of the total projected GHG benefits of the pr ogram of 962 million metric tons. This GHG emissions impact could be smaller or larger, of course, based on the actual number of EVs that would certify at 0 grams per mile.

In the preamble to the final rule, EPA stat ed that it would reassess this issue for rulemakings beginning in MY 2017 based on th e status of advanced vehicle technology commercialization, the status of upstream GHG control programs, and other relevant factors.

c. Supplemental Notice of Intent

In our most recent Supplemental Notice of Intent, 265 EPA stated that: “EPA intends to propose an incentive multiplier for a ll electric vehicles (EVs), plug-in hybrid electric vehicles (PHEVs), and fuel cell vehicles (FCVs) sold in MYs 2017 through 2021. This multiplier approach means that each EV/PHEV/FCV would count as more than one vehicle in the manufacturer’s compliance calculation. EPA intend s to propose that EVs and FCVs start with a multiplier value of 2.0 in MY 2017, phasing down to a value of 1.5 in MY 2021. PHEVs would start at a multiplier value of 1.6 in MY 2017 and phase down to a value of 1.3 in MY 2021. These multipliers would be proposed for in corporation in EPA’s GHG program....As an additional incentive for EVs, PHEVs and FCVs, EPA intends to propose allowing a value of 0 g/mile for the tailpipe compliance value for EVs, PHEVs (electricity usage) and FCVs for MY 2017–2021, with no limit on the quantity of vehicles eligible for 0 g/mi tailpipe emissions accounting. For MY 2022–2025, 0 g/mi will only be allowed up to a per-company cumulative sales cap based on significant penetration of th ese advanced vehicles in the marketplace. EPA intends to propose an appropriate cap in the NPRM.”

265 76 Federal Register 48758 (August 9, 2011).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 262 of 768 d. Proposal for MY 2017-2025

EPA is proposing the following temporary regulatory incentives for EVs, PHEVs, and
FCVs consistent with the discussion in th e August 2011 Supplemental Notice of Intent.

For MY 2017 through 2021, EPA is propos ing two incentives. The first proposed incentive is to allow all EVs, PHEVs (electric operation), and FCVs to use a GHG emissions compliance value of 0 grams per mile. There would be no cap on the number of vehicles eligible for the 0 grams per mile compliance value for MY 2017 through 2021.

The second proposed incentive for MY 2017 through 2021 is a multiplier for all EVs, PHEVs, and FCVs, which would allow each of these vehicles to “count” as more than one vehicle in the manufacturer’s compliance calculation. 266 While the Agency rejected a multiplier incentive in the MY 2012-2016 final rule, we are proposing a multiplier for MY 2017-2025 because, while advanced technologies were not necessary for compliance in MY 2012-2016, they are necessary, for some manufacturers, in the MY 2022-2025 timeframe. A multiplier for MY 2017-2021 can promote the initial commercialization of these advanced technologies. . In order for a PHEV to be eligible for the mu ltiplier incentive, EPA proposes that PHEVs be required to be able to complete a full EPA highway test (10.2 miles), without using any conventional fuel, or alternatively, have a minimum equivalent all-electric range of 10.2 miles as measured on the EPA highway cycle. EPA seeks comment on whether this minimum range should be lower or higher, or whether the multip lier should vary based on range. The specific proposed multipliers are shown in Table III-14.

Table III-14 Proposed EV, FCV, and PHEV Per-Vehicle Multiplier Incentives for MY 2017-2021

Model Year(s) EVs and FCVs PHEVs

2017-2019 2.0 1.6
2020 1.75 1.45
2021 1.5 1.3

For MY 2022 through 2025, EPA is proposing one incentive—the 0 grams per mile GHGemissions compliance incentive for EVs, PHEVs (electric operation), and FCVs up to a percompany cumulative production cap threshold for those model years. EPA is proposing a twotier, per-company cap based on cumulative production in prior years, consistent with the general approach that was adopted in the rulemaking for MY 2012-2016. For manufacturers that sell 300,000 or more EV/PHEV/FCVs combined in MY 2019-2021, the proposed cumulative

266 In the unlikely case where a PHEV with a low electric range might have an overall GHG emissions compliance value that is higher than its compliance target, EPA proposes that the automaker can choose not to use the multiplier.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 263 of 768 production cap would be 600,000 EV/PHEV/FCVs for MY 2022-2025. Other automakers would have a proposed cumulative production cap of 200,000 EV/PHEV/FCVs in MY 2022-2025.

This proposed cap design is appropriate as a way to encourage automaker investment in potential GHG emissions game-changing technologi es that face very significant cost and consumer barriers. In addition, as with the rulemaking for MY 2012-2016, EPA believes it is important to both recognize the benefit of early leadership in commercialization of these technologies, and encourage additional manufacturers to invest over time. As noted above, manufacturers are unlikely to do so if vehicles with these technologies are treated for compliance purposes to be no more advantageous than the best conventional hybrid vehicles. Finally, we believe that the proposed cap design provides a reasonable limit to the overall decrease in program GHG emissions reductions associated with the incentives, and EPA is being transparent about these GHG emissions impacts (see later in this section and also Section III.F).

EPA recognizes that a central tension in the design of a proposed cap relates to certainty and uncertainty with respect to both individual automaker caps and the overall number of vehicles that may fall under the cap, which determines the overall decrease in GHG emissions reductions. A per-company cap as described above would provide clear certainty for individual manufacturers at the time of the final rule, but would yield uncertainty about how many vehicles industry-wide would take advantage of the 0 grams per mile incentive and therefore the overall impact on GHG emissions. An alternative appr oach would be an industry-wide cap where EPA
would establish a finite limit on the total number of vehicles eligible for the 0 grams per mile incentive, with a method for allocating this indus try-wide cap to individual automakers. This would provide certainty with respect to the maximum number of vehicles and GHG emissions impact. If EPA were to make a specific numerical allocation at the time of the final rule, automakers would have certainty, but EPA is concerned that we may not have sufficient information to make an equitable allocation for a timeframe that is well over a decade away. If EPA were to adopt an allocation formula in the fi nal rule that was depend ent on future sales (as we are proposing above for the per-company cap), automakers would have much less certainty in compliance planning as they would not know their i ndividual caps until some point in the future.

To further assess the merits of an industry-wide cap approach, EPA also seeks comment on the following alternative for an industry-wide cap. EPA would place an industry-wide cumulative production cap of 2 million EV/PHEV/FCVs eligible for the 0 grams per mile incentive in MY 2022-2025. EPA has chosen 2 million vehicles because, as shown below, we project that this limits the maximum decrease in GHG emissions reductions to about 5 percent of total program GHG savings. EPA would allocate this 2 million vehicle cap to individual automakers in calendar year 2022 based on cumulative EV/PHEV/FCV sales in MY 2019-2021, i.e., if an automaker sold X percent of industry-wide EV/PHEV/FCV sales in MY 2019-2021, that automaker would get X percent of the 2 million industry-wide cumulative production cap inSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 264 of 768 MY 2022-2025 (or possibly somewhat less than X percent, if EPA were to reserve some small volumes for those automakers that sold zero EV/PHEV/FCVs in MY 2019-2021).

For both the proposed per-company cap and the alternative industry-wide cap, EPA proposes that, for production beyond the cumulative vehicle production cap for a given manufacturer in MY 2022-2025, compliance values would be calculated according to a methodology that accounts for one-half of the net increase in upstream GHG emissions relative to that of a comparable gasoline vehicle.

EPA also seeks comments on whether any changes should be made for MY 2012-2016, i.e., whether the compliance value for production beyond the cap should be one-half of the net increase in upstream GHG emissions, or whether the current cap for MY 2012-2016 should be
removed.

EPA is not proposing any multiplier incentives for MY 2022 through 2025. EPA believes that the 0 gram per mile compliance value, with cumulative vehicle production cap, is a
sufficient incentive for MY 2022-2025.

One key issue here is the appropriate electrici ty upstream GHG emissions factor or rate to use in future projections of EV/PHEV emissions based on the net upstream approach. In the following example, we use a 2025 nationwide av erage electricity upstream GHG emissions rate (powerplant plus feedstock) of 0.574 grams GHG/watt-hour, based on simulations with the EPA Office of Atmospheric Program’s Integrated Planning Model (IPM). 267 For the example below, EPA is using a projected national average value from the IPM model, but EPA recognizes that values appropriate for future vehicle use may be higher or lower than this value. EPA isconsidering running the IPM model with a more robust set of vehicle and vehicle chargingspecific assumptions to generate a better electricity upstream GHG emissions factor for EVs and PHEVs for our final rulemaking, and, at minimum, intends to account for the likely regional sales variation for initial EV/PHEV/FCVs, and di fferent scenarios for the relative frequency of daytime and nighttime charging. EPA seeks comment on whether there are additional factors that we should try to include in th e IPM modeling for the final rulemaking.

EPA proposes a 5-step methodology for calculating the GHG emissions compliance value for vehicle production in excess of the cumulative production cap for an individual automaker. For example, for an EV in MY 2025, this methodology would include the following steps and calculations:

 Measuring the vehicle electricity consumptio n in watt-hours/mile over the EPA city and highway tests (for example, a midsize EV in 2025 might have a 2-cycle test electricity consumption of 230 watt-hours/mile)

267 Technical Support Document, Chapter 4.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 265 of 768  Adjusting this watt-hours/mile value upward to account for electricity losses during electricity transmission (dividing 230 wa tt-hours/mile by 0.93 to account for grid/transmission losses yields a value of 247 watt-hours/mile)

 Multiplying the adjusted watt-hours/mile value by a 2025 nationwide average electricityupstream GHG emissions rate of 0.574 grams/watt-hour at the powerplant (247 watthours/mile multiplied by 0.574 grams GHG/watt-hour yields 142 grams/mile)

 Subtracting the upstream GHG emissions of a comparable midsize gasoline vehicle of 39 grams/mile 268 to reflect a true net increase in up stream GHG emissions (142 grams/mile for the EV minus 39 grams/mile for the gasoline vehicle yields a net increase and EV compliance value of 103 grams/mile). 269

 To reflect the proposed phase-in from 0 grams per mile to full net upstream accounting, the MY 2025 value would be one-half of 103 grams per mile, or 52 grams per mile.

The full accounting methodology for FCVs and the portion of PHEV operation on grid electricity would use this same approach. Th e proposed regulations contain EPA’s proposed method to determine the compliance value for PHEVs, and EPA proposes to develop a similar methodology for FCVs if and when the need arises. 270 Given the uncertainty about how hydrogen would be produced, if and when it were used as a transportation fuel, EPA seeks comment on projections for the fuel production and distribution GHG emissions associated with hydrogen production for various feedstocks and processes.

EPA is fully accounting for the upstream GHG emissions associated with all electricity used by EVs and PHEVs (and any hydrogen used by FCVs), both in our regulatory projections of the impacts and benefits of the program, and in all GHG emissions inventory accounting.

EPA seeks public comment on the proposed incentives for EVs, PHEVs, and FCVs described above. In addition, EPA seeks public comment on the following additional questions related to the design of these incentives:

268 A midsize gasoline vehicle with a footprint of 46 squa re feet would have a MY 2025 GHG target of about 140 grams/mile; dividing 8887 grams CO2/gallon of gasoline by 140 grams/mile yields an equivalent fuel economy level of 63.5 mpg; and dividing 2478 gram s upstream GHG/gallon of gasoline by 63.5 mpg yields a midsize gasoline vehicle upstream GHG value of 39 grams/mile. The 24 78 grams upstream GHG/gallon of gasoline is calculated from 21,546 grams upstream GHG/million Btu (EPA value for future gasoline based on DOE’s GREET model modified by EPA standards and data; see docket memo to MY2012-2016 rulemaking titled “Calculation of Upstream Emissions for the GHG Vehicle Rule”) a nd multiplying by 0.115 million Btu/gallon of gasoline.

269 Manufacturers can utilize alternate calculation methodologie s if shown to yield equivalent or superior results and if approved in advance by the Administrator.

270 Cite the regs here for more details.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 266 of 768 e. Projection of Impact on GHG Emissions Reductions Due to Incentives

EPA believes it is important to project th e impact on GHG emissions that will be associated with the proposed incentives (both 0 grams per mile and the multiplier) for
EV/PHEV/FCVs over the MY 2017-2025 timeframe. Since it is impossible to know precisely how many EV/PHEV/FCVs will be sold in the MY 2017-2025 timeframe that will utilize the proposed incentives, EPA presents projections for two scenarios: 1) the number of EV/PHEV/FCVs that EPA's OMEGA technology an d cost model predicts based exclusively on its projections for the most cost-effective way fo r the industry to meet the proposed standards, and 2) a scenario with a greater number of EV /PHEV/FCVs, based not on ly on compliance with the proposed GHG and CAFE standards, but other factors such as the proposed cumulative production caps and manufacturer investments. For this analysis, EPA assumes that EVs and PHEVs each account for 50 percent of all EV /PHEV/FCVs. EPA seeks comment on whether there are other scenarios which should be evaluated for this purpose in the final rule.

Table III-15 Projected Impact of EV/PHEV/FCV Incentives on GHG Emissions Reductions

Scenario Cumulative EV/PHEV/FCV Sales 2017-2025 Cumulative EV/PHEV/FCV Sales 2022-2025 Cumulative Decrease in GHG Emissions

Reductions 2017-2025 271 Percentage Decrease in GHG Emissions

Reductions 2017-2025 272

EPA OMEGA model projection 1.9 million 1.3 million 80 million metric

tons 3.5%

EPA alternative projection 2.8 million 2.0 million 120 million metric

tons 5.3%

EPA projects that the cumulative GHG emissi ons savings of the proposed MY 2017-2025 standards, on a model year lifetime basis, is approximately 2 billion metric tons. Table III-15 projects that the likely decrease in cumula tive GHG emissions reductions due to the

271 The number of metric tons represents the number of addi tional tons that would be redu ced if the standards stayed the same and there was no 0 gram per mile compliance value.

272 The percentage change represents the ratio of the cu mulative decrease in GHG emissions reductions from the prior column to the total cumulative GHG emissions reduc tions associated with the proposed standards and the proposed 0 gram per mile compliance value.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 267 of 768 EV/PHEV/FCV incentives for MY 2017-2025 vehicles is in the range of 80 to 120 million metric tons, or about 4 to 5 percent.

It is important to note that the above pr ojection of the impact of the EV/PHEV/FCV incentives on the overall program GHG emissions reductions assumes that the EV 0 gram per mile incentive is not in effect, and there is no change to the standard, i.e., that EPA would have proposed exactly the same standard if the 0 gram per mile compliance value were not allowed for any EV/PHEV/FCVs. While EPA has not analyzed su ch a scenario, it is clear that not allowing a 0 gram per mile compliance value would change the technology mix and cost projected for the proposed standard.

It is also important to note that the project ed impact on GHG emissions reductions in the
above table are based on the 2025 nationwide aver age electricity upstream GHG emissions rate (powerplant plus feedstock) of 0.574 grams GHG/watt-hour discussed above (based on simulations with the EPA’s Integrated Planning Model (IPM) for powerplants in 2025, and a 1.06 factor to account for feedstock-related GHG emissions).

EPA recognizes two factors which could sign ificantly reduce the electricity upstream GHG emissions factor by calendar year 2025. First, there is a likelihood that early
EV/PHEV/FCV sales will be much more concentrated in parts of the country with lower electricity GHG emissions rates and much less con centrated in regions with higher electricity
GHG emissions rates. This has been the case with sales of hybrid vehicles, and is likely to be more so with EVs in particular. Second, there is the possibility of a future comprehensive program addressing upstream emissions of GHGs from the generation of electricity. Other factors which could also help in this regard include technology innovation and lower prices for some powerplant fuels such as natural gas.

On the other hand, EPA also recognizes f actors which could increase the appropriate electricity upstream GHG emissions factor in the future, such as a consideration of marginal electricity demand rather than average demand, high use of high-power charging, and the possibility that EVs won't displace gasoline ve hicle use on a 1:1 basis (i.e., multi-vehicle households may use EVs for more shorter trips and fewer longer trips, which could lead to lower overall travel for typical EVs and higher overall travel for gasoline vehicles).

EPA seeks comment on information relevant to these and other factors which could both decrease or increase the proper electricity ups tream GHG emissions factor for calendar year 2025 modeling.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 268 of 768 3. Incentives for “Game-Changing” Technologies Performance for Full-Size Pickup Trucks Including Hybridization

As explained in section II. C above, the agencies recognize that the standards under consideration for MY 2017-2025 will be most challenging to large trucks, including full size pickup

trucks that are often used for commercial purposes and have generally higher payload and towing capabilities, and cargo volumes than other light-duty vehicles . In Section II.C and Chapter 2 of the joint TSD, EPA and NHTSA describe how the slope of the truck curve has been adjusted compared to the 2012-2016 rule to reflect these di sproportionate challenges. In Section III.B, and IV, EPA describes the progression of the truck standards. In this section, EPA describes a proposed incentive for full size pickup trucks, proposed by EPA under both section 202 (a) of the CAA and section 32904 (c) of EPCA, to incentivize advanced technologies on this class of vehicles. This incentize would be in the form of credits under the EPA GHG program, and fuel consumption improvement values (essentially equivalent to EPA’s credits) under the CAFE program.

The agencies’ goal is to incentivize the penetration into the marketplace of “game changing” technologies for these pickups, including th eir hybridization. For that reason, EPA is proposing credits for manufacturers that hybridize a significant quantity of their full size pickup trucks, or use other technologies that significantly reduce CO 2 emissions and fuel consumption. This proposed credit would be available on a per-vehicle basis for mild and strong HEVs, as well as for use of other technologies that significantl y improve the efficiency of the full sized pickup class. As described in section II.F. and III.B.10, EPA, in coordination with NHTSA, is also proposing that manufacturers be able to include “fuel consumption improvement values” equivalent to EPA CO 2 credits in the CAFE program. The proposed gallon per mile values are provided below in addition to the proposed CO 2 credits. These credits and fuel consumption improvement values provide the incentive to begin transforming this most challenged category of vehicles toward use of the most advanced technologies.

Access to this credit is conditioned on a mi nimum penetration of the technologies in a manufacturer’s full size pickup truck fleet. The proposed penetration rates can be found in Table 5-26 in the TSD. EPA is seeking comment on these penetration rates and how they should be applied to a manufacturer’s truck fleet.

To ensure its use for only full sized pickup trucks, EPA is proposi ng a specific definition for a full sized pickup truck based on minimum bed size and minimum towing capability. The specifics of this proposed definition can be found in Chapter 5 of the draft joint TSD (see Section 5.3.1) and in the draft regulations at [cite]. This proposed definition is meant to ensure that smaller pickup trucks, which are not used as often for commercial purposes, such as the Ford Ranger or the Honda Ridgeline do not qualify. 273 . For this proposal, a full sized pickup truck

273 As discussed in TSD Section 5.3.1, EPA is seeking comment on expanding the scope of this credit to somewhat smaller pickups, provided they have the towing and/or hauling capabilities of the larger full-size trucks.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 269 of 768 would be defined as meeting requirements 1 and 2, below, as well as either requirement 3 or 4,
below:

1. The vehicle must have an open cargo box with a minimum width between the
wheelhouses of 48 inches measured as the minimum lateral distance between the limiting interferences (pass-through) of the wheelhouses. The measurement would exclude the transitional arc, local prot rusions, and depressions or pockets, if
present. 274 An open cargo box means a vehicle where the cargo bed does not have a permanent roof or cover. Vehicles sold with detachable covers are considered “open” for the purposes of these criteria.

2. Minimum open cargo box length of 60 inches defined by the lesser of the pickup bed length at the top of the body (defined as the longitudinal distance from the inside front of the pickup bed to the inside of the closed endgate; this would be measured at the height of the top of the open pickup bed along vehicle centerline and the pickup bed length at the floor) and the pickup bed length at the floor (defined as the longitudinal distance from the inside front of the pickup bed to the inside of the closed endgate; this would be measured at the cargo floor surface along vehicle centerline). 275

3. Minimum Towing Capability – the vehicle must have a GCWR (gross combined weight rating) minus GVWR (gross vehicle weight rating) value of at least 5,000 pounds. 276

4. Minimum Payload Capability – the vehicle must have a GVWR (gross vehicle weight rating) minus curb weight value of at least 1,700 pounds.

EPA proposes that mild HEV pickup trucks would be eligible for a per-truck 10 g/mi

CO 2 credit (equal to a 0.0011 gal/mi credit for a 25 mpg truck) during MYs 2017-2021 if the mild HEV technology is used on a minimum percentage of a company’s full sized pickups. That minimum percentage would be 30 percent of a company’s full sized pickup production in MY 2017 with a ramp up to at least 80 percent of production in MY 2021.

274 This dimension is also known as dimension W202 as defined in Society of Automotive Engineers Procedure
J1100.

275 The pickup body length at the top of the body is al so known as dimension L506 in Society of Automotive Engineers Procedure J1100. The pickup body length at th e floor is also known as dimension L505 in Society of Automotive Engineers Procedure J1100.

276 Gross combined weight rating means the value specified by the vehicle ma nufacturer as the maximum weight of a loaded vehicle and trailer, consistent with good engi neering judgment. Gross vehicle weight rating means the value specified by the vehicle manufacturer as the maximum design loaded weight of a single vehicle, consistent with good engineering judgment. Curb weight is define d in 40 CFR 86.1803, consistent with the provisions of 40 CFR 1037.140.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 270 of 768 EPA is also proposing that strong HEV pickup trucks would be eligible for a per-truck 20 g/mi CO 2 credit (equal to a 0.0023 gal/mi credit for a 25 mpg truck) during MYs 2017-2025 if the strong HEV technology is used on a minimum percentage of a company’s full sized pickups. That minimum percentage would be 10 percent of a company’s full sized pickup production in each year over the model years 2017-2025.

To ensure that the hybridization technology used by manufacturers seeking one of these credits meets the intent behind the incentives, EPA is proposing very specific definitions of what qualifies as a mild and a strong HEV. These definitions are described in detail in Chapter 5 of the draft joint TSD (see section 5.3.3).

EPA is also proposing performance-based incentive credits, and fuel consumption improvement values for CAFE, for full size pickup trucks that achieve an emission level significantly below the applicable target and/ or fuel economy performance significantly above the CAFE target for that footprint. EPA pro poses that this credit be either 10 g/mi CO 2 (equivalent to 0.0011 gal/mi for the CAFE program) or 20 g/mi CO 2 (equivalent to 0.0023 gal/mi for the CAFE program) for pickups achieving 15 percent or 20 percent, respectively,
better CO 2 or fuel consumption than their footprint based target in a given model year. EPA provides further details on this performance-based incentive in Chapter 5 of the draft joint TSD (see Section 5.3.4). The 10 g/ mi (equivalent to 0.0011 gal/mi) performance-based credit/value would be available for MYs 2017 to 2021 and a vehicle meeting the requirements would receive
the credit/value until MY 2021 unless its CO 2 level or fuel consumption increases. The 10 g/mi credit/value is not available after 2021 because the post-2021 standards quickly overtake a 15% overcompliance. Earlier in the program, an overcompliance lasts for more years, making the credit/value appropriate for a longer period. The 20 g/mi CO 2 (equivalent to 0.0023 gal/mi) performance-based credit/value would be available for a maximum of 5 years within the model years of 2017 to 2025, provided its CO2 level and fuel consumption does not increase. The credits would begin in the model year of introduction, and (as noted) could not extend past MY 2021 for the 10 g/mi credit (equivalent to 0.0011 gal/mi) and MY 2025 for the 20 g/mi credit (equivalent to 0.0023 gal/mi).

As with the HEV-based credit, the perform ance-based credit/value requires that the technology be used on a minimum percentage of a manufacturer’s full-size pickup trucks. That minimum percentage for the 10 g/mi GHG credit (equivalent to 0.0011 gal/mi fuel consumption improvement value) would be 15 percent of a company’s full sized pickup production in MY 2017 with a ramp up to at least 40 percent of production in MY 2021. The minimum percentage for the 20 g/mi credit (equivalent to 0.0011 gal/mi fuel consumption improvement value) would be 10 percent of a company’s full sized pickup production in each year over the model years 2017-2025. These minimum percentages are set to encourage significant penetration of these technologies, leading to long-term market acceptance.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 271 of 768 Importantly, the same vehicle could not receive credit/values under both the HEV and the performance-based approaches. EPA requests comment on all aspects of this proposed pickup truck incentive credit, including the proposed defi nitions for full sized pickup truck and mild and strong HEV.

4. Treatment of Plug-in Hybrid Electric Vehicles, Dual Fuel Compressed Natural Gas Vehicles, and Ethanol Flexible Fuel Vehicles for GHG Emissions Compliance

a. Greenhouse Gas Emissions

i. Introduction

This section addresses proposed approaches for determining the compliance values for greenhouse gas (GHG) emissions for those vehicles that can use two different fuels, typically
referred to as dual fuel vehicles under the CAFE program. Three specific technologies are addressed: plug-in hybrid electric vehicles (PHEVs), dual fuel compressed natural gas (CNG) vehicles, and ethanol flexible fuel vehicles (FFVs). 277 EPA’s underlying principle is to base compliance values on demonstrated vehicle tailpipe CO 2 emissions performance. The key issue with vehicles that can use more than one fuel is how to weight the operation (and therefore GHG emissions performance) on the two different fuels. EPA proposes to do this on a technology-bytechnology basis, and the sections below will e xplain the rationale for choosing a particular approach for each vehicle technology.

EPA is proposing no changes to the tailpipe GHG emissions compliance approach for dedicated vehicles, i.e., those vehicles that can use only one fuel. As finalized for MY 2016 and later vehicles in the 2012-2016 rule, tailpipe CO 2 emissions compliance levels are those values measured over the EPA 2-cycle city/highway tests. 278 EPA is proposing provisions for how and when to also account for the upstream fuel production and distribution related GHG emissions associated with electric vehicles, fuel cell ve hicles, and the electric portion of plug-in hybrid electric vehicles, and these provisions ar e discussed in Section III.C.2 above.

ii. Plug-In Hybrid Electric Vehicles

PHEVs can operate both on an on-board battery that can be charged by wall electricity from the grid, and on a conventional liquid fuel such as gasoline. Depending on how these vehicles are fueled and operated, PHEVs c ould operate exclusively on grid electricity, exclusively on the conventional fuel, or any combination of both fuels. EPA can determine the

CO 2 emissions performance when operated on the battery and on the conventional fuel. But, in order to generate a single CO 2 emissions compliance value, EPA must adopt an approach for

277 EPA recognizes that other vehicle technologies may be intr oduced in the future that can use two (or more) fuels.

278 For dedicated alternative fuel vehicles. See 75 at FR 25434.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 272 of 768 determining the appropriate weighting of the CO 2 emissions performance on grid electricity and
the CO 2 emissions performance on gasoline.

EPA is proposing no changes to the Society of Automotive Engineers (SAE) cyclespecific utility factor approach for PHEV co mpliance and label emissi ons calculations first adopted by EPA in the joint EPA/DOT final ru lemaking establishing new fuel economy and environment label requirements for MY 2013 and later vehicles. 279 This utility factor approach is based on several key assumptions. One, PHEVs are designed such that the first mode of operation is all-electric drive or electric assist. Every PHEV design with which EPA is familiar is consistent with this assumption. Two, PH EVs will be charged once per day. While this critical assumption is unlikely to be met by every PHEV driver every day, EPA believes that a large majority of PHEV owners will be highly mo tivated to re-charge as frequently as possible, both because the owner has paid a considerably hi gher initial vehicle cost to be able to operate off grid electricity, and because electricity is c onsiderably cheaper, on a per mile basis, than gasoline. Three, it is reasonable to assume that future PHEV dr ivers will retain driving profiles similar to those of past drivers on which the utility factors were based. More detailed information on the development of this utility factor approach can be obtained from the Society of Automotive Engineers. 280 EPA will continue to reevalua te the appropriateness of these assumptions overtime.

Based on this approach, and PHEV-specific specifications such as all-electric drive or equivalent all-electric range, the cycle-specific utility factor methodology yields PHEV-specific values for projected average percent of operation on grid electricity and average percent of operation on gasoline over both the city and highway test cycles. For example, the Chevrolet Volt PHEV, the only original equipment manufactu rer (OEM) PHEV in the U.S. market today, which has an all-electric range of 35 miles on EPA’s fuel economy label, has city and highway cycle utility factors of about 0.65, meaning that the average Volt driver is projected to drive about 65 percent of the miles on grid electricity and about 35 percent of the miles on gasoline. Each PHEV will have its own utility factor.

Based on this utility factor approach, EP A calculates the GHG emissions compliance
value for an individual PHEV as the sum of 1) the GHG emissions value for electric operation (either 0 grams per mile or a non-zero value reflecting net upstream GHG emissions accounting depending on whether automaker EV/PHEV/FCV production is below or above its cumulative production cap as discussed in Section III.C.2 above ) multiplied by the utility factor, and 2) the tailpipe CO2 emissions value on gasoline multip lied by (1 minus the utility factor).

279 76 FR 39504-39505 (July 6, 2011) and 40 CFR 600.116-12(b).

280 http://www.SAE.org , specifically SAE J2841 “Utility Factor Definitions for Plug-In Hybrid Electric Vehicles Using Travel Survey Data,” September 2010.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 273 of 768 iii. Dual Fuel Compressed Natural Gas Vehicles

Dual fuel CNG vehicles operate on either compressed natural gas or gasoline, but not both at the same time, and have separate tanks for the two fuels. 281 There are no OEM dual fuel CNG vehicles in the U.S. market today, but some manufacturers have expressed interest. Under current EPA regulations through MY 2015, GHG em issions compliance values for dual fuel CNG vehicles are based on a methodology that provides significant GHG emissions incentives equivalent to the “CAFE credit” approach for dual and flexible fuel vehicles. For MY 2016, current EPA regulations utilize a methodology based on demonstrated vehicle emissions performance and real world fuels usage, similar to that for ethanol flexible fuel vehicles
discussed below.

EPA proposes to develop a new approach for dual fuel CNG vehicle GHG emissions compliance that is very similar to the utility factor approach developed and described above for PHEVs, and for this new approach to take effect with MY 2016. As with PHEVs, EPA believes that owners of dual fuel CNG vehicles will prefer entially seek to refuel and operate on CNG fuel as much as possible, both because the owner paid a much higher price for the dual fuel capability, and because CNG fuel is considerably cheaper than gasoline on a per mile basis. EPA notes that there are some relevant differences between dual fuel CNG vehicles and PHEVs, and some of these differences might weaken the case for using utility factors for dual fuel CNG vehicles. For example, a dual fuel CNG vehicle might be able to run on gasoline when both fuels are available on board (depending on how the vehicle is designed), it may be much more inconvenient for some private dual fuel CNG vehicle owners to fuel every day relative to PHEVs, and there are many fewer CNG refueling stations than electrical charging facilities. 282
On the other hand, there are differences that could strengthen the case as well, e.g., many dual fuel CNG vehicles will likely have smaller gaso line tanks given the expectation that gasoline will be used only as an “emergency” fuel, and it may be easier for a dual fuel CNG vehicle to be refueled during the day than a PHEV (which is most conveniently refueled at night with a home charging unit).

Taking all these considerations into account, EPA believes that the merit of using a utility factor-based approach for dual fuel CNG vehicles is similar to that of doing so for PHEVs, and we propose to develop a similar methodology for dual fuel CNG vehicles. For example, applying the current SAE fleet utility factor approach developed for PHEVs to a dual fuel CNG vehicle with a 150-mile CNG range would result is a compliance assumption of about 95 percent operation on CNG and about 5 percent operation on gasoline. EPA is proposing to directly extend the PHEV utility factor methodology to dual fuel CNG vehicles, using the same

281 EPA considers “bi-fuel” CNG vehicles to be those vehicl es that can operate on a mixture of CNG and gasoline. Bi-fuel vehicles would not be eligible for this treatment, since they are not designed to allow the use of CNG only.

282 EPA assumes that most PHEV owners will charge at ho me with electrical charging equipment that they purchase and install for their own use.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 274 of 768 assumptions about daily refueling. EPA invites comment on this proposal, including the appropriateness of the assumptions descri bed above for dual fuel CNG vehicles.

In determining eligibility for the utility factor approach, EPA may consider placing additional constraints on the designs of dual fu el CNG vehicles including, but not limited to, whether we should place a minimum value on CN G tank size or CNG range, a maximum value on gasoline tank size or gasoline range, a minimum ratio of CNG-to-gasoline range, and whether we should require an onboard control system so that a dual fuel CNG vehicle is only able to access the gasoline fuel tank if the CNG tank is empty.

iv. Ethanol Flexible Fuel Vehicles

Ethanol FFVs can operate on E85 (a blend of 15 percent gasoline and 85 percent ethanol, by volume), gasoline, or any blend of the two. There are many ethanol FFVs in the market today.

In the final rulemaking for MY 2012-2016, EPA promulgated regulations for MY 2012- 2015 ethanol FFVs that provided significant GHG emissions incentives equi valent to the longstanding “CAFE credits” for ethanol FFVs under the Energy Independence and Security Act of 2007, since many manufacturers had relied on the availability of these credits in developing their compliance strategies. 283 Beginning in MY 2016, EPA ended the GHG emissions compliance incentives and adopted a methodology based on demonstrated vehicle emissions performance. This methodology established a default value assumption where ethanol FFVs are operated 100 percent of the time on gasoline, but allows manufacturers to use a relative E85 and gasoline vehicle emissions performance weighting based either on national average E85 and gasoline sales data, or manufacturer-specific data showing the percentage of miles that are driven on E85 vis-à-vis gasoline for that manufacturer’s ethanol FFVs. 284 EPA is not proposing any changes to this methodology for MY 2017-2025.

EPA believes there is a compelling rationale for not adopting a utility factor-based approach, as discussed above for PHEVs and dual fuel CNG vehicles, for ethanol FFVs. Unlike
with PHEVs and dual fuel CNG vehicles, owners of ethanol FFVs do not pay any more for the E85 fueling capability. Unlike with PHEVs and dual fuel CNG vehicles, operation on E85 is not cheaper than gasoline on a per mile basis, it is typically the same or somewhat more expensive to operate on E85. Accordingly, there is no direct economic motivation for the owner of an ethanol FFVs to seek E85 refueling, and in some cases there is an economic disincentive. Because E85 has a lower energy content per gallon than gasoline, an ethanol FFV will have a lower range on

283 75 FR at 25432-433.

284 75 FR at 25433-434.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 275 of 768 E85 than on gasoline, which provides an additional disincentive. The data confirm that, on a national average basis in 2008, less than one percent of ethanol FFVs used E85 fuel. 285

If, in the future, these economic dynamics were to change (e.g., if E85 were less expensive, on a per mile basis), then EPA would reconsider its approach to this issue.

b. Procedures for CAFE Calculations for MY 2020 and Later

EPCA specifies how the fuel economy of dual fuel vehicles is to be calculated for the purposes of CAFE through the 2019 model year. The basic calculation is a 50/50 harmonic average of the fuel economy for the alternative fuel and the conventional fuel, irrespective of the actual usage of each fuel. In addition, the fuel economy value for the alternative fuel is significantly increased by dividing by 0.15 in the case of CNG and ethanol and by using a petroleum equivalency factor methodology that yields a similar overall increase in the CAFE mpg value for electricity. 286 EPCA section 32905. In a related provision, the amount by which a manufacturer’s CAFE value (for domestic passenger cars, import passenger cars, or light-duty trucks) can be improved by dual fuel vehicles is limited by EPCA to 1.2 mpg through 2014, and then gradually reduced until it is phased out entirely starting in model year 2020. 287 With the expiration of the special calculation procedures in 49 U.S.C. 32905 for dual fueled vehicles, the CAFE calculation procedures for model years 2020 and later need to be set under the general provisions authorizing EPA to establish testing and calculation procedures. 288

With the expiration of the specific procedures fo r dual fueled vehicles, there is less need to base the procedures on whether a vehicle meets the specific definition of a dual fueled vehicle in EPCA. Instead, EPA's focus is on establishing appropriate procedures for the broad range of vehicles that can use both alternative and conventional fuels. For convenience, this discussion uses the term dual fuel to refer to vehicles that can operate on an alternative fuel and on a
conventional fuel.

EPA sees two potential approaches for dual fuel vehicle CAFE calculations for model years 2020 and later. EPA requests comment on the two options discussed here, and we welcome comments on other potential options as well.

Determining the fuel economy of the vehicle for purposes of CAFE requires a determination on how to weight the fuel economy performance on the alternative fuel and the fuel economy performance on the conventional fu el. For PHEVs, dual-fuel CNG vehicles, and FFVs, EPA proposes to apply the same weighting for CAFE purposes as for purposes of GHG

285 75 FR 14762 (March 26, 2010).

286 49 U.S.C. 32905.

287 49 U.S.C. 32906. NHTSA interprets section 32906(a) as not limiting the impact of duel fueled vehicles on CAFE calculations after MY2019. See section IV. XXX.

288 49 U.S.C. 32904(a), (c).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 276 of 768 emissions compliance values. EPA proposes that , for PHEVs and dual-fuel CNG vehicles, the fuel economy weightings will be determined usi ng the SAE utility factor methodology, while for ethanol FFVs, manufacturers can choose to use a default based on 100% gasoline operation, or can choose to base the fuel economy weightings on national average E85 and gasoline use, or on manufacturer-specific data showing the percentage of miles that are driven on E85 vis-à-vis gasoline for that manufacturer’s ethanol FFVs. Where the two options differ is whether the 0.15 divisor or similar adjustment factor is retained or not. EPA believes that there are legitimate arguments both for and against retaining the 0.15 divisor.

EPA proposes to continue to use the 0.15 divisor for CNG and ethanol, and the petroleum equivalency factor for electricity, both of which are required to be used through 2019, for model years 2020 and later. EPA believes there are two primary arguments for retaining the 0.15 divisor and petroleum equivalency factor. One, this approach is directionally consistent with the overall petroleum reduction goals of EPCA and the CAFE program. Two, the 0.15 divisor and petroleum equivalency factor are used under EPCA to calculate CAFE compliance values for dedicated alternative fuel vehicles, and retaining this approach for dual fuel vehicles would maintain consistency, for MY 2020 and later, between the approaches for dedicated alternative
fuel vehicles and for the alternative fuel portion of dual fuel vehicle operation.

EPA recognizes that this proposed calculat ion procedure would continue to provide, directionally, an increase in fuel economy valu es for the vehicles previously covered by the special calculation procedures in 49 U.S.C. 32905, and that Congress chose both to end the specific calculation procedures in that section and over time to reduce the benefit for CAFE purposes of the increase in fuel economy mandated by those special calculation procedures. However the proposed provisions differ signific antly in important wa ys from the special calculation provisions mandated by EPCA. Most importantly, they are changed to reflect actual usage rates of the alternative fuel and do not use the artificial 50/50 weighting previously mandated by 49 U.S.C. 32905. In practice this means the primary vehicles to benefit from the proposed provision will be PHEVs and dual-fuel CNG vehicles, and not FFVs, while the primary source of benefit under 49 U.S.C. 32905 came from FFVs. Changing the weighting to better reflect real world usage is a major change from that mandated by 49 U.S.C. 32905, and it orients the calculation procedure more to the real world impact on petroleum usage. In addition, as noted above, Congress clearly continued the calculation procedures for dedicated alternative fuel vehicles that result in increased fuel economy valu es. This proposed approach is consistent with this, as it uses the same approach for calculating fuel economy on the alternative fuel when there is real world usage of the alternative fuel. Si nce the proposed provisions are quite different in effect from the specified provisions in 49 U.S.C. 32905, and are consistent with the calculation procures for dedicated vehicles that use the sa me alternative fuel, EPA believes this proposal would be an appropriate exercise of discretion under the general authority provided in 49 U.S.C.

32904.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 277 of 768 An alternative option to the above proposal, and about which EPA seeks comment, is to not adopt the 0.15 divisor and petroleum equivalency factor for model years 2020 and later. The fuel economy for the CNG portion of a dual fuel CNG vehicle and the electric portion of a PHEV would be determined strictly on an energy -equivalent basis, without any adjustment based on the 0.15 divisor or petroleum equivalency f actor. For E85 FFVs, the manufacturer would almost certainly use the gasoline fuel economy value only. 289 This approach would place less emphasis on conservation of petroleum and more on conservation of energy. It would also place more emphasis on Congress' decision to reduce over time the impact on CAFE from the increased fuel economy values derived from the specified calculation procedures in 49 U.S.C. 32905. EPA invites comment on both approaches.

5. Off-cycle Technology Credits

For MYs 2012-2016, EPA provided an option for manufacturers to generate credits for employing new and innovative technologies that achieve CO 2 reductions which are not reflected on current 2-cycle test procedures. For this proposal, EPA, in coordination with NHTSA, is proposing to apply the off-cycle credits and equivalent fuel consumption improvement values to both the CAFE and GHG programs. This proposed expansion is a change from the 2012-16 final rule where only EPA provided the off-cycle cred its for the GHG program. For MY 2017 and later, EPA is proposing that manufacturers may continue to use off-cycle credits for GHG compliance and begin to use fuel consumption improvement values (essentially equivalent to EPA credits) for CAFE compliance. In addition, EPA is proposing a set of defined (e.g. default) values for identified off-cycle technologies that would apply unless the manufacturer
demonstrates to EPA that a different value fo r its technologies is appropriate. The proposed changes to incorporate off-cycle technologies for the GHG prog ram are described in Section III.C.a-b below, and for the CAFE program are described in Section III.C.5.c below.

a. Off-cycle Credit Program Adopted in MY 2012-2016 Rule

In the MY 2012-2016 Final Rule, EPA adopted an optional credit opportunity for new and innovative technologi es that reduce vehicle CO 2 emissions, but for which the CO 2 reduction benefits are not significantly captured over the 2-cycle test procedure used to determine compliance with the fleet average standards (i.e., “off-cycle”). 290 EPA indicated that eligible innovative technologies are those that may be relatively newly introduced in one or more vehicle models, but that are not yet implemented in widespread use in the light-duty fleet, and which provide novel approaches to reducing greenhouse gas emissions. The technologies must have

289 Manufacturers can also can choose to base the fuel economy weightings on national average E85 and gasoline use, or on manufacturer-specific data showing the percentage of miles that are driven on E85 vis-à-vis gasoline for that manufacturer’s ethanol FFVs, but since E85 fuel ec onomy ratings are based on miles per gallon of E85, not adjusted for energy equivalency with gasoline, E85 mpg va lues are lower than gasoline mpg values, which makes this a non-option.

290 75 FR 25438-440,Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 278 of 768 verifiable and demonstrable real-world GHG reductions. 291 EPA adopted the off-cycle credit option to provide an incentive to encourage th e introduction of these types of technologies, believing that bona fide reductions from these technologies should be considered in determining a manufacturer’s fleet average, and that a credit mechanism is an effective way to do this. This optional credit opportunity is currently available through the 2016 model year.

EPA finalized a two-tiered process for OEMs to demonstrate that CO 2 reductions of an innovative and novel technology are verifiable and measureable but are not captured by the 2- cycle test procedures. First, a manufacturer must determine whether the benefit of the technology could be captured using the 5-cycle methodology currently used to determine fuel economy label values. EPA established the 5-cycle test methods to better represent real-world factors impacting fuel economy, including higher speeds and more aggressive driving, colder temperature operation, and the use of air conditioning. If this determination is affirmative, the manufacture must follow the 5-cycle procedures.

If the manufacturer finds that the technology is such that the benefit is not adequately captured using the 5-cycle approach, then the manufacturer would have to develop a robust methodology, subject to EPA approval, to demonstrate the benefit and determine the appropriate

CO 2 gram per mile credit. This case-by-case , non-5-cycle credits approach includes an opportunity for public comment as part of the approval process. The demonstration program must be robust, verifiable, and capable of demons trating the real-world emissions benefit of the technology with strong statistical significance. Whether the approach involves on-road testing, modeling, or some other analytical approach, the manufacturer is required to present a proposed methodology to EPA. EPA will approve the methodology and credits only if certain criteria are
met. Baseline emissions and control emissions must be clearly demonstrated over a wide range of real world driving conditions and over a suffici ent number of vehicles to address issues of uncertainty with the data. Data must be on a vehicle model-specific basis unless a manufacturer demonstrated model specific data was not necessary. See generally 75 FR at 25438-40.

b. Proposed Changes to the Off-cycle Credits Program

EPA has been encouraged by automakers’ inte rest in off-cycle credits since the program was finalized. Though it is early in the program, several manufacturers have shown interest in introducing off-cycle technologies which are in various stages of development and testing. EPA believes that continuing the option for off-cycle credits would further encourage innovative strategies for reducing CO 2 emissions beyond those measured by the 2-cycle test procedures. Continuing the program provides manufacturers with additional flexibility in reducing CO 2 to meet increasingly stringent CO 2 standards and to encourage early penetration of off-cycle technologies into the light duty fleet. Furthermore, extending the program may encourage automakers to invest in off-cycl e technologies that could have th e benefit of realizing additional

291 See 40 CFR section 1866.12 (d); 75 FR at 25438.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 279 of 768 reductions in the light-duty fleet over the longer-term. Therefore, EPA is proposing to extend the off-cycle credits program to 2017 and later model years.

In implementing the program, some manufacturers have expressed concern that adrawback to using the program is uncertainty over which technologies may be eligible for offcycle credits plus uncertainties resulting from a case-by-case approval process. Current EPA eligibility criteria require technologies to be new, innovative, and not in widespread use in order to qualify for credits. Also, the MY 2012-2016 Fi nal Rule specified that technologies must not be significantly measurable on the 2-cycle test procedures. As discussed below, EPA proposes to significantly modify the eligibility criteria, as the current criteria are not well defined and have been a source of uncertainty for manufacturers, thereby interfering with the goal of providing an incentive for the development and use of additional technologies to achieve real world reductions
in CO2 emissions. The focus will be on whether or not add-on technologie s can be demonstrated to provide off-cycle CO 2 emissions reductions that are not sufficiently reflected on the 2-cycle

tests.

In addition, as described below in section III.C.5.b.i, EPA is proposing thatmanufacturers would be able to generate credits by applying technologies listed on an EPA predefined and pre-approved technology list starting with MY 2017. These credits would be verified and approved as part of certification with no prior approval process needed. We believe this new option would significantly streamlin e and simplify the program for manufacturers choosing to use it and would provide manufacturers with certainty that cr edits may be generated through the use of pre-approved technologies. For credits not based on the pre-defined list, EPA is proposing to streamline and better define a step-by-step process for demonstrating emissions reductions and applying for credits. EPA is proposing that these procedural changes to the caseby-case approach would be effective for new credit applications for both the remaining years of the MY 2012-2016 program as well as for MY 2017 and later credits that are not based on the pre-defined list.

As discussed in section II.F. and III.B.10, EP A, in coordination w ith NHTSA, is also proposing that manufacturers be able to include fuel consumption reductions resulting from the use of off-cycle technologies in their CAFE compliance calculations. Manufacturers would generate “fuel consumption improvement values” essentially equivalent to EPA credits, for use in the CAFE program. The proposed changes to the CAFE program to incorporate off-cycle technologies are discussed below in section III.5.c.

i. Pre-defined Credit List for MY 2017 and Later

As noted above, EPA proposes to establish a list of off-cycle technologies from which manufacturers could select to earn a pre-defined level of CO 2 credits in MY 2017 and later. Both technologies and credit values based on the list would be pre-approved. The manufacturer would demonstrate in the certification process that their technology meets the definition of theSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 280 of 768 technology in the list. Table III-16 provides an initial proposed list of the technologies and per vehicle credit levels for cars and light trucks. EPA has used a combination of available activity data from the MOVES model, vehicle and test da ta, and vehicle simulation modeling to estimate a proposed credit value EPA believes to be appropriate. Chapter 5 of the joint TSD provides a detailed description of how these technologies are defined and how the proposed credits levels
were derived.

Table III-16 Off-cycle Technologies and Proposed Credits for Cars and Light
Trucks

Technology Credit for Cars Credit for Light
Trucks g/mi g/mi High Efficiency Exterior Lighting 1.1 1.1 Engine Heat Recovery 0.7 0.7
Solar Roof Panels 3.0 3.0 Active Aerodynamic Improvements 0.6 1.0 Engine Start-Stop 2.9 4.5
Electric Heater Circul ation Pump 1.0 1.5 Active Transmission Warm-Up 1.8 1.8 Active Engine Warm-Up 1.8 1.8 Solar Control Up to 3.0 Up to 4.3

Two technologies on the list - active aerodynamic improvements and stop start – are in a different position than the other technologies on the list. Both of these technologies are included in the agencies’ modeling analysis of technologies projected to be available for use in achieving the reductions needed for the standards. We have information on their effectiveness, cost, and availability for purposes of considering them along with the various other technologies we
consider in determin ing the appropriate CO 2 emissions standard. These technologies are among those listed in Chapter 3 of the joint TSD and have measureable benefit on the 2-cycle test. However in the context of off-cycle credits, stop start is any technology which enables a vehicle to automatically turn off the engine when the vehicle comes to a rest and restart the engine when the driver applies pressure to the accelerator or releases the brake. This includes HEVs and PHEVs (but not EVs). In addition, active grill s hutters is just one of various technologies that can be used as part of aerodynamic design improvements (as part of the “aero2” technology). The modeling and other analysis developed for determining the appropriate emissions standard includes these technologies, using the effectiveness va lues on the 2-cycle test. This is consistent
with our consideration of all of the other technolo gies included in these analyses. Including them on the list for off-cycle credit generation, for purposes of compliance with the standard, would recognize that these technologies have a higher de gree of effectiveness than reflected in their 2- cycle effectiveness. The agencies have taken into account the generation of off-cycle credits bySummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 281 of 768 these two technologies in determining the appropri ateness of the proposed standards, considering the amount of credit, the projected degree of penetr ation of these technologies, and other factors.
Section III.D has a more detailed discussion on the feasibility of the standa rds within the context of the flexibilities (such as off-cycle credits) propos ed in this rule. As discussed in section III.D., EPA plans to incorporate the off-cycle credits for these two technologies in the cost analysis for the final rule (which EPA anticipates would slightly reduce costs with no change to benefits). EPA requests comments on this approach for stop start and active aerodynamic improvements.

Although EPA believes that there is sufficient information to estimate performance of other listed technologies for purposes of a credit program, EPA does not believe it appropriate to reflect these technologies in setting the level of st andards at this point. There remains significant uncertainty as to the extent listed technologi es other than stop start and active aerodynamic improvements may be used across the light duty fleet and (in some instances) costs of the technologies. Including them in the standard se tting, as is done with A/C control technology, calls for a reasonable projection of the penetration of these technologies across the fleet and over time, along with reasonable estimates of their cost . EPA does not have adequate data at this point in time to make such fleet wide projections for other technologies on the list, or for other technologies addressed by the case-by-case approach. As in the 2012-2016 rule, the use of these technologies continues to be not nearly so well developed and understood for purposes of consideration in setting the standards. See 75 FR at 25438. Based on this, technologies that are considered by EPA in setting the standard, as di scussed in section III.D and in Chapter 3 of the TSD, may not generate off-cycle credits under this approach, except for active aerodynamic improvements and stop start. 292 This would amount to the double counting discussed at 75 FR 25438, as EPA has already considered these t echnologies and assigned them an emission reduction effectiveness for purposes of standard setting, and has enough information on effectiveness, cost, and applicability to project their use for purposes of standard setting. EPA will reassess the list above for the Final Rule, based on additional information that becomes available during the comment period. It may also be appropriate to reconsider this approach as part of the mid-term review as information on these technologies’ applicability, costs, and performance becomes more robust.

EPA proposes to cap the amount of credits a manufacturer could generate using the above list to 10 g/mile per year on a combined car an d truck fleet-wide average basis. The cap would not apply on a vehicle model basis, allowing manufacturers the flexibility to focus off-cycle technologies on certain vehicle models and generate credits for that vehicle model in excess of 10 g/mile. EPA is proposing a fleet-wide cap because the proposed credits are based on limited data, and also EPA recognizes that some uncertainty is introduced when credits are provided based on a general assessment of off-cycle performance as opposed to testing on the individual

292 Section III.D provides EPA projected technology penetrat ion rates. Technologies projected to be used to meet the standards would not be eligible for off-cycle cred its, with the exception of stop start and active aerodynamic improvements.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 282 of 768 vehicle models. Also, as discussed in Chapter 5 of the draft TSD, EPA believes the credits proposed are based on conservative estimates, pr oviding additional assurance that the list would
not result in an overall loss of CO 2 benefits. EPA proposes that manufacturers wanting to generate credits in excess of th e 10 g/mile limit for these listed technologies could do so by generating necessary data and going through the credit approval process described below in
Section III.C.5.b.iii and iv.

As noted above, EPA proposes to make the list available for credit generation starting in MY 2017.. Prior to MY 2017, manufacturers would need to demonstrate off-cycle emissions reductions in order to generate credits for off-cycle technologies, including those on the list. Requirements for demonstrating off-cycle credits not based on the list are described below. Manufacturers may also opt to generate data for listed technologies in MY 2017 and later where they are able to demonstrate a credit value greater than that provided on the list.

Prior to MY2017, EPA would continue to evalua te off-cycle technologies. Based on data provided by manufacturers for non-listed techno logies, and other available data, EPA would consider adding technologies to the list through rulemaking or issuing guidance in the future for additional off-cycle technologies, indicating the level of credits that EPA expects could be approved for any manufacturer through the case-by-case approach, helping to streamline the case-by-case approach until a rulemaking was conducted to update the list. If the CO 2 reduction benefits of a technology have been established through manufacturer data and testing, EPA believes that it would be appropriate to list th e technology and a conservative associated credit
value.

Since one purpose of the off-cycle credits is to encourage market penetration of the technologies (see 75 FR at 25438), EPA also proposes to require minimum penetration rates for non-hybrid based listed technologies as a condition for generating credit from the list as a way to further encourage their widespread adoption by MY 2017 and later. At the end of the model year for which the off-cycle credit is claimed, manufacturers would need to demonstrate that production of vehicles equipped with the technologies for that model year exceeded the percentage thresholds in order to receive the listed credit. EPA proposes to set the threshold at 10 percent of a manufacturer’s overall combined car and light truck production for all technologies not specific to HEVs. EPA believes 10 percent is an appropriate threshold as it would encourage manufacturers to develop technologies for use on larger volume models and bring the technologies into the mainstream. On the other hand, EPA is not proposing a larger value because EPA does not want to discourage the use of technologies. For solar roof panels (solar control) and electric heater circulati on pumps, which are HEV-specific, EPA is not proposing a minimum penetration rate threshold for credit generation. Hybrids may be a small subset of a manufacturer’s fleet, less than 10 percent in some cases, and EPA does not believe establishing a threshold for hybrid-based technol ogies would be useful and could unnecessarily impede the introduction of these technologies. EPA requests comments on applying this type ofSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 283 of 768 threshold, the appropriateness of 10 percent as the threshold for listed technologies that are not HEV-specific, and the proposed treatme nt of hybrid-based technologies.

ii. Proposed Technology Eligibility Criteria

EPA proposes to remove the criteria in the 2012-2016 rule that off-cycle technologies must be ‘new, innovative, and not widespread’ because these terms are imprecise and have created implementation issues and uncertainty in the program. For example, it is unclear if technologies developed in the past but not used extensively would be considered new, if only the first one or two manufacturers using the technolo gy would be eligible or if all manufacturers could use a technology to generate credits, or if credits for a technology would sunset after a period of time. It has also been unclear if a technology such as active aerodynamics would be eligible since it provides a small measurable reduction on the 2-cycle test but provides additional reductions off-cycle, especially du ring high speed driving. These criteria have interfered with the goal of providing an incentive for the development and use of off-cycle technology that
reduces CO 2 emissions. EPA proposes this approach for new MY 2012-2016 credits as well as
for MY 2017-2025.

EPA believes it is appropriate to provide credit opportunities for technologies that achieve bona fide real world reductions beyond t hose measured under the two-cycle test without further making (somewhat subjective) judgments regarding the newness and innovativeness of the technology. Instead, EPA proposes to provide off-cycle credits for any technologies that are
added to a vehicle model that are demonstrated to provide significant incremental off-cycle CO 2 reductions, like those on the list. The proposed technology demonstration and step-by-step application process is described in detail below in section III.C.5.b.ii. EPA is proposing to clarify that technologies providing small reductio ns on the 2-cycle tests but additional significant reductions off-cycle could be eligible to generate off-cycle credits. EPA thus proposes to remove the “not significantly measurable over th e 2-cycle test” criteria. EPA proposes that, instead, manufacturers must be able to make a demonstration through testing with and without the off-cycle technology.

As noted above, EPA proposes that technologies included in EPA’s assessment in this rulemaking of technology for purposes of developing the standard would not be allowed to generate off-cycle credits, as their cost and eff ectiveness and expected use are already included in the assessment of the standard. (As explained above, the agencies have done so with respect to stop start and active aerodynamic improvements by including the projected level of credits in determining the appropriateness of the proposed standards.) EPA proposes that technologies integral or inherent to the basic vehicle design including engine, transmission, mass reduction, passive aerodynamic design, and base tires would not be eligible for credits. For example, manufacturers would not be able to generate o ff-cycle credits by moving to an eight-speed
transmission. EPA believes that it would be diffic ult to clearly establish an appropriate A/B testSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 284 of 768 (with and without technologies) for technologies so integral to the basic vehicle design. EPA proposes to limit the off-cycle program to technolo gies that can be clearly identified as add-on technologies conducive to A/B testing. Further, EPA would not provide credits for a technology required to be used by Federal law, such as tire pressure monitoring systems, as EPA would consider such credits to be windfall credits (i.e. not generated as a result of the rule). The base versions of such technologies would be considered part of the base vehicle. However, if a manufacturer demonstrates that an improvement to such technologies provides additional offcycle benefits above and beyond a system meeting minimum Federal requirements, those incremental improvements could be eligible for off-cycle credits, assuming an appropriate quantification of credits is demonstrated.

By proposing to remove the “new, innovative, not widespread use” criteria in the present rule, EPA is also making clear that once approv ed, EPA does not intend to sunset a technology’s credit eligibility or deny credits to other vehicl e applications using the technology, as may have been implied by those criteria under the MY 2012-2016 program. EPA believes, at this time, that it should encourage the wider use of t echnologies with legitimate off-cycle emissions benefits. Manufacturers demonstrating through the EPA approval process that the technology is
effective on additional vehicle mode ls would be eligible for credits. Limiting the application of a technology or sunsetting the availability of credits during the 2017-2025 time frame would be counterproductive because it would remove part of the incentive for manufacturers to invest in developing and deploying off-cy cle technologies, some of which may be promising but have considerable development costs associated with them. Also, approving a technology only to later disallow it could lead to a manufacturer discontinuing the use of the technology even if it remained a cost effective way to reduce emissions. EPA also believes that this approach provides an incentive for manufacturers to conti nue to improve technologies without concern that they will become ineligible for credits at some future time. EPA requests comments on all aspects of the above approach for the off-cycle credits program criteria.

iii. Demonstrating Off-cycle Emissions Reductions

5-cycle testing

EPA is retaining a two-tiered process for demonstrating the CO 2 reductions of off-cycle technologies (in those instances when a manufacturer is not using the default value provided by the rule), but is clarifying several of the requirements. The process described below would be used for all credits not based on the pre-defined list described in Section III.C.5.i, above. As noted above, the proposed approach would replace the requirement in the 2012-2016 rule that technology must not be “significantly measurabl e” over the 2-cycle test. See section 86. 1866-12 (d) (ii). This criterion has been problematic because several technologies provide some benefit on the 2-cycle test but much greater benefits off-cycle. Under today’s proposal, technologies would need to be demonstrated to provide signi ficant incremental off-cycle benefits above andSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 285 of 768 beyond those provided over the 2-cycle test. EPA proposes this approach for new MY 2012-
2016 credits as well as for MY 2017-2025.

The 5-cycle test procedures would remain the starting point for demonstrating off-cycle emissions reductions. The MY 2012-2016 rulemaking established general 5-cycle testing requirements and EPA is proposing several provis ions to delineate what EPA would expect as part of a 5-cycle based demonstration. Manufacturers requested clarification on the amount of 5- cycle testing that would be needed to demonstr ate off-cycle credits, and EPA is proposing the following as part of the step-by-step met hodology manufacturers would follow to generate credits. In addition to the general 5-cycle demonstration requirements of the MY 2012-2016 program, EPA proposes to specifically require model-based verification of 5-cycle results where off-cycle reductions are small and could be a pr oduct of testing variability. EPA is also proposing to specifically require that all applicatio ns include an engineering analysis for why the technology provides off-cycle emissions reductions . EPA proposes to specify that manufacturerswould run an initial set of three 5-cycle tests with and without the technology providing the offcycle CO 2 reduction. Testing must be conducted on a representative vehicle, selected using good engineering judgment, for each vehicle model. EPA proposes that manufacturers could bundle off-cycle technologies together for testing in order to reduce testing costs and improve their ability to demonstrate consistently measurable reductions over the tests. If these A/B 5-cycle tests demonstrate an off-cycle benefit of 3 percent or greater, comparing average test results with and without the off-cycle technology, the manufacturer would be able to use the data as the basis for credits. EPA has long used 3 percent as a threshold in fuel economy confirmatory testing for determining if a manufacturer’s fuel economy test results are comparable to those run by EPA. 293

If the initial three sets of 5-cycle results demonstrate a reduction of less than a 3 percent difference in the 5-cycle results with and with out the off-cycle technology, the manufacturer
would have to run an additional two additiona l 5-cycle tests with and without the off-cycle technologies and verify the emission reduction using the EPA Light-duty Simulation Tool described below. If the simulation tool supports credits that are less than 3 percent of the baseline 2-cycle emissions, then EPA would approve the credits based on the test results. As outlined below, credits based on this methodology would be subject to a 60 day EPA review period starting when EPA receives a complete ap plication, which would not include a public
review.

EPA believes that small off-cycle credit claims (i.e., less than 3 percent of the vehicle model 2-cycle CO 2 level) should be supported with modeling and engineering analysis. EPA is proposing the approach above for a number of reasons. Emissions reductions of only a few grams may not be statistically significant and could be the product of gaming. Also,
manufacturers have raised test-to-test variabilit y as an issue for demonstrating technologies through 5-cycle testing. Modeling and engineering analyses can help resolve these questions.

293 40 CFR 600.008 (b)(3).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 286 of 768 EPA also requests comments on allowing manufacturers to use the EPA simulation tool and engineering analysis in lieu of additional 5-cycl e testing. For some technologies providing very small incremental benefits, it may not be possible to accurately measure their benefit with vehicle testing.

Demonstrations not based on 5-cycle testing

In cases where the benefit of a technological approach to reducing CO 2 emissions cannot be adequately represented using 5-cycle testing, manufacturers will need to develop test procedures and analytical approaches to estimate the effectiveness of the technology for the purpose of generating credits. See 75 FR at 25440

. EPA is not proposing to make significant changes to this aspect of the program. If the 5-cycle process is inadequate for the specific technology being considered by the manufacturer (i .e., the 5-cycle test does not demonstrate any emissions reductions), then an alternative approach may be developed by the manufacturer and submitted to EPA for approval. The demonstration program must be robust, verifiable, and capable of demonstrating the real-world emissions benefit of the technology with strong statistical significance. The methodology develope d and submitted to EPA would be subject to public review as explained at 75 FR 25440 and in 86.1866 (d) (2)(ii).

EPA has identified two general situations where manufacturers would need to develop their own demonstration methodology. The first is a situation where the technology is active only during certain operating conditions that are not represented by any of the 5-cycle tests. To determine the overall emissions reductions, manufact urers must determine not only the emissions impacts during operation but also real-world activit y data to determine how often the technology is utilized during actual, in-use driving on average across the fleet. EPA has identified some of these types of technologies and has calculated a default credit for them, including items such as high efficiency (e.g., LED) lights and solar panels on hybrids. See Table III-4 above. In their demonstrations, manufacturers may be able to apply the same type of methodologies used by EPA as a basis for these default values (see TSD Chapter 5).

The second type of situation where manuf acturers would need to develop their own demonstration data would be for technologies that involve action by the driver to make the technology effective in reducing CO 2 emissions. EPA believes that driver interactive technologies face the highest demonstration hurdle because manufacturers would need to provide actual real-world usage data on driver response rates. Such technologies would include “eco buttons” where the driver has the option of selecting more fuel efficient operating modes, traffic avoidance systems, and more advanced tire pressure monitor systems (i.e., technologies that go beyond the minimum Federal requirements) notifying the driver to fill their tires more often. 294
EPA proposes that data would need to be from instrumented vehicles and not through driver

294 A tire pressure monitor system that also automatically fills the tire without driver interaction would obviously not involve driver response data for the automatic system, but the demonstration may involve the driver response rates for the baseline system to dete rmine an incremental credit.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 287 of 768 surveys where drivers try to recall their response behavior. Systems such as On-star could be one promising way to collect driver response data if they are designed to do so. Manufacturers might have to design extensive on-road test programs. Any such on-road testing programs would need to be statistically robust and based on average U.S. driving conditions, factoring in differences in geography, climate, and driving behavior across the U.S. EPA proposes this approach for new
MY 2012-2016 credits as well as for MY 2017-2025.

EPA Light-duty Vehicle Simulation Tool

As explained above and further discussed in Section III.C.5.d below, EPA has developed full vehicle simulation capabilities in order to support regulations and vehicle compliance by quantifying the effectiveness of different technol ogies with scientific rigor over a wide range of engine and vehicle operating conditions. This in -house simulation tool has been developed for modeling a wide variety of light, medium, and heavy duty vehicle applications over various driving cycles. In order to ensure transparen cy of the models and free public access, EPA has developed the tool in MATLAB/Simulink environment with a completely open source code. EPA’s first application of the vehicle simulati on tool was for purposes of heavy-duty vehicle compliance and certification. For the model years 2014 to 2017 final rule for medium and heavy duty trucks, EPA created the “Greenhouse gas Emissions Model” (GEM), which is used both to
assess Class 2b-8 vocational vehicle and Class 7/8 combination tractor GHG emissions and fuel efficiency and to demonstrate compliance with the vocational vehicle and combination tractor
standards. See 76 FR at 57146-147. 295 EPA will submit the simulation tool for peer review for the final rule. Chapter 2 of the Draft RIA ha s more details of this simulation tool.

As mentioned previously, the tool is based on MATLAB/Simulink and is a forwardlooking full vehicle model that uses the same physical principles as other commercially available vehicle simulation tools (e.g. Autonomie, AV L-CRUISE, GT-Drive, etc.) to derive the governing equations. These governing equations de scribe steady-state and transient behaviors of each of electrical, engine, transmission, driveline, and vehicle systems, and they are integrated together to provide overall system behavior dur ing transient conditions as well as steady-state operations. In the light-duty vehicle simulation tool, there are four key system elements that describe the overall vehicle dynamics behavior and the corresponding fuel efficiency: electrical, engine, transmission, and vehicle. The electrical system model consists of parasitic electrical load and A/C blower fan, both of which were assumed to be constant. The engine system model is comprised of engine torque and fueling maps . For the vehicle system, four vehicles were modeled: small, mid, large size passenger vehicles, and a light-duty pick-up truck. The engine maps, transmission gear ratios and shifting sche dules were appropriately sized and adjusted

295 See also US EPA, “Final Rule Making to Establish Greenhouse Gas Emissions Standards and Fuel Efficiency Standards for Medium- and Heavy-Duty Engines and Vehicl es,” Heavy-Duty Regulatory Impact Analysis.give cite to where GEM is written up in theheavy duty RIASummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 288 of 768 according to the vehicle type represented by the simulation. Chapter 2 of the Draft Regulatory Impact Analysis provides more details on this light-duty vehicle simulation tool.

As discussed in section III.C.1, EPA has used the light-duty vehicle simulation tool to
estimate indirect A/C CO 2 emissions from conventional (non-hybrid) vehicles, helping to quantify the indirect A/C credit. In addition to A/C related CO 2 reductions, EPA believes this same simulation tool may be useful in estimating CO 2 reductions from off-cycle technologies. Currently, the model provides A/B relative compar isons with and without technologies that can help inform credits estimates. EPA has used it to estimate credits for some of the technologies in the proposed pre-defined list, including active aerodynamic improvements. As discussed above, EPA is proposing to require this simulation tool be used as an additional way to estimate emissions reductions in cases where the 5-cycle test results indicate the potential reductions to be small, and EPA is also requesting comments on using the simulation tool as a basis for estimating off-cycle credits in lieu of 5-cycle testing.

iv. In-use Emissions Requirements

EPA requires off-cycle components to be durable in-use and continues to believe that this is an important aspect of the program. See 86.1866-12 (d)(1)(iii). The technologies upon which the credits are based are subject to full useful li fe compliance provisions, as with other emissions controls. Unless the manufacturer can demonstrate that the technology would not be subject to
in-use deterioration over the useful life of the vehicle, the manufacturer must account for
deterioration in the estimation of the credits in order to ensure that the credits are based on real in-use emissions reductions over the life of the vehicle. In-use requirements would apply to technologies generating credits based on the pre-defined list as well as to those based on a
manufacturer’s demonstration.

Manufacturers have requested clarification of these provisions and guidance on how to demonstrate in-use performance. EPA is proposing to clarify that off-cycle technologies are considered emissions related components and a ll in-use requirements apply including defect reporting, warranty, and recall. OBD requirements do not apply under the MY 2012-2016 program and EPA is not proposing any OBD requirements at this time for off-cycle technologies. Manufacturers may establish maintenance intervals for these components in the same way they would for other emissions related components. The performance of these components would be considered in determining complian ce with the applicable in-use CO 2 standards. Manufacturers may demonstrate in-use emissions durability at time of certification by submitting an engineering analysis describing why the technology is durable and expected to last for the full useful life of the vehicle. This demonstration may also include component durability testing or through whole vehicle aging if the manufacturer has such data. The demonstration would be subject to EPA approval prior to credits being awarded. 296 EPA believes these provisions are important to

296 Listed technologies are pre-approved assumi ng the manufacturer demonstrates durability.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 289 of 768 ensure that promised emissions reductions and fuel economy benefit to the consumer are delivered in-use. EPA requests comments on the ab ove approach for in-use emissions durability.

v. Step-by-Step EPA Review Process

EPA proposes to provide a step-by-step process and timeline for reviewing credit applications and providing a decision to manufacturers. EPA requests comments on the process described below including comments on how to further improve or streamline it while maintaining its effectiveness. EPA proposes thes e clarifications and further detailed step-b-step
instructions for new MY 2012-2016 credits as well as for MY 2017-2025. EPA believes these additional details are consistent with the general off-cycle requirements adopted in the MY 2012- 2016 rule. Starting in MY 2017, EPA is proposing that manufacturers may generate credits using technologies on a pre-defined list, and th ese technologies would not be required to go through the approval process described below.

Step 1: Manufacturer Conducts Testing and Prepares Application

 5-cycle - Manufacturers would conduct the testing and/or simulation described
above

 Non 5-cycle - Manufacturers would develop a methodology for non 5-cycle based demonstration and carry-out necessary testing and analysis

o Manufacturers may opt to meet with EPA to discuss their plans for demonstrating technologies and seek EPA input prior to conducting testing or analysis

 Manufacturers conduct engineering analysis and/or testing to demonstrate in-use durability

Step 2 : Manufacturer Submits Application

The manufacturer application must contain the following:

 Description of the off-cycle technologi es and how they function to reduce offcycle emissions

 The vehicle models on which the technology will be applied

 Test vehicles selection and supporting e ngineering analysis for their selection

 5-cycle test data, and/or including si mulation results using EPA Light-duty Simulation Tool, as applicable

 For credits not based on 5-cycle testing, a complete description of methodology used to estimate credits and supporting data (vehicle test data and activity data)

o Manufacturer may seek EPA input on methodology prior to conducting testing or analysisSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 290 of 768  An estimate of off-cycle credits by vehicle model, and fleetwide based on projected vehicle sales

 Engineering analysis and/or component durability testing or whole vehicle test data (as necessary) demonstrating in-use durability of components

Step 3: EPA Review

Once EPA receives an application, EPA would do the following:

 EPA will review the application for comp leteness and within 30 days will notify
the manufacturer if additiona l information is needed

 EPA will review the data and information pr ovided to determine if the application supports the level of credits estimated by manufacturers

 For applications where the rule specifi es public participation in the review process, EPA will make the applications av ailable to the public within 60 days of receiving a complete application

o The public review period will be 30 da y review of the methodology used by the manufacturer to estimate credits , during which time the public may
submit comments.

o Manufacturers may submit a written rebuttal of comments for EPA consideration or may revise their application in response to comments following the end of the public review period.

Step 4: EPA Decision

 For applications where the rule does not specify public participation and review, EPA will notify the manufacturer of its decision within 60 days of receiving a complete application

 For applications where the rule does specify public participation and review, EPA will notify the manufacturer of its deci sion on the application after reviewing public comments.

 EPA will notify manufacturers in writing of its decision to approve or deny the credits application, and provide a written explanation for its action (supported by the administrative record for the application proceeding)

c. Off-cycle Technology Fuel Consumptio n Improvement Values in the CAFE Program

EPA proposes, in coordination with NHTSA, that manufacturers would be able to generate fuel consumption improvement values for use in the CAFE program. The fuel consumption improvement values for listed technologies are provided below. For fuel consumption improvement values not based on the list, manufacturers would go though the stepsSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 291 of 768 described above in Section III.C.5.b. Once a CO 2 credits has been determined, the credit would be converted to a gallons per mile fuel consumption improvement value using the 8887 conversion factor for gasoline engines (CO 2 credits would be divided by 8887). EPA would approve credit generation and corresponding fuel consumption improvement values in
consultation with NHTSA.

III-17 Proposed Fuel Consumption Improvement Values

Technology Cars Light Trucks gallons/mi gallons/mi High Efficiency Exterior Lighting 0.000124 0.000124 Engine Heat Recovery 0.000778 0.000778
Solar Roof Panels 0.000338 0.000338 Active Aerodynamic Improvements 0.0000675 0.000113 Engine Start-Stop 0.000326 0.000506
Electric Heater Circulat ion Pump 0.000123 0.000169 Active Transmission Warm-Up 0.000203 0.000203 Active Engine Warm-Up 0.000203 0.000203 Solar Control Up to 0.000338 Up to 0.000484

d. Vehicle Simulation Model

Chapter 2 of the RIA provides a detailed desc ription of the vehicle simulation tool that EPA has been developing. This tool is capable of simulating a wide range of conventional and advanced engines, transmissions, and vehicle te chnologies over various driving cycles. It evaluates technology package effectiveness while taking into account synergy (and dis-synergy) effects among vehicle components and estimates GHG emissions for various combinations of technologies. For the 2017 to 2025 GHG proposal, this simulation tool was used to assist estimating the amount of GHG credits for improved A/C systems and off-cycle technologies.EPA seeks public comments on this approach of using the tool for directly generating and finetuning some of the credits in order to capture the amount of GHG reductions provided by primarily off-cycle technologies.

There are a number of technologies that c ould bring additional GHG reductions over the 5-cycle drive test (or in the real world) compar ed to the combined FTP/Highway (or two) cycle test. These are called off-cycle technologies and are described in chapter 5 of the Joint TSD in detail. Among them are technologies related to reducing vehicle’s electrical loads, such as High Efficiency Exterior Lights, Engine Heat Recove ry, and Solar Roof Panels. In an effort to streamline the process for approving off-cycle cr edits, we have set a relatively conservative estimate of the credit based on our efficacy analysis. EPA seeks comment on utilizing the model in order to quantify the credits more accurately, if actual data of electrical load reduction and/orSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 292 of 768 on-board electricity generation by one or more of these technologies is available through data submission from manufacturers. Similarly, there are technologies that would provide additional GHG reduction benefits in the 5-cycle test by actively reducing the vehicle’s aerodynamic drag forces. These are referred to as active aerodynamic technologies, which include but are not limited to Active Grill Shutters and Active Susp ension Lowering. Like the electrical load reduction technologies, the vehicle simulation tool can be used to more accurately estimate the additional GHG reductions (therefore the credits) provided by these active aerodynamic technologies over the 5-cycle drive test. EPA seeks comment on using the simulation tool in order to quantify these credits. In order to do this properly, manufacturers would be expected to submit two sets of coast-down coefficients (with and without the active aerodynamic technologies). Or, they could submit two sets of aerodynamic drag coefficient (with and without the active aerodynamic technologies) as a function of vehicle speed.

There are other technologies that would resu lt in additional GHG reduction benefits that cannot be fully captured on the combined FTP/High way cycle test. These technologies typically reduce engine loads by utilizing advanced engine controls, and they range from enabling the vehicle to turn off the engine at idle, to reducing cabin temperature and thus A/C compressor loading when the vehicle is restarted. Exampl es include Engine Start-Stop, Electric Heater Circulation Pump, Active Engine/Transmission Warm-Up, and Solar Control. For these types of technologies, the overall GHG re duction largely depends on the control and calibration strategies of individual manufacturers and vehicle types. Also, the current vehicle simulation tool does not have the capability to properly simulate the vehicle behaviors that depend on thermal conditions of the vehicle and its surroundings, such as Active Engine/Transmission Warm-Up and Solar Control. Therefore, the vehicle simulation may not provide full benefits of the technologies on the GHG reductions. For this reason, the agency is not proposing to use the simulation tool to generate the GHG credits for these technologies at this time, though future versions of the model may be more capable of quantifying the efficacy of these off-cycle technologies as well.

D. Technical Assessment of the Proposed CO 2 Standards

This proposed rule is based on the need to obtain significant GHG emissions reductions from the transportation sector, and the recognition that there are cost-effective technologies available in this timeframe to achieve such reductions for MY 2017-2025 light duty vehicles. As in many prior mobile source rulemakings, the decisi on on what standard to set is largely based on the effectiveness of the emissions control technology, the cost and other impacts of implementing the technology, and the lead time needed for manufacturers to employ the control technology. The standards derived from assessing these factors are also evaluated in terms of the need for reductions of greenhouse gases, the degree of reductions achieved by the standards, and the impacts of the standards in terms of costs, quantified benefits, and other impacts of the standards. The availability of technology to achieve reductions and the cost and other aspects of this technology are therefore a central focus of this rulemaking.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 293 of 768 EPA is taking the same basic approach in this rulemaking as that taken in the MYs 2012- 2016 rulemaking. EPA is evaluating emissions control technologies which reduce CO 2 and other greenhouse gases. CO 2 emissions from automobiles are largely the product of fuel combustion. Vehicles combust fuel to perform two basic functi ons: 1) to transport the vehicle, its passengers and its contents (and any towed loads), and 2) to operate various accessories during the operation of the vehicle such as the air conditioner. Technology can reduce CO 2 emissions by either making more efficient use of the energy that is produced through combustion of the fuel or reducing the energy needed to perform either of these functions.

This focus on efficiency calls for looking at the vehicle as an entire system, and as in the MYs 2012-2016 rule, the proposed standards reflect this basic paradigm. In addition to fuel delivery, combustion, and aftertreatment technolog y, any aspect of the vehicle that affects the need to produce energy must also be considered. For example, the efficiency of the transmission system, which takes the energy produced by the engine and transmits it to the wheels, and the resistance of the tires to rolling both have major impacts on the amount of fuel that is combusted while operating the vehicle. The braking system, the aerodynamics of the vehicle, and the efficiency of accessories, such as the air conditioner, all affect how much fuel is combusted as
well.

In evaluating vehicle efficiency, we have excluded fundamental changes in vehicles’ utility. 297 For example, we did not evaluate converting minivans and SUVs to station wagons, converting vehicles with four wheel drive to two wheel drive, or reducing headroom in order to lower the roofline and reduce aerodynamic drag. We have limited our assessment of technical feasibility and resultant vehicle cost to technolog ies which maintain vehicle utility as much as possible (and, in our assessment of the costs of the rule, included the costs to manufacturers of preserving vehicle utility). Manufacturers may d ecide to alter the utility of the vehicles which they sell, but this would not be a necessary consequence of the rule but rather a matter of
automaker choice.

This need to focus on the efficient use of energy by the vehicle as a system leads to a broad focus on a wide variety of technologies that affect vehicle design. As discussed below, there are many technologies that are currently available which can reduce vehicle energy consumption. Several of these are “game-changing” technologies and are already being commercially utilized to a limited degree in th e current light-duty fleet. Examples include hybrid technologies that use high efficiency ba tteries and electric motors as the power source in
combination with or instead of internal combustion engines, plug- in hybrid electric vehicles, and battery-electric vehicles. While already commer cialized, these technologies continue to be developed and offer the potential for even more significant efficiency improvements. There are

297 EPA recognizes that electric vehicles, a technology considered in this analysis, have unique attributes and discusses these considerations in Section III.H.1.b. There is also a fuller discu ssion of the utility of Atkinson engine hybrid vehicles in EPA DRIA Chapter 1.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 294 of 768 also other advanced technologies under development and not yet on production vehicles, such as high BMEP engines with cooled EGR, which offer the potential of improved energy generation taking the gasoline combustion process nearly to its thermodynamic limit. In addition, the available technologies are not limited to powertr ain improvements but also include a number of technologies that are expected to continually improve incrementally, such as engine friction reduction, rolling resistance reduction, mass reduction, electrical system efficiencies, and aerodynamic improvements.

The large number of possible technologies to consider and the breadth of vehicle systems that are affected mean that consideration of the manufacturer’s design, product development and manufacturing process plays a major role in developing the final standards. Vehicle manufacturers typically develop many different models by basing them on a limited number of vehicle platforms. The platform typically consists of a common set of vehicle architecture and structural components. 298 This allows for efficient use of design and manufacturing resources. Given the very large investment put into designing and producing each vehicle model, manufacturers typically plan on a major redesign for the models approximately every 5 years. 299
At the redesign stage, the manufacturer will upgrad e or add all of the technology and make most other changes supporting the manufacturer’s plans for the next several years, including plans to comply with emissions, fuel economy, and safety regulations. 300 This redesign often involves significant engineering, development, manufacturing, and marketing resources to create a new product with multiple new features. In order to leverage this signifi cant upfront investment, manufacturers plan vehicle redesigns with several model years’ of production in mind. Vehicle models are not completely static between redesigns as limited changes are often incorporated for each model year. This interim process is called a refresh of the vehicle and generally does not allow for major technology changes although more minor ones can be done (e.g., small aerodynamic improvements, valve timing improvements, etc). More major technology upgrades that affect multiple systems of the vehicle thus occur at the vehicle redesign stage and not in the time period between redesigns.

This proposal affects nine years of vehicle production, model years 2017-2025. Given the now-typical five year redesign cycle, many vehicles will be redesigned three times between MY 2012 and MY 2025 and are expected to be redesigned twice during the 2017-2025 timeframe. Due to the relatively long lead time before 2017, there are fewer lead time concerns with regard to product redesign in this proposal than with the MYs 2012-2016 rule (or the MY 2014-2018 rule for heavy duty vehi cles and engines). However, there are still some technologies that require significant lead time, and are not project ed to be heavily utilized in the first years of this proposal. An example is the advanced high BMEP, cooled EGR engines. As these engines

298 Examples of shared vehicle platforms include the Ford Taurus and Ford Explorer or the Chrysler Sebring and Dodge Journey.

299 See TSD Chapter 3

300 TSD 3 discusses redesign schedules in greater detail.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 295 of 768 are not yet in vehicles today, a research and development period is required, even if there are a number of demonstration projects complete (as discussed in Chapter 3 of the joint TSD).

In developing the proposed MY 2021 and 2025 car and truck curves (discussed in Section III.B), EPA used the OMEGA model to evaluate technologies that manufacturers could use tocomply with the targets which those curves would establish. These curves correspond to salesweighted fleetwide CO 2 average targets of 200 g/mile in MY 2021 and 163 g/mile in MY 2025.As discussed later in this section, we believe that this level of technology application to the lightduty vehicle fleet can be achieved in this time frame, the standards will produce significant reductions in GHG emissions, and the costs for bo th the industry and the costs to the consumer are reasonable and that consumer savings due to improved fuel economy will more than pay for
the increased vehicle cost over the life of th e vehicles. EPA also estimated costs for the intermediate model years 2017 through 2020 based on the OMEGA analyses in MYs 2016 and 2021 as well as the intermediate model years 2022-2024 based on the OMEGA analyses in MYs
2021 and 2025.

EPA’s technical assessment of the proposed MY2017-2025 standards is described
below. EPA has also evaluated a set of alternat ive standards for these model years two of which are more stringent and two of which are less stringent than the standards proposed. The
technical assessment of these alternative standards in relation to the ones proposed is discussed at
the end of this section.

Evaluating the appropriateness of these standards includes a core focus on identifying available technologies and assessing their effectiven ess, cost, and impact on relevant aspects of vehicle performance and utility. The wide number of technologies which are available and likely to be used in combination requires a sophisti cated assessment of their combined cost and effectiveness. An important factor is also the degree that these technologies are already being used in the current vehicle fleet and thus, unavailable for use to improve energy efficiency beyond current levels. Finally, the challenge for manufacturers to design the technology into their products within the constraints of the redesign cycles, and the appropriate lead time needed to employ the technology over the product line of the industry must be considered.

Applying these technologies efficiently to the wide range of vehicles produced by various manufacturers is a challenging task involving do zens of technologies and hundreds of vehicle platforms. In order to assist in this task, EP A is again using a computerized program called the Optimization Model for reducing Emissions of Gr eenhouse gases from Automobiles (OMEGA). Broadly, OMEGA starts with a description of the future vehicle fleet (i.e. the ‘reference fleet’; see section II.B above), including manufacturer, sales, base CO 2 emissions, footprint and the extent to which emission control technologies are already employed. For the purpose of this analysis, EPA uses OMEGA to analyze over 2 00 vehicle platforms comprising approximately 1300 vehicle models in order o capture the important differences in vehicle and engine design and utility of future vehicle sales of roughl y 16-18 million units an nually in the 2017-2025Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 296 of 768 timeframe. The model is then provided with a list of technologies which are applicable to various types of vehicles, along with the technologies’ cost and effectiveness and the percentage of vehicle sales which can receive each technology during the redesign cycle of interest. The model combines this information with economic pa rameters, such as fuel prices and a discount rate, to project how various manufacturers would apply the available technology in order to meet increasing levels of emission control. The resu lt is a description of which technologies are added to each vehicle platform, along with the resulting cost. While OMEGA can apply technologies
which reduce CO 2 efficiency related emissions and refrige rant leakage emissions associated with air conditioner use, this task is currently handled outside of the OMEGA model. A/C improvements are relatively cost-effective, and would always be added to vehicles by the model, thus they are simply added into the results at the projected penetration levels. The model can also be set to account for the various proposed compliance flexibilities (and to accommodate compliance flexibilities in general.

The remainder of this section describes the techni cal feasibility analysis in greater detail. Section III.D.1 describes the development of our reference and control case projections of the
MY 2017-2025 fleet. Section III.D.2 describes our estimates of the effectiveness and cost of the control technologies available for application in the 2017-2025 timeframe. Section III.D.3describes how these technologies are combined into packages likely to be applied at the same time by a manufacturer. In this section, the overall effectiveness of the technology packages vis-à-vis their effectiveness when adopted individually is described. Section III.D.4 describes EPA’s OMEGA model and its approach to estimating how manufacturers will add technology to their vehicles in order to comply with potential CO 2 emission standards. Section III.D.5 presents the results of the OMEGA modeling, namely the level of technology added to manufacturers’ vehicles and the cost of adding th at technology. Section III.D.6 discusses the appropriateness (or lack of appropriateness) of the alternative standards in relation to those proposed. Further technical detail on all of these issues can be found in EPA and NHTSA’s Draft Joint Technical Support Document as well as EPA’s Regulatory Impact Analysis.

1. How did EPA develop a reference and control fleet for evaluating standards?

In order to calculate the impacts of this proposal, it is necessary to project the GHG emissions characteristics of the future vehicle fleet absent the proposed regulation. EPA and NHTSA develop this projection using a three step process. (1) Develop a set of detailed vehicle characteristics and sales for a specific model year (in this case, 2008). 301 This is called the baseline fleet. (2) Adjust the sales of this baseline fleet using projections made by the Energy Information Administration (EIA) and CSM to account for projected sales volumes in future

301 As discussed in TSD Chapter 1, and in Section II.B.2, the agencies will consider using Model Year 2010 for the final rule, based on availability and an analysis of the data representativeness.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 297 of 768 MYs absent future regulation. 302 (3)Apply fuel saving and emission control technology to these vehicles to the extent necessary for manufacturers to comply with the existing 2016 standards and the proposed standards.

Thus, the analyzed fleet differs from the MY 2008 baseline fleet in both the level of technology utilized and in terms of the sales of any particular vehicle. A similar method is used to analyze both reference and control cases, with the major distinction being the stringency of the
standards.

EPA and NHTSA perform steps one and two above in an identical manner. The development of the characteristics of the baseline 2008 fleet and the sales adjustment to match AEO and CSM forecasts is described in Section II.B above and in greater detail in Chapter 1 of the joint TSD. The two agencies perform step three in a conceptually identical manner, but each agency utilizes its own vehicle technology and emis sion model to project the technology needed to comply with the reference and proposed standards. Further, each agency evaluates its own proposed and MY 2016 standards; neither NHTSA nor EPA evaluated the other agency’s standard in this proposal. 303

The use of MY 2008 vehicles in our fleet projections includes vehicle models which already have or will be discontinued by the time this rule takes effect and will be replaced by more advanced vehicle models. However, we belie ve that the use of MY 2008 vehicle designs is still the most appropriate approach available for this proposal. 304 First, as discussed in Section II.B above, the designs of these new vehicles at the level of detail required for emission and cost modeling are not publically available, and in many cases, do not yet exist. Even the confidential descriptions of these vehicle designs are usually no t of sufficient detail to facilitate the level of technology and emission modeling performed by both agencies. Second, steps two and three of the process used to create the reference case fleet adjust both the sales and technology of the 2008 vehicles. Thus, our reference fleet reflects the extent that completely new vehicles are expected to shift the light vehicle market in te rms of both segment and manufacturer. Also, by adding technology to facilitate compliance with the MY 2016 standards, we account for the vast majority of ways in which these new vehicles will differ from their older counterparts.

a. Reference Fleet Scenario Modeled

EPA projects that in the absence of the proposed GHG and CAFE standards, the reference case fleet in MY 2017-2025 would have fleetwide GHG emissions performance no better than that projected to be necessary to meet the MY 2016 standards. While it is not possible to know with certainty the future fleet wide GHG emissions performance in the absence

302 See generally Chapter 1 of the Joint TSD for details on de velopment of the baseline fleet, and Section III.H.1 for a discussion of the potential sales impacts of this proposal.

303 While the MY 2012-2016 standards are largely similar, so me important differences remain. See 75 FR at 25342

304 See section II.B.2 concerning the selection of MY 2008 as the appropriate baseline.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 298 of 768 of more stringent standards, EPA believes that th is approach is the most reasonable projection for developing the reference case fleet for MY 2017-2025. One important element supporting the proposed approach is that AEO2011 projects relatively stable gasoline prices over the next 15 years, dropping to $3.25 in 2017 (less than the average gasoline price in 2011 to date), and then rising slowly to $3.54 per gallon in 2025 (similar to the average gasoline price in 2011). Thus the reference fleet for MY2017-2025 should correspond to a time period where there is a stable, unchanging GHG standard, and stable gasoline prices.

EPA looked back at similar periods in history when we had stable fuel economy standards and stable gasoline prices. The historical evidence is compelling in this regard. EPA maintains, and publishes every year, the seminal reference on new light-duty vehicle CO 2 emissions and fuel economy. 305 This report contains exhaustive data from MYs 1975-2010. There was an extended 18-year period from 1986 through 2003, fully one-half of the entire 36- year database, where CAFE standards were essentially unchanged, 306 and gasoline prices were relatively stable and remained below $1.50 per gallon for almost the entire period. The 1975- 1985 and 2004-2010 timeframes are not informative in this regard due to either rising gasoline prices, rising CAFE standards, or both. Thus, the 1986-2003 period is an excellent analogue in many ways to the period out to MY 2025 during which AEO projects stable gasoline prices. EPA staff have analyzed the fuel economy trends data from the 1986-2003 timeframe and there are three clear conclusions: 1) there was a small, industry-wide, average over-compliance with CAFE on the order of 1-2 mpg or 3-4%, 2) almost all of this industry-wide over-compliance was from 3 companies (Toyota, Honda, and Nissan) that produced smaller and lighter vehiclesrelative to the industry average and which therefore naturally and essentially necessarily overcomplied with the universal CAFE standards (standards that did not vary by footprint), and 3) full line car and truck manufacturers, such as General Motors, Ford, and Chrysler, which produced larger and heavier vehicles relative to the industry average and which were constrained by the universal CAFE standards, rarely over-complied during the entire 18-year period. 307

Since the MY 2012-2016 standards are footprint-based, every major manufacturer is expected to be constrained by the new standa rds in 2016 and manufacturers of small vehicles will not naturally (or consistently) over-comply as they had with a flat standard. 308 Thus, the historical evidence and the footprint-base d design of the 2016 GHG emissions and CAFE standards strongly support the use of a refere nce case fleet where there are no further fuel economy improvements beyond those required by th e MY 2016 standards. There are additional
factors here that reinforce the historical evidence . While it is possible that one or two companies may over-comply, any voluntary over-compliance by one company would generate credits that

305 Light-Duty Automotive Technology, Carbon Dioxide Em issions, and Fuel Economy Trends: 1975 through 2010, November 2010, available at www.epa.gov/otaq/fetrends.htm.

306 There are no EPA LD GHG emissions regulations prior to MY 2012.

307 See Regulatory Impact Analysis, Chapter 3.

308 With the notable exception of manufacturers who only ma rket electric vehicles or other limited product lines.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 299 of 768 other companies may buy and use to substitu te for their more expensive compliance technologies; this ability to buy and sell credits would tend to eliminate over-compliance for the
overall fleet. 309 A NHTSA analysis of EIA/AEO projections of future fuel economy levels also supports a flat, 2016-based reference case fleet. From a consumer market driven perspective, while there is considerable evidence that many consumers now care more about fuel economy than in past decades, the 2016 compliance level is projected to be several mpg higher than that being demanded in the market today. 310 On the other hand, some manufacturers have already announced plans to introduce technology well beyond that required by the 2016 MY GHG
standards. 311 However, it is difficult, if not impos sible, to separate future fuel economy improvements made for marketing purposes from those designed to efficiently plan for compliance with anticipated future CAFE or CO 2 emission standards, i.e., some manufacturers may have made public statements about higher mpg levels in the future in part because of the expectation of higher future standards.

All estimates of actual GHG emissions and fuel economy performance in 2016 or any other future year are projections, and it is plau sible that actual GHG emissions and fuel economy performance in 2016 and later years, absent more stringent standards, could be lower than projected if there are shifts from car market share to truck market share, or to higher footprint levels. This exact situation occurred over the period from 1986-2003, when average fuel economy performance levels decreased over time even as car CAFE standards were stable and truck CAFE levels rose slightly. 312 There is always a possibility that future performance could be higher than MY2016 levels. While EPA has not performed a quantified sensitivity assessment for this proposal, a reasonable range for a sensitivity analysis would evaluate over or under compliance on the order of a few percent which EPA projects would not result in a meaningful impact.

Based on this assessment, the EPA reference case fleet is estimated through the target curves defined in the MY 2016 rulemaking applied to the projected 2017-2025 fleet. 313 As in the previous rulemaking, EPA assumes that manufacturers make use of 10.2 grams of air conditioning credits on cars and 11.5 on light trucks, or an average of approximately 11 grams on the U.S. fleet and the technology for doing so is included in the reference case (Section III.C).

309 Oates, Wallace E., Paul R. Portne y, and Albert M. McGartland. “The Net Benefits of Incentive-Based Regulation: A Case Study of Environmental Standard Setting." American Economic Review 79(5) (December 1989): 1233-1242.

310 The average, fleetwide “laboratory” or “unadjusted” fuel economy value for MY 2010 is 28.3 mpg (see LightDuty Automotive Technology, Carbon Dioxide Emissi ons, and Fuel Economy Trends: 1975 Through 2010, November 2010, available at www.epa.gov/otaq/fetrends.htm ), 6-7 mpg less than the 34-35 mpg levels necessary to meet the EPA GHG and NHTSA CAFE levels in MY 2016.

311 For example, Hyundai has made a public commitment to achieve 50 mpg by 2025.

312 See Regulatory Impact Analysis, Chapter 3.

313 75 FR at 25686Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 300 of 768 b. Control Scenarios Modeled

For the control scenario, EPA modeled the proposed standard curves discussed in Section III.B, as well as the alternative scenarios discu ssed in III.D.6. Other flexibilities are accounted for in the analysis. The air conditioning credits modeled are discussed in III.D.2. Air conditioning credits (both leakage and efficiency) are included in the cost and technology analysis described below. The compliance value of 0 g/mi for PHEVs and EVs are also included. However, off-cycle credits, PH/EV multipliers through MY 2021, pickup truck credits, flexible fuel, and carry forward/back credits are not included explicitly in the cost analysis. These flexibilities will offer the manufacturers more compliance options. Moreover, the overall cost analysis includes small volume manufacturers in the fleet, the former of which would be excluded from the rule, and the later would have company specific standards assuming this part of the proposal is finalized (see section III.XX). As we expect all of these flexibilities together to only have a small impact on the fleet compliance costs on average, we will re-evaluate including them in the final rule analysis

c. Vehicle Groupings Used

In order to create future technology projections and enable compliance with the modeled standards, EPA aggregates vehicle sales by a co mbination of manufacturer, vehicle platform, and engine design for the OMEGA model. As discussed above, manufacturers implement major design changes at vehicle redesign and tend to implement these changes across a vehicle platform (such as large SUV, mid-size SUV, large automobile, etc) at a given manufacturing plant. Because the cost of modifying the engine depends on the valve train design (such as SOHC, DOHC, etc.), the number of cylinders and in some cases head design, the vehicle sales are broken down beyond the platform level to re flect relevant engine differences. The vehicle groupings are shown in Table III-18.

Table III-18 Vehicle Groupings a

Vehicle Description Vehicle Type Vehicle Description Vehicle Type Large SUV (Car) V8+ OHV 13 Large Pickup V8+ DOHC 19 Large SUV (Car) V6 4v 16 Large Pickup V8+ SOHC 3v 14 Large SUV (Car) V6 OHV 12 Large Pickup V8+ OHV 13 Large SUV (Car) V6 2v SOHC 9 Large Pickup V8+ SOHC 10 Large SUV (Car) I4 and I5 7 Large Pickup V6 DOHC 18 Large SUV V8+ DOHC 17 Large Pickup V6 OHV 12 Large SUV V8+ SOHC 3v 14 Large Pickup V6 SOHC 2v 11 Large SUV V8+ OHV 13 Large Pickup I4 S/DOHC 7 Large SUV V8+ SOHC 10 Small Pickup V6 OHV 12 Large SUV V6 S/DOHC 4v 16 Small Pickup V6 2v SOHC 8 Large SUV V6 OHV 12 Small Pickup I4 7 Large SUV V6 SOHC 2v 9 Cargo Van V8+ OHV 13 Large SUV I4/ 7 Cargo Van V8+ SOHC 10 Midsize SUV (Car) V6 2v SOHC 8 Cargo Van V6 OHV 12Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

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Midsize SUV (Car) V6 S/DOHC 4v 5 Minivan V6 S/DOHC 16 Midsize SUV (Car) I4 7 Minivan V6 OHV 12
Midsize SUV V6 OHV 12 Minivan I4 7
Midsize SUV V6 2v SOHC 8
Midsize SUV V6 S/DOHC 4v 5
Midsize SUV I4 S/DOHC 7 Small SUV (Car) V6 OHV 12 Small SUV (Car) V6 S/DOHC 4 Small SUV (Car) I4 3
Small SUV V6 OHV 12

Vehicle Description Vehicle Type Vehicle Description Vehicle Type Large Auto V8+ OHV 15 Co mpact Auto V7+ S/DOHC 6 Large Auto V8+ SOHC 10 Compact Auto V6 OHV 12 Large Auto V8+ DOHC, 4v SOHC 6 Co mpact Auto V6 S/DOHC 4v 4 Large Auto V6 OHV 12 Compact Auto I5 7 Large Auto V6 SOHC 2/3v 5 Compact Auto I4 2 Midsize Auto V8+ OHV 15 Subcompact Auto V8+ OHV 15 Midsize Auto V8+ SOHC 10 Subcompact Auto V8+ S/DOHC 6 Midsize Auto V7+ DOHC, 4v SOHC 6 Subcompact Auto V6 2v SOHC 8 Midsize Auto V6 OHV 12 Subcompact Auto I5/V6 S/DOHC 4v 4 Midsize Auto V6 2v SOHC 8 Subcompact Auto I4 1
Midsize Auto V6 S/DOHC 4v 5
Midsize Auto I4 3

a I4 = 4 cylinder engine, I5 = 5 cylinder engine, V6, V7, and V8 = 6, 7, and 8 cylinder engines, respectively, DOHC = Double overhead cam, SOHC = Single overhead cam, OHV = Overhead valve, v = number of valves per cylinder, “/” = and, “+” = or larger.

2. What are the Effectiveness and Costs of CO2-reducing Technologies?

EPA and NHTSA worked together to develop information on the effectiveness and cost
of most CO 2 -reducing technologies, and fuel economy-improving technologies. This joint work is reflected in Chapter 3 of the draft Joint TSD and in Section II.D of this preamble. The work on technology cost and effectiveness also includes maximum penetration rates, or “caps” for the OMEGA model. These caps are an important input to OMEGA that capture the agencies’ analysis concerning the rate at which technologies can be added to the fleet (see Chapter 3.5 of the draft joint TSD for more detail). This preamb le section, rather than repeating those details, focuses upon EPA-only technology assumptions, sp ecifically, those relating to air conditioning refrigerant.

EPA expects all manufacturers will choose to use AC improvement credit opportunities as a strategy for meeting compliance with the CO 2 standards, and set the stringency of the standard accordingly (see section II.F above). EPA estimates that the level of the credits earned will increase from 2017 (13 grams/mile) to 2021 ( 21 grams/mile) as more vehicles in the fleetSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 302 of 768 convert to use of the new alternative refrigerant. 314 By 2021, we project that 100% of the MY 2021 fleet will be using alternative refrigerants, and that credits will remain constant on a car and
truck basis until 2025. Note from the table below that costs then decrease from 2021 to 2025 due to manufacturer learning as discussed in Section II of this preamble and in Chapter 3 of the draft joint TSD. A more in-depth discussi on of feasibility and availability of low GWP alternative refrigerants, can be found in Section III.C of the Preamble.

Table III-19 Total CO 2 Reduction Potential and Costs for A/C Technologies Related to Alternative Refrigerants (Costs in 2009 dollars)

Technology 2017 2021 2025

Car Leakage reduction (continued from the 2012-2016 rule) $3 $3 $3
Low GWP refrigerant $17 $57 $49 Low GWP refrigerant hardware $4 $16 $15 Total $23 $76 $67

Truck Leakage reduction (continued from the 2012-2016 rule) $1 $3 $3
Low GWP refrigerant $0 $57 $49 Low GWP refrigerant hardware $0 $16 $15 Total $1 $76 $67 Fleet Total $24 $76 $67
Note that the costs shown in Table III-19 do not include maintenance savings thatwould be expected from the new AC systems. Further, EPA does not include ACrelated maintenance savings in our cost and be nefit analysis presented in Section III.H. EPA discusses the likely maintenance saving s in Chapter 5 of the draft joint TSD, though these savings are not included in our final cost estimates for the final rule. EPA requests comment on and information regarding maintenance costs (and savings) due to new technologies included in this proposal.

Additionally, by MY 2019, EPA estimates that 100% of the A/C efficiency improvements will by fully phased-in. However 85% of these costs are al ready in the reference fleet, as this is the level of penetration assume d in the 2012-2016 final rule. The penetration of A/C costs for this proposal can be found in Chapter 5 of the draft joint TSD.

3. How were Technologies combined into “Packages” and What is the Cost and Effectiveness of Packages?

Individual technologies can be used by manufacturers to achieve incremental CO 2 reductions. However, as discussed extensively in the MYs 2012-2016 Rule, EPA believes that manufacturers are more likely to bundle technologies into “packages” to capture synergistic aspects and reflect progressively larger CO 2 reductions with additions or changes to any given

314 See table in III.BSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 303 of 768 package. In this manner, and consistent with the concept of a redesign cycle, manufacturers can optimize their available resources, including e ngineering, development, manufacturing and marketing activities to create a product with multiple new features. Therefore, the approach taken here is to group technologies into pack ages of increasing cost and effectiveness.

EPA built unique technology p ackages for each of 19 “vehicle types,” which, as in the MYs 2012-2016 rule and the Interim Joint TAR, pr ovides sufficient resolution to represent the technology of the entire fleet. This was the result of analyzing the existing light duty fleet with respect to vehicle size and powertrain configurat ions. All vehicles, including cars and trucks, were first distributed based on their relative size, starting from compact cars and working upward to large trucks. Next, each vehicle was evaluated for powertrain, specifically the engine size (I4, V6, and V8) then by valvetrain configuration (DOHC, SOHC, OHV), and finally by the number of valves per cylinder. For purposes of calculating some technology costs and effectiveness values, each of these 19 vehicle types is mapped into one of seven classes of vehicles: Subcompact, Small car, Large car, Minivan, Minivan with towing, Small truck, and Large
truck. 315 We believe that these seven vehicle classes, along with engine cylinder count, provide adequate representation for the cost basis associated with most technology application. Note also that these 19 vehicle types span the range of vehicle footprints—smaller footprints for smaller vehicles and larger footprints for larger vehi cles—which served as the basis for the 2012-2016 GHG standards and the standards in this proposal. A detailed table showing the 19 vehicle types, their baseline engines and their descriptions is contained in xx and in Chapter 1 of EPA’s draft

RIA.

Within each of the 19 vehicle types, multip le technology packages were created in increasing technology content resulting in increasin g effectiveness. As stated earlier, with few exceptions, each package is meant to provide equivalent driver-perceived performance to the baseline package. Note that we refer throughout this discussion of package building to a “baseline” vehicle or a “baseline” package. This should not be confused with the baseline fleet, which is the fleet of roughly 16 million 2008MY i ndividual vehicles comprised of over 1,100 vehicle models. In this discussion, when we refer to “baseline” vehicle we refer to the “baseline” configuration of the given vehicle type. So, we have 19 baseline vehicles in the context of building packages. Each of those 19 baseline vehicles is equipped with a port fuel injected engine and a 4 speed automatic transmission. The valvetrain configuration and the number of cylinders changes for each vehicle type in an effort to encompass the diversity in the 2008 baseline fleet as discussed above. In short, wh ile the baseline vehicle that defines the vehicle type is relevant when discussing the package building process, the baseline and reference case
fleets of real vehicles are not relevant to the di scussion here. We describe this in more detail in Chapter 1 of EPA’s draft RIA.

315 Note that, for the current assessment and representi ng an update since the 2010 TAR, EPA has created a new vehicle class called “minivan with towing” which allows for greater differentiation of costs for this popular class of vehicles (such as the Ford Edge, Honda Odyssey, Jeep Grand Cherokee).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 304 of 768 To develop a set of packages as OMEGA inputs, EPA builds packages consisting of every legitimate permutation of technology available, subject to constraints. 316 This “preliminary-set” of packages consists of roughly 2,000 possible packages of technologies for each of 19 vehicle types, or nearly 40,000 packages in all. The cost of each package is determined by adding the cost of each individual technology contained in the package for the given year of interest. The effectiveness of each package is determined in a more deliberate manner; one cannot simply add the effectiveness of individual technologies to arrive at a package-level effectiveness because of the synergistic effects of technologies when grouped with other technologies that seek to improve the same or similar efficiency loss mechanism. As an example, the benefits of the engine and tran smission technologies can usually be combined multiplicatively, 317 but in some cases, the benefit of th e transmission-related technologies overlaps with the engine technologies. This occurs because the transmission technologies shift operation of the engine to more efficient locations on the engine map by incorporating more ratio selections and a wider ratio span into the transmissions. Some of the engine technologies have the same goal, such as cylinder deactivation, advanced valvetrains, and turbocharging. In order to account for this overlap and avoid over-esti mating emissions reduction effectiveness, EPA uses an engineering approach known as the lumped-parameter technique. The results from this approach were then applied directly to the vehicle packages. The lumped-parameter technique is well documented in the literature, and the specifi c approach developed by EPA is detailed in Chapter 3 (Section 3.3.2) of the draft joint TSD as well as Chapter 1 of EPA’s draft RIA.

Table III-20 presents the cost and effectiveness values from a 2025MY master-set of packages used in the OMEGA model for EPA’s vehicle type 5, a large car class equipped with a V6 engine. Similar packages were generated for each of the 19 vehicle types and the costs and effectiveness estimates for each of those packages are discussed in detail in Chapter 1 of EPA’s
draft RIA.

As detailed in Chapter 1 of EPA’s draft RIA, this preliminary-set of packages is then ranked according to technology application ranking factors (TARFs) to eliminate packages that are not as cost-effective as others. 318 The result of this TARF ranking process is a “ranked-set” of packages for use as OMEGA inputs. EPA prepares a ranked set of packages for any MY in which OMEGA is run, 319 the initial packages represent what we believe a manufacturer will

316 Example constraints include the requirement for stoichio metric gasoline direct injection on every turbocharged and downsized engine and/or any 27 bar BMEP turbocharged and downsized engine must also include cooled EGR. Some constraints are the result of engineering judgment wh ile others are the result of effectiveness value estimates which are tied to specific combinations of technologies.

317 For example, if an engine technology reduces CO 2 emissions by five percent and a transmission technology reduces CO 2 emissions by four percent, the benefit of applying both technologies is 8.8 percent (100% - (100% – 4%) * (100% - 5%)).

318 The Technology Application Ranking Factor (TARF) is discussed further in III.D.5

319 Note that a ranked-set of package is generated for any year for which OMEGA is run due to the changes in costs and maximum penetration rates. EPA’s draft RIA chap ter 3 contains more details on the OMEGA modeling and draft Joint TSD Chapter 3 has more detail on both costs ch anges over time and the maximum penetration limits of certain technologies.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 305 of 768 most likely implement on all vehicles, includi ng lower rolling resistance tires, low friction lubricants, engine friction reduction, aggressive shift logic, early torque converter lock-up, improved electrical accessories, and low drag brakes (to the extent not reflected in the baseline vehicle). 320 Subsequent packages include gasoline direct injection, turbocharging and downsizing, and more advanced transmission tec hnologies such as six and eight speed dualclutch transmissions and 6 and 8 speed automati c transmissions. The most technologically advanced packages within a vehicle type incl ude the hybrids, plug-in hybrids and electric vehicles. Note that plug-in hybrid and electri c vehicle packages are only modeled for the nontowing vehicle types, in order to better maintain utility. We request comment on this decision and whether or not we should perhaps consider plug-in hybrids for towing vehicle types.

Table III-20 CO 2 Reducing Technology Vehicle Packages for a Large Car

Effectiveness and Costs in the 2025MY (Costs in 2009 dollars)

Pkg# Engine & Vehicle technologies Trans Electrical Mass Rdxn Cost Effectiveness
500 3.3L 4V DOHC V6 4sp AT 12V base $0 0.0%

501 4V DOHC V6 +EFR2 +LDB +ASL2 +IACC +EPS +Aero1 +LRRT1 +HEG 6sp DCTwet 12V 5% $646 27.3%

502 4V DOHC V6 +EFR2 +LDB +ASL2 +IACC +EPS +Aero1 +LRRT1 +HEG 8sp DCTwet 12V 5% $760 30.2%

503 4V DOHC I4 +EFR2 +LDB +ASL2 +IACC +EPS +Aero1 +LRRT1 +HEG +DCP +GDI +TDS18 6sp DCTwet 12V 5% $1,058 37.4%

504 4V DOHC I4 +EFR2 +LDB +ASL2 +IACC +EPS +Aero1 +LRRT1 +HEG +DCP +GDI +TDS18 8sp DCTwet 12V 5% $1,172 39.4%

505 4V DOHC I4 +EFR2 +LDB +ASL2 +IACC2 +EPS +Aero2 +LRRT2 +HEG +DCP +GDI +TDS18 8sp DCTwet 12V 5% $1,386 42.6%

506 4V DOHC I4 +EFR2 +LDB +ASL2 +IACC2 +EPS +Aero2 +LRRT2 +HEG +DCP +GDI +TDS18 8sp DCTwet 12V 10% $1,507 44.2%

509 4V DOHC I4 +EFR2 +LDB +ASL2 +IACC2 +EPS +Aero2 +LRRT2 +HEG +DCP +GDI +TDS18 8sp DCTwet 12V 15% $1,741 45.8%

507 4V DOHC I4 +EFR2 +LDB +ASL2 +IACC2 +EPS +Aero2 +LRRT2 +HEG +DCP +GDI +TDS24 8sp DCTwet 12V 10% $1,719 46.1%

511 4V DOHC I4 +EFR2 +LDB +ASL2 +IACC2 +EPS +Aero2 +LRRT2 +HEG +DCP +GDI +TDS18 8sp DCTwet 12V 20% $2,048 47.4%

513 4V DOHC I4 +EFR2 +LDB +ASL2 +IACC2 +EPS +Aero2 +LRRT2 +HEG +DCP +GDI +SAX +TDS18 8sp DCTwet 12V 20% $2,128 47.7%

508 4V DOHC I4 +EFR2 +LDB +ASL2 +IACC2 +EPS +Aero2 +LRRT2 +HEG +DCP +GDI +TDS24 +EGR 8sp DCTwet 12V 10% $1,966 48.0%

515 4V DOHC I4 +EFR2 +LDB +ASL2 +IACC2 +EPS +Aero2 +LRRT2 +HEG +DCP +DVVL +GDI +SAX +TDS18 8sp DCTwet 12V 20% $2,259 48.2%

516 4V DOHC I4 +EFR2 +LDB +ASL2 +IACC2 +EPS +Aero2 +LRRT2 +HEG +DCP +DVVL +GDI +SS +SAX +TDS18 8sp DCTwet 12V S-S 20% $2,602 48.7%

519 4V DOHC I4 +EFR2 +LDB +ASL2 +IACC2 +EPS +Aero2 +LRRT2 +HEG +DCP +DSL-Adv +SAX 8sp DCTwet 12V 20% $4,673 49.4%

510 4V DOHC I4 +EFR2 +LDB +ASL2 +IACC2 +EPS +Aero2 +LRRT2 +HEG +DCP +GDI +TDS24 +EGR 8sp DCTwet 12V 15% $2,200 49.5%

512 4V DOHC I4 +EFR2 +LDB +ASL2 +IACC2 +EPS +Aero2 +LRRT2 +HEG +DCP +GDI +TDS24 +EGR 8sp DCTwet 12V 20% $2,507 51.0%

514 4V DOHC I4 +EFR2 +LDB +ASL2 +IACC2 +EPS +Aero2 +LRRT2 +HEG +DCP +GDI +SAX +TDS24 +EGR 8sp DCTwet 12V 20% $2,588 51.3%

517 4V DOHC I4 +EFR2 +LDB +ASL2 +IACC2 +EPS +Aero2 +LRRT2 +HEG +DCP +GDI +SS +SAX +TDS24 +EGR 8sp DCTwet 12V S-S 20% $2,931 51.8%

320 When making reference to low friction lubricants, the t echnology being referred to is the engine changes and possible durability testing that would be done to accomm odate the low friction lubricants, not the lubricants themselves.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

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518 4V DOHC I4 +EFR2 +LDB +ASL2 +IACC2 +EPS +Aero2 +LRRT2 +HEG +DCP +GDI +SS +SAX +TDS27 +EGR 8sp DCTwet 12V S-S 20% $3,356 52.2%

520 4V DOHC V6 +EFR2 +LDB +ASL2 +IACC2 +EPS +Aero2 +LRRT2 +HEG +DCP +DVVL +GDI +ATKCS +HEV 8sp DCTwet HEV 20% $5,353 59.3%

521 4V DOHC V6 +EFR2 +LDB +ASL2 +IACC2 +EPS +Aero2 +LRRT2 +HEG +DCP +DVVL +GDI +ATKCS +HEV +SAX 8sp DCTwet HEV 20% $5,433 59.6%

522 4V DOHC V6 +EFR2 +LDB +ASL2 +IACC2 +EPS +Aero2 +LRRT2 +HEG +DCP +DVVL +GDI +ATKCS +REEV20 8sp DCTwet EV 20% $12,485 75.2%

523 4V DOHC V6 +EFR2 +LDB +ASL2 +IACC2 +EPS +Aero2 +LRRT2 +HEG +DCP +DVVL +GDI +ATKCS +REEV40 8sp DCTwet EV 20% $15,670 84.7%

524 EV75 mile +IACC2 +Aero2 +LRRT2 +EPS N/A EV 20% $12,908 100% 525 EV100 mile +IACC2 +Aero2 +LRRT2 +EPS N/A EV 20% $14,643 100% 526 EV150 mile +IACC2 +Aero2 +LRRT2 +EPS N/A EV 20% $20,280 100% Aero=aerodynamic treatments;ASL=aggressive shift logic; AT=auto trans; ATKCS=Atkinson-cycle; DCP=dual cam phasing; DCT=dual clutch trans; DSL-Adv=advanced diesel; DOHC=dual overhead cam; EFR=engine friction reduction; EGR=exhaust gas recirculation; EPS=electric pow er steering; EV=electric vehicle; GDI=stoich gasoline direct injection; HEG=high efficiency gearbox; HE V=hybrid EV; IACC=improved accessories; LDB=low drag brakes; LRRT=lower rolling resistance tires; REEV=range extended EV or plug-in HEV; SAX=secondary axle disconnect; S-S=stop-start; TDS18/24/27=turbocharged & downsized 18 bar BMEP/24 bar BMEP/27 bar BMEP. “1” and “2” suffixes to certain technologies indicate the first level versus the second level of the technology as described in Chapter 3 of the draft joint TSD.

4. How does EPA Project how a Manufacturer Would Decide Between Options to Improve CO 2 Performance to Meet a Fleet Average Standard?

As discussed, there are many ways for a manufacturer to reduce CO 2 -emissions from its vehicles. A manufacturer can choose from a myriad of CO 2 reducing technologies and can apply one or more of these technologies to some or all of its vehicles. Thus, for a variety of levels of

CO 2 emission control, there are an almost infin ite number of technology combinations which produce a desired CO 2 reduction. As noted earlier, EPA used the same model used in the MYs 2012-2016 Rule, the OMEGA model, in order to make a reasonable estimate of how manufacturers will add technologies to vehi cles in order to meet a fleet-wide CO 2 emissions level. EPA has described OMEGA’s specific met hodologies and algorithms previously in the model documentation, 321 makes the model publically available on its website, 322 and has recently peer reviewed the model. 323

The OMEGA model utilizes four basic sets of input data. The first is a description of the vehicle fleet. The key pieces of data required for each vehicle are its manufacturer, CO 2 emission level, fuel type, projected sales and footprint. The model also requires that each vehicle be assigned to one of the 19 vehicle types, which tells the model which set of technologies can be applied to that vehicle. (For a description of how the 19 vehicle types were created, see Section III.D.3.) In addition, the degree to which each baseline vehicle already reflects the effectiveness and cost of each available technology must also be input. This avoids the situation,

321 Previous OMEGA documentation for versions used in MYs 2012-2016 Final Rule (EPA-420-B-09-035), Interim Joint TAR (EPA-420-B-10-042)

322 http://www.epa.gov/oms/climate/models.htm

323 EPA-420-R-09-016, September 2009.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 307 of 768 for example, where the model might try to add a basic engine improvement to a current hybrid vehicle. Except for this type of information, th e development of the requ ired data regarding the reference fleet was described in Section III.D.1 above and in Chapter 1 of the Joint TSD.

The second type of input data used by the model is a description of the technologies available to manufacturers, primarily their cost and effectiveness. This information was described above as well as Chapter 3 of the Joint TSD and Chapter 1 of EPA’s draft RIA. In all cases, the order of the technologies or technology packages for a particular vehicle type is determined by the model user prior to running the model. The third type of input data describes vehicle operational data, such as annual vehicle scrappage rates and mileage accumulation rates, and economic data, such as fuel prices and discount rates. These estimates are described in Section II.E above, Section III.H below an d Chapter 4 of the Joint TSD.

The fourth type of data describes the CO 2 emission standards being modeled. These include the MY 2016 standards, proposed MY 20 21 and proposed MY 2025 standards. As described in more detail below, the application of A/C technology is evaluated in a separate analysis from those technologies which impact CO 2 emissions over the 2-cycle test procedure. Thus, for the percent of vehicles that are projected to achieve A/C related reductions, the CO 2 credit associated with the projected use of improved A/C systems is used to adjust the final CO 2 standard which will be applicable to each manufacturer to develop a target for CO 2 emissions over the 2-cycle test which is assessed in our OMEGA modeling. As an example, on an industry wide basis, EPA projects that manufacturers will ge nerate 11 g/mi of A/C credit in 2016. Thus,
the 2016 CO 2 target in OMEGA was approximately eleven grams less stringent for each manufacturer than predicted by the curves. Similar adjustments were made for the control cases (i.e. the A/C credits allowed by the rule are accounted for in the standards), but for a larger amount of A/C credit (approximately 25 grams).

As mentioned above for the market data input file utilized by OMEGA, which characterizes the vehicle fleet, our modeling account s for the fact that many 2008 MY vehicles are already equipped with one or more of the t echnologies discussed in Section III.D.2 above. Because of the choice to apply technologies in packages, and because 2008 vehicles are equipped with individual technologies in a wide variety of combinations, accounting for the presence of specific technologies in terms of their proportion of package cost and CO 2 effectiveness requires careful, detailed analysis.

Thus, EPA developed a method to account for the presence of the combinations of applied technologies in terms of their proportion of the technology packages. This analysis can be broken down into four steps

The first step in the updated process is to break down the available GHG control technologies into five groups: 1) engine-related , 2) transmission-related, 3) hybridization, 4) weight reduction and 5) other. Within each group, each individual technology was given a ranking which generally followed the degree of complexity, cost and effectiveness of theSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 308 of 768 technologies within each group. More specifical ly, the ranking is based on the premise that a technology on a 2008 baseline vehicle with a lower ranking would be replaced by one with a higher ranking which was contained in one of the technology packages which we included in our OMEGA modeling. The corollary of this premise is that a technology on a 2008 baseline vehicle with a higher ranking would be not be replaced by one with an equal or lower ranking which was contained in one of the technology packages which we chose to include in our OMEGA modeling. This ranking scheme can be seen in an OMEGA pre-processor (the TEB/CEB calculation macro), available in the docket.

In the second step of the process, these rankings were used to estimate the complete list of technologies which would be present on each baseline vehicle after the application of a technology package. In other words, this step indicates the specific technology on each baseline vehicle after a package has been applied to it. EPA then used the lumped parameter model to estimate the total percentage CO2 emission redu ction associated with the technology present on the baseline vehicle (termed package 0), as well as the total percentage reduction after application of each package. A similar approach was used to determine the total cost of all of the technology present on the baseline vehicle and after the application of each applicable technology package.

The third step in this process is to account for the degree of each technology package’s
incremental effectiveness and incremental cost is affected by the technology already present on the baseline vehicle. In this step, we calculate the degree to which a technology package’s effectiveness is already present on the baseline vehicle, and produce a value for each package termed the technology effectiveness basis, or TEB. The degree to which a technology package’s incremental cost is reduced by technology already present on the baseline vehicle is termed the cost effectiveness basis, or CEB, in the OMEGA model. The equations for calculating these values can be seen in RIA chapter 3.

As described in Section III.D.3 above, technology packages are applied to groups of vehicles which generally represent a single vehicle platform and which are equipped with a single engine size (e.g., compact cars with four cylinder engine produced by Ford). These groupings are described in xx. Thus, the fourth step is to combine the fractions of the CEB and TEB of each technology package already present on the individual MY 2008 vehicle models for each vehicle grouping. For cost, percentages of each package already present are combined using a simple sales-weighting procedure, since the cost of each package is the same for each vehicle in a grouping. For effectiveness, the individual percentages are combined by weighting them by both sales and base CO 2 emission level. This appropriat ely weights vehicle models with either higher sales or CO 2 emissions within a grouping. Once again, this process prevents the model from adding technology which is already present on vehicles, and thus ensures that the model does not double count technology effectiven ess and cost associated with complying with
the modeled standards.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 309 of 768 Conceptually, the OMEGA model begins by determining the specific CO 2 emission standard applicable for each manufacturer and its vehicle class (i.e., car or truck). Since the proposal allows for averaging across a manufacturer’s cars and trucks, the model determines the

CO 2 emission standard applicable to each manufacturer’s car and truck sales from the two sets of coefficients describing the piecewise linear st andard functions for cars and trucks (i.e. the respective car and truck curves) in the inputs, an d creates a combined car-truck standard. This combined standard considers the difference in lifetime VMT of cars and trucks, as indicated in the proposed regulations which govern credit tr ading between these two vehicle classes (which reflect the final 2012-2016 rules on this point). 324

As noted above, EPA estimated separately the cost of the improved A/C systems required to generate the credit. In the reference case fleet that complies with the MY 2016 standards, 85% of vehicles are modeled with improved A/C ef ficiency and leakage prevention technology.

The model then works with one manufacturer at a time to add technologies until that manufacturer meets its applicab le proposed standard. The OMEGA model can utilize several approaches to determining the order in which vehicles receive technologies. For this analysis,
EPA used a “manufacturer-based net cost-effectiv eness factor” to rank the technology packages in the order in which a manufacturer is likely to apply them. Conceptually, this approach estimates the cost of adding the technology from the manufacturer’s perspective and divides it by
the mass of CO 2 the technology will reduce. One component of the cost of adding a technology is its production cost, as discussed above. Howe ver, it is expected that new vehicle purchasers value improved fuel economy since it reduces the co st of operating the vehicle. Typical vehicle purchasers are assumed to value the fuel savings accrued over the period of time which they will own the vehicle, which is estimated to be roughly five years. It is also assumed that consumers discount these savings at the same rate as that used in the rest of the analysis (3 or 7 percent). 325
Any residual value of the additional technology wh ich might remain when the vehicle is sold is
not considered. The CO 2 emission reduction is the change in CO 2 emissions multiplied by the percentage of vehicles surviving after each year of use multiplied by the annual miles travelled by age.

Given this definition, the higher priority technologies are those with the lowest manufacturer-based net cost-effectiveness value (r elatively low technology cost or high fuel savings leads to lower values). Because the order of technology application is set for each vehicle, the model uses the manufacturer-based net cost-effectiveness primarily to decide which vehicle receives the next technology addition. Initially, technolo gy package #1 is the only one available to any particular vehicle. However, as soon as a vehicle receives technology package

324 The analysis for the control cases in this proposal was run with slightly different lifetime VMT estimates than those proposed in the regulation. The impact is on the cost estimates is small and varies by manufacturer.

325 While our costs and benefits are discounted at 3% or 7%, the decision algorithm (TARF) used in OMEGA was run at a discount rate of 3%. Given that manufacturers must comply with the standard regardless of the discount rate used in the TARF, this has little impact on the technology projections shown here.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 310 of 768 #1, the model considers the manufacturer-based net cost-effectiveness of technology package #2 for that vehicle and so on. In general terms, the equation describing the calculation of
manufacturer-based cost effectiveness is as follows:

݂ݑܽ݊ܯ݂݂ܧݐݏ݋ܥ ௧ ൌ ܵܨ∆ െ ݐݏ݋ܥ݄ܶ݁ܿ∆

∆ܥܱ ଶ ݔ ܸܯܶ ௚௘௥௨௟௔௧௢௥௬

Where:

CostEffManuf t = Manufacturer-Based Cost Effectiveness (in dollars per kilogram CO 2 ), TechCost = Marked up cost of the technology (dollars), FS = Difference in fuel consumption due to the addition of technology times fuel price and discounted over the payback period, or the number of years of vehicle use over which consumers value fuel savings when evaluating the value of a new vehicle at time of purchase dCO 2 = Difference in CO 2 emissions (g/mile) due to the addition of technology
VMT regulatory = the statutorily defined VMT

EPA describes the technology ranking methodology and manufacturer-based cost effectiveness metric in greater detail in the OMEGA documentation (XX reference here).

When calculating the fuel savings in the TARF equation, the full retail price of fuel, including taxes is used. While taxes are not generally included when calculating the cost or benefits of a regulation, the net cost component of the manufacturer-based net cost-effectiveness equation is not a measure of the social cost of this final rule, but a measure of the private cost, (i.e., a measure of the vehicle purchaser’s willingn ess to pay more for a vehicle with higher fuel efficiency). Since vehicle operators pay the full price of fuel, including taxes, they value fuel costs or savings at this level, and the manufactur ers will consider this when choosing among the technology options. 326

The values of manufacturer-based net cost -effectiveness for specific technologies will vary from vehicle to vehicle, often substantially. This occurs for three reasons. First, both the cost and fuel-saving component cost, ownership fuel-savings, and lifetime CO 2 effectiveness of a specific technology all vary by the type of vehicle or engine to which it is being applied (e.g., small car versus large truck, or 4-cylinder versus 8-cylinder engine). Second, the effectiveness

326 This definition of manufacturer-based net cost-effectiv eness ignores any change in the residual value of the vehicle due to the additional technology when the vehicle is five years old. Based on historic used car pricing, applicable sales taxes, and insurance, vehicles are wort h roughly 23% of their original cost after five years, discounted to year of vehicle purchase at 7% per annum. It is reasonable to estimate that the added technology to improve CO2 level and fuel economy will retain this same pe rcentage of value when the ve hicle is five years old. However, it is less clear whether first purchasers, and thus , manufacturers consider this residual value when ranking technologies and making vehicle purchases, respectively. For this proposal, this factor was not included in our determination of manufacturer-based net cost-effectiveness in the analyses.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 311 of 768 of a specific technology often depends on the pr esence of other technologies already being used on the vehicle (i.e., the dis-synergies). Third, the absolute fuel savings and CO 2 reduction of a percentage an incremental reduction in fuel consumption depends on the CO 2 level of the vehicle prior to adding the technology. Chapter 1 of EPA’s draft RIA contains further detail on the values of manufacturer-based net cost-effectiveness for the various technology packages.

5. Projected Compliance Costs and Technology Penetrations

The following tables present the projected incremental costs and technology penetrations for the proposed program. Overall projected cost increases are $734 in MY 2021 and $1946 in MY 2025. Relative to the reference fleet complying with of MY 2016 standards, we see significant increases in advanced transmission tech nologies such as the high efficiency gear box and 8 speed transmissions, as well as more moderate increase in turbo downsized, cooled EGR 24 bar BMEP engines. In the control case, 15 percent of the MY 2025 fleet is projected to be a strong P2 hybrid as compared to 5% in the 2016 reference case. Similarly, 3 percent of the MY 2025 fleet are projected to be electric vehicles while less than 1 percent are projected to be
electric vehicles in the reference case.

Table III-21 Total Costs per Vehicle by Company, Incremental to the 2016 Standards (2009$)

Company 2021 2025
Cars Trucks Fleet Cars Trucks Fleet
BMW $950 $905 $938 $2,255 $1,949 $2,175 Chrysler/Fiat $575 $843 $696 $1,919 $2,202 $2,041 Daimler $1,954 $945 $1,703 $2,936 $1,942 $2,709 Ferrari 327 $6,357 n/a $6,357 $7,114 n/a $7,114 Ford $661 $765 $696 $2,056 $2,453 $2,178 Geely-Volvo $2,041 $1,076 $1,741 $3,233 $2,030 $2,876
GM $508 $669 $588 $2,214 $1,824 $2,028 Honda $473 $746 $557 $1,457 $1,927 $1,595 Hyundai $619 $874 $671 $1,682 $1,978 $1,741 Kia $489 $916 $584 $1,447 $1,665 $1,493 Mazda $930 $887 $922 $2,201 $1,796 $2,134 Mitsubishi $818 $987 $877 $2,119 $2,161 $2,133 Nissan $764 $652 $730 $2,002 $2,202 $2,061 Porsche $5,460 $1,317 $4,484 $5,832 $2,044 $5,013 Spyker-Saab $3,341 $888 $2,990 $4,006 $1,458 $3,673

327 Note that Ferrari is shown as a separate entity in the table above but could be combined with other Fiat-owned companies for purposes of GHG compliance at the manufacturer's discretion. Also, in Section III.B., EPA is requesting comment on the concept of allowing companies th at are able to demonstrate "operational independence" to be eligible for SVM alternative standards. Howeve r, the costs shown above are based on Ferrari meeting the primary program standards.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 312 of 768 Subaru $1,023 $912 $996 $2,241 $2,077 $2,204 Suzuki $1,166 $990 $1,135 $2,312 $1,822 $2,228
Tata-JLR $2,226 $1,638 $1,933 $3,260 $2,643 $2,974 Toyota $338 $703 $480 $1,404 $1,621 $1,483
VW $1,630 $786 $1,459 $2,623 $2,038 $2,508 Fleet $723 $753 $734 $1,946 $1,944 $1,946 Costs for Aston Martin, Lotus and Tesla are not included here but can be found in EPA’s draft RIA. Costs include stranded capital and A/C-related costs.Summary of Interagency Working Comments Received on Draftrule under EO 12866 review. Subject to further policyreview.Page313of768Table III-22 Technology Penetrations for the 2021 MY Reference Case – Combined FleetMass TDS18 TDS24 TDS27 AT6 AT8 DCT6 DCT8 MT HEG EGR HEV EV PHEV SS LRRT2 IACC2 EFR2 GDI DSLBMW -8% 51% 15% 0% 28% 8% 36% 19% 9% 0% 15% 15% 0% 0% 57% 0% 30% 0% 77% 13%Chrysler/Fiat-7% 45% 11% 0% 27% 12% 31% 17% 3% 0% 4% 0% 0% 0% 0% 0% 18% 0% 56% 0%Daimler -8% 48% 14% 0% 16% 19% 39% 21% 5% 0% 14% 15% 0% 0% 57% 0% 30% 0% 69% 16%Ferrari -8% 42% 15% 0% 14% 0% 52% 28% 5% 0% 15% 15% 0% 0% 57% 0% 30% 0% 72% 13%Ford -7% 52% 12% 0% 30% 12% 29% 16% 6% 0% 10% 2% 0% 0% 0% 0% 21% 0% 63% 0%GeelyVolvo-8% 54% 15% 0% 37% 12% 32% 17% 2% 0% 15% 15% 0% 0% 57% 0% 30% 0% 72% 13%GM -7% 37% 8% 0% 38% 18% 20% 11% 3% 0% 6% 0% 0% 0% 0% 0% 21% 0% 46% 0%Honda -3% 6% 0% 0% 24% 6% 41% 19% 8% 0% 0% 2% 0% 0% 0% 0% 8% 0% 6% 0%Hyundai -3% 28% 0% 0% 24% 11% 32% 17% 6% 0% 0% 0% 0% 0% 0% 0% 4% 0% 28% 0%Kia -3% 9% 0% 0% 22% 9% 35% 19% 7% 0% 0% 0% 0% 0% 0% 0% 8% 0% 9% 0%Mazda -5% 26% 11% 0% 22% 7% 34% 19% 14% 0% 4% 0% 0% 0% 0% 0% 24% 0% 37% 0%Mitsubishi -7% 68% 15% 0% 17% 7% 39% 22% 6% 0% 15% 2% 0% 0% 0% 0% 27% 0% 85% 0%Nissan -5% 33% 8% 0% 20% 8% 39% 21% 4% 0% 3% 1% 0% 0% 0% 0% 21% 0% 41% 0%Porsche -5% 48% 15% 0% 20% 7% 19% 10% 43% 0% 15% 15% 0% 0% 57% 0% 30% 0% 78% 13%SpykerSaab-8% 57% 15% 0% 19% 4% 41% 23% 11% 0% 15% 15% 0% 0% 57% 0% 30% 0% 72% 13%Subaru -7% 46% 5% 0% 6% 2% 39% 22% 22% 0% 3% 0% 0% 0% 0% 0% 17% 0% 50% 0%Suzuki -1% 67% 15% 0% 11% 4% 42% 23% 9% 0% 15% 3% 0% 0% 0% 0% 26% 0% 85% 0%Tata-JLR -8% 48% 15% 0% 33% 10% 37% 20% 0% 0% 15% 15% 0% 0% 57% 0% 30% 0% 72% 13%Toyota -2% 5% 0% 0% 26% 10% 28% 15% 5% 0% 0% 12% 0% 0% 0% 0% 12% 0% 12% 0%VW -7% 50% 15% 0% 22% 6% 40% 21% 11% 0% 15% 15% 0% 0% 57% 0% 30% 0% 86% 13%Fleet -5% 30% 7% 0% 27% 11% 31% 16% 6% 0% 5% 5% 0% 0% 7% 0% 18% 0% 40% 2%Mass=true mass reduction; TDS18/24/27=turbocharged & downsized at18/24/27 bar BMEP; AT=automatic transmission; DCT=dual clutchtransmission; MT=manual transmission; HEG=highefficiency gearbox; EGR=cooled exhaust gas recirculation; HEV=hybrid electric vehicle; EV=full electric vehicle; PHEV=plug-in HEV; SS=12V stop-start; LRRT2=lowerrolling resistance tires level2; IACC2=Improved accessories level 2; EFR2=engine friction reduction level 2; GDI=stoichiometricgasoline direct injection; DSL=advanced dieselNote that technology penetrations for Aston Martin, Lotus and Tesla are not included here but can be found in EPA’s draft RIA.Negative values for Mass Reduction represent percentage of mass removed.Summary of Interagency Working Comments Received on Draftrule under EO 12866 review. Subject to further policyreview.Page314of768Table III-23 Technology Penetrations for the 2025 MY Reference Case – Combined FleetMass TDS18 TDS24 TDS27 AT6 AT8 DCT6 DCT8 MT HEG EGR HEV EV PHEV SS LRRT2 IACC2 EFR2 GDI DSLBMW -8% 51% 15% 0% 31% 10% 33% 18% 9% 0% 15% 15% 0% 0% 57% 0% 30% 0% 76% 13%Chrysler/Fiat-7% 47% 13% 0% 33% 15% 26% 14% 3% 0% 12% 0% 0% 0% 0% 0% 22% 0% 60% 0%Daimler -8% 51% 14% 0% 22% 23% 32% 18% 6% 0% 14% 15% 0% 0% 57% 0% 30% 0% 68% 18%Ferrari -8% 42% 15% 0% 14% 0% 52% 28% 5% 0% 15% 15% 0% 0% 57% 0% 30% 0% 72% 13%Ford -7% 46% 12% 0% 28% 12% 29% 16% 5% 0% 7% 2% 0% 0% 0% 0% 23% 0% 57% 0%GeelyVolvo-8% 54% 15% 0% 40% 14% 29% 16% 2% 0% 15% 15% 0% 0% 57% 0% 30% 0% 72% 13%GM -8% 35% 12% 0% 39% 19% 18% 10% 3% 0% 11% 0% 0% 0% 0% 0% 22% 0% 48% 0%Honda -3% 17% 0% 0% 27% 7% 38% 21% 7% 0% 0% 2% 0% 0% 0% 0% 5% 0% 17% 0%Hyundai -3% 22% 0% 0% 21% 9% 34% 19% 6% 0% 0% 0% 0% 0% 0% 0% 5% 0% 22% 0%Kia -2% 0% 0% 0% 20% 8% 36% 20% 8% 0% 0% 0% 0% 0% 0% 0% 9% 0% 0% 0%Mazda -5% 24% 11% 0% 19% 5% 37% 20% 14% 0% 3% 0% 0% 0% 0% 0% 24% 0% 35% 0%Mitsubishi -8% 66% 15% 0% 19% 8% 39% 21% 3% 0% 15% 4% 0% 0% 0% 0% 28% 0% 85% 0%Nissan -5% 31% 7% 0% 18% 7% 40% 22% 4% 0% 3% 1% 0% 0% 0% 0% 22% 0% 39% 0%Porsche -6% 50% 15% 0% 29% 11% 16% 9% 36% 0% 15% 15% 0% 0% 57% 0% 30% 0% 79% 13%SpykerSaab-9% 57% 15% 0% 17% 3% 44% 24% 11% 0% 15% 15% 0% 0% 57% 0% 30% 0% 72% 13%Subaru -7% 40% 5% 0% 6% 2% 40% 22% 22% 0% 3% 0% 0% 0% 0% 0% 19% 0% 44% 0%Suzuki -1% 68% 15% 0% 12% 4% 42% 23% 9% 0% 15% 2% 0% 0% 0% 0% 26% 0% 85% 0%Tata-JLR -8% 48% 15% 0% 30% 8% 40% 22% 0% 0% 15% 15% 0% 0% 57% 0% 30% 0% 72% 13%Toyota -3% 3% 0% 0% 24% 9% 37% 9% 5% 0% 0% 12% 0% 0% 0% 0% 12% 0% 10% 0%VW -7% 50% 15% 0% 22% 6% 40% 21% 11% 0% 15% 15% 0% 0% 57% 0% 30% 0% 86% 13%Fleet -5% 29% 8% 0% 27% 11% 32% 15% 6% 0% 6% 5% 0% 0% 7% 0% 19% 0% 40% 2%Mass=true mass reduction; TDS18/24/27=turbocharged & downsized at18/24/27 bar BMEP; AT=automatic transmission; DCT=dual clutchtransmission; MT=manual transmission; HEG=highefficiency gearbox; EGR=cooled exhaust gas recirculation; HEV=hybrid electric vehicle; EV=full electric vehicle; PHEV=plug-in HEV; SS=12V stop-start; LRRT2=lowerrolling resistance tires level2; IACC2 = improved accessories level 2; EFR2=engine friction reduction level 2; GDI=stoichiometric gasoline direct injection;DSL=advanced dieselNote that technology penetrations for Aston Martin, Lotus and Tesla are not included here but can be found in EPA’s draft RIA.Negative values for Mass Reduction represent percentage of mass removed.Summary of Interagency Working Comments Received on Draftrule under EO 12866 review. Subject to further policyreview.Page315of768Table III-24 Technology Penetrations for the 2021 MY Control Case – Combined FleetMass TDS18 TDS24 TDS27 AT6 AT8 DCT6 DCT8 MT HEG EGR HEV EV PHEV SS LRRT2 IACC2 EFR2 GDI DSLBMW -9% 49% 25% 2% 5% 21% 13% 52% 8% 59% 28% 30% 1% 0% 0% 75% 80% 59% 99% 0%Chrysler/Fiat-7% 64% 15% 2% 8% 32% 11% 45% 3% 60% 14% 0% 0% 0% 0% 75% 80% 60% 81% 0%Daimler -10% 48% 20% 4% 5% 20% 13% 52% 4% 57% 24% 30% 6% 0% 0% 75% 80% 57% 91% 3%Ferrari -7% 0% 0% 15% 0% 0% 16% 65% 2% 50% 15% 30% 16% 15% 15% 75% 80% 50% 60% 24%Ford -8% 75% 16% 3% 8% 32% 10% 42% 6% 59% 18% 2% 0% 0% 0% 74% 79% 59% 94% 0%GeelyVolvo-10% 52% 18% 6% 8% 32% 10% 42% 1% 57% 24% 30% 6% 0% 11% 75% 80% 57% 94% 0%GM -8% 41% 14% 3% 12% 49% 7% 29% 3% 60% 14% 0% 0% 0% 0% 75% 80% 60% 58% 0%Honda -5% 33% 0% 0% 4% 15% 14% 56% 8% 59% 0% 2% 0% 0% 0% 73% 78% 59% 33% 0%Hyundai -6% 45% 6% 0% 7% 29% 12% 46% 6% 60% 6% 0% 0% 0% 0% 75% 80% 60% 51% 0%Kia -4% 37% 0% 0% 6% 23% 13% 51% 7% 60% 0% 0% 0% 0% 0% 41% 44% 60% 37% 0%Mazda -6% 78% 22% 0% 5% 19% 12% 50% 14% 60% 11% 0% 0% 0% 0% 75% 80% 60% 100% 0%Mitsubishi -10% 64% 30% 0% 5% 18% 14% 58% 5% 60% 30% 6% 0% 0% 0% 75% 80% 60% 100% 0%Nissan -5% 68% 14% 1% 5% 21% 14% 56% 4% 60% 15% 1% 0% 0% 0% 75% 80% 60% 83% 0%Porsche -5% 24% 25% 4% 5% 19% 9% 36% 21% 54% 29% 30% 11% 11% 16% 75% 80% 54% 86% 3%SpykerSaab-8% 34% 24% 3% 3% 11% 14% 55% 7% 54% 27% 30% 10% 3% 10% 75% 80% 54% 90% 0%Subaru -9% 69% 30% 0% 1% 5% 14% 58% 22% 60% 30% 1% 0% 0% 0% 75% 80% 60% 100% 0%Suzuki -2% 49% 30% 0% 3% 11% 16% 63% 7% 60% 30% 21% 0% 0% 0% 75% 80% 60% 100% 0%Tata-JLR -9% 54% 9% 11% 7% 26% 12% 48% 0% 56% 19% 30% 7% 0% 4% 75% 80% 56% 93% 0%Toyota -3% 40% 0% 1% 7% 26% 10% 41% 5% 53% 1% 12% 0% 0% 0% 38% 40% 53% 41% 0%VW -8% 42% 27% 1% 4% 16% 13% 54% 8% 57% 29% 30% 5% 0% 0% 75% 80% 57% 95% 0%Fleet -6% 50% 11% 2% 7% 28% 11% 44% 6% 58% 12% 7% 1% 0% 0% 66% 71% 58% 65% 0%Mass=true mass reduction; TDS18/24/27=turbocharged & downsized at18/24/27 bar BMEP; AT=automatic transmission; DCT=dual clutchtransmission; MT=manual transmission; HEG=highefficiency gearbox; EGR=cooled exhaust gas recirculation; HEV=hybrid electric vehicle; EV=full electric vehicle; PHEV=plug-in HEV; SS=12V stop-start; LRRT2=lowerrolling resistance tires level2; IACC2=Improved accessories level 2; EFR2=engine friction reduction level 2; GDI=stoichiometric gasoline direct injection; DSL=advanced dieselNote that technology penetrations for Aston Martin, Lotus and Tesla are not included here but can be found in EPA’s draft RIA.Negative values for Mass Reduction represent percentage of mass removed.Summary of Interagency Working Comments Received on Draftrule under EO 12866 review. Subject to further policyreview.Page316of768Table III-25 Technology Penetrations for the 2025 MY Control Case – Combined FleetMass TDS18 TDS24 TDS27 AT6 AT8 DCT6 DCT8 MT HEG EGR HEV EV PHEV SS LRRT2 IACC2 EFR2 GDI DSLBMW -10% 8% 58% 6% 0% 26% 0% 59% 7% 92% 64% 34% 8% 0% 0% 100% 100% 92% 92% 0%Chrysler/Fiat-11% 16% 66% 5% 0% 38% 0% 58% 2% 99% 71% 15% 1% 0% 0% 100% 100% 99% 99% 0%Daimler -11% 11% 41% 11% 0% 23% 0% 62% 4% 88% 53% 36% 12% 0% 0% 100% 100% 88% 86% 2%Ferrari -6% 0% 0% 5% 0% 0% 0% 77% 0% 77% 5% 50% 23% 22% 5% 100% 100% 77% 77% 0%Ford -11% 18% 56% 9% 0% 39% 0% 51% 4% 95% 65% 19% 4% 0% 0% 99% 99% 95% 95% 0%GeelyVolvo-10% 11% 42% 13% 0% 39% 0% 50% 1% 89% 54% 44% 11% 0% 0% 100% 100% 89% 89% 0%GM -11% 21% 60% 8% 0% 59% 0% 37% 2% 98% 68% 10% 2% 0% 0% 100% 100% 98% 98% 0%Honda -8% 24% 73% 0% 0% 18% 0% 71% 8% 98% 73% 3% 0% 0% 0% 98% 98% 98% 98% 0%Hyundai -10% 25% 75% 0% 0% 35% 0% 58% 6% 100% 75% 0% 0% 0% 0% 100% 100% 100% 100% 0%Kia -7% 39% 61% 0% 0% 27% 0% 66% 7% 100% 42% 0% 0% 0% 0% 100% 100% 100% 100% 0%Mazda -8% 6% 73% 0% 0% 23% 0% 65% 11% 98% 73% 19% 2% 0% 0% 100% 100% 98% 98% 0%Mitsubishi -12% 8% 70% 0% 0% 21% 0% 69% 4% 95% 70% 17% 5% 0% 0% 100% 100% 95% 95% 0%Nissan -7% 13% 69% 3% 0% 25% 0% 69% 3% 98% 72% 20% 2% 0% 0% 100% 100% 98% 98% 0%Porsche -5% 8% 35% 7% 0% 21% 0% 42% 19% 83% 41% 34% 17% 10% 1% 100% 100% 83% 83% 0%SpykerSaab-10% 5% 47% 3% 0% 13% 0% 66% 6% 84% 50% 32% 16% 5% 2% 100% 100% 84% 84% 0%Subaru -10% 6% 71% 0% 0% 6% 0% 72% 19% 96% 71% 19% 4% 0% 0% 100% 100% 96% 96% 0%Suzuki -3% 3% 67% 0% 0% 14% 0% 72% 6% 92% 67% 22% 8% 0% 0% 100% 100% 92% 92% 0%Tata-JLR -9% 15% 16% 29% 0% 31% 0% 58% 0% 88% 45% 43% 12% 0% 0% 100% 100% 88% 88% 0%Toyota -7% 23% 60% 4% 0% 30% 0% 53% 5% 88% 64% 13% 0% 0% 0% 88% 88% 88% 88% 0%VW -8% 6% 60% 3% 0% 20% 0% 63% 8% 90% 62% 31% 10% 1% 0% 100% 100% 90% 90% 0%Fleet -9% 19% 62% 5% 0% 34% 0% 55% 5% 94% 66% 15% 3% 0% 0% 97% 97% 94% 94% 0%Mass=true mass reduction; TDS18/24/27=turbocharged & downsized at18/24/27 bar BMEP; AT=automatic transmission; DCT=dual clutchtransmission; MT=manual transmission; HEG=highefficiency gearbox; EGR=cooled exhaust gas recirculation; HEV=hybrid electric vehicle; EV=full electric vehicle; PHEV=plug-in HEV; SS=12V stop-start; LRRT2=lowerrolling resistance tires level2; IACC2=Improved accessories level 2; EFR2=engine friction reduction level 2; GDI=stoichiometric gasoline direct injection; DSL=advanced dieselNote that technology penetrations for Aston Martin, Lotus and Tata are not included here but can be found in EPA’s draft RIA.Negative values for Mass Reduction represent percentage of mass removed.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 317 of 768 6. How does the technical assessment support the proposed CO 2 standards as compared
to the alternatives has EPA considered?

a. What are the Targets and Achieved Levels for the Fleet in this Proposal?

In this section EPA analyzes the proposed standards alongside several potential alternative GHG standards.

Table III-26 includes a summary of the proposed standards and the four alternatives considered by EPA for this notice. In this table and for the majority of the data presented in this section, EPA focuses on two specific model years in the 2017-2025 time frame addressed by this proposal. For the purposes of considering altern atives, EPA assessed these two specific years as being reasonably separated in time in order to evaluate a range of meaningfully different standards, rather than analyzing alternatives for each individual model year. After discussing the reasons for selecting the proposed standards rather than any of the alternatives, EPA will describe the specific standard phase-in schedule for the proposal. Table III-26 presents the projected reference case targets for the fleet in 2021 and 2025, that is the estimated industry wide targets that would be required for the projected fleet in those years by the MY 2016 standards. 328 The alternatives, like the proposed standards, account for projected use of A/C related credits. They represent the average targets for cars and trucks projected for the proposed standards and four alternative standards. They do not represent the manner in which manufacturers are projected to achieve compliance with these targets, which includes the abil ity to transfer credits to and from the car and truck fleets. That is discussed later.

Table III-26 2021 and 2025 Fleet Targets for the Proposal and Alternative Standards (grams/mile CO 2 )

Car Target Truck Target Fleet Target 2021 Proposal 173 249 199
Alternative 1: 2021 Trucks+20 173 270 207
Alternative 2: 2021 Trucks-20 173 230 193
Alternative 3: 2021 Cars+20 193 250 213
Alternative 4: 2021 Cars-20 153 250 187 2021 Reference Case 225 297 250

2025 Proposal 144 203 163
Alternative 1: 2025 Trucks+20 144 223 170
Alternative 2: 2025 Trucks-20 144 183 157
Alternative 3: 2025 Cars+20 164 203 177
Alternative 4: 2025 Cars-20 124 203 150

328 The reference case targets for 2021 and 2025 may be different even though the footprint based standards are identical (the 2016 curves). This is because the fleet distribution of ca rs and trucks may change in the intervening years thus changing the targets in 2021 and 2025.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 318 of 768 2025 Reference Case 225 295 248

Alternative 1 and 2 are focused on changes in the level of stringency for just light-duty trucks: Alternative 1 is 20 grams/mile CO 2 less stringent (higher) in 2021 and 2025, and Alternative 2 is 20 grams/mile CO 2 more stringent (lower) in 2021 and 2025. Alternative 3 and 4 are focused on changes in the level of stringency for just passenger cars: Alternative 3 is 20 grams/mile CO 2 less stringent (higher) in 2021 and 2025, and Alternative 4 is 20 grams/mile CO 2 more stringent (lower) in 2021 and 2025. When combined with the sales projections for 2021 and 2025, these alternatives span fleet wide targets with a range of 187-213 g/mi CO 2 in 2021 (equivalent to a range of 42-48 mpge if all improvements were made with fuel economy technologies) and a range of 150-177 g/mi CO 2 in 2025 in 2025 (equivalent to a range of 50-59 mpg if all improvements were made with fuel economy technologies).

Using the OMEGA model, EPA evaluated the proposed standards and each of the alternatives in 2021 and in 2025. It is worth noting that although Alternatives 1 and 2 consider different truck footprint curves compared to th e proposal and Alternatives 3 and 4 evaluate different car footprint curves compared to the proposal, in all cases EPA evaluated the alternatives by modeling both the car and truck fo otprint curves together (which achieve the fleet targets shown in Table III-26) as this is how manufacturers would view the future standards given the opportunity to transfer credits between cars and trucks under the GHG program. A manufacturer’s ability to transfer GHG credits between its car and truck fleets without limit does have the effect of muting the “truck” focused and “car” focused nature of the alternatives EPA is evaluating. For example, while Alternative 1 has truck standards projected in 2021 and 2025 to be 20 grams/mile less stringent than the proposed truck standards and the same carstandards as the proposed car standards, individual firms may over comply on trucks and undercomply on cars (or vice versa) in order to meet Alternative 1 in a cost effective manner from each company’s perspective. EPA’s modeling of single manufacturer fleets reflects this flexibility, and appropriately so given that it reflects manufacturers’ expected response.

Table III-27 shows the projected target and projected achieved levels in 2025 for the proposed standards. This accounts for a manufactur er’s ability to transfer credits to and from cars and trucks to meet a manufacturer’s car and truck targets.

Table III-27 2025 Projected Target and Achieved Levels for the Proposal for Individual Firms (grams/mile CO2)

Target Achieved

CarTargetAchieved TruckTargetAchieved Company Cars Trucks Fleet Cars Trucks Fleet
BMW 146 194 159 145 196 158 1 -2 Chrysler/Fiat 146 201 170 148 199 170 -2 2
Daimler 153 208 166 146 230 165 8 -22
Ferrari 150 n/a 150 159 n/a 159 -9 n/a
Ford 147 213 167 153 200 167 -6 13Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 319 of 768 Geely-Volvo 148 189 160 141 204 159 8 -15
GM 146 213 178 146 212 178 0 1
Honda 142 191 156 143 186 156 -2 5 Hyundai 142 188 151 145 178 152 -3 11
Kia 143 199 155 146 189 155 -3 10
Mazda 142 186 149 145 172 150 -3 14
Mitsubishi 139 180 153 144 171 153 -5 8
Nissan 145 202 162 143 204 161 1 -2
Porsche 131 195 144 119 231 143 12 -36 Spyker-Saab 141 188 148 133 231 146 8 -43
Subaru 137 177 146 147 149 147 -10 28
Suzuki 132 181 140 132 179 140 -1 3
Tata-JLR 161 182 171 134 208 168 27 -26 Toyota 141 200 163 140 201 162 1 -1
VW 139 203 152 133 225 151 6 -22
Fleet 144 203 163 144 202 163 -0.1 1.6

Note: This table and the remainder in this section do not include projections for Aston Martin and Lotus. These two firms would qualify for consideration of the unique Small Volume Manufacturer alternative standards discussed in Section III.XX, and thus while we have included modeling for these companies in the Draft RIA, we do not present the results in this section. In addition, we do not present in this section results for the firm Tesla, as our forecast assumes they only make all electric vehi cles, and thus under any standard we analyzed the firm always complies without the addition of any technology.

Similar tables for each of the alternatives for 2025 and for the alternatives and the proposal for 2021 are contained in Chapter 3 of EPA’s draft RIA. With the proposed standards and for Alternatives 1 and 2, all companies are projected to be able to comply both in 2021 and 2025, with the with the exception of Ferrari, which in each case falls 9 g/mi short of its projected fleet wide obligation in 2025. 329 In Alternatives 3 and 4, where the car stringency varies, all companies are again projected to comply with the exception of Ferrari, which complies under Alternative 3, but has a 30 gram shortfall under Alternative 4. This was not the case for the 2016 standards from the previous rule. The primary reas on for this result is the penetration of more efficient technologies beyond 2016. As described earlier, many technologies projected as not to be available by MY 2016 or whose penetration was limited due to lead time issues are projected to be available or available at greater penetr ation rates in the 2017-2025 timeframe, especially given two more redesign cycles.

329 Note that Ferrari is shown as a separate entity in th e table above but could be comb ined with other Fiat-owned companies for purposes of GHG compliance at the manufact urer's discretion. Also, in Section III.B., EPA is requesting comment on the concept of allowing companies th at are able to demonstrate "operational independence" to be eligible for SVM alternative standards. Howeve r, the costs shown above are based on Ferrari meeting the primary program standards.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 320 of 768 b. Why is the Relative Rate of Ca r Truck Stringency Appropriate?

Table III-27 illustrates the importance of car-truck credit transfer for individual firms. For example, the OMEGA model projects for the proposed standards that in 2025, Daimler would under comply for trucks by 22 g/mile but over comply in their car fleet by 8 g/mi in order to meet their overall compliance obligation, while for Kia the OMEGA model projects that under the proposed standards Kia’s truck fleet would ov er comply by 10 g/mi and under comply in their car fleet by 3 g/mi in order to meet their compliance obligations. However, for the fleet as a whole, we project only a relatively small degree of net credit transfers from the truck fleet to the car fleet.

Table III-21 shows that the average costs for cars and trucks are also nearly equivalent for 2021 and 2025. For MY 2021, the average cost to comply with the car standards is $723, while it is $753 for trucks. For MY 2025, the average cost to comply with the car standards is $1,946, while it is $1,944 for trucks. These results are highly consistent with the small degree of net projected credit transfer between cars and trucks.

The average cost for complying with the truck and car standards are similar, even though the level of stringency for trucks is increasing at a slower rate than for cars. As described in Section I.B.2 of the preamble, the proposed car standards are decreasing (in CO 2 ) at a rate of 5% per year from MYs 2017-2025, while the proposed truck standards are decreasing at a rate of 3.5% per year on average from MYs 2017-2021, then 5% per year thereafter till 2025. Given this difference in percentage rates, the close simi larity in average cost stems from the fact that it is more costly to add the technolog ies to trucks (in general) than to cars as described in Chapter 1 of the draft RIA. Moreover, some technologies are not even available for towing trucks. These include EVs, PHEVs, Atkinson Cycle engines (m atched with HEVs), and dry DCT – the latter two are relatively cost effective. Together thes e result in a decrease in effectiveness potential for the heavier towing trucks compared to non-towing trucks and cars. In addition, , there is more mass reduction projected for these vehicles, but this comes at higher cost as well, as the cost for mass reduction goes up with higher levels of mass reduction. As described in greater detail in Chapter 2 of the joint TSD, these factors help explain the reason EPA and NHTSA are proposing to make the truck curve steeper relative to the 2016 curve, thus resulting in a truck curve that is “more parallel” to cars than the 2016 truck curve.

Taken together, our analysis shows that under the proposed standards, there is relatively little net trading between car and trucks; average costs for compliance with cars is similar to that of trucks in MY 2021 as well as MY 2025; and it is more costly to add technologies to trucks than to cars. These facts corroborate the reasonableness for increasing the slope of the truck curve. These observations also lead us to the conclusion that (at a fleet level) starting from MYs 2017-2021, the slower rate of increase for trucks compared to cars (3.5% compared to 5% per year), and the same rate of increase (5% per year) for both cars and trucks for MY2022-2025 results in car and truck standards that reflect increases in stringency over time that are comparable and consistent. There are no indicatio ns that either the truck or car standards are leading manufacturers to choose technology pa ths that lead to significant over or under compliance for cars or trucks, on an industry wide level. E.g., there is no indication that on average the proposed car standards would lead manufacturers to consistently under or over comply with the car standard in light of the truck standard, or vice versa. A consistent patternSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 321 of 768 across the industry of manufacturers choosing to under or over comply with a car or trucks standard could indicate that the car or truck standa rd should be evaluated further to determine if one was more or less stringent than might be appropriate in light of the technology choices available to manufacturers and their costs. As sh own above, that is not the case for the proposed car and truck standards. However, EPA did evaluate a set of alternative standards that reflect separately increasing or decreasing the stringency of the car and truck standards, as discussed below.

c. What are the Costs and Advanced Technology Penetration Rates for the
Alternative Standards in Relation to the Proposed Standards?

Below we discuss results for the proposed car and truck standards compared to the truck alternatives evaluated (Alternatives 1 and 2), and then discuss the proposed car and truck standards compared to the car alternatives (Alternatives 3 and 4).

Table III-28 presents our projected per-vehicle cost for the average car, truck and for the fleet in model year 2021 and 2025 for the proposal and for Alternatives 1 and 2. All costs are relative to the reference case (i.e. the fleet with technology added to meet the 2016 MY standards). As can be seen, even though only the truck standards vary among these three scenarios, in each case the projected average car and truck costs vary as a result of car-truck credit transfer by individual companies. Table III-28 shows that compared to the proposal, Alternative 1 (with a 2021 and 2025 truck target 20 g/mile less stringent, or 20 g/mile greater, than the proposal) is $281 per vehicle less than the proposal in 2021 and $430 per vehicle less than the proposal in 2025. Alternative 2 (with a 2021 and 2025 truck target 20g/mile more stringent, or 20 g/mile less, than the proposal) is $343 per vehicle more than the proposal in 2021 and $516 per vehicle more than the proposal in 2025.

Note that while the car and truck costs are nearly equivalent for Alternative 2 in 2021 and 2025, cars are over complying on average by 7 g/mi, while trucks are under complying by 11 g/mi, thus indicating significant flow of credits from cars to trucks. 330 The situation is reversed in Alternative 1, where cars are under complying on average by 9 g/mi and trucks are over complying by 16 g/mi, implying significant flow of credits from truck to cars.

Table III-28 2021 and 2025 Fleet Average Projected Per-Vehicle Costs for Proposal and Alternatives 1 and 2 ($/vehicle)

Cars Trucks Fleet 2021 Proposal $723 $753 $734

Alternative 1: 2021 Trucks+20 $441 $477 $453

Alternative 2: 2021 Trucks-20 $1,061 $1,110 $1,077

2025 Proposal $1,946 $1,944 $1,946

Alternative 1: 2025 Trucks+20 $1,489 $1,570 $1,516

Alternative 2: 2025 Trucks-20 $2,448 $2,491 $2,462

330 These detailed tables are in Chapter 3 of EPA’s draft RIA.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 322 of 768 Table III-29 presents the per-vehicle cost estimates in MY2021 by company for the proposal, Alternative 1 and Alternative 2. In ge neral, for most of the companies our projected results show the same trends as for the industry as a whole.

Table III-29 : 2021 Projected Per-Vehicle Costs for the Pr oposal and Alternatives 1 and 2 by Company (cars & trucks, $/vehicle)

Proposal Alternative 1 (trucks+20) Alternative 2 (trucks-20)

BMW $938 $428 $1,355 Chrysler/Fiat $696 $279 $1,124

Daimler $1,703 $1,257 $2,210

Ferrari $6,357 $6,357 $6,357

Ford $696 $369 $1,132 Geely-Volvo $1,741 $1,191 $2,438

GM $588 $200 $1,121

Honda $557 $411 $759 Hyundai $671 $561 $831

Kia $584 $481 $706

Mazda $922 $766 $1,115

Mitsubishi $877 $508 $1,385

Nissan $730 $463 $986

Porsche $4,484 $4,072 $5,150 Spyker-Saab $2,990 $2,700 $3,345

Subaru $996 $768 $1,321

Suzuki $1,135 $893 $1,373

Tata-JLR $1,933 $1,095 $2,819 Toyota $480 $320 $678

VW $1,459 $1,036 $1,815

Fleet $734 $453 $1,077

Table III-30 presents the per-vehicle cost estimates in MY2025 by company for the proposal, Alternative 1 and Alternative 2. In ge neral, for most of the companies our projected results show the same trends as for the industry as a whole, with Alternative 1 on the order of $200 to $600 per vehicle less expensive then the proposal, and Alternative 2 on the order of $200 to $800 per vehicle more expensive. For the fleet as a whole, the average cost for Alternative 1 is $430 less costly, while Alternative 2 is $516 more costly. Thus the incremental average cost is higher for the more stringent alternative than fo r an equally less stringent alternative standard. This is not a surprise as more technologies must be added to vehicles to meet tighter standards, and these technologies increase in cost in a non-linear fashion.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 323 of 768 Table III-30: 2025 Projected Per-Vehicle Costs for Proposal and Alternatives 1 and 2 by Company (cars & trucks, $/vehicle)

Proposal Alternative 1 (trucks+20) Alternative 2 (trucks-20)

BMW $2,175 $1,781 $2,608 Chrysler/Fiat $2,041 $1,453 $2,672

Daimler $2,709 $2,346 $3,128

Ferrari $7,114 $7,114 $7,114

Ford $2,178 $1,671 $2,671 Geely-Volvo $2,876 $2,375 $3,547

GM $2,028 $1,352 $2,875

Honda $1,595 $1,328 $1,988 Hyundai $1,741 $1,511 $2,006

Kia $1,493 $1,284 $1,716

Mazda $2,134 $1,897 $2,349

Mitsubishi $2,133 $1,758 $2,574

Nissan $2,061 $1,616 $2,487

Porsche $5,013 $4,556 $5,479 Spyker-Saab $3,673 $3,341 $3,890

Subaru $2,204 $1,926 $2,454

Suzuki $2,228 $2,053 $2,438

Tata-JLR $2,974 $2,335 $3,785 Toyota $1,483 $1,133 $2,014

VW $2,508 $2,170 $2,873

Fleet $1,946 $1,516 $2,462

The previous tables present the costs for the proposal and alternatives 1 and 2 at both the industry and company level. In addition to costs, another key is the technology required to meet potential future standards. The EPA assessment of the proposal, as well as Alternatives 1 and 2 predict the penetration into the fleet of a large number of technologies at various rates of penetration. A subset of these technologies ar e discussed below, while EPA’s draft RIA Chapter 3 includes the details on this much longer list for the passenger car fleet, light-duty truck fleet, and the overall fleet at both the industry and individual company level. Table III-31 and Table
III-32 present only a sub-set of the technologies EPA estimates could be used to meet the proposed standards as well as alternative 1 and 2 in MY 2021. Table III-33 and Table III-34 show the same for 2025. The technologies listed in these tables are those for which there is a large difference in penetration rates between the proposal and the alternatives. We have not included here, for example, the penetration rates for improved high efficiency gear boxes because in 2021 our modeling estimates a 58% penetration of this technology across the total fleet for the proposal as well as for alternatives 1 and 2, or 8 speed automatic transmissions which in 2021 we estimate at a 28 % penetration rate for the proposed standards as well as forSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 324 of 768 alternatives 1 and 2. There are several other technologies (shown in the Chapter 3 of the DRIA) where there is little differentiation between the proposal and alternatives 1 and 2.

Table III-31 shows that in 2021, for several technologies the proposal requires higher levels of penetration for trucks than alternative 1. For example for trucks, compared to the proposal, alternative 1 leads to an 8% decrease in the 24 bar turbo-charged/downsized engines, a 10% decrease in the penetration of cooled EGR, and a 12% decrease in the penetration of gasoline direct injection fuel systems. We also see that due to credit transfer between cars and trucks , the lower level of stringency considered for trucks in alternative 1 also impacts the penetration of technology to the car fleet – with alternative 1 leading to a 14% decrease inpenetration of 18 bar turbo-downsized engines, 5% decrease in penetration of 24 bar turbodownsize engines, 8% decrease in penetration of 8 speed dual clutch transmissions, and a 19% decrease in penetration of gasoline direct injecti on fuel systems in the car fleet. For the more stringent alternative 2, we see increases in th e penetration of many of these technologies projected for 2021, for the truck fleet as well as for the car fleet . Table III-32 shows these same overall trends but at the sales weighted fleet level in 2021.

Table III-31: 2021 Projected Technology Penetrations for Proposal and Alternatives 1 and 2 for all Cars and Trucks

Cars Trucks Technology Proposal Alt. 1 Alt. 2 Proposal Alt. 1 Alt. 2 Turbo-downsize(18 bar) 45% 31% 50% 59% 57% 66% Turbo-downsize (24 bar) 10% 5% 17% 14% 6% 19% 8 speed DCT 61% 53% 61% 13% 12% 13%
Cooled EGR* 9% 6% 18% 17% 7% 23% Hybrid Electric Vehicle 8% 7% 9% 4% 4% 7%
LRRT2 62% 53% 72% 74% 62% 74%
IACC2 67% 57% 77% 79% 66% 79%
GDI 60% 41% 73% 76% 64% 91% * In EPA packages TDS27 engines have cooled EGR, nearly al l TDS24 engines also have cooled EGR, virtually none of the TDS18 bar engines have cooled EGR (See Chapter 1 of the draft RIA)

Table III-32: 2021 Projected Technology Penetrations for Proposal and Alternatives 1 and 2 for Fleet

Proposal Al t . 1 Al t . 2 Turbo-downsize (18 bar) 50% 40% 55% Turbo-downsize (24 bar) 11% 5% 18% 8 speed DCT 44% 39% 44%
Cooled EGR 12% 6% 20% Hybrid Electric Vehicle 7% 6% 8%

LRRT2 66% 56% 73%Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 325 of 768 IACC2 71% 60% 78%
GDI 65% 49% 79%

Table III-33 s hows that in 2025, there is only a small change in many of these technology penetration rates when comparing the proposal to alte rnative 1 for trucks, and most of the change shows up in the car fleet. One important exception is hybrid electric vehicles, where the less stringent alternative 1 is projected to be met with a 4% decrease in penetration of HEVs compared to the proposal. As in 2021, we s ee that due to credit transfer between cars and trucks, the lower level of stringen cy considered for trucks in alternative 1 also impacts the carfleet penetration – with alternative 1 leading to a 8% decrease in penetration of 24 bar turbodownsized engines, 12% decrease in penetration of cooled EGR, 6% decrease in penetration of HEVs, and a 2% decrease in penetration of electric vehicles. For the more stringent alternative 2, we see only small increases in the penetrat ion of many of these technologies projected for 2025, with a major exception being a significant 14% increase in the penetration of HEVs for trucks compared to the proposal, a 6 % increase in the penetration of HEVs for cars compared to the proposal, and a 3% increase in the penetration of EVs for cars compared to the proposal.

Table III-33: 2025 Projected Technology Penetrations for Proposal and Alternatives 1 and 2 for all Cars and Trucks

Cars Trucks Proposal Alt. 1 Alt. 2 Proposal Alt. 1 Alt. 2 Turbo-downsize (18 bar) 14% 23% 8% 27% 24% 26% Turbo-downsize (24 bar) 65% 57% 63% 57% 57% 56% 8 speed DCT 75% 76% 73% 15% 16% 15%
Cooled EGR 66% 54% 64% 67% 68% 67% Hybrid Electric Vehicle 15% 9% 21% 13% 9% 27%
EV 4% 2% 7% 1% 0% 1%
LRRT2 96% 96% 96% 99% 99% 99%
IACC2 96% 96% 96% 99% 99% 99%
GDI 93% 88% 90% 97% 94% 97%

Table III-34: 2025 Projected Technology Penetrations for Proposal and Alternatives 1 and 2 for Fleet

Proposal Alt. 1 Alt. 2 Turbo-downsize (18 bar) 19% 24% 14% Turbo-downsize (24 bar) 62% 57% 60% 8 speed DCT 55% 56% 54%
Cooled EGR 66% 59% 65% Hybrid Electric Vehicle 15% 9% 23%Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 326 of 768 EV 3% 2% 5%
LRRT2 97% 97% 97%
IACC2 97% 97% 97%
GDI 94% 90% 92%

The results are similar for Alternatives 3 and 4, where the truck standard stays at the proposal level and the car stringency varies, +20 g/mi and -20 g/mi respectively. Table III-35 presents our projected per-vehicle cost for the average car, truck and for the fleet in model year 2021 and 2025 for the proposal and for Alternatives 3 and 4. Compared to the proposal, Alternative 3 (with a 2021 and 2025 car target 20 g/mile less stringent then the proposal) is $442 per vehicle less on average than the proposal in 2021 and $708 per vehicle less than the proposal in 2025. Alternative 4 (with a 2021 and 2025 car target 20g/mile more stringent then the proposal) is $635 per vehicle more on average than the proposal in 2021 and $923 per vehicle more than the proposal in 2025. These differences are even more pronounced than Alternatives 1 and 2. As in the analysis above, the costs increases are greater for more stringent alternatives than the reduced costs from the less stringent alternatives.

Note that although the car and truck costs are not too dissimilar for cars and trucks for Alternative 3 in 2025, what is not shown is that cars are over complying by 5 g/mi, while trucks are under complying by 7 g/mi, thus indicating sign ificant flow of credits from cars to trucks. The situation is reversed in Alternative 4, where cars are under complying by 6 g/mi and trucks are over complying by 12 g/mi implying significant flow of credits from truck to cars.

Table III-35: 2021 and 2025 Fleet Average Projected Per-Vehicle Costs for Proposal and Alternatives 3 and 4 ($/vehicle)

Cars Trucks Fleet 2021 Proposal $723 $753 $734

Alternative 3: 2021 Cars+20 $249 $379 $292

Alternative 4: 2021 Cars-20 $1,421 $1,265 $1,369

2025 Proposal $1,946 $1,944 $1,946

Alternative 3: 2025 Cars+20 $1,166 $1,384 $1,238

Alternative 4: 2025 Cars-20 $2,928 $2,750 $2,869

Table III-36 presents the per-vehicle cost estimates in MY2021 by company for the proposal, Alternative 3 and Alternative 4. In ge neral, for most of the companies our projected results show the same trends as for the industry as a whole, with Alternative 3 being a several hundred dollars per vehicle less expensive then the proposal, and Alternative 4 being several hundred dollars per vehicle more expensive (with larger increment for more stringent than lessSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 327 of 768 stringent alternatives). In some case the differences exceed $1,000 (e.g. BMW, Daimler, Geely/Volvo, Mazda, Spyker/Saab, and Tata).

Table III-36: 2021 Projected Per-Vehicle Costs for Proposal and Alternatives 3 and 4 by Company (cars & trucks combined, $/vehicle)

Proposal Alt. 3 (cars+20) Alt. 4 (cars-20)

BMW $938 -$216 $2,144 Chrysler/Fiat $696 $271 $1,141

Daimler $1,703 $569 $3,116

Ferrari $6,357 $6,357 $6,357

Ford $696 $241 $1,501 Geely-Volvo $1,741 $663 $3,216

GM $588 $243 $1,040

Honda $557 $293 $994 Hyundai $671 $320 $1,358

Kia $584 $328 $1,068

Mazda $922 $357 $1,960

Mitsubishi $877 $326 $1,803

Nissan $730 $288 $1,470

Porsche $4,484 $3,134 $5,475 Spyker-Saab $2,990 $1,591 $4,821

Subaru $996 $480 $1,908

Suzuki $1,135 $334 $2,130

Tata-JLR $1,933 $1,095 $2,861 Toyota $480 $298 $758

VW $1,459 $188 $2,857

Fleet $734 $292 $1,369

Table III-37 presents the per-vehicle cost estimates in MY2025 by company for the proposal, Alternative 3 and Alternative 4. In ge neral, for most of the companies our projected results show the same trends as for the industry as a whole, with Alternative 3 on the order of $500 to $1,400 per vehicle less expensive then the proposal, and Alternative 4 on the order of $700 to $1,600 per vehicle more expensive. Again these differences are more pronounced for
the car alternatives than the truck alternatives.

Table III-37: 2025 Projected Per-Vehicle Costs for Proposal and Alternatives 3 and 4 by Company (cars & trucks, $/vehicle)

NPRM Alt. 3 (cars+20) Alt. 4 (cars-20)

BMW $2,175 $1,165 $3,429Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 328 of 768 Chrysler/Fiat $2,041 $1,422 $2,756

Daimler $2,709 $1,617 $4,088

Ferrari $7,114 $6,297 $7,114

Ford $2,178 $1,299 $3,215 Geely-Volvo $2,876 $1,790 $4,308

GM $2,028 $1,398 $2,841

Honda $1,595 $1,065 $2,387 Hyundai $1,741 $1,046 $2,773

Kia $1,493 $910 $2,409

Mazda $2,134 $1,231 $3,282

Mitsubishi $2,133 $1,414 $3,050

Nissan $2,061 $1,247 $2,957

Porsche $5,013 $3,687 $6,322 Spyker-Saab $3,673 $2,299 $5,264

Subaru $2,204 $1,402 $3,042

Suzuki $2,228 $1,386 $3,276

Tata-JLR $2,974 $2,244 $3,951 Toyota $1,483 $981 $2,252

VW $2,508 $1,393 $4,003

Fleet $1,946 $1,238 $2,869

Table III-38 shows that in 2021, for several technologies Alternative 3 leads to lower levels of penetration for cars as well as trucks compared to the proposal. For example (on cars) there is an 13% decrease in the 18 bar turbo-charged/downsized engines, a 5% decrease in the penetration of cooled EGR, and a 22% decrease in the penetration of gasoline direct injection fuel systems. We also see that due to credit transfer between cars and trucks, the lower level of stringency considered for cars in alternative 3 also impacts the penetration of technology to the truck fleet – with alternative 3 leading to 12% decrease in penetration of 24 bar turbo-downsized engines, 13% decrease in penetration of cooled EGR, and a 17% decrease in penetration of gasoline direct injection fuel systems in the car fl eet. For the more stringent alternative 4, we see increases in the penetration of many of these technologies projected for 2021, for the truck fleet
as well as for the car fleet. Table III-39 shows these same overall trends but at the sales weighted fleet level in 2021.

Table III-38: 2021 Projected Technology Penetrations for Proposal and Alternatives 3 and 4 for all Cars and Trucks

Technology Cars Trucks Proposal Alt. 3 Alt. 4 Proposal Alt. 3 Alt. 4 Turbo-downsize (18 bar) 45% 32% 51% 59% 55% 62% Turbo-downsize (24 bar) 10% 4% 21% 14% 2% 22%Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 329 of 768 8 speed DCT 61% 46% 61% 13% 11% 13%
Cooled EGR 9% 4% 20% 17% 4% 26% Hybrid Electric Vehicle 8% 5% 12% 4% 3% 9%
LRRT2 62% 43% 72% 74% 54% 74%
IACC2 67% 46% 77% 79% 58% 79%
GDI 60% 38% 82% 76% 59% 91%

Table III-39: 2021 Projected Technology Penetrations for Proposal and Alternatives 3 and 4 for Fleet

Technologies Proposal Alt. 3 Alt. 4 Turbo-downsize (18 bar) 50% 40% 55% Turbo-downsize (24 bar) 11% 3% 21% 8 speed DCT 44% 34% 44%
Cooled EGR 12% 4% 22% Hybrid Electric Vehicle 7% 4% 11%
LRRT2 66% 47% 73%
IACC2 71% 50% 78%
GDI 65% 46% 85%

Table III-40 shows that in 2025, there is only a small change in many of these technology penetration rates when comparing the proposal to alternative 3 for cars, and most of the change shows up in the car fleet. There are a few exceptions: there is a 15% decrease in the penetrate rate of 24bar bmep engines (made up somewhat by a 4% increase in 18bar engines); there is 20% less EGR boost and GDI, and 9% less hybrid electr ic vehicles compared to the proposal. As in 2021, we see that due to credit transfer between cars and trucks at the , the lower level of stringency considered for cars in alternative 3 al so impacts the truck fleet penetration – with alternative 3 leading to 7% decrease in penetratio n of HEVs. For the more stringent alternative 4, we see only small increases in the penetrat ion of many of these technologies projected for 2025, with a major exception being a significant 9% increase in the penetration of HEVs for cars compared to the proposal (along with drop in advanced engines), and a 20% increase in the penetration of HEVs for trucks compared to the proposal.

Table III-40: 2025 Projected Technology Penetrations for Proposal and Alternatives 3 and 4 for all Cars and Trucks

Technologies Cars Trucks Proposal Alt. 3 Alt. 4 Proposal Alt.3 Alt. 4 Turbo-downsize (18 bar) 14% 18% 6% 27% 25% 26%Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 330 of 768 Turbo-downsize (24 bar) 65% 50% 59% 57% 58% 55% 8 speed DCT 75% 76% 71% 15% 16% 14%
Cooled EGR 66% 46% 61% 67% 68% 66% Hybrid Electric Vehicle 15% 6% 24% 13% 6% 33%
EV 4% 1% 9% 1% 0% 2%
LRRT2 96% 96% 96% 99% 98% 99%
IACC2 96% 96% 96% 99% 98% 99%
GDI 93% 73% 88% 97% 94% 97%

Table III-41: 2025 Projected Technology Penetrations for Proposal and Alternatives 3 and 4 for Fleet

Technologies Proposal Alt. 3 Alt. 4 Turbo-downsize (18 bar) 19% 20% 12% Turbo-downsize (24 bar) 62% 53% 58% 8 speed DCT 55% 56% 53%
Cooled EGR 66% 54% 63% Hybrid Electric Vehicle 15% 6% 27%
EV 3% 1% 7%
LRRT2 97% 97% 97%
IACC2 97% 97% 97%
GDI 94% 80% 91%

The trend for Alternatives 3 and 4 have thus far been that the impacts have been more extreme that Alternatives 1 and 2 compared to the proposal. Thus we will focus the discussion of feasibility on Alternatives 1 and 2 (as the same will also then apply to 3 and 4 respectively).

As stated above, EPA’s OMEGA analysis indicat es that there is a technology pathway for
all manufacturers to build vehicles that would meet the proposed standards as well as the
alternative standards. 331 The differences lie in the per-vehicle costs and the associated technology penetrations. With the proposed standards, we estimate that the average per-vehicle cost is $734 in 2021 and $1,946 in 2025. We have also shown that the relative rate of increase in the stringencies of cars and trucks are at an appr opriate level such that there is greater balance amongst the manufacturers where the distribution of the burden is relatively evenly spread. In Section I.C of the Preamble, we also showed that the benefits of the program are significant, and that this cost can be recovered within the first four years of vehicle ownership.

EPA’s analysis of the four alternatives indicates that under all of the alternatives the projected response of the manufacturers is to change both their car and truck fleets. Whether the car or truck standard is being changed, and whether it is being made more or less stringent, the

331 Except Ferrari.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 331 of 768 response of the manufacturers is to make changes across their fleet, in light of their ability to transfer credits between cars and trucks. For example, Alternatives 1 and 3 make either car or trucks standard less stringent, and keep the other standard as is. For both alternatives, manufacturers increase their projected CO 2 g/mile level achieved by their car fleet, and to a
lesser extent their truck fleet. For alternatives 2 a nd 4, where either the truck or car fleet is made more stringent, and the other standard is kept as is, manufacturers reduce the projected CO 2 g/mile level achieved by both their car and trucks fleets, in a generally comp arable fashion. This
is summarized in Table III-42 for MY 2025.

Table III-42: A Comparison of the Achieved CO2 levels in Relation to the Proposed Achieved Levels for all Alternative Scenarios in MY 2025

Alternative Change in car achieved level compared to proposal achieved
level Change in truck achieved level compared to proposal achieved
level
1: truck +20 +8 +6 2: truck -20 -8 -7
3: car +20 +15 +9
4: car -20 -14 -10

This demonstrates that the four alternatives are indicative of what would happen if EPA increased the stringency of both the car and truck fleet at the same time, or decreased the stringency of the car and truck fleet at the same time. E.g., Alternative 4 would be comparable to an alternative where EPA made the car standard more stringent by 14 gm/mi and the truck standard by 10 gm/mile. Under such an alternative, there would logically be little if any net transfer of credits between cars and trucks. In that context, the results from alternatives 1 and 3 can be considered as indicative of what would be expected if EPA decreased the stringency of both the car and truck standards, and alternatives 2 and 4 as indicative of what would happen if EPA increased the stringency of both the car and truck standards. In general, it appears that decreasing the stringency of the standards woul d lead the manufacturers to focus more on increasing the CO 2 gm/mile of cars than trucks (alternatives 1 and 3). Increasing the stringency of the car and truck standards would generally lead to comparable increases in gm/mi for both
cars and trucks.

Alternatives 1 and 3 would achieve significantly lower reductions, and would therefore forego important benefits that the proposed st andards would achieve at reasonable costs and penetrations of technology. EPA judges that there is not a good reason to forego such benefits, and is not proposing less stringent standards such as alternatives 1 and 3.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 332 of 768 Alternatives 2 and 4 increase the per vehicle estimates to $1,077 and $1,369 respectively in 2021 and $2,462 and $2,869 respectively in 2025. This increase in cost from the proposal originates from the dramatic increases in the co stlier electrification technologies, such as HEVs and EVs. The following tables and charts show the technology penetrations by manufacturer in greater detail.

Table III-43 and later tables describe the projected penetration rates for the OEMs of some key technologies in MY 2021 and MY2025 under the proposed standards. TDS27, HEV, and PHEV+EV technologies represent the most costly technologies added in the package generation process, and the OMEGA model generally adds them as one of the last technology choices for compliance. They are therefore an indicator of the extent to which the stringency of the standard is pushing the manufacturers to the most costly technology. Cost (as shown above)
is a similar indicator.

Table III-43 describes technology penetration for MY2021 under the proposal.

Table III-43: Percent Penetration of Technologies in MY 2021 for the Proposed Standards (Ferrari has been removed from this table)

2021 CAR 2021 TRUCK 2021 Fleet

TDS24 TDS27 HEV PHEV
+EV TDS24 TDS27 HEV PHEV
+EV TDS24 TDS27 HEV PHEV
+EV

BMW 26% 2% 30% 2% 24% 3% 30% 0% 25% 2% 30% 1%

Chrysler/Fiat 7% 1% 0% 0% 25% 3% 0% 0% 15% 2% 0% 0%

Daimler 21% 4% 30% 8% 14% 6% 30% 0% 20% 4% 30% 6%

Ford 15% 1% 2% 0% 17% 6% 2% 0% 16% 3% 2% 0%

Geely/Volvo 15% 8% 30% 9% 27% 2% 30% 0% 18% 6% 30% 6%

GM 9% 1% 0% 0% 19% 5% 0% 0% 14% 3% 0% 0%

Honda 0% 0% 3% 0% 0% 0% 0% 0% 0% 0% 2% 0% Hyundai 0% 0% 0% 0% 30% 0% 0% 0% 6% 0% 0% 0%

Kia 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%

Mazda 20% 0% 0% 0% 30% 0% 0% 0% 22% 0% 0% 0%

Mitsubishi 30% 0% 6% 0% 30% 0% 4% 0% 30% 0% 6% 0%

Nissan 9% 0% 1% 0% 24% 3% 0% 0% 14% 1% 1% 0%

Porsche 25% 3% 30% 29% 24% 8% 30% 0% 25% 4% 30% 22%

Spyker/Saab 25% 3% 30% 16% 19% 6% 30% 0% 24% 3% 30% 13%

Subaru 30% 0% 2% 0% 30% 0% 0% 0% 30% 0% 1% 0%

Suzuki 30% 0% 24% 0% 30% 0% 6% 0% 30% 0% 21% 0% Tata/JLR 7% 11% 30% 10% 10% 10% 30% 4% 9% 11% 30% 7%
Toyota 0% 0% 15% 0% 0% 3% 5% 0% 0% 1% 12% 0%

VW 29% 1% 30% 6% 23% 3% 30% 0% 27% 1% 30% 5%Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 333 of 768 Fleet 10% 1% 8% 1% 14% 4% 4% 0% 11% 2% 7% 1% TDS24 = 24 bar bmep Turbo downsized GDI Engines, where most of these are EGR boosted, TDS27 = EGR boosted turbo downsized GDI 24 bar bmep, HEV= Hybrid Electric Vehicle, EV = Electric Vehicle, PHEV = Plug-in Hybrid Electric Vehicle

It can be seen from this table that the larger volume manufacturers have levels of advanced technologies that are below the phase in caps (described in the next table). On the other hand, smaller “luxury” volume manufacturers tend to require higher levels of these technologies. BMW, Daimler, Volvo, Porsche, Saab, Jaguar/LandRover, and VW all reach the maximum penetration cap for HEVs (30%) in 2021. Suzuki is the only other company with greater than 20% penetration of HEVs and only two manufacturers have greater than 10% penetration of PH/EVs: Porsche and Saab. Together these seven “luxury” vehicle manufacturer represent 12% of vehicle sales and their estimated cost of compliance with 2021 proposed standards is $2,178 compared to $744 for the others.

It is important to review some of the caps or limits on the technology phase in rates described in Chapter 3.5.2.3 of the joint TSD as it relates to the remainder of this discussion. These are upper limits on the penetration rates allowed under our modeling, and reflect an estimate of the physical limits for such penetration. It is not a judgment that rates below that cap are practical or reasonable, and is intended to be more of a physical limit of technical capability in light of conditions such as supplier capaci ty, up-front investment capital requirements, manufacturability, and other factors. For example, In MY 2010, there are presently 3% HEVs in the new vehicle fleet. In MYs 2015, 2021 and 2025 we project that this cap on technology penetration rate increases to 15%, 30% and 50% re spectively. For PH/EVs in MY 2010, there is practically none of these technologies. In MYs 2015, 2021 and 2025 we project that this cap on technology penetration rate increases to approximately 5%, 10% and 15% respectively for EVs and PHEVs separately. These highly complex t echnologies also have the slowest penetration phase-in rates to reflect the relatively long lead time required to implement into substantial fractions of the fleet subject to the manufacturers’ product redesign schedules. In contrast, an advanced technology still under de velopment based on an improved engine design, TDS27, has a cap on penetration phase in rate in MYs 2015, 2021, and 2025 of 0%, 15%, and 50% indicative of a longer lead time to develop the technology, but a relatively faster phase in rate once the technology is “ready” (consistent with other “conventional” evolutionary improvements). Table III-44 summarizes the caps on the phase in rates of some of the key technologies. A penetration rate result from the analysis that approaches the caps for these technologies for a given manufacturer is an indication of how much that manufacturer is being “pushed” to technical limits by the standards. This will be in direct correlation to the cost of compliance for that same
manufacturer.

Table III-44: Phase-in Rates for Some Key Advanced Technologies

Technology Abbr. 2016 2021 2025 Turbocharging & downsizing with EGR Level 1 (w/ cooled EGR, 24 bar) EGRB1 or TDS24 15% 30% 75%Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 334 of 768 Turbocharging & downsizing with EGR Level 2 (w/ cooled EGR, 27 bar) EGRB2 or TDS27 0% 15% 50% Strong Hybrid HEV 15% 30% 50% Plug-in Hybrid PHEV 5% 10% 14%

Electric Vehicle EV 1 6% 11% 15%

Table III-45 shows the technology penetrations for Alternative 2. Immediately striking is the penetration rates of truck HEVs in the fleet: even in 2021, it nearly doubles in comparison to the proposal. The Ford truck fleet (to take one of the largest volume manufacturers as an example) increases from 2% HEVs in the proposal trucks to 16% in Alternative 2, an eight fold
increase.

There are other significant increases in the larger manufacturers and even more dramatic increases in the HEV penetration in smaller manufacturers’ fleets. For example, Suzuki cars now reach the maximum technology penetration cap of 30% for HEVs and Mitsubishi now has 20% HEVs. Also, there are now four manufactur ers with total fleet PH/EV penetration rates equal to 10% or greater.

The larger volume manufacturers have an estimated per vehicle cost of compliance with 2021 alternative standards of $1,044, which is $555 higher than the proposed standards. The the seven “luxury” vehicle manufacturers now have estimated costs of $2,733, which is $300 higher than the proposed standards (See Table III -12 above).

Table III-45: Percent Penetration of Technologies in MY 2021 for Alternative 2

2021 CAR 2021 TRUCK 2021 Fleet

TDS24 TDS27 HEV PHEV

+EV TDS24 TDS27 HEV PHEV

+EV TDS24 TDS27 HEV PHEV

+EV

BMW 26% 2% 30% 6% 24% 3% 30% 0% 25% 2% 30% 4%

Chrysler/Fiat 28% 1% 1% 0% 25% 3% 2% 0% 27% 2% 2% 0%

Daimler 21% 4% 30% 12% 14% 6% 30% 0% 20% 4% 30% 9%

Ford 27% 1% 4% 0% 17% 6% 16% 0% 23% 3% 8% 0%

Geely/Volvo 15% 8% 30% 15% 27% 2% 30% 0% 18% 6% 30% 10%

GM 28% 1% 1% 0% 20% 5% 2% 0% 24% 3% 2% 0%

Honda 0% 0% 3% 0% 22% 0% 0% 0% 7% 0% 2% 0% Hyundai 7% 0% 0% 0% 30% 0% 0% 0% 12% 0% 0% 0%

Kia 0% 0% 0% 0% 9% 0% 0% 0% 2% 0% 0% 0%

Mazda 30% 0% 1% 0% 30% 0% 1% 0% 30% 0% 1% 0%

Mitsubishi 30% 0% 25% 0% 30% 0% 11% 1% 30% 0% 20% 0%

Nissan 30% 0% 1% 0% 24% 3% 0% 0% 28% 1% 1% 0%

Porsche 25% 3% 30% 31% 27% 8% 30% 0% 25% 4% 30% 24%Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 335 of 768 Spyker/Saab 25% 3% 30% 19% 19% 6% 30% 0% 24% 3% 30% 16%

Subaru 30% 0% 17% 0% 30% 0% 0% 0% 30% 0% 13% 0%

Suzuki 30% 0% 30% 0% 30% 0% 6% 1% 30% 0% 26% 0% Tata/JLR 7% 11% 30% 13% 10% 10% 30% 11% 9% 11% 30% 12%
Toyota 0% 0% 15% 0% 13% 3% 5% 0% 5% 1% 12% 0%

VW 29% 1% 30% 8% 23% 3% 30% 0% 27% 1% 30% 7%

Fleet 17% 1% 9% 2% 19% 4% 7% 0% 18% 2% 8% 1%

Table III-46 shows the technology penetrations for Alternative 4 for MY 2021. The large volume manufacturer, Ford now has a 25% penetration rate of truck HEVs (a 23% increase compared to the proposed standards) and the fleet penetration has gone up 11 fold for this company in comparison to the proposed standards.

Mitsubishi, and Suzuki cars now reach the maximum technology penetration cap of 30% for HEVs and Mazda, Subaru cars as well as Ford trucks now have greater than 20% HEVs. Also, there are now six manufacturers with PH/EV penetration rates greater than 10%.

The larger volume manufacturers now have an estimated per vehicle cost of compliance with 2021 alternative standards of $1,428, which is $683 higher than the proposed standards. The seven “luxury” vehicle manufacturers now have estimated costs of $3,499, which is $1,320 higher than the proposed standard (See Table III-30 above). For the seven luxury manufacturers, this per vehicle cost exceeds the costs under the proposal for complying with the considerably more stringent 2025 standards.

Table III-46: Percent Penetration of Technologies in MY 2021 for Alternative 4

2021 CAR 2021 TRUCK 2021 Fleet

TDS24 TDS27 HEV PHEV

+EV TDS24 TDS27 HEV PHEV

+EV TDS24 TDS27 HEV PHEV

+EV

BMW 26% 2% 30% 12% 24% 3% 30% 0% 25% 2% 30% 9%

Chrysler/Fiat 28% 1% 1% 0% 25% 3% 2% 0% 27% 2% 2% 0%

Daimler 21% 4% 30% 19% 14% 6% 30% 0% 20% 4% 30% 14%

Ford 27% 1% 14% 0% 17% 6% 25% 1% 23% 3% 18% 0%

Geely/Volvo 15% 8% 30% 21% 27% 2% 30% 0% 18% 6% 30% 15%

GM 28% 1% 0% 0% 20% 5% 2% 0% 24% 3% 1% 0%

Honda 14% 0% 3% 0% 30% 0% 0% 0% 19% 0% 2% 0% Hyundai 30% 0% 3% 0% 30% 0% 3% 0% 30% 0% 3% 0%

Kia 12% 0% 0% 0% 30% 0% 0% 0% 16% 0% 0% 0%

Mazda 30% 0% 26% 1% 30% 0% 11% 1% 30% 0% 23% 1%

Mitsubishi 30% 0% 30% 3% 30% 0% 11% 2% 30% 0% 23% 2%Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 336 of 768 Nissan 30% 0% 14% 0% 24% 3% 13% 0% 28% 1% 14% 0%

Porsche 12% 15% 30% 31% 25% 15% 30% 0% 15% 15% 30% 24%

Spyker/Saab 25% 3% 30% 28% 19% 6% 30% 0% 24% 3% 30% 24%

Subaru 30% 0% 27% 1% 30% 0% 23% 0% 30% 0% 26% 1%

Suzuki 30% 0% 30% 7% 30% 0% 6% 2% 30% 0% 26% 6% Tata/JLR 7% 11% 30% 14% 10% 10% 30% 11% 9% 11% 30% 12%
Toyota 1% 0% 15% 0% 21% 3% 5% 0% 9% 1% 12% 0%

VW 29% 1% 30% 16% 29% 3% 30% 0% 29% 1% 30% 13%

Fleet 21% 1% 12% 3% 22% 4% 9% 0% 21% 2% 11% 2%Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 337 of 768 Table III-47 shows the technology penetrations for the proposed standards in 2025. The larger volume manufacturers have levels of advanced technologies that are below the phase in caps (described in the next table), though there are some notably high penetration rates for truck
HEVs for Ford and Nissan. 332 For the fleet in general, we note a 3% penetration rate of PHEV+EVs – it is interesting to note that this is the penetration rate of HEVs today. EPA
believes that there is sufficient lead time to have this level of penetration of these vehicles by 2025. Case in point, it has taken approximately 10 years for HEV penetration to get to the levels that we see today, and that was without an increase in the stringency of passenger car CAFE
standards.

Table III-47: Percent Penetration of Technologies in MY 2025 for the Proposed Standards

2025 CAR 2025 TRUCK 2025 Fleet

TDS24 TDS27 HEV PHEV

+EV TDS24 TDS27 HEV PHEV

+EV TDS24 TDS27 HEV PHEV

+EV

BMW 56% 5% 28% 10% 61% 10% 50% 0% 58% 6% 34% 8%

Chrysler/Fiat 70% 2% 19% 1% 61% 8% 10% 1% 66% 5% 15% 1%

Daimler 43% 9% 32% 15% 35% 19% 50% 0% 41% 11% 36% 12%

Ford 64% 4% 13% 4% 40% 20% 31% 3% 56% 9% 19% 4% Geely/Volvo 31% 16% 41% 15% 66% 6% 50% 0% 42% 13% 44% 11%

GM 68% 2% 15% 3% 51% 15% 3% 1% 60% 8% 10% 2%

Honda 73% 0% 3% 0% 75% 0% 2% 0% 73% 0% 3% 0% Hyundai 75% 0% 0% 0% 74% 0% 2% 1% 75% 0% 0% 0%

Kia 57% 0% 0% 0% 75% 0% 0% 0% 61% 0% 0% 0%

Mazda 73% 0% 21% 2% 74% 0% 8% 0% 73% 0% 19% 2%

Mitsubishi 69% 0% 21% 6% 71% 0% 9% 4% 70% 0% 17% 5%

Nissan 73% 0% 18% 1% 59% 9% 24% 2% 69% 3% 20% 2%

Porsche 35% 1% 29% 35% 34% 28% 50% 0% 35% 7% 34% 27%

Spyker/Saab 47% 1% 29% 23% 46% 19% 50% 0% 47% 3% 32% 20%

Subaru 70% 0% 20% 5% 74% 0% 19% 1% 71% 0% 19% 4%

Suzuki 66% 0% 25% 9% 72% 0% 5% 3% 67% 0% 22% 8% Tata/JLR 14% 26% 44% 15% 18% 33% 41% 8% 16% 29% 43% 12%
Toyota 61% 1% 17% 0% 59% 8% 7% 0% 60% 4% 13% 0%

VW 60% 1% 26% 13% 58% 11% 50% 0% 60% 3% 31% 11%

Fleet 65% 2% 15% 4% 57% 11% 13% 1% 62% 5% 15% 3%

332 EPA has not conducted an analysis of pickup truck HEV penetration rates compared to the remainder of the truck fleet. This may be conducted for the final rule.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 338 of 768 Six of the seven luxury vehicle manufacturers reach the maximum penetration cap on their truck portion of their fleet, however, no company reaches 50% for their combined fleet. The seven do have over 30% penetration rate of HEVs, while Suzuki is the only company to have between 20 and 30% HEVs. 6 of the 7 luxury vehicle manufacturers also have greater than 10% penetration of PH/EVs (which has a total cap of 29%). The only company to have large penetration rates (>15%) of TDS27 is Jaguar/LandRover at 29%.

The estimated per vehicle cost of compliance with 2025 proposed standards is $1,943 for the larger volume manufacturers and $3,133 for the seven “luxury” vehicle manufacturers.

Table III-48 shows the technology penetrations for Alternative 2 in 2025. In this alternative Chrysler trucks nearly double their penetration rate of HEVs along with dramatic increases in car and truck PH/EVs. GM has a very large increase in truck HEVs as well: from 3% in the proposed to 39% in the alternative standards along with a doubling of PH/EVs. Toyota also has double the number of HEVs. In this alternative there are many more companies with 20-30% HEVs: Chrysler, Ford, GM, Mitsubishi, Nissan, Subaru, Suzuki, and Toyota. Suzuki (in addition to the seven) now also has 10% or greater penetration of PH/EVs. Ford, GM, Chrysler, and Nissan now have more than 20% penetration of HEVs in trucks.

The estimated per vehicle cost of compliance with 2025 alternative 2 standards is $2,354, which is $410 higher than the proposed standards. The seven luxury vehicle manufacturers now have costs of $3,616, which is $483 higher than the proposed standards. See Table III-30 above.

Table III-48: Percent Penetration of Technologies in MY 2025 for Alternative 2

2025 CAR 2025 TRUCK 2025 Fleet

TDS24 TDS27 HEV PHEV
+EV TDS24 TDS27 HEV PHEV
+EV TDS24 TDS27 HEV PHEV
+EV

BMW 52% 4% 28% 15% 61% 10% 50% 0% 55% 6% 34% 11%

Chrysler/Fiat 64% 2% 20% 8% 59% 8% 21% 3% 62% 5% 20% 6%

Daimler 42% 6% 32% 19% 35% 19% 50% 0% 41% 9% 36% 15%

Ford 61% 4% 19% 7% 38% 20% 38% 5% 54% 9% 25% 7% Geely/Volvo 30% 11% 41% 21% 66% 6% 50% 0% 41% 10% 44% 15%

GM 64% 2% 20% 7% 51% 15% 39% 1% 58% 8% 29% 4%

Honda 71% 0% 13% 1% 73% 0% 10% 2% 72% 0% 12% 1% Hyundai 73% 0% 9% 2% 74% 0% 2% 1% 74% 0% 7% 1%

Kia 75% 0% 0% 0% 75% 0% 0% 0% 75% 0% 0% 0%

Mazda 70% 0% 21% 5% 74% 0% 8% 1% 71% 0% 19% 4%

Mitsubishi 64% 0% 25% 11% 71% 0% 9% 4% 66% 0% 20% 9%

Nissan 69% 0% 24% 5% 59% 9% 27% 2% 66% 3% 25% 4%

Porsche 30% 1% 29% 40% 34% 28% 50% 0% 31% 7% 34% 31%Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 339 of 768 Spyker/Saab 45% 1% 29% 25% 46% 19% 50% 0% 45% 3% 32% 22%

Subaru 68% 0% 22% 7% 74% 0% 19% 1% 69% 0% 22% 6%

Suzuki 63% 0% 25% 12% 72% 0% 5% 3% 65% 0% 22% 10% Tata/JLR 14% 22% 44% 19% 10% 33% 41% 15% 13% 27% 43% 18%
Toyota 58% 1% 30% 3% 58% 8% 17% 0% 58% 4% 25% 2%

VW 57% 0% 26% 17% 58% 11% 50% 0% 57% 3% 31% 13%

Fleet 63% 2% 21% 7% 56% 11% 27% 2% 60% 5% 23% 5%

Table III-49 shows the technology penetrations for Alternative 4 in 2025. In this alternative every company except Honda, Hyundai, Kia have greater than 20% HEVs. Many of the large
volume manufacturers have even more dramatic increases in the volumes of P/H/EVs than in Alternative 2. Ford, GM, Nissan, and Toyota have greater than 20 or 30% penetration rates of HEVs on trucks. Mazda, Mitsubishi, Subaru, Suz uki (in addition to the seven) now also have 10% or greater penetration of PH/EVs, while Daimler, Volvo, Porsche, Saab, and VW have over
20%.

The estimated per vehicle cost of compliance with 2025 alternative standards is $2,853, which is $910 higher than the proposed standards. The seven luxury vehicle manufacturers nowhave costs of $4,481, which is $1,348 higher than the proposed standards. Much of this nonlinear increase in cost is due to increased pene tration of PHEVs and EVs (more so than HEVs).

Table III-49: Percent Penetration of Technologies in MY 2025 for Alternative 4

2025 CAR 2025 TRUCK 2025 Fleet

TDS24 TDS27 HEV PHEV

+EV TDS24 TDS27 HEV PHEV

+EV TDS24 TDS27 HEV PHEV

+EV

BMW 48% 1% 28% 23% 61% 10% 50% 0% 51% 3% 34% 17%

Chrysler/Fiat 64% 2% 24% 8% 59% 8% 21% 3% 62% 5% 23% 6%

Daimler 38% 2% 32% 28% 35% 19% 50% 0% 37% 6% 36% 22%

Ford 58% 4% 28% 11% 38% 20% 44% 6% 52% 9% 33% 9% Geely/Volvo 26% 6% 41% 30% 66% 6% 50% 0% 38% 6% 44% 21%

GM 64% 2% 20% 7% 51% 15% 39% 1% 58% 8% 29% 4%

Honda 68% 0% 16% 4% 71% 0% 17% 4% 69% 0% 16% 4% Hyundai 67% 0% 20% 8% 74% 0% 7% 1% 69% 0% 17% 6%

Kia 71% 0% 20% 4% 75% 0% 0% 0% 72% 0% 16% 3%

Mazda 62% 0% 22% 13% 72% 0% 42% 3% 64% 0% 25% 11%

Mitsubishi 61% 0% 25% 14% 70% 0% 25% 5% 64% 0% 25% 11%

Nissan 66% 0% 25% 9% 57% 9% 39% 4% 63% 3% 29% 7%

Porsche 0% 14% 41% 45% 11% 50% 50% 0% 2% 22% 43% 35%

Spyker/Saab 34% 1% 29% 36% 46% 19% 50% 0% 36% 3% 32% 31%Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 340 of 768 Subaru 63% 0% 25% 12% 69% 0% 25% 6% 65% 0% 25% 10%

Suzuki 55% 0% 25% 20% 72% 0% 45% 3% 58% 0% 28% 17% Tata/JLR 14% 20% 44% 21% 10% 33% 41% 15% 13% 26% 43% 18%
Toyota 57% 1% 30% 5% 57% 8% 26% 1% 57% 4% 28% 3%

VW 47% 0% 26% 27% 58% 11% 50% 0% 49% 2% 31% 21%

Fleet 59% 1% 24% 10% 55% 11% 33% 2% 58% 4% 27% 8%

d. Summary of the Technology Penetration Rates and Costs from the Alternative Scenarios in Relation to the Proposed Standards

As described above, alternatives 2 and 4 would lead to significant increases in the penetration of advanced technologies into the flee t during the time frame of these standards. In general, both alternatives would lead to an increase in the average penetration rate for advanced technologies in 2021, in effect accelerating some of the technology penetration that would otherwise occur in the 2022-2025 timeframe. For the fleet as a whole, in 2021 alternative 2 would lead to a significant increase in cooled EG R use and a limited increase in HEV use, while alternative 4 would lead to an even larger in crease in cooled EGR as well as a significant
increase in HEV use. In 2025 these alternatives would dramatically affect penetration rates of HEVs, EVs, and PHEVs, in each case leading to very significant increases on average for the fleet. Again, Alternative 4 would lead to greater penetration rates than Al ternative 2. When one considers the technology penetration rates for in dividual manufacturers, in 2021 the alternatives lead to much higher increases than average for some individual large volume manufacturers. Smaller volume manufacturers start out with higher penetration rates and are pushed to even higher levels. This result is even more pronounced in 2025.

This increase in technology penetration rate s raises serious concer ns about the ability and likelihood manufacturers can smoothly implement the increased technology penetration in a fleet that has so far seen limited usage of these tec hnologies, especially for trucks – and for towing trucks in particular. While this is more pronounced for 2025, there are still concerns for the 2021 technology penetration rates. Although EPA be lieves that these penetration rates are, in the narrow sense, technically achievable, it is more a question of judgment whether we are confident at this time that these increased rates of advanced technology usage can be practically and smoothly implemented into the fleet -- a reason the agencies are attempting to encourage
more utilization of this tech nology with the proposed HEV pickup truck credits but being reasonably prudent in proposing standards that could de facto force high degrees of penetration of this technology on towing trucks. 333

333 See 76 FR at 57220 discussing a similar issue in the context of the standards for heavy duty pickups and vans: “Hybrid electric technology likewise could be applied to heavy-duty vehicles, and in fact has already been so applied on a limited basis. However, the development, design, and tooling effort needed to apply this technology to a vehicle model is quite large, and seems less likely to prove cost-effective in this time frame, due to the small salesSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 341 of 768 EPA notes that the same concerns support the proposed decision to steepen the slope of the truck curve in acknowledgement of the special challenges these larger footprint trucks (which in many instances are towing vehicles) would face. Without the steepening , the penetration rates of these challenging technologies would have been even greater.

From a cost point of view, the impacts on cost track fairly closely with the technology penetration rates discussed above. The average cost increases under Alternatives 2 and 4 are significant for 2021 (approximately $300 and $600), and for some manufacturers they result in very large cost increases. For 2025 the cost increases are even higher (approximately $500 and $900). Alternative 4, as expected, is signifi cantly more costly than alternative 2. From another perspective, the average cost of compliance to the industry on average is $23 and $44 billion for the 2021 and 2025 proposed standards respectively. Alternative 2 will cost the industry on average $7 and $9 billion in excess, while Alternative 4 will cost the industry on average $10 and $16 billion in excess of the costs for the proposed standards. These are large increases in percentage terms, ranging from approximately 25% to 45% in 2021, and from approximately
20% to 35% in 2025.

Per vehicle costs will also increase dramatically including for some of the largest, fullline manufacturers. Under Alternative 2, per vehicle costs for Chrysler, Ford, GM, Honda and Nissan increase by an estimated one-third to nearly double (200%) to meet 2021 standards and from roughly 25% to 45% to meet 2025 sta ndards (see Table III-29 and Table III-30 above). The per-vehicle costs to meet Alternative 4 for th ese manufacturers is significantly greater and in the same proportions, see Table III-36 and Table III-37.

As noted, these cost increases are associated especially with increased utilization of advanced technologies. As shown in Figure below, HEV+PHEV+EV penetration are projected to increase in 2025 from 17% in the proposed standards to 28% and to nearly 35% under Alternatives 2 and 4 respectively for manufacturers with annual sales above 500,000 vehicles (including Chrysler, Ford, GM, Honda, Hyundai, Nissan, Toyota and VW). The differences are less pronounced for 2021, but still (in alterna tive 4) over double the penetration level of the proposal. EPA regards these differences as significant, given the factors of expense, consumer cost, consumer acceptance, and potentially (for 2021) lead time.

Figure 4- HEV + PHEV + EV Penetration for Manufacturers above 500,000 Sales

volumes relative to the light-duty sector. Here again, potential customer acceptan ce would need to be better understood because the smaller engines that facilitate mu ch of a hybrid’s benefit are typically at odds with the importance pickup truck buyers place on engine horsepower and torque, whatever the vehicle’s real performance”.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 342 of 768 The Figure below shows the HEV+PHEV+EV penetration for manufacturers with sales below 500,000 but exceeding 30,000 (including BMW, Daimler, Volvo, Kia, Mazda, Mitsubishi, Porsche, Subaru, Suzuki, and Jaguar/LandRover while excluding Aston Martin, Ferrari, Lotus, Saab, and Tesla). While the penetration rates of these advanced technologies also increase, the distribution within these are shifting to the higher cost EVs and PHEVs as noted above.

Figure 5- HEV + PHEV + EV Penetration for Manufacturers below 500,000 (but above 30,000 Sales) 0% 5% 10% 15% 20% 25% 30% 35% 40%

Proposal Trucks+20 Trucks

‐ 20 Cars+20 Cars

‐ 20

1234HEV+PHEV+EVPenetration MY 2021

MY 2025Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 343 of 768 EPA did not model a number of flexibilities when conducting the analysis for the NPRM. For example, PHEV, EV and fuel cell vehicle incentive multipliers for 2017-2021, full size pickup truck HEV incentive credits, full size pickup truck performance based incentive credits, and off-cycle credits, were not explicitly captured. We plan on modeling these flexibilities for the final rule. For this proposal, while we have not been able to explicitly model the impacts on the program costs, the impact will only be to reduce the estimated costs of the program for most manufacturers. From an industry wide perspectiv e, EPA expects that their overall impact on costs, technology penetration, an d emissions reductions and other be nefits will be limited. They will provide some additional, important flexibility in achieving the proposed levels and promoting more advanced technology, on a case by case basis, but their impact is not expected to be of enough significance to warrant a change to the standards proposed. Instead they are expected to support the reasonableness of the proposed standards.

Overall, EPA believes that the characteristics and impacts of these and other alternative standards generally reflect a continuum in term s of technical feasibility, cost, lead time, consumer impacts, emissions reductions and oil savings, and other factors evaluated under section 202 (a). In determining the appropriate standard to propose in this context, EPA judges that the proposed standards are appropriate and pr eferable to more stringent alternatives based largely on consideration of cost – both to manufacturers and to consumers – and the potential for 0% 5% 10% 15% 20% 25% 30% 35% 40% 45%

Proposal Trucks+20 Trucks

‐ 20 Cars+20 Cars

‐ 20

1234HEV+PHEV+EVPenetration MY 2021

MY 2025Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 344 of 768 overly aggressive penetration rates for advanced technologies relative to the penetration rates seen in the proposed standards, especially in the face of unknown degree of consumer acceptance of both the increased costs and the technologies themselves. At the same time, the proposal helps to address these issues by providing incentives to promote early and broader deployment of advanced technologies, and so provides a means of encouraging their further penetration while leaving manufacturers alternative technology choices. EPA thus judges that the increase in technology penetration rates and the increase in costs under the increased stringency for the car and truck fleets reflected in alternatives 2 and 4 are such that it would not be appropriate to propose standards that would increase the stringency of the car and truck fleets in this manner.

On a year by year basis, EPA believes that the progression of standards are appropriate based on cost projections. The table below shows the year on year costs as described in Chapter 5 of the RIA. These projections show a steady increase in costs from 2017 thru 2025 (as interpolated). [placeholder for expanded year on year discussion]

Table III-50 Costs by Manufacturer by MY– Combined Fleet (2009$)

Company 2017 2018 2019 2020 2021 2022 2023 2024 2025 BMW $217 $417 $564 $716 $938 $1,406 $1,740 $2,054 $2,175 Chrysler/Fiat $194 $311 $398 $494 $696 $1,170 $1,533 $1,886 $2,041 Daimler $352 $721 $1,014 $1,319 $1,703 $2,220 $2,474 $2,700 $2,709 Ferrari $1,693 $3,124 $4,199 $5,284 $6,357 $7,365 $7,486 $7,597 $7,114 Ford $204 $336 $433 $521 $696 $1,201 $1,608 $1,997 $2,178 Geely-Volvo $406 $792 $1,070 $1,358 $1,741 $2,290 $2,579 $2,853 $2,876 GM $189 $287 $360 $428 $588 $1,070 $1,465 $1,842 $2,028 Honda $117 $229 $314 $402 $557 $915 $1,195 $1,467 $1,595 Hyundai $159 $299 $403 $511 $671 $1,056 $1,343 $1,618 $1,741 Kia $136 $245 $335 $430 $584 $905 $1,150 $1,387 $1,493 Mazda $198 $409 $566 $715 $922 $1,372 $1,693 $2,009 $2,134 Mitsubishi $153 $350 $487 $634 $877 $1,341 $1,680 $2,002 $2,133 Nissan $209 $356 $467 $575 $730 $1,197 $1,559 $1,904 $2,061 Porsche $1,113 $2,123 $2,871 $3,637 $4,484 $5,256 $5,317 $5,373 $5,013 Spyker-Saab $815 $1,476 $1,966 $2,462 $2,990 $3,578 $3,718 $3,849 $3,673 Subaru $238 $456 $613 $773 $996 $1,465 $1,785 $2,092 $2,204 Suzuki $300 $544 $722 $903 $1,135 $1,587 $1,877 $2,149 $2,228 Tata-JLR $242 $691 $1,005 $1,353 $1,933 $2,485 $2,744 $2,987 $2,974 Toyota $128 $217 $283 $342 $480 $812 $1,089 $1,352 $1,483 Volkswagen $377 $691 $930 $1,172 $1,459 $1,941 $2,213 $2,468 $2,508 Fleet $203 $343 $448 $552 $734 $1,169 $1,497 $1,809 $1,946

Table III-51 Industry Average Vehicle Costs Associated with the Proposed Standards (2009$)

Model Year 2017 2018 2019 2020 2021 2022 2023 2024 2025

$/car $172 $319 $463 $591 $723 $1,051 $1,357 $1,658 $1,947 $/truck $49 $180 $292 $407 $753 $1,068 $1,373 $1,670 $1,944 Combined $126 $268 $402 $527 $734 $1,057 $1,362 $1,662 $1,946Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 345 of 768 E. Certification, Compliance, and Enforcement

1. Compliance Program Overview

This section summarizes EPA's comprehensiv e program to ensure compliance with emission standards for carbon dioxide (CO 2 ), nitrous oxide (N 2 O), and methane (CH 4 ), as
described in Section III.B. An effective co mpliance program is essential to achieving the environmental and public health benefits promised by these mobile source GHG standards. EPA's GHG compliance program is designed aro und two overarching priorities: 1) to address Clean Air Act (CAA) requirements and policy obj ectives; and 2) to streamline the compliance process for both manufacturers and EPA by building on existing practice wherever possible, and by structuring the program such that manufacturer s can use a single data set to satisfy both GHG and Corporate Average Fuel Economy (CAFE) testing and reporting requirements. The EPA and NHTSA programs replicate the compliance protocols established in the MY 2012-2016
rule. 334 The certification, testing, reporting, an d associated compliance activities track current practices and are thus familiar to manufacturers. As is the case under the 2012-2016 program, EPA and NHTSA have designed a coordinated compliance approach for 2017-2025 such that the compliance mechanisms for both GHG and CAFE st andards are consistent and non-duplicative. Readers are encouraged to review the MY 2012-2016 final rule for background and a detailed description of these certification, compliance, and enforcement requirements.

Vehicle emission standards established under the CAA apply throughout a vehicle's full useful life. Today’s rule establishes fleet average greenhouse gas standards where compliance with the fleet average is determined based on the testing performed at time of production, as with the current CAFE fleet average. EPA is also establishing in-use standards that apply throughout a vehicle’s useful life, with the in-use standard determined by adding an adjustment factor to the
emission results used to calculate the fleet av erage. EPA’s program will thus not only assess compliance with the fleet average standards described in Section III.B, but will also assess compliance with the in-use standards. As it does now, EPA will use a variety of compliancemechanisms to conduct these assessments, including pre-production certification and postproduction, in-use monitoring once vehicles enter customer service. Under this compliance program manufacturers will also be afforded numerous flexib ilities to help achieve compliance, both stemming from the program design itself in the form of a manufacturer-specific CO 2 fleet average standard, as well as in various credit banking and trading opportunities, as described in Section III.C. The compliance program is summarized in further detail below.

334 75 FR 25468Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 346 of 768 2. Compliance with Fleet-Average CO 2 Standards

Fleet average emission levels can only be determined when a complete fleet profile
becomes available at the close of the model year. Therefore, EPA w ill determine compliance with the fleet average CO 2 standards when the model year closes out, based on actual production figures for each model and on model-level emissions data collected through testing over the course of the model year. Manufacturers will subm it this information to EPA in an end-of-year report which is discussed in detail in Section III.E.5.h of the MY 2012-2016 final rule preamble (see 75 FR 25481).

a. Compliance Determinations

As described in Section III.B above, the flee t average standards will be determined on a manufacturer by manufacturer basis, separately for cars and trucks, using the footprint attribute curves. EPA will calculate the fleet average em ission level using actual production figures and, for each model type, CO 2 emission test values generated at the time of a manufacturer's CAFE testing. EPA will then compare the actual fleet av erage to the manu facturer's footprint standard to determine compliance, taki ng into consideration use of averaging and credits.

Final determination of compliance with fleet average CO 2 standards may not occur until several years after the close of the model year due to the flexib ilities of carry-forward and carryback credits and the remediation of deficits (s ee Section III.B). A failure to meet the fleet average standard after credit opportunities have been exhauste d could ultimately result in penalties and injunctive orders under the CAA as described in Section III.E.6 below.

b. Required Minimum Testing For Fleet Average CO 2

EPA will require and use the same test data to determine a manufacturer’s compliance with both the CAFE standard and the fleet average CO 2 emissions standard. Please see Section III.E.2.b of the MY 2012-2016 final rule preamble (75 FR 25469) for details.

3. Vehicle Certification

CAA section 203(a)(1) prohibits manufacturers from introducing a new motor vehicle into commerce unless the vehicle is covered by an EPA-issued certificate of conformity. Section 206(a)(1) of the CAA describes the requirements fo r EPA issuance of a certificate of conformity, based on a demonstration of compliance with th e emission standards established by EPA under section 202 of the Act. The certification demonstration requires emission testing, and must be done for each model year. 335

335 CAA section 206(a)(1).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 347 of 768 Since compliance with a fleet average standard depends on actual production volumes, it is not possible to determine compliance with th e fleet average at the time the manufacturer applies for and receives a certificate of conformity for a test group. Instead, EPA will continue to condition each certificate of conformity for the GHG program upon a manufacturer's demonstration of compliance with the manufacturer’s fleet-wide average CO 2 standard. Please see Section III.E.3 of the MY 2012-2016 final rule preamble (75 FR 25470) for a discussion of how EPA will certify vehicles under the GHG standards.

4. Useful Life Compliance

Section 202(a)(1) of the CAA requires emission standards to apply to vehicles throughout their statutory useful life, as further described in Section III.A. The in-use CO 2 standard under the greenhouse gas program would apply to indivi dual vehicles and is separate from the fleetaverage standard. The in-use CO2 standard for each model would be the model specific CO2 level used in calculating the fleet average, adjusted to be 10% higher to account for test-to-test and production variability that might affect in-use test results . Please see Section III.E.4 of the MY 2012-2016 final rule preamble (75 FR 25473 for a detailed discussion of the in-use standard, in-use testing requirements, and deterioration factors for CO2, N2O, and CH4.

5. Credit Program Implementation

As described in Section III.C, several credit programs are available under this rulemaking. Please see Section III.E.5 of the MY 2012-2016 final rule preamble (75 FR 25477) for a detailed explanation of credit program implementation, sample credit and deficit calculations, and end-of-year reporting requirements.

6. Enforcement

The enforcement structure EPA promulgated under the MY 2012-2016 rulemaking remains in place. Please see Section III.E.6 of the MY 2012-2016 final rule preamble (75 FR 25482) for a discussion of these provisions.

Prohibited Acts in the CAA

Section 203 of the Clean Air Act describes acts that are prohibited by law. This section and associated regulations apply equally to the greenhouse gas standards as to any other regulated emission. Acts that are prohibited by section 203 of the Clean Air Act include the introduction into commerce or the sale of a vehicle without a certificate of conformity, removing or otherwise defeating emission control equipment, the sale or installation of devices designed to defeat emission controls, and other actions. This proposal includes a section that details these prohibited acts, as did the 2012 greenhouse gas regulations.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 348 of 768 7. Other Certification Issues

a. Carryover/Carry Across Certification Test Data

EPA's certification program for vehicles allows manufacturers to carry certification test data over and across certification testing from one model year to the next, when no significant changes to models are made. EPA would continue to apply this policy to CO 2 , N 2 O and CH 4 certification test data and would allow manufacturers to use carryover and carry across data to
demonstrate CO 2 fleet average compliance if they have done so for CAFE purposes.

b. Compliance Fees

The CAA allows EPA to collect fees to cover the costs of issuing certificates of conformity for the classes of vehicles covered by this rule.

At this time the extent of any added costs to EPA as a result of this rule is not known. EPA will assess its compliance testing and other activities associated with the rule and may amend its fees regulations in the future to include any warr anted new costs.

c. Small Entity Exemption

EPA would exempt small entities, and these en tities (necessarily) would not be subject to the certification requirements of this rule.

As discussed in Section III.B.7, businesses meeting the Small Business Administration (SBA) criterion of a small business as described in 13 CFR 121.201 would not be subject to the GHG requirements, pending future regulatory action. Small entities are currently covered by a number of EPA motor vehicle emission regulations, and they routinely submit information and data on an annual basis as part of their compliance responsibilities.

As discussed in detail in Section III.B.5, small volume manufacturers with annual sales volumes of less than 5,000 vehicles would be required to meet primary GHG standards or to petition the Agency for alternative standards

d. Onboard Diagnostics (OBD) and CO 2 Regulations

As under the current program, EPA would not require CO 2 , N 2 O, and CH 4 emissions as one of the applicable standards required for the OBD monitoring threshold.

e. Applicability of Current High Altitu de Provisions to Greenhouse Gases

As under the current program, vehicles covered by this rule would be required to meet the

CO 2 , N 2 O and CH 4 standard at altitude but would not normally be required to submit vehicleSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 349 of 768 CO 2 test data for high altitude. Instead, they would submit an engineering evaluation indicating that common calibration approaches will be utilized at high altitude..

f. Applicability of Standards to Aftermarket Conversions

With the exception of the small entity and small business exemptions, EPA’s emission standards, including greenhouse gas standards, will continue to apply as stated in the applicability sections of the relevant regulations . EPA expects that some aftermarket conversion companies will qualify for and seek the small enti ty and/or small busine ss exemption, but those that do not qualify will be required to meet th e applicable emission st andards, including the greenhouse gas standards to qualify for a tampering exemption under 40 CFR subpart F. Fleet average standards are not generally appropriate for fuel conversion manufacturers because the “fleet” of vehicles to which a conversion system may be applied has already been accounted for under the OEM’s fleet average standard. Therefore, EPA is proposing to retain the process promulgated in 40 CFR subpart F anti-tampering regulations whereby conversion manufacturers demonstrate compliance at the vehicle rather than th e fleet level. Fuel converters will continue to show compliance with greenhouse gas standards by submitting data to demonstrate that the conversion EDV N2O, CH4 and CREE results are less than or equal to the OEM’s in-use standard for that subconfiguration.. EPA is also proposing to continue to allow conversion manufacturers, on a test group basis, to convert CO2 overcompliance into CO2 equivalents of
N20 and/or CH4 that can be subtracted from th e CH4 and N20 measured values to demonstrate compliance with CH4 and/or N20 standards.

g. Geographical Location of Gree nhouse Gas Fleet Vehicles

EPA emission certification regulati ons require emission compliance 336 in the 50 states, the District of Columbia, the Puerto Rico, the Virgin Islands, Guam, American Samoa and the
Commonwealth of the Northern Mariana Islands.

8. Warranty, Defect Reporting, and Other Emission-related Components Provisions

This rulemaking would retain warranty, defect reporting, and other emission-related component provisions promulgated in the MY 2012-2016 rulemaking. Please see Section III.E.10 of the MY 2012-2016 final rule preamb le (75 FR 25486) for a discussion of these provisions.

336 Section 216 of the Clean Air Act defines the term co mmerce to mean “(A) comm erce between any place in any State and any place outside thereof; and (B) commer ce wholly within the District of Columbia.” Section 302(d) of the Clean Air Act reads “The term `` State'' means a State, the District of Columbia, the Commonwealth of Puerto Rico, the Vi rgin Islands, Guam, and American Samoa and includes the Commonwealth of the Northern Mariana Islands.” In addition, 40 CFR 85.1 502 (14) regarding the importation of motor vehicles and motor vehicle engines defines the United States to include “the States, the District of Columbia, the Commonwealth of Puerto Rico, the Commonwealth of the Northern Marian a Islands, Guam, American Samoa, and the U.S. Virgin Islands.”Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 350 of 768 9. Miscellaneous Technical Amendments and Corrections

EPA is proposing a number of noncontroversial amendments and corrections to the existing regulations. Because the regulatory provisions for the EPA greenhouse gas program, NHTSA’s CAFE program, and the joint fuel economy and environment labeling program are all intertwined in 40 CFR Part 600, this proposed rule presents an opportunity to make correctionsand clarifications to all or any of these programs. Consequently, a number of minor and nonsubstantive corrections are being proposed to the regulations that implement these programs.

We are also proposing a solution to a situation in which a manufacturer of a clean alternative fuel conversion is attempting to co mply with the fuel conversion regulations (see 40 CFR Part 85 subpart F) at a point in time before which certain data is available from the original
manufacturer of the vehicle. Clean alternative fuel conversions are subject to greenhouse gas standards if the vehicle as originally manufactured was subject to greenhouse gas standards, unless the conversion manufacturer qualifies for exemption as a small business. Compliance with light-duty vehicle greenhouse gas emission standards is demonstrated by complying with
the N2O and CH4 standards and the in-use CO2 exhaust emission standard set forth in 40 CFR 86.1818–12(d) as determined by the original manufacturer for the subconfiguration that is
identical to the fuel conversion emission data vehicle (EDV). However, the subconfiguration data may not be available to the fuel conversion manufacturer at the time they are seeking EPA certification. Several compliance options are currently provided to fuel conversion
manufacturers that are consistent with the co mpliance options for the original equipment manufacturers. EPA is proposing to add another optio n that would be applicable starting with the 2012 model year. The new option would allow clean alternative fuel conversion manufacturers to satisfy the greenhouse gas standards if the sum of CH4 plus N2O plus CREE emissions from the vehicle pre-conversion is less than the sum post-conversion, adjusting for the global warming potential of the constituents.

F. How Would This Proposal Reduce GHG Emissions and Their Associated Effects?

This action is an important step towards curbing growth of GHG emissions from cars and light trucks. In the absence of control, GHG emissions worldwide and in the U.S. are projected to continue steady growth. Tabl e III-52 shows emissions of CO 2 , methane (CH 4 ), nitrous oxide (N 2 O) and air conditioning refrigerant (HFC-134a) on a CO 2 -equivalent basis for calendar years 2010, 2020, 2030, 2040 and 2050. As shown below, U.S. GHGs are estimated to make up roughly 15 percent of total worldwide emissions in 2010. Further, the contribution of direct emissions from cars and light-trucks to this U.S. share reaches an estimated 17 percent of U.S. emissions by 2030 in the absence of control. As disc ussed later in this section, this steady rise in GHG emissions is associated with numerous adverse impacts on human health, food and agriculture, air quality, and water and forestry resources.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 351 of 768 Table III-52 GHG Emissions by Calendar Year without the Proposed Standards (MMTCO 2 eq) 337

2010 2020 2030 2040 2050

All Sectors (Worldwide) a 45,000 53,000 61,000 69,000 76,000

All Sectors (U.S. Only) b 6,800 7,300 7,600 8,000 8,100

U.S. Cars/Light Truck Only c 1,300 1,300 1,300 1,500 1,700

a GCAM model 338

b ADAGE model, 339

c OMEGA model, Tailpipe CO 2 and HFC134a only (includes impacts of MYs 2012-2016 rule)

This rule will result in significant reductions as newer, cleaner vehicles come into the fleet. As discussed in Section I, this GHG rule is part of a joint National Program such that a large part of the projected benefits, but by no means all, would be achieved jointly with NHTSA’s CAFE standards, which are described in detail in Section IV. EPA estimates the reductions attributable to the GHG program over time assuming the model year 2025 standards continue indefinitely post-2025, compared to a reference scenario in which the 2016 model year GHG standards continue indefinitely beyond 2016.

EPA estimated greenhouse impacts from several sources including: (a) the impact of the standards on tailpipe CO 2 emissions, (b) projected improvements in the efficiency of vehicle air conditioning systems, 340 (c) reductions in direct emissions of the refrigerant and potent greenhouse gas HFC-134a from air conditioning systems, (d) “upstream” emission reductions from gasoline extraction, production and distribution processes as a result of reduced gasoline demand associated with this rule, and (e) “upstream” emission increases from power plants as electric powertrain vehicles incr ease in prevalence as a result of this rule. EPA additionally accounted for the greenhouse gas impacts of additi onal vehicle miles travelled (VMT) due to the "rebound" effect discussed in Section III.H.

Using this approach EPA estimates the proposed standards would cut annual fleetwide car and light truck tailpipe CO 2 emissions by approximately 230 MMT or 18 percent by 2030, when 85 percent of car and light truck miles will be travelled by vehicl es meeting the MY 2017 or later standards. An additional 65 MMTCO 2 eq of reduced emissions are attributable to reductions in gasoline production, distribution and transport. 10 MMTCO 2 eq of additional

337 ADAGE and GCAM model projections of worldwide and U.S. GHG emissions are provided for context only. The baseline data in these models differ in certain a ssumptions from the baseline used in this proposal. For example, the ADAGE baseline is calibrated to AEO 2010, which includes the EISA 35 MPG by 2020 provision, but does not explicitly include the MYs 2012-2016 rule. All em issions data were rounded to two significant digits.

338 Based on the Representative Concentratio n Pathway scenario in GCAM available at www.globalchange.umd.edu/gcamrcp . See section III.F.3 and DRIA Chapter 6.4 for additional information on GCAM.

339 Based on the ADAGE reference case used in U.S. EPA (2010). “EPA Analysis of the American Power Act of 2010” U.S. Environmental Protection Agency, Washington, DC, USA (www.epa.gov/climatechange/economics/economicanalyses.html).

340 While EPA anticipates that the majority of mobile air conditioning systems will be improved in response to the MY 2012-2016 rulemaking, the agency expects that the remainder will be improved as a result of this action.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 352 of 768 emissions will be attributable to increased electri city production. In total, EPA estimates that compared to a baseline of indefinite 2016 model year standards, net GHG emission reductions from the program would be approximately 310 million metric tons CO 2 -equivalent (MMTCO 2 eq) annually by 2030, which represents a reduction of 4% percent of total U.S. GHG emissions and 0.5% percent of total worldwide GHG emissions projected in that year. These GHG savings correspond to approximately 26 billion gallons of petroleum-based gasoline.

EPA projects the total reduction of the program over the full life of model year 2017- 2025 vehicles to be about 2,060 MMTCO 2 eq, with fuel savings of 170 billion gallons (4.0 billion barrels) of gasoline over the life of these vehicles.

The impacts on atmospheric CO 2 concentrations, global mean surface temperature, sea level rise, and ocean pH resulting from these emission reductions are discussed in Section III.F.3.

1. Impact on GHG Emissions

The modeling of fuel savings and greenhouse gas emissions is substantially similar to that which was conducted in the 2012-2016 Final Rulemaking and the MY 2017-2025 Interim Joint Technical Assessment Report (TAR). As detailed in Draft RIA chapter 4, EPA estimated calendar year tailpipe CO 2 reductions based on pre- and post-control CO 2 gram per mile levels from EPA’s OMEGA model, coupled with VM T projections derived from AEO 2011 Final Release. These estimates reflect the real-world CO 2 emissions reductions projected for the entire U.S. vehicle fleet in a specified calendar year. EPA also estimated full lifetime reductions for model years 2017-2025 using pre- and post-control CO 2 levels projected by the OMEGA model, coupled with projected vehicle sales and lifetime m ileage estimates. These estimates reflect the real-world CO 2 emissions reductions projected for model years 2017 through 2025 vehicles over their entire life. Upstream impacts from power plant emissions came from OMEGA estimates of EV/penetration into the fleet (approximately 3%). For both calendar year and model year assessments, EPA estimated the environmental impact of the advanced technology multiplier, pickup truck hybrid electric vehicle (HEV) and performance based incentives and air conditioning credits. The impact of the off-cycle credits were not explicitly estimated, as these credits are assumed to be inherently environmentally neutral (Section XX). EPA also did not assess the impact of the credit banking carry-forward programs.

As in the MY 2012-2016 rulemaking, this proposal allows manufacturers to earn credits for improvements to controls for both direct and indirect AC emissions.. Since these improvements are relatively low cost, EPA again projects that manufacturers will take advantage of this flexibility, leading to reductions from emissions associated with vehicle air conditioning systems. As explained above, these reductions will come from both direct emissions of air conditioning refrigerant over the life of the vehicle and tailpipe CO 2 emissions produced by the increased load of the A/C system on the engine . In particular, EPA estimates that direct emissions of HFC-134a, one of the most potent greenhouse gases, would be fully removed from light-duty vehicles through the phase-in of al ternative refrigerants. More efficient air conditioning systems would also lead to fuel savings and additional reductions in upstreamSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 353 of 768 emissions from fuel production and distribution. Our estimated reductions from the A/C credit program assume that manufacturers will fu lly utilize the program by MY 2021.

Upstream greenhouse gas emission reductio ns associated with the production and distribution of fuel were estimated using emis sion factors from DOE’s GREET1.8 model, with modifications as detailed in Chapter 5 of the DR IA. These estimates incl ude both international and domestic emission reductions, since reductions in foreign exports of finished gasoline and/or crude would make up a significant share of the fu el savings resulting from the GHG standards. Thus, significant portions of the upstream GHG emission reductions will occur outside of the U.S.; a breakdown of projected international versus domestic reductions is included in the DRIA.

Electricity emission factors were derived from EPA’s Integrated Planning Model (IPM). EPA uses IPM to analyze the projected impact of environmental policies on the electric power sector in the 48 contiguous states and the District of Columbia. IPM is a multi-regional, dynamic, deterministic linear programming model of the U.S. electric power sector. It provides forecasts of least-cost capacity expansion, electricity dispatch, and emission control strategies for meeting energy demand and environmental, transmission, dispatch, and reliability constraints. EPA derived average national CO 2 emission factors from the IPM version 4.10 base case run for the “Proposed Transport Rule. 341 ” As discussed in Draft TSD Chapter 4, for the Final Rulemaking, EPA may consider emission factors other than national power generation, such as marginal power emission factors, or regional emission factors.

a. Calendar Year Reductions for Future Years

Table III-53 shows reductions estimated from these GHG standards assuming a precontrol case of 2016 MY standards continuing indefinitely beyond 2016, and a post-control case in which 2025 MY GHG standards continue indefinitely beyond 2025. These reductions are broken down by upstream and downstream components, including air conditioning improvements, and also account for the offset from a 10 percent VMT “rebound” effect as discussed in Section III.H. Including the reductions from upstream emissions, total reductions are estimated to reach 307 MMTCO 2 eq annually by 2030, and grow to over 580 MMTCO 2 eq in 2050 as cleaner vehicles continue to come into the fleet.

341 EPA. IPM. http://www.epa.gov/airmarkt/progsre gs/epa-ipm/BaseCasev410.html . "Proposed Transport Rule/NODA version" of IPM . TR_SB_Limited Trading v.4.10Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 354 of 768 Table III-53 Projected GHG Deltas (MMTCO 2 eq per year)

Calendar Year: 2020 2030 2040 2050

Net Delta * -28 -306 -486 -580

Net CO 2 -24 -276 -442 -529

Net other GHG -4 -30 -44 -52

Downstream -23 -255 -407 -487

CO 2 (excluding A/C) -19 -230 -372 -446

A/C – indirect CO 2 -1 -3 -5 -5

A/C – direct HFCs -4 -22 -31 -36

CH 4 (rebound effect) 0 0 0 0

N

2 O (rebound effect) 0 0 0 0

Gasoline Upstream -6 -65 -105 -126

CO 2 -5 -57 -92 -110

CH 4 -1 -8 -13 -16

N

2 O 0 0 0 -1

Electricity Upstream 1 15 27 32

CO 2 1 15 26 32

CH 4 0 0 0 0

N

2 O 0 0 0 0
* includes impacts of 10% VMT rebound rate presented in Table III-55

The total program emission reductions yield significant emission decreases relative to worldwide and national total emissions.

Table III-54 Projected GHG Deltas (MMTCO 2 eq per year)

Emission Reduction Relative to: 2020 2030 2040 2050

Worldwide reference -0.1% -0.5% -0.7% -0.8%

U.S. reference (all sectors) -0.4% -4.0% -6.1% -7.2%

U.S. reference (cars + light trucks )* -2.2% -23.5% -32.4% -34.1%

*Note that total emission reductions include sectors (such as fuel refineries) that are not part of this reference.

b. Lifetime Reductions for 2017-2025 Model YearsSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 355 of 768 EPA also analyzed the emission reductions over the full life of the 2017-2025 model year cars and light trucks that would be affected by this program. 342 These results, including both upstream and downstream GHG contributions, are presented in Table III-55, showing lifetime reductions of about 2,065 MMTCO 2 eq.

Table III-55 Projected Net GHG Deltas (MMTCO 2 eq per year)

MY Downstream Upstream (Gasoline) Electricity Total CO2e
2017 -25 -6 1 -31
2018 -62 -15 2 -75
2019 -95 -22 3 -115
2020 -132 -31 4 -160
2021 -191 -46 5 -233
2022 -239 -59 9 -289
2023 -282 -71 13 -340
2024 -327 -84 18 -392
2025 -372 -96 23 -445
Total -1,725 -432 78 -2,079

c. Impacts of VMT Rebound Effect

As noted above and discussed more fully in Sect ion III.H., the effect of a decrease in fuel cost per mile on vehicle use (VMT “rebound”) was accounted for in our assessment of economic and environmental impacts of this proposed rule. A 10 percent rebound case was used for this analysis, meaning that VMT for affected model years is modeled as increasing by 10 percent as much as the decrease in fuel cost per mile; i.e., a 10 percent decrease in fuel cost per mile from our proposed standards would result in a 1 percent increase in VMT. Results are shown in Table Table III-56; using the 10 percent rebound rate results in an overall emission increase of 29
MMTCO 2 eq annually in 2030 (this increase is accounted for in the reductions presented in Table III-53 and Table III-54).

Table III-56 Delta GHG Impa ct Of 10% VMT Rebound a

( MMTCO 2 eq per year )

CY Downstream Upstream Gasoline Electricity 343 Total CO2e

2020 3 1 0 4

342 As detailed in DRIA Chapter 4 and TSD Chapter 4, for th is analysis the full life of the vehicle is represented by average lifetime mileages for cars (201,000 miles [MY 2017] and 213,000 miles [MY 2025] ) and trucks (240,000 miles [MY 2017] and 255,000 miles [MY 2025]). These estimat es are a function of how far vehicles are driven per year and scrappage rates.

343 This assessment assumes that owners of grid-electric pow ered vehicles react similarly to changes in the cost of driving as owners of conventional gasoline vehicles. We seek comment on this approach in Section III.H.4c.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 356 of 768 2030 22 6 1 29

2040 34 10 1 45

2050 45 12 1 58

a These impacts are included in the reductions shown in Table III-53 and Table III-54.

d. Analysis of Alternatives

EPA analyzed four alternative scenarios for this proposal (Table III-57). EPA assumed that manufacturers would use air conditioning improvements and the HEV and performance based pickup incentives in identical penetrations as in the primary scenario. EPA re-estimated the impact of the electric vehicle multiplier unde r each alternative. Under these assumptions, EPA expects achieved fleetwide average emission levels of 150 g/mile CO 2 to 177 g/mile CO 2 eq(6%) in 2025. As in the primary scenario, EPA assumed that the fleet complied with the standards. For full details on modeling assumptions, please refer to DRIA Chapter 4. EPA’s assessment of these alternative stan dards is discussed in Section III.D.6

Table III-57 GHG g/mile Targets of Alternative Scenarios

2021 CO 2 g/mile Targets 2025 CO 2 g/mile Targets

Title Cars Trucks Fleet Cars Trucks Fleet Primary 173 250 200 144 203 164
A - Cars +20 g/mile 193 250 213 164 203 177
B - Cars -20 g/mile 153 250 187 124 203 150
C - Trucks +20 g/mile 173 270 207 144 223 170
D - Trucks -20 g/mile 173 230 193 144 183 157

Table III-58 Calendar Year Impacts of Alternative Scenarios

GHG Delta (MMT2 CO2eq) Fuel Savings (B. Gallons petroleum gasoline)

Scenario 2020 2030 2040 2050 2020 2030 2040 2050 Primary -28 -306 -486 -580 -2.2 -26.3 -42.4 -50.7
A - Cars +20 g/mile -19 -255 -417 -500 -1.4 -21.0 -34.8 -41.7
B - Cars -20 g/mile -35 -345 -536 -639 -2.9 -31.7 -50.3 -60.0
C - Trucks +20 g/mile -28 -283 -453 -541 -2.2 -23.7 -38.4 -45.9
D - Trucks -20 g/mile -38 -332 -517 -617 -3.1 -29.4 -46.6 -55.7

Table III-59 Model Year Lifetime Impacts of Alternative Scenarios (Summary of MY 2017-MY2025)Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 357 of 768 Total CO2e Fuel Delta (b gal petroleum gasoline) Fuel Delta (b. barrels petroleum gasoline)

Primary -2,079 - 174 -4.1
A - Cars +20 g/mile -1,657 -132 -3.2
B - Cars -20 g/mile -2,409 -213 -5.1
C - Trucks +20 g/mile -1,888 -154 -3.7
D - Trucks -20 g/mile -2,382 -205 -4.9

2. Climate Change Impacts from GHG Emissions

The impact of GHG emissions on the climate has been reviewed in the 2012-2016 lightduty rulemaking and recent heavy-duty GHG rulemaking. See 75 FR at 25491; 76 FR at 57294. This section briefly discusses again some of the climate impact context for transportation emissions. These previous discu ssions noted that once emitted, GHGs that are the subject of this regulation can remain in the atmosphere for decades to millenia, meaning that 1) their concentrations become well-mixed throughout the global atmosphere regardless of emission origin, and 2) their effects on climate are long lasting. GHG emissions come mainly from the combustion of fossil fuels (coal, oi l, and gas), with additional contributions from the clearing of forests, agricultural activities, cement production, and some industrial activities. Transportation activities, in aggregate, were the second larges t contributor to total U.S. GHG emissions in 2009 (27 percent of total emissions). 344

The Administrator relied on thorough and peer-reviewed assessments of climate change science prepared by the Intergovernmental Panel on Climate Change (“IPCC”), the United States Global Change Research Program (“USGCRP”), and the National Research Council of the National Academies (“NRC”) 345 as the primary scientific and technical basis for the Endangerment and Cause or Contribute Finding s for Greenhouse Gases Under Section 202(a) of the Clean Air Act (74 FR 66496, December 15, 2009). These assessments comprehensively
address the scientific issues the Administrato r had to examine, providing her both data and information on a wide range of issues pert inent to the Endangerment Finding. These assessments have been rigorously reviewed by the expert community, and also by United States government agencies and scientists, including by EPA itself.

Based on these assessments, the Administrator determined, in essence, that greenhouse gases cause warming; that levels of greenhouse gases are increasing in the atmosphere due to human activity; the climate is warming; recent warming has been attributed to the increase in

344 U.S. EPA (2011) Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2009. EPA 430-R-11-005.

345 For a complete list of core references from IPCC, USGCRP/CCSP, NRC and others relied upon for development of the TSD for EPA’s Endangerment and Cause or Contribut e Findings see section 1(b), specifically, Table 1.1 of the TSD. Docket: EPA-HQ-OAR-2009-0171-11645.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 358 of 768 greenhouse gases; and that warming of the climate threatens human health and welfare. The Administrator further found that emissions of well-mixed greenhouse gases from new motor vehicles and engines contribute to the air po llution for which the endangerment finding was made. Specifically, the Administrator found unde r section 202 (a) of the Act that six greenhouse gases (carbon dioxide, methane, nitrous oxide, hydrofluorocarbons, perfluorocarbons, and sulfur hexafluoride) taken in combination endanger both the public health and the public welfare of current and future generations, and further found that the combined emissions of these greenhouse gases from new motor vehicles and engines contribute to the greenhouse gas air pollution that endangers public health and welfare.

More recent assessments have produced similar conclusions to those of the assessments upon which the Administrator relied. In May 2010, the NRC published its comprehensive assessment, “Advancing the Science of Climate Change.” 346 It concluded that “climate change is occurring, is caused largely by human activities, and poses significant risks for—and in many cases is already affecting—a broad range of human and natural systems.” Furthermore, the NRC stated that this conclusion is based on findings that are “consistent with the conclusions of recent assessments by the U.S. Global Change Research Program, the Intergovernmental Panel on Climate Change’s Fourth Assessment Report, and other assessments of the state of scientific knowledge on climate change.” These are the same assessments that served as the primary scientific references underlying the Administrator’s Endangerment Finding. Another NRC assessment, “Climate Stabilization Targets: Emissions, Concentra tions, and Impacts over Decades to Millenia”, was published in 2011. This report found that climate change due to carbon dioxide emissions will persist for many ce nturies. The report also estimates a number of specific climate change impacts, finding that every degree Celsius (C) of warming could lead to increases in the heaviest 15% of daily rainfalls of 3 to 10%, decreases of 5 to 15% in yields for a number of crops (absent adaptation measures that do not presently exist), decreases of Arctic sea ice extent of 25% in September and 15% annually averaged, along with changes in precipitation and streamflow of 5 to 10% in many regions and river basins (increases in some regions, decreases in others). The assessment also found that for an increase of 4 degrees C nearly all land areas would experience summers warmer than all but 5% of summers in the 20 th century, that for an increase of 1 to 2 degrees C the area burnt by wildfires in western North America will likely more than double, that coral bleaching and erosion will increase due both to warming and ocean acidification, and that sea level will rise 1.6 to 3.3 feet by 2100 in a 3 degree C scenario. The assessment notes that many important aspects of climate change are difficult to quantify but that the risk of adverse impacts is likely to increase with increasing temperature, and that the risk of abrupt climate changes can be expected to increase with the duration and magnitude of the warming.

346 National Research Council (NRC) (2010). Advancing the Science of Climate Change. National Academy Press. Washington, DC.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 359 of 768 In the 2010 report cited above, the NRC stated that some of the largest potential risks associated with future climate change may come not from relatively smooth changes that are reasonably well understood, but from extreme even ts, abrupt changes, and surprises that might occur when climate or environmental system th resholds are crossed. Examples cited as warranting more research include the release of large quantities of GHGs stored in permafrost (frozen soils) across the Arctic, rapid disintegration of the major ice sheets, irreversible drying and desertification in the subtropics, changes in ocean circulation, and the rapid release of destabilized methane hydrates in the oceans.

On ocean acidification, the same report noted the potential for broad, “catastrophic” impacts on marine ecosystems. Ocean acidity has increased 25 percent since pre-industrial times, and is projected to continue in creasing. By the time atmospheric CO 2 content doubles over its preindustrial value, there would be virtua lly no place left in the ocean that can sustain coral reef growth. Ocean acidification could have dramatic consequences for polar food webs including salmon, the report said.

Importantly, these recent NRC assessments represent another independent and critical inquiry of the state of climate change science, separate and apart from the previous IPCC and

USGCRP assessments.

3. Changes in Global Climate Indicators Associ ated with the Proposal’s GHG Emissions
Reductions

EPA examined 347 the reductions in CO 2 and other GHGs associated with this rulemaking and analyzed the projected effects on atmospheric CO 2 concentrations, global mean surface temperature, sea level rise, and ocean pH which are common variables used as indicators of climate change. 348 The analysis projects that the pr oposed rule, if adopted, will reduce atmospheric concentrations of CO 2 , global climate warming, ocean acidification, and sea level rise relative to the reference case. Although the projected reductions and improvements are small in comparison to the total projected climate change, they are quantifiable, directionally consistent, and will contribute to reducing the risks associated with climate change. Climate change is a global phenomenon and EPA recognizes that this one national action alone will not prevent it: EPA notes this would be true for an y given GHG mitigation action when taken alone or when considered in isolation. EPA also notes that a substantial portion of CO 2 emitted into the atmosphere is not removed by natural processes for millennia, and therefore each unit of CO 2 not

347 Using the Model for the Assessment of Greenhou se Gas Induced Climate Change (MAGICC) 5.3v2, http://www.cgd.ucar.edu/cas/wigley/magicc/), EPA estima ted the effects of this rulemaking’s greenhouse gas emissions reductions on global mean temperature and sea level. Please refer to Chapter 6.4 of the DRIA for additional information.

348 Due to timing constraints, this anal ysis was conducted with preliminary estimates of the emissions reductions projected from this proposal, which were highly similar to the final estimates.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 360 of 768 emitted into the atmosphere due to this rule avoids essentially permanent climate change on
centennial time scales.

EPA determines that the projecte d reductions in atmospheric CO 2 , global mean temperature and sea level rise are meaningful in the context of this final action. In addition, EPA has conducted an analysis to evaluate the projected changes in ocean pH in the context of the changes in emissions from this rulemaking. The results of the analysis demonstrate that relative to the reference case, projected atmospheric CO 2 concentrations are estimated by 2100 to be reduced by 3.29 to 3.68 part per million by volume (ppmv), global mean temperature is estimated to be reduced by 0.0076 to 0.0184°C, and sea-level rise is projected to be reduced by approximately 0.074-0.166 cm, ba sed on a range of climate sens itivities. The analysis also demonstrates that ocean pH will increase by 0. 0018 pH units by 2100 relative to the reference

case.

a. Estimated Reductions in Atmospheric CO 2 Concentration, Global Mean Surface Temperatures, Sea Level Rise, and Ocean pH

EPA estimated changes in the atmospheric CO 2 concentration, global mean temperature, and sea level rise out to 2100 resulting from the emissions reductions in this rulemaking using the Global Change Assessment Model (GCAM, formerly MiniCAM), integrated assessment
model 349 coupled with the Model for the Assessment of Greenhouse Gas Induced Climate Change (MAGICC, version 5.3v2). 350 GCAM was used to create the globally and temporally consistent set of climate relevant variables required for running MAGICC. MAGICC was then used to estimate the projected change in these variables over time. Give n the magnitude of the
estimated emissions reductions associated with this action, a simple climate model such as
MAGICC is reasonable for estima ting the atmospheric and climate response. This widely-used, peer reviewed modeling tool was also used to project temperature and sea level rise under
different emissions scenarios in the Third and Fourth Assessments of the IPCC.

The integrated impact of the following pollutant and greenhouse gas emissions changes
are considered: CO 2 , CH 4 , N 2 O, HFC-134a, NO X , CO, SO 2 , and volatile organic compounds (VOC). For these pollutants an annual time -series of (upstream + downstream) emissions reductions estimated from the rulemaking were applied as net reductions to a global reference

349 GCAM is a long-term, global integrated assessment m odel of energy, economy, agriculture and land use, that considers the sources of emis sions of a suite of GHG’s, emitted in 14 gl obally disaggregated regions, the fate of emissions to the atmosphere, and the consequences of changing concentrations of greenhouse related gases for climate change. GCAM begins with a representation of demographic and economic developments in each region and combines these with assumptions about technology development to describe an internally consistent representation of energy, agriculture, land-use, and economic developments that in turn shape global emissions. Brenkert A, S. Smith, S. Kim, and H. Pitcher, 2003: Model Documentation for the MiniCAM. PNNL-14337, Pacific Northwest National Laboratory, Richland, Washington.

350 Wigley, T.M.L. 2008. MAGICC 5.3.v2 User Manual. UCAR – Climate and Global Dynamics Division, Boulder, Colorado. http://www.cgd.ucar.edu/cas/wigley/magicc/Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 361 of 768 case (or baseline) emissions scenario in GCAM to generate an emissions scenario specific to this proposed rule. 351 The emissions reductions past 2050 for all gases were scaled with total U.S. road transportation fuel consumption from the GCAM reference scenario. Road transport fuel consumption past 2050 does not change significa ntly and thus emissions reductions remain relatively constant from 2050 through 2100. Specific details about the GCAM reference case scenario can be found in Chapter 6.4 of the DRIA that accompanies this proposal .

MAGICC calculates the forcing response at th e global scale from changes in atmospheric
concentrations of CO 2 , CH 4 , N 2 O, HFCs, and tropospheric ozone (O 3 ). It also includes the effects of temperature changes on stratospheric ozone and the effects of CH 4 emissions on stratospheric water vapor. Changes in CH 4 , NOx, VOC, and CO emissions affect both O 3 concentrations and CH 4 concentrations. MAGICC includes the relative climate forcing effects of changes in sulfate concentrations due to changing SO 2 emissions, including both the direct effect of sulfate particles and the indirect effects related to cloud interactions. However, MAGICC does not calculate the effect of changes in concentra tions of other aerosols such as nitrates, black carbon, or organic carbon, making the assumption th at the sulfate cooling effect is a proxy for the sum of all the aerosol effects. Therefore, th e climate effects of changes in PM2.5 emissions and precursors (besides SO 2 ) which are presented in the DRIA Chapter 6 were not included in the calculations in this chapter. MAGICC also cal culates all climate effects at the global scale. This global scale captures the climate effects of the long-lived, well-mixed greenhouse gases, but
does not address the fact that short-lived climate forcers such as aerosols and ozone can have effects that vary with location and timing of em issions. Black carbon in particular is known to cause a positive forcing or warming effect by ab sorbing incoming solar radiation, but there are uncertainties about the magnitude of that warming effect and the interaction of black carbon (and other co-emitted aerosol species) with clouds. Wh ile black carbon is likely to be an important contributor to climate change, it would be prem ature to include quantification of black carbon climate impacts in an analysis of these proposed standards. See generally, EPA, Response to Comments to the Endangerment Finding Vol. 9 section 9.1.6.1 and the discussion of black carbon in the endangerment finding at 74 FR at 66520. Additionally, the magnitude of PM2.5 emissions changes (and therefore, black carbon emission changes) related to these proposed standards are small in comparison to the change s in the pollutants which have been included in
the MAGICC model simulations.

Changes in atmospheric CO 2 concentration, global mean temperature, and sea level rise
for both the reference case and the emissions sc enarios associated with this action were computed using MAGICC. To calculate the reductions in the atmospheric CO 2 concentrations as well as in temperature and sea level resulting from this proposal, the output from the policy scenario associated with EPA’s proposed stan dards was subtracted from an existing Global

351 Due to timing constraints, this anal ysis was conducted with preliminary estimates of the emissions reductions projected from this proposal, which were highly similar to the final estimates.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 362 of 768 Change Assessment Model (GCAM, formerly MiniCAM) reference emission scenario. To capture some key uncertainties in the climate system with the MAGICC model, changes in atmospheric CO 2 , global mean temperature and sea level rise were projected across the most current IPCC range of climate sensitivities, from 1.5°C to 6.0°C. 352 This range reflects the uncertainty for equilibrium climate sensitivity for how much global mean temperature would rise
if the concentration of carbon dioxide in the atmo sphere were to double. The information for this range come from constraints from past climate change on various time scales, and the spread of results for climate sensitivity from ensembles of models. 353 Details about this modeling analysis can be found in the DRIA Chapter 6.4.

The results of this modeling, summarized in Table III-60, show small, but quantifiable, reductions in atmospheric CO 2 concentrations, projected global mean temperature and sea level resulting from this action, across all climate sens itivities. As a result of the emission reductions from the proposed standards, relative to the reference case the atmospheric CO 2 concentration is projected to be reduced by 3.29-3.68 ppmv by 2100, the global mean temperature is projected to be reduced by approximately 0.0076-0.0184°C by 2100, and global mean sea level rise is projected to be reduced by approximately 0.074-0.166 cm by 2100. The range of reductions in global mean temperature and sea level rise is larger than that for CO 2 concentrations because

CO 2 concentrations are only weakly coupled to climate sensitivity through the dependence on temperature of the rate of ocean absorption of CO 2 , whereas the magnitude of temperature change response to CO 2 changes (and therefore sea level rise) is more tightly coupled to climate sensitivity in the MAGICC model.

Table III-60 Impact of GHG Emissions Reductions on Projected Changes in Global Climate Associated with EPA’s Proposed Rulemaking (Based on a range of climate sensitivities from 1.5-6°C)

VARIABLE U NITS Y EAR PROJECTE D CHANGE Atmospheric CO 2 Concentration pp

mv 2 100 -3.29 to - 3.68
Global Mean Surface oC 2 -0.0076 to -

352 In IPCC reports, equilibrium climate sensitivity refers to the equilibrium change in the annual mean global surface temperature following a doubling of the atmospheri c equivalent carbon dioxide concentration. The IPCC states that climate sensitivity is “likely” to be in the range of 2°C to 4.5°C, “very unlikely” to be less than 1.5°C, and “values substantially higher than 4.5°C cannot be excluded.” IPCC WGI, 2007, Climate Change 2007 - The Physical Science Basis, Contribution of Working Group I to the Fourth Assessment Report of the IPCC, http://www.ipcc.ch/

353 Meehl, G.A. et al. (2007) Global Climate Projections. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Ma rquis, K.B. Averyt, M. Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 363 of 768 Temperature 100 0.0184
Sea Level Rise cm 2 100 -0.074 to - 0.166 Ocean pH pH units 2 100 +0.0018 a

a The value for projected change in ocean pH is based on a climate sensitivity of 3.0. The projected reductions are small relative to the change in temperature (1.8 – 4.8 oC), sea level rise (23 – 55 cm), and ocean acidity (-0.30 pH units) from 1990 to 2100 from the MAGICC simulations for the GCAM reference case. However, this is to be expected given the magnitude of emissions reductions expected from the program in the context of global emissions. This uncertainty range does not include the effects of uncertainty in future emissions. It should
also be noted that the calculations in MAGICC do not include the possible effects of accelerated ice flow in Greenland and/or Antarctica: the recent NRC report estimated a likely sea level
increase for a business-as-usual scenario of 0.5 to 1.0 meters. 354 Further discussion of EPA’s modeling analysis is found in the DRIA, Chapter 6.

EPA used the computer program CO2SYS, 355 version 1.05, to estimate projected changes in ocean pH for tropical waters based on the atmospheric CO 2 concentration change (reduction) resulting from this proposal. The program performs calculations relating parameters of the CO 2 system in seawater. EPA used the program to calculate ocean pH as a function of atmospheric

CO 2 concentrations, among other specified input conditions. Based on the projected atmospheric

CO 2 concentration reductions resulting from this proposal, the program calculates an increase in ocean pH of 0.0018 pH units in 2100 relative to the reference case (compared to a decrease of 0.3 pH units from 1990 to 2100 in the reference case). Thus, this analysis indicates the projected decrease in atmospheric CO 2 concentrations from the program w ill result in an increase in ocean pH. For additional validation, results were generated using different known constants from the literature. A comprehensive discussion of the modeling analysis associated with ocean pH is provided in the DRIA, Chapter 6.

b. Program’s Effect on Climate

As a substantial portion of CO 2 emitted into the atmosphere is not removed by natural processes for millennia, each unit of CO 2 not emitted into the atmosphere avoids essentially permanent climate change on centennial time scal es. Reductions in emissions in the near-term are important in determining long-term climate stabilization and associated impacts experienced

354 National Research Council (NRC), 2011. Climate Stabilization Targets: Emissions, Concentrations, and Impacts over Decades to Millennia. Washington, DC: National Academies Press.

355 Lewis, E., and D. W. R. Wallace. 1998. Program Developed for CO 2 System Calculations. ORNL/CDIAC-105. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 364 of 768 not just over the next decades but in the coming centu ries and millennia. 356 Though the magnitude of the avoided climate change projected here is small in comparison to the total projected changes, these reductions represent a reduction in the adverse risks associated with climate change (though these risks were not formally estimated for this action) across a range of equilibrium climate sensitivities.

EPA’s analysis of the program’s impact on global climate conditions is intended to quantify these potential reductions using the best available science. EPA’s modeling results show repeatable, consistent reductions relative to the reference case in changes of CO 2 concentration, temperature, sea-level rise, and ocean pH over the next century.

G. How Would the Proposal Impact Non-GHG Emissions and Their Associated
Effects?

Although this rule focuses on GHGs, it will al so have an impact on non-GHG pollutants. Sections G.1 of this preamble details the criteria pollutant and air toxic in ventory changes of this proposed rule. The following sections, G.2 and G.3, discuss the health and environmental effects associated with the criteria and toxic air pollutants that are being impacted by this proposed rule. In Section G.4 we discuss the potential impact of this proposal on concentrations of criteria and air toxic pollutants in the ambient air. The tool s and methodologies used in this analysis are substantially similar to those used in the MYs 2012-2016 light duty rulemaking.

1. Inventory

a. Impacts

In addition to reducing the emissions of greenhouse gases, this rule would influence “non-GHG” pollutants, i.e., “criteria” air pollutants and their precursors, and air toxics. The proposal would affect emissions of carbon mono xide (CO), fine particulate matter (PM2.5), sulfur dioxide (SO X ), volatile organic compounds (VOC), nitrogen oxides (NO X ), benzene, 1,3- butadiene, formaldehyde, acetaldehyde, and acrolei n. Our estimates of these non-GHG emission impacts from the GHG program are shown by pollutant in Table III.G-1 and Table III.G-2 both in total and broken down by the three drivers of these changes: a) “downstream” emission changes, reflecting the estimated effects of VMT rebound (discussed in Sections III.F and III.H) and decreased consumption of fuel; b) “upstream” emission reductions due to decreased extraction, production and distribution of motor vehicle gasoline; c) “upstream” emission increases from power plants as electric powertrain vehicles increase in prevalence as a result of this rule. Program impacts on criteria and toxics emissions are discussed below, followed by

356 National Research Council (NRC) (2011). Climate Stabili zation Targets: Emissions, Concentrations, and Impacts over Decades to Millennia. National Academy Press. Washington, DC.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 365 of 768 individual discussions of the methodology used to calculate each of these three sources of impacts.

As shown in Table III-61, EPA estimates that the proposed light duty vehicle program
would result in reductions of NO X , VOC, PM2.5 and SO X , but would increase CO emissions. 357

For NO x, VOC, and PM2.5, we estimate net reductions because the net emissions reductions from reduced fuel refining, distribution and transport is larger than the emission increases due to increased VMT and increased electricity production. In the case of CO, we estimate slight emission increases, because there are relatively small reductions in upstream emissions, and thus the projected emission increases due to VMT reb ound and electricity production are greater than the projected emission decreases due to reduced fuel production. For SO
x , downstream emissions are roughly proportional to fuel consum ption, therefore a decrease is seen in both downstream and fuel refining sources.

For all criteria pollutants the overall impact of the proposed proposed program would be small compared to total U.S. inventories across all sectors. In 2030, EPA estimates that the program would reduce total NO X , PM and SO X inventories by 0.1 to 0.8 percent and reduce the VOC inventory by 1.1 percent, while increasing the total national CO inventory by 0.5 percent.

As shown in Table III-62, EPA estimates that the proposed program would result in similarly small changes for air toxic emissions compared to total U.S. inventories across all sectors. In 2030, EPA estimates the proposed program would increase total 1,3 butadiene and acetaldehyde emissions by 0.1 to 0.3 percent. Total acrolein, benzene and formaldehyde emissions would decrease by similarly small amounts.

Table III-61 Annual Criteria Emission Impacts of Program (short tons)

CY 2020 CY 2030

Pollutant Impacts (Short Tons) % of Total US Inventory Impacts (Short Tons) % of Total US Inventory

Total VOC -12,214 -0.1% -142,293 -1.1% CO 20,965 0.0% 287,940 0.5%

NO X -2,395 0.0% -21,452 -0.2% PM2.5 -344 0.0% -3,574 -0.1%

SO X -1,616 0.0% -10,569 -0.1%

Downstream VOC 374 0.0% 6,111 0.0% CO 21,915 0.0% 295,802 0.5%

NO X 769 0.0% 10,804 0.1%
PM2.5 62 0.0% 760 0.0%

SO X -440 0.0% -5,198 -0.1%

Fuel Production and Distribution VOC -12,602 -0.1% -148,715 -1.2% CO -1,204 0.0% -14,212 0.0%

NO X -3,769 0.0% -44,474 -0.4%

357 While estimates for CY 2020 and 2030 are shown here , estimates through 2050 are shown in RIA Ch. 4.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 366 of 768 PM2.5 -514 0.0% -6,061 -0.1%

SO X -2,306 0.0% -27,214 -0.3%

Electricity VOC 14 0.0% 311 0.0% CO 254 0.0% 6,350 0.0%

NO X 605 0.0% 12,219 0.1% PM2.5 108 0.0% 1,727 0.0%

SO X 1,131 0.0% 21,843 0.3%

Table III-62 Annual Air Toxic Emission Impacts of Program (short tons)

CY 2020 CY 2030

Pollutant Impacts (Short Tons) % of Total US Inventory Impacts (Short Tons) % of Total US Inventory

Total 1,3- Butadiene 2 0.02% 33 0.3% Acetaldehyde 4 0.00% 76 0.1%

Acrolein 0 0.01% -8 0.0%
Benzene -15 -0.01% -118 -0.1% Formaldehyde -5 0.00% -34 0.0%

Downstream 1,3- Butadiene 2 0.02% 35 0.3% Acetaldehyde 6 0.01% 89 0.2%

Acrolein 0 0.01% 4 0.0%
Benzene 13 0.01% 203 0.1% Formaldehyde 5 0.00% 84 0.1%

Fuel Production and Distribution 1,3- Butadiene 0 0.00% -3 0.0% Acetaldehyde -1 0.00% -16 0.0%

Acrolein 0 -0.01% -16 0.0%
Benzene -27 -0.01% -322 -0.2% Formaldehyde -10 0.00% -119 -0.1%

Electricity 1,3- Butadiene 0 0.00% 2 0.0% Acetaldehyde 0 0.00% 3 0.0%

Acrolein 0 0.01% 4 0.0%
Benzene 0 0.00% 2 0.0% Formaldehyde 0 0.00% 1 0.0%

b. Methodology

As in the MYs 2012-2016 rulemaking, for the downstream analysis, the current version of the EPA motor vehicle emission simulator (MOVES2010a) was used to estimate base VOC, CO, NO X , PM and air toxics emission rates. A dditional emissions from light duty cars andtrucks attributable to the rebound effect were then calculated using the OMEGA model postprocessor. A more complete discussion of the i nputs, methodology, and results is contained in RIA Chapter 4.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 367 of 768 This proposal assumes that MY 2017 and late r vehicles are compliant with the agency’s Tier 2 emission standards. This proposal does not model any future Tier 3 emission standards, because these standards have not yet been pr oposed (see Section III.A). We intend for the analysis assessing the impacts of both the fina l Tier 3 emission standards and the final 2017-
2025 LD GHG to be included in the final Tier 3 rule. For the proposals, we are taking care to coordinate the modeling of each rule to proper ly assess the air quality impact of each action independently without double counting.

As in the MYs 2012-2016 GHG rulemaking, for this analysis we attribute decreased fuel consumption from this program to petroleum-based fuels only, while assuming no effect on volumes of ethanol and other renewable fuels because they are mandated under the Renewable Fuel Standard (RFS2). For the purposes of this emission analysis, we assume that all gasoline in the timeframe of the analysis is blended with 10 percent ethanol (E10). However, as a consequence of the fixed volume of renewable fuels mandated in the RFS2 rulemaking and the decreasing petroleum consumption predicted here, we anticipate that this proposal would in fact increase the fraction of the U.S. fuel supply that is made up by renewable fuels. Although we are not modeling this effect in our analysis of this proposal, the Tier 3 rulemaking will make more refined assumptions about future fuel pr operties, including (in a final Tier 3 rule) accounting for the impacts of the LD GHG rule. In this rulemaking EPA modeled the three impacts on criteria pollutant emissions (rebound driving, changes in fuel production, and changes in electricity production) discussed above.

Other factors which may impact downstream non-GHG emissions, but are not estimated in this analysis, include: The potential for decreased criteria pollutant emissions due to increased air conditioner efficiency; reduced refueling emissi ons due to less frequent refueling events and reduced annual refueling volumes resulting from the GHG standards; and increased hot soak evaporative emissions due to the likely increase in number of trips associated with VMT rebound modeled in this proposal. In all, these additional analyses would likely result in small changes relative to the national inventory.

To determine the upstream fuel production impacts, EPA estimated the impact of reduced petroleum volumes on the extraction and transportation of crude oil as well as the production and distribution of finished gasoline. For the purpose of assessing domestic-only emission reductions it was necessary to estimate the fraction of fuel savings attributable to domestic finished gasoline, and of this gasoline what fraction is produced from domestic crude. For this analysis EPA estimated that 50 percent of fuel savings is attributable to domestic finished gasoline and that 90 percent of this gasoline or iginated from imported crude. Emission factors for most upstream emission sources are based on the GREET1.8 model, developed by DOE’s Argonne National Laboratory, 358 but in some cases the GREET values were modified or updated

358 Greenhouse Gas, Regulated Emissions, and Energy Use in Transportation model (GREET), U.S. Department of Energy, Argonne National Laboratory, http://www.tr ansportation.anl.gov/mode ling_simulation/GREET/Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 368 of 768 by EPA to be consistent with the National Emission Inventory (NEI). 359 The primary updates for this analysis were to incorporate newer information on gasoline distribution emissions for VOC from the NEI, which were significantly higher than GREET estimates; and the incorporation of upstream emission factors for the ai r toxics estimated in this analysis: benzene, 1,3-butadiene, acetaldehyde, acrolein, and formaldehyde. The deve lopment of these emission factors is detailedin a memo to the docket. These emission factors were incorporated into the OMEGA postprocessor.

As with the GHG emission analysis discussed in section III.F, electricity emission factors were derived from EPA’s Integrated Planning Model (IPM). EPA uses IPM to analyze the projected impact of environmental policies on the electric power sector in the 48 contiguous states and the District of Columbia. IPM is a multi-regional, dynamic, deterministic linear programming model of the U.S. electric power sect or. It provides forecasts of least-cost capacity expansion, electricity dispatch, and emission cont rol strategies for meeting energy demand and environmental, transmission, disp atch, and reliability constraints. EPA derived average national CO 2 emission factors from the IPM version 4.10 run for the “Proposed Transport Rule. 360 ” As discussed in Draft TSD Chapter 4, for the Fina l Rulemaking, EPA may consider emission factors other than national power generation, such as ma rginal power emission factors, or regional emission factors.

359 U.S. EPA. 2002 National Emissions Inve ntory (NEI) Data and Documentation, http://www.epa.gov/ttn/chief/net/2002inventory.html .

360 EPA. IPM. http://www.epa.gov/air markt/progsregs/epa-ipm/BaseCasev410.html . "Proposed Transport Rule/NODA version" of IP M . TR_SB_Limited Trading v.4.10Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 369 of 768 2. Health Effects of Non-GHG Pollutants

In this section we discuss health effects associ ated with exposure to some of the criteria and air toxic pollutants impacted by the proposed vehicle standards.

a. Particulate Matter

i. Background

Particulate matter is a generic term for a broad class of chemically and physically diverse substances. It can be principally characterized as discrete particles that exist in the condensed (liquid or solid) phase spanning several orders of magnitude in size. Since 1987, EPA has delineated that subset of inhalable particles small enough to penetrate to the thoracic region (including the tracheobronchial and alveolar regi ons) of the respiratory tract (referred to as thoracic particles). 361 Current National Ambient Air Quality Standards (NAAQS) use PM 2.5 as the indicator for fine particles (with PM 2.5 generally referring to particles with a nominal mean aerodynamic diameter less than or equal to 2.5 micrometers (μm), and use PM 10 as the indicator for purposes of regulating the coarse fraction of PM 10 (referred to as thoracic coarse particles or coarse-fraction particles; generally including particles with a nominal mean aerodynamic diameter greater than 2.5 μm and less than or equal to 10 μm, or PM 10-2.5 ). Ultrafine particles are a subset of fine particles, generally less than 100 nanometers (0.1 μ m) in diameter.

Fine particles are produced primarily by comb ustion processes and by transformations of gaseous emissions (e.g., sulfur oxides (SO X ), nitrogen oxides (NO X ), and volatile organic compounds (VOC)) in the atmosphere. The chemical and physical properties of PM 2.5 may vary greatly with time, region, meteorology, and source category. Thus, PM 2.5 may include a complex mixture of different components including sulfates, nitrates, organic compounds, elemental carbon and metal compounds. These pa rticles can remain in th e atmosphere for days
to weeks and travel hundreds to thousands of kilometers.

ii. Health Effects of Particulate Matter

Scientific studies show ambient PM is associated with a series of adverse health effects. These health effects are discussed in detail in EPA’s Integrated Science Assessment (ISA) for
Particulate Matter. 362 Further discussion of health effects associated with PM can also be found
in the draft RIA. The ISA summarizes health ef fects evidence associated with both short-term and long-term exposures to PM 2.5 , PM 10-2.5 , and ultrafine particles.

361 Regulatory definitions of PM size fractions, and inform ation on reference and equivalent methods for measuring PM in ambient air, are provided in 40 CFR Parts 50, 53, and 58.

362 U.S. EPA (2009) Integrated Science Assessment for Particulate Matter (Final Report). U.S. Environmental Protection Agency, Washington, DC, EPA/600/R-08/139F, Docket EPA-HQ-OAR-2010-0162.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 370 of 768 The ISA concludes that health effects associated with short-term exposures (hours to days) to ambient PM 2.5 include mortality, cardiovascular effects, such as altered vasomotor function and hospital admissions and emergency depa rtment visits for ischemic heart disease and congestive heart failure, and respiratory effects, such as exacerbation of asthma symptoms in children and hospital admissions and emergency department visits for chronic obstructive pulmonary disease and respiratory infections. 363 The ISA notes that long-term exposure (months to years) to PM 2.5 is associated with the development/progression of cardiovascular disease, premature mortality, and respiratory effects, in cluding reduced lung function growth, increased respiratory symptoms, and asthma development. 364 The ISA concludes that the currently available scientific evidence from epidemiologic, controlled human exposure, and toxicological studies supports a causal association between short- and long-term exposures to PM 2.5 and cardiovascular effects and mortality. Furthe rmore, the ISA concludes that the collective evidence supports likely causal associations between short- and long-term PM 2.5 exposures and respiratory effects. The ISA also concludes that the scientific evidence is suggestive of a causal association for reproductive and developmental effects and cancer, mutagenicity, and genotoxicity and long-term exposure to PM 2.5

. 365

For PM 10-2.5 , the ISA concludes that the current evidence is suggestive of a causal relationship between short-term exposures and card iovascular effects. There is also suggestive evidence of a causal relationship between short-term PM 10-2.5 exposure and mortality and respiratory effects. Data are inadequate to draw conclusions regarding the health effects associated with long-term exposure to PM 10-2.5

. 366

For ultrafine particles, the ISA concludes that there is suggestive evidence of a causal relationship between short-term exposures and cardiovascular effects, such as changes in heart rhythm and blood vessel function. It also concludes that there is suggestive evidence of association between short-term exposure to ultrafine particles and respiratory effects. Data are inadequate to draw conclusions regarding the hea lth effects associated with long-term exposure to ultrafine particles. 367

b. Ozone

i. Background

Ground-level ozone pollution is typically formed by the reaction of VOC and NO X in the lower atmosphere in the presence of sunlight. These pollutants, often referred to as ozone precursors, are emitted by many types of pollution sources, such as highway and nonroad motor

363 See U.S. EPA, 2009 Final PM ISA, Note 362, at Section 2.3.1.1.

364 See U.S. EPA 2009 Final PM ISA, Note 362, at page 2-12, Sections 7.3.1.1 and 7.3.2.1.

365 See U.S. EPA 2009 Final PM ISA, Note 362, at Section 2.3.2.

366 See U.S. EPA 2009 Final PM ISA, Note 362, at Section 2.3.4, Table 2-6.

367 See U.S. EPA 2009 Final PM ISA, Note 362, at Section 2.3.5, Table 2-6.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 371 of 768 vehicles and engines, power plants, chemical plants, refineries, makers of consumer and commercial products, industrial fa cilities, and smaller area sources.

The science of ozone formation, transport, and accumulation is complex. Ground-level ozone is produced and destroyed in a cyclical set of chemical reactions, many of which are sensitive to temperature and sunlig ht. When ambient temperatures and sunlight levels remain high for several days and the air is relatively stagnant, ozone and its precursors can build up and result in more ozone than typically occurs on a single high-temperature day. Ozone can be transported hundreds of miles downwind from precu rsor emissions, resulting in elevated ozone
levels even in areas with low local VOC or NO X emissions.

ii. Health Effects of Ozone

The health and welfare effects of ozone are well documented and are assessed in EPA’s 2006 Air Quality Criteria Document and 2007 Staff Paper. 368,369 People who are more susceptible to effects associated with exposure to ozone can include children, the elderly, and individuals with respiratory disease such as asthma. Those with greater exposures to ozone, for instance due to time spent outdoors (e.g., children and outdoor workers), are of particular concern. Ozone can irritate the respiratory system, causing coughing, throat irritation, and breathing discomfort. Ozone can reduce lung function and cause pulmonary inflammation in healthy individuals. Ozone can also aggravate asthma, leading to more asthma attacks that require medical attention and/or the use of additional medication. Thus, ambient ozone may cause both healthy and asthmatic individuals to limi t their outdoor activities. In addition, there is suggestive evidence of a contri bution of ozone to cardiovascular-related morbidity and highlysuggestive evidence that short-term ozone exposure directly or indirectly contributes to nonaccidental and cardiopulmonary-related mortality, but a dditional research is needed to clarify the underlying mechanisms causing these effects. In a report on the estimation of ozone-related premature mortality published by NRC, a panel of experts and reviewers concluded that shortterm exposure to ambient ozone is likely to contribute to premature deaths and that ozone-related mortality should be included in estimates of th e health benefits of reducing ozone exposure. 370
Animal toxicological evidence indicates that wi th repeated exposure, ozone can inflame and damage the lining of the lungs, which may lead to permanent changes in lung tissue and irreversible reductions in lung function. The respiratory effects observed in controlled human exposure studies and animal studies are coherent with the evidence from epidemiologic studies

368 U.S. EPA. (2006). Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final). EPA/600/R05/004aF-cF. Washington, DC: U.S. EPA. Docket EPA-HQ-OAR-2010-0162.

369 U.S. EPA. (2007). Review of the National Ambient Air Quality Standards for Ozone: Policy Assessment of Scientific and Technical Information, OAQPS Staff Paper. EPA-452/R-07-003. Washington, DC, U.S. EPA. Docket EPA-HQ-OAR-2010-0162.

370 National Research Council (NRC), 2008. Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution . The National Academies Press: Wash ington, D.C. Docket EPA-HQ-OAR-2010- 0162Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 372 of 768 supporting a causal relationship between acute ambient ozone exposures and increased respiratory-related emergency room visits and hospitalizations in the warm season. In addition, there is suggestive evidence of a contribution of ozone to cardiovascular-related morbidity and non-accidental and cardiopulmonary mortality.

c. Nitrogen Oxides and Sulfur Oxides

i. Background

Nitrogen dioxide (NO 2 ) is a member of the NO X family of gases. Most NO 2 is formed in the air through the oxidation of nitric oxide (NO) emitted when fuel is burned at a high temperature. Sulfur Dioxide (SO 2 ) a member of the sulfur oxide (SO X ) family of gases, is formed from burning fuels containing sulfur (e.g., coal or oil derived), extracting gasoline from oil, or extracting metals from ore.

SO 2 and NO 2 can dissolve in water droplets and further oxidize to form sulfuric and nitric
acid which react with ammonia to form sulfat es and nitrates, both of which are important components of ambient PM. The health effects of ambient PM are discussed in Section III.G.3.a.ii of this preamble. NO X and NMHC are the two major precursors of ozone. The health
effects of ozone are covered in Section III.G.3.b.ii.

ii. Health Effects of NO 2

Information on the health effects of NO 2 can be found in the EPA Integrated Science Assessment (ISA) for Nitrogen Oxides. 371 The EPA has concluded that the findings of epidemiologic, controlled human exposure, and animal toxicological studies provide evidence that is sufficient to infer a likely causal relatio nship between respiratory effects and short-term

NO 2 exposure. The ISA concludes that the strongest evidence for such a relationship comes from epidemiologic studies of respiratory effects in cluding symptoms, emergency department visits, and hospital admissions. The ISA also draws two broad conclusions regarding airway responsiveness following NO 2 exposure. First, the ISA concludes that NO 2 exposure may enhance the sensitivity to allergen-induced decrements in lung function and increase the allergen-induced airway inflammatory response following 30-minute exposures of asthmatics to

NO 2 concentrations as low as 0.26 ppm. Second, exposure to NO 2 has been found to enhance the inherent responsiveness of the airway to subsequent nonspecific challenges in controlled human exposure studies of asthmatic subjects. Sma ll but significant increases in non-specific airway hyperresponsiveness were reported following 1-hour exposures of asthmatics to 0.1 ppm NO 2

. Enhanced airway responsiveness could have impor tant clinical implications for asthmatics since transient increases in airway responsiveness following NO 2 exposure have the potential to

371 U.S. EPA (2008). Integrated Science Assessment for Oxides of Nitrogen – Health Criteria (Final Report). EPA/600/R-08/071. Washington, DC: U.S.EPA. Docket EPA-HQ-OAR-2010-0162 .Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 373 of 768 increase symptoms and worsen asthma control. Together, the epidemiologic and experimental data sets form a plausible, consistent, and coherent description of a relationship between NO 2 exposures and an array of adverse health effects that range from the onset of respiratory symptoms to hospital admission.

Although the weight of evidence supporting a causal relationship is somewhat less certain than that associated with respiratory morbidity, NO 2 has also been linked to other health endpoints. These include all-cause (nonaccidental) mortality, hospital admissions or emergency department visits for cardiovascular disease, and decrements in lung function growth associated with chronic exposure.

iii. Health Effects of SO 2

Information on the health effects of SO 2 can be found in the EPA Integrated Science
Assessment for Sulfur Oxides. 372 SO 2 has long been known to cause adverse respiratory health effects, particularly among individuals with asthma. Other potentially sensitive groups include children and the elderly. During periods of el evated ventilation, asthmatics may experience symptomatic bronchoconstriction within minu tes of exposure. Following an extensive evaluation of health evidence from epidemiologic and laboratory studies, the EPA has concluded that there is a causal relationship between respiratory health effects and short-term exposure to

SO 2 . Separately, based on an evaluation of the epidemiologic evidence of associations between short-term exposure to SO 2 and mortality, the EPA has concluded that the overall evidence is suggestive of a causal relationship between short-term exposure to SO 2 and mortality.

d. Carbon Monoxide

Information on the health effects of CO can be found in the EPA Integrated Science Assessment (ISA) for Carbon Monoxide. 373 The ISA concludes that ambient concentrations of
CO are associated with a number of adverse health effects. 374 This section provides a summary of the health effects associated with exposure to ambient concentrations of CO. 375

372 U.S. EPA. (2008). Integrated Science Assessment (ISA) for Sulfur Oxides – Health Criteria (Final Report)

. EPA/600/R-08/047F. Washington, DC: U.S. Environmental Protection Agency. Docket EPA-HQ-OAR-2010-0162.

373 U.S. EPA, 2010. Integrated Science Assessment for Carbon Monoxide (Final Report). U.S. Environmental Protection Agency, Washington, DC, EPA/600/R-09/019F, 2010. Available at http://cfpub.epa.gov/ncea/cfm/r ecordisplay.cfm?deid=218686 . Docket EPA-HQ-OAR-2010-0162

374 The ISA evaluates the health evidence associated with different health effects, assigning one of five “weight of evidence” determinations: causal relationship, likely to be a causal relationship, suggestive of a causal relationship, inadequate to infer a causal relationship, and not likely to be a causal relationship. For definitions of these levels of evidence, please refer to Section 1.6 of the ISA.

375 Personal exposure includes contributions from many s ources, and in many different environments. Total personal exposure to CO includes both ambient and nona mbient components; and both components may contribute to adverse health effects.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 374 of 768 Human clinical studies of subjects with cor onary artery disease show a decrease in the time to onset of exercise-induced angina (che st pain) and electrocardiogram changes following CO exposure. In addition, epidemiologic studi es show associations between short-term CO exposure and cardiovascular morbidity, particularly increased emergency room visits and hospital admissions for coronary heart disease (i ncluding ischemic heart disease, myocardial infarction, and angina). Some epidemiologic evidence is also available for increased hospital admissions and emergency room visits for congestive heart failure and cardiovascular disease as a whole. The ISA concludes that a causal relationship is likely to exist between short-term exposures to CO and cardiovascular morbidity. It also concludes that available data are inadequate to conclude that a causal relationshi p exists between long-term exposures to CO and cardiovascular morbidity.

Animal studies show various ne urological effects with in-utero CO exposure. Controlled human exposure studies report inconsistent neural and behavioral effects following low-level CO exposures. The ISA concludes the evidence is suggestive of a causal relationship with both short- and long-term exposure to CO and central nervous system effects.

A number of epidemiologic and animal toxi cological studies cited in the ISA have evaluated associations between CO exposure and birth outcomes such as preterm birth or cardiac birth defects. The epidemiologic studies provi de limited evidence of a CO-induced effect on preterm births and birth defects, with weak ev idence for a decrease in birth weight. Animal toxicological studies have found associations be tween perinatal CO exposure and decrements in birth weight, as well as other developmental outcomes. The ISA concludes these studies are suggestive of a causal relationship between long-term exposures to CO and developmental
effects and birth outcomes.

Epidemiologic studies provide evidence of effects on respiratory morbidity such as changes in pulmonary function, respiratory symptoms, and hospital admissions associated with
ambient CO concentrations. A limited number of epidemiologic studies considered copollutants such as ozone, SO 2 , and PM in two-pollutant models and found that CO risk estimates were generally robust, although this limited evidence makes it difficult to disentangle effects attributed to CO itself from those of the larger complex air pollution mixture. Controlled human exposure studies have not extensively evaluated the effect of CO on respiratory morbidity. Animal studies at levels of 50-100 ppm CO show preliminary evidence of altered pulmonary vascular remodeling and oxidative injury. The ISA concludes that the evidence is suggestive of a causal relationship between short-term CO exposure and respiratory morbidity, and inadequate to conclude that a causal relationship exists between long-term exposure and respiratory morbidity.

Finally, the ISA concludes that the epidemiologic evidence is suggestive of a causal relationship between short-term exposures to CO and mortality. Epidemiologic studies provide evidence of an association between short-term exposure to CO and mortality, but limitedSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 375 of 768 evidence is available to evaluate cause-specific mo rtality outcomes associated with CO exposure. In addition, the attenuation of CO risk estimates which was often observed in copollutant models contributes to the uncertainty as to whether CO is acting alone or as an indicator for other combustion-related pollutants. The ISA also conclu des that there is not likely to be a causal relationship between relevant long-term exposures to CO and mortality.

e. Air Toxics

Light-duty vehicle emissions contribute to ambient levels of air toxics known or suspected as human or animal carcinogens, or that have noncancer health effects. The population experiences an elevated risk of cancer and other noncancer health effects from exposure to the class of pollutants known collectively as “air toxics.” 376 These compounds include, but are not limited to, benzene, 1,3-butadiene, formaldehyde, acetaldehyde, acrolein, polycyclic organic matter, and naphthalene. These compounds were identified as national or regional risk drivers or contributors in the 2005 National-scale Air Toxics Assessment and have significant inventory contribu tions from mobile sources. 377

i. Benzene

The EPA’s Integrated Risk Information System (IRIS) database lists benzene as a known human carcinogen (causing leukemia) by all routes of exposure, and concludes that exposure is associated with additional health effects, includ ing genetic changes in both humans and animals and increased proliferation of bone marrow cells in mice. 378,379,380 EPA states in its IRIS database that data indicate a causal relationship between benzene exposure and acutelymphocytic leukemia and suggest a relationship between benzene exposure and chronic nonlymphocytic leukemia and chronic lymphocytic leukemia. The International Agency for Research on Carcinogens (IARC) has determined that benzene is a human carcinogen and the U.S. Department of Health and Human Services (DHHS) has characterized benzene as a known human carcinogen. 381,382

376 U.S. EPA. (2011) Summary of Results for the 2005 National-Scale Assessment. www.epa.gov/ttn/atw/nata2005/05pdf/sum_r esults.pdf. Docket EPA-HQ-OAR-2010-XXXX.

377 U.S. EPA (2011) 2005 National-Scale Air Toxics A ssessment. http://www.epa.gov/ttn/atw/nata2005. Docket EPA-HQ-OAR-2010-XXXX.

378 U.S. EPA. 2000. Integrated Risk Information System File for Benzene. This material is available electronically at http://www.epa.gov/iris/subst/0276.htm. Docket EPA-HQ-OAR-2010-0162.

379 International Agency for Research on Cancer. 1982. Monographs on the evaluation of carcinogenic risk of chemicals to humans, Volume 29. Some industrial chem icals and dyestuffs, World Health Organization, Lyon, France, p. 345-389. Docket EPA-HQ-OAR-2010-0162

380 Irons, R.D.; Stillman, W.S.; Colagiovanni, D.B.; Henry, V.A. 1992. Synergistic action of the benzene metabolite hydroquinone on myelopoietic stimulating activity of granul ocyte/macrophage colony-stimulating factor in vitro, Proc. Natl. Acad. Sci. 89:3691-3695. Docket EPA-HQ-OAR-2010-0162.

381 See IARC, Note 379, above.

382 U.S. Department of Health and Human Services National Toxicology Program 11th Report on Carcinogens available at: http://ntp.niehs.nih.gov/go/16183. Docket EPA-HQ-OAR-2010-0162Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 376 of 768 A number of adverse noncancer health effects including blood disorders, such as preleukemia and aplastic anemia, have also been associated with long-term exposure to
benzene. 383,384 The most sensitive noncancer effect observed in humans, based on current data, is the depression of the absolute lymphocyte count in blood. 385, 386 In addition, published work, including studies sponsored by the Health Eff ects Institute (HEI), provides evidence that biochemical responses are occurring at lower levels of benzene exposure than previously
known. 387,388,389,390 EPA’s IRIS program has not yet evaluated these new data.

ii. 1,3-Butadiene

EPA has characterized 1,3-butadiene as carcinogenic to humans by inhalation. 391,392 The IARC has determined that 1,3-butadiene is a human carcinogen and the U.S. DHHS has characterized 1,3-butadiene as a known human carcinogen. 393,394 There are numerous studies consistently demonstrating that 1,3-butadiene is metabolized into genotoxic metabolites by experimental animals and humans. The specific mechanisms of 1,3-butadiene-induced

383 Aksoy, M. (1989). Hematotoxicity and carcinogenicity of benzene. Environ. Health Perspect. 82: 193-197. Docket EPA-HQ-OAR-2010-0162.

384 Goldstein, B.D. (1988). Benzene toxicity. Occupational medicine. State of the Art Reviews. 3: 541-554. Docket EPA-HQ-OAR-2010-0162.

385 Rothman, N., G.L. Li, M. Dosemeci, W.E. Bechtold, G.E. Marti, Y.Z. Wang, M. Linet, L.Q. Xi, W. Lu, M.T. Smith, N. Titenko-Holland, L.P. Zhang, W. Blot, S.N. Yin, and R.B. Hayes (1996) Hematotoxicity among Chinese workers heavily exposed to benzene. Am. J. Ind. Med. 29: 236-246. Docket EPA-HQ-OAR-2010-0162.

386 U.S. EPA (2002) Toxicological Review of Benzene (Noncancer Effects). Enviro nmental Protection Agency, Integrated Risk Information System, Research and Deve lopment, National Center for Environmental Assessment, Washington DC. This material is available electronically at http://www.epa.gov/iris/subst/0276.htm. Docket EPAHQ-OAR-2010-0162.

387 Qu, O.; Shore, R.; Li, G.; Jin, X.; Chen, C.L.; Cohen, B.; Melikian, A.; Eastmond, D.; Rappaport, S.; Li, H.; Rupa, D.; Suramaya, R.; Songnian, W.; Huifant, Y.; Meng, M.; Winnik, M.; Kwok, E.; Li, Y.; Mu, R.; Xu, B.; Zhang, X.; Li, K. (2003) HEI Report 115, Validation & Ev aluation of Biomarkers in Workers Exposed to Benzene in China. Docket EPA-HQ-OAR-2010-0162.

388 Qu, Q., R. Shore, G. Li, X. Jin, L.C. Chen, B. Cohen, et al. (2002) Hematological changes among Chinese workers with a broad range of benzene exposures. Am. J. Industr. Med. 42: 275-285. Docket EPA-HQ-OAR-2010-
0162.

389 Lan, Qing, Zhang, L., Li, G., Vermeulen, R., et al. ( 2004) Hematotoxically in Workers Exposed to Low Levels of Benzene. Science 306: 1774-1776. Docket EPA-HQ-OAR-2010-0162.

390 Turtletaub, K.W. and Mani, C. (2003) Benzene metabolis m in rodents at doses relevant to human exposure from Urban Air. Research Reports Health Effect Inst. Report No.113. Docket EPA-HQ-OAR-2010-0162.

391 U.S. EPA (2002) Health Assessment of 1,3-Butadiene. Office of Research and Development, National Center for Environmental Assessment, Washington Office, Washington, DC. Report No. EPA600-P-98-001F. This document is available electronically at http://www.epa.gov/iris/supdocs/buta-sup.pdf. Docket EPA-HQ-OAR-2010-0162.

392 U.S. EPA (2002) Full IRIS Summary for 1,3-butadiene (CASRN 106-99-0). Environmental Protection Agency, Integrated Risk Information System (IRIS), Research and Development, National Center for Environmental Assessment, Washington, DC http://www.epa.gov/iris/subst/0139.htm. Docket EPA-HQ-OAR-2010-0162

393 International Agency for Research on Cancer (1999) Monographs on the evaluation of carcinogenic risk of chemicals to humans, Volume 71, Re-evaluation of some organic chemicals, hydrazine and hydrogen peroxide and Volume 97 (in preparation), World Health Organization, Lyon, France. Docket EPA-HQ-OAR-2010-0162

394 U.S. Department of Health and Human Services (2005) National Toxicology Program 11th Report on Carcinogens available at: ntp.niehs.nih.gov/index.cfm?objectid=32BA9724-F1F6-975E-7FCE50709CB4C932. Docket EPA-HQ-OAR-2010-0162Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 377 of 768 carcinogenesis are unknown; however, the scientific evidence strongly suggests that the carcinogenic effects are mediated by genotoxic metabolites. Animal data suggest that females may be more sensitive than males for cancer effects associated with 1,3-butadiene exposure;
there are insufficient data in humans from which to draw conclusions about sensitive subpopulations. 1,3-butadiene also causes a variety of reproductive and developmental effects in mice; no human data on these effects are availa ble. The most sensitive effect was ovarian atrophy observed in a lifetime bioassay of female mice. 395

iii. Formaldehyde

Since 1987, EPA has classified formaldehyde as a probable human carcinogen based on evidence in humans and in rats, mice, hamsters, and monkeys. 396 EPA is currently reviewing epidemiological data published since that time. For instance, research conducted by the National
Cancer Institute found an increased risk of nasopharyngeal cancer and lymphohematopoietic malignancies such as leukemia among workers exposed to formaldehyde. 397, 398 In an analysis of the lymphohematopoietic cancer mortality from an extended follow-up of these workers, the
National Cancer Institute confirmed an associ ation between lymphohematopoietic cancer risk and peak exposures. 399 A National Institute of Occupational Safety and Health study of garment workers also found increased risk of death due to leukemia among workers exposed to formaldehyde. 400 Extended follow-up of a cohort of British chemical workers did not find evidence of an increase in nasopharyngeal or lymphohematopoietic cancers, but a continuing statistically significant excess in lung cancers was reported. 401 In 2006, the IARC re-classified formaldehyde as a human carcinogen (Group 1). 402

Formaldehyde exposure also causes a range of noncancer health effects, including irritation of the eyes (burning and watering of th e eyes), nose and throat. Effects from repeated

395 Bevan, C.; Stadler, J.C.; Elliot, G.S.; et al. (1996) Subc hronic toxicity of 4-vinylcyclohexene in rats and mice by inhalation. Fundam. Appl. Toxicol. 32:1-10. Docket EPA-HQ-OAR-2010-0162.

396 U.S. EPA (1987) Assessment of Health Risks to Garm ent Workers and Certain Home Residents from Exposure to Formaldehyde, Office of Pesticides and Toxic Substances, April 1987. Docket EPA-HQ-OAR-2010-0162.

397 Hauptmann, M..; Lubin, J. H.; Stewart, P. A.; Hayes, R. B.; Blair, A. 2003. Mortality from lymphohematopoetic malignancies among workers in formaldehyde industries. Journal of the National Cancer Institute 95: 1615-1623. Docket EPA-HQ-OAR-2010-0162.

398 Hauptmann, M..; Lubin, J. H.; Stewart, P. A.; Hayes, R. B.; Blair, A. 2004. Mortality from solid cancers amongworkers in formaldehyde industries. American Journal of Epidemiology 159: 1117-1130. Docket EPA-HQ-OAR2010-0162.

399 Beane Freeman, L. E.; Blair, A.; Lubin, J. H.; Stewart, P. A.; Hayes, R. B.; Hoover, R. N.; Hauptmann, M. 2009. Mortality from lymphohematopoietic malignancies among work ers in formaldehyde industries: The National Cancer Institute cohort. J. National Cancer Inst. 101: 751-761. Docket EPA-HQ-OAR-2010-0162.

400 Pinkerton, L. E. 2004. Mortality among a cohort of garment workers exposed to formaldehyde: an update. Occup. Environ. Med. 61: 193-200. Docket EPA-HQ-OAR-2010-0162.

401 Coggon, D, EC Harris, J Poole, KT Palmer. 2003. Exte nded follow-up of a cohort of British chemical workers exposed to formaldehyde. J National Cancer Inst. 95:1608-1615. Docket EPA-HQ-OAR-2010-0162.

402 International Agency for Research on Cancer. 2006. Fo rmaldehyde, 2-Butoxyethanol and 1-tert-Butoxypropan-2- ol. Volume 88. (in preparation), World Health Organization, Lyon, France. Docket EPA-HQ-OAR-2010-0162Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 378 of 768 exposure in humans include respiratory tract irri tation, chronic bronchitis and nasal epithelial lesions such as metaplasia and loss of cilia. An imal studies suggest that formaldehyde may also cause airway inflammation – including eosinophil in filtration into the airways. There are several studies that suggest that formaldehyde may increase the risk of asthma – particularly in the

young. 403,404

iv. Acetaldehyde

Acetaldehyde is classified in EPA’s IRIS database as a probable human carcinogen,
based on nasal tumors in rats, and is considered toxic by the inhalation, oral, and intravenous

routes. 405 Acetaldehyde is reasonably anticipated to be a human carcinogen by the U.S. DHHS
in the 11 th Report on Carcinogens and is classified as possibly carcinogenic to humans (Group 2B) by the IARC. 406,407 EPA is currently conducting a reassessment of cancer risk from inhalation exposure to acetaldehyde.

The primary noncancer effects of exposure to acetaldehyde vapors include irritation of the eyes, skin, and respiratory tract. 408 In short-term (4 week) rat studies, degeneration of olfactory epithelium was observed at various concentration levels of acetaldehyde exposure. 409,

410 Data from these studies were used by EPA to develop an inhalation reference concentration. Some asthmatics have been shown to be a sensitive subpopulation to decrements in functional expiratory volume (FEV1 test) and bronchoconstriction upon acetaldehyde inhalation. 411 The

403 Agency for Toxic Substances and Disease Registry (ATSDR). 1999. Toxicological profile for Formaldehyde. Atlanta, GA: U.S. Department of Health a nd Human Services, Public Health Service. http://www.atsdr.cdc.gov/toxprofiles/tp11 1.html Docket EPA-HQ-OAR-2010-0162.

404 WHO (2002) Concise International Chemical Assessmen t Document 40: Formaldehyde. Published under the joint sponsorship of the United Nations Environment Programme, the International Labour Organization, and the World Health Organization, and produced within the frame work of the Inter-Organization Programme for the Sound Management of Chemicals. Geneva. Docket EPA-HQ-OAR-2010-0162.

405 U.S. EPA. 1991. Integrated Risk Information System File of Acetaldehyde. Research and Development, National Center for Environmental Assessment, Washington, DC. Available at http://www.epa.gov/iris/subst/0290.htm. Docket EPA-HQ-OAR-2010-0162.

406 U.S. Department of Health and Human Services National Toxicology Program 11th Report on Carcinogensavailable at: ntp.niehs.nih.gov/index.cfm?objectid=32BA9724-F1F6-975E-7FCE50709CB4C932. Docket EPA-HQOAR-2010-0162.

407 International Agency for Research on Cancer. 1999. Re -evaluation of some organic chemicals, hydrazine, and hydrogen peroxide. IARC Monographs on the Evaluation of Carcinogenic Risk of Chemical to Humans, Vol 71. Lyon, France. Docket EPA-HQ-OAR-2010-0162

408 See Integrated Risk Information System File of Acetaldehyde, Note 405, above.

409 Appleman, L. M., R. A. Woutersen, V. J. Feron, R. N. Hooftman, and W. R. F. Notten. 1986. Effects of the variable versus fixed exposure levels on the toxicity of acetaldehyde in rats. J. Appl. Toxicol. 6: 331-336. Docket EPA-HQ-OAR-2010-0162

410 Appleman, L.M., R.A. Woutersen, and V.J. Feron. 1982. Inhalation toxicity of acetaldehyde in rats. I. Acute and subacute studies. Toxicology. 23: 293-297. Docket EPA-HQ-OAR-2010-0162.

411 Myou, S.; Fujimura, M.; Nishi K.; Ohka, T.; and Ma tsuda, T. 1993. Aerosolized acetaldehyde induces histamine-mediated bronchoconstriction in asthmatics. Am. Rev. Respir.Dis. 148(4 Pt 1): 940-3. Docket EPA-HQOAR-2010-0162Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 379 of 768 agency is currently conducting a reassessment of the health hazards from inhalation exposure to acetaldehyde.

v. Acrolein

Acrolein is extremely acrid and irritating to humans when inhaled, with acute exposure resulting in upper respiratory tract irritation, mucus hypersecretion and congestion. The intense irritancy of this carbonyl has been demonstrated during controlled tests in human subjects, who suffer intolerable eye and nasal mucosal sensory reactions within minutes of exposure. 412 These data and additional studies regarding acute effects of human exposure to acrolein are
summarized in EPA’s 2003 IRIS Human Health Assessment for acrolein. 413 Evidence available from studies in humans indicate that levels as low as 0.09 ppm (0.21 mg/m 3 ) for five minutes may elicit subjective complaints of eye irritation with increasing concentrations leading to more extensive eye, nose and respiratory symptoms. 414 Lesions to the lungs and upper respiratory tract of rats, rabbits, and hamsters have been observed after subchronic exposure to acrolein. 415 Acute exposure effects in animal studies report bronchial hyper-responsiveness. 416 In one study, the acute respiratory irritant effects of exposure to 1.1 ppm acrolein were more pronounced in mice with allergic airway disease by comparison to non-diseased mice which also showed decreases in respiratory rate. 417 Based on these animal data and demonstration of similar effects in humans (e.g., reduction in respiratory rate), individu als with compromised respiratory function (e.g., emphysema, asthma) are expected to be at increased risk of developing adverse responses to strong respiratory irritants such as acrolein.

EPA determined in 2003 that the human carcinogenic potential of acrolein could not be determined because the available data were inadequate. No information was available on the carcinogenic effects of acrolein in humans and the animal data provided inadequate evidence of

412 U.S. EPA (U.S. Environmental Protection Agency). (2003) Toxicological review of acrolein in support of summary information on Integrated Risk Information System (IRIS) National Center for Environmental Assessment, Washington, DC. EPA/635/R-03/003. p. 10. Available online at: http://www.epa.gov/ncea/iris/toxreviews/0364tr.pdf . Docket EPA-HQ-OAR-2010-0162

413 See U.S. EPA 2003 Toxicological review of acrolein, Note 412, above.

414 See U.S. EPA 2003 Toxicological review of acrolein, Note 412, at p. 11.

415 Integrated Risk Information System File of Acrolein. Office of Research and Development, National Center for Environmental Assessment, Washington, DC. This material is available at http://www.epa.gov/iris/subst/0364.htm Docket EPA-HQ-OAR-2010-0162.

416 See U.S. 2003 Toxicological review of acrolein, Note 412, at p. 15.

417 Morris JB, Symanowicz PT, Olsen JE, et al. 2003. Immedi ate sensory nerve-mediated respiratory responses to irritants in healthy and allergic airway-diseased mi ce. J Appl Physiol 94(4):1563-1571. Docket EPA-HQ-OAR2010-0162.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 380 of 768 carcinogenicity. 418 The IARC determined in 1995 that acrolein was not classifiable as to its carcinogenicity in humans. 419

vi. Polycyclic Organic Matter

The term polycyclic organic matter (POM) defines a broad class of compounds that includes the polycyclic aromatic hydrocarbon compounds (PAHs). One of these compounds, naphthalene, is discussed separately below. POM compounds are formed primarily from combustion and are present in the atmosphere in gas and particulate form. Cancer is the major concern from exposure to POM. Epidemiologic studies have reported an increase in lung cancer in humans exposed to diesel exhaust, coke oven emissions, roofing tar emissions, and cigarette smoke; all of these mixtures contain POM compounds. 420421 Animal studies have reported respiratory tract tumors from inhalation exposure to benzo[a]pyrene and alimentary tract and liver tumors from oral exposure to benzo[a]pyrene. In 1997 EPA classified seven PAHs (benzo[a]pyrene, benz[a]anthracene, chrysene, benzo[b]fluoranthene, benzo[k]fluoranthene, dibenz[a,h]anthracene, and indeno[1,2,3-cd]pyrene) as Group B2, probable human carcinogens. 422 Since that time, studies have found that maternal exposures to PAHs in a population of pregnant women were associated with several adverse birth outcomes, including low birth weight and reduced length at birth, as well as impaired cognitive development in preschool children (3 years of age). 423,424 EPA has not yet evaluated these studies.

vii. Naphthalene

Naphthalene is found in small quantities in gasoline and diesel fuels. Naphthalene emissions have been measured in larger quantities in both gasoline and diesel exhaust compared with evaporative emissions from mobile sour ces, indicating it is primarily a product of

418 U.S. EPA. 2003. Integrated Risk Information System Fi le of Acrolein. Research and Development, National Center for Environmental Assessment, Washington, DC. This material is available at http://www.epa.gov/iris/subst/0364.htm Docket EPA-HQ-OAR-2010-0162.

419 International Agency for Research on Cancer. 1995. Monographs on the evaluation of carcinogenic risk of chemicals to humans, Volume 63. Dry cl eaning, some chlorinated solvents and other industrial chemicals, World Health Organization, Lyon, Fran ce. Docket EPA-HQ-OAR-2010-0162

420 Agency for Toxic Substances and Disease Registry (ATSDR). 1995. Toxicological profile for Polycyclic Aromatic Hydrocarbons (PAHs). Atlanta, GA: U.S. Depa rtment of Health and Human Services, Public Health Service. Available electronically at http://www .atsdr.cdc.gov/ToxProfile s/TP.asp?id=122&tid=25.

421 U.S. EPA (2002). Health Assessment Document for Diesel Engine Exhaust . EPA/600/8-90/057F Office of Research and Development, Washington DC. http://cfpub.epa.gov/ncea/cfm/reco rdisplay.cfm?deid=29060. Docket EPA-HQ-OAR-2010-0162

422 U.S. EPA (1997). Integrated Risk Information System File of indeno(1,2,3-cd)pyrene. Research and Development, National Center for Environmental Assess ment, Washington, DC. This material is available electronically at http://www.ep a.gov/ncea/iris/subst/0457.htm.

423 Perera, F.P.; Rauh, V.; Tsai, W-Y.; et al. (2002) Effect of transplacental exposure to environmental pollutants on birth outcomes in a multiethnic population. Environ Health Perspect. 111: 201-205.

424 Perera, F.P.; Rauh, V.; Whyatt, R.M.; Tsai, W.Y.; Tang, D.; Diaz, D.; Hoepner, L.; Barr, D.; Tu, Y.H.; Camann, D.; Kinney, P. (2006) Effect of prenatal exposure to airborne polycyclic aromatic hydrocarbons on neurodevelopment in the first 3 years of life among inner- city children. Environ Health Perspect 114: 1287-1292.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 381 of 768 combustion. EPA released an external review draft of a reassessment of the inhalation carcinogenicity of naphthalene based on a number of recent animal carcinogenicity studies. 425
The draft reassessment completed external peer review. 426 Based on external peer review comments received, additional analyses are being undertaken. This external review draft does not represent official agency opinion and was released solely for the purposes of external peer review and public comment. The National Toxicology Program listed naphthalene as "reasonably anticipated to be a human carcinogen" in 2004 on the basis of bioassays reporting clear evidence of carcinogenicity in rats and some evidence of carcinogenicity in mice. 427
California EPA has released a new risk assessment for naphthalene, and the IARC has reevaluated naphthalene and re-classified it as Group 2B: possibly carcinogenic to humans. 428
Naphthalene also causes a number of chronic non- cancer effects in animals, including abnormal cell changes and growth in respiratory and nasal tissues. 429

viii. Other Air Toxics

In addition to the compounds described above, other compounds in gaseous hydrocarbon and PM emissions from light-duty vehicles will be affected by this propos al. Mobile source air toxic compounds that would potentially be impacted include ethylbenzene, propionaldehyde, toluene, and xylene. Information regarding the health effects of these compounds can be found
in EPA’s IRIS database. 430

f. Exposure and Health Effects Associat ed with Traffic-Related Air Pollution

Populations who live, work, or attend school near major roads experience elevated exposure to a wide range of air pollutants, as well as higher risks for a number of adverse health effects. While the previous sections of this preamble have focused on the health effects associated with individual criteria pollutants or ai r toxics, this section discusses the mixture of different exposures near major roadways, rather than the effects of any single pollutant. As such,

425 U. S. EPA. 2004. Toxicological Review of Naphthalene (Reassessment of the Inhalation Cancer Risk), Environmental Protection Agency, Inte grated Risk Information System, Research and Development, National Center for Environmental Assessment, Washington, DC. This material is available electronically at http://www.epa.gov/iris/subst/0436.htm. Docket EPA-HQ-OAR-2010-0162.

426 Oak Ridge Institute for Science and Education. (2004). External Peer Review for the IRIS Reassessment of the Inhalation Carcinogenicity of Naphthalene. August 2004. http://cfpub.epa.gov/ncea/cfm/r ecordisplay.cfm?deid=84403 Do cket EPA-HQ-OAR-2010-0162.

427 National Toxicology Program (NTP). (2004). 11th Report on Carcinogens. Public Health Service, U.S. Department of Health and Human Services, Re search Triangle Park, NC. Available from: http://ntpserver.niehs.nih.gov . Docket EPA-HQ-OAR-2010-0162.

428 International Agency for Research on Cancer. (2002). Monographs on the Evaluation of the Carcinogenic Risk of Chemicals for Humans. Vol. 82. Lyon, France. Docket EPA-HQ-OAR-2010-0162.

429 U. S. EPA. 1998. Toxicological Review of Naphthalene , Environmental Protection Agency, Integrated Risk Information System, Research and Development, National Center for Environmental Assessment, Washington, DC. This material is available electronically at http://w ww.epa.gov/iris/subst/0436.htm Docket EPA-HQ-OAR-2010-
0162.

430 U.S. EPA Integrated Risk Information System (IRI S) database is available at: www.epa.gov/irisSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 382 of 768 this section emphasizes traffic-related air polluti on, in general, as the relevant indicator of exposure rather than any particular pollutant.

Concentrations of many traffic-generated air pollutants are elevated for up to 300-500 meters downwind of roads with high traffic volumes. 431 Numerous sources on roads contribute to elevated roadside concentrations, includi ng exhaust and evaporative emissions, and resuspension of road dust and tire and brake wear. Concentrations of several criteria and hazardous air pollutants are elevated near major roads. Furthermore, different semi-volatile organic compounds and chemical components of particulate matter, including elemental carbon, organic material, and trace metals, have been reported at higher concentrations near major roads.

Populations near major roads experience greater risk of certain adverse health effects. The Health Effects Institute published a report on the health effects of traffic-related air pollution. 432 It concluded that evidence is “sufficient to infer the presence of a causal association” between traffic exposure and exacerbation of childhood asthma symptoms. The HEI report also concludes that the evidence is either “sufficient” or “suggestive but not
sufficient” for a causal association between tra ffic exposure and new childhood asthma cases. A review of asthma studies by Salam et al. (2008) reaches similar conclusions. 433 The HEI report also concludes that there is “suggestive” evidence for pulmonary function deficits associated with traffic exposure, but concluded that there is “inadequate and insufficient” evidence for causal associations with respir atory health care utilization, adult-onset asthma, chronic obstructive pulmonary disease symptoms, and allergy. A review by Holguin (2008) notes that the effects of traffic on asthma may be modified by nutrition status, medication use, and genetic
factors. 434

The HEI report also concludes that evidence is “suggestive” of a causal association between traffic exposure and all-cause and cardiovascular mortality. There is also evidence of an association between traffic-related air pollutant s and cardiovascular effects such as changes in heart rhythm, heart attack, and cardiovascular disease. The HEI report characterizes this evidence as “suggestive” of a causal association, and an independent epidemiological literature

431 Zhou, Y.; Levy, J.I. (2007) Factors influencing the spatia l extent of mobile source air pollution impacts: a metaanalysis. BMC Public Health 7: 89. doi:10.1186/1471-2458-7-89 Docket EPA-HQ-OAR-2010-0162.

432 HEI Panel on the Health Effects of Air Pollution. (2010) Traffic-related air pollution: a critical review of the literature on emissions, exposure, and health effects. [Online at www.healtheffects.org ] Docket EPA-HQ-OAR2010-0162.

433 Salam, M.T.; Islam, T.; Gilliland, F.D. (2008) Recent evidence for adverse effects of residential proximity to traffic sources on asthma. Current Opin Pulm Med 14: 3-8. Docket EPA-HQ-OAR-2010-0162

434 Holguin, F. (2008) Traffic, outdoor air pollution, and asthma. Immunol Allergy Clinics North Am 28: 577-588. Docket EPA-HQ-OAR-2010-0162.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 383 of 768 review by Adar and Kaufman (2007) concludes that there is “consistent evidence” linking traffic-related pollution and adverse cardiovascular health outcomes. 435

Some studies have reported associations be tween traffic exposure and other health effects, such as birth outcomes (e.g., low bi rth weight) and childhood cancer. The HEI report concludes that there is currently “inadequate and insufficient” evidence for a causal association between these effects and traffic exposure. A review by Raaschou-Nielsen and Reynolds (2006)
concluded that evidence of an association be tween childhood cancer and traffic-related air pollutants is weak, but noted the inability to draw firm conclusions based on limited evidence. 436

There is a large population in the United States living in close proximity of major roads. According to the Census Bureau’s American Housing Survey for 2007, approximately 20 million residences in the United States, 15.6% of all ho mes, are located within 300 feet (91 m) of a highway with 4+ lanes, a railroad, or an airport. 437 Therefore, at current population of approximately 309 million, assuming that populat ion and housing are similarly distributed, there are over 48 million people in the United States living near such sources. The HEI report also notes that in two North American cities, Los Angeles and Toronto, ov er 40% of each city’s population live within 500 meters of a highway or 100 meters of a major road. It also notes that about 33% of each city’s population resides within 50 meters of major roads. Together, the evidence suggests that a large U.S. population live s in areas with elevated traffic-related air pollution.

People living near roads are often socioeconomically disadvantaged. According to the2007 American Housing Survey, a renter-occupied property is over twice as likely as an owneroccupied property to be located near a highway with 4+ lanes, railroad or airport. In the same survey, the median household income of rental housing occupants was less than half that of owner-occupants ($28,921/$59,886). Numerous studies in individual urban areas report higher levels of traffic-related air pollutants in areas with high minority or poor populations. 438,439,440

435 Adar, S.D.; Kaufman, J.D. (2007) Cardiovascular di sease and air pollutants: evaluating and improving epidemiological data implicating traffic exposure. Inhal Toxicol 19: 135-149. Docket EPA-HQ-OAR-2010-0162.

436 Raaschou-Nielsen, O.; Reynolds, P. (2006) Air pollution and childhood cancer: a review of the epidemiological literature. Int J Cancer 118: 2920-2929. Docket EPA-HQ-OAR-2010-0162

437 U.S. Census Bureau (2008) American Housing Survey for the United States in 2007. Series H-150 (National Data), Table 1A-7. [Accessed at http://www.census. gov/hhes/www/housing/ahs/ahs07/ ahs07.html on January 22, 2009] Docket EPA- HQ-OAR-2010-0162.

438 Lena, T.S.; Ochieng, V.; Carter, M.; Holguín-Veras, J.; Kinney, P.L. (2002) Elemental carbon and PM2.5 levels in an urban community heavily impacted by truck traffic. Environ Health Perspect 110: 1009-1015. Docket EPAHQ-OAR-2010-0162

439 Wier, M.; Sciammas, C.; Seto, E.; Bhatia, R.; Rivard, T. (2009) Health, traffic, and environmental justice: collaborative research and community action in San Franci sco, California. Am J Public Health 99: S499-S504. Docket EPA-HQ-OAR-2010-0162

440 Forkenbrock, D.J. and L.A. Schweitzer, Envir onmental Justice and Transportation Investment Policy . Iowa City: University of Iowa, 1997. Docket EPA-HQ-OAR-2010-0162Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 384 of 768 Students may also be exposed in situations where schools are located near major roads. In a study of nine metropolitan areas across the United States, Appatova et al. (2008) found that on average greater than 33% of schools were located within 400 m of an Interstate, U.S., or state highway, while 12% were located within 100 m. 441 The study also found that among the metropolitan areas studied, schools in the Eastern United States were more often sited near major roadways than schools in the Western United States.

Demographic studies of students in schools near major roadways suggest that this population is more likely than the general student population to be of non-white race or Hispanic ethnicity, and more often live in low socioeconomic status locations. 442,443,444 There is some inconsistency in the evidence, which may be du e to different local development patterns and measures of traffic and geographic scale used in the studies. 441

3. Environmental Effects of Non-GHG Pollutants

In this section we discuss some of the envi ronmental effects of PM and its precursors such as visibility impairment, atmospheric deposi tion, and materials damage and soiling, as well as environmental effects associated with the presence of ozone in the ambient air, such as impacts on plants, including trees, agronomic cr ops and urban ornamentals, and environmental
effects associated with air toxics.

a. Visibility

Visibility can be defined as the degree to which the atmosphere is transparent to visible light. 445 Visibility impairment is caused by light scattering and absorption by suspended particles and gases. Visibility is important because it has direct significance to people’s enjoyment of daily activities in a ll parts of the country. Individuals value good visibility for the well-being it provides them directly, where they live and work, and in places where they enjoy recreational opportunities. Visibility is also high ly valued in significant natural areas, such as

441 Appatova, A.S.; Ryan, P.H.; LeMasters, G.K.; Grinshpun, S.A. (2008) Proximal exposure of public schools and students to major roadways: a nationwide U.S. survey. J Environ Plan Mgmt Docket EPA-HQ-OAR-2010-0162

442 Green, R.S.; Smorodinsky, S.; Kim, J.J.; McLaughlin, R.; Ostro, B. (2004) Proximity of California public schools to busy roads. Environ Health Perspect 112: 61-66. Docket EPA-HQ-OAR-2010-0162

443 Houston, D.; Ong, P.; Wu, J.; Winer, A. (2006) Proximity of licensed child care facilities to near-roadway vehicle pollution. Am J Public Health 96: 1611-1617. Docket EPA-HQ-OAR-2010-0162

444 Wu, Y.; Batterman, S. (2006) Proximity of schools in De troit, Michigan to automobile and truck traffic. J Exposure Sci Environ Epidemiol 16: 457-470. Docket EPA-HQ-OAR-2010-0162

445 National Research Council, 1993. Protecting Visibility in National Parks and Wilderness Areas. National Academy of Sciences Committee on Haze in National Parks and Wilderness Areas. National Academy Press, Washington, DC. Docket EPA-HQ-OAR-2010-0162. This book can be viewed on the National Academy Press Website at http://www.nap. edu/books/0309048443/html/Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 385 of 768 national parks and wilderness areas, and special emph asis is given to protecting visibility in these areas. For more information on visibility see the final 2009 PM ISA. 446

EPA is pursuing a two-part strategy to address visibility impairment. First, EPA developed the regional haze program (64 FR 35714) which was put in place in July 1999 to protect the visibility in Mandatory Class I Federal areas. There are 156 national parks, forests and wilderness areas categorized as Mandatory Class I Federal areas (62 FR 38680-38681, July 18, 1997). These areas are defined in CAA sec tion 162 as those national parks exceeding 6,000 acres, wilderness areas and memorial parks excee ding 5,000 acres, and all international parks which were in existence on August 7, 1977. Second, EPA has concluded that PM 2.5 causes adverse effects on visibility in other areas that are not protected by the Regional Haze Rule, depending on PM 2.5 concentrations and other factors th at control their visibility impact effectiveness such as dry chemical composition a nd relative humidity (i.e., an indicator of the water composition of the particles), and has set secondary PM 2.5 standards to address these areas. The existing annual primary and secondary PM 2.5 standards have been remanded and are being addressed in the currently ongoing PM NAAQS review.

b. Plant and Ecosystem Effects of Ozone

Elevated ozone levels contribute to environmental effects, with impacts to plants and ecosystems being of most concern. Ozone can produce both acute and chronic injury in sensitive species depending on the concentration level and the duration of the exposure. Ozone effects also tend to accumulate over the growing season of the plant, so that even low concentrations experienced for a longer duration have the potenti al to create chronic stress on vegetation. Ozone damage to plants includes visible injury to leaves and impaired photosynthesis, both of which can lead to reduced plant growth and reproduction, resulting in reduced crop yields, forestry production, and use of sensitive ornamentals in landscaping. In addition, the impairment of photosynthesis, the process by which the plant makes carbohydrates (its source of energy and food), can lead to a subsequent reduction in root growth and carbohydrate storage below ground, resulting in other, more subtle plant and ecosystems impacts.

These latter impacts include increased susceptibil ity of plants to insect attack, disease, harsh weather, interspecies competition and overall decreased plant vigor. The adverse effects of ozone on forest and other natural vegetation can potentially lead to species shifts and loss from the affected ecosystems, resulting in a loss or reduction in associated ecosystem goods and services. Lastly, visible ozone injury to leaves can result in a loss of aesthetic value in areas of special scenic significance like national parks a nd wilderness areas. The final 2006 Ozone Air Quality Criteria Document presents more detailed information on ozone effects on vegetation and ecosystems.

446 See U.S. EPA 2009 Final PM ISA, Note 362.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 386 of 768 c. Atmospheric Deposition

Wet and dry deposition of ambient particulate matter delivers a complex mixture of metals (e.g., mercury, zinc, lead, nickel, aluminum, cadmium), organic compounds (e.g., polycyclic organic matter, dioxins, furans) and inorganic compounds (e.g., nitrate, sulfate) to terrestrial and aquatic ecosystems. The chemical form of the compounds deposited depends on a variety of factors including ambi ent conditions (e.g., temperature, humidity, oxidant levels) and the sources of the material. Chemical and physical transformations of the compounds occur in the atmosphere as well as the media onto which they deposit. These transformations in turn influence the fate, bioavailability and potential toxicity of these compounds. Atmospheric deposition has been identified as a key component of the environmental and human health hazard posed by several pollutants including mercury, dioxin and PCBs. 447

Adverse impacts on water quality can occur when atmospheric contaminants deposit to the water surface or when material deposited on the land enters a waterbody through runoff. Potential impacts of atmospheric deposition to waterbodies include those related to both nutrient and toxic inputs. Adverse effects to human health and welfare can occur from the addition of excess nitrogen via atmospheric deposition. Th e nitrogen-nutrient enrichment contributes to toxic algae blooms and zones of depleted oxygen, which can lead to fish kills, frequently in coastal waters. Deposition of heavy metals or ot her toxics may lead to the human ingestion of contaminated fish, impairment of drinking water, damage to freshwater and marine ecosystem components, and limits to recreational uses. Several studies have been conducted in U.S. coastal waters and in the Great Lakes Region in which the role of ambient PM deposition and runoff is investigated. 448,449,450,451,452

Atmospheric deposition of nitrogen and sulf ur contributes to acidification, altering biogeochemistry and affecting animal and plant li fe in terrestrial and aquatic ecosystems across the United States. The sensitivity of terrestria l and aquatic ecosystems to acidification from nitrogen and sulfur deposition is predominantly governed by geology. Prolonged exposure to

447 U.S. EPA (2000) Deposition of Air Pollutants to th e Great Waters: Third Report to Congress. Office of Air Quality Planning and Standards. EPA-453/R-00-0005. Docket EPA-HQ-OAR-2010-0162.

448 U.S. EPA (2004) National Coastal Condition Report II. Office of Research and Development/ Office of Water. EPA-620/R-03/002. Docket EPA-HQ-OAR-2010-0162.

449 Gao, Y., E.D. Nelson, M.P. Field, et al. 2002. Characterization of atmospheric trace elements on PM2.5 particulate matter over the New York-New Jersey harbor estuary. Atmos. Environ. 36: 1077-1086. Docket EPAHQ-OAR-2010-0162.

450 Kim, G., N. Hussain, J.R. Scudlark, and T.M. Church . 2000. Factors influencing the atmospheric depositional fluxes of stable Pb, 210Pb, and 7Be into Chesapeake Bay. J. Atmos. Chem. 36: 65-79. Docket EPA-HQ-OAR2010-0162.

451 Lu, R., R.P. Turco, K. Stolzenbach, et al. 2003. Dry deposition of airborne trace metals on the Los Angeles Basin and adjacent coastal waters. J. Geophys. Res. 108(D2, 4074): AAC 11-1 to 11-24. Docket EPA-HQ-OAR2010-0162.

452 Marvin, C.H., M.N. Charlton, E.J. Reiner, et al. 2002. Surficial sediment contamination in Lakes Erie and Ontario: A comparative analysis. J. Great Lakes Res. 28(3): 437-450. Docket EPA-HQ-OAR-2010-0162.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 387 of 768 excess nitrogen and sulfur deposition in sensitiv e areas acidifies lakes, rivers and soils. Increased acidity in surface waters creates inho spitable conditions for biota and affects the abundance and nutritional value of preferred pr ey species, threatening biodiversity and ecosystem function. Over time, acidifying de position also removes essential nutrients from forest soils, depleting the capacity of soils to neutralize future acid loadings and negatively affecting forest sustainability. Major effects in clude a decline in sensitive forest tree species, such as red spruce ( Picea rubens ) and sugar maple ( Acer saccharum ), and a loss of biodiversity of fishes, zooplankton, and macro invertebrates.

In addition to the role nitrogen deposition play s in acidification, nitrogen deposition also leads to nutrient enrichment and altered biogeoche mical cycling. In aquatic systems increased nitrogen can alter species assemblages and cause eutrophication. In terrestrial systems nitrogen loading can lead to loss of nitr ogen sensitive lichen species, decreas ed biodiversity of grasslands, meadows and other sensitive habitats, and increased potential for invasive species. For a broader explanation of the topics treated here, refer to the description in Section 6.1.2.2 of the RIA.

Adverse impacts on soil chemistry and plant life have been observed for areas heavily influenced by atmospheric deposition of nutrients, metals and acid species, resulting in species shifts, loss of biodiversity, forest decline, damage to forest productivity and reductions in ecosystem services. Potential impacts also include adverse effects to human health through ingestion of contaminated vegetation or livestock (as in the case for dioxin deposition), reduction in crop yield, and limited use of land due to contamination.

Atmospheric deposition of pollutants can reduce the aesthetic appeal of buildings and culturally important articles through soiling, and can contribute directly (or in conjunction with other pollutants) to structural damage by means of corrosion or erosion. Atmospheric deposition may affect materials principally by promoti ng and accelerating the corrosion of metals, by degrading paints, and by deteriorating building materials such as concrete and limestone.
Particles contribute to these effects because of their electrolytic, hygroscopic, and acidic properties, and their ability to adsorb corrosi ve gases (principally sulfur dioxide).

d. Environmental Effects of Air Toxics

Emissions from producing, transporting and co mbusting fuel contribute to ambient levels of pollutants that contribute to adverse effects on vegetation. Volatile organic compounds, some of which are considered air toxics, have long been suspected to play a role in vegetation damage. 453 In laboratory experiments, a wide range of tolerance to VOCs has been observed. 454

453 U.S. EPA. 1991. Effects of organic chemicals in the at mosphere on terrestrial plants. EPA/600/3-91/001. Docket EPA-HQ-OAR-2010-0162.

454 Cape JN, ID Leith, J Binnie, J Content, M Donkin, M Skewes, DN Price AR Brown, AD Sharpe. 2003. Effects of VOCs on herbaceous plants in an open-top chamber expe riment. Environ. Pollut. 124:341-343. Docket EPA-HQOAR-2010-0162.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 388 of 768 Decreases in harvested seed p od weight have been reported fo r the more sensitive plants, and some studies have reported effects on seed germination, flowering and fruit ripening. Effects of individual VOCs or their role in conjunction with other stressors (e.g., acidification, drought, temperature extremes) have not been well studied. In a recent study of a mixture of VOCs including ethanol and toluene on herbaceous plan ts, significant effects on seed production, leaf water content and photosynthetic efficiency were reported for some plant species. 455

Research suggests an adverse impact of vehicle exhaust on plants, which has in some cases been attributed to aromatic compounds and in other cases to nitrogen oxides. 456, 457, 458 The impacts of VOCs on plant reproduction may have long-term implications for biodiversity and survival of native species near major roadways. Most of the studies of the impacts of VOCs on vegetation have focused on short-term exposure and few studies have focused on long-term effects of VOCs on vegetation and the potential for metabolites of these compounds to affect
herbivores or insects.

4. Air Quality Impacts of Non-GHG Pollutants

a. Current Levels of Non-GHG Pollutants

This proposal may have impacts on ambient concentrations of criteria and air toxic pollutants. Nationally, levels of PM 2.5 , ozone, NO X , SO X , CO and air toxics are declining. 459
However, approximately 127 million people lived in counties that exceeded any NAAQS in

2008. 460 These numbers do not include the people living in areas where there is a future risk of failing to maintain or attain the NAAQS. It is important to note that these numbers do not account for potential ozone, PM 2.5 , CO, SO 2 , NO 2 or lead nonattainment areas which have not yet been designated. Further, the majority of Americans continue to be exposed to ambient concentrations of air toxics at levels which have the potential to cause adverse health
effects. 461,462 The levels of air toxics to which people are exposed vary depending on where

455 Cape JN, ID Leith, J Binnie, J Content, M Donkin, M Skewes, DN Price AR Brown, AD Sharpe. 2003. Effects of VOCs on herbaceous plants in an open-top chamber expe riment. Environ. Pollut. 124:341-343. Docket EPA-HQOAR-2010-0162.

456 Viskari E-L. 2000. Epicuticular wax of Norway spruce needles as indicator of traffic pollutant deposition. Water, Air, and Soil Pollut. 121:327-337. Docket EPA-HQ-OAR-2010-0162.

457 Ugrekhelidze D, F Korte, G Kvesitadze. 1997. Uptake and transformation of benzene and toluene by plant leaves. Ecotox. Environ. Safety 37:24-29. Docket EPA-HQ-OAR-2010-0162.

458 Kammerbauer H, H Selinger, R Rommelt, A Ziegler-Jons, D Knoppik, B Hock. 1987. Toxic components of motor vehicle emissions for the spruce Picea abies. E nviron. Pollut. 48:235-243. Docket EPA-HQ-OAR-2010-
0162.

459 U. S. EPA (2010) Our Nation’s Air: Status and Trends through 2008. Office of Air Quality Planning and Standards, Research Triangle Park, NC. Publication No . EPA 454/R-09-002. http://www.epa.gov/airtrends/2010/. Docket EPA-HQ-OAR-2010-0162

460 See U. S. EPA Trends, Note 459.

461 U. S. Environmental Protection Agency (2007). Control of Hazardous Air Pollutants from Mobile Sources; Final Rule. 72 FR 8434, February 26, 2007.

462 See U. S. EPA 2010, Light-Duty 2012-2016 MY Vehicle Rule.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 389 of 768 people live and work and the kinds of activities in which they engage, as discussed in detail in
U.S. EPA’s recent mobile source air toxics rule. 463

b. Impacts of Proposed Standards on Future Ambient Concentrations of PM 2.5 , Ozone and Air Toxics

Full-scale photochemical air quality modeling is necessary to accurately project levels of criteria pollutants and air toxics. For the final rulemaking, a national-scale air quality modeling analysis will be performed to analyze the impacts of the standards on PM 2.5 , ozone, and selected air toxics (i.e., benzene, formaldehyde, acetaldehyde, acrolein and 1,3-butadiene). The length of time needed to prepare the necessary emissions inventories, in addition to the processing time associated with the modeling itself, has precluded us from performing air quality modeling for this proposal.

Sections III.G.1 and III.G.2 of the preamble pres ent projections of the changes in criteria pollutant and air toxics emissions due to the pr oposed vehicle standards; the basis for those estimates is set out in Chapter 4 of the draft RI A. The atmospheric chemistry related to ambient
concentrations of PM 2.5 , ozone and air toxics is very complex, and making predictions based solely on emissions changes is extremely difficult. However, based on the magnitude of the emissions changes predicted to result from the proposed standards, EPA expects that there will be an improvement in ambient air quality, pending a more comprehensive analysis for the final rulemaking.

For the final rulemaking, EPA intends to use a Community Multi-scale Air Quality (CMAQ) modeling platform as the tool for the air quality modeling. The CMAQ modeling system is a comprehensive three-dimensional grid-based Eulerian air quality model designed to estimate the formation and fate of oxidant precursors, primary and secondary PM concentrations and deposition, and air toxics, over regional and urban spatial scales (e.g., over the contiguous United States). 464,465,466,467 The CMAQ model is a well-known and well-established tool and is commonly used by EPA for regulatory analyses and by States in developing attainment

463 See U. S. EPA 2007, Note 461.

464 U.S. Environmental Protection Agency, Byun, D.W., and Ching, J.K.S., Eds, 1999. Science algorithms of EPA Models-3 Community Multiscale Air Quality (CMAQ modeli ng system, EPA/600/R-99/030, Office of Research and Development). Docket EPA-HQ-OAR-2010-0162

465 Byun, D.W., and Schere, K.L., 2006. Review of the Gove rning Equations, Computational Algorithms, and Other Components of the Models-3 Community Multiscale Air Quality (CMAQ) Modeling System, J. Applied Mechanics Reviews, 59 (2), 51-77. Docket EPA-HQ-OAR-2010-0162

466 Dennis, R.L., Byun, D.W., Novak, J.H., Galluppi, K.J., Coats, C.J., and Vouk, M.A., 1996. The next generation of integrated air quality modeling: EPA’s Models-3, At mospheric Environment, 30, 1925-1938. Docket EPA-HQOAR-2010-0162

467 Carlton, A., Bhave, P., Napelnok, S., Edney, E., Sarwar, G., Pinder, R., Pouliot, G., and Houyoux, M. Model Representation of Secondary Organic Aerosol in CMAQv4.7. Ahead of Print in Environmental Science and Technology. Accessed at: http://pubs.acs.org/doi/abs/10.1021/es1 00636q?prevSearch=CMAQ&searchHistoryKey Docket EPA-HQ-OAR-2010-0162.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 390 of 768 demonstrations for their State Implementation Plans. The CMAQ model version 4.7 was most recently peer-reviewed in February of 2009 for the U.S. EPA. 468

CMAQ includes many science modules that simulate the emission, production, decay, deposition and transport of organic and inorganic gas-phase and particle-phase pollutants in the atmosphere. EPA intends to use the most recent version of CMAQ, which reflects updates to version 4.7 to improve the underlying science. These include aqueous chemistry mass conservation improvements, improved vertical convective mixing and lowered CB05 mechanism unit yields for acrolein from 1,3-butadiene tracer reactions which were updated to be consistent with laboratory measurements.

5. Other Unquantified Health and Environmental Effects

In addition, EPA seeks comment on whether there are any other health and environmental impacts associated with advancements in vehi cle GHG reduction technologies that should be considered. For example, the use of technologie s and other strategies to reduce GHG emissions could have effects on a vehicle’s life-cycle impact s (e.g., materials usage, manufacturing, end of life disposal), beyond the issues regarding ups tream emissions discussed in Section III.C. EPA seeks comment on any studies or research in this area that should be considered in the future to assess a fuller range of health and environmental impacts from the light-duty vehicle fleet moving to advanced GHG-reducing technologies.

EPA is aware of some studies examining the lifecycle GHG emissions for advanced technology vehicles, with a particular focus on production-related emissions. 469 The American Iron and Steel Institute (AISI) recommends that EP A transition in the longer-term to an approachof basing future standards on lifecycle assessments that include vehicle production, use, and endof-life impacts; AISI is working on related res earch with the University of California, Davis. 470
At this point, there is very little information about the lifecycle impacts of future advanced technologies to conduct such an assessment, but EPA seeks comment on any current or future studies and research underway on this topic.

468 Allen, D. et al (2009). Report on the Peer Review of the Atmospheric Modeling and Analysis Division, National Exposure Research Laboratory, Office of Research and Development, U.S.EPA. http://www.epa.gov/asmdnerl/peer/reviewdocs.html Docket EPA-HQ-OAR-2010-0162

469 Preparing for a Life Cycle CO2 Measure, Jane Patterson, et al, Ricardo Inc. for the Low Carbon Vehicle Partnership, August 2011 and Life Cycle Assessment of Greenhouse Gas Emissions from Plug-in Hybrid Vehicles: Implications for Policy , C. Samaras and K. Meisterling, Environmental Science & Technology Vol. 42, 3170-3176,
2008.

470 See AISI comments on the 2012-2016 rulemaking and Interim Joint TAR: Document ID # EPA-HQ-OAR-2009- 0472-7088 and EPA-HQ-OAR-2010-0799-0313, respectivelySummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 391 of 768 H. What are the Estimated Cost, Economic, and Other Impacts of the Proposal?

In this section, EPA presents the costs and im pacts of the proposed GHG standards. It is important to note that NHTSA’s CAFE standa rds and EPA’s GHG standards will both be in effect, and each will lead to aver age fuel economy increases and CO 2 emissions reductions. The two agencies’ standards comprise the National Program, and this discussion of costs and benefits of EPA’s GHG standard does not change the f act that both the CAFE and GHG standards, jointly, will be the source of the benefits and costs of the National Pr ogram. These costs and benefits are appropriately analyzed separately by each agency and should not be added together.

This section outlines the basis for assessing the benefits and costs of the GHG standards and provides estimates of these costs and benefits. Some of these effects are private, meaning that they affect consumers and producers directly in their sales, purchases, and use of vehicles. These private effects include the increase in vehicl e prices due to costs of the technology, fuel savings, and the benefits of additional driving and reduced refueling. Other costs and benefits affect people outside the markets for vehicles an d their use; these effects are termed external, because they affect people in ways other than the effect on the market for and use of new vehicles and are generally not taken into account by the purchaser of the vehicle. The external effects include the climate impacts, the effects on non-GHG pollutants, energy security impacts, and the effects on traffic, accidents, and noise due to additional driving. The sum of the private
and external benefits and costs is the net social benefits of the standards.

There is some debate about the behavior of private markets in the context of these standards: if consumers optimize their purcha ses of fuel economy, with full information and perfect foresight, in perfectly efficient market s, they should have already considered these benefits in their vehicle purchase decisions. If so, then no net private benefits would result from the program, because consumers would already bu y vehicles with the amount of fuel economy that is optimal for them; requiring additional fu el economy would alter both the purchase prices of new cars and their lifetime streams of oper ating costs in ways that will inevitably reduce consumers’ well-being. Section III.H.1 discusses this issue more fully.

The net benefits of EPA’s proposal consist of the effects of the proposed standards on:

 the vehicle costs;

 fuel savings associated with reduced fuel usage resulting from the proposed program

 greenhouse gas emissions;

 other air pollutants;

 other impacts, including noise, congestion, accidents,

 energy security impacts;

 changes in refueling events;

 increased driving due to the “rebound” effect.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 392 of 768 EPA also presents the cost per ton of GHG reductions associated with the proposed GHG
standards on a CO 2 eq basis, in Section III.H.3 below.

The total present value of monetized benefits (excluding fuel savings) under the proposed standards are projected to be between $334 to $846 billion, using a 3 percent discount rate and depending on the value used for the social cost of carbon. With a 7 percent discount rate, the total present value of monetized benefits (excluding fuel savings) under the proposed standards are projected to be between $147 to $660 billion, depending on the value used for the social cost
of carbon. These benefits are summarized below in Table III-3. The present value of costs of the proposed standards are estimated to be between $239 to $545 billion for new vehicle technology (assuming a 7 and 3 percent discount rate, respectively), less $600 to $1,600 billion in savings realized by consumers through fewer fuel expenditures (calculated using pre-tax fuel prices and using a 7 and 3 percent discount ra te, respectively). These costs are summarized below in Table III-1 and the fuel savings are su mmarized in Table III-2. The total net present value of benefits under the propos ed standards are projected to be between $1.4 and $1.9 trillion, using a 3 percent discount rate and depending on the value used for the social cost of carbon. With a 7 percent discount rate, the total net present value of benefits under the proposed standards are projected to be between $530 billio n to $1.0 trillion, depending on the value used for the social cost of carbon. The estimates developed here use as a baseline for comparison the greenhouse gas performance and fuel economy associated with MY 2016 standards. To the extent that greater fuel economy improvements than those assumed to occur under the baseline may have occurred due to market forces alone (absent these proposed standards), the analysis overestimates private and social net benefits.

While NHTSA and EPA each modeled their respective regulatory programs, the analyses were generally consistent and featured similar parameters. For this proposal, EPA has not conducted an overall uncertainty analysis of the impacts associated with its regulatory program, though it did conduct sensitivity analyses of in dividual components of the analysis (e.g., alternative SCC estimates. NHTSA, however, conducted a Monte Carlo simulation of the uncertainty associated with its regulatory pr ogram. The focus of the simulation model was variation around the chosen uncertainty parameters and their resulting impact on the key output parameters, fuel savings, and net benefits. Becau se of the similarities between the two analyses, EPA references NHTSA RIA Chapters X and XII as indicative of the relative magnitude, uncertainty and sensitivities of pa rameters of the cost/benefit an alysis. For the final rule, EPA plans to perform sensitivity analyses for a wider variety of parameters.

EPA has also analyzed the potential impact of this proposed rule on vehicle sales, employment, and the overall economy. The results of these analyses were not a factor that EPA considered in evaluating the appropriateness of the proposed GHG standards, nor did EPA include them in the analysis of overall costs and benefits of the proposed standards.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 393 of 768 Further information on these and other aspects of the economic impacts of EPA’s proposed rule are summarized in the following sections and are presented in more detail in the DRIA for this rulemaking. EPA requests comment on all aspects of the cost, savings, and benefits analysis presented here and in the DRIA. EPA also requests comment on the inputs used in these analyses as described in the Draft Joint TSD.

1. Conceptual Framework for Evaluating Consumer Impacts

For this proposed rule, EPA projects significan t private gains to consumers in three major areas: (1) reductions in spending on fuel, (2) for ga soline-fueled vehicles, time saved due to less refueling, and (3) additional driving that result s from the rebound effect. In combination, these private benefits, mostly from fuel savings, appear to outweigh the costs of the standards, even without accounting for externalities.

Admittedly, these findings pose an economic conundrum. On the one hand, assuming that they do not have high personal rates of discount, consumers are expected to gain significantly from the rules, as the increased cost of fuel efficient cars is smaller than the fuel savings. Yet many of these technologies are readily available; financially savvy consumers could have sought vehicles with improved fuel efficiency, and auto makers seeking those customers could have offered them. Assuming full information, perfect foresight, perfect competition, and financially rational consumers and producers, standard economic theory suggests that normal market operations would have provided the private net gains to consumers, and the only benefits of the rule would be due to external benefits. If our analysis projects net private benefits that consumers have not realized in this perfectly func tioning market, then, with the above assumptions, there must be additional co sts of these private net benefits that are not accounted for. This calculation assumes that consumers accurately predict and act on all the fuel-saving benefits they will get from a new vehicle, and that producers market products providing those benefits. The existence estimate of large private net benefits from this rule, then, suggests either that the assumptions noted above do not hold, or that EPA’s analysis has missed some factor(s) tied to improved fuel econom y that reduce(s) consumer welfare.

This subsection discusses the economic princi ples underlying the assessment of impacts on consumer well-being due to the proposed changes in the vehicles. Because conventional gasoline- and diesel-fueled vehicles have qui te different characteristics from advanced technology vehicles (especially electric vehicles), the principles for these different kinds vehicles are discussed separately below.

a. Conventional Vehicles

For conventional vehicles, the estimates of technology costs developed for this proposed
rule take into account the cost needed to ensu re that vehicle utility (including performance, reliability, and size) stay constant, except for fuel economy and vehicle price, with some minorSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 394 of 768 exceptions (e.g., see the discussion of the “Atkinson-cycle” engine and towing capacity in III.D.3). For example, using a 4-cylinder engine instead of a 6-cylinder engine reduces fuel economy, but also reduces performance; turbocharging the 4-cylinder engine, though, produces fuel savings while maintaining performance. The cost estimates assume turbocharging accompanies engine downsizing. As a result, if the market for fuel economy is efficient and
these cost estimates are correct , then the existence of large privat e net benefits implies that there would need to be some other changed qualities, missed in the cost estimates, that would reduce
the benefits consumers receive from their vehicles. 471 We seek comments that identify any such changed qualities omitted from the analysis. Such comments should describe how changed qualities affect consumer benefits from vehicles , and provide cost estimates for eliminating the effects of the changes.

The central conundrum observed in this market, that consumers appear not to purchase products that are in their economic self-interest, has been referred to as the Energy Paradox in this setting (and in several others). 472 There are many possible reasons discussed in academic research why this might occur: 473

 Consumers might be “myopic” and hence undervalue future fuel savings in their purchasing decisions – either by discounting the value of fuel savings more heavily than this analysis assumes or by requiring shorter payback periods to recover technology costs, or both.

 Consumers might lack the information necessary to estimate the value of fuel savings, or not have a full understanding of this info rmation even when it is presented.

 Consumer may be inaccurately accounting for uncertainty in future fuel savings when comparing upfront cost to future returns.

 Consumers may consider fuel economy after other vehicle attributes and, as such, not utility maximize along this attribute (instead “satisfici ng” or selecting vehicles that have some sufficient amount of fuel economy)

 Consumers might be especially averse to the short-term losses associated with the higher prices of energy efficient products relative to the future fuel savings (the behavioral phenomenon of “loss aversion”).

 Consumers might associate higher fuel economy with inexpensive, less well designed vehicles.

471 It should be noted that adding fuel-saving technology does not preclude future improvements in performance, safety, or other attributes, though it is possible that the costs of these additions may be affected by the presence of fuel-saving technology.

472 Jaffe, A. B., and Stavins, R. N. (1994). “The Energy Paradox and the Diffusion of Conservation Technology.” Resource and Energy Economics 16(2), 91-122. Docket EPA-HQ-OAR-2009-0472-11415.

473 For an overview, see Helfand, Gloria and Ann Wolverton, “Evaluating the Consumer Response to Fuel Economy: A Review of the Literature.” Internati onal Review of Environmental and Resource Economics 5 (2011):

103-146.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 395 of 768  Even if consumers have relevant knowledge, selecting a vehicle is a highly complex undertaking, involving many vehicle characteristics. In the face of such a complicated choice, consumers may use simplified decision rules.

 In the case of vehicle fuel efficiency, and perhaps as a result of one or more of the foregoing factors, consumers may have relatively few choices to purchase vehicles with greater fuel economy once other characteristics, such as vehicle class, are chosen. 474

A great deal of work in behavioral economic s identifies and elaborates factors of this sort, which help account for the Energy Paradox. 475 This point holds in the context of fuel savings (the main focus here), but it applies equally to the other private benefits, including reductions in refueling time and additional driving. For example, it might well be questioned whether significant reductions in refueling time , and corresponding private savings, are fully internalized when consumers are making purchasing decisions.

EPA discussed this issue at length in the 2012-2016 light duty rulemaking and in the medium- and heavy-duty greenhouse gas rulemaking. See 75 FR at 25510-13; 76 FR 57315-19. Considerable research indicates that the Energy Paradox is may be a real and significant phenomenon, although the literature has not reached a consensus about the reasons for its existence. Several researchers have found evidence suggesting that consumers do not give full or appropriate weight to fuel economy in pur chasing decisions. For example, Sanstad and
Howarth 476 argue that consumers make decisions without the benefit of full information by resorting to imprecise but convenie nt rules of thumb. Some studies find that a substantial portion of this undervaluation can be explained by inaccurate assessments of energy savings, or by uncertainty and irreversibility of energy invest ments due to fluctuations in energy prices. 477 For

474 For instance, in MY 2010, the range of fuel economy (c ombined city and highway) available among all listed 6- cylinder minivans was 18 to 20 miles per gallon. With a manual-transmission 4-cylinder minivan, it is possible to get 24 mpg. See http://www.fueleconomy.gov, which is join tly maintained by the U.S. Department of Energy and the EPA. For recent but unpublished evidence, see Allcott, Hunt, and Nath an Wozny, “Gasoline Prices, Fuel Economy, and the Energy Paradox” (2010), available at http://web.mit.edu/allcott/www/A llcott%20and%20Woz ny%202010%20- %20Gasoline%20Prices,%20Fuel%20Economy,%20and%20the%20Energy%20Paradox.pdf .

475 Jaffe, A. B., and Stavins, R. N. (1994). “The Energy Paradox and the Diffusion of Conservation Technology.” Resource and Energy Economics 16(2), 91-122. See also Allcott and Wozny, supra note.

476 Sanstad, A., and R. Howarth (1994). “’Normal’ Markets, Market Imperfections, and Energy Efficiency.” Energy Policy 22(10): 811

‐ 818 (Docket EPA-HQ-OAR-2009-0472-11416).

477 Greene, D., J. German, and M. Delucchi (2009). “Fuel Economy: The Case for Market Failure” in Reducing Climate Impacts in the Transportation Sector

, Sperling, D., and J. Cannon, eds. Springer Science (Docket EPA-HQOAR-2009-0472-11538); Dasgupta, S., S. Siddarth, and J. Silva

‐ Risso (2007). “To Lease or to Buy? A Structural

Model of a Consumer’s Vehicle and Contract Choice Deci sions.” Journal of Marketing Research 44: 490 – 502 (Docket EPA-HQ-OAR-2009-0472-11539); Metcalf, G., and D. Rosenthal (1995). "The ‘New’ View of Investment Decisions and Public Policy Analysis: An Application to Green Lights and Cold Refrigerators,’’ Journal of Policy Analysis and Management 14: 517–531(Docket EPA- HQ-OAR-2009-0472-11540); Hassett, K., and G. Metcalf (1995), "Energy Tax Credits and Residential Cons ervation Investment: Evidence from Panel Data," Journal ofSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 396 of 768 a number of reasons, consumers may undervalue future energy savings due to routine mistakes in how they evaluate these trade-offs. For instance, the calculation of fuel savings is complex, and consumers may not make it correctly. 478 The attribute of fuel economy may be insufficiently salient, leading to a situation in which consumers are not willing to pay $1 for an expected $1 benefit in terms of discounted gasoline costs. 479 Larrick and Soll (2008) find that consumers do not understand how to translate changes in miles-per-gallon into fuel savings (a concern that EPA is continuing to attempt to address, for instance, through the recently revised fuel economy label). 480 In addition, future fuel price (a major component of fuel savings) is highly uncertain. Consumer fuel savings also vary across indivi duals, who travel different amounts and have different driving styles. Cost calculations base d on the average do not distinguish between those that may gain or lose as a result of the policy. 481 In addition, it is possible that the level of cost savings may be affected by the underlying reasons for the gap: factors such as transactions costs and differences in quality may not be adequately measured. 482 Studies regularly show that fuel economy plays a role in consumers’ vehicle pur chases, but modeling that role is still in development, and there is no consensus that most consumers make fully informed tradeoffs. 483 A

Public Economics 57: 201

‐ 217(Docket EPA-HQ-OAR-2009-0472-11543); Metcalf, G., and K. Hassett (1999), "Measuring the Energy Savings from Home Improvement Investments: Evidence from Monthly Billing Data," The Review of Economics and Statistics 81(3): 516

‐ 528 (Docket EPA-HQ-OAR-2009-0472-0051); van Soest D., and E. Bulte (2001), “Does the Energy

‐ Efficiency Paradox Exist? Technological Progress and Uncertainty.”

E nvironmental and Resource Economics 18: 101–12 (Docket EPA-HQ-OAR-2009-0472-11542).

478 Turrentine, T. and K. Kurani (2007). “Car Buyers and Fuel Economy?” Energy Policy 35: 1213-1223 (Docket EPA-HQ-OAR-2009-0472); Larrick, R. P., and J.B. Soll (2008). “The MPG illusion

. ” Science 320: 1593-1594 (Docket EPA-HQ-OAR-2009-0472-0041).

479 Allcott, Hunt, and Nathan Wozny, “Gasoline Prices, Fuel Economy, and the Energy Paradox” (2010), available at http://web.mit.edu/allcott/www/A llcott%20and%20Woz ny%202010%20-%20Gasoline%20Prices,%20Fuel%20Economy,%20and%20the%20Energy%20Paradox.pdf (Docket EPA-HQOAR-2009-0472-11554) .

480 Sanstad, A., and R. Howarth (1994). “’Normal’ Markets, Market Imperfections, and Energy Efficiency.” Energy Policy 22(10): 811-818 (Docket EPA-HQ-OAR-2009-0472-11415); Larrick, R. P., and J.B. Soll (2008). “The MPG
illusion

. ” Science 320: 1593-1594 (Docket EPA-HQ-OAR-2009-0472-0043); Environmental Protection Agency and Department of Transportation, “Revisions and Additions to Motor Vehicle Fuel Economy Label,” Federal Register XX(XX) (XXXX, 2011): XX-XX.

481 Hausman J., Joskow P. (1982). “Evaluating the Cost s and Benefits of Appliance Efficiency Standards.” American

Economic Review 72: 220–25 (Docket EPA-HQ-OAR-2009-0472-11541).

482 Jaccard, Mark. “Paradigms of Energy Efficiency’s Cost and their Policy Iplications: Déjà Vu All Over Again.” Modeling the Economics of Gr eenhouse Gas Mitigation: Summary of a Wo rkshop, K. John Holmes, Rapporteur. National Academies Press, 2010. http://www.nap.edu/openbook.php?record_id=13023&page=42

483 E.g., Goldberg, Pinelopi Koujianou, “Product Differentia tion and Oligopoly in International Markets: The Case of the U.S. Automobile Industry,” Econometrica 63(4) (July 1995): 891-951 (Docket EPA-HQ-OAR-2009-0472- 0021); Goldberg, Pinelopi Koujianou, “The Effects of the Corporate Average Fuel Ef ficiency Standards in the U.S.,” Journal of Industrial Economics 46(1) (March 1998): 1-33 (Docket EPA-HQ-OAR-2009-0472-0017); Busse, Meghan R., Christopher R. Knittel, and Florian Zettelmeyer ( 2009). “Pain at the Pump: How Gasoline Prices AffectSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 397 of 768 review commissioned by EPA finds great variability in estimates of the role of fuel economy in consumers’ vehicle purchase decisions. 484 Of 27 studies, significant numbers of them find that consumers undervalue, overvalue, or value approximately correctly the fuel savings that they will receive from improved fuel economy. The variation in the value of fuel economy in these studies is so high that it appears to be inapprop riate to identify one central estimate of value from the literature. Thus, estimating consumer res ponse to higher vehicle fuel economy is still
unsettled science.

If there is a difference between the estimated value of expected fuel savings and consumers’ willingness to pay for fuel savings, the next question is, which is the appropriate measure of consumer benefit? Fuel savings measure the actual monetary value that consumers will receive after purchasing a vehicle; the w illingness to pay for fuel economy measures the value that, before a purchase, consumers place on additional fuel economy. As noted, there are a number of reasons that consumers may incorrectly estimate the benefits that they get from improved fuel economy, including risk or loss aversion, and poor ability to calculate savings. Also as noted, fuel economy may not be as salient as other vehicle characteristics when a consumer is considering vehicles . If these arguments are valid, then there will be significant gains to consumers of the government mandating additional fuel economy. On the other hand, consumers may be worse off if they incur additional costs for an attribute that they consider to have a risky value or that th ey are unwilling to purchase. 485

While acknowledging the conundrum, EPA continues to value fuel savings from the proposed standards using the projected market value over the vehicles’ entire lifetimes, and to report that value among private benefits of the proposed rule. Improved fuel economy will significantly reduce consumer expenditures on fuel, thus benefiting consumers. Real money is being saved and accrued by the consumer. In a ddition, using a measure based on consumer consideration at the time of vehicle purchase would involve a very wide range of uncertainty, due to the lack of consensus on the value of additional fuel economy in vehicle choice models. Due partly to this factor, it is true that limita tions in modeling affect our ability to estimate how much of these savings would have occurred in the absence of the rule. For example, some of the technologies predicted to be adopted in response to the rule may already be developing due to shifts in consumer demand for fuel economy, or due to expectations by auto makers of future GHG/fuel economy standards. It is not impo ssible that some of these savings would have

Automobile Purchasing in New and Used Markets, ” Working paper (accessed 6/30/09), available at http://www.econ.ucdavis.edu/faculty/knittel/papers/gasp aper_latest.pdf (Docket EPA-HQ-OAR-2009-0472-0044).

484 Greene, David L. “How Consumers Value Fuel Economy: A Literature Review.” EPA Report EPA-420-R-10- 008, March 2010 (Docket EP A-HQ-OAR-2009-0472-11575).

485 Helfand and Wolverton, p. 105.

Formatted: Indent: First line: 0"Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 398 of 768 occurred in the absence of the rule. 486 To the extent that greater fuel economy improvements than those assumed to occur under the baseline may have occurred due to market forces alone (absent the rule), the analysis ove restimates private and social benefits and costs. As discussed below, limitations in modeling also affect our ab ility to estimate the effects of the rule on net
benefits in the market for vehicles.

Consumer vehicle choice models estimate wh at vehicles consumers buy based on vehicle and consumer characteristics. In principle, such models could provide a means of understanding both the role of fuel economy in consumers’ purchase decisions and the effects of this rule on the benefits that consumers will get from vehicles . Helfand and Wolverton discuss the wide
variation in the structure and results of these models. 487 Models or model results have not frequently been systematically compared to each other. When they have, the results show large variation over, for instance, the value that consumers place on additional fuel economy.

In order to develop greater understanding of these models, EPA is in the process of developing a vehicle choice model. It uses a “nested logit” structure common in the vehicle choice modeling literature. “Nesting” refers to the decision-tree structure of buyers’ choices among vehicles the model employs, and “logit” refers to the specific pattern by which buyers’ choices respond to differences in overall utility that individual vehicle choice model’s combinations of attributes provide and the fact that the choices are discrete (i.e., yes/no decisions about which vehicles to purchase, instead of continuous values. 488 The nesting involves a hierarchy of choices. In its current form, at the initial decision node, consumers choose between buying a new vehicle or not. Conditional on choosing a new vehicle, consumers then choose between passenger vehicles, cargo vehicles, and ul tra-luxury vehicles. The next set of choices subdivides each of these categories into vehicle type (e.g., standard car, minivan, SUV, etc.). Next, the vehicle types are divided into classe s (small, medium, and large SUVs, for instance), and then, at the bottom, are the individual models. At this bottom level, ve hicles that are similar to each other (such as standard subcompacts, or prestige large vehicles) end up in the same
“nest.” Substitution within a nest is considered mu ch more likely than substitution across nests,
because the vehicles within a nest are more similar to each other than vehicles in different nests. For instance, a person is more likely to substitu te between a Chevrolet Aveo and a Toyota Yaris than between an Aveo and a pickup truck. In a ddition, substitution is greater at low decision nodes (such as individual vehicles) than at higher decision nodes (such as the buy/no buy decision), because there are more choices at lower levels than at higher levels. Parameters for the model (including demand elasticities and the valu e of fuel economy in purchase decisions) are being selected based on a review of values f ound in the literature on vehicle choice modeling.

486 However, as discussed at section III.D above, the assumpti on of a flat baseline absent this rule rests on strong historic evidence of lack of increase in fuel economy absent either regulatory control or sharply rising fuel prices.

487 Helfand, Gloria and Ann Wolverton, “Evaluating the Consumer Response to Fuel Economy: A Review of the Literature.” International Review of Environmental and Resource Economics 5 (2011): 103-146.

488 Logit refers to a statistical analysis method used for anal yzing the factors that affect discrete choices (i.e., yes/no decisions or the choice among a countable number of options).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 399 of 768 Additional discussion of this mo del can be found in Chapter 8.1.2.8 of the DRIA. The model is still undergoing development; the agency will seek peer review on it before it is utilized. In addition, concerns remain over the ability of any vehicle choice model to make reasonable predictions of the response of the total number and composition of new vehicle sales to changes in the prices and characteristics of specific ve hicle models. EPA seeks comments on the use of vehicle choice modeling for predicting changes in sales mix due to policies, and on methods to test the ability of a vehicle choice model to produce reasonable estimates of changes in fleet mix.

The next issue is the potential for loss in cons umer welfare due to the rule. As mentioned above (and discussed more thoroughly in Section III.D.3 of this preamble), the technology cost estimates developed here for conventional vehicl es take into account the costs to hold other vehicle attributes, such as size and performance, constant. 489 In addition, the analysis assumes that the full technology costs are passed along to consumers. With these assumptions, because welfare losses are monetary estimates of how much consumers would have to be compensated to be made as well off as in the absence of the change, 490 the price increase measures the loss to the

consumer. 491 Assuming that the full technology cost gets passed along to the consumer as an increase in price, the technology cost thus measur es the welfare loss to the consumer. Increasing fuel economy would have to lead to other changes in the vehicles that consumers find
undesirable for there to be ad ditional losses not included in the technology costs.

b. Electric Vehicles and other Advanced Technology Vehicles

This proposal finds that electric vehicles (E Vs) may form a part (albeit limited) of some manufacturers’ compliance strategy. The following discussion will focus on EVs, because they are expected to play more of a role in compliance than vehicles with other alternative fuels, but related issues may arise for other alternatively fueled vehicles. It should be noted that EPA’s projection of the penetration of EVs in the MY 2025 fleet is very small (X%).

Electric vehicles (EVs), at the time of this rulemaking, have very different refueling infrastructures than conventional gasoline- or diesel-fueled vehicles: refueling EVs requires

489 If the reference-case vehicles include different vehicl e characteristics, such as improved acceleration or towing capacity, then the costs for the proposed standards would be, as here, the costs of adding compliance technologies to those reference-case vehicles. These costs may differ from those estimated here, due to our lack of information on how those vehicle characteristics might change between now and 2025.

490 This approach describes the economic concept of comp ensating variation, a payment of money after a change that would make a consumer as well off after the change as before it. A related conc ept, equivalent variation, estimates the income change that would be an alternativ e to the change taking place. The difference between them is whether the consumer’s point of reference is her welfar e before the change (compensating variation) or after the change (equivalent variation). In practice, these two measures are typically very close together for marketed goods.

491 Indeed, it is likely to be an overestimate of the loss to the consumer, because the consumer has choices other than buying the same vehicle with a higher price; she could ch oose a different vehicle, or decide not to buy a new vehicle. The consumer would choose one of those options only if the alternative invo lves less loss than paying the higher price. Thus, the increase in price that the co nsumer faces would be the upper bound of loss of consumer welfare, unless there are other changes to the vehicle due to the fuel economy improvements, unaccounted for in the costs, that make the vehicle less desirable to consumers.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 400 of 768 either access to electric charging facilities or batt ery replacement. In addition, because of the expense of increased battery capacity, EVs commonly have a smaller driving range than
conventional vehicles. Because of these diff erences, the vehicles cannot be considered conventional vehicles unmodified except for cost and fuel economy. As a result, the consumer welfare arguments presented above need to be modified to account for these differences.

A first important point to observe is that, although auto makers are required to comply with the proposed standards, producing EVs as a compliance strategy is not specifically required. Auto makers will choose to provide EVs either if they have few alternative ways to comply, or if EVs are, for some range of production, likely to be more profitable (or less unprofitable) than other ways of complying.

From the consumer perspective, it is important to observe that there is no mandate for any consumer to choose any particular kind of vehicl e. An individual consum er will buy an EV only if the price and characteristics of the vehicle make it more attractive to her than other vehicles. If the range of vehicles in the conve ntional fleet does not shrink, th e availability of EVs should not reduce consumer welfare compared to a fleet with no EVs: increasing options should not reduce consumer well-being, because other existing options still are available. On the other hand, if the variety of vehicles in the conventional market does change, there may be consumers who are
forced to substitute to alternative vehicles. The us e of the footprint-based standard is intended to help maintain the diversity of vehicle sizes and attributes . Because the agencies do not expect any vehicle classes to become unavailable, cons umers who buy EVs therefore are expected to choose them voluntarily, in preference to the other vehicles available to them.

From a practical perspective, the key issue is whether the consumer demand for EVs is large enough to absorb all the EV s that automakers will produce in order to comply with these standards, or whether automakers will need to increase consumer purchases by providing subsidies to consumers. If enough consumers find EVs more attractive than other vehicles, and automakers therefore do not need to subsidize their purchase, then both consumers and producers
will benefit from the introduction of EVs. On the other hand, it is possible that automakers will find EVs to be part of a cost-effective compliance technology but nevertheless need to price them below cost them to sell sufficient numbers. If so, then there is a welfare loss associated with the sale of EVs beyond those that would be sold in the free market. The deadweight loss can be approximated as one-half of the size of the subsidy needed for the marginal purchaser,
times the number of sales that would need the subsidy. Estimating this value would require knowing the number of sales necessary beyond the expected sales level in an unregulated market, and the amount of the subsidy that would be necessary to induce the desired number of sales. Given the fledgling state of the market for EVs, neither of these values is easily knowable
for the 2017 to 2025 time frame.

A number of factors will affect the likelihood of consumer acceptance of EVs. People with short commutes may find little obstacle in th e relatively short driving range, but others whoSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 401 of 768 regularly drive long distances may find EVs’ ranges limiting. The reduced tailpipe emissions and reduced noise may be attractive features to some consumers. 492 Recharging at home could be a convenient, desirable feature for people who have garages with electric charging capability, but not for people who park on the street. If an infrastructure develops for recharging vehicles with the convenience approaching that of buying gasoline, range or home recharging may become less of a barrier to purchase. Of course, other attributes of the marketed EVs, such as their performance and their passenger and storag e capacity, will also affect the share of
consumers who will consider them. As infrastru cture, EV technology, and costs evolve over time, consumer interest in EVs will adjust as well. Thus, modeling consumer response to advanced technology vehicles in the 2017-2025 time frame poses even more challenges than those associated with modeling consumer response for conventional vehicles.

Because range is a major factor in EV acceptabi lity, it is starting to draw attention in the research community. For instance, several studies have examined consumers’ willingness to pay for increased vehicle range. Results vary, depending on when the survey was conducted (studies from the early 1990s have much higher values than more recent studies) and on household income and other demographic factors; some find range to be statistically indistinguishable from zero, while others find the value of increasing range from 150 to 300 miles to be as much as $59,000 (2009$) (see RIA Chapter XX for more discussion).

Other research has examined how the range limitation may affect driving patterns. Pearre et al. observed daily driving patterns for 484 vehicles in the Atlanta area over a year. 493 In their sample, 9 percent of vehicles never exceeded 100 miles in one day, and 21 percent never exceeded 150 miles in one day. Lin and Greene compared the cost of reduced range to the cost of additional battery capacity for EVs. 494 They find that an “optimized” range of about 75 miles would be sufficient for 98% of days for “modest” drivers (those who average about 25 miles per day); the optimized EV range for “average” drivers (who average about 43 miles per day), close to 120 miles, would meet their needs on 97 percen t of days. Turrentine et al. studied drivers who leased MINI E EVs (a conversion of the MINI Cooper) for a year. 495 They found that drivers adapted their driving patterns in response to EV ownership: for instance, they modified where they shopped and increased their use of regenerative braking in order to reduce range as a constraint. These finding suggest that, for some consumers, range may be a limiting factor only

492 For instance, Hidrue et al. (Hidrue, Michael K., George R. Parsons, Willett Kempton, and Meryl P. Gardner. “Willingness to Pay for Electric Vehicles and th eir Attributes.” Resource and Energy Economics 33(3) (2011): 686-705) find that some consumers are willing to pay $ 5100 for vehicles with 95% lower emissions than the vehicles they otherwise aim to purchase.

493 Pearre, Nathaniel S., Willett Kempton, Randall L. Guensl er, and Vetri V. Elango. “Electric vehicles: How much range is required for a day’s driving?” Transportation Research Part C (2011), in press.

494 Lin, Zhenhong, and David Greene. “Rethinking FCV/BEV Vehicle Range: A Consumer Value Trade-off Perspective.” The 25 th World Battery, Hybrid and Fuel Cell Electric Vehicle Symposium and Exhibition, Shenzhen, China, Nov. 5-9, 2010.

495 Turrentine, Tom, Dahlia Garas, Andy Lentz, and Justin Woodjack. “The UC Davis MINI E Consumer Study.” UC Davis Institute of Transportation Resear ch Report UCD-ITS-RR-11-05, May 4, 2011.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 402 of 768 occasionally. If those consumers are willing to consider alternative ways of driving long distances, such as renting a gasoline vehicle or exchanging vehicles within the household, then limited range may not be a barrier to adoption for them. These studies also raise the question whether analysis of EV use should be based on the driving patterns from conventional vehicles, because consumers may use EVs differently than conventional vehicles.

EVs themselves are expected to change over time, as battery technologies and costs develop. In addition, c onsumer interest in EVs is likely to change over time, as early adopters share their experiences. The initial research in the area suggests that consumers put a high value on increased range, though this value appears to be changing over time. The research also suggests that some segments of the driving public may experience little, if any, restriction on their driving due to range limitations if they were to purchase EVs. At this time it is not possible to estimate whether the number of people who wi ll choose to purchase EVs at private-market prices will be more or less than the number that auto makers are expected to produce to comply with the standards. We note that our projections of technology penetrations indicate that a very small portion (fewer than 3 percent) of new vehicles produced in 2025 will need to be EVs. For the purposes of the analysis presented here for this proposal, we assume that the consumer
market will be sufficient to abso rb the number of EVs expected to be used for compliance under this rule. We seek comment and further research that might provide evidence on the consumer market for EVs in the 2017-2025 period.

c. Summary

The Energy Paradox, also known as the efficiency gap, raises the question, why do private markets not provide energy savings that en gineering, technology cost analyses find are cost-effective? Though a number of hypotheses have been raised to explain the paradox, studies have not been able at this time to identify the relative importance of different explanations. As a result, it is not possible at this point to state wi th any degree of certainty whether the market for fuel efficiency is operating efficien tly, or whether the market has failings.

For conventional vehicles, the key implication is that the there may be two different estimates of the value of fuel savings. One value comes from the engineering estimates, based on consumers’ expected driving patterns over the vehicle’s lifetime; the other value is what the consumer factors into the purchase decision when buying a vehicle. Although economic theory suggests that these two values should be the same in a well functioning market if engineering estimates are able to accurately measure the fuel savings that would be achieved under realworld driving conditions , the available evidence does not provide support for that theory. The fuel savings estimates presented here are based on expected consumers’ in-use fuel consumption rather than the value they estimate at the time that they consider purchasing a vehicle. The costs imposed on the consumer are measured by the costs of the technologies needed to comply
with the standards. Because the cost estimates have built into them the costs required to holdSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 403 of 768 other vehicle attributes constant, then, in prin ciple, compensating consumers for the increased costs would hold them harmless, even if they paid no attention to the fuel efficiency of vehicles when making their purchase decisions. However, if some consumers are no longer able to purchase a vehicle with the attributes that they would have otherwise purchased, they may be
made worse off.

For electric vehicles, and perhaps for other advanced-technology vehicles, other vehicle attributes are not expected to be held constant. In particular, their ranges and modes of refueling will be different from those of conventional vehicles. From a social welfare perspective, the key question is whether the number of consumers who will want to buy EVs at their private-market prices will exceed the number that auto makers are expected to produ ce to comply with the standards. If too few consumers are willing to buy them at their private-market prices, then auto makers will have to subsidize their prices. Though current research finds that consumers typically have a high value for increasing the range of EVs (and thus would consider a shorter range a cost of an EV), current research also suggests that consumers may find ways to adapt to the shorter range so that it is less constraining. The technologies, prices, infrastructure, and consumer experiences associated with EVs are a ll expected to evolve between the present and the period when this rule becomes effective. The analysis in this proposal assumes that the
consumer market is sufficient to absorb th e expected number of EVs without subsidies.

We seek comment and further research on the efficiency of the market for fuel economy for conventional vehicles and on the likely size of the consumer market for EVs in 2017-2025.

2. Costs Associated with the Vehicle Standards (Sherwood)

In this section, EPA presents our estimate of the costs associated with the proposed vehicle program. The presentation here summarizes the vehicle level costs associated with the new technologies expected to be added to meet the proposed GHG standards, including hardware costs to comply with the proposed A/C credit program. The analysis summarized here provides our estimate of incremental costs on a per vehicle basis and on an annual total basis.

The presentation here summarizes the outputs of the OMEGA model that was discussed in some detail in Section III.D of this preamble. For details behind the analysis such as the OMEGA model inputs and the estimates of cost s associated with indi vidual technologies, the reader is directed to Chapter 1 of the EPA’s draft RIA and Chapter 3 of the draft Joint TSD. For more detail on the outputs of the OMEGA model and the overall vehicle program costs summarized here, the reader is directed to Chapters 3 and 5 of EPA’s draft RIA.

With respect to the aggregate cost estimations presented here, EPA notes that there are a number of areas where the results of our analysis may be conservative and, in general, EPA believes we have directionally overestimated the costs of compliance with these new standards, especially in not accounting for the full range of credit opportunities availabl e to manufacturers.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 404 of 768 For example, some cost saving programs are considered in our analysis, such as full car/truck trading, while others are not, such as advanced vehicle technology credits.

a. Costs per Vehicle

To develop costs per vehicle, EPA has used the same methodology as that used in the
recent 2012-2016 final rule and the 2010 TAR. I ndividual technology direct manufacturing costs have been estimated in a variety of ways—vehicle and technology tear down, models developed by outside organizations, and literature review—and indirect costs have been estimated using the updated and revised indirect cost multiplier (ICM) approach that was first developed for the
2012-2016 final rule. All of these individual techno logy costs are described in detail in Chapter 3 of the draft joint TSD. Also described there ar e the ICMs used in this proposal and the ways the ICMs have been updated and revised since the 2012-2016 final rule which results in considerably higher indirect costs in this proposal than estimated in the 2012-2016 final rule. Further, we describe in detail the adjustments to technology costs to account for manufacturing learning and the cost reductions that result from that learning. We note here that learning impacts are applied only to direct manufacturing costs which differs from the 2012-2016 final rule which applied learning to both direct and indi rect costs. Lastly, we have included costs associated with stranded capital (i.e., capital investments that are not fully recaptured by auto makers because they would be forced to update vehicles on a more rapid schedule than they may have intended absent this proposal). Again, this is detailed in Chapter 3 of the draft joint TSD.

EPA then used the technology costs to build GHG and fuel consumption reducing packages of technologies for each of 19 different vehicle types meant to fully represent the range of baseline vehicle technologies in the marketplace (i.e., number of cylinders, valve train configuration, vehicle class). This package building process as well as the process we use to determine the most cost effective packages for each of the 19 vehicle types is detailed in Chapter 1 of EPA’s draft RIA. These packages are then used as inputs to the OMEGA model to estimate the most cost effective means of compliance with the proposed standards giving due consideration to the timing required for manufacturers to implement the needed technologies. That is, we assume that manufacturers cannot add the full suite of needed technologies in the first year of implementation. Instead, we expect them to add technologies to vehicles during the typical 4 to 5 year redesign cycle. As such, we expect that every vehicle can be redesigned to add significant levels of new technology every 4 to 5 years. Fu rther, wedo not expect manufacturers to redesign or refresh vehicles at a pace more rapid than the industry standard four to five year cycle.

The results, including costs associated with the air conditioning program and estimates of stranded capital as described in Chapter 3 of the draft joint TSD, are shown in Table III-63.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 405 of 768 Table III-63 Industry Average Vehicle Costs Associated with the Proposed Standards (2009 dollars)

Model Year 2017 2018 2019 2020 2021 2022 2023 2024 2025 2030 2040 2050

$/car $172 $319 $463 $591 $723 $1,051 $1,357 $1,658 $1,947 $1,931 $1,931 $1,931

$/truck $49 $180 $292 $407 $753 $1,068 $1,373 $1,670 $1,944 $1,928 $1,928 $1,928

Combined $126 $268 $402 $527 $734 $1,057 $1,362 $1,662 $1,946 $1,930 $1,930 $1,930

b. Annual Costs of the Proposed National Program

The costs presented here represent the incremental costs for newly added technology to comply with the proposed program. Together with the projected increases in car and truck sales, the increases in per-car and per-truck average costs shown in Table III-63, above result in the total annual costs presented in Table III-64 below. Note that the costs presented in Table III-64 do not include the fuel savings that consumers w ould experience as a result of driving a vehicle with improved fuel economy. Those impacts are presented in Section III.H.4. Note also that the costs presented here represent costs estimated to occur presuming that the proposed MY 2025 standards would continue in perpetuity. Any changes to the proposed standards would be considered as part of a future rulemaking. In other words, the proposed standards do not apply only to 2017-2025 model year vehicles - they do, in fact, apply to all 2025 and later model year
vehicles.

Table III-64 Undiscounted Annual Costs, & Proposed Program Costs Discounted back to 2012 (millions of 2009 dollars)

Calendar

Year Cars Truck Total Annual

Costs

2017 $1,710 $283 $2,000

2018 $3,160 $1,020 $4,180

2019 $4,630 $1,630 $6,260

2020 $6,090 $2,280 $8,370

2021 $7,600 $4,280 $11,900

2022 $11,300 $6,090 $17,400Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 406 of 768 2023 $14,900 $7,810 $22,700

2024 $18,700 $9,480 $28,200

2025 $22,500 $11,100 $33,600

2030 $24,200 $11,500 $35,700

2040 $27,200 $12,500 $39,800

2050 $30,600 $14,100 $44,600

NPV, 3% $371,000 $174,000 $545,000

NPV, 7% $162,000 $76,600 $239,000

Annual costs represent undiscounted values; net present values represent annual costs discounted to 2012.

3. Cost per Ton of Emissions Reduced (Sherwood)

EPA has calculated the cost per ton of GHG reductions associated with the proposed
GHG standards on a CO 2 eq basis using the costs and the emissions reductions described in Section III.F. These values are presented in Table III-65 for cars, trucks and the combined fleet. The cost per metric ton of GHG emissions reduc tions has been calculated in the years 2020, 2030, 2040, and 2050 using the annual vehicle compliance costs and emission reductions for each of those years. The value in 2050 represents the long-term cost per ton of the emissions reduced. EPA has also calculated the cost per metric ton of GHG emission reductions including the savings associated with reduced fuel consumption (presented below in Section III.H.4). This
latter calculation does not include the other benefits associated with this program such as those associated with energy security benefits as disc ussed later in Section III. By including the fuel savings, the cost per ton is generally less than $0 since the estimated value of fuel savings outweighs the program costs.

Table III-65 Annual Cost per Metric Ton of CO 2 eq Reduced (2009 dollars)

Calendar

Year Undiscounted Annual Costs

($millions) Undiscounted Annual Pre-tax Fuel Savings ($millions) Annual CO 2 eq Reduction

(mmt) $/ton

(w/o fuel savings) $/ton

(w/ fuel savings

Cars 2020 $6,090 $4,730 19 $323 $72

2030 $24,200 $55,900 188 $129 -$168

2040 $27,200 $95,400 297 $91 -$229Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 407 of 768 2050 $30,600 $124,000 351 $87 -$266

Trucks 2020 $2,280 $2,300 9 $243 -$2

2030 $11,500 $35,000 118 $98 -$200

2040 $12,500 $60,700 188 $66 -$256

2050 $14,100 $80,900 229 $62 -$292

Combined 2020 $8,370 $7,030 28 $297 $47

2030 $35,700 $90,900 306 $117 -$180

2040 $39,800 $156,000 486 $82 -$239

2050 $44,600 $204,000 580 $77 -$275

4. Reduction in Fuel Consumption and its Impacts

a. What Are the Projected Changes in Fuel Consumption?

The proposed CO 2 standards will result in significant improvements in the fuel efficiency
of affected vehicles. Drivers of those vehicles will see corresp onding savings associated with reduced fuel expenditures. EPA has estimated the impacts on fuel consumption for both the tailpipe CO 2 standards and the A/C credit program. While gasoline consumption would decrease under the proposed GHG standards, electricity consumption would increase slightly due the small penetration of EVs and PHEVs (1-3% for the 2021 and 2025 MYs). The fuel savings includes both the gasoline consumption reductions and the electricity consumption increases. Note that the total number of miles that vehicles are driven each year is different under the control case than in the reference case due to the “rebound effect,” which is discussed in Section III.H.4.c and in Chapter 4 of the draft joint TSD. EPA also notes that consumers who drive more than our average estimates for vehicle miles tr aveled (VMT) will experience more fuel savings; consumers who drive less than our average VMT estimates will experience less fuel savings.

The expected impacts on fu el consumption are shown in Table III-66. The gallons reduced and kilowatt hours increased (kWh) as shown in the tables reflect impacts from the proposed CO 2 standards, including the A/C credit program, and include increased consumption resulting from the rebound effect.

Table III-66 Fuel Consumption Impacts of the Proposed Standards and A/C Credit Programs

Calendar Year Petroleum-based Petroleum-based Electricity IncreasedSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 408 of 768 Gasoline Reference

(million gallons) Gasoline Reduced

(million gallons) (kWh)

2017 133,808 191 113

2018 132,789 626 338

2019 131,894 1,294 680

2020 131,336 2,231 1,154

2021 131,278 3,622 1,766

2022 131,370 5,379 2,907

2023 131,898 7,498 4,600

2024 132,569 9,951 6,871

2025 133,612 12,759 9,755

2030 142,185 26,327 24,068

2040 161,688 42,411 42,313

2050 187,307 50,722 51,203

Total 5,158,999 983,847 948,660

b. What are the Fuel Savings to the Consumer?

Using the fuel consumption estimates presented in Section III.H.4.a, EPA can calculate the monetized fuel savings associ ated with the proposed standard s. To do this, we multiply reduced fuel consumption in each year by the corresponding estimated average fuel price in that year, using the reference case taken from the AEO 2011 Final Release. 496 These estimates do not account for the significant uncertainty in future fuel prices; the monetized fuel savings would be understated if actual fuel prices are higher (or overstated if fuel prices are lower) than
estimated. AEO is a standard reference used by NHTSA and EPA and many other government agencies to estimate the projected price of fuel . This has been done using both the pre-tax and post-tax gasoline prices. Since the post-tax gasoline prices are the prices paid at fuel pumps, the

496 In the Preface to AEO 2011, the Energy Information Admi nistration describes the reference case. They state that, “Projections by EIA are not statements of what w ill happen but of what might happen, given the assumptions and methodologies used for any particular scenario. The Reference case projection is a business-as-usual trend estimate, given known technology and t echnological and demographic trends.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 409 of 768 fuel savings calculated using these prices repres ent the savings consumers would see. The pretax fuel savings are those savings that society w ould see. Assuming no change in gasoline tax rates, the difference between these two columns represents the reduction in fuel tax revenues that will be received by state and federal government s - about $81 million in 2017 and $19 billion by
2050. These results are shown in Table III-67. Note that in Secti on III.H.9, the overall benefits and costs of the proposal are presented and, for that reason, only the pre-tax fuel savings are presented there.

Table III-67 Undiscounted Annual Fuel Savi ngs, & Proposed Program Fuel Savings Discounted back to 2012 (millions of 2009 dollars)

Calendar

Year Gasoline Savings

(pre-tax) Gasoline Savings

(taxed) Electricity Costs Total Fuel Savings

(pre-tax) Total Fuel Savings

(taxed)

2017 $572 $653 $10.9 $561 $642

2018 $1,910 $2,180 $32.1 $1,870 $2,140

2019 $4,020 $4,550 $64.6 $3,960 $4,490

2020 $7,030 $7,940 $111 $6,920 $7,830

2021 $11,400 $12,900 $170 $11,300 $12,800

2022 $17,200 $19,600 $282 $17,000 $19,300

2023 $24,300 $27,400 $451 $23,900 $27,000

2024 $32,800 $36,900 $680 $32,100 $36,200

2025 $42,700 $47,600 $985 $41,700 $46,600

2030 $90,900 $101,000 $2,530 $88,300 $98,400

2040 $156,000 $172,000 $4,850 $151,000 $167,000

2050 $204,000 $223,000 $6,360 $198,000 $216,000

NPV, 3% $1,620,000 $1,790,000 $47,600 $1,570,000 $1,740,000

NPV, 7% $619,000 $684,000 $17,700 $601,000 $667,000

Annual values represent undiscounted values; net present values represent annual costs discounted to 2012.

As shown in Table III-67, the agencies are pr ojecting that consumers would realize very large fuel savings as a result of the proposed standards. As discussed further in the introductory paragraphs of Section III.H.1, it is a conundrum from an economic perspective that these largeSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 410 of 768 fuel savings have not been provided by automakers and purchased by consumers. A number of behavioral and market phenomena may lead to this disparity between the fuel economy that makes financial sense to consumers and the fuel economy they purchase. Regardless how
consumers make their decisions on how much fu el economy to purchase, EPA expects that, in the aggregate, they will gain these fuel savings , which will provide actua l money in consumers’ pockets.

c. VMT Rebound Effect

The rebound effect refers to the increase in vehicle use that results if an increase in fuel efficiency lowers the cost per mile of driving. For this proposal, EPA is using an estimate of 10 percent for the rebound effect (i.e., we assume a 10 percent decrease in fuel cost per mile from our proposed standards would result in a 1 percent increase in VMT).

As we discussed in the 2012-2016 rulemaking and in Chapter 4 of the Joint TSD, this value was not derived from a single point estimate from a particular study, but instead represents a reasonable compromise between the historical estimates and the projected future estimates.
This value is consistent with the rebound estimate for the most recent time period analyzed in the Small and Van Dender 2007 paper, 497 and falls within the range of the larger body of historical
work on the rebound effect. 498 Recent work by David Greene on the rebound effect for lightduty vehicles in the U.S. supports the hypothesis that the rebound effect is decreasing over time,

499 which could mean that rebound estimates based on recent time period data may be more reliable than historical estimates that are based on older time period data. New work by Hymel, Small, and Van Dender also supports the theory that the rebound effect is declining over time, although the Hymel et al. estimates are higher than the 2007 Small and Van Dender estimates. 500
Furthermore, by using an estimate of the future rebound effect, analysis by Small and Greene show that the rebound effect could be in the range of 5% or lower. 501

Most studies that estimate the rebound effect use the fuel cost per mile of driving or gasoline prices as a surrogate for fuel efficiency. Recent work conducted by Kenneth

497 Small, K. and K. Van Dender, 2007. “Fuel Efficien cy and Motor Vehicle Travel: The Declining Rebound Effect”, The Energy Journal, vol. 28, no. 1, pp. 25-51 (Docket EPA-HQ-OAR-XXX).

498 Sorrell, S. and J. Dimitropoulos, 2007. “UKERC Revi ew of Evidence for the Rebound Effect, Technical Report 2: Econometric Studies”, UKERC/WP/TPA/2007/010, UK En ergy Research Centre, London, October (Docket EPA-HQ-OAR-XXX).

499 Greene, David, “Rebound 2007: Analysis of National Light-Duty Vehicle Travel Statistics,” February 9, 2010 (Docket EPA-HQ-OAR-2009-0472-0220). This paper has been accepted for an upcoming special issue of Energy Policy, although the publication date has not yet been determined.

500 Hymel, Kent M., Kenneth A. Small, and Kurt Van Dender, “Induced demand and rebound effects in road transport,” Transportation Research Part B: Methodologi cal, Volume 44, Issue 10, December 2010, Pages 1220- 1241, ISSN 0191-2615, DOI: 10.1016/j.trb.2010.02.007.

501 Report by Kenneth A. Small of University of California at Irvine to EPA, “The Rebound Effect from Fuel Efficiency Standards: Measurement and Projection to 2030”, June 12, 2009 (Docket EPA-HQ-OAR-XXX). See also Greene, 2010.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 411 of 768 Gillingham, however, provides suggestive evidence that consumers may be less responsive to changes in fuel efficiency than to changes in fuel prices. 502 While this research pertains specifically to California, this finding suggests that the common assumption that consumers respond similarly to changes in gasoline prices and changes in fuel efficiency may overstate the potential rebound effect. Additional research is n eeded in this area, and EPA requests comments and data on this topic.

Another factor discussed by Gillingham is whether consumers actually respond the same way to an increase in the cost of driving compared to a decrease in the cost of driving. There is
some evidence in the literature that consumers ar e more responsive to an increase in prices than to a decrease in prices. 503,504,505 Furthermore, it is also possible that consumers respond more to a large shock than a small, gradual change in prices. Since these proposed standards would decrease the cost of driving gradually over time, it is possible that the rebound effect would be
much smaller than some of the estimates included in the historical literature. More research in this area is also important, and EPA invites comment and data on this aspect of the rebound
effect.

Finally, for purposes of analyzing the proposed standards, EPA assumes the rebound
effect will be the same whether a consumer is driving a conventional gasoline vehicle or a vehicle powered by grid electricity. We are not aware of any research that has examinedconsumer responses to changes in the cost per mile of driving that result from driving an electricpowered vehicle instead of a conventional gasoline vehicle. EPA requests comment and data on this topic.

Chapter 4.2.5 of the Joint TSD reviews the rele vant literature and discusses in more depth the reasoning for the rebound value used here. The rebound effect is also discussed in Section II.E of the preamble. While EPA has used a weight of evidence approach for determining that 10 percent is a reasonable value to use for the rebound effect, EPA requests comments on this and alternative methodologies for estimating the rebound effect over the period that our proposed standards would go into effect. EPA also invite s the submission of new data regarding estimates
of the rebound effect.

502 Gillingham, Kenneth. “The Consumer Response to Ga soline Price Changes: Empirical Evidence and Policy Implications.” Ph.D. diss., Stanford University, 2011.

503 Dargay, J.M.,Gately,D.,1997. “The demand for tr ansportation fuels: imperfect price-reversibility?” Transportation Research Part B 31(1).

504 Dermot Gately, 1993. "The Imperfect Price-Revers ibility of World Oil Demand," The Energy Journal, International Association for Energy Economics, vol. 14(4), pages 163-182.

505 Sentenac-Chemin, E. (2010) Is the price effect on fuel consumption symmetric? Some evidence from an empirical study, Energy Policy ( 2010), doi:10.1016/j. enpol.2010.07.016Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 412 of 768 5. CO 2 Emission Reduction Benefits

EPA has assigned a dollar value to reductions in CO 2 emissions using global estimates of the social cost of carbon (SCC). The SCC is an estimate of the monetized damages associated
with an incremental increase in carbon emissions in a given year. It is intended to include (but is not limited to) changes in net agricultural productivity, human health, property damages from increased flood risk, and the value of ecosystem services due to climate change. The SCC estimates used in this analysis were developed through an interagency process that included EPA, DOT/NHTSA, and other executive branch en tities, and concluded in February 2010. We first used these SCC estimates in the benefits analysis for the 2012-2016 light-duty GHG rulemaking; see 75 FR at 25520. We have continued to use these estimates in other rulemaking analyses, including the heavy-duty GHG rulemaking; see 76 FR at 57332

. The SCC Technical Support Document (SCC TSD) provides a comple te discussion of the methods used to develop
these SCC estimates. 506

The interagency group selected four SCC values for use in regulatory analyses, which we have applied in this analysis: $5, $22, $36, and $67 per metric ton of CO 2 emissions in 2010, in
2009 dollars. 507,508 The first three values are based on the average SCC from three integrated assessment models, at discount rates of 5, 3, and 2.5 percent, respectively. SCCs at several
discount rates are included because the literature shows that the SCC is quite sensitive to assumptions about the discount rate, and because no consensus exists on the appropriate rate to use in an intergenerational context. The fourth value is the 95th percentile of the SCC from all three models at a 3 percent discount rate. It is included to represent higher-than-expected impacts from temperature change further out in the tails of the SCC distribution. Low probability, high impact events are incorporated into all of the SCC values through explicit
consideration of their effects in two of the three models as well as the use of a probability density function for equilibrium climate sensitivity. Tr eating climate sensitivity probabilistically results in more high temperature outcomes, which in tu rn lead to higher projections of damages.

506 Docket ID EPA-HQ-OAR-2009-0472-114577, Technical Support Document: Social Cost of Carbon for Regulatory Impact Analysis Under Executive Order 12866, Interagency Working Group on Social Cost of Carbon

, with participation by Council of Economic Advisers, Counc il on Environmental Quality, Department of Agriculture, Department of Commerce, Department of Energy, Depart ment of Transportation, Environmental Protection Agency, National Economic Council, Office of Energy and Climat e Change, Office of Management and Budget, Office of Science and Technology Policy, and Department of Treasury (February 2010). Also available at http://epa.gov/otaq/climate/regulations.htm [Planning to add to 2017 rule docket; updated reference needed]

507 The interagency group decided that these estimates apply only to CO 2 emissions. Given that warming profiles and impacts other than temperature change (e.g., ocean acidification) vary across GHGs, the group concluded “transforming gases into CO 2 -equivalents using GWP, and then multiplying the carbon-equivalents by the SCC, would not result in accurate estimates of the social costs of non-CO 2 gases” (SCC TSD, pg 13).

508 The SCC estimates were converted from 2007 dollars to 2008 dollars using a GDP price deflator (1.021) and again to 2009 dollars using a GDP price deflator (1.009) obtained from the Bureau of Economic Analysis, National Income and Product Accounts Table 1.1.4, Prices Indexes for Gross Domestic Product

.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 413 of 768 The SCC increases over time because future emissions are expected to produce larger incremental damages as physical and economic systems become more stressed in response to greater climatic change. Note that the interagency group estimated the growth rate of the SCC directly using the three integrated assessment models rather than assuming a constant annual growth rate. This helps to ensure that the estim ates are internally consistent with other modeling assumptions. Table III-68 presents the SCC estimates used in this analysis.

When attempting to assess the incremental economic impacts of carbon dioxide emissions, the analyst faces a number of serious challenges. A recent report from the National Academies of Science points out that any assessment will suffer from uncertainty, speculation, and lack of information about (1) future emissi ons of greenhouse gases, (2) the effects of past and future emissions on the climate system, (3) the impact of changes in climate on the physical and biological environment, and (4) the translation of these environmental impacts into economic damages. 509 As a result, any effort to quantify and monetize the harms associated with climate change will raise serious questions of science, economics, and ethics and should be viewed as provisional.

The interagency group noted a number of limitations to the SCC analysis, including theincomplete way in which the integrated assessment models capture catastrophic and noncatastrophic impacts, their incomplete treatme nt of adaptation and technological change, uncertainty in the extrapolation of damages to high temperatures, and assumptions regarding risk aversion. The limited amount of research linking climate impacts to economic damages makes the interagency modeling exercise even more difficult. The interagency group hopes that over
time researchers and modelers will work to fill these gaps and that the SCC estimates used for regulatory analysis by the Fede ral government will continue to evolve with improvements in modeling.

Another limitation of the GHG benefits analysis in this proposed rule is that it does not monetize the impacts associated with the non-CO 2 GHG reductions expected under the proposed standards (in this case, nitrous oxides, methane, and hydorfluorocarbons). The interagency group did not estimate the social costs of non-CO 2 GHG emissions when it developed the current
social cost of CO 2 values. EPA recently requested comment on a methodology to estimate the
benefits associated with non-CO 2 GHG reductions under the proposed New Source Performance Standards (NSPS) for oil and gas exploration (76 FR at 52792). Referred to as the “global warming potential (GWP) approach,” the calculation uses the GWP of the non-CO 2 gas to
estimate CO 2 equivalents and then multiplies these CO 2 equivalent emission reductions by the
social cost of CO 2

.

509 National Research Council (2009). Hidden Costs of Energy: Unpriced Consequences of Energy Production and
Use . National Academies Press. See docket ID EPA-HQ-OAR-2009-0472-11486.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 414 of 768 EPA presented and requested comment on the GWP approach in the NSPS proposal as an interim method to produce estimates of the so cial cost of methane until the Administration develops such values. Similarly, we request comments in this proposed rulemaking on using the GWPs as an interim approach and more broadly about appropriate methods to monetize the
climate benefits of non-CO 2 GHG reductions.

In addition, the U.S. government intends to revise the SCC estimates, taking into account new research findings that were not included in the first round, and has set a preliminary goal of revisiting the SCC values in the ne xt few years or at such time as substantially updated models become available, and to continue to support res earch in this area. In particular, DOE and EPA hosted a series of workshops to help motivate and inform this process. 510 The first workshop focused on conceptual and methodological issues related to integrated assessment modeling and valuing climate change impacts, along with methods of incorporating these estimates into policy analysis.

Applying the global SCC estimates, shown in Table III-68, to the estimated reductions in

CO 2 emissions under the proposed standards, we estimate the dollar value of the GHG related benefits for each analysis year. For internal cons istency, the annual benefits are discounted back to net present value terms using the same discount rate as each SCC estimate (i.e., 5%, 3%, and 2.5%) rather than 3% and 7%. 511 These estimates are provided in Table III-69.

Table III-68: Social Cost of CO 2 , 2017 – 2050 a (in 2009 dollars per Metric Ton)

Y EAR DISCOUNT RATE AND STATISTIC
5% Average 3% Average 2.5% Average 3% 95th Percentile
2017 $6.36 $25.59 $40.94 $78.28

2020 $7.01 $27.10 $42.98 $83.17

2025 $8.53 $30.43 $47.28 $93.11

2030 $10.05 $33.75 $51.58 $103.06

2035 $11.57 $37.08 $55.88 $113.00

2040 $13.09 $40.40 $60.19 $122.95

2045 $14.63 $43.34 $63.59 $131.66

2050 $16.18 $46.27 $66.99 $140.37

a The SCC values are dollar-year and emissions-year specific.

510 Improving the Assessment and Valuation of Climate Change Impacts for Policy and Regulatory Analysis , held November 18-19, 2010 and January 27-28, 2011. Materials available at: http://yosemite.epa.gov/ee/epa/eerm.nsf/vwRepNumLookup/EE-0564?OpenDocument and http://yosemite.epa.gov/ee/epa/eerm.nsf/vwRepNumLookup/EE-0566?OpenDocument

511 It is possible that other benefits or costs of final regulations unrelated to CO 2 emissions will be discounted at rates that differ from those used to develop the SCC estimates.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 415 of 768 Table III-69: Undiscounted Annual Monetized CO 2 Benefits of Proposed Vehicle Program, Annual CO 2 Emission Reductions a & CO 2 Benefits Discounted back to 2012 (dollar values in Millions of 2009$)

YE AR CO 2 EMISSIONS REDUCTION (MMT) BENEFITS

Avg SCC at 5% ($6-$16) a Avg SCC at 3% ($26-$46) a Avg SCC at 2.5% ($41-$67) a 95 th percentile SCC at 3% ($78-$140) a

201
7 2.0 $13 $52 $83 $159

201 8 6.7 $44 $175 $279 $536

201 9 13.9 $94 $369 $587 $1,130

202 0 23.9 $168 $649 $1,030 $1,990

202
1 38.9 $285 $1,080 $1,710 $3,320

202
2 57.6 $439 $1,640 $2,580 $5,020

202 3 80.0 $634 $2,330 $3,640 $7,130

202
4 105.7 $869 $3,150 $4,910 $9,630

202
5 135.0 $1,150 $4,110 $6,380 $12,60
0

203 0 276.2 $2,770 $9,320 $14,200 $28,50
0

204 0 442.1 $5,790 $17,900 $26,600 $54,40
0

205 0 528.6 $8,550 $24,500 $35,400 $74,20
0

Net
Present Value b $34,200 $179,00
0 $306,00
0 $546,0
00

Notes:

a Except for the last row (net presen t value), the SCC values are dollar-y ear and emissions-year specific.

b Net present value of reduced CO 2 emissions is calculated differently from other benefits. The same discount rate used to discount the value of damages from future emissi ons (SCC at 5, 3, 2.5 percent) is used to calculate net present value of SCC for internal consistency. Refer to the SCC TSD for more detail.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 416 of 768 6. Non-Greenhouse Gas Health and Environmental Impacts

This section presents EPA’s analysis of the non-GHG health and environmental impacts that can be expected to occur as a result of the proposed 2017-2025 light-duty vehicle GHG
standards. CO 2 emissions are predominantly the byproduct of fossil fuel combustion processes that also produce criteria and hazardous air poll utants. The vehicles that are subject to the proposed standards are also significant sources of mobile source air pollution such as direct PM,

NO X , VOCs and air toxics. The proposed standa rds would affect exhaust emissions of these pollutants from vehicles. They would also af fect emissions from upstream sources related to changes in fuel consumption. Changes in ambient ozone, PM 2.5 , and air toxics that would result from the proposed standards are expected to affect human health in the form of premature deaths and other serious human health effects, as well as other important public health and welfare
effects.

It is important to quantify the health and environmental impacts associated with the proposed standard because a failure to adequately consider these ancillary co-pollutant impacts
could lead to an incorrect assessment of their net costs and benefits. Moreover, co-pollutant impacts tend to accrue in the near term, while any effects from reduced climate change mostly accrue over a time frame of several decades or longer.

EPA typically quantifies and monetizes the health and environmental impacts related to both PM and ozone in its regulatory impact analyses (RIAs) when possible. However, EPA was unable to do so in time for this proposal. EPA attempts to make emissions and air quality modeling decisions early in the analytical process so that we can complete the photochemical air quality modeling and use that data to inform the health and environmental impacts analysis. Resource and time constraints precluded the Agency from completing this work in time for the proposal. Instead, EPA is using PM-related benefits-per-ton values as an interim approach to estimating the PM-related benefits of the propos al. EPA also provides a characterization of the health and environmental impacts that will be quantified and monetized for the final rulemaking.

This section is split into two sub-sections: th e first presents the PM-related benefits-perton values used to monetize the PM-related co-benefits associated with the proposal; the second explains what PM- and ozone-related health an d environmental impacts EPA will quantify and monetize in the analysis for the final rule. EPA ba ses its analyses on peer-reviewed studies of air quality and health and welfare effects and peer-revi ewed studies of the monetary values of public health and welfare improvements, and is generally consistent with benefits analyses performed for the analysis of the final Cross-State Air Pollution Rule, 512 the final 2014-2018 MY Heavy-

512 Final Cross-State Air Pollution Rule. (76 FR 48208, August 8, 2011).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 417 of 768 Duty Vehicle Greenhouse Gas Rule, 513 and the final Portland Cement National Emissions Standards for Hazardous Air Pollutants (NESHAP) RIA. 514

Though EPA is characterizing the changes in em issions associated with toxic pollutants, we will not be able to quantify or monetize the human health effects associated with air toxic pollutants for either the proposal or the final rule analyses. Please refer to Section III.G for more information about the air toxics emissions imp acts associated with the proposed standards.

a. Economic Value of Reductions in Criteria Pollutants

As described in Section III.G, the proposed standards would reduce emissions of several criteria and toxic pollutants and precursors. In this analysis, EPA estimates the economic value of the human health benefits associated with reducing PM 2.5 exposure. Due to analytical limitations, this analysis does not estimate benefi ts related to other crite ria pollutants (such as ozone, NO 2 or SO 2 ) or toxics pollutants, nor does it monetize all of the potential health and
welfare effects associated with PM 2.5

.
This analysis uses a “benefit-per-ton” method to estimate a selected suite of PM 2.5 -related
health benefits described below. These PM 2.5 benefit-per-ton estima tes provide the total monetized human health benefits (the sum of premature mortality and premature morbidity) of reducing one ton of directly emitted PM 2.5 , or its precursors (such as NO X , SO X , and VOCs), from a specified source. Ideally, the human health benefits would be estimated based on changes
in ambient PM 2.5 as determined by full-scale air qualit y modeling. However, this modeling was not possible in the timeframe for this proposal.

The dollar-per-ton estimates used in this analysis are provided in Table III-70. In the summary of costs and benefits, Section III.H.9 of this preamble, EPA presents the monetized value of PM-related improvements associated with the proposal.

Table III-70 Benefits-per-ton Values (2009$) Derived Using the American Cancer Society Cohort Study for PM-related Premature Mortality (Pope et al., 2002) a

Year c All Sources d Stationary (Non-EGU)

Sources e Mobile Sources

SO X VOC NO X Direct PM2.5 NO X Direct PM2.5

513 U.S. Environmental Protection Agency. (2011). Final Rulemaking to Establish Heavy-Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average Fuel Economy Standards: Regulatory Impact Analysis

, Assessment and Standards Division, Office of Transportation and Air Quality, EPA-420-R-10-009, July 2011. Available on the internet: http://www.epa. gov/otaq/climate/regulations/420r10009.pdf

514 U.S. Environmental Protection Agency (U.S. EPA). 2010. Regulatory Impact Analysis: National Emission Standards for Hazardous Air Pollutants from the Portland Cement Manufacturing Industry. Office of Air Quality Planning and Standards, Research Triangle Park, NC. Augues. Available on the Internet at < http://www.epa.gov/ttn/ecas/regdata/RIAs/portlandcem entfinalria.pdf >. EPA-HQ-OAR-2009-0472-0241Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 418 of 768 Estimated Using a 3 Percent Discount Rate b
2015 $29,000 $1,200 $4,800 $230,000 $5,000 $280,000 2020 $32,000 $1,300 $5,300 $250,000 $5,500 $300,000 2030 $38,000 $1,600 $6,300 $290,000 $6,600 $360,000 2040 $44,000 $1,900 $7,500 $340,000 $7,900 $430,000 Estimated Using a 7 Percent Discount Rate b
2015 $27,000 $1,100 $4,400 $210,000 $4,600 $250,000 2020 $29,000 $1,200 $4,800 $220,000 $5,000 $280,000 2030 $34,000 $1,400 $5,700 $260,000 $6,000 $330,000 2040 $40,000 $1,700 $6,800 $310,000 $7,200 $390,000

a The benefit-per-ton estimates presented in this table are based on an estimate of premature mortality derived from the ACS study (Pope et al., 2002). If the benefit-per-ton es timates were based on the Six-Cities study (Laden et al., 2006), the values would be approximately two-and-a-half ti mes larger. See below for a description of these studies.

b The benefit-per-ton estimates presented in this table assume either a 3 percent or 7 percent discount rate in the valuation of premature mortality to account for a twenty-year segmented cessation lag.

c Benefit-per-ton values were estimated for the years 2015, 2020, and 2030. For intermediate years, such as 2017 (the year the standards begin), we in terpolated exponentially. For years beyond 2030 (including 2040), EPA and NHTSA extrapolated exponentially based on the growth between 2020 and 2030.

d Note that the benefit-per-ton value for SOx is based on the value for Stationary (Non-EGU) sources; no SOx value was estimated for mobile sources. The benefit-per-t on value for VOCs was estimated across all sources.

e Non-EGU denotes stationary sources of emi ssions other than electric generating units.

The benefit per-ton technique has been used in previous analyses, including EPA’s 2012- 2016 Light-Duty Vehicle Greenhouse Gas Rule, 515 516 and the Portland Cement National Emissions Standards for Hazardous Air Pollutants (NESHAP) RIA. 517 Table III-71 shows the quantified and unquantified PM 2.5 -related co-benefits captured in those benefit-per-ton estimates.

Table III-71 Human Health and Welfare Effects of PM 2.5

Pollutant /

Effect Quantified and Monetized in Primary Estimates Unquantified Effects Changes in:

PM 2.5 Adult premature mortality Bronchitis: chronic and acute Hospital admissions: respiratory and cardiovascular Emergency room visits for asthma Nonfatal heart attacks (myocardial infarction) Lower and upper respiratory illness Subchronic bronchitis cases Low birth weight Pulmonary function Chronic respiratory diseas es other than chronic bronchitis Non-asthma respiratory emergency room visits Visibility

515 U.S. Environmental Protection Agency (U.S. EPA), 2010. Regulatory Impact Analysis, Final Rulemaking to Establish Light-Duty Vehicle Greenhouse Gas Emissi on Standards and Corporate Average Fuel Economy Standards. Office of Transportation and Air Quality. April. Available at http://www.epa.gov/otaq/climate/regulat ions/420r10009.pdf. EPA-420-R-10-009

516 U.S. Environmental Protection Agency (U.S. EPA). 2008. Regulatory Impact Analysis, 2008 National Ambient Air Quality Standards for Ground-level Ozone, Chapter 6. Office of Air Quality Planni ng and Standards, Research Triangle Park, NC. March. Available at <http://www.epa.gov/ttn/ecas/regdata/RIAs/6-ozoneriachapter6.pdf>.

517 U.S. Environmental Protection Agency (U.S. EPA). 2010. Regulatory Impact Analysis: National Emission Standards for Hazardous Air Pollutants from the Portland Cement Manufacturing Industry. Office of Air Quality Planning and Standards, Research Triangle Park, NC. Augues. Available on the Internet at < http://www.epa.gov/ttn/ecas/regdata/RIAs/portlandcem entfinalria.pdf >. EPA-HQ-OAR-2009-0472-0241Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 419 of 768 Minor restricted-activity days Work loss days Asthma exacerbations (asthmatic population) Infant mortality Household soiling

Consistent with the cost-benefit analysis that accompanied the NO 2 NAAQS, 518,519 the benefits estimates utilize the concentration-resp onse functions as reporte d in the epidemiology literature. To calculate the total monetized imp acts associated with quantified health impacts, EPA applies values derived from a number of sources. For premature mortality, EPA applies a value of a statistical life (VSL) derived from the mortality valuation literatu re. For certain health impacts, such as chronic bronchitis and a number of respiratory-related ailments, EPA applies willingness-to-pay estimates derived from the va luation literature. For the remaining health impacts, EPA applies values derived from current cost-of-illness and/or wage estimates.

A more detailed description of the benefit-per-ton estimates is provided in Chapter 4 of the Draft Joint TSD that accompanies this rulemaking. Readers interested in reviewing the complete methodology for creating the benefit-per-ton estimates used in this analysis can consult the Technical Support Document (TSD) 520 accompanying the recent final ozone NAAQS RIA (U.S. EPA, 2008). 521 Readers can also refer to Fann et al. (2009) 522 for a detailed description of the benefit-per-ton methodology. 523

518 Although we summarize the main issues in this chapter, we encourage intere sted readers to see benefits chapter of the RIA that accompanied the NO2 NAAQS for a more deta iled description of recent changes to the PM benefits presentation and preference for the no-threshold model. Note that the cost-benefit analys is was prepared solely for purposes of fulfilling analysis requirements under Executive Order 12866 and was not considered, or otherwise played any part, in the decision to revise the NO2 NAAQS.

519 U.S. Environmental Protection Agency (U.S. EPA). 2010. Final NO2 NAAQS Regulatory Impact Analysis (RIA). Office of Air Quality Planning and Standards, Resear ch Triangle Park, NC. April. Available on the Internet

at http://www.epa.gov/ttn/ecas/regdata /RIAs/FinalNO2RIAfulldocument.pdf. Accessed March 15, 2010. EPA-HQOAR-2009-0472-0237U.S. Environmental Protection Agency (U.S. EPA). 2009.

520 U.S. Environmental Protection Agency (U.S. EPA). 2008. Technical Support Document: Calculating Benefit Per-Ton estimates, Ozone NAAQS Docket #EPA-HQ-OAR-20 07-0225-0284. Office of Air Quality Planning and Standards, Research Triangle Park, NC. March. Av ailable on the Internet at <http://www.regulations.gov>.

521 U.S. Environmental Protection Agency (U.S. EPA). 2008. Regulatory Impact Analysis, 2008 National Ambient Air Quality Standards for Ground-level Ozone, Chapter 6. Office of Air Quality Planni ng and Standards, Research Triangle Park, NC. March. Available at <http://www. epa.gov/ttn/ecas/regdata/RIAs/6- ozoneriachapter6.pdf>. Note that the cost-benefit analysis was prepared solely for purposes of fulfilling analysis requirements under Executive Order 12866 and was not considered, or otherwise played any part, in the decision to revise the Ozone NAAQS.

522 Fann, N. et al. (2009). The influence of location, s ource, and emission type in estimates of the human health benefits of reducing a ton of air pollution. Air Qu al Atmos Health. Published online: 09 June, 2009.

523 The values included in this report are different from those presented in the article cited above. Benefits methods change to reflect new information and evaluation of the scie nce. Since publication of the June 2009 article, EPA has made two significant changes to its benefits methods: (1) We no longer assume that a threshold exists in PM-related models of health impacts; and (2) We have revised the Va lue of a Statistical Life to equal $6.3 million (year 2000$), up from an estimate of $5.5 million (year 2000$) used in the June 2009 report. Please refer to the following website for updates to the dollar-per-ton estimates: http://www.epa.gov/air/benmap/bpt.htmlSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 420 of 768 As described in the documentation for the benefit per-ton estimates cited above, nationalper-ton estimates were developed for selected pollutant/source category combinations. The perton values calculated therefore apply only to tons reduced from those specific pollutant/source combinations (e.g., NO 2 emitted from mobile sources; direct PM emitted from stationary sources). Our estimate of PM 2.5 benefits is therefore based on the total direct PM 2.5 and PMrelated precursor emissions controlled by sect or and multiplied by each per-ton value.

The benefit-per-ton estimates are subject to a number of assumptions and uncertainties:

 They do not reflect local variability in population density, meteorology, exposure, baseline health incidence rates, or other local factors that might lead to an
overestimate or underestimate of the actual benefits of controlling fine particulates. EPA will conduct full-s cale air quality modeling for the final rulemaking in an effort to capture this variability.

 This analysis assumes that all fine particles, regardless of their chemical composition, are equally potent in caus ing premature mortality. This is an important assumption, because PM 2.5 produced via transported precursors emitted from stationary sources may differ significantly from direct PM 2.5 released from diesel engines and other industrial sources, but no clear scientific grounds exist for supporting differen tial effects estimates by particle type.

 This analysis assumes that the health imp act function for fine particles is linear within the range of ambient concentrations under consideration. Thus, the
estimates include health benefits from reduc ing fine particles in areas with varied
concentrations of PM 2.5, including both regions that are in attainment with fine particle standard and those that do not meet the standard down to the lowest
modeled concentrations.

 There are several health benefits categories that EPA was unable to quantify due to limitations associated with using be nefits-per-ton estimates, several of which
could be substantial. Because the NO X and VOC emission reductions associated with this proposal are also precursors to ozone, reductions in NO X and VOC
would also reduce ozone formation and the health effects associated with ozone exposure. Unfortunately, ozone-related benefits-per-ton estimates do not exist due to issues associated with the comple xity of the atmospheric air chemistry and
nonlinearities associated with ozone format ion. The PM-related benefits-per-ton estimates also do not include any human welfare or ecological benefits. Please refer to Chapter 6.3 of the DRIA that accompanies this proposal for a description of the agecy’s plan to quantify and monetize the PM- and ozone-related health impacts for the FRM and a description of the unquantified co-pollutant benefits associated with this rulemaking.

 There are many uncertainties associated with the health impact functions used in this modeling effort. These include: w ithin-study variability (the precision withSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 421 of 768 which a given study estimates the relationship between air quality changes and health effects); across-study variation (d ifferent published studies of the same pollutant/health effect relationship typically do not report identical findings and insome instances the differences are substantial); the application of concentrationresponse functions nationwide (does not account for any relationship between region and health effect, to the extent that such a relationship exists); extrapolation of impact functions across population (we assumed that certain health impact functions applied to age ranges broader than that considered in theoriginal epidemiological study); and various uncertainties in the concentrationresponse function, including causality an d thresholds. These uncertainties may
under- or over-estimate benefits.

 EPA has investigated methods to characterize uncertainty in the relationship
between PM 2.5 exposure and premature mortality. EPA’s final PM 2.5 NAAQS analysis provides a more complete picture about the overall uncertainty in PM 2.5 benefits estimates. For more information, please consult the PM 2.5 NAAQS RIA (Table 5.5). 524

 The benefit-per-ton estimates used in this analysis incorporate projections of key variables, including atmospheric conditi ons, source level emissions, population, health baselines and incomes, technology. These projections introduce some uncertainties to the benefit per ton estimates.

 As described above, using the benefit-per-ton value derived from the ACS study (Pope et al., 2002) alone provides an incomplete characterization of PM 2.5 benefits. When placed in the context of the Expert Elicitation results, this estimate
falls toward the lower end of the dist ribution. By contrast, the estimated PM 2.5 benefits using the coefficient reported by Laden in that author’s reanalysis of the
Harvard Six Cities cohort fall toward th e upper end of the Expert Elicitation
distribution results.

As mentioned above, emissions changes and benefits-per-ton estimates alone are not a good indication of local or regional air quality and health impacts, as there may be localized impacts associated with the proposed rulemaki ng. Additionally, the atmospheric chemistry
related to ambient concentrations of PM 2.5 , ozone and air toxics is very complex. Full-scale photochemical modeling is therefore necessary to provide the needed spatial and temporal detail to more completely and accurately estimate the changes in ambient levels of these pollutants and their associated health and welfare impacts. As discussed above, timing and resource constraints precluded EPA from conducting a full-scale photochemical air quality modeling analysis in time
for the NPRM. For the final rule , however, a national-scale air quality modeling analysis will be

524 U.S. Environmental Protection Agency. October 2006. Final Regulatory Impact An alysis (RIA) for the Final National Ambient Air Quality Standards for Particulate Ma tter. Prepared by: Office of Air and Radiation.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 422 of 768 performed to analyze the impacts of the standards on PM 2.5 , ozone, and selected air toxics. The benefits analysis plan for the final rulemaking is discussed in the next section.

b. Human Health and Environmenta l Benefits for the Final Rule

i. Human Health and Environmental Impacts

To model the ozone and PM air quality benefits of the final rule, EPA will use the Community Multiscale Air Quality (CMAQ) model (see Section III.G.5. for a description of the CMAQ model). The modeled ambient air qualit y data will serve as an input to the Environmental Benefits Mapping and Analysis Program (BenMAP). 525 BenMAP is a computer program developed by EPA that integrates a number of the modeling elements used in previous RIAs (e.g., interpolation functions, population pr ojections, health impact functions, valuation functions, analysis and pooling methods) to tran slate modeled air concentration estimates into
health effects incidence estimates and monetized benefits estimates.

Chapter 6.3 in the DRIA that accompanies this proposal lists the co-pollutant health effect concentration-response functions EPA will use to quantify the non-GHG incidence impacts associated with the final light-duty ve hicles standard. These include PM- and ozonerelated premature mortality, chronic bronchitis, nonfatal heart attacks, hospital admissions (respiratory and cardiovascular) , emergency room visits, acute bronchitis, minor restricted activity days, and days of work and school lost.

ii. Monetized Impacts

To calculate the total monetized impacts asso ciated with quantified health impacts, EPA applies values derived from a number of sources. For premature mortality, EPA applies a value of a statistical life (VSL) derived from the mort ality valuation literature. For certain health impacts, such as chronic bronchitis and a number of respiratory-related ailments, EPA applies willingness-to-pay estimates derived from the va luation literature. For the remaining health impacts, EPA applies values derived from current cost-of-illness and/or wage estimates. Chapter 6.3 in the DRIA that accompanies this proposal presents the monetary values EPA will apply to changes in the incidence of health and welfar e effects associated with reductions in non-GHG pollutants that will occur when these GHG control strategies are finalized.

iii. Other Unquantified Health and Environmental Impacts

In addition to the co-pollutant health and environmental impacts EPA will quantify for the analysis of the final standard, there are a number of other health and human welfare endpoints that EPA will not be ab le to quantify or monetize because of current limitations in the methods or available data. These impacts are asso ciated with emissions of air toxics (including

525 Information on BenMAP, including downloads of the so ftware, can be found at http://www.epa.gov/ttn/ecas/ benmodels.html.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 423 of 768 benzene, 1,3-butadiene, formaldehyde, acetaldehyde, acrolein, and ethanol), ambient ozone, and
ambient PM 2.5 exposures. Chapter 6.3 of the DRIA lists these unquantified health and environmental impacts.

While there will be impacts associated with air toxic pollutant emission changes that result from the final standard, EPA will not attemp t to monetize those impacts. This is primarily because currently available tools and methods to asse ss air toxics risk from mobile sources at the national scale are not adequate for extrapolation to incidence estimations or benefits assessment. The best suite of tools and methods currently available for assessment at the national scale are those used in the National-Scale Air Toxics Assessment (NATA). The EPA Science Advisory Board specifically commented in their review of the 1996 NATA that these tools were not yet ready for use in a national-scale benefits analysis, because they did not consider the full distribution of exposure and risk, or address sub-chronic health effects. 526 While EPA has since improved the tools, there remain critical limitations for estimating incidence and assessing benefits of reducing mobile source air toxics. EPA continues to work to address theselimitations; however, EPA does not anticipate having methods and tools available for nationalscale application in time for the analysis of the final rules. 527

7. Energy Security Impacts

The proposed GHG standards require improvemen ts in light-duty vehicle fuel efficiency which, in turn, will reduce overall fuel consumpti on and help to reduce U.S. petroleum imports. Reducing U.S. petroleum imports lowers both the financial and strategic risks caused by potential sudden disruptions in the supply of imported petroleum to the U.S. The economic value of reductions in these risks provides a measure of improved U.S. energy security. This section summarizes EPA’s estimates of U.S. oil import reductions and energy security benefits from this proposal. Additional discussion of this issue can be found in Chapter 4.2.8 of the Joint

TSD.

a. Implications of Reduced Petroleum Use on U.S. Imports

In 2010, U.S. petroleum import expenditures re presented 14 percent of total U.S. imports of all goods and services. 528 These expenditures rose to 18 percent by April of 2011. 529 In 2010,

526 Science Advisory Board. 2001. NATA – Evaluating the National-Scale Air Toxics Assessment for 1996 – an SAB Advisory. http://www.epa. gov/ttn/atw/sab/sabrev.html.

527 In April, 2009, EPA hosted a workshop on estimating the benefits of reducing hazardo us air pollutants. This workshop built upon the work accomplish ed in the June 2000 Science Advi sory Board/EPA Wo rkshop on the Benefits of Reductions in Exposure to Hazardous Air Pollutants, which generated thoughtful discussion on approaches to estimating human health benefits from reductions in air toxics exposure, but no consensus was reached on methods that could be impl emented in the near term for a broad selection of air toxics. Please visit http://epa.gov/air/toxicair/2009workshop.html for more information about the workshop and its associated materials.

528 http://www.eia.gov/dnav/pet/hist/LeafHandler.ashx?n=PET&s=WTTIMUS2&f=W

529 http://www.eia.gov/dnav/pet/pet_move_impcus_a2_nus_ep00_im0_mbblpd_a.htmSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 424 of 768 the United States imported 49 percent of the petroleum it consumed 530 , and the transportation sector accounted for 71 percent of total U.S. petroleum consumption. This compares to approximately 37 percent of total U.S. petroleum supplied by imports and 55 percent of U.S. petroleum consumption in the transportation sector in 1975. 531

Requiring vehicle technology that reduces GHGs and fuel consumption in light-duty vehicles is expected to lower U.S. oil impo rts. EPA’s estimates of reductions in fuel consumption resulting from the proposed standards are discussed in Section III.H.3 above, and in
EPA’s draft RIA. 532

The agencies conducted a detailed analysis of future changes in U.S. transportation fuel consumption, petroleum imports, and domestic fuel refining projected to occur under alternative economic growth and oil price scenarios reported by the EIA in its Annual Energy Outlook

2011. 533 On the basis of this analysis, we estimate that approximately 50 percent of the reduction in fuel consumption resulting from adopting improved GHG emission and fuel efficiency standards is likely to be reflec ted in reduced U.S. imports of re fined fuel, while the remaining 50 percent is expected to be reflected in reduced do mestic fuel refining. Of this latter figure, 90 percent is anticipated to reduce U.S. imports of crude petroleum for use as a refinery feedstock, while the remaining 10 percent is expected to reduce U.S. domestic production of crude petroleum. Thus, on balance, each gallon of fuel saved as a consequence of the GHG and fuel efficiency standards is anticipated to reduce to tal U.S. imports of petroleum by 0.95 gallons. 534
Table III-1 below compares EPA’s estimates of the reduction in imports of U.S. crude oil and petroleum-based products from this program to projected total U.S. imports for selected years

.
Table III-72 Projected Reductions from th is Proposal and Total U.S. PetroleumBased Imports for Selected Years (Millions of Barrels per Day, mmbd)

530 http://www.eia.gov/dnav/pet/pet_pri_rac2_dcu_nus_m.htm

531 Source: U.S. Department of Energy, Annual Energy Re view 2008, Report No. DOE/EIA-0384(2008), Tables 5.1 and 5.13c, June 26, 2009.

531 Due to timing constraints, the analysis of energy secu rity impacts was conducted with preliminary estimates of the fuel savings projected from this proposal. Relative to the gasoline savings presented in the proposal, the savings used for the energy security analysis were roughly 1% lower over the years modeled.

533 Energy Information Administration, Annual Energy Outlook 2011, Reference Case and other scenarios, available at http://www.eia.gov/oiaf/aeo/tablebrowser/ (last accessed October 12, 2011).

534 This figure is calculated as 0.50 + 0.50*0.9 = 0.50 + 0.45 = 0.95.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 425 of 768 Year U.S. Petroleum-Based
Reductions from the Proposal (mmbd) U.S. Total PetroleumBased Imports without the Proposal

(mmbb)

2020 0.138 9.26

2030 1.63 8.94

2040 2.63 NA

2050 3.14 NA
Note: NA –Not available, (forecasts reported in EI A’s Annual Energy Outlook 2011 extend only to 2035)

b. Energy Security Implications

In order to understand the energy security implications of reducing U.S. petroleum imports, EPA worked with Oak Ridge National Laboratory (ORNL), which has developed approaches for evaluating the economic costs and en ergy security implications of oil use. Theenergy security estimates provided below are based upon a methodology developed in a peerreviewed study entitled, ” The Energy Security Benefits of Reduced Oil Use, 2006-2015 ,” completed in March 2008. This study is included as part of the docket for this proposal. 535,536

When conducting its analysis, ORNL considered the full economic cost of importing petroleum into the United States. The economic cost of importing petroleum into the U.S. is defined to include two components in addition to the purchase price of petroleum itself. These are: (1) the higher costs for oil imports resulting from the effect of increasing U.S. import demand on the world oil price and on the market power of the Organization of the Petroleum Exporting Countries (i.e., the “demand” or “monopsony” costs); and (2) the risk of reductions in U.S. economic output and disruption of the U.S. economy caused by sudden disruptions in the supply of imported petroleum to the U.S. (i.e ., “macroeconomic disruption/adjustment costs”). In its analysis of energy security benefits from reducing U.S. petroleum imports, however, the agencies included only the latter component (discussed below).

ORNL’s analysis of energy security benefits from reducing U.S. oil imports did not include an estimate of potential reductions in costs for maintaining a U.S. military presence to help secure stable oil supply from potentially vulnerable regions of the world because attributing military spending to particular missions or activitie s is difficult. Attempts to attribute some share of U.S. military costs to oil imports are further complicated by the need to estimate how those costs vary with incremental variations in U.S. oil imports. Several commenters for the 2012-

535 Leiby, Paul N., " Estimating the Energy Security Benefits of Reduced U.S. Oil Imports " Oak Ridge National Laboratory, ORNL/TM-2007/028, Final Report, 2008. (Docket EPA-HQ-OAR-2010-0162)

536 The ORNL study “ The Energy Security Benefits of Reduced Oil Use, 2006-2015 ," completed in March 2008, is an update version of the approach used for estimating th e energy security benefits of U.S. oil import reductions developed in an ORNL 1997 Report by Leiby, Paul N., Do nald W. Jones, T. Randall Curlee, and Russell Lee, entitled “ Oil Imports: An Assessment of Benefits and Costs. " (Docket EPA-HQ-OAR-2010-0162)Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 426 of 768 2016 light-duty vehicle proposal recommended that the agencies attempt to estimate the avoided U.S. military costs associated with reductions in U.S. oil imports. The agencies request comment on this issue, including whether there are new stud ies that credibly estimate the military cost of securing stable oil supplies and, if so, how should these new estimates be factored into this proposal’s energy security analysis. See Section 4.2.8 of the TSD for a more detailed discussion of the national security implications of this proposed rule.

For this action, ORNL estimated energy s ecurity premiums by incorporating the most recently available AEO 2011 Reference Case oil price forecasts and market trends. Energy security premiums for the years 2020, 2030, 2035, 2040 and 2050 are presented in Table III-73 as well as a breakdown of the components of the energy security premiums for each of these

years. 537 The components of the energy security premium and their values are discussed in detail in the Joint TSD Chapter 4.2.8.

Table III-73 Energy Security Premiums in Selected Years (2009$/Barrel)

Year (range) Monopsony Macroeconomic Disruption/Adjustment Costs Total Mid-Point

2020 $11.12 ($3.78 - $21.21) $7.10 ($3.40 - $10.96) $18.22 ($9.53 - $29.06)

2030 $10.91 ($3.74 - $20.47) $8.32 ($4.09 – $13.34) $19.23 ($10.51 - $29.02)

2035 $10.11 ($3.51 - $18.85) $8.60 ($4.41 - $13.62) $18.71 ($10.30 – $28.20)

2040 $10.11 ($3.51 - $18.85) $8.60 ($4.41 - $13.62) $18.71 ($10.30 – $28.20)

2050 $10.11 ($3.51 - $18.85) $8.60 ($4.41 - $13.62) $18.71 ($10.30 – $28.20)

Note: Values in parentheses represent a 90% confidence interval around the central value.

The literature on the energy security for the last two decades has routinely combined the monopsony and the macroeconomic disruption components when calculating the total value of the energy security premium. However, in the context of using a global social cost of carbon (SCC) value, the question arises: how should the energy security premium be determined when a global perspective is taken? Monopsony benefits represent avoided payments by the United States to oil producers in foreign countries that result from a decrease in the world oil price as the U.S. decreases its consumption of imported oil.

537 AEO 2011 forecasts energy market trends and values on ly to 2035. The energy security premium estimates post2035 were assumed to be the 2035 estimate.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 427 of 768 Although there is clearly a benefit to the U.S. when considered from a domestic perspective, the decrease in price due to decreased demand in the U.S. also represents a loss to other countries. Given the redistributive nature of this monopsony effect from a global perspective, it is excluded in the energy security benefits calculations for this proposal. In contrast, the other portion of the energy security premium, the U.S. macroeconomic disruption and adjustment cost that arises from U.S. pe troleum imports, does not have offsetting impacts outside of the U.S., and, thus, is included in the energy security benefits estimated for this proposal. To summarize, EPA has included only the macroeconomic disruption portion of the energy security benefits to estimate the monetary value of the total energy security benefits of this program.

For this proposal, using EPA’s fuel consump tion analysis in conjunction with ORNL’s energy security premium estimates, 538

, 539 the agencies’ developed estimates of the total energy security benefits for the years 2017 through 2050 as shown in Table III-74. 540

Table III-74. Undiscounted Annual Energy Security Benefits, & Proposed Program Benefits Discounted back to 2012 (2009$)

Year Oil Imports
Reduced (mmb) Benefits ($Millions)

2017 4.3 $29 2018 14.2 $97 2019 29.3 $204 2020 50.5 $358 2021 81.9 $593 2022 122 $896 2023 170 $1,270 2024 225 $1,710 2025 289 $2,240 2030 595 $4,950 2040 959 $8,250 2050 1,147 $9,870 NPV, 3% $84,900 NPV, 7% $32,700 Note: Annual values represent undiscounted benefits; net present values represent annual costs discounted to 2012.

538 AEO 2011 forecasts energy market trends and values on ly to 2035. The energy security premium estimates post2035 were assumed to be the 2035 estimate.

539 Due to timing constraints, the analys is of energy security impacts was conducted with preliminary estimates of the fuel savings projected from this proposal. Relative to the gasoline savings presented in the proposal, the savings used for the energy security analysis were roughly 1% lower over the years modeled.

540 Estimated reductions in U.S. imports of finished petr oleum products and crude oil are 95% of 50.6 million barrels (MMB) in 2020, 619 MMB in 2030, 1,000 MMB in 2040, and 1,195 MMB in 2050.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 428 of 768 The energy security analysis conducted for this proposal estimates that the world price of oil will fall modestly in response to lower U.S. demand for refined fuel. One potential result of this decline in the world price of oil would be an increase in the consumption of petroleum products, particularly outside the U.S. In addition, other fuels could be displaced from the increasing use of oil worldwide. For example, if a decline in the world oil price causes an increase in oil use in China, India, or another country’s industrial sector, this increase in oil consumption may displace natural gas usage. Alterna tively, the increased oil use could result in a decrease in coal used to produce electricity. An increase in the consumption of petroleum products particularly outside the U.S., could lead to a modest increase in emissions of greenhouse gases, criteria air pollutants, and air borne toxics from their refining and use. However, lower usage of, for example, displaced coal would result in a decrease in greenhouse gas emissions. Therefore, any assessment of the impacts on GHG emissions from a potential increase in world oil demand would need to take into account the impacts on all portions of global energy sector. The agencies’ analyses have not attempted to estimate these effects.

Since EPA anticipates that more electric ve hicles (EVs) and plug-in hybrid electric vehicles (PHEVs) will penetrate the U.S. autom obile market over time as a result of this proposal, the Agency is considering analyzing the energy security implications of these vehicles and the fuels that they consume. These vehicles run on electricity either in whole (EVs), or in part (PHEVs), which displaces conventional trans portation fuel such as gasoline and diesel. EPA does not have sufficient information for this proposal to conduct an analysis of the energy security implications of increased use of EVs/PHEVs, but is considering how to conduct this type of analysis in the future. The Agency r ecognizes that the fleet penetration of EV/PHEV’s will be relatively small in the time period of th ese standards (fewer than 3% of new vehicles in 2025), but views establishing a framework for exam ining the energy security implications of these vehicles as important for longer-term analysis.

Key questions that arise with increased use of electricity in vehicles in the U.S. include whether there is the potential for disruptions in el ectricity supply in general, or more specifically, from increased electrification of the U.S. vehicle fleet. Also, if there is the potential for supply disruptions in electricity markets, how likel y would the disruptions be associated with disruptions in the supply of oil? In addition, what is the overall expected impact, if any, of additional EV/PHEV use on the stability and flexibi lity of fuel and electricity markets? Finally, such analysis may also need to consider the s ource of electricity used to power EVs/PHEVs.
EPA solicits comments on how to best conduct this type of analysis, including any studies or research that have been published on these issues.

8. Additional Impacts

There are other impacts associated with the CO 2 emissions standards and associated reduced fuel consumption that vary with m iles driven. Lower fuel consumption would,Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 429 of 768 presumably, result in fewer trips to the filling station to refuel and, thus, time saved. The rebound effect, discussed in deta il in Section III.H.4.c, produces additional benefits to vehicle owners in the form of consumer surplus from the increase in vehicle-miles driven, but may also
increase the societal costs associated with traffi c congestion, motor vehicle crashes, and noise. These effects are likely to be relatively small in comparison to the value of fuel saved as a result of the standards, but they are nevertheless important to include. Table III.H.8-1 summarizes the other economic impacts. Please refer to Preamble Section II.E and the Joint TSD that accompanies this rule for more information about these impacts and how EPA and NHTSA use them in their analyses.

Table III.H.8-1 Additional Impacts Associ ated with the Light-Duty Vehicle GHG Program ($Millions of 2007 dollars)

2017 2020 2030 2040 2050 NPV, 3% NPV, 7% Accidents, Noise, Congestion $66 $848 $7,960 $12,500 $16,300 $136,000 $53,300

Value of Increased Driving a $92 $1,250 $13,700 $23,600 $33,300 $250,000 $95,400

Value of Less Frequent Refueling $24 $295 $3,890 $6,990 $9,320 $71,600 $27,100

a Calculated using post-tax fuel prices.

9. Summary of Costs and Benefits

In this section, the agencies present a summary of costs, benefits, and net benefits of the proposed program.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 430 of 768 Table III-75 Undiscounted Annual Costs & Costs of the Proposed Program Discounted Back to 2012 at 3% and 7% Discount Rates (Millions, 2009$) a

shows the estimated annual monetized costs of the proposed program for the indicated calendar years. The table also shows the net pres ent values of those costs for the calendar years 2012-2050 using both 3 percent and 7 percent discount rates. 541 Table III-76 shows the undiscounted annual monetized fuel savings of the proposed program. The table also shows the net present values of those fuel savings for the same calendar years using both 3 percent and 7percent discount rates. In this table, the aggregate value of fuel savings is calculated using pretax fuel prices since savings in fuel taxes do no t represent a reduction in the value of economic resources utilized in producing and consuming fuel . Note that the fuel savings shown here result from reductions in fleet-wide fuel use. Thus, fuel savings grow over time as an increasing fraction of the fleet meets the proposed standards.

Table III-75 Undiscounted Annual Cost s & Costs of the Proposed Program Discounted Back to 2012 at 3% and 7% Discount Rates (Millions, 2009$) a

2 017 2 020 2 030 2 040 2 050 NPV, Years 2012-

2050, 3% Discount Rate NPV, Years 2012-

2050, 7% Discount Rate Technology Costs $ 2,000 $ 8,370 $ 35,700 $ 39,800 $ 44,600 $545,00
0 $239,0
00

Note:

a Technology costs for separate light-duty vehicle segments can be found in Section III.H.2. Annual costs shown are undiscounted values.

Table III-76: Undiscounted Annual Fuel S avings & Proposed Program Fuel Savings Discounted Back to 2012 at 3% and 7% Discount Rates (Millions, 2009$) a

2017 2 020 2 030 2040 2 050 NPV, Years 2012-

2050, 3% Discount Rate NPV, Years 2012-

2050, 7% Discount Rate Fuel Savings (pre-tax) $561 $ 6,920 $ 88,300 $151,000 $ 198,000 $1,570,0
00 $601,00
0

Note:

a Fuel savings for separate light-duty vehicle segments can be found in Section III.H.3. Annual costs shown are undiscounted values.

Table III-77 presents estimated annual monetized benefits for the indicated calendar years. The table also shows the net present values of those benefits for the calendar years 2012- 2050 using both 3 percent and 7 percent discount rates. The table shows the benefits of reduced

CO 2 emissions—and consequently the annual quantified benefits ( i.e. , total benefits)—for each of the four social cost of carbon (SCC) values estimated by the interagency working group. As

541 For the estimation of the stream of costs and benefits, we assume that after implementation of the proposed MY 2017-2025 standards, the 2025 standard s apply to each year thereafter.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 431 of 768 discussed in the RIA Chapter 7.2, there are some limitations to the SCC analysis, including theincomplete way in which the integrated assessment models capture catastrophic and noncatastrophic impacts, their incomplete treatme nt of adaptation and technological change, uncertainty in the extrapolation of damages to high temperatures, and assumptions regarding risk
aversion.

In addition, these monetized GHG benefits exclude the value of net reductions in nonCO 2 GHG emissions (CH 4 , N 2 O, HFC) expected under this action. Although EPA has not
monetized the benefits of reductions in non-CO 2 GHGs, the value of these reductions should not be interpreted as zero. Rather, the net reductions in non-CO 2 GHGs will contribute to this program’s climate benefits, as explained in Section III.H.5.

Table III-77: Monetized Undiscounted Annual Benefits & Benefits of the Proposed Program Discounted Back to 2012 at 3% and 7% Discount Rates (Millions, 2009$)

2 017 2 020 2 030 2 040 2 050 NP V, Years 2012-2050, 3% Discount

Rate a NP V, Years 2012-2050, 7% Discount
Rate a

Reduced CO 2 Emissions at each assumed SCC value b

5% (avg SCC) $
13 $
168 $ 2,770 $ 5,790 $ 8,550 $34,
200 $34,
200

3% (avg SCC) $
52 $
649 $ 9,320 $ 17,900 $ 24,500 $17 9,000 $17 9,000

2.5% (avg SCC) $
83 $ 1,030 $ 14,200 $ 26,600 $ 35,400 $30 6,000 $30 6,000

3% (95th %ile) $
159 $ 1,990 $ 28,500 $ 54,400 $ 74,200 $54 6,000 $54 6,000

Energy SecurityBenefits (macrodisruption costs) $
29 $
358 $ 4,950 $ 8,250 $ 9,870 $84,
900 $32,
700

Accidents, Congestion, Noise Costs g $
66 $
848 $ 7,960 $ 12,500 $ 16,300 $13 6,000 $53,
300

Increased Travel Benefits $
92 $ 1,250 $ 13,700 $ 23,600 $ 33,300 $25 0,000 $95,
400 Refueling Time Savings $
24 $
587 $ 6,930 $ 11,200 $ 13,300 $11 7,000 $45,
500
PM 2.5 Related Impacts
c,d,e $
11 $
147 $ 1,570 $ 2,840 $ 4,050 $29,
700 $11,
300
Non-CO 2 GHG Impacts f n /a n /a n /a n /a n/a n/aSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 432 of 768 Total Annual Benefits at each assumed SCC value b

5% (avg SCC) $
103 $ 1,370 $ 18,900 $ 34,900 $ 48,800 $33 4,000 $14 7,000

3% (avg SCC) $
142 $ 1,850 $ 25,500 $ 47,000 $ 64,700 $47 9,000 $29 3,000

2.5% (avg SCC) $
173 $ 2,230 $ 30,400 $ 55,700 $ 75,700 $60 5,000 $41 9,000

3% (95th %ile) $
249 $ 3,190 $ 44,600 $ 83,500 $ 114,000 $84 6,000 $66 0,000

Notes:

a Net present value of reduced CO 2 emissions is calculated differently than other benefits. The same discount rate used to discount the value of damages from future emissi ons (SCC at 5, 3, 2.5 percent) is used to calculate net present value of SCC for internal cons istency. Refer to the SCC TSD for more detail. Annual costs shown are undiscounted values.

b Section III.H.5 notes that SCC increases over time. For the years 2012-2050, the SCC estimates range as follows: for Average SCC at 5%: $5-$16; for Average SCC at 3%: $23-$46; for Average SCC at 2.5%: $38-$67; and for
95 th percentile SCC at 3%: $70-$140.

c Note that the co-pollutant impacts associated with the standards presen ted here do not include the full complement of endpoints that, if quantified and monetized, would change the total monetized estimate of rule-related impacts. Instead, the co-pollutant benefits are based on benefit- per-ton values that reflect only human health impacts
associated with reductions in PM 2.5 exposure. Ideally, human health and environmental benefits would be based on changes in ambient PM 2.5 and ozone as determined by full-scale air qua lity modeling. However, EPA was unable to conduct a full-scale air quality modeling an alysis in time for the proposal. We intend to more fully capture the copollutant benefits for the analysis of the final standards.

d The PM 2.5 -related benefits (derived from benefit-per-ton values) presented in this table are based on an estimate of premature mortality derived from the ACS study (Pope et al ., 2002). If the benefit-per-ton estimates were based on the Six Cities study (Laden et al., 2006), the values would be nearly two-and-a-half times larger.

e The PM 2.5 -related benefits (derived from benefit-per-ton values) presented in this table assume a 3% discount rate in the valuation of premature mortality to account for a twenty-year segmented cessation lag. If a 7% discount rate had been used, the values would be approximately 9% lower.
f The monetized GHG benefits presented in this analysis exclude the value of changes in non-CO 2 GHG emissions expected under this program ( See DRIA Chapter 7.1). Although EPA has not monetized changes in non-CO 2 GHGs, the value of any increases or reductions should not be interpreted as zero. We seek comment on a method of quantifying non-CO 2 GHG benefits in Section III.H.5.

g Positive values for Accidents, Congestion, and Noise costs represent an increase in cost s. Therefore, they are treated as negative values when calculating the total benefits.

Table III-78 presents estimated annual net bene fits for the indicated calendar years. The table also shows the net present values of those net benefits for the calendar years 2012-2050 using both 3 percent and 7 percent discount rates. The table includes the benefits of reduced CO 2 emissions (and consequently the annual net benefits) for each of the four SCC values considered by EPA.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 433 of 768 Table III-78: Undiscounted Annual Monetized Ne t Benefits & Net Benefits of the Proposed Program Discounted Back to 2012 at 3% and 7% Discount Rates (Millions, 2009$)

2 017 2 020 2 030 2040 2 050 NPV, 3% a NPV, 7% a

Technology Costs $ 2,000 $ 8,370 $ 35,700 $39,800 $ 44,600 $545,000 $239,000

Fuel Savings $
561 $ 6,920 $ 88,300 $151,000 $ 198,000 $1,570,000 $601,000

Total Annual Benefits at each assumed SCC value b

5% (avg SCC) $
103 $ 1,710 $ 22,600 $40,100 $ 54,200 $390,000 $170,000

3% (avg SCC) $
142 $ 2,190 $ 29,100 $52,200 $ 70,100 $536,000 $315,000

2.5% (avg SCC) $
173 $ 2,570 $ 34,100 $60,900 $ 81,000 $662,000 $442,000

3% (95th %ile) $
249 $ 3,540 $ 48,300 $88,700 $ 120,000 $903,000 $682,000

Monetized Net Benefits at each assumed SCC value c

5% (avg SCC) - $1,330 $
265 $ 75,200 $152,000 $ 208,000 $1,420,000 $532,000

3% (avg SCC) - $1,290 $
746 $ 81,700 $164,000 $ 224,000 $1,560,000 $677,000

2.5% (avg SCC) - $1,260 $ 1,130 $ 86,700 $172,000 $ 235,000 $1,690,000 $803,000

3% (95th %ile) - $1,190 $ 2,090 $ 101,000 $200,000 $ 273,000 $1,930,000 $1,040,000

Notes:

a Net present value of reduced CO 2 emissions is calculated differently than other benefits. The same discount rate used to discount the value of damages from future emissi ons (SCC at 5, 3, 2.5 percent) is used to calculate net present value of SCC for internal cons istency. Refer to the SCC TSD for more detail. Annual costs shown are undiscounted values.

b Section VIII.H.5 notes that SCC increases over time. For the years 2012-2050, the SCC estimates range as follows: for Average SCC at 5%: $5-$16; for Average SCC at 3%: $23-$46; for Average SCC at 2.5%: $38-$67; and for 95 th percentile SCC at 3%: $70-$140 Section VIII.H.5 also presents these SCC estimates.

c Net Benefits equal Fuel Savings minus Technology Costs plus Benefits.

EPA also conducted a separate analysis of the total benefits over the model year lifetimes of the 2017 through 2025 model year vehicles. In contrast to the calendar year analysis presented above in Table III-75 through Table I II-78, the model year lifetime analysis belowSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 434 of 768 shows the impacts of the proposed program on ve hicles produced during each of the model years 2017 through 2025 over the course of their expected lifetimes. The net societal benefits over the full lifetimes of vehicles produced during each of the nine model years from 2017 through 2025
are shown in Table III-79 and Table III-80 at bo th 3 percent and 7 percent discount rates, respectively.

Table III-79: Monetized Technol ogy Costs, Fuel Savings, Benefits, and Net Benefits Associated with the Lifetimes of 2017-2025 Model Year Light-Duty Vehicles (Millions, 2009$; 3% Discount Rate) h

2 017
MY 2018
MY 2 019
MY 2020
MY 2 021
MY 2 022
MY 2 023
M
Y 2 024
MY 2 025
MY S

um

Tech nology Costs $ 1,970 $ 4,120 $ 6,160 $ 8,250 $ 11,700 $ 17,100 $ 22,400 $ 27,700 $ 33,100 $ 133,000 FuelSavings (pretax) $ 6,470 $ 15,300 $ 23,800 $ 33,700 $ 50,100 $ 64,400 $ 77,600 $ 91,400 $ 105,000 $ 468,000

Ener gy Security Benefits (mac ro-disruption costs) $
344 $
813 $ 1,270 $ 1,810 $ 2,690 $ 3,490 $ 4,240 $ 5,030 $ 5,830 $ 25,500

Acci dents, Congestion, Noise Costs f $
536 $ 1,300 $ 2,040 $ 2,890 $ 4,170 $ 5,320 $ 6,370 $ 7,480 $ 8,590 $ 38,700

Incre ased Travel Benefits $
794 $ 1,990 $ 3,210 $ 4,660 $ 6,870 $ 8,980 $ 11,000 $ 13,200 $ 15,400 $ 66,100

Refu eling Time Savings $
279 $
657 $ 1,030 $ 1,450 $ 2,160 $ 2,800 $ 3,400 $ 4,030 $ 4,680 $ 20,500

PM 2.

5 Related Impacts c,d,e $
147 $
372 $
588 $
843 $ 1,310 $ 1,500 $ 1,640 $ 1,790 $ 1,930 $ 10,100

NonCO 2 GHG Impacts g n /a n/a n /a n/a n /a n /a n /a n /a n /a n /a

Reduced CO 2 Emissions at each assumed SCC value a, b 5% (avg SCC) $
152 $
367 $
587 $
851 $ 1,300 $ 1,700 $ 2,090 $ 2,510 $ 2,960 $ 12,500 3% (avg SCC) $
640 $ 1,530 $ 2,410 $ 3,450 $ 5,190 $ 6,720 $ 8,170 $ 9,700 $ 11,300 $ 49,100 2.5% (avg SCC) $ 1,040 $ 2,470 $ 3,880 $ 5,520 $ 8,300 $ 10,700 $ 13,000 $ 15,400 $ 17,800 $ 78,100 3% (95th %ile) $ 1,960 $ 4,680 $ 7,370 $ 10,500 $ 15,900 $ 20,500 $ 25,000 $ 29,600 $ 34,500 $ 150,000 Monetized Net Benefits at each assumed SCC value a, b 5% (avg $ $ $ $ $ $ $ $ $ $Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 435 of 768 SCC) 5,680 14,100 22,300 32,200 48,500 60,400 71,300 82,700 94,500 432,000 3% (avg SCC) $ 6,170 $ 15,200 $ 24,100 $ 34,800 $ 52,400 $ 65,400 $ 77,300 $ 89,900 $ 103,000 $ 468,000 2.5% (avg SCC) $ 6,570 $ 16,200 $ 25,600 $ 36,900 $ 55,500 $ 69,400 $ 82,100 $ 95,600 $ 109,000 $ 497,000 3% (95th %ile) $ 7,490 $ 18,400 $ 29,100 $ 41,900 $ 63,100 $ 79,300 $ 94,100 $ 110,000 $ 126,000 $ 569,000

Notes:

a Net present value of reduced CO 2 emissions is calculated differently than other benefits. The same discount rate used to discount the value of damages from future emissi ons (SCC at 5, 3, 2.5 percent) is used to calculate net present value of SCC for internal consistency. Refer to the SCC TSD for more detail.

b Section III.H.5 notes that SCC increases over time. For the years 2012-2050, the SCC estimates range as follows: for Average SCC at 5%: $5-$16; for Average SCC at 3%: $23-$46; for Average SCC at 2.5%: $38-$67; and for
95 th percentile SCC at 3%: $70-$140. Section III.H.5 also presents these SCC estimates.

c Note that the co-pollutant impacts associated with the standards presen ted here do not include the full complement of endpoints that, if quantified and monetized, would change the total monetized estimate of rule-related impacts. Instead, the co-pollutant benefits are based on benefit- per-ton values that reflect only human health impacts
associated with reductions in PM 2.5 exposure. Ideally, human health and environmental benefits would be based on changes in ambient PM 2.5 and ozone as determined by full-scale air qua lity modeling. However, EPA was unable to conduct a full-scale air quality modeling an alysis in time for the proposal. We intend to more fully capture the copollutant benefits for the analysis of the final standards.

d The PM 2.5 -related benefits (derived from benefit-per-ton values) presented in this table are based on an estimate of premature mortality derived from the ACS study (Pope et al ., 2002). If the benefit-per-ton estimates were based on the Six Cities study (Laden et al., 2006), the values would be nearly two-and-a-half times larger.

e The PM 2.5 -related benefits (derived from benefit-per-ton values) presented in this table assume a 3% discount rate in the valuation of premature mortality to account for a twenty-year segmented cessation lag. If a 7% discount rate had been used, the values would be approximately 9% lower. f Positive values for Accidents, Congestion, and Noise costs represent an increase in costs. Therefore, they are treated as nega tive values when calculating the total benefits. g The monetized GHG benefits presented in this analysis exclude the value of changes in non-CO 2 GHG emissions expected under this action ( See DRIA Chapter 7.1). Although EPA has not monetized changes in nonCO 2 GHGs, the value of any increases or reductions should not be interpreted as zero. We seek comment on a method of quantifying non-CO 2 GHG benefits in Section III.H.5.

h Model year values are discounted to the first year of each model year; the “Sum” represents those discounted values summed across model years.

Table III-80: Monetized Technol ogy Costs, Fuel Savings, Benefits, and Net Benefits Associated with the Lifetimes of 2017-2025 Model Year Light-Duty Vehicles (Millions, 2009$; 7% Discount Rate) h

017
MY 2018
MY 019
MY 2020
MY 021
MY 022
MY 023

Y 024
MY 025
MY um

Tech nology Costs 1,930 4,040 6,050 8,100 11,500 16,800 21,900 27,200 32,500 130,00 0 FuelSavings (pretax) 4,990 11,800 18,500 26,200 38,800 49,900 60,200 71,000 81,900 363,00 0
Ener gy Security 264 627 984 1,400 2,080 2,700 3,290 3,900 4,530 19,800Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 436 of 768 Benefits(macrodisruption costs)
Acci dents, Congestion, Noise Costs f 434 1,050 1,660 2,350 3,390 4,320 5,180 6,080 6,990 31,400

Incre ased Travel Benefits 638 1,600 2,590 3,760 5,550 7,260 8,900 10,700 12,500 53,500

Refu eling Time Savings 215 508 794 1,130 1,670 2,160 2,630 3,120 3,620 15,800

PM 2.

5 Related Impacts c,d,e 112 286 453 650 1,010 1,150 1,260 1,370 1,470 7,770

NonCO 2 GHG Impacts g /a n/a /a n/a /a /a /a /a /a /a

Reduced CO 2 Emissions at each assumed SCC value a, b 5% (avg SCC) 152 367 587 851 1,300 1,700 2,090 2,510 2,960 12,500 3% (avg SCC) 640 1,530 2,410 3,450 5,190 6,720 8,170 9,700 11,300 49,100 2.5% (avg SCC) 1,040 2,470 3,880 5,520 8,300 10,700 13,000 15,400 17,800 78,100

3% (95th %ile) 1,960 4,680 7,370 10,500 15,900 20,500 25,000 29,600 34,500 150,00 0 Monetized Net Benefits at each assumed SCC value a, b

5% (avg SCC) 4,000 10,100 16,200 23,500 35,500 43,800 51,300 59,200 67,500 311,00 0

3% (avg SCC) 4,490 11,300 18,000 26,100 39,400 48,800 57,300 66,400 75,800 348,00 0

2.5% (avg SCC) 4,890 12,200 19,500 28,200 42,500 52,800 62,100 72,100 82,400 377,00 0

3% (95th %ile) 5,810 14,400 23,000 33,200 50,100 62,600 74,100 86,300 99,000 449,00 0

Notes:

a Net present value of reduced CO 2 emissions is calculated differently than other benefits. The same discount rate used to discount the value of damages from future emissi ons (SCC at 5, 3, 2.5 percent) is used to calculate net present value of SCC for internal consistency. Refer to the SCC TSD for more detail.

b Section III.H.5 notes that SCC increases over time. For the years 2012-2050, the SCC estimates range as follows: for Average SCC at 5%: $5-$16; for Average SCC at 3%: $23-$46; for Average SCC at 2.5%: $38-$67; and for
95 th percentile SCC at 3%: $70-$140. Section III.H.5 also presents these SCC estimates.

c Note that the co-pollutant impacts associated with the standards presen ted here do not include the full complement of endpoints that, if quantified and monetized, would change the total monetized estimate of rule-related impacts. Instead, the co-pollutant benefits are based on benefit- per-ton values that reflect only human health impacts
associated with reductions in PM 2.5 exposure. Ideally, human health and environmental benefits would be based onSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 437 of 768 changes in ambient PM 2.5 and ozone as determined by full-scale air qua lity modeling. However, EPA was unable to conduct a full-scale air quality modeling an alysis in time for the proposal. We intend to more fully capture the copollutant benefits for the analysis of the final standards.

d The PM 2.5 -related benefits (derived from benefit-per-ton values) presented in this table are based on an estimate of premature mortality derived from the ACS study (Pope et al ., 2002). If the benefit-per-ton estimates were based on the Six Cities study (Laden et al., 2006), the values would be nearly two-and-a-half times larger.

e The PM 2.5 -related benefits (derived from benefit-per-ton values) presented in this table assume a 3% discount rate in the valuation of premature mortality to account for a tw enty-year segmented cessation lag. If a 7% discount rate had been used, the values would be approximately 9% lower

. f Positive values for Accidents, Congestion, and Noise cost s represent an increase in co sts. Therefore, they are treated as negative values when calculating the total benefits.

g The monetized GHG benefits presented in this analysis exclude the value of changes in non-CO 2 GHG emissions expected under this action ( See DRIA Chapter 7.1). Although EPA has not monetized changes in non-CO 2 GHGs, the value of any increases or reductions should not be interpreted as zero. We seek comment on a method of quantifying non-CO 2 GHG benefits in Section III.H.5.

h Model year values are discounted to the first year of each model year; the “Sum” represents those discounted values summed across model years.

10. U.S. Vehicle Sales Impacts and Payback Period

a. Vehicle Sales Impacts

Here we present an approximate calculation of the effects of the proposed 2017-2025 GHG standards on light duty vehicle sales at the aggregate market level. This analysis compares two effects. On the one hand, the vehicles desi gned to meet the proposed standards will become more expensive, which would, by itself, discourag e sales. On the other hand, the vehicles will have improved fuel economy and thus lower operating costs. If consumers do not accurately compare the value of fuel savings with the incr eased cost of fuel economy technology in their vehicle purchase decisions, as discussed in Preamble III.H.1, they will continue to behave in this way after this rule. If auto makers have accurately gauged how consumers consider fuel economy when purchasing vehicles and have pr ovided the amount that consumers want in vehicles, then consumers should not be expected to want the more fuel-efficient vehicles. After all, auto makers would already have provided as much fuel economy as consumers want. If, on the other hand, auto makers underestimated consumer demand for fuel economy, then this rule may lead to production of more desirable vehi cles, and vehicle sales may increase. This assumption implies that auto makers may have, for various reasons, missed some profit-making opportunities.

The methodology EPA used for estimating the impact on vehicle sales is consistent with the approach in the 2012-16 light-duty GHG and CAFE rule, and in several previous CAFE rulemakings by NHTSA. It is relatively stra ightforward, but makes a number of simplifying assumptions. According to the literature, the pr ice elasticity of demand for vehicles is commonlySummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 438 of 768 estimated to be about -1. 542 In other words, a one percent increase in the price of a vehicle would be expected to decrease sales by one percent, holding all other factors constant. This elasticity is generally considered to be a short-run elastic ity, reflecting the immediate impacts of an immediate price change on vehicle sales. For a durable good such as an auto, the elasticity may be smaller in the long run: though people may be able to change the timing of their purchase when price changes in the short run, they must eventually make the investment. Using a smaller elasticity would reduce the magnitude of the estimates presented here for vehicle sales, but it would not change the direction. A short-run el asticity is more valid for initial responses to changes in price, but, over time, a long-run elastic ity may better reflect beha vior; thus, the results presented for the initial years of the program may be more appropriate for modeling with the short-run elasticity than the later years of the program. A search of the literature has not found
studies more recent than the 1970s that specifically investigate long-run elasticities. 543 We seek comments and research on methods and results for estimating the long-run elasticity of demand
for vehicles.

For our estimates, EPA calculated the effect of an increase in vehicle costs due to the
GHG standards and assumes that consumers will f ace the full increase in costs, not an actual (estimated) change in vehicle price. (The estima ted increases in vehicle cost due to the rule are discussed in Section III.H.2) This is a conservative methodology, since an increase in cost may not pass fully into an increase in market price in an oligopolistic industry such as the automotive

sector. 544 EPA also notes that we have not used these estimated sales impacts in the OMEGA
Model.

Although EPA uses the price elasticity of dema nd of -1 for vehicles as the basis for our vehicle sales impact estimates, we assumed that the consumer would take into account both the higher vehicle purchase costs as well as some of the fuel savings benefits when deciding whether

542 Kleit A.N., 1990. “The Effect of Annual Changes in Automobile Fuel Economy Standards.” Journal of Regulatory Economics 2: 151-172 (Docket EPA-HQ-OAR-2 009-0472-0015); McCarthy, Patrick S., 1996. “Market Price and Income Elasticities of New Vehicle Demands.” Review of Economics and Statistics 78: 543-547 (Docket EPA-HQ-OAR-2009-0472-0016); Goldberg, Pinelopi K., 1998. “The Effects of the Corporate Average Fuel Efficiency Standards in the U.S.,” Journal of Indus trial Economics 46(1): 1-33 (Docket EPA-HQ-OAR-2009-0472- 0017).

543 E.g., Hymans, Saul H. “Consumer Durable Spending: Explanation and Prediction.” Brookings Papers on Economic Activity 1 (1970): 173-206. http://www.brookings.edu/~/media/Files/Programs/ES/BPE A/1970_2_bpea_papers/1970b_bpea_hymans_ackley_ju ster.pdf finds a short-run elasticity of auto expenditures ( not sales) with respect to price of 0.78 50 1.17, and a longrun elasticity of 0.3 to 0.46.

544 See, for instance, Gron, Ann, and Deborah Swenson, 2000. “Cost Pass-Through in the U.S. Automobile Market,” Review of Economics and Statistics 82: 316-324 (Docket EPA-HQ-OAR-2009-0472-0007), who found significantly less than full-cost pass-through using data from 1984-1994. Using full-cost pass-through overstates costs and thus contributes to lower vehicle sales than using a lower estimate. To the extent that the auto industry has become more competitive over time, full-cost pass-throug h may be more appropriate than a result based on this older study.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 439 of 768 to purchase a new vehicle. 545 Therefore, the incremental cost increase of a new vehicle would be offset by reduced fuel expenditures over a certain period of time (i.e., the “payback period”). For the purposes of this rulemaking, EPA used a five-year payback period, which is consistent with the length of a typical new light-duty vehicle loan , and is similar to the average time that a new vehicle purchaser holds onto the vehicle; it ha s also been used by NHTSA in previous CAFE rulemakings. 546 This approach may not accurately reflect the role of fuel savings in consumers’ purchase decisions, as the discussion in Section III.H.1 suggests. If consumers consider fuel savings in a different fashion th an modeled here, then this appr oach will not accurately reflect the impact of this rule on vehicle sales.

This increase in costs has other effects on consumers as well: if vehicle prices increase, consumers will face higher insurance costs and sa les tax, and additional finance costs if the vehicle is bought on credit. In addition, the resa le value of the vehicles will increase. The details of the calculations to incorporate these factors are in the DRIA, Chapter 8.1.l.

Once the cost estimates are adjusted for these additional factors, five years of the fuel cost savings associated with the rule, discussed in Section III.H.4, are subtracted to get the net effect on consumer expenditures for a new vehicle. With the assumed elasticity of demand of -1, the percent change in this “effective price,” estima ted as the adjusted increase in cost, is equal to the negative of the percent change in vehicle purchases. The net effect of this calculation is in
Table III-81 and Table III-82.

The estimates provided in Table III-81 and Table III-82 are meant to be illustrative rather than a definitive prediction. When viewed at the industry-wide level, they give a general indication of the potential impact of the propose d rule on vehicle sales. As shown below, the overall impact is small (less than 5 percent) but positive. Because the fuel savings associated with this rule are expected to exceed the technology costs, the effective prices of vehicles (the adjusted increase in technology cost less the fuel savings over five years) to consumers will fall, and consumers will buy more new vehicles. As a result, the lower net cost of the vehicles is projected to lead to an increase in sales for both cars and trucks.

As discussed above, this result depends on the assumption that more fuel efficient vehicles that yield net consumer benefits over five years would not otherwise be offered on the

545 PRR, Inc., in a recent literature review (“Environm ental Protection Agency Fuel Economy Label Literature Review,” EPA-420-R-10-906, August 2010), found that “fue l economy is one of the top factors that consumers report influence which vehicles they choose.” This attenti on seems to be greater when gasoline prices are high or greatly fluctuating.

546 As discussed further in Section III.H.1, there is not a consensus in the literature on how consumers consider fuel economy in their vehicle purchases. Re sults are inconsistent, possibly due to fuel economy not being a major focus of many of the studies, and possibly due to sensitivity of results to modeling and data used. A survey by Greene (Greene, David L. “How Consumers Value Fuel Economy: A Literature Review.” EPA Report EPA-420-R-10- 008, March 2010 (Docket EPA-HQ-OAR-2009- 0472-11575)) finds that estimates in the literature of the value that consumers place on fuel economy when buying a vehi cle range from negative – consumers would pay to reduce fuel economy – to more than 1000 times the value of fuel savings.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 440 of 768 vehicle market due to market failures or other barriers on the part of vehicle manufacturers. If vehicles that achieve the fuel economy standards prescribed by today’s rulemaking would already be available, but consumers chose not to purchase them, then this rulemaking would not result in an increase in vehicle sales, because it does not alter how consumers make decisions about which vehicles to purchase. In addition, this analysis has not accounted for a number of factors that might affect consumer vehicle pur chases, such as changing market conditions, changes in vehicle characteristics that might accompany improvements in fuel economy, fuel prices different than those used here, or consumers considering a different “payback period” for their fuel economy purchases. If consumers use a shorter payback period, the sales impacts will be less positive, possibly negative; if consumers use a higher payback period, the impacts will be more positive. Also, this is an aggregate anal ysis; some individual consumers (those who drive less than estimated here) will face lower net be nefits, while others (who drive more than estimated here) will have even greater savings. These complications add considerable uncertainty to our vehicle sales impact analysis. EPA notes that we have not used these estimated sales impacts in the OMEGA model or in our estimate of the costs and benefits of this proposal.

Table III-81 New Vehicle Sales Impacts Using a 3% Discount Rate

Change in Car Sales % Change Change in Truck Sales % Change

2017 3,900 0.0% 33,400 0.6% 2018 60,800 0.6% 50,300 0.9% 2019 120,300 1.2% 65,100 1.2% 2020 195,000 1.9% 85,600 1.5% 2021 272,900 2.6% 157,300 2.8% 2022 286,100 2.7% 199,600 3.5% 2023 292,500 2.7% 239,000 4.2% 2024 303,800 2.7% 280,300 4.9% 2025 319,700 2.8% 324,600 5.7%

Table III-81 shows the impacts on new vehicle sales using a 3% discount rate. The fuel savings over five years are always higher than the technology costs. Although both cars and trucks show very small effects initially, over ti me vehicle sales become increasingly positive, as increased fuel prices make improved fuel economy more desirable. The increases in sales for cars are larger than the increases for trucks (except in 2017) in absolute numbers; in percentage terms, the effect on trucks is larger than the effect on cars (except in 2020).

Table III-82 New Vehicle Sales Impacts Using an 7% Discount Rate

Change in Car Sales % Change Change in Truck Sales % ChangeSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 441 of 768 2017 3,400 0.0% 31,600 0.5% 2018 57,100 0.6% 47,600 0.8% 2019 113,200 1.1% 61,500 1.1% 2020 183,700 1.8% 80,900 1.4% 2021 257,300 2.4% 148,600 2.6% 2022 269,300 2.5% 188,700 3.3% 2023 274,800 2.5% 225,800 4.0% 2024 284,900 2.5% 264,800 4.7% 2025 299,400 2.6% 306,600 5.4%

Table III-82 shows the impacts on new vehicle sales using a 7% interest rate. While a 7% interest rate shows slightly lower impacts than using a 3% discount rate, the results are qualitatively similar. Sales increase for every year. For both cars and trucks, sales become increasingly positive over time, as higher fuel prices make improved fuel economy more valuable. The car market grows more than the truck market in absolute numbers (except in 2017 and 2025), but less on a percentage basis (except in 2020).

Another method to estimate effects on vehicle sa les is to model the market for vehicles.
Consumer vehicle choice models estimate what vehicles consumers buy based on vehicle and consumer characteristics. In principle, such models could provide a means of understanding both the role of fuel economy in consumers’ purchase decisions and the effects of this rule on the benefits that consumers will get from vehicles . Helfand and Wolverton discuss the wide
variation in the structure and results of these models. 547 Models or model results have not frequently been systematically compared to each other. When they have, the results show large variation over, for instance, the value that c onsumers place on additiona l fuel economy. As discussed in Section III.H.1 and in Chapter 8.1.2.8 of the DRIA, EPA is exploring development of a consumer vehicle choice model, but the model is not sufficiently developed for use in this

NPRM.

The effect of this rule on the use and scrappa ge of older vehicles will be related to its effects on new vehicle prices, the fuel efficiency of new vehicle models, the fuel efficiency of used vehicles, and the total sales of new vehicles . If the value of fuel savings resulting from improved fuel efficiency to the typical potenti al buyer of a new vehicle outweighs the average increase in new models’ prices, sales of new vehicles will rise, while scrappage rates of used vehicles will increase slightly. This will cause the “turnover” of the vehicle fleet (i.e., the retirement of used vehicles and their replacemen t by new models) to accelerate slightly, thus accentuating the anticipated effect of the rule on fleet-wide fuel consumption and CO 2 emissions. However, if potential buyers value future fuel savings resulting from the increased fuel efficiency of new models at less than the increase in their average selling price, sales of new

547 Helfand, Gloria, and Ann Wolverton. “Evaluating the Consumer Response to Fuel Economy: A Review of the Literature.” International Review of Environmental and Resource Economics 5 (2011): 103-146.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 442 of 768 vehicles will decline, as will the rate at which us ed vehicles are retired from service. This effect will slow the replacement of used vehicles by new models, and thus partly reduce the anticipated
effects of this rule on fuel use and emissions.

Because of the uncertainty regarding how the value of projected fuel savings from this rule to potential buyers will compare to their es timates of increases in new vehicle prices, we have not attempted to estimate explicitly the effect s of the rule on scrappage of older vehicles
and the turnover of the vehicle fleet.

A detailed discussion of the vehicle sales impacts methodology is provided in the Chapter 8 of EPA’s DRIA. We seek comment on all aspects of this analysis.

b. Consumer Payback Period and Lifetime Savings on New Vehicle Purchases

Another factor of interest is the payback period that consumers would experience on the purchase of a new vehicle that meets the proposed standards. In other words, how long would it take for the expected fuel savings to outweigh the increased cost of a new vehicle? For example, a new 2025 MY vehicle is estimated to cost $1,946 more (on average, and relative to the reference case vehicle) due to the addition of new GHG reducing/fuel economy improving technology (see Section III.D.6 for details on this cost estimate). This new technology will result in lower fuel consumption and, therefore, savi ngs in fuel expenditures (see Section III.H.10 for details on fuel savings). But how many months or years would pass before the fuel savings exceed the upfront costs?

Table III-83 provides the answer to this question for a vehicle purchaser who pays for the new vehicle upfront in cash (we discuss later in this section the payback period for consumers who finance the new vehicle purchase with a loan). The table uses annual miles driven (vehicle miles traveled, or VMT) and survival rates cons istent with the emission and benefits analyses presented in Chapter 4 of the Joint TSD. The control case includes fuel savings associated with A/C controls. Not included here are the likely A/C-related maintenance savings as discussed in Chapter 2 of EPA’s RIA. Further, this analysis does not include other private impacts, such as reduced refueling events, or other societal impacts, such as the potential rebound miles driven or the value of driving those rebound miles, or noise, congestion and accidents, since the focus is meant to be on those factors consumers think about most while in the showroom considering a new car purchase. Car/truck fleet weighting is handled as described in Chapter 1 of the Joint TSD. As can be seen in the table, it will take ju st under four y ears at a 3% disc ount rate, and exactly 4 years at a 7% discount rate for the cumulative discounted fuel savings to exceed the present value of increased vehicle costs. More detail on this analysis can be found in Chapter 5
of EPA’s draft RIA.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 443 of 768 Table III-83 Payback Period on a 2025 MY New Vehicle Purchase via Cash (2009 dollars)

Year of Ownership Increased Vehicle Cost a (undiscounted) Annual Fuel Savings b (undiscounted) Cumulative Discounted Fuel Savings at 3% Cumulative Discounted Fuel Savings at 7% 1 -$2,087 $626 $617 $606 2 -$31 $609 $1,200 $1,156 3 -$26 $615 $1,772 $1,676 4 -$21 $612 $2,324 $2,160 5 -$16 $611 $2,859 $2,611 6 -$11 $587 $3,357 $3,015 7 -$6 $559 $3,818 $3,375 8 -$1 $534 $4,246 $3,697

a Increased vehicle cost due to the rule is $1,946; the value here includes nationwide average sales tax of 5.32% and increased insurance premiums of 1.85% in year one decreas ing to 0% by year 9. Both of these percentages are discussed in Section 8.1.1 of EPA’s RIA. This results in a present value of increased costs of $2,189 at 3% discounting and $2,180 at 7% discounting. These present value costs are used in determining the payback period.

b Calculated using AEO 2011 reference case fuel prices including taxes.

However, most people purchase a new vehicle using credit rather than paying cash up front. A common car loan today is a five year, 60 month loan. As of June 7, 2011, the national average interest rate for a 5 year new car loan was 5.52 percent. 548 If the increased vehicle cost is spread out over 5 years at 5.52 percent, the analysis would look like that shown in Table III-84. As can be seen in this table, the fuel savings immediately outweigh the increased payments on the car loan, amounting to $128 in discounted net savings (3% discount rate) in the first year and similar savings for the next four years although savings decline some due to reduced VMT as the average vehicle ages. Results are similar using a 7% discount rate. This means that for every month that the average owner is making a payment for the financing of the average new vehicle their monthly fuel savings would be greater than the increase in the loan payments. This amounts to a savings on the order of $11 per month throughout the duration of the 5 year loan. Note that in year six when the car loan is paid off, the net savings equal the fuel savings less the increased insurance premiums (as would be the case for the remaining years of ownership).

Table III-84 Payback Period on a 2025 MY New Vehicle Purchase via Credit (2009 dollars)

Year of Ownership Increased Vehicle

Cost a (undiscounted) Annual Fuel Savings b (undiscounted) Annual Discounted Net Savings at 3% c Annual Discounted Net Savings at 7% c

1 -$489 $626 $128 $116 2 -$488 $609 $109 $94 3 -$487 $615 $113 $95

548 According to www.bankrate.com on June 7, 2011 (docket #XX)Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 444 of 768 4 -$485 $612 $108 $87 5 -$484 $611 $105 $81 6 -$11 $587 $489 $397 7 -$6 $559 $456 $356 8 -$1 $534 $427 $321

a This uses the same increased cost as Table III-12 but spr eads it out over 5 years assuming a 5 year car loan at 5.52 percent.
b Calculated using AEO 2011 reference case fuel prices including taxes.

c Note that the cumulative discounted fuel savings are id entical to those shown in Table III-12. Here we show discounted net savings.

The lifetime fuel savings and net savings can also be calculated for those who purchase the vehicle using cash and for those who purcha se the vehicle with credit. This calculation applies to the vehicle owner who retains the vehicle for its entire life and drives the vehicle each year at the rate equal to the national projected av erage. The results are shown in Table III-85. In either case, the present value of the lifetime net savings is greater than $4,300 at a 3% discount rate, or $3,000 at a 7% discount rate.

Table III-85 Lifetime Discounted Net Savings on a 2025 MY New Vehicle Purchase (2009 dollars)

PURCHASE OPTION INCREASED DISCOUNTED VEHICLE COST LIFETIME DISCOUNTED FUEL SAVINGS B LIFETIME DISCOUNTED NET SAVINGS 3% discount rate Cash $2,189 $6,639 $4,449

Credit a $2,310 $6,639 $4,328

7% discount rate Cash $2,180 $5,187 $3,005

Credit a $2,147 $5,187 $3,037

a Assumes a 5 year loan at 5.52 percent.

b Fuel savings here were calculated using AEO 2011 reference case fuel prices including taxes.

Note that throughout this consumer payback discussion, the average number of vehicle miles traveled per year has been used. Drivers who drive more miles than the average would incur fuel-related savings more quickly and, therefore, the payback would come sooner. Drivers who drive fewer miles than the average would incur fuel related savings more slowly and, therefore, the payback would come later.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 445 of 768 11. Employment Impacts

a. Introduction

Although analysis of employment impacts is not part of a cost-benefit analysis (except to the extent that labor costs contribute to costs) , employment impacts of federal rules are of particular concern in the current economic climate of sizeable unemployment. When President Obama requested that the agencies develop this program, he sought a program that would “strengthen the [auto] industry and enhance job creation in the United States.” 549 The recently issued Executive Order 13563, “Improving Regulation and Regulatory Review” (January 18, 2011), states, “Our regulatory system must protect public health, welfare, safety, and our
environment while promoting economic growth, innovation, competitiveness, and job creation ” (emphasis added). EPA is accordingly providing estimates of the effects of this proposal on domestic employment.

This proposal is expected to affect employ ment in the United States through the regulated sector – the auto manufacturing industry – and through several related sectors, specifically, industries that supply the auto manufacturing industry (e.g., vehicle parts), auto dealers, the fuel refining and supply sectors, and the general retail sector. According to the U.S. Bureau of Labor Statistics, in 2010, about 677,000 people in the U.S. were employed in Motor Vehicle and Parts Manufacturing Sector (NAICS 3361, 3362, and 3363). About 129,000 people in the U.S. were employed specifically in the Automobile and Li ght Truck Manufacturing Sector (NAICS 33611), the directly regulated sector, since it encompasses the auto manufacturers that are responsible for complying with the proposed standards. 550 The employment effects of this rule are expected to expand beyond the regulated sector. Though some of the parts used to achieve the proposed standards are likely to be built by auto manufacturers themselv es, the auto parts manufacturing sector also plays a significant ro le in providing those parts, and will also be affected by changes in vehicle sales. Changes in light duty vehicle sa les, discussed in Section III.H.10, could affect employment for auto dealers. As discussed in Chapter 5.3 of the DRIA, this proposal is expected to reduce the amount of fuel these vehicles use, and thus affect the petroleum refinery and supply industries. Finally, since the net reduction in co st associated with this proposal is expected to lead to lower household expenditures on fuel ne t of vehicle costs, consumers then will have additional discretionary income that can be spent on other goods and services.

When the economy is at full employment, an environmental regulation is unlikely to have much impact on net overall U.S. employment; inst ead, labor would primarily be shifted from one sector to another. These shifts in employ ment impose an opportunity cost on society, approximated by the wages of the employees, as regulation diverts workers from other activities

549 President Barack Obama. “Presidential Memorandum Rega rding Fuel Efficiency Sta ndards. The White House,Office of the Press Secretary, May 21, 2010. http://www.whitehouse.gov/the-press-office/presidentialmemorandum-regarding-fuel-efficiency-standards

550 U.S. Bureau of Labor Statistics, Quarterly Census of Employment and Wages, as accessed on August 9, 2011.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 446 of 768 in the economy. In this situation, any effects on net employment are likely to be transitory as workers change jobs (e.g., some workers may need to be retrained or require time to search for new jobs, while shortages in some sectors or regi ons could bid up wages to attract workers).

On the other hand, if a regulation comes into effect during a period of high unemployment, a change in labor demand due to regulation may affect net overall U.S. employment because the labor market is not in equilibrium. Schmalansee and Stavins point out that net positive employment effects are possible in the near term when the economy is at less than full employment due to the potential hiring of idle labor resources by the regulated sector to meet new requirements (e.g., to install new equipment) and new economic activity in sectors related to the regulated sector. 551 In the longer run, the net effect on employment is more difficult to predict and will depend on the way in which the related industries respond to the regulatory requirements. As Schmalansee and Stavin s note, it is possible that the magnitude of the effect on employment could vary over tim e, region, and sector, and positive effects on employment in some regions or sectors could be offset by negative effects in other regions or sectors. For this reason, they urge caution in reporting partial employment effects since it can “paint an inaccurate picture of net employment impacts if not placed in the broader economic

context.”

A number of different approaches have been used in published literature to conduct employment analysis. All potential methods of estimating employment impacts of a rule have advantages and limitations. We seek comment on the analytical approach presented here, other appropriate methods for analyzing employment impacts for this rulemaking, and the inputs used here for employment analysis.

b. Approaches to Quantitative Employment Analysis

Measuring the employment impacts of a policy depend on a number of inputs and assumptions. For instance, as discussed, assumptions about the overall state of unemployment in the economy play a major role in measured job impacts. The inputs to the models commonly are the changes in quantities or expenditures in the affected sectors; model results may vary in different studies depending on the assumptions about the levels of those inputs, and which sectors receive those changes. Which sectors are in cluded in the study can also affect the results. For instance, a study of this program that look s only at employment impacts in the refinery sector may find negati ve effects, because consumers will purchase less gasoline; a study that looks only at the auto parts sector, on the other hand, may find positive impacts, because the program will require redesigned or additional part s for vehicles. In both instances, these would only be partial perspectives on the overall change in national employment due to Federal regulation.

551 Schmalensee, Richard, and Robert N. Stavins. “A Gu ide to Economic and Policy Analysis of EPA’s Transport Rule.” White paper commissioned by Excelon Corporation, March 2011.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 447 of 768 i. Conceptual Framework for Employment Impacts in the Regulated Sector

One study by Morgenstern, Pizer, and Shih 552 provides a retrospective look at the impacts of regulation in employment in the regulated sectors. The paper provides a theoretical framework that can be useful for examining the impacts of a regulatory change on the regulated sector in the medium to longer term. In pa rticular, it identifies three separate ways that employment levels may change in the regulated industry in response to a new (or more stringent) regulation.

 Demand effect : higher production costs due to th e regulation will lead to higher market prices; higher prices in turn reduce demand for the good, reducing the demand for labor to make that good. In the authors’ words, the “extent of this effect depends on the cost increase passed on to consumers as well as the demand elasticity of industry output.”

 Cost effect : as costs go up, plants add more capital and labor (holding other factors constant), with potentially positive effects on employment. In the authors’ words, as “production costs rise, more inputs, incl uding labor, are used to produce the same amount of output.”

 Factor-shift effect : post-regulation production technologies may be more or less labor-intensive (i.e., more/less labor is required per dollar of output). In the authors’ words, “environmental activi ties may be more labor in tensive than conventional production,” meaning that “the amount of labor per dollar of output will rise,” though it is also possible that “cleaner operat ions could involve automation and less employment, for example.”

According to the authors, the “demand effect” is expected to have a negative effect on employment, 553 the “cost effect” to have a positive eff ect on employment, and the “factor-shift effect” to have an ambiguous effect on employment. Without more information with respect to the magnitudes of these competing effects, it is not possible to predict the total effect environmental regulation will have on em ployment levels in a regulated sector.

Morgenstern et al. estimated the effects on employment of spending on pollution abatement for four highly polluting/regulated U.S. industries (pulp and paper, plastics, steel, and petroleum refining) using data for six years between 1979 and 1991. The authors conclude that increased abatement expenditures generally have not caused a significant change in employment in those sectors. More specifically, their resu lts show that, on average across the industries

552 Morgenstern, Richard D., William A. Pizer, and Jhih-Shyang Shih. “Jobs Versus the Environment: An IndustryLevel Perspective.” Journal of Environmental Economics and Management 43 (2002): 412-436.

553 As will be discussed below, the demand effect in this pr oposal is potentially an exception to this rule. While the vehicles become more expensive, they also produce redu ced fuel expenditures; the re duced fuel costs provide a countervailing impact on vehicle sales. As discussed in Pr eamble Section III.H.1, this possibility that vehicles may become more attractive to consumers after the program pos es a conundrum: why have interactions between vehicle buyers and producers not provided these benefits without government intervention?Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 448 of 768 studied, each additional $1 million spent on po llution abatement results in a (statistically insignificant) net increase of 1.5 jobs.

This approach to employment analysis has the advantage of carefully controlling for many possibly confounding effects in order to separate the effect of changes in regulatory costs on employment. It was, however, conducted for only four sectors. It could also be very difficult to update the study for other sectors, because one of the databases on which it relies, the Pollution Abatement Cost and Expenditure survey, has been conducted infrequently since 1994, with the last survey conducted in 2005. In addition, it does not examine the effects of regulation on employment in sectors related to but outside of the regulated sector. Nevertheless, the theory that Morgenstern et al. developed continues to be useful in this context.

The following discussion of additional methodologies draws from Berck and Hoffmann’s review of employment models. 554

ii. Computable General Equilibrium (CGE) Models

Computable general equilibrium (CGE) models are often used to assess the impacts of policy. These models include a stylized representation of supply and demand curves for all major markets in the economy. The labor market is commonly included. CGE models are very useful for looking at interaction effects of mark ets: “they allow for substitution among inputs in production and goods in consumption.” Thus, if one market experiences a change, such as a new regulation, then the effects can be observed in all other markets. As a result, they can measure the employment changes in the economy due to a regulation. Because they usually assume equilibrium in all markets, though, they typically lack involuntary unemployment. If the total amount of labor changes, it is due to people voluntarily entering or leaving the workforce. As a result, these models may not be appropriate for measuring effects of a policy on unemployment, because of the assumption that there is no invo luntary unemployment. In addition, because of the assumptions of equilibrium in all markets an d forward-looking consumers and firms, they aredesigned for examining the long-run effects of a policy but may offer little insight into its shortrun effects.

iii. Input-Output (IO) Models

Input-output models represent the economy through a matrix of coefficients that describe the connections between supplying and consuming sectors. In that sense, like CGE models, they describe the interconnections of the economy. These interconnections look at how changes in one sector ripple through the rest of the economy. For instance, a requirement for additional technology for vehicles requires additional steel, which requires more workers in both the auto and steel sectors; the additional workers in those sectors then have more money to spend, which

554 Berck, Peter, and Sandra Hoffmann. “Assessing the Employment Impacts of Environmental and Natural Resource Policy.” Environmental and Resource Economics 22 (2002): 133-156.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 449 of 768 leads to more employment in retail sectors. These are known as “multiplier” effects, because an initial impact in one sector gets multiplied through the economy. Unlike CGE models, inputoutput models have fixed, linear relationship s among the sectors (e.g., substitution among inputs or goods is not allowed), and quantity supplied need not equal quantity demanded. In particular, these models do not allow for price changes – an increase in the demand for labor or capital does not result in a change in its price to help reallocat e it to its best use. As a result, these models cannot capture opportunity costs from using resources in one area of the economy over another. The multipliers take an initial impact and can increase it substantially.

IO models are commonly used for regional analysis of projects. In a regional analysis, the markets are commonly considered small enough that wages and prices are determined outside the region, and any excess supply or demand is due to exports and imports (or, in the case of labor, emigration or immigration). For national-level employment analysis, the use of input-output models requires the assumption that workers flow into or out of the labor market perfectly freely. Wages do not adjust; instead, people join into or depart from the labor pool as production requires them. For other markets as well, there is no substitution of less expensive inputs for more expensive ones. As a result, IO models provide an upper bound on employment impacts. As Berck and Hoffmann note, “For the same reason, they can be thought of as simulating very short-run adjustment,” in contrast to the CGE’s implicit assumption of long-run adjustment. Changes in production processes, in troduce new technologies, or learning over time due to new regulatory requirements are also generally not captured by IO models, as they are calibrated to already established rela tionships between inputs and outputs.

iv. Hybrid Models

As Berck and Hoffmann note, input-output models and CGE models “represent a continuum of closely related models.” Though not separately discussed by Berck and Hoffmann, some hybrid models combine some of the features of CGE models (e.g., prices that can change) with input-output relationships. For instance, a hybrid model may include the ability to examine disequilibrium phenomena, such as labor being at less than full employment. Hybrid models depend on assumptions about how adjustments in the economy occur. CGE models characterize equilibria but say little about the pathway between them, while IO models assume that adjustments are largely constrained by previously defined relationships; the effectiveness of hybrid models depends on their success in overcoming the limitations of each of these approaches. Hybrid models could potentially be used to model labor market impacts of various vehicle policy options, although a number of judgments need to be made about the appropriate assumptions underlying the model as well the empirical basis for the modeling results.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 450 of 768 v. Single Sectors

It is possible to conduct a bottom-up analys is of the partial eff ect of regulation on employment in a single sector by estimating the change in output or expenditures in a sector and multiplying it by an estimate of the number of workers per unit of output or expenditures, under the assumption that labor demand is proportiona l to output or expenditures. As Berck and Hoffmann note, though, “Compliance with regula tions may create additional jobs that are not accounted for.” While such an analysis can approximate the effects in that one sector in a simple way, it also may miss important connections to related sectors.

vi. Ex-Post Econometric Studies

A number of ex-post econometric analyses examine the net effect of regulation on employment in regulated sectors. Morgenstern, Pizer, and Shih (2002), discussed above, and Berman and Bui (2001) are two notable examples that rely on highly disaggregated
establishment-level time series data to estimate longer-run employment effects. 555 While often a sophisticated treatment of the issues analyzed, these studies commonly analyze specific scenarios or sectors in the past; care needs to be taken in extrapolating their results to other scenarios and to the future. For instance, neither of these tw o studies examines the auto industry and are therefore of limited appli cability in this context.

vii. Summary

All methods of estimating employment impacts of a regulation have advantages and limitations. CGE models may be most appropr iate for long-term impacts, but the usual assumption of equilibrium in the employment market means that it is not useful for looking at changes in overall employment: overall levels are likely to be premised on full employment. IO models, on the other hand, may be most appropriate for small-scale, short-term effects, because they assume fixed relationships across sectors an d do not require market equilibria. Hybrid models, which combine some features of CGEs with IO models, depend upon key assumptions and economic relationships that are built into them. Single-sector models are simple and straightforward, but they are often based on the assumptions that labor demand is proportional to output, and that other sectors are not affected. Finally, econometric models have been developed to evaluate the longer-run net effects of regula tion on sector employment, though these are expost analyses commonly of specific sectors or situations, and the results may not have direct bearing for the regulation being reviewed. We seek comment on the analytical approaches presented here, the inputs used below for employment analysis, and other appropriate methods for analyzing employment impacts for this rulemaking.

555 Berman, Eli, and Linda T. Bui, (2001) “Environmental Regulation and Labor Demand: Evidence from the South Coast Air Basin,” Journal of Public Economics , 79, 265 – 295.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 451 of 768 c. Employment analysis of this proposal

As mentioned above, this program is expected to affect employment in the regulated sector (auto manufacturing) and other sectors di rectly affected by the proposal: auto parts suppliers, auto dealers, the fuel supply mark et (which will face reduced petroleum production due to reduced fuel demand but which may see ad ditional demand for electricity or other fuels), and consumers (who will face higher vehicle costs a nd lower fuel expenditures). In addition, as the discussion above suggests, each of these sectors could potentially have ripple effects in the rest of the economy. These ripple effects depend much more heavily on the state of the macroeconomy than do the direct effects. At the national level, employment may increase in one industry or region and decrease in another, w ith the net effect being smaller than either individual-sector effect. EPA does not attempt to quantify the net eff ects of the regulation on overall national employment.

The discussion that follows provides a partial, bottom-up quantitative estimate of the effects of this proposal on the regulated sector (the auto industry; for reasons discussed below, we include some quantitative assessment of effect s on suppliers to the industry, although they are not regulated directly). It also includes qualitati ve discussion of the effe cts of the proposal on other sectors. Focusing quantification of employ ment impacts on the regulated sector has some advantages over quantifying all impacts. First, the analysis relies on data generated as part of the rulemaking process, which focuses on the regulated sector; as a result, what is presented here is based on internally consistent assumptions and estimates made in this proposal. Secondly, as discussed above, net effects on employment in the economy as a whole depend heavily on the overall state of the economy when this rule has its effects. Focusing on the regulated sector provides insight into employment effects in that sector without having to make assumptions about the state of the economy when this rule has its impacts. We include a qualitative discussion of employment effects other sectors to provide a broader perspective on the impacts
of this rule.

As noted above, in a full-employment economy, any changes in employment will resultfrom people changing jobs or voluntarily entering or exiting the workforce. In a fullemployment economy, employment impacts of this proposal will change employment in specific sectors, but it will have small, if any, effect on aggregate empl oyment. This rule would take effect in 2017 through 2025; by then, the current high unemployment may be moderated or ended. For that reason, this analysis does not include multiplier effects, but instead focuses on employment impacts in the most directly affected industries. Those sectors are likely to face the most concentrated employment impacts. The agencies seek comment on other sectors that are likely to be significantly affected and thus warrant further analysis in the final rulemaking analysis.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 452 of 768 i. Employment Impacts in the Auto Industry

Following the Morgenstern et al. conceptual framework for the impacts of regulation on employment in the regulated sector, we consider three effects for the auto sector: the demand effect, the cost eff ect, and the factor shift effect. However, we are only able to offer quantitative
estimates for the demand and cost effects. We no te that these estimates, based on extrapolations from current data, become more uncertain as time goes on.

(1) The Demand Effect

The demand effect depends on the effects of this proposal on vehicle sales. If vehicle sales increase, then more people will be require d to assemble vehicles and their components. If vehicle sales decrease, employment associated w ith these activities will unambiguously decrease. Unlike in Morgenstern et al.’s study, where the demand effect decreased employment, there are countervailing effects in the vehicle market due to the fuel savings resulting from this program. On one hand, this proposal will increase vehicle co sts; by itself, this effect would reduce vehicle sales. On the other hand, this proposal will redu ce the fuel costs of operating the vehicle; by itself, this effect would increase vehicle sales, es pecially if potential buyers have an expectation of higher fuel prices. This issue is discussed further in Sections III.H.1 and III.H.10.

Our approach here follows a method used by NHTSA in both the MY 2011 and the MY 2012-16 CAFE rulemakings: we estimate the number of workers required per vehicle and multiply that value by the expected change in the number of vehicles. DRIA Chapter 8.2.3.1.1 provides details about our calculation of the demand effect. We use data from the Bureau of Labor Statistics on employment in the Motor Vehicle and Parts sector, 556 and from Ward’s Automotive Group on data on U.S. production of cars and trucks, 557 to estimate an average of 0.096 workers per vehicle between 2001 and 2010. In addition, as described in DRIA Chapter 8.2.3.1, we incorporate a factor to reflect productivity improvements over time in the auto manufacturing industry of about 4.4 percent per ye ar; this estimate is derived from trends in employment requirements from 1993-2008 provided by the Bureau of Labor Statistics. We note that BLS has stated that it expects improv ements in productivity over time as well. 558

Section III.H.10 of this preamble provides es timates of the effects of this proposal on
vehicle sales. Not all U.S. sales are of domes tically produced vehicles, however. To estimate the proportion of domestic production affected by the change in sales, we again used data from Ward’s Automotive Group for total car and truck production in the U.S. compared to total car and truck sales in the U.S. For the period 2001-2010, the proportion is 66.7%. We thus weight

556 http://data.bls.gov/timeseries/CEU313360010 1?data_tool=XGtable, accessed August 3, 2011.

557 U.S. Vehicle Production by Manufacturer. UsaPr05.xls, accessed July 25, 2011 at http://subscribers.wardsauto.com/refcenter/ , ©Copyright 2011, Ward's Automotive Group, a division of Penton Media Inc. Redistribution prohibited.

558 http://www.bls.gov/oco/cg/cgs012.htm#outlook , accessed 10/4/11.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 453 of 768 sales by this factor to get an estimate of the effect on employment in the motor vehicle manufacturing sector due to this proposal.

Table Table III-86 shows the employment effect s associated with the change in vehicle sales for the two discount rates (3 and 7 percent) used in the vehicle sales analysis. Because, in total, we project vehicle sales to increase in all years, employment is also expected to increase in
order to build these additional vehicles.

Table III-86 Effects of Changes in Vehicle Sales on Employment in the Motor Vehicle Manufacturing Sector

Year Estimated change in vehicle sales, 3% discount
rate Estimated manufacturing

employment impact Estimated change in vehicle sales, 7% discount rate Estimated manufacturing

employment impact

2017 37,200 1,400 35,000 1,300 2018 111,200 4,000 104,700 3,800 2019 185,400 6,400 174,800 6,100 2020 280,600 9,300 264,600 8,800 2021 430,200 13,700 406,000 12,900 2022 485,700 14,800 458,000 13,900 2023 531,500 15,500 500,600 14,600 2024 584,100 16,300 549,800 15,300 2025 644,400 17,200 606,000 16,100

(2) The Cost Effect

The demand effect, discussed above, measures employment changes due to new vehicle sales only. The cost effect measures employment impacts due to the new or additional technologies needed for vehicles to comply w ith the proposed standards. As DRIA Chapter 8.2.3.1.3 explains, we estimate the cost effect by multiplying the costs of rule compliance by ratios of workers to each $1 million of expenditures in that sector. The magnitude and relative size of these ratios depends on the sectors’ labor intensity of the production process.

The use of these ratios has both advantages and limitations. It is often possible to estimate these ratios for quite specific sectors of the economy; as a result, it is not necessary to extrapolate employment ratios from possibly unr elated sectors. On the other hand, these estimates are averages for the sectors, covering all the activities in those sectors; they may not be representative of the labor requ ired when expenditures are required on specific activities, as the factor shift effect (discussed below) indicates . In addition, these estimates do not include changes in sectors that supply these sectors, such as steel or electronics producers. They thus may best be viewed as the effects on employment in the auto sector due to the changes inSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 454 of 768 expenditures in that sector, rather than as an assessment of all employment changes due to these changes in expenditures.

Some of the costs of this proposal will be spent directly in the auto manufacturing sector, but some of the costs will be spent in the auto parts manufacturing sector. Because we do not have information on the proportion of expenditures in each sector, we separately present the ratios for both the auto manufacturing sector and the auto parts manufacturing sector. These are not additive, but should instead be considered as a range of estimate s for the cost effect, depending on which sector adds technologies to the vehicles to comply with the regulation.

We use several public sources for estimates of employment per $1 million expenditures: the U.S. Bureau of Labor Statistics’ (BLS) Employment Requirements Matrix (ERM); 559 the Census Bureau’s Annual Survey of Manufactures 560 (ASM); and the Census Bureau’s Economic Census. DRIA Chapter 8.2.3.1.2 provides details on all these sources. The ASM and the
Economic Census have more sectoral detail than the ERM; we provide estimates for both Motor Vehicle Manufacturing and Light Duty Vehicle Ma nufacturing sectors for comparison purposes. For all of these, we adjust for the ratio of domestic production to domestic sales. The maximum value for employment impacts per $1 million exp enditures (after accounting for the share of domestic production) in 2009 was estimated to be 2.049 if all the additional costs are in the parts sector; the minimum value is 0.407, if all the additional costs are in the light-duty vehicle manufacturing sector: that is, the range of em ployment impacts is between 0.4 and 2 additional jobs per $1 million expenditures in the sector. The different data sources provide similar magnitudes for the estimates for the sectors. Parts manufacturing appears to be more laborintensive than vehicle manufacturing; light-duty vehicle manufacturing appears to be slightly less labor-intensive than motor vehicle manufacturing as a whole. As discussed in the DRIA, trends in the BLS ERM are used to estimate productivity improvements over time that are used to adjust these ratios over time. Table III-87 shows the cost estimates developed for this rule, discussed in Section XX.XX. Multiplying those cost estimates by the maximum and minimum values for the cost effect (maximum using the AS M ratio if all additional costs are in the parts sector, and minimum using the Economic Census ra tio for the light-duty sector if all additional costs are borne by auto manufacturers) provid es the cost effect employment estimates.

Table III-87 Employment Effects due to In creased Expenditures on Vehicles and Parts

Year Costs (before adjustment for domestic proportion of production) Minimum employment effect if all expenditures are in light duty vehicle mfg sector Maximum employment effect if all expenditures

are in the parts sector

559 http://www.bls.gov/emp/ep_data_emp_requirements.htm

560 http://www.census.gov/manufacturing/asm/index.htmlSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 455 of 768 ($Millions)

2017 $ 1,997 500 3,100
2018 $ 4,179 1,000 6,200
2019 $ 6,255 1,500 9,000
2020 $ 8,369 1,900 11,600
2021 $ 11,875 2,600 15,900
2022 $ 17,374 3,700 22,500
2023 $ 22,690 4,600 28,300
2024 $ 28,151 5,400 33,900
2025 $ 33,566 6,200 39,000

(3) The Factor Shift Effect

The factor shift effect looks at the effects on employment due to changes in labor intensity associated with a regulation. As noted above, th e estimates of the cost effect assume constant labor per $1 million in expenditures, though the ne w technologies may be either more or less
labor-intensive than the exis ting ones. An estimate of the factor shift effect would either increase or decrease the estimate used for the cost effect.

We are not quantifying the factor shift effect here, for lack of data on the labor intensity of all the possible technologies that manufactu rers could use to comply with the proposed standards. As discussed in DRIA Chapter 8.2.3.1.3, though, for a subset of the technologies, EPA-sponsored research (discussed in Chapter 3.2.1.1 of the Joint TSD), which compared new technologies to existing ones at the level of in dividual components, found that labor use for the new technologies increased: the new fuel-savi ng technologies use more labor than the baseline technologies. For instance, switching from a con ventional mid-size vehicle to a hybrid version of that vehicle involves an additional $395.85 in labor costs, which we estimate to require an additional 8.6 hours per vehicle. For a subset of the technologies likely to be used to meet the standards in this proposal, then, the factor shi ft effect increases labor demand, at least in the short run; in the long run, as with all technologi es, the cost structure is likely to change due to learning, economies of scale, etc. The technologies examined in this research are, however, only a subset of the technologies that auto makers may use to comply with the standards proposed here. As a result, these results cannot be considered definitive evidence that the factor-shift effect increases employment for this rule. We therefore do not quantify the factor shift effect.

(4) Summary of Employment Effects in the Auto Sector

Some challenges arise in adding up the effects of this proposal on employment in the auto sector. First, the vehicle sales estimates are not cycled back into the overall rule impacts, due to modeling limitations: changing the modeling results due to vehicle sales might require iterating the vehicle sales analysis with the technology cost analysis, which the technology cost model is not set up to do. Secondly, the costs of the rule, used to estimate the “cost effect,” do not includeSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 456 of 768 the effects of changes in vehicle sales. Third, as noted, the “factor shift effect” is not fully quantified: though a subset of potential co mpliance technologies requires increased labor compared to the baseline technologies, those represent only a portion of the technologies available for complying with this rule. Nevert heless, following Morgenstern et al., we sum the demand and cost effects in Table III-88. Though these results are not precisely estimated, they show that employment effects in the regulated sector (and, possibly, the parts sector) are expected to be positive, and on the order of a few thousand in the initial years of the program. As noted above, the motor vehicle and parts manufacturing sectors employed about 677,000 people in 2010, with automobile and light truck manufacturing accounting for about 129,000 of
that total.

Table III-88 Partial Employment Effects in the Auto Manufacturing and Auto Parts Manufacturing Sectors due to Changes in Vehicle Sales and Changes in Costs

Year Employment Effects due to

Changes in Vehicle Sales, 3% Discount
Rate Employment Effects due to

Changes in Vehicle Sales, 7% Discount
Rate Employment Effects due to Cost Changes (Minimum – Maximum) Summed, Partial Employment Effects in the Motor Vehicle Manufacturing

Sector, 3% Discount Rate Summed, Partial Employment Effects in the Motor Vehicle Manufacturing

Sector, 7% Discount Rate

2017 1,400 1,300 500-3,100 1,900-4,500 1,800-4,400
2018 4,000 3,800 1,000-6,200 5,100-10,300 4,800-10,000
2019 6,400 6,100 1,500-9,000 7,900-15,400 7,600-15,100
2020 9,300 8,800 1,900-11,600 11,200-20,900 10,700-20,400
2021 13,700 12,900 2,600-15,900 16,300-29,600 15,500-28,800
2022 14,800 13,900 3,700-22,500 18,400-37,200 17,600-36,400
2023 15,500 14,600 4,600-28,300 20,000-43,800 19,100-42,900
2024 16,300 15,300 5,400-33,900 21,700-50,100 20,700-49,200
2025 17,200 16,100 6,200-39,000 23,400-56,100 22,300-55,100

ii. Effects on Employment for Auto Dealers

The effects of the proposed standards on employment for auto dealers depend principally on the effects of the standards on light duty vehicle sales. As discussed in Section III.H.10, if vehicle buyers consider five years’ worth of fuel savings when considering whether to invest in additional fuel economy, then this proposal is expected to increase light duty vehicle sales, which should be expected to increase employment for those who sell new light duty vehicles. As discussed in Section III.H.1.a, the role of fuel economy in consumer vehicle purchase decisions
is not well understood.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 457 of 768 Although this proposal predicts very small penetration of advanced technology vehicles, the uncertainty on consumer acceptance of such technology vehicles is even greater. As discussed in Section III.H.1.b, consumers may find some characteristics of electric vehicles and plug-in hybrid electric vehicles, such as the ability to fuel with electricity rather than gasoline, attractive; they may find other characteristics, such as the limited range for electric vehicles, undesirable. Auto dealers may play a major role in explaining the merits and disadvantages of these new technologies to vehicle buyers. There may be a temporary need for increased employment to train sales staff in the new technologies as the new technologies become
available.

iii. Effects on Employment in the Auto Parts Sector

As discussed in the context of employment in the auto industry, some vehicle parts are made in-house by auto manufacturers; others are made by independent suppliers who are not directly regulated, but who will be affected by the proposed stan dards as well. The additional expenditures on technologies are expected to have a positive eff ect on employment in the parts sector as well as the manufacturing sector; the breakdown in employment between the two sectors is difficult to predict. The effects on the parts sector also depend on the effects of the proposed standards on vehicle sales and on the labor intensity of the new technologies, qualitatively in the same ways as for the auto manufacturing sector. Because employment in the auto parts sector is expected to be affected in the same direction as in the auto manufacturing sector, we expect an increase in employment in the parts sector. Note that, under full employment, these workers would be pulled fr om other sectors, which would have an opportunity cost associated with it.

iv. Effects on Employment for Fuel Suppliers

In addition to the effects on the auto manufacturing and parts sectors, these rules will result in changes in fuel use that lower GHG em issions. Fuel saving, principally reductions in liquid fuels such as gasoline and diesel, will affect employment in the fuel suppliers industry sectors throughout the supply chain, from refineries to gasoline stations. To the extent that the proposed standards result in increased use of elect ricity, natural gas, or other fuels, employment effects will result from providing these fuels and de veloping the infrastructure to supply them to

consumers.

Expected petroleum fuel consumption reductions can be found in Section III.H.3. While those figures represent fuel savings for purchasers of fuel, it represents a loss in value of output for the petroleum refinery industry, fuel distribution, and gasoline stations. The loss of expenditures to petroleum fuel suppliers throughout the petroleum fuel supply chain, from the petroleum refiners to the gasoline stations, is likely to result in reduced employment in these

sectors.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 458 of 768 This rule is also expected to lead to increas es in electricity consumption by vehicles, as discussed in Section XX.XX. This new fuel may require additional infrastructure, such as electricity charging locations. Providing this infrastructure will require some increased employment. In addition, the generation of electr icity will also require some additional labor.
We have insufficient information at this time to predict whether the increases in labor associated with increased infrastructure provision and fuel generation for these newer fuels will be greater or less than the employment reductions associated with reduced demand for petroleum fuels.

v. Effects on Employment due to Impacts on Consumer Expenditures and EconomyWide Impacts

As a result of these proposed standards, c onsumers will pay a higher up-front cost for the vehicles, but they will recover those costs in a fairly short payback period (see Section III.H.10.b); indeed, people who fina nce their vehicles are expected to find that their fuel savings per month exceed the increase in the loan cost. As a result, consumers will have additional money to spend on other goods and services, though, for those who do not finance their vehicles, it will occur after the initial payback period. These increased expenditures will support employment in those sectors where consumers spend their savings.

These increased expenditures will occur in 201 7 and beyond. If the economy returns to full employment by that time, any change in consumer expenditures would primarily represent a shift in employment among sectors. If, on the other hand, the economy still has substantial unemployment, these expenditures would contribute to employment through increased consumer
demand.

Economy-wide CGE modeling of this rule provides additional insight into the effects of this rule on consumer expenditures, in addition to impacts on the overall market economy. 561
We conducted similar economy-wide impact analyses for both the 2012-2016 light-duty GHG final rule and the recent heavy-duty GHG final rule. 562 Our analysis focused on two key economic measures: U.S Gross Domestic Product (GDP) and consumption. 563 We analyzed the change in these two economic measures from the proposed rule’s anticipated impacts on vehicle

561 We provide general background on CGE models in Section III.H.11. b.ii.
562 See Memorandum to Docket, "Economy-Wide Impacts of Proposed Greenhouse Gas Tailpipe Standards for the Final Rulemaking," March 4, 2010, Document ID: EPA-HQ-OAR-2009-0472-11467 and Memorandum to Docket, “Economy-Wide Impacts of Heavy-Duty Truck Greenhouse Gas Emissions and Fuel Efficiency Standards”, May 20, 2011, Document ID: EPA-HQ-OAR-2010-0162-3342.
563 GDP is one widely-used measure of overall economic activity. It measures the market value of all goods and services produced in a given year and reflects the sum of its four components: consumption, investment, government spending, and net exports. Consumption, one component of GDP, may provide a more explicit indicator of households’ well being by showing the value of goods a nd services that households consume in a given year.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 459 of 768 costs, fuel consumption, U.S. oil imports, and world oil prices. 564 Our analysis indicated that
U.S. GDP would increase over time as a result of the proposed rule. For example, we estimated that U.S. GDP would increase by 0.36% in 2020 and 0.88% in 2030. We estimated that overall U.S. consumption would decline slightly in the first two years of the proposed program, but
would increase thereafter as the benefits from fu el savings outweigh higher vehicle costs. For example, we estimated that consumption per U.S. household would increase by $30 in 2020 and $860 in 2030 (in 2009 dollars). A more detailed discussion of these results and the methodology we used to conduct this economy-wide analysis are available in Chapter 8.3 of the DRIA.

For comparison, a modeling analysis of the TAR scenarios conducted by Management Information Services, Inc., for Ceres found that, in 2030, gross economic output would increase by $15.5 - $31.2 billion, personal income in the U.S. would increase by $ 10.2 to $20.5 billion, and national employment would increase by 350,000-680,000 jobs, with more stringent standards producing higher results. 565 Similar to the economy-wide analysis conducted for this rule, this study incorporated the effects of both increased vehicle costs and increased fuel savings. Unlike the economy-wide analysis here, this study used an input-output model (see Section III.H.11.b.iii for further discussion of these models).

d. Summary

The primary employment effects of this proposal are expected to be found throughout several key sectors: auto manufacturers, auto dealers, auto parts manufacturing, fuel production and supply, and consumers. We emphasize that the discussion here is a partial view of these effects. Whether the economy is in full em ployment will determine whether the discussed changes in employment in these sectors is offset in other sectors of the economy. The extent to which employment in the sectors discussed above responds to this program will also be influenced by how consumers consider fuel savi ngs in their vehicle purchase decisions, changes in vehicle manufacturing technologie s and locations, and other factors.

This rule initially takes effect in model year 2017, a time period sufficiently far in the future that the current sustained high unemployment at the national level may be moderated or ended. In an economy with full employment, the primary employment effect of a rulemaking is likely to be to move employment from one sector to another, rather than to increase or decrease employment. For that reason, we focus our quantitative analysis on employment in the regulated

564 Due to time constraints, the econo my-wide analysis was based on preliminary fuel savings and vehicle cost estimates. Relative to final estimates presented in the pro posed rulemaking, vehicle costs and fuels savings used in the economy-wide analysis were roughly 3-7% and 1% lowe r, respectively, over the years modeled. We projected the impact on world oil prices using a model developed by the Oak Ridge National Laboratory, which we discuss in III.H.7 and Chapter 4 of the Joint TSD. Note that the reduction in world oil prices is not reflected in the projected fuel prices that we assume elsewhere in the proposed rule, as described in II.E.

565 Management Information Services, Inc. “More Jobs per Gallon: How Strong Fuel Economy/GHG Standards will Fuel American Jobs.” Ceres Report, July 2011, http://www.ceres.org/resources/reports/more-jobs-pergallon/view, accessed 9/29/11.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 460 of 768 sector, to examine the impacts on that sector dir ectly. We discuss the likely direction of impacts in other directly related sectors, but we do not quantify those impacts, because employment impacts outside the regulated sector are more difficult to quantify with reasonable accuracy, particularly so far into the future.

For the regulated sector, the demand effect is expected to increase employment needs by perhaps 1,200 workers in 2017. The cost effect is expected to increase employment by 500 – 2,900 workers in 2017depending on the share of that employment that is in the auto manufacturing sector compared to the auto part s manufacturing sector. Though we do not have estimates of the factor shift effect for all pot ential compliance technologies, the evidence which we do have for some technologies suggests that many of the technologies will have increased
labor needs.

Increased vehicle sales are expected to lead to increased labor needs in auto dealerships. Increased vehicle sales and increased expenditures for auto parts are expected to require increased labor to build parts, though this effect also depends on any changes in the labor intensity of production; as noted, the subset of potential compliance technologies for which data are available show increased labor requirements. Reduced fuel production implies less employment in the fuel provision sectors. Finally, net cost savings to consumers are expected to increase employment through their increased expenditures in general retail sectors.

I. Statutory and Executive Order Reviews

a. Executive Order 12866: “Regulatory Planning and Review and Executive Order 13563: Improving Regulation and Regulatory Review”

Under section 3(f)(1) of Executive Order 12866 (58 FR 51735, October 4, 1993), this action is an "economically significant regulatory ac tion” because it is likely to have an annual effect on the economy of $100 million or more

. Accordingly, EPA submi tted this action to the Office of Management and Budget (OMB) for review under Executive Orders 12866 and 13563 (76 FR 3821, January 21, 2011) and any changes made in response to OMB recommendations
have been documented in the docket for this act ion as required by CAA section 307(d)(4)(B)(ii).

In addition, EPA prepared an analysis of the potential costs and benefits associated with this action. This analysis is contained in the Draft Regulatory Impact Analysis, which is available in the docket for this rulemaking a nd at the docket internet address listed under
ADDRESSES above.

b. Paperwork Reduction Act

The information collection requirements in this proposed rule have been submitted for approval to the Office of Management and Budget (OMB) under the Paperwork Reduction Act,Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 461 of 768 44 U.S.C. 3501 et seq . The Information Collection Request (ICR) document prepared by EPA has been assigned EPA ICR number 0783.61.

The Agency proposes to collect information to ensure compliance with the provisions in this rule. This includes a variety of requirements for vehicle manufacturers. Section 208(a) of the Clean Air Act requires that vehicle manufacturers provide information the Administrator may reasonably require to determine compliance with the regulations; submission of the information is therefore mandatory. We will consider confid ential all information meeting the requirements of section 208(c) of the Clean Air Act.

As shown in Table III-89, the total annual repo rting burden associated with this proposal is about xx hours and $x million, based on a projection of xx respondents. The estimated burden for vehicle manufacturers is a total estimate for both new and existing reporting requirements. Burden means the total time, effort, or financial resources expended by persons to generate, maintain, retain, or disclose or provide information to or for a Federal agency. This includes the time needed to review instructions; develop, acquire, install, and utilize technology and systems for the purposes of collecting, validating, and verifying information, processing and maintaining information, and disclosing and providing informatio n; adjust the existing ways to comply with any previously applicable instructions and requirem ents; train personnel to be able to respond to a collection of information; search data sources; complete and review the collection of information; and transmit or othe rwise disclose the information.

Table III-89 Estimated Burden for Repo rting and Recordkeeping Requirements

Number of respondents Annual burden hours Annual costs

xx xx $xx

An agency may not conduct or sponsor, and a person is not required to respond to a collection of information unless it displays a currently valid OMB cont rol number. The OMB control numbers for EPA's regulations in 40 CFR are listed in 40 CFR part 9.

To comment on the Agency's need for this information, the accuracy of the provided burden estimates, and any suggested methods for minimizing respondent burden, including the use of automated collection techniques, EPA has established a public docket for this rule, which includes this ICR, under Docket ID number EPA-HQ-OAR-2010-0799. Submit any comments related to the ICR for this proposed rule to EPA and OMB. See ‘Addresses’ section at the beginning of this notice for where to submit co mments to EPA. Send comments to OMB at the Office of Information and Regulatory Affairs, Office of Management and Budget, 725 17th Street, NW, Washington, DC 20503, Attention: Desk Office for EPA. Since OMB is required to make a decision concerning the ICR between 30 and 60 days after [Insert date of publication in the FEDERAL REGISTER], a comment to OMB is be st assured of having its full effect if OMBSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 462 of 768 receives it by [Insert date 30 days after pub lication in the FEDERAL REGISTER]. The final rule will respond to any OMB or public commen ts on the information collection requirements contained in this proposal.

c. Regulatory Flexibility Act

The Regulatory Flexibility Act (RFA) genera lly requires an agency to prepare a regulatory flexibility analysis of any rule subject to notice and comment rulemaking requirements under the Administrative Procedure Act or any other statute unless the agency certifies that the rule will not have a signifi cant economic impact on a substantial number of
small entities. Small entities include small businesses, small organizations, and small governmental jurisdictions.

For purposes of assessing the impacts of this ru le on small entities, small entity is defined as: (1) a small business as defined by the Small Business Ad ministration’s (SBA) regulations at 13 CFR 121.201 (see table below); (2) a small governmental jurisdiction that is a government of a city, county, town, school distri ct or special district with a population of less than 50,000; and (3) a small organization that is any not-for-prof it enterprise which is independently owned and operated and is not dominant in its field.

Table III-90 provides an overview of the primary SBA small business categories included in the light-duty vehicle sector:

Table III-90 Primary SBA Small Business Categories in the Light-Duty Vehicle Sector

Industry a Defined as Small Entity by SBA if Less Than or Equal to: NAICS Codes b

Vehicle manufacturers (including small volume manufacturers) 1,000 employees 336111, 336112

Independent commercial importers $7 million annual sales $23 million annual sales 100 employees 811111, 811112, 811198 441120 423110

Alternative Fuel Vehicle
Converters 750 employees 1,000 employees $7 million annual sales 336312, 336322, 336399 335312 811198

a. Light-duty vehicle entities that qualify as small businesses would not be subject to this proposed rule. We are proposing to exempt small business en tities from the proposed standards.

b. North American Industrial Classification System

After considering the economic impacts of today’s proposal on small entities, EPA certifies that this action will not have a signifi cant economic impact on a substantial number of small entities. As with the MY 2012-2016 GHG standards, EPA is proposing to exemptSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 463 of 768 manufacturers meeting SBA’s defini tion of small business as described in 13 CFR 121.201 due to unique issues involved with establishing appropriate GHG standards for these small businesses and the potential need to develop a program that would be structured differently for them (which would require more time), and the extremely small emissions contribution of these entities. EPA would instead consider appropriate GHG standards for these entities as part of a future regulatory action.

Potentially affected small entities fall into three distinct categories of businesses for lightduty vehicles: small volume manufacturers (SVMs) , independent commercial importers (ICIs), and alternative fuel vehicle converters. Based on our preliminary assessment, EPA has identified
a total of about 17 entities that fit the Small Bu siness Administration (SBA) criterion of a small business. There are about 4 small manufacturers, including three electri c vehicle manufacturers, 8 ICIs, and 5 alternative fuel vehicle converters in the light-duty vehicle market which are small businesses (no major vehicle manufacturers meet the small-entity criteria as defined by SBA). EPA estimates that these small entities comprise less than 0.1 percent of the total light-duty vehicle sales in the U.S., and therefore the propos ed exemption will have a negligible impact on the GHG emissions reductions from the proposed standards.

As discussed in Section III.B.7, EPA is proposing to allow small businesses to waive their small entity exemption and optionally cert ify to the GHG standards. This would allow small entity manufacturers to earn CO 2 credits under the GHG program, if their actual fleetwide

CO 2 performance was better than their fleetwide CO2 target standard. EPA proposes to make the GHG program opt-in available starting in MY 2014, as the MY 2012, and potentially the MY 2013, certification process will have already occurred by the time this rulemaking is finalized. EPA is also proposing that manufacturers certi fying to the GHG standards for MY 2014 would be eligible to generate early credits for vehicles sold in MY 2012 and MY 2013. Manufacturers waiving their small entity exemption would be requ ired to meet all aspects of the GHG standards and program requirements across their entire product line. However, the exemption waiver would be optional for small entities and presumab ly manufacturers would only opt into the GHG program if it is economically advantageous for them to do so, for example through the generation
and sale of CO 2 credits. Therefore, EPA believes adding this voluntary option does not affect EPA’s determination that the proposed standards would impose no significant adverse impact on
small entities.

Some commenters to the 2012-2016 light duty vehicle GHG rulemaking argued that EPA is obligated under the RFA to consider indirect impacts of the rules in assessing impacts on small businesses, in particular potential impacts on stationary sources that would not be directly regulated by the rule. EPA disagrees. When considering whether a rule should be certified, the RFA requires an agency to look only at the small entities to which the proposed rule will apply and which will be subject to the requirement of the specific rule in question. 5 USC section 603, 605 (b); Mid-Tex Elec. Coop. v. FERC , 773 F.3d 327, 342 (D.C. Cir. 1985). Reading sectionSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 464 of 768 605 in light of section 603, we conclude that an agency may properly certify that no regulatory flexibility analysis is necessary when it determ ines that the rule will not have a significant economic impact on a substantial number of small en tities that are subject to the requirements of the rule; see also Cement Kiln Recycling Coalition , v. EPA, 255 F.3d 855, 869 (D.C. Cir. 2001). D.C. Circuit has consistently rejected the cont ention that the RFA applies to small businesses indirectly affected by the regulation of other entities. 566

Since the proposal would regulate exclusively large motor vehicle manufacturers and small vehicle manufacturers are exempted from the standards, EPA is properly certifying that the 2017-2025 standards would not have a significant economic impact on a substantial number of small entities directly subject to the rule or othe rwise would have a positive economic effect on all of the small entities opting in to the rule.

We continue to be interested in the poten tial impacts of the proposed rule on small entities and welcome comments on issues related to such impacts.

d. Unfunded Mandates Reform Act

Title II of the Unfunded Mandates Reform Act of 1995 (UMRA), P.L. 104-4, establishes requirements for Federal agencies to assess the eff ects of their regulatory actions on State, local, and tribal governments and the private sector.

This proposal contains no Federal mandates (und er the regulatory provisions of Title II of the UMRA) for State, local, or tribal governments. The rule imposes no enforceable duty on any State, local or tribal governments. This action is also not subject to the requirements of section 203 of UMRA because EPA has determined that this rule contains no regulatory requirements that might significantly or uniquely affect small governments. EPA has determined that this proposal contains a Federal mandate that may result in expenditures of $100 million or more for the private sector in any one year. EPA believes that the proposal represents the least costly, most cost-effective approach to revise the light duty vehicle standards as authorized by section 202(a)(1). See Section III.A.2.a above. The costs and benefits associated with the proposal are discussed above and in the Draft Regulatory Impact Analysis, as required by the UMRA.

e. Executive Order 13132: “Federalism”

This proposed action would not have federalis m implications. It will not have substantial direct effects on the States, on the relationshi p between the national government and the States, or on the distribution of power and responsibilities among the various levels of government, as specified in Executive Order 13132. This rulemaking would apply to manufacturers of motor

566 In any case, any impacts on stationary sources arise becau se of express statutory requirements in the CAA, not as a result of vehicle GHG regulation. Moreover, GHGs have become subject to regulation under the CAA by virtue of other regulatory actions taken by EPA before this proposal.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 465 of 768 vehicles and not to state or local governments; state and local governments that purchase new model year 2017 and later vehicles will enjoy substantial fuel savings from these more fuel
efficient vehicles. Thus, Executive Order 13132 does not apply to this action

. Although section 6 of Executive Order 13132 does not apply to this action, EPA did consult with representatives of state and local governments in developing this action.

In the spirit of Executive Order 13132, and consistent with EPA policy to promote communications between EPA and State and local governments, EPA specifically solicits comment on this proposed action from State and local officials.

f. Executive Order 13175: “Consultation and Coordination with Indian Tribal

Governments”

This proposed rule does not have tribal implications, as specified in Executive Order 13175 (65 FR 67249, November 9, 2000). This rule will be implemented at the Federal level and impose compliance costs only on vehicle manufacturers. Tribal governments would be affected only to the extent they purchase and use regulated vehicles; tribal governments that purchase new model year 2017 and later vehicles will enjoy substantial fuel savings from these more fuel efficient vehicles. Thus, Executive Order 13175 do es not apply to this rule. EPA specifically solicits additional comment on this proposed rule from tribal officials.

g. Executive Order 13045: “Protection of Children from Environmental Health Risks and Safety Risks”

This action is subject to EO 13045 (62 FR 19885, April 23, 1997) because it is an economically significant regulator y action as defined by EO 12866, and EPA believes that the environmental health or safety risk addressed by this action may have a disproportionate effect on children. Climate change impacts, and in particular the determinations of the Administrator in the Endangerment and Cause or Contribute Findings for Greenhouse Gases Under Section 202(a) of the Clean Air Act (74 FR 66496, December 15, 2009), are summarized in Section III.F.2. In making those Findings, the Administrator placed weig ht on the fact that certain groups, including children, are particularly vulnerable to climate-related health effects. In those Findings, the Administrator determined that the health effects of climate change linked to observed and projected elevated concentrations of GHGs include the increased likelihood of more frequent and intense heat waves, increases in ozone concentrations over broad areas of the country, an increase of the severity of extreme weather events such as hurricanes and floods, and increasing severity of coastal storms due to rising sea levels. . These effects can all increase mortality and morbidity, especially in vulnerable populations such as children, the elderly, and the poor. In addition, the occurrence of wildfires in North America have increased and are likely to intensify
in a warmer future. PM emissions from these wildfires can contribute to acute and chronicSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 466 of 768 illnesses of the respiratory system, including pn eumonia, upper respiratory diseases, asthma, and chronic obstructive pulmonary disease, especially in children.

EPA has estimated reductions in projected global mean surface temperature and sea level
rise as a result of reductions in GHG emissions as sociated with the standards proposed in this action (Section III.F.3). Due to their vulnerability, children may receive disproportionate benefits from these reductions in temperature and the subsequent reduction of increased ozone and severity of weather events.

The public is invited to submit comments or id entify peer-reviewed studies and data that assess effects of early life exposure to the pollutants addressed by this proposed rule.

2. Executive Order 13211: “Energy Effects” (Coe, Shelby)

Executive Order 13211 567 applies to any rule that: (1) Is determined to be economically significant as defined under E.O. 12866, and is likely to have a significant adverse effect on the supply, distribution, or use of energy; or (2) that is designated by the Administrator of the Office of Information and Regulatory Affairs as a significant energy action. If the regulatory action meets either criterion, we must evaluate the adverse energy effects of the proposed rule and explain why the proposed regulation is preferable to other potentially effective and reasonably feasible alternatives considered by us.

The proposed rule seeks to establish passenge r car and light truck fuel economy standards that would significantly reduce the consumption of petroleum, would achieve energy security benefits, and would not have any adverse energy effects (Section III.H.7). In fact, this rule has a positive effect on energy supply and use. Beca use the GHG emission standards finalized today result in significant fuel savings, this rule encour ages more efficient use of fuels. Accordingly, this proposed rulemaking action is not designate d as a significant energy action as defined by

E.O. 13211.

a. National Technology Transfer Advancement Act

Section 12(d) of the National Technology Transfer and Advancement Act of 1995 (“NTTAA”), Public Law No. 104-113, 12(d) (15 U.S.C. 272 note) directs EPA to use voluntary consensus standards in its regulatory activities unless to do so would be inconsistent with applicable law or otherwise impractical. Volunt ary consensus standards are technical standards (e.g., materials, specifications, test methods, sampling procedures, and business practices) that are developed or adopted by voluntary consen sus standards bodies. NTTAA directs EPA to provide Congress, through OMB, explanations when the Agency decides not to use available and applicable voluntary consensus standards.

567 66 FR 28355 (May 18, 2001).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 467 of 768 For CO 2 emissions, EPA is proposing to collect data over the same tests that are used for
the MY 2012-2016 CO 2 standards and for the CAFE program. This will minimize the amount of testing done by manufacturers, since manufacturers are already required to run these tests. For A/C credits, EPA is proposing to use a consensus methodology developed by the Society of Automotive Engineers (SAE) and also a new A/C idle test. EPA knows of no consensus
standard available for the A/C idle test.

b. Executive Order 12898: “Federal Actions to Address Environmental Justice in Minority Populations and Low-Income Populations”

Executive Order (EO) 12898 (59 FR 7629 (Feb. 16, 1994)) establishes federal executive policy on environmental justice. Its main provision directs federal agencies, to the greatest extent practicable and permitted by law, to make environmental justice part of their mission by identifying and addressing, as appropriate, disproportionately high and adverse human health orenvironmental effects of their programs, policies, and activities on minority populations and lowincome populations in the United States.

With respect to GHG emissions, EPA has dete rmined that this proposed rule will not have disproportionately high and adverse human h ealth or environmental effects on minority or low-income populations because it increases th e level of environmental protection for all affected populations without having any dispr oportionately high and adverse human health or environmental effects on any population, including any minority or low-income population. The
reductions in CO 2 and other GHGs associated with the proposed standards will affect climate change projections, and EPA has estimated reductions in projected global mean surface temperatures and sea-level rise (Section III.F. 3). Within settlements experiencing climate change, certain parts of the population may be especially vulnerable; these include the poor, the elderly, those already in poor health, the disabled, those living alone, and/or indigenous populations dependent on one or a few resources. 568 Therefore, these populations may receive disproportionate benefits from reductions in GHGs.

For non-GHG co-pollutants such as ozone, PM 2.5 , and toxics, EPA has concluded that it is not practicable to determine whether ther e would be disproportionately high and adverse
human health or environmental effects on minor ity and/or low income populations from this proposed rule.

J. Statutory Provisions and Legal Authority

Statutory authority for the vehicle controls proposed today is found in section 202 (a) (which authorizes standards for emissions of pollutants from new motor vehicles which

568 U.S. EPA. (2009). Technical Support Document for Endangerment or Cause or Contribute Findings for Greenhouse Gases under Section 202(a) of the Clean Air Act. Washington, D.C.: U.S. EPA. Retrieved on April 21, 2009 from http://epa.gov/climatechange/enda ngerment/downloads/TSD_Endangerment.pdf.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Page 468 of 768 emissions cause or contribute to air pollution which may reasonably be anticipated to endanger public health or welfare), 202 (d), 203-209, 216, and 301 of the Clean Air Act, 42 U.S.C. 7521 (a), 7521 (d), 7522, 7523, 7524, 7525, 7541, 7542, 7543, 7550, and 7601. Statutory authority for EPA to establish CAFE test procedures is fou nd in section 32904 (c) of the Energy Policy and Conservation Act, 49 USC section 32904 (c).

[Placeholder: Section IV – NHTSA’s CAFE Proposal]DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 469 of 768 Environmental Protection Agency

40 CFR Chapter I

For the reasons set forth in the preamble, the Environmental Protection Agency amends parts 85, 86, and 600 of title 40, Chapter I of the Code of Federal Regulations as follows:

PART 85—CONTROL OF AIR POLLUTION FROM MOBILE SOURCES

1. The authority citation for part 86 continues to read as follows:

Authority: 42 U.S.C. 7401–7671q.

Subpart F—[Amended]

2. Section 85.525 is amended by adding paragr aph (a)(2)(i)(D), to read as follows:

§ 85.525 Applicable standards.
* * * * *

(a) * * *

(2) * * *

(i) * * *

(D) Optionally, compliance with greenhouse gas emission requirements may be demonstrated by comparing the sum of CH 4 plus N 2 O plus CO 2 emissions from the before fuel conversion FTP results to the after fuel conversion FTP results. This comparison is based on test results from the emission data vehicle (EDV) from the conversion test group at issue. The summation of the post fuel conversion test results must be lower than the summation of the before conversion greenhouse gas emission results. CO 2 emissions are calculated as specified in

40 CFR 600.113-12. CH 4 and N 2 O emissions, before and after fuel conversion, are adjusted by applying multiplicative factors of 25 and 298, respectively, to account for their increased global warming potential. If statements of compliance are applicable and accepted in lieu of measuring

N 2 O, as permitted by EPA regulation, the comparison of the greenhouse gas results also need not
measure or include N 2 O in the before and after emission comparisons.

* * * * *DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 470 of 768 PART 86—CONTROL OF EMISSIONS FROM NEW AND IN-USE HIGHWAY
VEHICLES AND ENGINES

3. The authority citation for part 86 continues to read as follows:

Authority: 42 U.S.C. 7401–7671q.

4. Section 86.1 is amended to read as follows:

§ 86.1 Reference materials.

(a) Certain material is incorporated by reference into this part with the approval of the Director of the Federal Register under 5 U.S.C. 552(a) and 1 CFR part 51. To enforce any edition other than that specified in this sec tion, the Environmental Protection Agency must publish a notice of the change in the Federal Register and the material must be available to the public. All approved material is available for in spection at U.S. EPA, Air and Radiation Docket and Information Center, 1301 Constitution Ave., NW., Room B102, EPA West Building, Washington, DC 20460, (202) 202–1744, and is available from the sources listed below. It is also available for inspection at the National Ar chives and Records Administration (NARA). For information on the availability of this material at NARA, call 202–741–6030, or go to: http://www.archives.gov/ federal_register/ code _of_federal_regulations/ ibr_locations.html and
is available from the sources listed below:

(b) American Society for Testing and Material s, 100 Barr Harbor Drive, P.O. Box C700, West Conshohocken, PA, 19428–2959, (610) 832–9585, http:// www.astm.org/.

(1) ASTM D 975–04c, Standard Specification for Diesel Fuel Oils, IBR approved for §§86.1910, 86.213–11.

(2) ASTM D1945–91, Standard Test Method for Analysis of Natural Gas by Gas Chromatography, IBR approved for §§86.113–94, 86.513–94, 86.1213–94, 86.1313–94.

(3) ASTM D2163–91, Standard Test Method for Analysis of Liquefied Petroleum (LP) Gases and Propane Concentrates by Gas Chromatography, IBR approved for §§86.113–94, 86.1213–94, 86.1313–94.

(4) ASTM D2986–95a, Reapproved 1999, Standard Practice for Evaluation of Air Assay Media by the Monodisperse DOP (Dioctyl Phthalate) Smoke Test, IBR approved for §§86.1310–

2007.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 471 of 768 (5) ASTM D5186–91, Standard Test Method for Determination of Aromatic Content of Diesel Fuels by Supercritical Fluid Chroma tography, IBR approved for §§86.113–07, 86.1313– 91, 86.1313–94, 86.1313–98, 1313–2007.

(6) ASTM E29–67, Reapproved 1980, Standard Recommended Practice for Indicating Which Places of Figures Are To Be Considered Significant in Specified Limiting Values, IBR approved for §86.1105–87.

(7) ASTM E29–90, Standard Practice for Using Significant Digits in Test Data to Determine Conformance with Specifications, IBR approved for §§86.609–84, 86.609–96, 86.609–97, 86.609–98, 86.1009–84, 86.1009–96, 86.1442, 86.1708–99, 86.1709–99, 86.1710– 99, 86.1728–99.

(8) ASTM E29–93a, Standard Practice for Using Significant Digits in Test Data to Determine Conformance with Specifications, IBR approved for §§86.098–15, 86.004–15, 86.007–11, 86.007–15, 86.1803–01, 86.1823–01, 86.1824–01, 86.1825–01, 86.1837–01.

(9) ASTM F1471–93, Standard Test Method for Air Cleaning Performance of a HighEfficiency Particulate Air-Filter System, IBR approved §86.1310–2007.

(10) ASTM E903-96, Standard Test Method for Solar Absorptance, Reflectance, and Transmittance of Materials Using Integrating Spheres (Withdrawn 2005), IBR approved for §86.1866-12.

(11) ASTM E1918-06, Standard Test Method for Measuring Solar Reflectance of Horizontal and Low-Sloped Surfaces in the Field, IBR approved for §86.1866-12.

(12) ASTM C1549-09, Standard Test Method for Determination of Solar Reflectance Near Ambient Temperature Using a Portable Solar Reflectometer (2009) IBR approved for §86.1866-12.

(c) Society of Automotive Engineers, 400 Commonwealth Dr., Warrendale, PA 15096– 0001, (877) 606–7323 (U.S. and Canada) or (724) 776–4970 (outside the U.S. and Canada), http://www.sae.org.

(1) SAE J1151, December 1991, Methane Measurement Using Gas Chromatography, 1994 SAE Handbook—SAE International Coopera tive Engineering Program, Volume 1: Materials, Fuels, Emissions, and Noise; Section 13 and page 170 (13.170), IBR approved for §§86.111–94; 86.1311–94.

(2) SAE J1349, June 1990, Engine Power Test Code—Spark Ignition and Compression Ignition, IBR approved for §§86.094–8, 86.096–8.

(3) SAE J1850, July 1995, Class B Data Communication Network Interface, IBR approved for §§86.099–17, 86.1806–01.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 472 of 768 (4) SAE J1850, Revised May 2001, Class B Data Communication Network Interface, IBR approved for §§86.005–17, 86.007–17, 86.1806–04, 86.1806–05.

(5) SAE J1877, July 1994, Recommended Practice for Bar-Coded Vehicle Identification Number Label, IBR approved for §§86.095–35, 86.1806–01.

(6) SAE J1892, October 1993, Recommended Practice for Bar-Coded Vehicle Emission Configuration Label, IBR approved for §§86.095–35, 86.1806–01.

(7) SAE J1930, Revised May 1998, Electrica l/Electronic Systems Diagnostic Terms, Definitions, Abbreviations, and Acronyms, IBR approved for §§86.096–38, 86.004–38, 86.007– 38, 86.010–38, 86.1808–01, 86.1808–07.

(8) SAE J1930, Revised April 2002, Electri cal/Electronic Systems Diagnostic Terms, Definitions, Abbreviations, and Acronyms—Equivalent to ISO/TR 15031–2: April 30, 2002, IBR approved for §§86.005–17, 86.007–17, 86.010–18, 86.1806–04, 86.1806–05.

(9) SAE J1937, November 1989, Engine Te sting with Low Temperature Charge Air Cooler Systems in a Dynamometer Test Cell, IBR approved for §§86.1330–84, 86.1330–90.

(10) SAE J1939, Revised October 2007, Recommended Practice for a Serial Control and Communications Vehicle Network, IBR approved for §§86.010–18.

(11) SAE J1939–11, December 1994, Physical Layer—250K bits/s, Shielded Twisted Pair, IBR approved for §§86.005–17, 86.1806–05.

(12) SAE J1939–11, Revised October 1999, Physical Layer—250K bits/s, Shielded Twisted Pair, IBR approved for §§86.005–17, 86.007–17, 86.1806–04, 86.1806–05.

(13) SAE J1939–13, July 1999, Off-Board Diagnostic Connector, IBR approved for §§86.005–17, 86.007–17, 86.1806–04, 86.1806–05.

(14) SAE J1939–13, Revised March 2004, Off-Board Diagnostic Connector, IBR approved for §86.010–18.

(15) SAE J1939–21, July 1994, Data Link Layer, IBR approved for §§86.005–17,

86.1806–05.

(16) SAE J1939–21, Revised April 2001, Data Link Layer, IBR approved for §§86.005– 17, 86.007–17, 86.1806–04, 86.1806–05.

(17) SAE J1939–31, Revised December 1997, Network Layer, IBR approved for §§86.005–17, 86.007–17, 86.1806–04, 86.1806–05.

(18) SAE J1939–71, May 1996, Vehicle Application Layer, IBR approved for §§86.005– 17, 86.1806–05.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 473 of 768 (19) SAE J1939–71, Revised August 2002, Vehicle Application Layer—J1939–71 (through 1999), IBR approved for §§86.005–17, 86.007–17, 86.1806–04, 86.1806–05.

(20) SAE J1939–71, Revised January 2008, Vehicle Application Layer (Through February 2007), IBR approved for §86.010–38.

(21) SAE J1939–73, February 1996, Application Layer—Diagnostics, IBR approved for §§86.005–17, 86.1806–05.

(22) SAE J1939–73, Revised June 2001, Application Layer—Diagnostics, IBR approved for §§86.005–17, 86.007–17, 86.1806–04, 86.1806–05.

(23) SAE J1939–73, Revised September 2006, Application Layer—Diagnostics, IBR approved for §§86.010–18, 86.010–38.

(24) SAE J1939–81, July 1997, Recommended Practice for Serial Control and Communications Vehicle Network Part 81—Network Management, IBR approved for §§86.005–17, 86.007–17, 86.1806–04, 86.1806–05.

(25) SAE J1939–81, Revised May 2003, Network Management, IBR approved for §86.010–38.

(26) SAE J1962, January 1995, Diagnostic Connector, IBR approved for §§86.099–17,

86.1806–01.

(27) SAE J1962, Revised April 2002, Diagnostic Connector Equivalent to ISO/DIS 15031–3; December 14, 2001, IBR approved for §§86.005–17, 86.007–17, 86.010–18, 86.1806– 04, 86.1806–05.

(28) SAE J1978, Revised April 2002, OBD II Scan Tool—Equivalent to ISO/DIS 15031– 4; December 14, 2001, IBR approved for §§86.005–17, 86.007–17, 86.010–18, 86.1806–04,

86.1806–05.

(29) SAE J1979, July 1996, E/E Diagnostic Test Modes, IBR approved for §§86.099–17,

86.1806–01.

(30) SAE J1979, Revised September 1997, E/E Diagnostic Test Modes, IBR approved for §§86.096–38, 86.004–38, 86.007–38, 86.010–38, 86.1808–01, 86.1808–07.

(31) SAE J1979, Revised April 2002, E/E Diagnostic Test Modes—Equivalent to ISO/DIS 15031–5; April 30, 2002, IBR approved for §§86.099–17, 86.005–17, 86.007–17, 86.1806–01, 86.1806–04, 86.1806–05.

(32) SAE J1979, Revised May 2007, (R) E/E Diagnostic Test Modes, IBR approved for §86.010–18, 86.010–38.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 474 of 768 (33) SAE J2012, July 1996, Recommended Practice for Diagnostic Trouble Code Definitions, IBR approved for §§86.099–17, 86.1806–01.

(34) SAE J2012, Revised April 2002, (R) Diagnostic Trouble Code Definitions Equivalent to ISO/DIS 15031–6: April 30, 2002, IBR approved for §§86.005–17, 86.007–17, 86.010–18, 86.1806–04, 86.1806–05.

(35) SAE J2284–3, May 2001, High Speed CAN (HSC) for Vehicle Applications at 500 KBPS, IBR approved for §§86.096–38, 86.004–38, 86.007–38, 86.010–38, 86.1808–01,

86.1808–07.

(36) SAE J2403, Revised August 2007, Medium/Heavy-Duty E/E Systems Diagnosis Nomenclature—Truck and Bus, IBR approved for §§86.007–17, 86.010–18, 86.010–38,

86.1806–05.

(37) SAE J2534, February 2002, Recommended Practice for Pass-Thru Vehicle Programming, IBR approved for §§86.096–38, 86.004–38, 86.007–38, 86.010–38, 86.1808–01,

86.1808–07.

(38) SAE J2534–1, Revised December 2004, (R) Recommended Practice for Pass-Thru Vehicle Programming, IBR approved for §86.010–38.

(39) SAE J2064, Revised December 2005, R134a Refrigerant Automotive AirConditioned Hose, IBR ap proved for §86.166–12.

(40) SAE J2765, October, 2008, Procedure for Measuring System COP [Coefficient of Performance] of a Mobile Air Conditioning System on a Test Bench, IBR approved for §86.1866–12.

(41) SAE J1711, Recommended Practice for Measuring the Exhaust Emissions and Fuel Economy of Hybrid-Electric Vehicles, Including Plug-In Hybrid Vehicles, June 2010, IBR approved for § 86.1811-04(n).

(42) SAE J1634, Electric Vehicle Energy Consumption and Range Test Procedure, Cancelled October 2002, IBR approved for § 86.1811-04(n).

(43) SAE J1100, November, 2009, Motor Vehicle Dimensions, IBR approved for §86.1866–12(d).

(44) SAE J2064, Revised December 2005, R134a Refrigerant Automotive AirConditioned Hose, IBR approv ed for §86.166-12(d).

(d) American National Standards Institute, 25 W 43rd Street, 4th Floor, New York, NY 10036, (212) 642–4900, http://www.ansi.org.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 475 of 768 (1) ANSI/AGA NGV1–1994, Standard for Co mpressed Natural Gas Vehicle (NGV) Fueling Connection Devices, IBR approved for §§86.001–9, 86.004–9, 86.098–8, 86.099–8, 86.099–9, 86.1810–01.

(2) [Reserved]

(e) California Air Resources Board, (916) 322–2884, http://www.arb.ca.gov .

(1) California Regulatory Requ irements Applicable to the “ LEV II” Program, including:

(i) [Reserved]

(ii) California Non-Methane Organic Gas Test Procedures, August 5, 1999, IBR approved for §§86.1803–01, 86.1810–01, 86.1811–04.

(2) California Regulatory Requirements Applicable to the National Low Emission Vehicle Program, October 1996, IBR approved for §§86.113–04, 86.612–97, 86.1012–97, 86.1702–99, 86.1708–99, 86.1709–99, 86.1717–99, 86.1735–99, 86.1771–99, 86.1775–99, 86.1776–99, 86.1777–99, Appendix XVI, Appendix XVII.

(3) California Regulatory Requirements kn own as On-board Diagnostics II (OBD–II), Approved on April 21, 2003, Title 13, California Code Regulations, Section 1968.2, Malfunction and Diagnostic System Requirements for 2004 and Subsequent Model-Year Passenger Cars, Light-Duty Trucks, and Medium-Duty Vehicles and Engines (OBD–II), IBR approved for §86.1806–05.

(4) California Regulatory Requirements kn own as On-board Diagnostics II (OBD–II), Approved on November 9, 2007, Title 13, California Code Regulations, Section 1968.2, Malfunction and Diagnostic System Requirements for 2004 and Subsequent Model-Year Passenger Cars, Light-Duty Trucks, and Medium-Duty Vehicles and Engines (OBD–II), IBR approved for §§86.007–17, 86.1806–05.

(f) International Organization for Standardization, Case Postale 56, CH–1211 Geneva 20, Switzerland, 41–22–749–01–11, http://www.iso.org .

(1) ISO 9141–2, February 1, 1994, Road vehicles—Diagnostic systems—Part 2: CARB requirements for interchange of digital information, IBR approved for §§86.099–17, 86.005–17, 86.007–17, 86.1806–01, 86.1806–04, 86.1806–05.

(2) ISO 14230–4:2000(E), June 1, 2000, Road vehicles—Diagnostic systems—KWP 2000 requirements for Emission-related systems, IBR approved for §§86.099–17, 86.005–17, 86.007–17, 86.1806–01, 86.1806–04, 86.1806–05.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 476 of 768 (3) ISO 15765–4.3:2001, December 14, 2001, Road Vehicles—Diagnostics on Controller Area Networks (CAN)—Part 4: Requirements for emissions-related systems, IBR approved for §§86.005–17, 86.007–17, 86.1806–04, 86.1806–05.

(4) ISO 15765–4:2005(E), January 15, 2005, Road Vehicles—Diagnostics on Controller Area Networks (CAN)—Part 4: Requirements for emissions-related systems, IBR approved for §§86.007–17, 86.010–18, 86.1806–05.

(5) ISO 13837:2008, May 30, 2008, Road Ve hicles—Safety glazing materials. Method for the determination of solar transmittance, IBR approved for §86.1866-12.

(g) Government Printing Office, Washington, DC 20402, (202) 512–1800 http://www.nist.gov. .

(1) NIST Special Publication 811, 1995 Editi on, Guide for the Use of the International System of Units (SI), IBR approved for §86.1901.

(2) [Reserved]

(h) Truck and Maintenance Council, 950 North Glebe Road, Suite 210, Arlington, VA 22203–4181, (703) 838–1754.

(1) TMC RP 1210B, Revised June 2007, WINDOWSTMCOMMUNICATION API, IBR approved for §86.010–38.

(2) [Reserved]

Subpart B – [Amended]

5. Section 86.111-94 is amended by revising paragraph (b) introductory text to read as follows:

§ 86.111-94 Exhaust gas analytical system. * * * * *

(b) Major component description. The exhaust gas analytical system, Figure B94–7, consists of a flame ionization detector (FID) (h eated, 235 °±15 °F (113 °±8 °C) for methanolfueled vehicles) for the determination of THC, a methane analyzer (consisting of a gas chromatograph combined with a FI D) for the determination of CH 4, non-dispersive infrared analyzers (NDIR) for the determination of CO and CO 2 , a chemiluminescence analyzer (CL) for
the determination of NO X , and an analyzer meeting the requirements specified in 40 CFR
1065.275 for the determination of N 2 O. A heated flame ionization detector (HFID) is used forDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 477 of 768 the continuous determination of THC from petroleu m-fueled diesel-cycle vehicles (may also be used with methanol-fueled diesel-cycle vehicl es), Figure B94–5 (or B94–6). The analytical system for methanol consists of a gas chromatograph (GC) equipped with a flame ionization detector. The analysis for formaldehyde is performed using high-pressure liquid chromatography (HPLC) of 2,4-dinitrophenylhydrazine (DNPH) de rivatives using ultraviolet (UV) detection. The exhaust gas analytical system shall conform to the following requirements:

* * * * *

6. Section 86.135-12 is amended by revising paragraph (a) to read as follows:

§ 86.135-12 Dynamometer procedure. (a) Overview. The dynamometer run consists of two tests, a “cold” start test, after a minimum 12-hour and a maximum 36-hour soak according to the provisions of §§86.132 and 86.133, and a “hot” start test following the “cold” start by 10 minutes. Engine startup (with all accessories turned off), operation over the UDDS, and engine shutdown make a complete cold start test. Engine startup and operation over the first 505 seconds of the driving schedule complete the hot start test. The exhaust emissions are diluted with ambient air in the dilution tunnel as shown in Figure B94–5 and Figure B9 4–6. A dilution tunnel is not required for testing vehicles waived from the requirement to measure particulates. Six particulate samples are collected on filters for weighing; the first samp le plus backup is coll ected during the first 505 seconds of the cold start test; the second sample plus backup is collected during the remainder of the cold start test (including shutdown); the thir d sample plus backup is collected during the hot start test. Continuous proportional samples of gaseous emissions are collected for analysis during each test phase. For gasoline-fueled, natural gas-fu eled and liquefied petroleum gas-fueled Ottocycle vehicles, the composite samples collected in bags are analyzed for THC, CO, CO 2, CH 4 , NO X , and N 2 O. For petroleum-fueled diesel-cycle vehicles (optional for natural gas-fueled, liquefied petroleum gas-fueled and methanol-fueled diesel-cycle vehicles), THC is sampled and analyzed continuously according to the provisions of §86.110–94. Parallel samples of the dilution air are similarly analyzed for THC, CO, CO 2 , CH 4 , NO X , and N 2 O. For natural gasfueled, liquefied petroleum gas-fueled and meth anol-fueled vehicles, bag samples are collected and analyzed for THC (if not sampled continuously), CO, CO 2 , CH 4 , NO X , and N 2 O. For methanol-fueled vehicles, methanol and formaldehyde samples are taken for both exhaust emissions and dilution air (a single dilution air formaldehyde sample, covering the total test period may be collected). For ethanol-fueled vehicles, methanol, ethanol, acetaldehyde, and formaldehyde samples are taken for both exhaust emissions and dilution air (a single dilution air formaldehyde sample, covering the total test period may be coll ected). Parallel bag samples of dilution air are analyzed for THC, CO, CO 2 , CH 4 , NO X , and N 2 O.

* * * * *DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 478 of 768 7. Section 86.165-12 is amended by revising paragraphs (c)(1) and (c)(2) to read as follows:

§ 86.165-12 Air conditioning idle test procedure. * * * * *

(c) * * *

(1) Ambient humidity within the test cell durin g all phases of the test sequence shall be controlled to an average of 40 – 60 grains of water/pound of dry air.

(2) Ambient air temperature within the test cell during all phases of the test sequence shall be controlled to 73 - 80 °F on average and 75 ± 5 °F as an instantaneous measurement. Air temperature shall be recorded continuously at a minimum of 30 second intervals.

* * * * *

8. Section 86.166-12 is amended by revising paragraphs (b) and (d) to read as follows:

§ 86.166-12 Method for calculating emissi ons due to air conditioning leakage. * * * * *

(b) Rigid pipe connections . For 2017 and later model years, manufacturers may test the leakage of system connections by pressurizing the system with Helium and using a mass spectrometer to measure the leakage of the connect ions within the system. Connections that are demonstrated to be free of leaks using Helium mass spectrometry are considered to have a relative emission factor of 10 and are accounted for separately in the equation in paragraph (b)(2) of this section. The equation in paragraph (b)(1) of this section shall be us ed for the 2012 through 2016 model years, and for 2017 and later model years in cases where the connections are not demonstrated to be leak-free using Helium mass spectrometry.

(1) Determine the grams per year emission rate for rigid pipe connections using the following equation:

Grams/YR RP = 0.00522 × [(125 × SO) + (75 × SCO) + (50 × MO) + (10 × SW) + (5 × SWO) + (MG)]

Where:

Grams/YR RP = Total emission rate for rigid pipe connections in grams per year.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 479 of 768 SO = The number of single O-ring connections.

SCO = The number of single captured O-ring connections.

MO = The number of multiple O-ring connections.

SW = The number of seal washer connections.

SWO = The number of seal washer with O-ring connections.

MG = The number of metal gasket connections.

(2) For 2017 and later model years, manufacturers may test the leakage of system connections by pressurizing the system with Helium and using a mass spectrometer to measure the leakage of the connections within the system. Connections that are demonstrated to be free of leaks using Helium mass spectrometry are considered to have a relative emission factor of 10 and are accounted for separately in the following equation:

Grams/YR RP = 0.00522 × [(125 × SO) + (75 × SCO) + (50 × MO) + (10 × SW) + (10 × LTO) + (5 × SWO) + (MG)]

Where:

Grams/YR RP = Total emission rate for rigid pipe connections in grams per year.

SO = The number of single O-ring connections.

SCO = The number of single captured O-ring connections.

MO = The number of multiple O-ring connections.

SW = The number of seal washer connections.

LTO = The total number of O-ring connections (single, single captured, and multiple) that have demonstrated no leakage using Helium mass spectrometry. Connections included here should not be counted elsewhere in the equation, and all connections counted here must be tested using Helium mass spectrometry and demonstrated as free of leaks.

SWO = The number of seal washer with O-ring connections.

MG = The number of metal gasket connections.

* * * * *

(d) Flexible hoses . Determine the permeation emission rate in grams per year for each segment of flexible hose using the following equatio n, and then sum the values for all hoses inDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 480 of 768 the system to calculate a total flexible hose emission rate for the system. Hose end connections
shall be included in the calculations in paragraph (b) of this section.

Grams/YR FH = 0.00522 × (3.14159 × ID × L × ER)

Where:

Grams/YR FH = Emission rate for a segment of flexible hose in grams per year.

ID = Inner diameter of hose, in millimeters.

L = Length of hose, in millimeters.

ER = Emission rate per unit internal surface area of the hose, in g/mm 2 , selected from the following table, or, for 2017 and later model years, calculated according to SAE J2064 “R134a Refrigerant Automotive Air-Conditioned Hose” (incorporated by reference; see 86.1):

Material/configuration ERHighpressure side Lowpressure side
All rubber hose 0.0216 0.0144

Standard barrier or veneer hose 0.0054 0.0036 Ultra-low permeation barrier or veneer hose 0.00225 0.00167

* * * * *

9. A new section 86.167-17 is added to read as follows:

§ 86.167-17 AC17 Air Conditioning Efficiency Test Procedure. (a) Overview. The dynamometer operation consists of four elements: a pre-conditioning cycle, a 30-minute soak period under simulated solar heat, an SC03 drive cycle, and a Highway Fuel Economy Test (HFET) drive cycle. The ve hicle is preconditioned with the UDDS to bring the vehicle to a warmed-up stabilized condition. This preconditioning is followed by a 30 minute vehicle soak (engine off) that proceeds directly into the SC03 driving schedule, during which continuous proportional samples of gaseous em issions are collected for analysis. The SC03 driving schedule is followed immediately by the HFET cycle, during which continuous proportional samples of gaseous emissions are collected for analysis. The entire test, including the preconditioning driving, vehicle soak, and SC 03 and HFET official test cycles, is conducted in an environmental test facility. The environmental test facility must be capable of providing the following nominal ambient test conditions of: 77 °F air temperature, 50 percent relative humidity, a solar heat load intensity of 850 W/m 2 , and vehicle cooling air flow proportional to vehicle speed. Section 86.161–00 discusse s the minimum facility requirements andDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 481 of 768 corresponding control tolerances for air conditioning ambient te st conditions. The entire test sequence is run twice; with and without the vehi cle's air conditioner operating during the SC03 and HFET test cycles. For gasoline-fueled Otto-c ycle vehicles, the composite samples collected in bags are analyzed for THC, CO, CO 2 , and CH4. For petroleum-fueled diesel-cycle vehicles, THC is sampled and analyzed continuously according to the provisions of §86.110. Parallel bag samples of dilution air are analyzed for THC, CO, CO 2 , and CH 4 . The following figure shows the basic sequence of the test procedure.

(b) Dynamometer requirements. (1) Tests shall be run on a large single roll electric dynamometer or an equivalent dynamometer configuration that satisfies the requirements of §86.108–00. Time [min]
4 Hours

45

23

30

10

13

15

23

30

10

13

30 Drain and Fill Preperation Cycle
Soak for 12 to 36 Hours

Preconditioning - EPA 74

Solar Soak

Bag 1 - SC03 - A/C ON Vehicle/Site Preperation

Bag 2 - HWY - A/C ON

Soak

Preconditioning - EPA 74

Soak

Bag 3 - SC03 - A/C OFF

Bag 4 - HWY - A/C OFF

Analyze DataDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 482 of 768 (2) Position (vehicle can be driven) the test vehicle on the dynamometer and restrain.

(3) Required dynamometer inertia weight clas s selections are determined by the test vehicle’s test weight basis and corresponding eq uivalent weight as listed in the tabular information of §86.129–00(a) and discussed in §86.129–00 (e) and (f).

(4) Set the dynamometer test inertia weight and roadload horsepower requirements for the test vehicle (see §86.129–00 (e) and (f)). The dynamometer's horsepower adjustment settings shall be set such that the force imposed during dynamometer operation ma tches actual road load force at all speeds.

(5) The vehicle speed as measured from the dynamometer rolls shall be used. A speed vs. time recording, as evidence of dynamometer test validity, shall be supplied at request of the
Administrator.

(6) The drive wheel tires may be inflated up to a gauge pressure of 45 psi (310 kPa), or the manufacturer's recommended pressure if higher than 45 psi, in order to prevent tire damage. The drive wheel tire pressure shall be reported with the test results.

(7) The driving distance, as measured by counting the number of dynamometer roll or shaft revolutions, shall be determined for the test.

(8) Four-wheel drive and all-wheel drive vehicles may be tested either in a four-wheel drive or a two-wheel drive mode of operation. In order to test in the two-wheel drive mode, fourwheel drive and all-wheel drive vehicles may have one set of drive wheels disengaged; fourwheel and all-wheel drive vehicles which can be shifted to a two-wheel mode by the driver may be tested in a two-wheel drive mode of operation.

(c) Test cell ambient conditions.

(1) Ambient air temperature . (i) Ambient air temperature is controlled, within the test cell, during all phases of the test sequence to 77 ±2 °F on average and 77 ±5 °F as an
instantaneous measurement.

(ii) Air temperature is recorded continuously at a minimum of 30 second intervals. Records of cell air temperatures and values of average test temperatures are maintained by the manufacturer for all certification related programs.

(2) Ambient humidity . (i) Ambient humidity is controlled, within the test cell, during all phases of the test sequence to an average of 69 ±5 grains of water/pound of dry air.

(ii) Humidity is recorded continuously at a minimum of 30 second intervals. Records of cell humidity and values of average test humidity are maintained by the manufacturer for all certification related programs.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 483 of 768 (3) Solar heat loading . The requirements of 86.161-00(d) regarding solar heat loading specifications shall apply. The solar load of 850 W/m 2 is applied only during specified portions of the test sequence.

(d) Interior temperature measurement . The interior temperature of the vehicle shall be measured during the emission sampling phases of the test(s).

(1) Interior temperatures shall be measured by placement of thermocouples at the following locations:

(i) The outlet of the center duct on the dash.

(ii) Behind the driver and passenger seat headrests. The location of the temperature measuring devices shall be 30 mm behind each headrest and 330 mm below the roof.

(2) The temperature at each location shall be recorded a minimum of every 5 seconds.

(e) Air conditioning system settings . For the portion of the test where the air conditioner is required to be operating the settings shall be as follows:

(1) Automatic systems shall be set to automa tic and the temperature control set to 72 deg

F.

(2) Manual systems shall be set at the start of the SC03 drive cycle to full cool with the fan on the highest setting and the airflow setting to “r ecirculation.” Within the first idle period of the SC03 drive cycle (186 to 204 seconds) the fa n speed shall be reduced to the setting closest to 6 volts at the motor, the temperature setting sha ll be adjusted to provide 55 deg F at the center dash air outlet, and the airflow setting changed to “outside air.”

(f) Vehicle and test activities . The AC17 air conditioning test in an environmental test cell is composed of the followi ng sequence of activities.

(1) Drain and fill the vehicle's fuel tank to 40 percent capacity with test fuel. If a vehicle has gone through the drain and fuel sequence less than 72 hours previously and has remained under laboratory ambient temper ature conditions, this drain and fill operation can be omitted (see §86.132–00(c)(2)(ii)).

(2)(i) Position the variable speed cooling fan in front of the test vehicle with the vehicle's hood down. This air flow should provide representative cooling at the front of the test vehicle (air conditioning condenser and engine) during the driving cycles. See §86.161–00(e) for a discussion of cooling fan specifications.

(ii) In the case of vehicles with rear engine compartments (or if this front location provides inadequate engine coo ling), an additional cooling fan shall be placed in a position to provide sufficient air to maintain vehicle cooling. The fan capacity shall normally not exceedDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 484 of 768 5300 cfm (2.50 m 3 /s). If, however, it can be demonstrated that during road operation the vehicle receives additional cooling, and that such addition al cooling is needed to provide a representative test, the fan capacity may be increased or additional fans used if approved in advance by the
Administrator.

(3) Open all vehicle windows.

(4) Connect the emission test sampling system to the vehicle's exhaust tail pipe(s).

(5) Set the environmental test cell ambient te st conditions to the conditions defined in paragraph (c) of this section, except that the solar heat shall be off.

(6) Set the air conditioning system controls to off.

(7) Start the vehicle (with air conditioning system off) and conduct a preconditioning EPA urban dynamometer driving cycle (§86.115).

(i) If engine stalling should occur during any air conditioning test cycle operation, follow the provisions of §86.136–90 (Engine starting and restarting).

(ii) For manual transmission vehicles, th e vehicle shall be shifted according the provisions of §86.128–00.

(8) Following the preconditioning cycle, the test vehicle and cooling fan(s) are turned off, all windows are rolled up, and the vehicle is allowed to soak in the ambient conditions of paragraph (c)(1) of this section for 30 ±1 minutes. The solar heat system must be turned on and generating 850 W/m 2 within 1 minute of turning the engine off.

(9) Air conditioning on test

.
(i) Start engine (with air conditioning system also running). Fifteen seconds after the engine starts, place vehicle in gear.

(ii) Eighteen seconds after the engine starts, begin the initial vehicle acceleration of the SC03 driving schedule.

(iii) Operate the vehicle according to the SC03 driving schedule, as described in appendix I, paragraph (h), of this part, while sampling the exhaust gas.

(iv) At the end of the deceleration which is scheduled to occur at 594 seconds, simultaneously switch the sample flows from th e SC03 bags and samples to the “HFET” bags and samples, switch off gas flow measuring device No. 1, switch off the No. 1 petroleum-fueled diesel hydrocarbon integrator, mark the petroleum -fueled diesel hydrocarbon recorder chart, and start gas flow measuring device No. 2, and st art the petroleum-fueled diesel hydrocarbon integrator No. 2.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 485 of 768 (v) Allow the vehicle to idle for 14-16 seconds. Before the end of this idle period, record
the measured roll or shaft revolutions and reset the counter or switch to a second counter. As soon as possible transfer the SC03 exhaust and dilution air samples to the analytical system and process the samples according to §86.140 obtaining a stabilized reading of the bag exhaust sample on all analyzers within 20 minutes of the end of the sample collection phase of the test. Obtain methanol and formaldehyde sample analyses, if applicable, within 24 hours of the end of the sample collection phase of the test.

(vi) Operate the vehicle according to the HFET driving schedule, as described in 40 CFR 600.109-08, while sampling the exhaust gas.

(vii) Turn the engine off 2 seconds after the end of the last deceleration.

(viii) Five seconds after the engine stops running, simultaneously turn off gas flow measuring device No. 2 and if applicable, turn off the petroleum-fueled diesel hydrocarbon integrator No. 2, mark the hydrocarbon recorder chart, and position the sample selector valves to the “standby” position. Record th e measured roll or shaft revolu tions (both gas meter or flow measurement instrumentation readings), and re-set the counter. As soon as possible, transfer the HFET” exhaust and dilution air samples to the analytical system and process the samples according to §86.140, obtaining a stabilized reading of the exhaust bag sample on all analyzers within 20 minutes of the end of the sample collection phase of the test. Obtain methanol and formaldehyde sample analyses, if applicable, within 24 hours of the end of the sample period.

(10) Air conditioning off test . The air conditioning off test is identical to the steps identified in paragraphs (d)(1) through (9) of this section, except that the air conditioning system and fan speeds are set to complete off or the lowest. It is preferred that the air conditioning off test be conducted sequentially af ter the air conditioning on test, fo llowing a 10-15 minute soak.

Subpart S – [Amended]

10. Section 86.1801-12 is amended by revising paragraphs (b), (j), and (k) introductory text to read as follows:

§ 86.1801-12 Applicability. * * * * *

(b) Clean alternative fuel conversions. The provisions of this subpart apply to clean alternative fuel conversions as defined in 40 CFR 85.502, of all model year light-duty vehicles, light-duty trucks, medium duty passenger vehicles, and complete Otto-cycle heavy-duty
vehicles.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 486 of 768 * * * * *

(j) Exemption from greenhouse gas emissi on standards for small businesses. (1) Manufacturers that qualify as a small busin ess under the Small Business Administration regulations in 13 CFR part 121 are exempt from the greenhouse gas emission standards specified in §86.1818–12 and in associated provisions in this part and in part 600 of this chapter. This exemption applies to both U.S.-based and non-U.S.-based businesses. The following categories of businesses (with their associated NAICS codes) may be eligible for exemption based on the
Small Business Administration size standards in 13 CFR 121.201.

(i) Vehicle manufacturers (NAICS code 336111).

(ii) Independent commercial importers (NAICS codes 811111, 811112, 811198, 423110, 424990, and 441120).

(iii) Alternate fuel vehicle converters (NAICS codes 335312, 336312, 336322, 336399, 454312, 485310, and 811198).

(2) Effective for the 2014 and later model years, manufacturers that are otherwise exempt under the provisions of paragraph (j)(1) of this section may optionally comply with the greenhouse gas emission standards specified in §86.1818. A manufacturer making this choice is required to comply with all the applicable standa rds and provisions in §86.1818 and in associated provisions in this part and in part 600 of this chapter. Manufacturers may optionally earn early credits in the 2012 and/or 2013 model years by demonstrating compliance with the fleet average

CO 2 standard applicable in those model years. Ma nufacturers electing to earn these early credits must comply with the model year reporting requirements in §600.512-12 for each model year.

(k) Conditional exemption from greenhouse gas emission standards. Manufacturers meeting the eligibility requirements described in paragraphs (k)(1) and (2) of this section may request a conditional exemption from compliance with the emission standards described in §86.1818–12 paragraphs (c) through (e) and associated provisions in this part and in part 600 of this chapter. A conditional exemption under this paragraph (k) may be requested for the 2012 through 2016 model years. The terms “sales” and “sold” as used in this paragraph (k) shall mean vehicles produced and delivered for sale (or sold) in the states and territories of the United States. For the purpose of determining eligibil ity the sales of related companies shall be aggregated according to the provisions of §86.1838–01(b)(3).

* * * * *

11. Section 86.1803-01 is amended by revising the definitions for Footprint and Gross vehicle weight rating and adding defi nitions for Good engineering judgment, Gross combination weight rating, a nd Platform to read as follows:DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 487 of 768 § 86.1803-01 Definitions. * * * * *

Footprint is the product of average track width (rounded to the nearest tenth of an inch) and wheelbase (measured in inches and rounded to the nearest tenth of an inch), divided by 144 and then rounded to the nearest tenth of a square foot, where the average track width is the average of the front and rear track widths, where each is measured in inches and rounded to the
nearest tenth of an inch.

* * * * *

Good engineering judgment has the meaning given in 40 CFR 1068.30. See 40 CFR 1068.5 for the administrative process we use to evaluate good engineering judgment.

Gross combination weight rating (GCWR) means the value specified by the vehicle manufacturer as the maximum weight of a loaded vehicle and trailer, consistent with good engineering judgment.

* * * * *

Gross vehicle weight rating (GVWR) means the value specified by the manufacturer as the maximum design loaded weight of a sing le vehicle, consistent with good engineering judgment.

* * * * *

Platform means a group of vehicles with common body floor plan, chassis, engine, and transmission. A single platform may include mult iple fuel economy label classes or car lines.

* * * * *

12. Section 86.1818-12 is amended by adding paragraphs (b)(4), (c)(3)(i)(D), (c)(4), (g), and (h), and by revising paragraphs (c)(2)(i)(A) through (C), (c)(3)(i)(A) through (C), (f) introductory text, and (f)(3), to read as follows:

§ 86.1818-12 Greenhouse gas emission standards for light-duty vehicles, light-duty trucks, and medium-duty passenger vehicles. * * * * *

(b) * * *

(4) Emergency vehicle means a motor vehicle manufactured primarily for use as an ambulance or combination ambulance-hearse or for use by the United States Government or a State or local government for law enforcement.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 488 of 768 (c) * * *

(2) * * *

(i) * * *

(A) For passenger automobiles with a footprint of less than or equal to 41 square feet, the gram/mile CO 2 target value shall be selected for the appropriate model year from the following
table:DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 489 of 768 Model year CO 2 target value (grams/mile)

2012 244.0

2013 237.0

2014 228.0

2015 217.0

2016 206.0

2017 195.0

2018 185.0

2019 175.0

2020 166.0

2021 157.0

2022 150.0

2023 143.0

2024 137.0

2025 and later 131.0

(B) For passenger automobiles with a footprint of greater than 56 square feet, the gram/mile CO 2 target value shall be selected for the appropriate model year from the following
table:DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 490 of 768 Model year CO 2 target value (grams/mile)

2012 315.0

2013 307.0

2014 299.0

2015 288.0

2016 277.0

2017 263.0

2018 250.0

2019 238.0

2020 226.0

2021 215.0

2022 205.0

2023 196.0

2024 188.0

2025 and later 179.0

(C) For passenger automobiles with a footprint that is greater than 41 square feet and less than or equal to 56 square feet, the gram/mile CO 2 target value shall be calculated using the following equation and rounded to the nearest 0.1 grams/mile:

Target CO 2 = [a × f ] + b

Where:

f is the vehicle footprint, as defined in §86.1803; andDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 491 of 768 a and b are selected from the following tabl e for the appropriate model year:

Model year a b

2012 4.72 50.5

2013 4.72 43.3

2014 4.72 34.8

2015 4.72 23.4

2016 4.72 12.7

2017 4.53 8.9

2018 4.35 6.5

2019 4.17 4.2

2020 4.01 1.9

2021 3.84 -0.4

2022 3.69 -1.1

2023 3.54 -1.8

2024 3.4 -2.5

2025 and later 3.26 -3.2

* * * * *

(3) * * *

(i) * * *

(A) For light trucks with a footprint of less th an or equal to 41 square feet, the gram/mile

CO 2 target value shall be selected for the appropriate model year from the following table:DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 492 of 768 Model year CO 2 target value (grams/mile)

2012 294.0

2013 284.0

2014 275.0

2015 261.0

2016 247.0

2017 238.0

2018 227.0

2019 220.0

2020 212.0

2021 195.0

2022 186.0

2023 176.0

2024 168.0

2025 and later 159.0

(B) For light trucks with a footprint that is greater than 41 square feet and less than or equal to the maximum footprint value specified in the table below for each model year, the gram/mile CO 2 target value shall be calculated using the following equation and rounded to the nearest 0.1 grams/mile:

Target CO 2 = (a × f ) + bDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 493 of 768 Where:

f is the footprint, as defined in §86.1803; and

a and b are selected from the following tabl e for the appropriate model year:

Model year Maximum Footprint a b

2012 66.0 4.04 128.6

2013 66.0 4.04 118.7

2014 66.0 4.04 109.4

2015 66.0 4.04 95.1

2016 66.0 4.04 81.1

2017 50.7 4.87 38.3

2018 60.2 4.76 31.6

2019 66.4 4.68 27.7

2020 68.3 4.57 24.6

2021 73.5 4.28 19.8

2022 74.0 4.09 17.8

2023 74.0 3.91 16.0

2024 74.0 3.74 14.2

2025 and later 74.0 3.58 12.5

(C) For light trucks with a footprint that is greater than the minimum footprint value specified in the table below and less than or eq ual to the maximum footpr int value specified inDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 494 of 768 the table below for each model year, the gram/mile CO 2 target value shall be calculated using the following equation and rounded to the nearest 0.1 grams/mile:

Target CO 2 = (a × f ) + b

Where:

f is the footprint, as defined in §86.1803; and

a and b are selected from the following tabl e for the appropriate model year:

Model year Minimum Footprint Maximum Footprint a b

2017 50.7 66.0 4.04 80.5

2018 60.2 66.0 4.04 75.0

(D) For light trucks with a footprint greater than the minimum value specified in the table below for each model year, the gram/mile CO 2 target value shall be selected for the appropriate model year from the following table: Formatted TableDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 495 of 768 Model year Minimum Footprint CO 2 target value (grams/mile)

2012 66.0 395.0

2013 66.0 385.0

2014 66.0 376.0

2015 66.0 362.0

2016 66.0 348.0

2017 66.0 347.0

2018 66.0 342.0

2019 66.4 339.0

2020 68.3 337.0

2021 73.5 335.0

2022 74.0 321.0

2023 74.0 306.0

2024 74.0 291.0

2025 and later 74.0 277.0

* * * * *

(4) Emergency vehicles . Model year 2017 and later emergency vehicles may be excluded from the fleet average CO 2 exhaust emission standards described in paragraph (c) of this section. The manufacturer should notify the Administrator that they are making such an election in the model year reports required under §600.512 of this chapter. Such vehicles should be excluded from both the calculation of the fleet average standard for a manufacturer under this paragraph (c) and from the calculation of the fleet average carbon-related exhaust emissions in 86.510-12.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 496 of 768 * * * * *

(f) Nitrous oxide (N 2 O) and methane (CH 4 ) exhaust emission standards for passenger automobiles and light trucks . Each manufacturer's fleet of combined passenger automobile and light trucks must comply with N 2 O and CH 4 standards using either the provisions of paragraph (f)(1), (f)(2), or (f)(3) of this section. Except with prior EPA approval, a manufacturer may not use the provisions of both paragraphs (f)(1) and (f)(2) of this section in a model year. For example, a manufacturer may not use the provisions of paragraph (f)(1) of this section for their passenger automobile fleet and the provisions of para graph (f)(2) for their light truck fleet in the same model year. The manufacturer may use the provisions of both paragraphs (f)(1) and (f)(3) of this section in a model year. For example, a manufacturer may meet the N 2 O standard in paragraph (f)(1)(i) of this section and an alternative CH 4 standard determined under paragraph (f)(3) of this section.

* * * * *

(3) Optional use of alternative N 2 O and/or CH 4 standards

. Manufacturers may select an alternative standard applicable to a test group, for either N 2 O or CH 4 , or both. For example, a manufacturer may choose to meet the N 2 O standard in paragraph (f)(1)(i ) of this section and an
alternative CH 4 standard in lieu of the standard in pa ragraph (f)(1)(ii) of this section. The alternative standard for each pollutant must be greater than the applicable exhaust emission standard specified in paragraph (f)(1) of this section. Alternative N 2 O and CH 4 standards apply to emissions measured according to the Federal Test Procedure (FTP) described in Subpart B of this part for the full useful life, and become the applicable certification and in-use emission standard(s) for the test group. Manufacturers using an alternative standard for N 2 O and/or CH 4 must calculate emission debits according to the provisions of paragraph (f)(4) of this section for each test group/alternative standard combination. Debits must be included in the calculation of total credits or debits generated in a model year as required under § 86.1865-12(k)(5). For flexible fuel vehicles (or other vehicles cer tified for multiple fuels) you must meet these alternative standards when tested on any applicable test fuel type.

* * * * *

(g) Alternative fleet average standards for manufacturers with limited U.S. sales

. Manufacturers meeting the criteria in this para graph (g) may request that the Administrator establish alternative fleet average CO 2 standards that would apply instead of the standards in paragraph (c) of this section. The provisions of this paragraph (g) are applicable only to the 2017 and later model years.

(1) Eligibility for alternative standards . Eligibility as determined in this paragraph (g)
shall be based on the total sale s of combined passenger automobiles and light trucks. The terms “sales” and “sold” as used in this paragraph (g) shall mean vehicles produced and delivered for sale (or sold) in the states and territories of the United States. For the purpose of determiningDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 497 of 768 eligibility the sales of related companies shall be aggregated according to the provisions of §86.1838–01(b)(3). To be eligible for alternative standards established under this paragraph (g), the manufacturer's average sales for the three most recent consecutive model years must remain below 5,000. If a manufacturer's average sales for the three most recent consecutive model years exceeds 4999, the manufacturer will no longer be eligible for exemption and must meet applicable emission standards starting with the mo del year according to the provisions in this paragraph (g)(1).

(i) If a manufacturer's average sales for three consecutive model years exceeds 4999, and if the increase in sales is the result of corporate acquisitions, mergers, or purchase by another manufacturer, the manufacturer shall comply with the emission standards described in §86.1818– 12 paragraphs (c) through (d), as applicable, beginning with the first model year after the last year of the three consecutive model years.

(ii) If a manufacturer's average sales for three consecutive model years exceeds 4999 and is less than 50,000, and if the increase in sales is solely the result of the manufacturer's expansion in vehicle production (not the result of corporate acquisitions, mergers, or purchase by another manufacturer), the manufacturer shall comply with the emission standards described in §86.1818–12 paragraphs (c) through (e), as applicable, beginning with the second model year after the last year of the three consecutive model years.

(2) Requirements for new entrants into the U.S. market . New entrants are those manufacturers without a prior record of automobile sales in the United States and without prior certification to (or exemption from, under §86.1801-12(k)) greenhouse gas emission standards in §86.1818-12. In addition to the eligibility requirements stated in paragraph (g)(1) of this section,

new entrants must meet the following requirements:

(i) In addition to the information required und er paragraph (g)(4) of this section, new entrants must provide documentation that shows a clear intent by the company to actually enter the U.S. market in the years for which alternative standards are requested. Demonstrating such intent could include providing documentation th at shows the establishment of a U.S. dealer network, documentation of work underway to meet other U.S. requirements (e.g., safety standards), or other information that reasonably establishes intent to the satisfaction of the
Administrator.

(ii) Sales of vehicles in the U.S. by new entran ts must remain below 5,000 vehicles for the first two model years in the U.S. market and the average sales for any three consecutive years within the first five years of entering the U.S. market must remain below 5,000 vehicles. Vehicles sold in violation of these limits will be considered not covered by the certificate of conformity and the manufacturer will be subject to penalties on an in dividual-vehicle basis for sale of vehicles not covered by a certificate. In addition, violation of these limits will result in loss of eligibility for alternative standards until such point as the manufacturer demonstrates two consecutive model years of sales below 5,000 automobiles.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 498 of 768 (iii) A manufacturer with sales in the most recent model year of less than 5,000 automobiles, but where prior model year sales were not less than 5,000 automobiles, is eligible to request alternative standards under this paragraph (g). However, such a manufacturer will be considered a new entrant and subject to the provisions regard ing new entrants in this paragraph (g), except that the requirement to demonstrate an intent to enter the U.S. market it paragraph (g)(2)(i) of this section shall not apply.

(3) How to request alternative fleet average standards . Eligible manufacturers may petition for alternative standards for up to five consecutive model years if sufficient information is available on which to base such standards.

(i) To request alternative standards starting with the 2017 model year, eligible manufacturers must submit a completed applicatio n no later than July 30, 2013.

(ii) To request alternative standards starting with a model after 2017, eligible manufacturers must submit a completed request no later than 36 months prior to the start of the first model year to which the alternative standards would apply.

(iii) The request must contain all the information required in paragraph (g)(4) of this section, and must be signed by a chief officer of the company. If the Administrator determines that the content of the request is incomplete or insuffic ient, the manufacturer will be notified and given an additional 30 days to amend the request.

(4) Data and information submittal requirements . Eligible manufacturers requesting alternative standards under this paragraph (g) must submit the following information to the Environmental Protection Agency. The Administrator may re quest additional information as she deems appropriate. The completed request must be sent to the Environmental Protection Agency at the following address: Director, Compliance and Innova tive Strategies Division, U.S. Environmental Protection Agency, 2000 Traverwood Drive, Ann Arbor, Michigan 48105.

(i) Vehicle model and fleet information

.
(A) The model years to which the requested alternative standards would apply, limited to five consecutive model years.

(B) Vehicle models and projections of production volumes for each model year.

(C) Detailed description of each model, including the vehicle type, vehicle mass, power, footprint, and expected pricing.

(D) The expected production cycle for each model, including new model introductions and redesign or refresh cycles.

(ii) Technology evaluation information.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 499 of 768 (A) The CO 2 reduction technologies employed by the manufacturer on each vehicle model, including information regarding the cost and CO 2 -reducing effectiveness. Include technologies that improve air conditioning efficiency and reduc e air conditioning syst em leakage, and any “off-cycle” technologies that potentially provide benefits outside the operation represented by the Federal Test Procedure and the Highway Fuel Economy Test.

(B) An evaluation of comparable models from other manufacturers, including CO 2 results and air conditioning credits generated by the models. Comparable vehicles should be similar, but not necessarily identical, in the following respects: vehicle type, horsepower, mass, power-to-weight ratio, footprint, retail price, and any other re levant factors. For manufacturers requesting alternative standards starting with the 2017 model year, the analysis of comparable vehicles should include vehicles from the 2012 and 2013 model years, otherwise the analysis should at a minimum include vehicles from the most recent two model years.

(C) A discussion of the CO 2 -reducing technologies employed on vehicles offered outside of the U.S. market but not available in the U.S., includ ing a discussion as to wh y those vehicles and/or technologies are not being used to achieve CO 2 reductions for vehicles in the U.S. market.

(D) An evaluation, at a minimum, of the techno logies projected by the Environmental Protection Agency in a final rulemaking as those technologies likely to be used to meet greenhouse gas emission standards and the extent to which those technologies are employed or projected to be employed by the manufacturer. For any technology that is not projected to be fully employed, explain why this is the case.

(iii) Alternative fleet average CO 2 standards

.
(A) The most stringent CO 2 level estimated to be feasible for each model, in each model year, and the technological basis for this estimate.

(B) For each model year, a projection of the lowest feasible sales-weighted fleet average CO 2 value, separately for passenger automobiles and light trucks, and an explanation demonstrating that these projections are reasonable.

(C) A copy of any application, data, and related information submitted to NHTSA in support of a request for alternative Corporate Average Fuel Economy standards filed under 49 CFR Part 525.

(iv) Information supporting eligibility

.
(A) U.S. sales for the three previous model years and projected sales for the model years for which the manufacturer is seeking alternative standards.

(B) Information regarding ownership relationships with other manufacturers, including details regarding the application of the provisions of §86.1838–01(b)(3) regarding the aggregation of sales of related companies,DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 500 of 768 (4) Alternative standards . Upon receiving a complete appli cation, the Administrator will review the application and determine whether an alternative standard is warranted. If the Administrator judges that an alternative standard is warranted, the Administrator will publish a proposed determination in the Federal Register to establis h alternative standards for the manufacturer that the Administrator judges are appropriate. Following a 30 day public comment period, the Administrator will issue a final determinatio n establishing alternative standards for the manufacturer. If the Administrator does not establish alternative standards for an eligible manufacturer prior to 12 months before the first model year to which the alternative standards would apply, the manufacturer may request an extension of the exemption under 86.1801-12(k) or an extension of previously approved alternative standards, whichever may apply.

(5) Restrictions on credit trading . Manufacturers subject to alternative standards approved by the Administrator under this paragraph (g) may not trade credits to another manufacturer. Transfers between car and truck fleets within the manufacturer are allowed.

(h) Mid-term review of standards . No later than April 1, 2018, the Administrator shall determine whether the standards established in paragraph (c) of this section for the 2022 through 2025 model years are appropriate under section 202(a) of the Clean Air Act, in light of the record then before the Administrator. An opportunity for public comment shall be provided before making such determination. If the Administrator determines they are not appropriate, the
Administrator shall initiate a ru lemaking to revise the standard s, to be either more or less stringent as appropriate.

(1) In making the determination required by paragraph (h) of this section, the Administrator shall consider the information available on the factors relevant to setting greenhouse gas emission standards under section 202(a) of the Clean Air Act for model years 2022 through 2025, including but not limited to:

(i) The availability and effectiveness of technology, and the appropriate lead time for introduction of technology;

(ii) The cost on the producers or purchasers of new motor vehicles or new motor vehicle engines;

(iii) The feasibility and practicability of the standards;

(iv) The impact of the standards on reduction of emissions, oil conservation, energy security, and fuel savings by consumers;

(v) The impact of the standards on the automobile industry;

(vi) The impacts of the standards on automobile safety;

(vii) The impact of the greenhouse gas emission standards on the Corporate Average Fuel Economy standards and a national harmonized program; andDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 501 of 768 (viii) The impact of the standards on other relevant factors.

(2) The Administrator shall make the determination required by this paragraph (h) based upon a record that includes the following:

(i) A draft Technical Assessment Report addressi ng issues relevant to the standard for the 2022 through 2025 model years;

(ii) Public comment on the draft Technical Assessment Report;

(iii) Public comment on whether the standards established for the 2022 through 2025 model years are appropriate under section 202(a) of the Clean Air Act; and

(iv) Such other materials the Administrator deems appropriate.

(3) No later than November 15, 2017, the Administrator shall issue a draft Technical Assessment Report addressing issues relevant to the standards for the 2022 through 2025 model

years.

(4) The Administrator will set forth in detail the bases for the determination required by this paragraph (h), including the Administrator’s assessment of each of the factors listed in paragraph (h)(1) of this section.

13. Section 86.1823 is amended by revising paragraph (m)(2)(iii) to read as follows:

§ 86.1823-08 Durability demonstration procedures for exhaust emissions. * * * * *

(m) * * *

(2) * * *

(iii) For the 2012 through 2016 model years only, manufacturers may use alternative
deterioration factors. For N 2 O, the alternative deterioration factor to be used to adjust FTP and HFET emissions is the deterioration factor determined for (or derived from, using good engineering judgment) NO X emissions according to the provisions of this section. For CH 4 , the
alternative deterioration factor to be used to ad just FTP and HFET emissions is the deterioration factor determined for (or derived from, using good engineering judgment) NMOG or NMHC emissions according to the provisions of this section.

* * * * *DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 502 of 768 14. Section 86.1829 is amended by revising paragraph (b)(1)(iii) to read as follows:

§ 86.1829-01 Durability and emission testing requirements; waivers. * * * * *

(b) * * *

(1) * * *

(iii) Data submittal waivers. (A) In lieu of testing a methanol-fueled diesel-cycle light truck for particulate emissions a manufacturer ma y provide a statement in its application for certification that such light trucks comply with the applicable standards. Such a statement shall be based on previous emission tests, development tests, or other appropriate information and good engineering judgment.

(B) In lieu of testing an Otto-cycle light-duty vehicle, light-duty truck, or heavy-duty vehicle for particulate emissions for certification, a manufacturer may provide a statement in its application for certification that such vehicles comply with the applicable standards. Such a statement must be based on previous emission te sts, development tests, or other appropriate information and good engineering judgment.

(C) A manufacturer may petition the Administra tor for a waiver of the requirement to submit total hydrocarbon emission data. If the wa iver is granted, then in lieu of testing a certification light-duty vehicle or light-duty truck for total hydrocarbon emissions the manufacturer may provide a statement in its app lication for certification that such vehicles comply with the applicable standards. Such a statement shall be based on previous emission tests, development tests, or other appropriate information and good engineering judgment.

(D) A manufacturer may petition the Administra tor to waive the requirement to measure particulate emissions when conducting Selectiv e Enforcement Audit te sting of Otto-cycle
vehicles.

(E) In lieu of testing a gasoline, diesel, natural gas, liquefied petroleum gas, or hydrogen
fueled Tier 2 or interim non-Tier 2 vehicle for formaldehyde emissions when such vehicles are certified based upon NMHC emissions, a manu facturer may provide a statement in its application for certification that such vehicles comply with the applicable standards. Such a statement must be based on previous emission te sts, development tests, or other appropriate information and good engineering judgment.

(F) In lieu of testing a petroleum-, natural gas-, liquefied petroleum gas-, or hydrogenfueled heavy-duty vehicle for formaldehyde emis sions for certification, a manufacturer may provide a statement in its application for certif ication that such vehicles comply with the applicable standards. Such a statement must be based on previous emission tests, development tests, or other appropriate information and good engineering judgment.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 503 of 768 (G) For the 2012 through 2016 model years only, in lieu of testing a vehicle for N 2 O emissions, a manufacturer may provide a statement in its application for certification that such vehicles comply with the applicable standards. Such a statement must be based on previous emission tests, development tests, or othe r appropriate information and good engineering judgment.

* * * * *

15. Section 86.1865-12 is amended by adding paragraph (k)(5)(iv) and by revising paragraphs (k)(5) introductory text, (k)(6), (k)(7)(i), (k)(8)(iv)(A), (l)(1)(ii) introductory text, (l)(1)(ii)(F) to read as follows:

§ 86.1865-12 How to comply with the fleet average CO 2 standards.

* * * * *

(k) * * *

(5) Total credits or debits generated in a mode l year, maintained and reported separately for passenger automobiles and light trucks, shall be the sum of the credits or debits calculated in paragraph (k)(4) of this section and any of the following credits, if applicable, minus any N 2 O and/or CH 4 CO 2 -equivalent debits calculated according to the provisions of § 86.1818-12(f)(4):

* * * * *

(iv) Full size pickup truck credits earned according to the provisions of §86.1866–12(e).

(6) The expiration date of unused CO 2 credits is based on the model year in which the credits are earned, as follows:

(i) Unused CO 2 credits from the 2009 model year sha ll retain their full value through the 2014 model year. Credits remaining at the end of the 2014 model year shall expire.

(ii) Unused CO 2 credits from the 2010 through 2015 model years shall retain their full value through the 2021 model year. Credits remaining at the end of the 2021 model year shall expire.

(iii) Unused CO 2 credits from the 2016 and later model years shall retain their full value through the five subsequent model years after the model year in which they we re generated. Credits remaining at the end of the fifth model year afte r the model year in which they were generated shall expire.

(7) * * *DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 504 of 768 (i) Credits generated and calculated according to the method in paragraphs (k)(4) and (5) of this section may not be used to offset deficits other than those deficits accrued with respect to the standard in §86.1818. Credits may be banked and used in a future model year in which a manufacturer's average CO 2 level exceeds the applicable standard. Credits may be transferred between the passenger automobile and light truck fleets of a given manufacturer. Credits may also be traded to another manufacturer according to the provisions in paragraph (k)(8) of this section. Before trading or carrying over credits to the next model year, a manufacturer must apply available credits to offset any deficit, where the deadline to offset that credit deficit has not yet passed.

* * * * *

(8) * * *

(iv)(A) If a manufacturer ceases production of passenger automobiles and light trucks, the manufacturer continues to be responsible for offsetting any debits outstanding within the required time period. Any failure to offset the debits will be considered a violation of paragraph (k)(8)(i) of this section and may subject the manufacturer to an enforcement action for sale of vehicles not covered by a certificate, pursuant to paragraphs (k)(8)(ii) and (iii) of this section.

* * * * *

(l) * * *

(1) * * *

(ii) Manufacturers producing any passenger automobiles or light trucks subject to the provisions in this subpart must establish, maintain, and re tain all the following information in adequately organized records for each passenger automobile or light truck subject to this subpart:

* * * * *

(F) Carbon-related exhaust emission standard, N 2 O emission standard, and CH 4 emission standard to which the passenger automobile or light truck is certified.

* * * * *

16. Section 86.1866-12 is amended by revising the heading, by adding paragraphs (c)(5)(v) and (e), and by revising paragraphs (a), (b), (c) introductory text, (c)(2), (c)(3), (c)(5)(i), (c)(5)(iii) introductory text, (c)(5)(iv), and (d) to read as follows:

§ 86.1866-12 CO 2 fleet average credit and incentive programs. (a) Advanced technology vehicles

.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 505 of 768 (1) Electric vehicles, plug-in hybrid electric vehicles, and fuel cell vehicles, as those terms are defined in §86.1803–01, that are certified and produced and delivered for sale in the United States in the 2012 through 2025 model years may use a value of zero (0) grams/mile of

CO 2 to represent the proportion of electric operation of a vehicle that is derived from electricity that is generated from sources that are not onboard the vehicle.

(i) Model years 2012 through 2016: The use of zero (0) grams/mile CO 2 is limited to the first 200,000 combined electric vehicles, plug-in hy brid electric vehicles, and fuel cell vehicles produced and delivered for sale by a manufacturer in the 2012 through 2016 model years, except that a manufacturer that produces and delivers for sale 25,000 or more such vehicles in the 2012 model year shall be subject to a limitation on the use of zero (0) grams/mile CO 2 to the first 300,000 combined electric vehicles, plug-in hybr id electric vehicles, and fuel cell vehicles produced and delivered for sale by a manufacturer in the 2012 through 2016 model years.

(ii) Model years 2017 through 2021: For elect ric vehicles, plug-in hybrid electric vehicles, and fuel cell vehicles produced and delivered for sale in the 2017 through 2021 model years, such use of zero (0) grams/mile CO 2 is unrestricted.

(iii) Model years 2022 through 2025: The use of zero (0) grams/mile CO 2 is limited to the first 200,000 combined electric vehicles, plug-in hy brid electric vehicles, and fuel cell vehicles produced and delivered for sale by a manufacturer in the 2022 through 2025 model years, except that a manufacturer that produces and delivers for sale 300,000 or more such vehicles in the 2019 through 2021 model years shall be subject to a limitation on the use of zero (0) grams/mile CO 2 to the first 600,000 combined electric vehicles, plug-in hybrid electric vehicles, and fuel cell vehicles produced and delivered for sale by a manufacturer in the 2022 through 2025 model

years.

(2) For electric vehicles, plug-in hybrid electri c vehicles, and fuel cell vehicles, as those terms are defined in §86.1803–01, that are certified and produced and delivered for sale in the United States in the 2017 through 2021 model year s and that meet the additional specifications in this section, the manufacturer may use the produc tion multipliers in this paragraph (a)(2) when determining the manufacturer’s fleet average carbon-related exhaust emissions under §600.512 of this chapter.

(i) The production multipliers, by model year, fo r electric vehicles and fuel cell vehicles,
are as follows:

Model year Production multiplier
2017 2.0
2018 2.0
2019 2.0
2020 1.75
2021 1.5DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 506 of 768 (ii)(A) The production multipliers, by model year, for plug-in hybrid electric vehicles, are
as follows:

Model year Production multiplier
2017 1.6
2018 1.6
2019 1.6
2020 1.45
2021 1.3 (B) The minimum all-electric driving range th at a plug-in hybrid electric vehicle must have in order to qualify for use of a production multiplier is 10.2 miles on its nominal storage capacity of electricity when operated on the highway fuel economy test cycle. Alternatively, a plug-in hybrid electric vehicle may qualify for use of a production multiplier by having anequivalent all-electric driving range greater than or equal to 10.2 miles during its actual chargedepleting range as measured on the highway fuel economy test cycle and tested according to the requirements of SAE J1711, Recommended Practice for Measuring the Exhaust Emissions and Fuel Economy of Hybrid-Electric Vehicles, Includ ing Plug-In Hybrid Vehicles (incorporated by reference, see §86.1). The equivalent all-elect ric range of a PHEV is determined from the following formula:

ܧܣܧܴ ൌ ܴ ஼஽஺ ൈ ሺ ܥܱ2 ஼ௌ െ ܥܱ2 ஽஼ ሻ

ܱ2ܥ ௌ஼

Where:

EAER = the equivalent all-electric range attributed to charge-depleting operation of a plug-in hybrid electric vehicle on the highway fuel economy test cycle.

R CDA = The actual charge-depleting range determined according to SAE J1711,Recommended Practice for Measuring the Exhaust Emissions and Fuel Economy of HybridElectric Vehicles, Including Plug-In Hybrid Vehi cles (incorporated by reference, see §86.1).

CO2 CS = The charge-sustaining CO 2 emissions in grams per mile on the highway fuel economy test determined according to SAE J1711, Recommended Practice for Measuring the Exhaust Emissions and Fuel Economy of Hybrid -Electric Vehicles, Incl uding Plug-In Hybrid Vehicles (incorporated by reference, see §86.1).

CO2 CD = The charge-depleting CO 2 emissions in grams per mile on the highway fuel economy test determined according to SAE J1711, Recommended Practice for Measuring the Exhaust Emissions and Fuel Economy of Hybrid -Electric Vehicles, Incl uding Plug-In Hybrid Vehicles (incorporated by reference, see §86.1).

(iii) The actual production of qualifying vehicles may be multiplied by the applicable value according to the model year, and the result, rounded to the nearest whole number, may beDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 507 of 768 used to represent the production of qualifying vehicles when calculating average carbon-related exhaust emissions under §600.512 of this chapter.

(b) Credits for reduction of air conditioning refrigerant leakage. Manufacturers may generate credits applicable to the CO 2 fleet average program described in §86.1865–12 by implementing specific air conditioning system te chnologies designed to reduce air conditioning refrigerant leakage over the useful life of their passenger automobiles and/or light trucks. Credits shall be calculated according to this paragraph (b) for each air conditioning system that the manufacturer is using to generate CO 2 credits. Manufacturers may also generate early air conditioning refrigerant leakage credits under this paragraph (b) for the 2009 through 2011 model years according to the provisions of §86.1867–12(b).

(1) The manufacturer shall calculate an annual rate of refrigerant leakage from an air conditioning system in grams per year according to the provisions of §86.166–12.

(2) The CO 2 -equivalent gram per mile leakage reduction to be used to calculate the total leakage credits generated by the air conditioning system shall be determined according to the following formulae, rounded to the nearest tenth of a gram per mile:

(i) Passenger automobiles:

ൈ ݐ݁݀݅ݎܥݔܽܯ ൌ ݐ݁݀݅ݎܥ݁ܽ݇ܽ݃݁ ܮ ൤ െ 1 ൬ ݁ݎ݋݁ܽ݇ܵܿܮ

16.6 ൰൨ ൈ ൬ ܩܹܲ ோாி ܩܹܲ ுி஼ଵଷସ௔ ൰ ݏ݅ܦ݁ܽ݇ܮ݅ܪ െ

Where:

HiLeakDis means the high leak disincentive, which is zero for model years 2012 through 2016, and for 2017 and later model years is determ ined using the following equation, except that
if GWP REF is greater than 150 or if the result is le ss than zero HiLeakDis shall be set equal to zero and if the result is greater than 1.8 g/mi HiLeakDis shall be set to 1.8 g/mi:

ൈ 1.8 ൌ ݏ݅ܦ݁ܽ݇ܮ݅ܪ ቂ ሺ௅௘௔௞ௌ௖௢௥௘ିெ௜௡ௌ௖௢௥௘ ሺ ଵ଺.଺ିெ௜௡ௌ௖௢௥௘ ሻ ቃ

MaxCredit is 12.6 (grams CO 2 -equivalent/mile) for air conditioning systems using HFC– 134a, and 13.8 (grams CO 2 -equivalent/mile) for air conditioning systems using a refrigerant with a lower global warming potential.

LeakScore means the annual refrigerant leakage rate determined according to the provisions of §86.166–12(a), except if the calculated rate is less than 8.3 grams/year (4.1 grams/year for systems using only electric compressors), the rate for the purpose of this formula shall be 8.3 grams/year (4.1 grams/year for systems using only electric compressors).

The constant 16.6 is the average passenger automobile impact of air conditioning leakage in units of grams/year;DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 508 of 768 GWP REF means the global warming potential of the refrigerant as indicated in paragraph (b)(5) of this section or as otherwise determined by the Administrator;

GWP HFC134a means the global warming potential of HFC–134a as indicated in paragraph (b)(5) of this section or as otherwise determined by the Administrator.

MinScore is 8.3 grams/year, except that for systems using only electric compressors it is 4.1 grams/year.

(ii) Light trucks: ൬ െ 1 ൤ൈ ݐ݁݀݅ݎܥݔܽܯ ൌ ݐ݁݀݅ݎܥ݁ܽ݇ܽ݃݁ ܮ ݁ݎ݋݁ܽ݇ܵܿܮ

20.7 ൰൨ ൈ ൬ ܩܹܲ ோாி ܩܹܲ ுி஼ଵଷସ௔ ݏ݅ܦ݁ܽ݇ܮ݅ܪ െ ൰

Where:

HiLeakDis means the high leak disincentive, which is zero for model years 2012 through 2016, and for 2017 and later model years is determ ined using the following equation, except that
if GWP REF is greater than 150 or if the result is le ss than zero HiLeakDis shall be set equal to zero and if the result is greater than 2.1 g/mi HiLeakDis shall be set to 2.1g/mi:

ൈ 2.1 ൌ ݏ݅ܦ݁ܽ݇ܮ݅ܪ ቂ ሺ௅௘௔௞ௌ௖௢௥௘ିெ௜௡ௌ௖௢௥௘ ሺ ଶ଴.଻ିெ௜௡ௌ௖௢௥௘ ሻ ቃ

MaxCredit is 15.6 (grams CO 2 -equivalent/mile) for air conditioning systems using HFC– 134a, and 17.2 (grams CO 2 -equivalent/mile) for air conditioning systems using a refrigerant with a lower global warming potential.

Leakage means the annual refrigerant leakage rate determined according to the provisions of §86.166–12(a), except if the calculated rate is less than 10.4 grams/year (5.2 grams/year for systems using only electric compressors), the rate for the purpose of this formula shall be 10.4 grams/year (5.2 grams/year for systems using only electric compressors).

The constant 20.7 is the average light truck impact of air conditioning leakage in units of grams/year.

GWP REF means the global warming potential of the refrigerant as indicated in paragraph (b)(5) of this section or as otherwise determined by the Administrator;

GWP R134a means the global warming potential of HFC–134a as indicated in paragraph (b)(5) of this section or as otherwise determined by the Administrator.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 509 of 768 MinScore is 10.4 grams/year, except that fo r systems using only electric compressors it is 5.2 grams/year.

(3) The total leakage reduction credits generated by the air conditioning system shall be calculated separately for passenger automobiles and light trucks according to the following
formula:

Total Credits (megagrams) = (Leakage × Production × VLM) ÷ 1,000,000

Where:

Leakage = the CO 2 -equivalent leakage credit value in grams per mile determined in paragraph (b)(2) of this section.

Production = The total number of passenger automobiles or light trucks, whichever is applicable, produced with the air conditioning system to which to the leakage credit value from paragraph (b)(2) of this section applies.

VLM = vehicle lifetime miles, which for passenger automobiles shall be 195,264 and for light trucks shall be 225,865.

(4) The results of paragraph (b)(3) of this section, rounded to the nearest whole number,
shall be included in the manufacturer's cred it/debit totals calculated in §86.1865–12(k)(5).

(5) The following values for refrig erant global warming potential (GWP REF ), or alternative values as determined by the Administra tor, shall be used in the calculations of this paragraph (b). The Administrator will determine values for refrigerants not included in this paragraph (b)(5) upon request by a manufacturer.

(i) For HFC–134a, GWP REF = 1430;

(ii) For HFC–152a, GWP REF = 124;

(iii) For HFO–1234yf, GWP REF = 4;

(iv) For CO 2 , GWP REF = 1.

(c) Credits for improving air conditioning system efficiency. Manufacturers may generate credits applicable to the CO 2 fleet average program described in §86.1865–12 by implementing specific air conditioning system technologies de signed to reduce air conditioning-related CO 2 emissions over the useful life of their passenger automobiles and/or light trucks. Credits shall be calculated according to this paragraph (c) for each air conditioning system that the manufacturer is using to generate CO 2 credits. Manufacturers may also generate early air conditioning efficiency credits under this paragraph (c) for the 2009 through 2011 model years according to the provisions of §86.1867–12(b). For model years 2012 and 2013 the manufacturer mayDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 510 of 768 determine air conditioning efficiency credits usi ng the requirements in paragraphs (c)(1) through (4) of this section. For model years 2014 and later the eligibility requirements specified in paragraph (c)(5) of this section must be met before an air conditioning system is allowed to generate credits.

* * * * *

(2) Air conditioning efficiency credits ar e determined on an air conditioning system basis. For each air conditioning system that is eligible for a credit based on the use of one or more of the items listed in paragraph (c)(1) of this section, the total credit value is the sum of the gram per mile values listed in paragraph (c)(1) of this section for each item that applies to the air conditioning system.

(i) In the 2012 through 2016 model years the total credit value for an air conditioning system may not be greater than 5.7 grams per mile.

(ii) In the 2017 and later model years the to tal credit value for an air conditioning system may not be greater than 5.0 grams per mile for any passenger automobile or 7.2 grams per mile for any light truck.

(3) The total efficiency credits generated by an air conditioning system shall be calculated separately for passenger automobiles and light trucks according to the following
formula:

Total Credits (Megagrams) = (Credit × Production × VLM) ÷ 1,000,000

Where:

Credit = the CO 2 efficiency credit value in grams per mile determined in paragraph (c)(2) or (c)(5) of this section, whichever is applicable.

Production = The total number of passenger automobiles or light trucks, whichever is applicable, produced with the air conditioning sy stem to which to the efficiency credit value from paragraph (c)(2) of this section applies.

VLM = vehicle lifetime miles, which for passenger automobiles shall be 195,264 and for light trucks shall be 225,865.

* * * * *

(5) * * *

(i) After the 2013 model year, for each air conditioning system selected by the manufacturer to generate air conditioning efficiency credits, the manufacturer shall perform the Air Conditioning Idle Test Procedure specified in §86.165–12 of this part.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 511 of 768 * * * * *

(iii) For an air conditioning system to be eligible to generate credits in the 2014 through 2016 model years the increased CO 2 emissions as a result of the operation of that air conditioning system determined according to the Idle Test Procedure in §86.165–14 must be less than 21.3 grams per minute. In lieu of using 21.3 grams per minute, manufacturers may optionally use the procedures in paragraph (c)(5)(i v) of this section to determine an alternative
value.

* * * * *

(iv) For an air conditioning system to be eligible to generate credits in the 2017 and later model years, the increased CO 2 emissions as a result of the operation of that air conditioning system determined according to the Idle Test Procedure in §86.165–14 must be less than the value calculated by the following equation and rounded to the nearest tenth of gram per minute:

െ 20.5 ൌ ݈݀݋݄ݏ݁ݎ ݄ܶݐݏ݈݀݁ ܶ݁ܫ ሺ ݐ݈ܽܿ݉݁݊݌ݏ݅ܦ ൈ 1.58 ሻ

(A) If the increased CO 2 emissions determined from the Idle Test Procedure in §86.165– 14 is less than or equal to the Idle Test Thre shold, the total credit va lue for use in paragraph (c)(3) of this section shall be as determined in paragraph (c)(2) of this section.

(B) If the increased CO 2 emissions determined from the Idle Test Procedure in §86.165– 12 is greater than the Idle Test Threshold and less than the Idle Test Threshold plus 6.4, the total credit value for use in paragraph (c)(3) of this section shall be as determined according to the following formula:

ܶܥܸ ൌ ܶܥܸ ଵ ൈ ൤ 1 െ ൬ ܶܶܫ െ ܶܲܫ

6.4 ൰൨

Where:

TCV = The total credit value for use in paragraph (c)(3) of this section;

TCV 1 = The total credit value determined according to paragraph (c)(2) of this section;
and

ITP = the increased CO 2 emissions determined from the Idle Test Procedure in §86.165–

14.

ITT = the Idle Test Threshold from paragraph (c)(5)(iii) or (c)(5)(iv) of this section, whichever is applicable.

(v) Air conditioning systems with compressors that are solely powered by electricity shall submit Air Conditioning Idle Test Procedure data to be eligible to generate credits in the 2014DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 512 of 768 and later model years, but such systems are not required to meet a specific threshold to be eligible to generate such credits, as long as the engine remains off for a period of at least 2 minutes during the air conditioning on portion of the Idle Test Procedure in §86.165–12(d).

* * * * *

(d) Off-cycle credits. Manufacturers may generate credits for CO 2 -reducing technologies
where the CO 2 reduction benefit of the technology is not adequately captured on the Federal Test Procedure and/or the Highway Fuel Economy Test . These technologies must have a measurable, demonstrable, and verifiable real-world CO 2 reduction that occurs outside the conditions of the Federal Test Procedure and the Highway Fuel Economy Test. These optional credits are referred to as “off-cycle” credits. Off-cycle technologies used to generate emission credits are considered emission-related components subject to applicable requirements, and must be demonstrated to be
effective for the full useful life of the vehicle. Unless the manufacturer demonstrates that the technology is not subject to in-use deterioration, the manufacturer must account for the deterioration in their analysis. The manufacturer must use one of the three options specified in this paragraph (d) to determine the CO 2 gram per mile credit applicable to an off-cycle technology. Note that the option provided in paragraph (d)(1) of this section applies only to the 2017 and later model years. The manufacturer should notify EPA in their pre-model year report of their intention to generate any credits under this paragraph (d).

(1) Credit available for certain off-cycle technologies . The provisions of this paragraph (d)(1) are applicable only to 2017 and later model year vehicles.

(i) The manufacturer may generate a CO 2 gram/mile credit for certain technologies as specified in the following table, provided that each technology is applied to the minimum percentage of the manufacturer’s total U.S. production of passenger automobiles and light trucks specified in the table in each model year for whic h credit is claimed. Technology definitions are in paragraph (d)(1)(iv) of this section.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 513 of 768 Off-Cycle Technology Credit value: Passenger Automobiles (g/mi) Credit Value: Light Trucks (g/mi) Minimum percent of U.S. production Active aerodynamics 0.6 1.0 10 High efficiency exterior lighting 1.1 1.1 10

Engine heat recovery 0.7 per 100W of capacity 0.7 per 100W of capacity 10

Engine start-stop (idleoff) 2.9 4.5 10

Active transmission

warm-up 1.8 1.8 10

Active engine warmup 1.8 1.8 10

Electric heater circulation pump 1.0 1.5 n/a

Solar roof panels 3.0 3.0 n/a Thermal control ≤ 3.0 ≤ 4.3 n/a (A) Credits may also be accrued for thermal control technologies as defined in paragraph (d)(1)(iv) of this section in the amounts shown in the following table:

Thermal Control Technology Credit value: Passenger Automobiles (g/mi) Credit Value: Light Trucks (g/mi)

Glass or glazing ≤ 3.0 ≤ 4.3 Active seat ventilation 1.0 1.0 Solar reflective paint 0.3 0.4
Passive cabin ventilation 2.1 3.0

Active cabin ventilation 2.3 3.0

(B) The maximum credit allowed for thermal control technologies is limited to 3.0 g/mi for passenger automobiles and to 4.3 g/mi for light trucks. The maximum credit allowed for glass or glazing is limited to 3.0 g/mi for passenge r automobiles and to 4.3 g/mi for light trucks.

(C) Glass or glazing credits are calculate d using the following equation: 

### Credit ൌ െ ൥ܼ ൈ ෍ ܶ ௜ 

### ൈ ܩ ௜



### ܩ ௡

௜ୀଵ 

### ൩

Where:DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 514 of 768 Credit = the total glass or glazing credits, in grams per mile, for a vehicle, which may not exceed 3.0 g/mi for passenger automobiles or 4.3 g/mi for light trucks;

Z = 0.3 for passenger automobiles and 0.4 for light trucks;

G i = the measured glass area of window i , in square meters and rounded to the nearest tenth;

G = the total glass area of the vehicle, in square meters and rounded to the nearest tenth;

Ti = the estimated temperature reduction for the glass area of window i , determined using the following formula:

ܶ

௜ ൌ 0.3987 ൈ ሺ ܶݏݐ ௔௕௦௘ െܶݏݐ ௘௡௪ ሻ

Where:

Tts new = the total solar transmittance of the glass, measured according to ISO 13837, “Safety glazing materials – Meth od for determination of solar transmittance” (incorporated by reference; see §86.1).

Tts base = 62 for the windshield, side-front, side-rear, rear-quarter, and backlite locations,
and 40 for rooflite locations.

(ii) The maximum allowable decrease in the manufacturer’s combined passenger automobile and light truck fleet average CO 2 emissions attributable to use of the default credit values in paragraph (d)(1)(i) of this section is 10 grams per mile. If the total of the CO 2 g/mi credit values from the table in paragraph (d)(1)(i) of this section does not exceed 10 g/mi for any passenger automobile or light truck in a manufactu rer’s fleet, then the total off-cycle credits may be calculated according to paragraph (d)(5) of this section. If the total of the CO 2 g/mi credit values from the table in paragraph (d)(1)(i) of this section exceeds 10 g/mi for any passenger automobile or light truck in a manufacturer’s fleet, then the gram per mile decrease for the combined passenger automobile and light truck fleet must be determined according to paragraph (d)(1)(ii)(A) of this section to determine whet her the 10 g/mi limitation has been exceeded.

(A) Determine the gram per mile decrease for the combined passenger automobile and light truck fleet using th e following formula:

Decrease ൌ ݎܥ݁݀݅ݏݐ ൈ 1,000,000 ሾሺ Prod C ൈ 195,264 ሻ ൅ ሺ Prod T ൈ 225,865 ሻሿ

Where:DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 515 of 768 Credits = The total of passenger automobile and light truck credits, in Megagrams, determined according to paragraph (d)(5) of this section and limited to those credits accrued by using the default gram per m ile values in paragraph (d)(1)(i) of this section.

Prod C = The number of passenger automobiles produced by the manufacturer and
delivered for sale in the U.S.

Prod T = The number of light trucks produced by the manufacturer and delivered for sale
in the U.S.

(B) If the value determined in paragraph (d)(1) (ii)(A) of this section is greater than 10 grams per mile, the total credits, in Megagrams, that may be accrued by a manufacturer using the default gram per mile values in paragraph (d)(1)(i ) of this section shall be determined using the following formula:

Credit ሺMegagramsሻ ൌ ൣ10 ൈ ൫ ሺ Prod C ൈ 195,264 ሻ ൅ ሺ Prod T ൈ 225,865 ሻ ൯൧

1,000,000

Where:

Prod C = The number of passenger automobiles produced by the manufacturer and
delivered for sale in the U.S.

Prod T = The number of light trucks produced by the manufacturer and delivered for sale
in the U.S.

(C) If the value determined in paragraph (d)(1)(ii)(A) of this section is not greater than 10 grams per mile, then the credits that may be accrued by a manufacturer using the default gram per mile values in paragraph (d)(1)(i) of this s ection do not exceed the allowable limit, and total credits may be determined for each category of vehicles according to paragraph (d)(5) of this
section.

(D) If the value determined in paragraph (d)(1)(ii)(A) of this section is greater than 10 grams per mile, then the combined passenger automobile and light truck credits, in Megagrams, that may be accrued using the calculations in paragraph (d)(5) of this section must not exceed the value determined in paragraph (d )(1)(ii)(B) of this section. Th is limitation should generally be done by reducing the amount of credits attributable to the vehicle category that caused the limit to be exceeded such that the total value does not exceed the value determined in paragraph (d)(1)(ii)(B) of this section.

(iii) In lieu of using the default gram per mile values specified in paragraph (d)(1)(i) of this section for specific technologies, a manufactur er may determine an alternative value for any of the specified technologies. An alternative value must be determined using one of the methods specified in paragraph (d)(2) or (d)(3) of this section.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 516 of 768 (iv) Definitions for the purposes of this paragraph (d)(1) are as follows:

(A) Active aerodynamic improvements means technologies that are activated only at certain speeds to improve aerodynamic efficiency by a minimum of three percent, while preserving other vehicle attributes or functions.

(B) Electric heater circulation pump means a pump system installed in a stop-start equipped vehicle or in a hybrid electric vehicle or plug-in hybrid electric vehicle that continues to circulate hot coolant through the heater core when the engine is stopped during a stop-start event. This system must be calibrated to keep the engine off for 1 minute or more when the external ambient temperature is 30 deg F.

(C) High efficiency exterior lighting means a lighting technology that, when installed on the vehicle, is expected to reduce the total electri cal demand of the exterior lighting system by a minimum of 60 watts when compared to conventional lighting systems. To be eligible for this credit the high efficiency lighting must be installed in the following components: parking/position, front and rear turn signals, fr ont and rear side markers, stop/brake lights (including the center-mounted location), taillight s, backup/reverse lights, and license plate lighting.

(D) Engine start-stop means a technology which enables a vehicle to automatically turn off the engine when the vehicle comes to a rest and restart the engine when the driver applies pressure to the accelerator or releases the brake.

(E) Solar roof panels means the installation of solar panels on an electric vehicle or a plug-in hybrid electric vehicle such that the solar energy is used to provide energy to the electric drive system of the vehicle by charging the battery or directly providing power to the electric motor with the equivalent of at least 50 Watts of rated electricity output.

(F) Active transmission warmup means a system that uses waste heat from the exhaust system to warm the transmission fluid to an operating temperature range quickly using a heat exchanger in the exhaust system, increasing the overall transmission efficiency by reducing parasitic losses associated with the transmission fl uid, such as losses related to friction and fluid viscosity.

(G) Active engine warmup means a system using waste heat from the exhaust system to warm up targeted parts of the engine so that it reduces engine friction losses and enables the closed-loop fuel control more quickly. It would allow a faster transition from cold operation to warm operation, decreasing CO 2 emissions, and increasing fuel economy.

(H) Engine heat recovery means a system that captures heat that would otherwise be lost through the exhaust system or through the radiator and converting that heat to electrical energy that is used to meet the electrical requirements of the vehicle. Such a system must have a capacity of at least 100W to ach ieve 0.7 g/mi of credit. Ever y additional 100W of capacity will result in an additional 0.7 g/mi of credit.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 517 of 768 (I) Active seat ventilation means a device which draws air from the seating surface which is in contact with the occupant and exhausts it to a location away from the seat.

(J) Solar reflective paint means a vehicle paint or surface coating which reflects at least 65 percent of the impinging infrared solar energy, as determined using ASTM standards E903, E1918-06, or C1549-09. These ASTM standards are incorporated by reference; see §86.1.

(K) Passive cabin ventilation means ducts or devices which utilize convective airflow to
move heated air from the cabin interior to the exterior of the vehicle.

(L) Active cabin ventilation means devices which mechanically move heated air from the
cabin interior to the exterior of the vehicle.

(2) Technology demonstration using EPA 5-cycle methodology. To demonstrate an offcycle technology and to determine a CO 2 credit using the EPA 5-cycle methodology, the manufacturer shall determine the off-cycle city/highway combined carbon-related exhaust emissions benefit by using the EPA 5-cycle methodology described in 40 CFR Part 600. Testing shall be performed on a representative vehicle, selected using good engineering judgment, for each model type for which the credit is being demonstrated. The emission benefit of a technology is determined by testing both with and without the off-cycle technology operating. Multiple off-cycle technologies ma y be demonstrated on a test ve hicle. The manufacturer shall conduct the following steps and subm it all test data to the EPA.

(i) Testing without the off-cycle technology installed and/or operating. Determine carbon-related exhaust emissions over the FTP, the HFET, the US06, the SC03, and the cold temperature FTP test procedures according to the test procedure provisions specified in 40 CFR part 600 subpart B and using the calculation procedures specified in §600.113–08 of this chapter. Run each of these tests a minimum of three times without the off-cycle technology installed and operating and average the per phase (bag) results for each test procedure. Calculate the 5-cycle weighted city/highway combined carbon-related exhaust emissions from the averaged per phase results, where the 5-cycle city value is weighted 55% and the 5-cycle highway value is weighted 45%. The resulting combined city/highway value is the baseline 5-cycle carbon-related exhaust
emission value for the vehicle.

(ii)Testing with the off-cycle technology in stalled and/or operating. Determine carbonrelated exhaust emissions over the US06, the SC03, and the cold temperature FTP test procedures according to the test procedure provisions specified in 40 CFR part 600 subpart B and using the calculation procedures specified in §600.113–08 of this chapter. Run each of these tests a minimum of three times with the off-cycle technology installed and operating and average the per phase (bag) results for each test procedure. Calculate the 5-cycle weighted city/highway combined carbon-related exhaust emissions from the averaged per phase results, where the 5- cycle city value is weighted 55% and the 5-cycle highway value is weighted 44%. Use the averaged per phase results for the FTP and HFET determined in paragraph (d)(ii)(i)(A) of thisDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 518 of 768 section for operation without the off-cycle tec hnology in this calculation. The resulting combined city/highway value is the 5-cycle carbon-related exhaust emission value showing the off-cycle benefit of the technology but excluding any benefit of the technology on the FRP and

HFET.

(iii) Subtract the combined city/highway valu e determined in paragraph (d)(2)(i) of this
section from the value determined in paragraph (d)(2)(ii) of this section. The result is the offcycle benefit of the technology or technologies being evaluated. If this benefit is greater than or equal to three percent of the value determined in paragraph (d)(2)(i) of this section then the manufacturer may use this value, rounded to the nearest tenth of a gram per mile, to determine credits under paragraph (d)(4) of this section.

(iv) If the value calculated in paragraph (d)(i i)(i)(C) of this section is less than two percent of the value dete rmined in paragraph (d)(ii)(i)(A) of this section, then the manufacturer must repeat the testing required under paragraphs d)(ii)(i)(A) and (B) of this section, except instead of running each test three times they sh all run each test two additional times. The offcycle benefit of the technology or technologies being evaluated shall be calculated as in paragraph (d)(ii)(i)(C) of this section using all the tests conducted under paragraphs (d)(ii)(i)(A), (B), and (D) of this section. If the value calculated in paragraph (d)(ii)(i)(C) of this section is less than two percent of the value determined in pa ragraph (d)(ii)(i)(A) of this section, then the manufacturer must verify the emission reduction potential of the off-cycle technology or technologies using the [EPA Light-duty Simula tion Tool/Model], and if the results support a credit value that is less than two percent of the va lue determined in paragraph (d)(ii)(i)(A) of this section then the manufacturer may use the off-cycle benefit of the technology or technologies calculated as in paragraph (d)(ii)(i)(C) of th is section using all the tests conducted under paragraphs (d)(ii)(i)(A), (B), and (D) of this se ction, rounded to the nearest tenth of a gram per mile, to determine credits under pa ragraph (d)(4) of this section.

(3) Technology demonstration using alternative EPA-approved methodology. (i) This option may be used only with EPA approval, and the manufacturer must be able to justify to the Administrator why the 5-cycle option described in paragraph (d)(2) of this section insufficiently characterizes the effectiveness of the off-cy cle technology. In cases where the EPA 5-cycle methodology described in paragraph (d)(2) of this section cannot adequately measure the emission reduction attributable to an innovative off-cycle technology, the manufacturer may develop an alternative approach. Prior to a model year in which a manufacturer intends to seek these credits, the manufacturer must submit a deta iled analytical plan to EPA. The manufacturer may seek EPA input on the proposed methodology prior to conducting testing or analytical work, and EPA will provide input on the manufacturer’s analytical plan The alternative demonstration program must be approved in advance by the Administrator and should:

(A) Use modeling, on-road testing, on-road data collection, or other approved analytical or engineering methods;DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 519 of 768 (B) Be robust, verifiable, and capable of de monstrating the real-world emissions benefit with strong statistical significance;

(C) Result in a demonstration of baseline and controlled emissions over a wide range of driving conditions and number of vehicles such that issues of data uncertainty are minimized;

(D) Result in data on a model type basis unless the manufacturer demonstrates that another basis is appropriate and adequate.

(ii) Notice and opportunity for public comment. The Administrator will publish a notice of availability in the Federal Register notifying the public of a manufacturer's proposed alternative off-cycle credit calcu lation methodology. The notice will include details regarding the proposed methodology, but will not include any Co nfidential Business Information. The notice will include instructions on how to comment on the methodology. The Administrator will take public comments into consideration in the final de termination, and will notify the public of the final determination. Credits may not be accrued using an approved methodology until the first model year for which the Administra tor has issued a final approval.

(4) Review and approval process for off-cycle credits

.
(i) Initial steps required

.
(A) A manufacturer requesting off-cycle credits under the provisions of paragraph (d)(2) of this section must conduct the testing and/or simulation described in that paragraph.

(B) A manufacturer requesting off-cycle credits under the provisions of paragraph (d)(3) of this section must develop a methodology for demonstrating and determining the benefit of the off-cycle technology, and carry out any necessary testing and analysis required to support that methodology.

(C) A manufacturer requesting off-cycle credits under paragraph (d) of this section must conduct testing and/or prepare engineering analyses that demonstrate the in-use durability of the technology for the full useful life of the vehicle.

(ii) Data and information requirements . The manufacturer seeking off-cycle credits must submit an application for off-cycle credits determined under paragraphs (d)(2) and (d)(3) of this section. The application must contain the following:

(A) A detailed description of the off-cycle technology and how it functions to reduce CO 2 emissions under conditions not represented on the FTP and HFET.

(B) A list of the vehicle model(s) which will be equipped with the technology.

(C) A detailed description of the test vehicles selected and an engineering analysis that supports the selection of those vehicles for testing.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 520 of 768 (D) All testing and/or simulation data required under paragraph (d)(2) or (d)(3) of this section, as applicable, plus any other data the manufacturer has considered in the analysis.

(E) For credits under paragraph (d)(3) of this section, a complete description of the methodology used to estimate the off-cycle benefit of the technology and all supporting data, including vehicle testing and in-use activity data.

(F) An estimate of the off-cycle benefit by vehicle model and the fleetwide benefit based on projected sales of vehicle models equipped with the technology.

(G) An engineering analysis and/or component durability testing data or whole vehicle testing data demonstrating the in-use durability of the off- cycle technology components.

(iii) EPA review of the off-cycle credit application . Upon receipt of an application from a manufacturer, EPA will do the following:

(A) Review the application for completeness and notify the manufacturer within 30 days if additional information is required.

(B) Review the data and information provided in the application to determine if the application supports the level of credits estimated by the manufacturer.

(C) For credits under paragraph (d)(3) of this section, EPA will make the application available to the public for comment, as described in paragraph (d)(3)(ii) of this section, within 60 days of receiving a complete application. The pub lic review period will be specified as 30 days, during which time the public may submit comments. Manufacturers may submit a written rebuttal of comments for EPA consideration or may revise their application in response to comments. A revised application should be subm itted after the end of the public review period, and EPA will review the application as if it was a new application submitted under this paragraph (d)(4)(iii).

(iv) EPA decision

.
(A) For credits under paragraph (d)(2) of this section, EPA will notify the manufacturer of its decision within 60 days of receiving a complete application.

(B) For credits under paragraph (d)(3) of this section, EPA will notify the manufacturer of its decision after reviewing and evaluating the public comments.

(C) EPA will notify the manufacturer in writing of its decision to approve or deny the application, and if denied, EPA will pr ovide the reasons for the denial.

(5) Calculation of total off-cycle credits. Total off-cycle credits in Megagrams of CO 2 (rounded to the nearest whole number) shall be calculated separately for passenger automobiles and light trucks according to the following formula:DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 521 of 768 Total Credits (Megagrams) = (Credit × Production × VLM) ÷ 1,000,000

Where:

Credit = the credit value in grams per mile determined in paragraph (d)(1), (d)(2) or (d)(3) of this section.

Production = The total number of passenger automobiles or light trucks, whichever is applicable, produced with the off-cycle technology to which to the credit value determined in paragraph (d)(1), (d)(2), or (d)(3) of this section applies.

VLM = vehicle lifetime miles, which for passenger automobiles shall be 195,264 and for light trucks shall be 225,865.

(e) Credits for certain full-size pickup trucks . Full-size pickup trucks may be eligible for additional credits based on the implementation of hybrid technologies or on exhaust emission performance, as described in this paragraph (e). Credits may be generated under either paragraph (e)(2) or (e)(3) of this section for a qu alifying pickup truck, but not both.

(1) The following definitions apply for the purposes of this paragraph (e).

(i) Full size pickup truck means a light truck which has a passenger compartment and an open cargo box and which meets the following specifications:

(A) A minimum cargo bed width between the wh eelhouses of 48 inches, measured as the minimum lateral distance between the limiting interferences (pass-through) of the wheelhouses. The measurement shall exclude the transitional arc, local protrusions, and depressions or pockets, if present. An open cargo box means a vehicle where the cargo box does not have a permanent roof. Vehicles sold with detachable covers are considered “open” for the purposes of
these criteria.

(B) A minimum open cargo box length of 60 inches, where the length is defined by the lesser of the pickup bed length at the top of the body and the pickup bed length at the floor, where the length at the top of the body is define d as the longitudinal distance from the inside front of the pickup bed to the inside of the clos ed endgate as measured at the cargo floor surface along vehicle centerline, and the length at the floor is defined as the longitudinal distance from the inside front of the pickup bed to the inside of the closed endgate as measured at the cargo floor surface along vehicle centerline.

(C) A minimum towing capability of 5,000 pounds, where minimum towing capability is determined by subtracting the gross vehicle weight rating from the gross combined weight rating, or a minimum payload capability of 1,700 pounds, where minimum payload capability is determined by subtracting the curb weight from the gross vehicle weight rating.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 522 of 768 (ii) Mild hybrid gasoline-electric vehicle means a vehicle that has start/stop capability and regenerative braking capability, where the recaptured braking energy over the Federal Test Procedure is at least 15 percent but less than 75 percent of the total braking energy, where the percent of recaptured braking energy is measured and calculated according to §600.108(g).

(iii) Strong hybrid gasoline-electric vehicle means a vehicle that has start/stop capability and regenerative braking capability, where the recaptured braking energy over the Federal Test Procedure is at least 75 percent of the total braking energy, where the percent of recaptured braking energy is measured and calculated according to §600.108(g).

(2) Credits for implementation of gasoline-electric hybrid technology . Full size pickup trucks that implement hybrid gasoline-electric t echnologies may be eligible for an additional credit under this paragraph (e)(2). Pickup trucks using the credits under this paragraph (e)(2) may not use the credits described in paragraph (e)(3) of this section.

(i) Full size pickup trucks that are mild hybr id gasoline-electric vehicles and that are produced in the 2017 through 2021 model years are eligible for a credit of 10 grams/mile. To receive this credit, the manufacturer must produce a quantity of mild hybrid full size pickup trucks such that the proportion of production of such vehicles, when compared to the manufacturer’s total production of full size pickup tr ucks, is not less than the amount specified in the table below for each model year.

Model year Required minimum percent of full size pickup trucks
2017 30%
2018 40%
2019 55%
2020 70%
2021 80% (ii) Full size pickup trucks that are strong hybrid gasoline-electric vehicles and that are produced in the 2017 through 2025 model years are eligible for a credit of 20 grams/mile. To receive this credit, the manufacturer must produ ce a quantity of strong hybrid full size pickup trucks such that the proportion of production of such vehicles, when compared to the manufacturer’s total production of full size pickup trucks, is not less than 10 percent for each model year.

(3) Credits for emission reduction performance . Full size pickup trucks that achieve carbon-related exhaust emission values below the applicable target value determined in 86.1818- 12(c)(3) may be eligible for an additional credit. Pickup trucks using the credits under this paragraph (e)(3) may not use the credits described in paragraph (e)(2) of this section.

(i) Full size pickup trucks that achieve carbon-related exhaust emissions less than or equal to the applicable target value determined in 86.1818-12(c)(3) multiplied by 0.85 (roundedDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 523 of 768 to the nearest gram/mile) and greater than the applicable target value determined in 86.1818- 12(c)(3) multiplied by 0.80 (rounded to the nearest gram/mile) in a model year are eligible for a credit of 10 grams/mile. A pickup truck that qualifies for this credit in a model year may claim this credit for subsequent model years through the 2021 model year if the carbon-related exhaust emissions of that pickup truck do not increase relative to the emissions in the model year in which the pickup truck qualified for the credit. To qualify for this credit in each model year, the manufacturer must produce a quantity of full size pickup trucks that meet the emission requirements of this paragraph (e)(3)(i) such that the proportion of production of such vehicles, when compared to the manufacturer’s total producti on of full size pickup trucks, is not less than the amount specified in the table below for each model year.

Model year Required minimum percent of full size pickup trucks
2017 15%
2018 20%
2019 28%
2020 35%
2021 40% (ii) Full size pickup trucks that achieve car bon-related exhaust emissions less than or equal to the applicable target value determined in 86.1818-12(c)(3) multiplied by 0.80 (rounded to the nearest gram/mile) in a model year are eligible for a credit of 20 grams/mile. A pickup truck that qualifies for this credit in a model year may claim this credit for a maximum of five subsequent model years if the carbon-related exhaust emissions of that pickup truck do not increase relative to the emissions in the model year in which the pickup truck first qualified for the credit. This credit may not be claimed in any model year after 2025. To qualify for this credit, the manufacturer must produce a quantity of full size pickup trucks that meet the emission requirements of this paragraph (e)(3)(i) such that the proportion of production of such vehicles, when compared to the manufacturer’s total producti on of full size pickup trucks, is not less than 10 percent in each model year.

(4) Calculation of total full size pickup truck credits. Total credits in Megagrams of CO 2 (rounded to the nearest whole number) shall be cal culated for qualifying full size pickup trucks according to the following formula:

Total Credits (Megagrams) = ([(10 × Production 10 ) + (20 x Production 20 )] × 225,865) ÷ 1,000,000

Where:

Production 10 = The total number of full size pickup trucks produced with a credit value of 10 grams per mile from paragraphs (e)(2) and (e)(3).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 524 of 768 Production 20 = The total number of full size pickup trucks produced with a credit value of 20 grams per mile from paragraphs (e)(2) and (e)(3).

17. Section 86.1867-12 is amended by revising paragraph (a)(2)(i) to read as follows:

§ 86.1867-12 Optional early CO 2 credit programs. * * * * *

(i) Credits under this pathway shall be calculated according to the provisions of paragraph (a)(1) of this section, except credits may only be generated by vehicles sold in a model year in California and in states with a section 177 program in effect in that model year. For the purposes of this section, “section 177 program” m eans State regulations or other laws that apply to vehicle emissions from any of the follow ing categories of motor vehicles: Passenger automobiles, light-duty trucks up through 6,000 pounds GVWR, and medium-duty vehicles from 6,001 to 14,000 pounds GVWR, as these categories of motor vehicles are defined in the California Code of Regulations, Title 13, Division 3, Chapter 1, Article 1, Section 1900.

* * * * *

PART 600— FUEL ECONOMY AND GREENHOUSE GAS EXHAUST
EMISSIONS OF MOTOR VEHICLES

18. The authority citation for part 60 0 continues to read as follows:

Authority: 49 U.S.C. 32901—23919q, Pub. L. 109–58.

Subpart B—[Amended]

19. Section 600.113-12 is amended by revising paragraph (g)(2)(iv)(C), (j), (k), (l), and (m) to read as follows:

§ 600.113-12 Fuel economy, CO 2 emissions, and carbon-related exhaust emission calculations for FTP, HFET, US06, SC03 and cold temperature FTP tests.

* * * * *

(g) * * *

(2) * * *DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 525 of 768 (iv) * * *

(C) For the 2012 through 2016 model years only, manufacturers may use an assigned value of 0.010 g/mi for N 2 O FTP and HFET test values. This value is not required to be adjusted by a deterioration factor.

* * * * *

(j)(1) For methanol-fueled automobiles and automobiles designed to operate on mixtures of gasoline and methanol, the fuel economy in miles per gallon of methanol is to be calculated using the following equation:

mpg = (CWF × SG × 3781.8)/((CWF exHC × HC) + (0.429 × CO) + (0.273 × CO 2 ) + (0.375 × CH 3 OH) + (0.400 × HCHO))

Where:

CWF = Carbon weight fraction of the fuel as determined in paragraph (f)(2)(ii) of this section and rounded according to paragraph (g)(3) of this section.

SG = Specific gravity of the fuel as determin ed in paragraph (f)(2)(i) of this section and rounded according to paragraph (g)(3) of this section.

CWF exHC = Carbon weight fraction of exhaust hydrocarbons = CWF as determined in paragraph (f)(2)(ii) of this section and rounded according to paragraph (g)(3) of this section (for M100 fuel, CWF exHC = 0.866).

HC = Grams/mile HC as obtained in paragraph (g)(1) of this section.

CO = Grams/mile CO as obtained in paragraph (g)(1) of this section.

CO 2 = Grams/mile CO 2 as obtained in paragraph (g)(1) of this section.

CH 3 OH = Grams/mile CH 3 OH (methanol) as obtained in paragraph (g)(1) of this section.

HCHO = Grams/mile HCHO (formaldehyde) as obtained in paragraph (g)(1) of this
section.

(2)(i) For 2012 and later model year meth anol-fueled automob iles and automobiles designed to operate on mixtures of gasoline and methanol, the carbon-related exhaust emissions in grams per mile while operatin g on methanol is to be calculated using the following equation and rounded to the nearest 1 gram per mile:

CREE = (CWF exHC /0.273 × HC) + (1.571 × CO) + (1.374 × CH 3 OH) + (1.466 × HCHO)

+ CO 2DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 526 of 768 Where:

CREE means the carbon-related exhaust emission value as defined in §600.002.

CWF exHC = Carbon weight fraction of exhaust hydrocarbons = CWF as determined in paragraph (f)(2)(ii) of this section and rounded according to paragraph (g)(3) of this section (for M100 fuel, CWF exHC = 0.866).

HC = Grams/mile HC as obtained in paragraph (g)(2) of this section.

CO = Grams/mile CO as obtained in paragraph (g)(2) of this section.

CO 2 = Grams/mile CO 2 as obtained in paragraph (g)(2) of this section.

CH 3 OH = Grams/mile CH 3 OH (methanol) as obtained in paragraph (g)(2) of this section.

HCHO = Grams/mile HCHO (formaldehyde) as obtained in paragraph (g)(2) of this
section.

(ii) For manufacturers complying with the fleet averaging option for N 2 O and CH 4 as allowed under §86.1818 of this chapter, the carbon-related exhaust emissions in grams per mile for 2012 and later model year methanol-fueled automobiles and automobiles designed to operate on mixtures of gasoline and methanol while operating on methanol is to be calculated using the following equation and rounded to the nearest 1 gram per mile:

CREE = [(CWF exHC /0.273) × NMHC] + (1.571 × CO) + (1.374 × CH 3 OH) + (1.466 × HCHO) + CO 2 + (298 × N 2 O) + (25 × CH 4 )

Where:

CREE means the carbon-related exhaust emission value as defined in §600.002.

CWF exHC = Carbon weight fraction of exhaust hydrocarbons = CWF as determined in paragraph (f)(2)(ii) of this section and rounded according to paragraph (g)(3) of this section (for M100 fuel, CWF exHC = 0.866).

NMHC = Grams/mile HC as obtained in paragraph (g)(2) of this section.

CO = Grams/mile CO as obtained in paragraph (g)(2) of this section.

CO 2 = Grams/mile CO 2 as obtained in paragraph (g)(2) of this section.

CH 3 OH = Grams/mile CH 3 OH (methanol) as obtained in paragraph (g)(2) of this section.

HCHO = Grams/mile HCHO (formaldehyde) as obtained in paragraph (g)(2) of this
section.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 527 of 768 N 2 O = Grams/mile N 2 O as obtained in paragraph (g)(2) of this section.

CH 4 = Grams/mile CH 4 as obtained in paragraph (g)(2) of this section.

(k)(1) For automobiles fueled with natural gas and automobiles designed to operate on gasoline and natural gas, the fuel economy in miles per gallon of natural gas is to be calculated using the following equation:

Where:

mpg e = miles per gasoline gallon equivalent of natural gas.

CWF HC/NG = carbon weight fraction based on the hydrocarbon constituents in the natural gas fuel as obtained in paragraph (f)(3) of this section and rounded according to paragraph (g)(3)
of this section.

D NG = density of the natural gas fuel [grams/ft 3 at 68 °F (20 °C) and 760 mm Hg (101.3 kPa)] pressure as obtained in paragraph (g)(3) of this section.

CH 4 , NMHC, CO, and CO 2 = weighted mass exhaust emissions [grams/mile] for methane, non-methane HC, carbon monoxide, and carbon dioxide as obtained in paragraph (g)(2) of this section.

CWF NMHC = carbon weight fraction of the non-meth ane HC constituents in the fuel as determined from the speciated fuel composition pe r paragraph (f)(3) of this section and rounded according to paragraph (g)(3) of this section.

CO 2NG = grams of carbon dioxide in the natural gas fuel consumed per mile of travel.

CO 2NG = FC NG × D NG × WF CO2

Where:

= cubic feet of natural gas fuel consumed per mile

Where:

CWF NG = the carbon weight fraction of the natural gas fuel as calculated in paragraph (f)(3) of this section.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 528 of 768 WF CO2 = weight fraction carbon dioxide of the natural gas fuel calculated using the mole fractions and molecular weights of the natural gas fuel constituents per ASTM D 1945 (incorporated by reference in §600.011).

(2)(i) For automobiles fueled with natural gas and automobiles designed to operate on gasoline and natural gas, the carbon-related exhaust emissions in grams per mile while operating on natural gas is to be calculated for 2012 and later model year vehicl es using the following equation and rounded to the nearest 1 gram per mile:

CREE = 2.743 × CH 4 + CWF NMHC /0.273 × NMHC + 1.571 × CO + CO 2

Where:

CREE means the carbon-related exhaust emission value as defined in §600.002.

CH 4 = Grams/mile CH 4 as obtained in paragraph (g)(2) of this section.

NMHC = Grams/mile NMHC as obtained in paragraph (g)(2) of this section.

CO = Grams/mile CO as obtained in paragraph (g)(2) of this section.

CO 2 = Grams/mile CO 2 as obtained in paragraph (g)(2) of this section.

CWF NMHC = carbon weight fraction of the non-meth ane HC constituents in the fuel as determined from the speciated fuel composition pe r paragraph (f)(3) of this section and rounded according to paragraph (f)(3) of this section.

(ii) For manufacturers complying with the fleet averaging option for N 2 O and CH 4 as allowed under §86.1818 of this chapter, the carbon-related exhaust emissions in grams per mile for 2012 and later model year automobiles fueled with natural gas and au tomobiles designed to operate on gasoline and natural gas while operati ng on natural gas is to be calculated using the following equation and rounded to the nearest 1 gram per mile:

CREE = (25 × CH 4 ) + [(CWF NMHC /0.273) × NMHC] + (1.571 × CO) + CO 2 + (298 ×

N 2 O)

Where:

CREE means the carbon-related exhaust emission value as defined in §600.002.

CH 4 = Grams/mile CH 4 as obtained in paragraph (g)(2) of this section.

NMHC = Grams/mile NMHC as obtained in paragraph (g)(2) of this section.

CO = Grams/mile CO as obtained in paragraph (g)(2) of this section.

CO 2 = Grams/mile CO 2 as obtained in paragraph (g)(2) of this section.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 529 of 768 CWF NMHC = carbon weight fraction of the non-meth ane HC constituents in the fuel as determined from the speciated fuel composition pe r paragraph (f)(3) of this section and rounded according to paragraph (f)(3) of this section.

N 2 O = Grams/mile N 2 O as obtained in paragraph (g)(2) of this section.

(l)(1) For ethanol-fueled automobiles and automobiles designed to operate on mixtures of gasoline and ethanol, the fuel economy in miles per gallon of ethanol is to be calculated using the following equation:

mpg = (CWF × SG × 3781.8)/((CWF exHC × HC) + (0.429 × CO) + (0.273 × CO 2 ) + (0.375

× CH 3 OH) + (0.400 × HCHO) + (0.521 × C 2 H 5 OH) + (0.545 × C 2 H 4 O))

Where:

CWF = Carbon weight fraction of the fuel as determined in paragraph (f)(4) of this section and rounded according to paragraph (f)(3) of this section.

SG = Specific gravity of the fuel as determ ined in paragraph (f)(4) of this section and rounded according to paragraph (f)(3) of this section.

CWF exHC = Carbon weight fraction of exhaust hydrocarbons = CWF as determined in paragraph (f)(4) of this section and rounded according to paragraph (f)(3) of this section.

HC = Grams/mile HC as obtained in paragraph (g)(1) of this section.

CO = Grams/mile CO as obtained in paragraph (g)(1) of this section.

CO 2 = Grams/mile CO 2 as obtained in paragraph (g)(1) of this section.

CH 3 OH = Grams/mile CH 3 OH (methanol) as obtained in paragraph (g)(1) of this section.

HCHO = Grams/mile HCHO (formaldehyde) as obtained in paragraph (g)(1) of this
section.

C 2 H 5 OH = Grams/mile C 2 H 5 OH (ethanol) as obtained in paragraph (g)(1) of this section.

C 2 H 4 O = Grams/mile C 2 H 4 O (acetaldehyde) as obtained in paragraph (g)(1) of this
section.

(2)(i) For 2012 and later model year ethanol-fueled automobiles and automobiles designed to operate on mixtures of gasoline and ethanol, the carbon-related exhaust emissions in grams per mile while operating on ethanol is to be calculated using the following equation and rounded to the nearest 1 gram per mile:DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 530 of 768 CREE = (CWF exHC /0.273 × HC) + (1.571 × CO) + (1.374 × CH 3 OH) + (1.466 × HCHO) + (1.911 × C 2 H 5 OH) + (1.998 × C 2 H 4 O) + CO 2

Where:

CREE means the carbon-related exhaust emission value as defined in §600.002.

CWF exHC = Carbon weight fraction of exhaust hydrocarbons = CWF as determined in paragraph (f)(4) of this section and rounded according to paragraph (f)(3) of this section.

HC = Grams/mile HC as obtained in paragraph (g)(2) of this section.

CO = Grams/mile CO as obtained in paragraph (g)(2) of this section.

CO 2 = Grams/mile CO 2 as obtained in paragraph (g)(2) of this section.

CH 3 OH = Grams/mile CH 3 OH (methanol) as obtained in paragraph (g)(2) of this section.

HCHO = Grams/mile HCHO (formaldehyde) as obtained in paragraph (g)(2) of this
section.

C 2 H 5 OH = Grams/mile C 2 H 5 OH (ethanol) as obtained in paragraph (g)(2) of this section.

C 2 H 4 O = Grams/mile C 2 H 4 O (acetaldehyde) as obtained in paragraph (g)(2) of this
section.

(ii) For manufacturers complying with the fleet averaging option for N 2 O and CH 4 as allowed under §86.1818 of this chapter, the carbon-related exhaust emissions in grams per mile for 2012 and later model year ethanol-fueled automobiles and automobiles designed to operate on mixtures of gasoline and ethanol while opera ting on ethanol is to be calculated using the following equation and rounded to the nearest 1 gram per mile:

CREE = [(CWF exHC /0.273) × NMHC] + (1.571 × CO) + (1.374 × CH 3 OH) + (1.466 × HCHO) + (1.911 × C 2 H 5 OH) + (1.998 × C 2 H 4 O) + CO 2 + (298 × N 2 O) + (25 × CH 4 )

Where:

CREE means the carbon-related exhaust emission value as defined in §600.002.

CWF exHC = Carbon weight fraction of exhaust hydrocarbons = CWF as determined in paragraph (f)(4) of this section and rounded according to paragraph (f)(3) of this section.

NMHC = Grams/mile HC as obtained in paragraph (g)(2) of this section.

CO = Grams/mile CO as obtained in paragraph (g)(2) of this section.

CO 2 = Grams/mile CO 2 as obtained in paragraph (g)(2) of this section.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 531 of 768 CH 3 OH = Grams/mile CH 3 OH (methanol) as obtained in paragraph (g)(2) of this section.

HCHO = Grams/mile HCHO (formaldehyde) as obtained in paragraph (g)(2) of this
section.

C 2 H 5 OH = Grams/mile C 2 H 5 OH (ethanol) as obtained in paragraph (g)(2) of this section.

C 2 H 4 O = Grams/mile C 2 H 4 O (acetaldehyde) as obtained in paragraph (g)(2) of this
section.

N 2 O = Grams/mile N 2 O as obtained in paragraph (g)(2) of this section.

CH 4 = Grams/mile CH 4 as obtained in paragraph (g)(2) of this section.

(m) Manufacturers shall determine CO 2 emissions and carbon-related exhaust emissions for electric vehicles, fuel cell vehicles, and pl ug-in hybrid electric vehicles according to the provisions of this paragraph (m). Subject to the limitations on the number of vehicles produced and delivered for sale as described in §86.1866 of this chapter, the manufacturer may be allowed to use a value of 0 grams/mile to represent the emissions of fuel cell vehicles and the proportion of electric operation of a electric vehicles and pl ug-in hybrid electric vehicles that is derived from electricity that is generated from sources that are not onboard the vehicle, as described in paragraphs (m)(1) through (3) of this section. For purposes of labeling under this part, the CO 2 emissions for electric vehicles shall be 0 grams per mile. Similarly, for purposes of labeling under this part, the CO 2 emissions for plug-in hybrid electric vehicles shall be 0 grams per mile for the proportion of electric operation that is derived from electricity that is generated from
sources that are not onboard the vehicle.

(1) For 2012 and later model year electric vehicles, but not including fuel cell vehicles, the carbon-related exhaust emissions in grams pe r mile is to be calculated using the following equation and rounded to the nearest one gram per mile:

CREE = CREE UP − CREE GAS

Where:

CREE means the carbon-related exhaust emission value as defined in §600.002, which may be set equal to zero for eligible 2012 through 2025 model year electric vehicles for a certain number of vehicles produced and delivered for sale as described in §86.1866–12(a) of this chapter.

Where:DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 532 of 768 EC = The vehicle energy consumption in watt-hours per mile, determined according to procedures established by the Administrator under §600.111–08(f).

GRIDLOSS = 0.93 (to account for grid transmission losses).

AVGUSUP = 0.628 (the nationwide average el ectricity greenhouse gas emission rate at the powerplant, in grams per watt-hour).

TargetCO 2 = The CO 2 Target Value determined according to §86.1818 of this chapter for passenger automobiles and light trucks, respectively.

(2) For 2012 and later model year plug-in hybrid electric vehicles, the carbon-related exhaust emissions in grams per mile is to be cal culated according to the provisions of §600.116.

(3) For 2012 and later model year fuel cell vehicles, the carbon-related exhaust emissions in grams per mile shall be calcu lated using the method specified in paragraph (m)(1) of this section, except that CREE UP shall be determined according to procedures established by the Administrator under §600.111–08(f). As described in §86.1866 of this chapter the value of CREE may be set equal to zero for a certain number of 2012 through 2025 model year fuel cell
vehicles.

* * * * *

Section 600.116-12 is amended by revising paragraph (a) introductory text to read as
follows:

§ 600.116-12 Special procedures related to electric vehicles and plug-in hybrid electric vehicles. (a) Determine fuel economy values for elect ric vehicles as specified in §§600.210 and 600.311 using the procedures of SAE J1634 (incorporated by reference in §600.011), with the following clarifications and modifications:

* * * * *

20. Section 600.303-12 is amended by revising the introductory text, paragraphs (b) introductory text, (b)(6), an d (c) to read as follows:

§ 600.303-12 Fuel economy label—special requirements for flexible-fuel vehicles.

Fuel economy labels for flexible-fuel vehicles must meet the specifications described in §600.302, with the modifications described in this sectio n. This section describes how to label
flexible-fuel vehicles equipped with gasoline engines. If the vehicle has a diesel engine, all the references to “gas” or “gasoline” in this section are understood to refer to “diesel” or “dieselDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 533 of 768 fuel”, respectively. All values described in this secti on are based on gasoline operation, unless otherwise specifically noted.

* * * * *

(b) I nclude the following elements instead of the information identified in §600.302– 12(c)(1):

* * * * *

(6) Add the following statement after the statements described in §600.302–12(c)(2): “Values are based on gasoline and do not reflect performance and ratings based on E85.” Adjust this statement as appropriate for vehicles designed to operate on different fuels.

( c ) You may include the sub-heading “Driving Range” below the combined fuel economy value, with range bars below this sub-heading as follows:

( 1 ) Insert a horizontal range bar nominally 80 mm long to show how far the vehicle can drive from a full tank of gasoline. Include a vehicle logo at the right end of the range bar. Include the following left-justified expression inside th e range bar: “Gasoline: x miles”. Complete the expression by identifying the appropriate value for total driving range from §600.311.

( 2 ) Insert a second horizontal range bar as described in paragraph ( c )( 1 ) of this section
that shows how far the vehicle can drive from a full tank with the second fuel. Establish the length of the line based on the proportion of driving ranges for the different fuels. Identify the appropriate fuel in the range bar.

21. Section 600.510-12 is amended by reserving paragraph (b)(3)(iii), by adding paragraph (b)(4), and by revising paragraphs (b)(4), (c), (g)(1) introductory text, (g)(3), (h) introductory text, (j)(2)(v ii), and (k) to read as follows:

§ 600.510-12 Calculation of average fuel economy and average carbon-related exhaust emissions. * * * * *

(b) * * *

(3) * * *

(iii) [Reserved]

(4) Model year 2017 and later emergency vehicles may be excluded from the fleet average carbon-related exhaust emission calculations described in paragraph (j) of this section. The manufacturer should notify the Administrator that they are making such an election in theDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 534 of 768 model year reports required under §600.512 of this chapter. Such vehicles should be excluded from both the calculation of the fleet average standard for a manufacturer under 40 CFR 86.1818-12(c)(4) and from the calculation of the fleet average carbon-related exhaust emissions in paragraph (j) of this section.

(c)(1) Except as permitted in paragraph (d) of this section, the average fuel economy will be calculated individually for each category identified in paragraph (a)(1) of this section using the following equation:

Average MPG ൌ 1 ቂ 1 ܩܲܯ െ ሺ ܷܲ ൅ ܥܱ ൅ ܥܣ ሻ ቃ

Where:

Average MPG = the fleet average fuel economy for a category of vehicles;

MPG = the average fuel economy for a category of vehicles determined according to paragraph (c)(2) of this section;

AC = Air conditioning fuel economy credits for a category of vehicles, in gallons per mile, determined according to paragraph (c)(3)(i) of this section;

OC = Off-cycle technology fuel economy credits for a category of vehicles, in gallons per mile, determined according to paragraph (c)(3)(ii) of this section; and

PU = Pickup truck fuel economy credits for the light truck category, in gallons per mile, determined according to paragraph (c)(3)(iii) of this section.

(2) Divide the total production volume of that category of automobiles by a sum of terms, each of which corresponds to a model type within that category of automobiles and is a fraction determined by dividing the number of automobiles of that model type produced by the manufacturer in the model year by:

(i) For gasoline-fueled and diesel-fueled model types, the fuel economy calculated for that model type in accordance with paragraph (b)(2) of this section; or

(ii) For alcohol-fueled model types, the fuel economy value calculated for that model type in accordance with paragraph (b)(2) of this section divided by 0.15 and rounded to the nearest 0.1 mpg; or

(iii) For natural gas-fueled mo del types, the fuel economy value calculated for that model type in accordance with paragraph (b)(2) of this section divided by 0.15 and rounded to the nearest 0.1 mpg; orDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 535 of 768 (iv) For alcohol dual fuel model types, for model years 1993 through 2019, the harmonic average of the following two terms; the result rounded to the nearest 0.1 mpg:

(A) The combined model type fuel economy value for operation on gasoline or diesel fuel as determined in §600.208–12(b)(5)(i); and

(B) The combined model type fuel economy value for operation on alcohol fuel as determined in §600.208–12(b)(5)(ii) divided by 0.15 provided the requirements of paragraph (g) of this section are met; or

(v) For alcohol dual fuel model types, for model years after 2019, the combined model type fuel economy determined according to the following equation and rounded to the nearest 0.1 mpg: 

### ቆ ൌ ܩܲܯ ܨ

ܩܲܯ ஺ 

### ൅ ሺ 1െܨ ሻ

ܩܲܯ ீ 

### ቇ ିଵ

Where:

F = 0.00 unless otherwise approved by the Administrator according to the provisions of paragraph (k) of this section;

MPG A = The combined model type fuel economy for operation on alcohol fuel as determined in §600.208–12(b)(5)(ii) divided by 0.15 provided the requirements of paragraph (g) of this section are met; and

MPG G = The combined model type fuel economy for operation on gasoline or diesel fuel as determined in §600.208–12(b)(5)(i).

(vi) For natural gas dual fuel model types, for model years 1993 through 2019, the harmonic average of the following two terms; the result rounded to the nearest 0.1 mpg:

(A) The combined model type fuel economy value for operation on gasoline or diesel as determined in §600.208–12(b)(5)(i); and

(B) The combined model type fuel economy value for operation on natural gas as determined in §600.208–12(b)(5)(ii) divided by 0.15 provided the requirements of paragraph (g) of this section are met; or

(vii) For natural gas dual fuel model types, for model years after 2019, the combined model type fuel economy determined according to the following formula and rounded to the nearest 0.1 mpg:DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 536 of 768 

### ቆ ൌ ܩܲܯ ܨܷ

ܩܲܯ ீே஼ 

### ൅ ሺ 1 െ ܷܨ ሻ

ܩܲܯ ீ 

### ቇ ିଵ

Where:

MPG CNG = The combined model type fuel economy for operation on natural gas as determined in §600.208–12(b)(5)(ii) divided by 0.15 provided the requirements of paragraph (g) of this section are met; and

MPG G = The combined model type fuel economy for operation on gasoline or diesel fuel as determined in §600.208–12(b)(5)(i).

UF = A Utility Factor (UF) value selected from the following table based on the driving range of the vehicle while operating on natural gas. Determine the vehicle’s driving range in miles by multiplying the combined fuel economy as determin ed in §600.208–12(b)(5)(ii) by the vehicle’s usable fuel storage capacity (as define d at §600.002 and expressed in gasoline gallon equivalents), and rounding to the nearest 10 miles.

Driving Range (miles) UF

10 0.228
20 0.397
30 0.523
40 0.617
50 0.689
60 0.743
70 0.785
80 0.818
90 0.844
100 0.865
110 0.882
120 0.896
130 0.907
140 0.917
150 0.925
160 0.932
170 0.939
180 0.944
190 0.949
200 0.954
210 0.958
220 0.962
230 0.965
240 0.968DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 537 of 768 250 0.971
260 0.973
270 0.976
280 0.978
290 0.980
300 0.981 (3) Fuel consumption improvement . Calculate the separate air conditioning, off-cycle, and pickup truck fuel consumption improvement as follows:

(i) Air conditioning fuel consumption improvements are calculated separately for each category identified in paragra ph (a)(1) of this section using the following equation:

AC Credit ሺgal/miሻ ൌ ሺ ݎܥܥܣ݁݀݅ݐ ൈ 1,000,000 ሻ ሺ 8887 ൈ ݊݋݅ݐܿݑ݀݋ݎܲ ൈ ܯܮܸ ሻ

Where:

FE Credit = the fleet production-weighted total value of air conditioning efficiency credits for all air conditioning systems in the applicable fleet, expressed in gallons per mile;

ACCredit = the total of all air conditioning efficiency credits for the vehicle category, in megagrams, from 40 CFR 86.1866-12(c)(3);

VLM = vehicle lifetime miles, which for passenger automobiles shall be 195,264 and for light trucks shall be 225,865; and

Production = the total production volume for the category of vehicles (either passenger automobiles or light trucks).

(ii) Off-cycle technology fuel consumption improvements are calculated separately for each category identified in paragraph (a)(1) of this section using the following equation:

Off‐Cycle Credit ሺgal/miሻ ൌ ሺ ܱݎܥܥ݁݀݅ݐ ൈ 1,000,000 ሻ ሺ 8887 ൈ ݊݋݅ݐܿݑ݀݋ݎܲ ൈ ܯܮܸ ሻ

Where:

FE Credit = the fleet production-weighted total value of off-cycle technology credits for all off-cycle technologies in the applicab le fleet, expressed in gallons per mile;

OCCredit = the total of all off-cycle technology credits for the vehicle category, in megagrams, from 40 CFR 86.1866-12(d)(5);

VLM = vehicle lifetime miles, which for passenger automobiles shall be 195,264 and for light trucks shall be 225,865; andDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 538 of 768 Production = the total production volume for the category of vehicles (either passenger automobiles or light trucks).

(iii) Full size pickup truck fuel consumption improvements are calculated for the light truck category identified in paragraph (a)(1) of this section using the following equation:

Pickup Truck Credit ሺgal/miሻ ൌ ሺ ܷܲݎܥ݁݀݅ݐ ൈ 1,000,000 ሻ ሺ 8887 ൈ ݊݋݅ݐܿݑ݀݋ݎܲ ൈ ܯܮܸ ሻ

Where:

FE Credit = the fleet production-weighted total value of full size pickup truck credits for the light truck fleet, expressed in gallons per mile;

PUCredit = the total of all full size pickup truck credits, in megagrams, from 40 CFR 86.1866-12(e)(4); and

Production = the total production volume for the light truck category.

* * * * *

(g)(1) Dual fuel automobiles must provide equal or greater energy efficiency while operating on the alternative fuel as while operating on gasoline or diesel fuel to obtain the CAFE credit determined in paragraphs (c)(2)(iv) and (v) of this section or to obtain the carbon-related exhaust emissions credit determined in paragra phs (j)(2)(ii) and (iii) of this section. The following equation must hold true:

E alt /E pet ≥ 1

Where:

E alt = [FE alt /(NHV alt × D alt )] × 10 6 = energy efficiency while operating on alternative fuel
rounded to the nearest 0.01 miles/million BTU.

E pet = [FE pet /(NHV pet × D pet )] × 10 6 = energy efficiency while operating on gasoline or diesel (petroleum) fuel rounded to th e nearest 0.01 miles/million BTU.

FE alt is the fuel economy [miles/gallon for liqu id fuels or miles/100 standard cubic feet for gaseous fuels] while operated on the alternative fuel as determined in §600.113–12(a) and (b).

FE pet is the fuel economy [miles/gallon] while operated on petroleum fuel (gasoline or diesel) as determined in §600.113–12(a) and (b).

NHV alt is the net (lower) heating value [BTU/lb] of the alternative fuel.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 539 of 768 NHV pet is the net (lower) heating value [BTU/lb] of the petroleum fuel.

D alt is the density [lb/gallon for liquid fuels or lb/100 standard cubic feet for gaseous fuels] of the alternative fuel.

D pet is the density [lb/gallon] of the petroleum fuel.

* * * * *

(3) Dual fuel passenger automobiles manufactured during model years 1993 through 2019 must meet the minimum driving range requirements established by the Secretary of Transportation (49 CFR part 538) to obtain the CA FE credit determined in paragraphs (c)(2)(iv) and (v) of this section.

(h) For model years 1993 and later, and for each category of automobile identified in paragraph (a)(1) of this section, the maximum increase in average fuel economy determined in paragraph (c) of this section attributable to du al fuel automobiles, except where the alternative fuel is electricity, shall be as follows:

Model year Maximum increase (mpg)

1993–2014 1.2

2015 1.0

2016 0.8

2017 0.6

2018 0.4

2019 0.2

2020 and later 0.0

* * * * *

(j) * * *

(2) * * *DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 540 of 768 (vii) For natural gas dual fuel model types, for model years 2016 and later, the combined model type carbon-related exhaust emissions value determined according to the following formula and rounded to the nearest gram per mile:

ܥܴܧܧ ൌ ሾ ܥܴܧܧ ஼ேீ ൈ ܷܨ ሿ ൅ ሾ ܥܴܧܧ ீ஺ௌ ൈ ሺ 1 െ ܷܨ ሻሿ

Where:

CREE CNG = The combined model type carbon-related exhaust emissions value for operation on natural gas as determined in §600.208–12(b)(5)(ii); and

CREE GAS = The combined model type carbon-related exhaust emissions value for operation on gasoline or diesel fuel as determined in §600.208–12(b)(5)(i).

UF = A Utility Factor (UF) value selected from the following table based on the driving range of the vehicle while operating on natural gas. Determine the vehicle’s driving range in miles by multiplying the combined fuel economy as determin ed in §600.208–12(b)(5)(ii) by the vehicle’s usable fuel storage capacity (as define d at §600.002 and expressed in gasoline gallon equivalents), and rounding to the nearest 10 miles.

Driving Range (miles) UF

10 0.228
20 0.397
30 0.523
40 0.617
50 0.689
60 0.743
70 0.785
80 0.818
90 0.844
100 0.865
110 0.882
120 0.896
130 0.907
140 0.917
150 0.925
160 0.932
170 0.939
180 0.944
190 0.949
200 0.954
210 0.958DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 541 of 768 220 0.962
230 0.965
240 0.968
250 0.971
260 0.973
270 0.976
280 0.978
290 0.980
300 0.981

(k) Alternative in-use weighting factors for dual fuel model types . Using one of the methods in either paragraph (k)(1) or (2) of this section, manufacturers may request the use of alternative values for the weighting factor F in th e equations in paragraphs (c)(2)(v) and (j)(2)(vi) of this section. Unless otherwise approved by th e Administrator, the manufacturer must use the value of F that is in effect in paragraphs (c)(2)(v) and (j)(2)(vi) of this section.

(1) Upon written request from a manufactur er, the Administrator will determine and publish by written guidance an appropriate value of F for each requested alternative fuel based
on the Administrator's assessment of real-world use of the alternative fuel. Such published values would be available for any manufacturer to use. The Administrator will periodically update these values upon written request from a manufacturer.

(2) The manufacturer may optionally submit to the Administrator its own demonstration regarding the real-world use of th e alternative fuel in their vehicles and its own estimate of the appropriate value of F in the equations in paragr aphs (c)(2)(v) and (j)(2)(vi) of this section. Depending on the nature of the analytical appro ach, the manufacturer could provide estimates of F that are model type specific or that are generally applicable to the manufacturer's dual fuel fleet. The manufacturer's analysis could include use of data gathered from on-board sensors and computers, from dual fuel vehicles in fleets that are centrally fueled, or from other sources. The analysis must be based on sound statistical methodology and must account for analytical uncertainty. Any approval by the Administrator w ill pertain to the use of values of F for the model types specified by the manufacturer.

22. Section 600.514-12 is amended by revising paragraphs (b)(1)(v) and (b)(1)(vii) to read as follows:

§ 600.514-12 Reports to the Environmental Protection Agency.

* * * * *

(b) * * *DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 542 of 768 (1) * * *

(v) A description of the various credit, transfer and trading options that will be used to comply with each applicable standard category, including the amount of credit the manufacturer intends to generate for air conditioning leakage, air conditioning efficiency, off-cycle technology, advanced technology vehicles, hybrid or low emission full size pickup trucks, and various early credit programs;

(vii) A summary by model year (beginning with the 2009 model year) of the number of electric vehicles, fuel cell vehicles and plug-in hy brid vehicles using (or projected to use) the advanced technology vehicle credit and incentives program;

* * * * *DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 543 of 768 IV. NHTSA Proposed Rule for Passenger Car and Light Truck CAFE standards for Model Years 2017-2025 A. Executive Overview of NHTSA Proposed Rule 1. Introduction 2. Why does NHTSA set CAFE standards for passenger cars and light trucks? 3. Why is NHTSA proposing CAFE standards for MYs 2017-2025 now? a. President’s memorandum b. Benefits of continuing the National Program B. Background 1. Chronology of events since the MY 2012-2016 final rule was issued a. Manufacturers call for continuing National Program, and President’s Obama’s Memorandum b. Meetings and September 2010 Notice of Intent and Interim Joint Technical Assessment Report c. Meetings and November 2010 Supplemental Notice of Intent d. Meetings and more analysis; President Obama’s announcement of the forthcoming proposed standards for MYs 2017-2025; and second Supplemental Notice of Intent 2. How has NHTSA developed the proposed CAFE standards since the President’s announcement? C. Development and feasibility of the proposed standards 1. How was the baseline vehicle fleet developed? a. Why do the agencies establish a baseline and reference vehicle fleet? b. What data did the agencies use to construct the baseline, and how did they do so? c. How is the development of the baseline fleet for this rule different from the baseline fleet that NHTSA used for the MY 2012-2016 (May 2010) final rule? d. How is this baseline different quantitatively from the baseline that NHTSA used for the MY 2012-2016 (May 2010) final rule? e. How does manufacturer product plan data factor into the baseline used in this rule? f. What sensitivity analyses is NHTSA conducting on the baseline? g. How else is NHTSA considering looking at the baseline for the final rule? 2. How were the technology inputs developed? a. What technologies does NHTSA consider? b. How did NHTSA determine the costs and effectiveness of each of these technologies for use in its modeling analysis? c. How does NHTSA use these assumptions in its modeling analysis?DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 544 of 768 d. Where can readers find more detailed information about NHTSA’s technology analysis? 3. How did NHTSA develop its economic assumptions? a. Costs of Fuel Economy-Improving Technologies b. Potential Opportunity Costs of Improved Fuel Economy

c. The On-Road Fuel Economy “Gap” d. Fuel Prices and the Value of Saving Fuel e. Consumer Valuation of Fuel Economy and Payback Period f. Vehicle Survival and Use Assumptions g. Accounting for the Fuel Economy Rebound Effect h. Benefits From Increased Vehicle Use i. The Value of Increased Driving Range j. Added Costs From Congestion, Crashes and Noise k. Petroleum Consumption and Import Externalities i. Changes in Petroleum Imports ii. Benefits from Reducing U.S. Petroleum Imports l. Air Pollutant Emissions i. Changes in Criteria Air Pollutant Emissions ii. Reductions in CO 2 Emissions iii. Economic Value of Reductions in CO 2 Emissions m. Discounting Future Benefits and Costs n. Accounting for Uncertainty in Benefits and Costs o. Where can readers find more information about the economic assumptions? 4. How does NHTSA use the assumptions in its modeling analysis? a. How does the model operate? b. Has NHTSA considered other models? c. What changes has DOT made to the model? d. Does the model set the standards? e. How does NHTSA make the model available and transparent? D. Statutory Requirements 1. EPCA, as Amended by EISA a. Standard Setting i. Statutory Factors Considered in Determining the Achievable Level of Average Fuel Economy (1) Technological Feasibility (2) Economic Practicability (3) The Effect of Other Motor Vehicle Standards of the Government on Fuel Economy (4) The Need of the United States To Conserve Energy (a) Fuel Prices and the Value of Saving Fuel (b) Petroleum Consumption and Import Externalities (c) Air Pollutant EmissionsDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 545 of 768 ii. Other Factors Considered by NHTSA iii. Factors that NHTSA is Prohibited from Considering iv. Determining the Level of the Standards by Balancing
the Factors v. Other Standards (1) Minimum Domestic Passenger Car Standard (2) Alternative standards for certain manufacturers 2. Administrative Procedure Act 3. National Environmental Policy Act E. What are the proposed CAFE standards? 1. Form of the Standards 2. Passenger Car Standards for MYs 2017–2025 3. Minimum Domestic Passenger Car Standards 4. Light Truck Standards F. How do the proposed standards fulfill NHTSA’s statutory obligations? 1. What are NHTSA’s statutory obligations? 2. How did the agency balance the factors for this NPRM? G. Impacts of the Proposed CAFE Standards 1. How will these standards improve fuel economy and reduce GHG emissions for MY 2017–2025 vehicles? 2. How will these standards improve fleet-wide fuel economy and reduce GHG emissions beyond MY 2025? 3. How will these proposed standards impact non-GHG emissions and their associated effects? 4. What are the estimated costs and benefits of these proposed standards? 5. How would these proposed standards impact vehicle sales? 6. Potential Unquantified Consumer Welfare Impacts of the Proposed Standards 7. What other impacts (quantitative and unquantifiable) will these proposed standards have? H. Vehicle Classification I. Compliance and Enforcement 1. Overview 2. How does NHTSA determine compliance? a. Manufacturer Submission of Data and CAFE Testing by EPA b. NHTSA Then Analyzes EPA-Certified CAFE Values for Compliance 3. What compliance flexibilities are available under the CAFE program and how do manufacturers use them? a. Dual- and Alternative-Fueled Vehicles b. Credit Trading and Transfer c. Payment of Civil Penalties 4. What new incentives are being added to the CAFE program for MYs 2017-2025?DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 546 of 768 a. “Game Changing” technologies for full size pick-up trucks i. Pickup Truck Hybridization ii. Performance-based incentive for full-size pickups b. A/C efficiency-improving technologies i. What are the proposed testing approaches? ii. How are fuel consumption improvement values then estimated? c. Off-cycle technologies and adjustments 5. Other CAFE enforcement issues

a. Electronic Reporting
b. Reporting of how a vehicle is classified as a light truck

c. Base Tire Definition
d. Confirming Target and Fleet Standards J. Regulatory notices and analyses 1. Executive Order 12866, Executive Order 13563, and DOT Regulatory Policies and Procedures 2. National Environmental Policy Act 3. Regulatory Flexibility Act 4. Executive Order 13132 (Federalism) 5. Executive Order 12988 (Civil Justice Reform) 6. Unfunded Mandates Reform Act 7. Regulation Identifier Number 8. Executive Order 13045 9. National Technology Transfer and Advancement Act 10. Executive Order 13211 11. Department of Energy Review 12. Plain Language 13. Privacy Act

IV. NHTSA Proposed Rule for Passenger Car and Light Truck CAFE standards for Model Years 2017-2025

A. Executive Overview of NHTSA Proposed Rule

1. Introduction

The National Highway Traffic Safety Administration (NHTSA) is proposing Corporate Average Fuel Economy (CAFE) standards for passenger automobiles (passenger cars) and nonpassenger automobiles (light trucks) for model years (MY) 2017–2025. NHTSA’s proposed CAFE standards would require passenger cars and light trucks to meet an estimated combined average of 49.6 mpg in MY 2025. This represents an average annual increase of 4 percent from the estimated 34.4 mpg combined fuel economy level expected in MY 2016. Due to these proposed standards, we project total fuel savings of approximately 161 billion gallons over the lifetimes of the vehicles sold in model years 2017–2025, with corresponding net societalDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 547 of 768 benefits of over $335 billion using a 3 percent discount rate. 569

While NHTSA has been setting fuel economy standards since the 1970s, as discussed in Section I, NHTSA’s proposed MYs 2017–2025 CAFE standards are part of a National Program made up of complementary regulations by NHTSA and the Environmental Protection Agency. Today’s proposed standards build upon the success of the first phase of the National Program, finalized on May 7, 2010, in which NHTSA and EPA set coordinated CAFE and greenhouse gas (GHG) standards for MYs 2012-2016 passenger cars and light trucks. Because of the very direct and close relationship between improving fuel economy and reducing carbon dioxide (CO 2 ) tailpipe emissions, a large majority of the proj ected benefits are achieved jointly with EPA’s GHG rule, described in detail above in Sectio n III of this preamble. These proposed CAFE standards are consistent with the President’s National Fuel Efficiency Policy announcement of May 19, 2009, which called for harmonized rules for all automakers, instead of three overlapping and potentially inconsistent requirements from DOT, EPA, and the California Air Resources Board. And finally, the proposed CAFE standards and the analysis supporting them also respond to President’s Obama’s May 2010 memorandum requesting the agencies to develop, through notice and comment rulemaking, a coordinated National Program for passenger cars and light trucks for MYs 2017 to 2025.

2. Why does NHTSA set CAFE standards for passenger cars and light trucks?

Improving vehicle fuel economy has been long and widely recognized as one of the key ways of achieving energy independence, energy security, and a low carbon economy. 570

569 This value is based on what NHTSA refers to as “Reference Case” inputs, which are based on the assumptions that NHTSA has employed for its main analysis (as opposed to sensitivity analyses to examine the effect of variations in the assumptions on costs and benefits). Th e Reference Case inputs include fuel prices based on the AEO 2011 Reference Case, a 3 percent and a 7 percent discount rate, a 10 percent rebound effect, a value for the social cost of carbon (SCC) of $22/metric ton CO2 (in 2010, rising to $45/metric ton in 2050, at a 3 percent discount rate), etc. For a full listing of the Reference Case input assumptions, see Section IV.C.3 below.

570 Among the reports and studies noting this point are the following:

John Podesta, Todd Stern and Kim Batten, “Capturi ng the Energy Opportunity; Creating a Low- Carbon Economy,” Center for American Progress (November 2007), pp. 2, 6, 8, and 24–29, available at: http://www.americanprogress.org/issues/2007/11/pdf/en ergy_chapter.pdf (last accessed Sept. 24, 2011).

Sarah Ladislaw, Kathryn Zyla, Jonathan Pershing, Frank Verrastro, Jenna Goodward, David Pumphrey, and Britt Staley, “A Roadmap for a Secure, Low- Carbon Energy Economy; Balancing Energy Security and Climate Change,” World Resources Institute and Center for Strate gic and International Studies (January 2009), pp. 21–22; available at: http://pdf.wri.org/secure_low_carbon_ener gy_economy_roadmap.pdf (last accessed Sept. 24, 2011).

Alliance to Save Energy et al., “Reducing the Cost of Addressing Climate Change Through Energy Efficiency” (2009), available at: http://www.aceee.org/files/pdf/whitepaper/ReducingtheCostofAddressingClimateChang e_synopsis.pdf (last accessed Sept. 24, 2011).

John DeCicco and Freda Fung, “Global Warming on the Road; The Climate Impact of America’s Automobiles,” Environmental Defense (2006) pp. iv- vii; available at: http://www.edf.org/sites/default/file s/5301_Globalwarmingont heroad_0.pdf (last accessed Sept. 24, 2011).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 548 of 768 The significance accorded to improving fuel economy reflects several factors. Conserving energy, especially reducing the nation’s dependence on petroleum, benefits the U.S. in several ways. Improving energy efficiency has benefits for economic growth and the environment, as well as other benefits, such as reducing pollution and improving security of energy supply. More specifically, reducing total petroleum use decreases our economy’s vulnerability to oil price shocks. Reducing dependence on oil imports from regions with uncertain conditions enhances our energy security. Additionally, the emission of CO 2 from the tailpipes of cars and light trucks due to the combustion of petroleum is one of the largest sources of U.S. CO 2 emissions. 571 Using vehicle technology to improve fuel economy, an d thereby reducing tailpipe emissions of CO 2 , is one of the three main measures of reducing those tailpipe emissions of CO 2

. 572 The two other measures for reducing the tailpipe emissions of CO 2 are switching to vehicle fuels with lower carbon content and changing driver behavior, i.e. , inducing people to drive less.

Reducing petroleum consumption to improve energy security and save the U.S. money

In 1975, Congress enacted the Energy Policy and Conservation Act (EPCA), mandating that NHTSA establish and implement a regulatory program for motor vehicle fuel economy to meet the various facets of the need to conserve energy, including ones having energy independence and security, environmental, and foreign policy implications. The need to reduce energy consumption is even more crucial toda y than it was when EPCA was enacted. U.S. energy consumption has been outstripping U.S. energy production at an increasing rate. Improving our energy and national security by reducing our dependence on foreign oil has been a national objective since the first oil price shocks in the 1970s. Net petroleum imports accounted for approximately 51 percent of U.S. petroleum consumption in 2009. 573 World crude oil production is highly concentrated, exacerbating the risks of supply disruptions and price shocks as the recent unrest in North Africa and the Persian Gulf highlights. The export of U.S. assets for oil imports continues to be an important component of the historically unprecedented U.S. trade deficits. Transportation accounted for about 71 percent of U.S. petroleum consumption in 2009. 574 Light-duty vehicles account for about 60 percent of transportation oil use, which means that they alone account for about 40 percent of all U.S. oil consumption.

“Why is Fuel Economy Important?,” a Web page maintained by the Department of Energy and Environmental Protection Agency, available at http://w ww.fueleconomy.gov/feg/why.shtml (last accessed Sept. 24, 2011);

Robert Socolow, Roberta Hotinski, Jeffery B. Gree nblatt, and Stephen Pacala, “Solving The Climate Problem: Technologies Available to Curb CO2 Emissions,” Environment, volume 46, no. 10, 2004. pages 8–19, available at: http://www.princeton.edu/mae/people/ faculty/socolow/ENVIRONMENTDec2004issue.pdf (last accessed Sept. 24, 2011).

571 EPA Inventory of U.S. Greenhouse Gas Emissions a nd Sinks: 1990–2008 (April 2010), pp. ES–5, ES-8, and 2– 17. Available at http://www.epa.gov/climatechange/emi ssions/usgginv_archive.html (last accessed Sept. 25, 2011).

572 Podesta et al., p. 25; Ladislaw et al. p. 21; DeCicco et al. p. vii; “Reduce Climate Change, a Web page maintained by the Department of Energy and Envi ronmental Protection Agency at http:// www.fueleconomy.gov/feg/climate.shtml (last accessed Sept. 24, 2011).

573 Energy Information Administration, “How dependent are we on foreign oil?” Available at http://www.eia.gov/energy_in_brief/foreign_oil_de pendence.cfm (last accessed August 28, 2011).

574 Energy Information Administration, Annual Energy Outlook 2011, “Oil/Liquids.” Available at http://www.eia.gov/forecasts/aeo/MT_liquidfuels.cfm (last accessed August 28, 2011).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 549 of 768 Gasoline consumption in the U.S. has hist orically been relatively insensitive to fluctuations in both price and consumer income, and people in most parts of the country tend to view gasoline consumption as a non-discretionary expense. Thus, when gasoline’s share in consumer expenditures rises, the public experiences fiscal distress. Recent tight global oil markets led to prices over $100 per barrel, with gasoline reaching as high as $4 per gallon in many parts of the U.S., causing financial hardship for many families and businesses. This fiscal distress can, in some cases, have macroeconomic consequences for the economy at large.

Additionally, since U.S. oil production is only affected by fluctuations in prices over a period of years, any changes in petroleum consumption (as through increased fuel economy levels for the on-road fleet) largely flow into changes in the quantity of imports. Since petroleum imports account for about 2 percent of GDP, increases in oil imports can create a discernible fiscal drag. As a consequence, m easures that reduce petroleum consumption, like fuel economy standards, will directly benefit the balance-of-payments account, and strengthen the U.S. economy to some degree. And finally, U.S. foreign policy has been affected by decades by rising U.S. and world dependency on crude oil as the basis for modern transportation systems, although fuel economy standards have at best an indirect impact on U.S. foreign policy.

Reducing petroleum consumption to reduce climate change impacts

CO 2 is the natural by-product of the combustion of fuel to power motor vehicles. The more fuel-efficient a vehicle is, the less fuel it needs to burn to travel a given distance. The less fuel it burns, the less CO 2 it emits in traveling that distance. 575 Since the amount of CO 2 emissions is essentially constant per gallon combusted of a given type of fuel, the amount of fuel consumption per mile is directly related to the amount of CO 2 emissions per mile. Motor vehicles are the second largest GHG-emitting sector in the U.S. after electricity generation, and accounted for 27 percent of total U.S. GHG emissions in 2008. 576 Concentrations of greenhouse gases are at unprecedented levels compared to the recent and distant past, which means that fuel economy improvements to reduce those emissions are a crucial step toward addressing the risks of global climate change. These risks are well do cumented in Section III of this notice, and in NHTSA’s draft Environmental Impact Statem ent (DEIS) accompanying these proposed standards.

Fuel economy gains since 1975, due both to the standards and to market factors, have resulted in saving billions of barrels of oi l and avoiding billions of metric tons of CO 2 emissions. In December 2007, Congress enacted the Energy Independence and Security Act (EISA), amending EPCA to require substantial, continuing increases in fuel economy. NHTSA thus sets CAFE standards today under EPCA, as amended by EISA, in order to help the U.S. passenger car and light truck fleet save fuel to promote energy independence, energy security, and a low carbon economy.

575 Panel on Policy Implications of Greenhouse Warming, National Academy of Sciences, National Academy of Engineering, Institute of Medicine, “Policy Implications of Greenhouse Warming: Mitig ation, Adaptation, and the Science Base,” National Academ ies Press, 1992, at 287. Available at http://www.nap.edu/catalog.p hp?record_id=1605 (last accessed Sept. 25, 2011).

576 EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2008 (April 2010), p. 2-17. Available at http://www.epa.gov/climatechange/emissions/usgginv_a rchive.html (last accessed Sept. 25, 2011).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 550 of 768 3. Why is NHTSA proposing CAFE standards for MYs 2017-2025 now?

a. President’s memorandum

During the public comment period for the MY 2012-2016 proposed rulemaking, many stakeholders encouraged NHTSA and EPA to be gin working toward standards for MY 2017 and beyond in order to maintain a single nationwide program. After the publication of the final rule establishing MYs 2012-2016 CAFE and GHG standards, President Obama issued a Memorandum on May 21, 2010 requesting that NHTSA, on behalf of the Department of Transportation, and EPA work together to develop a national program for model years 2017-
2025. 577 Specifically, he requested that the agencies develop “ ...a coordinated national program under the CAA [Clean Air Act] and the EISA [Energy Independence and Security Act of 2007] to improve fuel efficiency and to reduce greenhouse gas em issions of passenge r cars and light-duty trucks of model years 2017-2025. ” The President recognized that our country could take a leadership role in addressing the global challenges of improving energy security and reducing greenhouse gas pollution, stating that “ America has the opportunity to lead the world in the development of a new generation of clean cars and trucks through innovative technologies and manufacturing that will spur economic growth and create high-quality domestic jobs, enhance our energy security, and improve our environment. ”

The Presidential Memorandum stated “ The program should also seek to achieve substantial annual progress in reducing trans portation sector greenhouse gas emissions and fossil fuel consumption, consistent with my Admi nistration's overall energy and climate security goals, through the increased domestic production and use of existing, advanced, and emerging technologies, and should strengthen the industry and enhance job creation in the United States. ” Among other things, the agencies were tasked with researching and then developing standards for MYs 2017 through 2025 that would be appropriate and consistent with EPA’s and NHTSA’s respective statutory authorities, in order to contin ue to guide the automotive sector along the road to reducing its fuel consumption and GHG emissions, thereby ensuring corresponding energy security and environmental benefits. Several major automobile manufacturers and CARB sent letters to EPA and NHTSA in support of a MYs 2 017 to 2025 rulemaking initiative as outlined in the President’s May 21, 2010 announcement. 578 The agencies began working immediately on the next phase of the National Program, work which has culminated in the standards proposed in this notice for MYs 2017-2025.

b. Benefits of continuing the National Program

577 The Presidential Memorandum is found at: http ://www.whitehouse.gov/the-press-office/presidentialmemorandum-regarding-fuel-efficiency-standards. For the reader’s reference, the President also requested the Administrators of EPA and NHTSA to issue joint rules und er the CAA and EISA to establish fuel efficiency and greenhouse gas emissions standards for commercial medium -and heavy-duty on-highway vehicles and work trucks beginning with the 2014 model year. The agencies recentl y promulgated final GHG and fuel efficiency standards for heavy duty vehicles and engines for MYs 2014-2018. 76 FR 57106 (September 15, 2011).

578 These commitment letters in response to the Ma y 21, 2010 Presidential Memorandum are available at http://www.epa.gov/otaq/climate/proposedregs.htm#cl; a nd http://www.nhtsa.gov/Laws+&+Regulations/CAFE+- +Fuel+Economy/Stakeholder+Commitment+Le tters (last accessed August 28, 2011).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 551 of 768 The National Program is both needed and possible because the relationship between improving fuel economy and reducing CO 2 tailpipe emissions is a very direct and close one. In the real world, there is a single pool of technologies for reducing fuel consumption and CO 2 emissions. Using these technologies in the way that minimizes fuel consumption also minimizes
CO 2 emissions. While there are emission control technologies that can capture or destroy the pollutants that are produced by imperfect combustion of fuel ( e.g. , carbon monoxide), there are at present no such technologies for CO 2 . In fact, the only way at present to reduce tailpipe emissions of CO 2 is by reducing fuel consumption. The National Program thus has dual benefits: it conserves energy by improving fuel economy, as required of NHTSA by EPCA and EISA; in the process, it necessarily reduces tailpipe CO 2 emissions consonant with EPA’s purposes and responsibilities under the Clean Air Act.

Additionally, by setting harmonized Federal standards to regulate both fuel economy and greenhouse gas emissions, the agencies are able to provide a predictable regulatory framework for the automotive industry while preserving the legal authorities of NHTSA, EPA, and the State of California. Consistent, harmonized, and streamlined requirements under the National Program, both for MYs 2012-2016 and for MYs 2017-2025, hold out the promise of continuing to deliver energy and environmental benefits, co st savings, and administrative efficiencies on a nationwide basis that might not be available under a less coordinated approach. The National Program makes it possible for the standards of two different Federal agencies and the standards of California and other “Section 177” states to act in a unified fashion in providing these benefits. A harmonized approach to regulating passenger car and light truck fuel economy and GHG emissions is critically important given the interdependent goals of addressing climate change and ensuring energy independence and security. Additionally, a harmonized approach would help to mitigate the cost to manufacturers of having to co mply with multiple sets of Federal and State standards.

One aspect of this phase of the National Program that is unique for NHTSA, however, is that the passenger car and light truck CAFE standards for MYs 2022-2025 must be conditional, while EPA’s standards for those model years will be legally binding when adopted in this round. EISA requires NHTSA to issue CAFE standards for “at least 1, but not more than 5, model years.” 579 To maintain the harmonization benefits of the National Program, NHTSA will therefore propose and adopt standards for all 9 model years from 2017-2025, but the last 4 years of standards will be conditional. The passenger car and light truck CAFE standards for MYs 2022-2025 will be determined with finality in a subsequent, de novo notice and comment rulemaking conducted in full compliance with EPCA/EISA and other applicable law – beyond simply reviewing the analysis and findings in the present rulemaking to see whether they are still accurate and applicable, and taking a fresh look at all relevant factors based on the best and most current information availabl e at that future time.

To facilitate that future effort, NHTSA and EPA will conduct a comprehensive mid-term evaluation. Up to date information will be de veloped and compiled for the evaluation, through a collaborative, robust, and transparent process, in cluding notice and comment. The agencies fully expect to conduct the mid-term evaluation in close coordination with the California Air Resources Board (CARB), consistent with the agencies’ commitment to maintaining a single

579 49 U.S.C. 32902(b)(3)(B).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 552 of 768 national framework for regulation of fuel economy and GHG emissions. 580 Prior to beginning NHTSA’s rulemaking process and EPA’s mid-term evaluation, the agencies will jointly prepare a draft Technical Assessment Report (TAR) to examine afresh the issues and, in doing so, conduct similar analyses and projections as those considered in the current rulemaking, including technical and other analyses and projections relevant to each agency’s authority to set standards as well as any relevant new issues that may present themselves. The agencies will provide an opportunity for public comment on the draft TAR, and appropriate peer review will be performed of underlying analyses in the TAR. The assumptions and modeling underlying the TAR will be available to the public, to the extent c onsistent with law. The draft TAR is expected to be issued no later than November 15, 2017. After the draft TAR and public comment, the agencies will consult and coordinate as NHTSA develops its NPRM. NHTSA will ensure that the subsequent final rule will be timed to provi de sufficient lead time for industry to make whatever changes to their products that the rulemaking analysis deems maximum feasible based on the new information available. At the very latest, NHTSA will complete its subsequent rulemaking on the standards with at least 18 months lead time as required by EPCA, 581 but additional lead time may be provided.

B. Background

1. Chronology of events since the MY 2012-2016 final rule was issued

a. Manufacturers call for continuing National Program, and President’s Obama’s Memorandum

As explained above, after many stakeholders (including many industry stakeholders) called on the agencies to continue a single National Program for MYs 2017 and beyond, President Obama issued the May 21, 2010 memorandum requesting the agencies to do just that for MYs 2017-2025. The President requested that the agencies

(a) Work with the State of California to develop by September 1, 2010, a technical assessment to inform the rulemaking process, reflecting input from an array of stakeholders on relevant factors, including vi able technologies, costs, benefits, lead time to develop and deploy new and emerging technologies, incentives and other flexibilities to encourage development and deployment of new and emerging technologies, impacts on jobs and the automotive manufacturing base in the United States, and infrastructure for advanced vehicle technologies; and

(b) Take all measures consistent with law to issue by September 30, 2010, a Notice of Intent to Issue a Proposed Rule th at announces plans for setting stringent fuel economy and greenhouse gas emissions standards for light-duty vehicles of model year

580 The agencies also fully expect that any adjustments to the standards as a result of the mid-term evaluation process from the levels enumerated in the current rulemaking will be made with the participation of CARB and in a manner that continues the harmonization of st ate and Federal vehicle standards.

581 49 U.S.C. 32902(a).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 553 of 768 2017 and beyond, incl uding plans for initiating joint rulemaking and gathering any additional information needed to support regulatory action. 582

The President stated that the Notice of Intent should describe the key elements of the program that the EPA and the NHTSA intend jointl y to propose, under their respective statutory authorities, including potential standards that could be practicably implemented nationally for the 2017–2025 model years and a schedule for setting t hose standards as expeditiously as possible, consistent with providing sufficient lead time to vehicle manufacturers. 583

The President’s memorandum thus began the process that led to today’s joint proposal; the agencies began working immediately on the next phase of the National Program.

b. Meetings and September 2010 Notice of Intent and Interim Joint Technical Assessment Report

During June through August 2010, NHTSA, EPA, and CARB held numerous meetings with a wide variety of stakeholders to gather input to consider in developing the Notice of Intent and technical assessment requested by the President, and to ensure that the agencies had available to them the most recent technical in formation. These stakeholders included the automobile original equipment manufacturers (OEMs), automotive suppliers, non-governmental organizations, states and state organizations, infrastructure providers, and labor unions. The agencies sought these stakeholders’ technical input and perspectives, consistent with the President’s request, on the key issues that should be considered in assessing a continued National Program to reduce greenhouse gas emissions and improve fuel economy for light-duty vehicles in model years 2017–2025.

In response to the agencies’ request, OEMs provided detailed and confidential input regarding several key areas including technology development, key regulatory design elements, infrastructure issues, perspective on the impacts on the U.S. manufacturing base and jobs, costs, and potential regulatory incentives and flexibilities. A common theme across the auto firms was that they are all heavily investing in advanced technologies including hybrids (HEVs), plug-in hybrid electric vehicles (PHEVs), electric vehicles (EVs), next generation internal combustion engines, and mass reduction technologies, and companies expect to increase their offerings and sales of these technologies significantly in the future. The companies generally stated, however, that the degree to which these advanced technol ogies will penetrate the U.S. market in the MYs 2017–2025 timeframe is dependent upon a number of challenges and factors, including future gasoline fuel prices, future decreases in battery costs, future regulatory fuel economy/GHG requirements, and government incentives for vehicle purchasers and owners such as the existing tax credits for EVs and PHEVs. EPA, NHTSA and CARB also met with a cross section of automotive suppliers as well as advanced technology infrastructure providers.

The agencies also requested input from numerous non-governmental organizations, including environmental organizations and labor organizations, and from state and local governments and their organizations. These stak eholders strongly supported the President’s call

582 75 Fed. Reg. 29399, 29400 (May 26, 2010).

583 Id

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Page 554 of 768 for continuing the National Program approach and setting new fuel economy and greenhouse gas standards for light-duty vehicles for the 2017–2025 model years.

The agencies released the NOI and an Interi m Joint Technical Assessment Report (TAR) at the end of September 2010, and posted both documents on their websites; 584 the NOI was later published in the Federal Register. 585 The NOI discussed the President’s memorandum; discussed stakeholder outreach conducted in developing the Interim Joint TAR; provided an overview of the agencies’ initial assessment of available technologies for improving fuel economy and reducing GHG emissions in MYs 2017-2025 and the costs, effectiveness, and lead time needed to implement those technologies based on our analysis of four different potential rates of increase in standard stringency (3%/year, 4%/year, 5%/year, and 6%/year) 586 and four “technology pathways” (one that focused on hybrids, one that focused on advanced gasoline vehicles and mass reduction, one that focused on both hybrids and advanced gasoline vehicles, and one that focused on electrifi cation technologies) 587 ; presented initial assessments of the range of costs and benefits of potential standards for MYs 2017-2025 based on that analysis; discussed the potential form of the future standards, potential flexib ilities, the need for a mid-term evaluation; and discussed next steps.

In addition to the analysis of the technology pathways and the different rates of standard stringency increase and the initial assessment of co sts and benefits mentioned above, the Interim Joint TAR also discussed in much more detail technical input received from stakeholders; an assessment of infrastructure needs to support the analyzed potential standards; incentives and flexibilities that might be part of the upcoming rulemaking; and other key factors in the rulemaking decision such as impacts on vehi cle sales, employment, and upstream GHG emissions. 588

The agencies opened rulemaking dockets and sought comment on the NOI and Interim Joint TAR, and explained that the agencies pla nned to issue a Supplemental Notice of Intent (SNOI) by November 30, 2010 that would describe plans for the National Program, including an

584 See http://www.nhtsa.gov/fuel-economy

585 75 FR 62739 (Oct. 13, 2010).

586 Specifically, the TAR analyzed four pot ential GHG targets, representing a 3, 4, 5, and 6 percent per year decrease in GHG levels from the MY 2016 fleet-wide average of 250 gram/mile (g/mi). For purposes of an initial assessment, this range represented a reasonably broad range of stringency increases for potential future GHG emissions standards, and was also consistent with the in creases suggested by CARB in its letter of commitment in response to the President’s memorandum.

587 For each of these levels of stringency, the agencies an alyzed these four “technologi cal pathways” as different ways by which they could be met. This approach was c hosen for the NOI and TAR to capture both the diversity in strategies expressed by OEMs in the stakeholder meeti ngs over Summer 2010, and uncertainties in forecasting 10– 15 years into the future the potential costs and use of vari ous advanced technologies in the light-duty vehicle fleet. Each of these technology pathways was defined to emphasi ze a different mix of advanced technologies, by assuming various degrees of penetration of advanced gasoline tech nologies, mass reduction, hybrids, plug-in hybrids, and electric vehicles. The NOI and TAR emphasized that th ese pathways were meant to represent ways that
manufacturers could respond to eventual standards, and did not represent ways that they must or necessarily will respond to those standards.

588 The TAR is available at http://www.nhtsa.gov/staticfiles/rulemaking/pdf/cafe/2017+CAFEGHG_Interim_TAR2.pdfDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 555 of 768 updated analysis of potential GHG and fuel economy standards for model years 2017–2025. Comments on the NOI and Interim Joint TAR would inform both that SNOI and the upcoming rulemaking.

c. Meetings and November 2010 Supplemental Notice of Intent

In response to our request for comment on the initial assessments contained in the September NOI and the TAR, the agencies received comments from more than 30 organizations and more than 100,000 individuals. In addition to the public comments, NHTSA, EPA, and CARB met individually with the ten largest automobile original equipment manufacturers (OEMs), 589 as well as environmental non-governmental organizations (NGOs), 590 and representatives of State and local governments. 591

The SNOI, issued at the end of November 2010, 592 represented a further step in the process to develop a proposed rulemaking to establish fuel economy and GHG standards for passenger cars and light trucks for MYs 2017–2025. The agencies explained that the SNOI was meant to aid the public’s understanding of some of the key issues facing the agencies in developing the upcoming rulemaking, by highlighting many of the key comments that the agencies received in response to the initial NOI an d to the Interim Joint TAR, and by discussing the agencies’ plans for some of the key technical work and analyses that will be undertaken in developing the upcoming proposed rulemaking. Although the original purpose of the November SNOI was to narrow the range of potential stringencies for the future proposed standards, as well as to reflect new technical data and information and, as appropriate, further analysis supplementing the Interim Joint TAR, the agencies explained that given the short amount of time between the issuance of the September NOI/TAR and the SNOI, the agencies were unable to complete several additional pieces of technical research in time for inclusion in analysis to support the SNOI, and that based on the stakeholder input between the NOI/TAR and the SNOI and on public comments, the agencies concluded that narrowing the range of potential stringencies would not be appropriate at that time, and that a more complete analysis will need to be done. The agencies stated that they would continue to conduct analyses for purposes of developing the proposal, as supported by comments to the NOI and TAR, and continue to work with California in our technical assessments of potential standards, and continue extensive dialogue with stakeholders.

As mentioned, the SNOI highlights many of the key comments that the agencies received in response to the NOI and Interim Joint TAR, concerning issues such as the benefits of continuing the National Program; appropriate levels for the standards for MYs 2017-2025; the

589 NHTSA, EPA, and CARB met with the representatives of the following OEMs: Chrysler, Ford, General Motors, Honda, Toyota, Hyundai, Nissan, BMW, Daimler, and Volkswagen.

590 NHTSA, EPA, and CARB met with representatives fr om several environmental NGOs, including the Natural Resources Defense Council, Union of Concerned Scientis ts, Sierra Club, National Wildlife Federation, ACEEE, Environment America, Safe Climate Campaign, and Environmental Defense Fund.

591 NHTSA, EPA and CARB met with representatives of th e National Association of Clean Air Agencies (NACAA)
and the Northeast States for Coordinated Air Use Mana gement (NESCAUM), and several representatives of individual State and local governments.

592 The SNOI was published in the Federal Register on December 8, 2010. See 75 FR 76337 (Dec. 8, 2010).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 556 of 768 availability, cost, and effectiveness of differ ent technologies; a mid-term evaluation; safety effects of the proposed standards; program de sign elements, credits and flexibilities, and treatment of upstream CO 2 emissions; and other areas. The SNOI does not present a comprehensive summary of comments received at that time, but by highlighting the key comments, it helps interested parties understand the landscape at that point in the rulemaking process. In the interest of brevity, we w ill not summarize those comments here, but we refer readers to the SNOI for more details. 593

d. Meetings and more analysis; President Obama’s announcement of the forthcoming proposed standards for MYs 2017-2025; and second Supplemental Notice of Intent

On July 29, 2011, President Obama announced with the support of thirteen major automakers for the next phase in the Administration’s national vehicle program, increasing fuel economy and reducing GHG emissions for passenger cars and light trucks built in MYs 2017-
2025. 594 The President was joined by Ford, GM, Chrysler, BMW, Honda, Hyundai, Jaguar/Land Rover, Kia, Mazda, Mitsubishi, Nissan, Toyota and Volvo, which together account for over 90 percent of all vehicles sold in the United Stat es. The California Air Resources Board (CARB), the United Auto Workers (UAW) and a number of environmental and consumer groups, also were integral to developing this agreement.

On the same day as the President’s announcement, the agencies released a second SNOI (published in the Federal Register on August 9, 2011) generally describing the joint proposal that the EPA and NHTSA expected to issue to establish the National Program for model years 2017– 2025, and which is set forth in this NPRM. Th e agencies explained that the proposal would be developed based on extensive technical analyses, an examination of the factors required under their respective statutes and discussions with and input from individual motor vehicle manufacturers and other stakeholders (including ce rtain members of the United States Congress). The input of stakeholders, which is encouraged by Executive Order 13563, has been invaluable to the agencies in developing today’s NPRM.

For background, as discussed above, after publishing the Supplemental NOI on December 8, 2010 (the December 8 SNOI), NHTSA, EPA and CARB continued studies and conducted more in-depth and comprehensive rulemaking analyses related to technology cost and effectiveness, technological feasibility, reas onable timing for manufacturers to implement technologies, and economic factors, and other re levant considerations. In addition to this ongoing and more in-depth work, the agencies continued meeting with stakeholders and received additional input and feedback to help inform th e rulemaking. Meetings were held with and relevant information was obtained from manufactu rers, manufacturer organizations, suppliers, a labor union, environmental groups, consumer inte rest groups, and investment organizations.

593 The SNOI is also available on NHTSA’s we bsite at http://www.nhtsa.gov/fuel-economy.

594 The President’s remarks are available at http://www.whitehouse.gov/the-press-office/2011/07/29/remarkspresident-fuel-efficiency-standards; s ee also http://www.nhtsa.gov/fuel-eco nomy for more information from the agency about the announcement.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 557 of 768 This section summarizes NHTSA stakeholde r engagement between December 2010 and July 29, 2011, the date on which President Obama announced the agencies’ plans for proposing standards for MY2017-2025, and the support of thirteen major automakers and other stakeholders for these plans. A complete list of stakeholder meeting dates and participants can be found in a memorandum to the docket. 595 Information that the agencies presented to stakeholders is posted in the docket and refere nced in multiple places in this section.

The agencies’ engagement with the large an d diverse group of stakeholders described above between December 2010 and July 29, 2011 shared the single aim of ensuring that the agencies possessed the most complete and comprehensive set of information possible to inform the proposed rulemaking.

Throughout this period, the stakeholders repeated many of the broad concerns and suggestions described in the TAR, NOI, and December 8 SNOI. For example, stakeholders uniformly expressed interest in maintaining a harmonized and coordinated national program that would be supported by CARB and allow auto make rs to build one fleet and preserve consumer choice. The stakeholders also raised concerns about potential stringency levels, consumer acceptance of some advanced technologies and th e potential structure of compliance flexibilities available under EPCA (as amended by EISA) an d the CAA. In addition, most of the stakeholders wanted to discuss issues concerni ng technology availability, cost and effectiveness and economic practicability. The auto manufacturers, in particular, sought to provide the agencies with a better understanding of their re spective strategies (and associated costs) for improving fuel economy while satisfying consumer demand in the coming years. Additionally, some stakeholders expressed concern about potential safety impacts associated with the standards, consumer costs and consumer acceptan ce, and potential disparate treatment of cars and trucks. Some stakeholders also stressed th e importance of investing in infrastructure to support more widespread deployment of alternativ e vehicles and fuels. Many stakeholders also asked the agencies to acknowledge prevailing economic uncertainties in developing proposed standards. In addition, many stakeholders shared on the number of years to be covered by the program and what they considered to be important features of a mid-term review of any standards set or proposed for MY 2022-2025. In all of these meetings, NHTSA and EPA sought additional data and information from the stakeholde rs that would allow them to refine their initial analyses and determine proposed standards that are consistent with the agencies’ respective statutory and regulatory requirements. The gene ral issues raised by those stakeholders are addressed in the sections of this NPRM discussing the topics to which the issues pertain ( e.g. , the form of the standards, technology cost and effec tiveness, safety impacts, impact on U.S. vehicle sales and other economic considerations, costs and benefits).

The first stage of the meetings occurred between December 2010 and June 20, 2011. These meetings covered topics that were generally similar to the meetings th at were held prior to the publication of the December 8 Supplemental NOI and that were summarized in the Supplemental NOI. The manufacturers provided the agencies with additional information related to their product plans for vehicle models an d fuel efficiency improving technologies and associated cost estimates. Detailed product plans generally extend only five or six model years into the future. Manufacturers also provided estimates of the amount of improvement in CAFE

595 [Memo Name], at NHTSA-2010-0131.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 558 of 768 and CO 2 emissions they could reasonably achieve in model MYs 2017-2025; feedback on the shape of MY 2012-2016 regulatory stringency cu rves and curve cut points, regulatory program flexibilities; recommendations for and on the structure of one or more mid-term reviews of the later model year standards; estimates of the cost, effectiveness and availability of some fuel efficiency improving technologies; and feedback on some of the cost and effectiveness assumptions used in the TAR analysis. In addition, manufacturers provided input on manufacturer experience with consumer acceptance of some advanced technologies and raised concerns over consumer acceptance if higher penetration of these technologies were needed in the future, consumer’s willingness to pay for improved fuel economy, and ideas on enablers and incentives that would increase consumer acceptance. Many manufacturers stated that technology is available to significantly improve fuel economy and CO 2 emissions; however, they maintained that the biggest challenges relate to the cost of the technologies, consumer willingness to pay and consumer acceptance.

During this first phase NHTSA and EPA conti nued to meet with other stakeholders, who provided their own perspectives on issues of importance to them. They also provided data to the extent available to them. Information obtained from stakeholders during this phase is contained in the docket.

The second stage of meetings occurred between June 21, 2011 and July 14, 2011, during which time EPA, NHTSA, CARB and several Wh ite House Offices kicked-off an intensive series of meetings, primarily with manufacturers, to share tentative regulatory concepts developed by the agencies, which included concept stringency curves and program flexibilities based on the analyses completed by the agencies as of June 21, 596 and requested feedback. 597 In particular, the agencies requested that the manufacturers provide detailed and reliable information on how they might comply with the concepts and, if they projected they could not comply, information supporting their belief that they would be unable to comply. Additionally, EPA and NHTSA sought detailed input from the manufacturers regarding potential changes to the concept stringency levels and program flexibilities available under EPA’s and NHTSA’s respective authority that might reduce the cost s of compliance. In addition, manufacturers provided input related to consumer acceptance and adoption of some advanced technologies and program costs based on their independent assessments or information previously submitted to the agencies.

In these second stage meetings, the agencies received considerable input from the manufacturers. The agencies carefully considered the manufacturer information along with information from the agencies’ independent analyses. The agencies used all available information to refine their assessment of the range of program concept stringencies and provisions that the agencies determined were consistent with their statutory mandates.

596 The agencies consider a range of standards that may satisfy applicable legal criteria, taking into account the complete record before them. The initia l concepts shared with stakeholders we re within the range the agencies were considering, based on the information then available to the agencies.

597 The agencies prepared materials prior to the meetings to present to the manufacturers which are included in a memo to docket. [add reference]DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 559 of 768 The third stage of meetings occurred between July 15, 2011 and July 28, 2011. During this time period the agencies continued to refine concept stringencies and compliance flexibilities based on further consideration of the informa tion available to them. They also met with manufacturers who expressed ongoing interest in engaging with the agencies. 598

Throughout all three stages, EPA and NHTSA continued to engage other stakeholders to ensure that the agencies were obtaining the most comprehensive and reliable information possible to guide the agencies in developing proposed standards for MY 2017-2025. Many of these stakeholders reiterated comments previous ly presented to the agencies. For instance, environmental organizations consistently stat ed that stringent standards are technically achievable and critical to important national interests, such as improving energy independence, reducing climate change, and enabling the domestic automobile industry to remain competitive in the global market. Labor interests stressed the need to carefully consider economic impacts and the opportunity to create and support new jobs, and consumer advocates emphasized the economic and practical benefits to consumers of improved fuel economy and the need to

preserve consumer c hoice. In addition, a number of stakehol ders stated that the standards under development should not have an adverse impact on safety.

On July 29, 2011, EPA and NHTSA the agencies issued a new SNOI with concept stringency curves and program provisions based on refined analyses and further consideration of the record before the agencies. The agencies have received letters of support for the concepts laid out in the SNOI from BMW, Chrysler, Ford , General Motors, Globa l Automakers, Honda, Hyundai, Jaguar Land Rover, Kia, Mazda, Mi tsubishi, Nissan, Toyota, Volvo and CARB. Numerous other stakeholders, including labor, environmental and consumer groups, have expressed their support for the agencies’ plans to move forward.

The agencies have considered all of this stakeholder input in developing this proposal, and look forward to continuing the productive dialogue through the comment period following this proposal.

2. How has NHTSA developed the proposed CAFE standards since the President’s announcement?

The CAFE standards proposed in this NPRM are based on much more analysis conducted by the agencies since July 29, including in-depth modeling analysis by DOT/NHTSA to support the proposed CAFE standards, and further refine ment of a number of our baseline, technology, and economic assumptions used to evaluate the proposed standards and their impacts. This NPRM, the draft joint TSD, and NHTSA’s PRIA and EPA’s DRIA contain much more information about the analysis underlying these proposed standards. The following sections provide the basis for NHTSA’s proposed passenger car and light truck CAFE standards for MYs 2017-2025, the standards themselves, the estimated impacts of the proposed standards, and much more information about the CAFE program relevant to the 2017-2025 timeframe.

C. Development and feasibility of the proposed standards

598 The agencies prepared materials prior to the meetings to present to the manufacturers which are included in a memo to docket. [add reference]DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 560 of 768 1. How was the baseline vehicle fleet developed?

a. Why do the agencies establish a baseline and reference vehicle fleet?

As also discussed in Section II.B above, in order to determine what levels of stringency are feasible in future model years, the agencies must project what vehicles will exist in those model years, and then evaluate what technologies can feasibly be applied to those vehicles in order to raise their fuel economy and lower their CO 2 emissions. The agencies therefore established a “baseline” vehicle fleet representing those vehicles, based on the best available transparent information. The agencies then de veloped a “reference” fleet, projecting the baseline fleet sales into MYs 2017-2025 and accounting for the effect that the MY 2012-2016 CAFE standards have on the baseline fleet. 599 This reference fleet is then used for comparisons of technologies’ incremental cost and effectiveness, as well as for other relevant comparisons in the rule.

b. What data did the agencies use to construct the baseline, and how did they do so?

As explained in the draft joint TSD, both agencies used a baseline vehicle fleet constructed beginning with EPA fuel economy ce rtification data for the 2008 model year, the most recent model year for which final data is currently available from manufacturers. These data were used as the source for MY 2008 production volumes and some vehicle engineering characteristics, such as fuel economy compliance ratings, engine sizes, numbers of cylinders, and transmission types.

For this NPRM, NHTSA and EPA chose again to use MY 2008 vehicle data as the basis of the baseline fleet. MY 2008 is now the most recent model year for which the industry had

599 In order to calculate the impacts of the proposed future GHG and CAFE standards, it is necessary to estimate the composition of the future vehicle fleet absent those proposed standards in order to conduct comparisons. The first step in this process was to develop a baseline fleet based on model year 2008 data. NHTSA and EPA create a baseline fleet in order to track the volumes and types of fuel economy-improving and CO 2 -reducing technologies which are already present in the existing vehicle fleet. The second step was to project the baseline fleet sales into MYs 2017-2025. This is called the reference fleet, and it represents the fleet volumes (but, until later steps, not levels of technology) that the NHTSA and EPA expect would exist in MYs 2017-2025 absent any change due to regulation in 2017-2025. After determining the reference fleet, a third step is needed to account for tech nologies (and corresponding increases in cost and reductions in fuel consumption and CO 2 emissions) that could be added to MY 2008- technology vehicles in the future, taking into previous ly-promulgated standards, and assuming MY 2016 standards are extended through MY2025. NHTSA accomplished this by using the Volpe model to add technologies to that
MY 2008-based market forecast such that each ma nufacturer’s car and truck CAFE and average CO 2 levels reflect baseline standards. The model’s output, the reference cas e (or adjusted baseline, or no-action alternative), is the light-duty fleet estimated to exist in MYs 2017-2025 wi thout new GHG/CAFE standard s covering MYs 2017-2025.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 561 of 768 what the agencies would consider to be “normal” sales. Complete MY 2009 data is now available for the industry, but the agencies believe that the model year was disrupted by the economic downturn and the bankruptcies of both General Motors and Chrysler. CAFE compliance data shows that there was a significant reduction in the number of vehicles sold by both companies and by the industry as a whole. These abnormalities led the agencies to conclude that MY 2009 data was likely not representative for projecting the future fleet for purposes of this analysis. While MY 2010 data is likely more representative for projecting the future fleet, it was not complete and available in time for it to be used for the NPRM analysis. Therefore, for purposes of the NPRM analysis, NHTSA and EPA chose to use MY 2008 CAFE compliance data for the baseline since it was the latest, most representative transparent data set that we had available. However, the agencies plan to use the MY 2010 data, if available, to develop an updated market forecast for use in the final rule. If and when the MY 2010 data becomes available, NHTSA will place a copy of this data into its rulemaking docket. Additionally, time and resources permitting, NHTSA may also docket an impacts analysis following the NPRM, to allow the public to see and comment on the difference in results using baselines developed using the MY 2010 data rather than the MY 2008 data.

Some information important for analyzing new CAFE standards is not contained in the EPA fuel economy certification data. EPA staff estimated vehicle wheelbase and track widths using data from Motortrend.com and Edmunds.com. This information is necessary for estimating vehicle footprint, which is required for the analysis of footprint-based standards. Considerable additional informa tion regarding vehicle engineering characteristics is also important for estimating the potential to add new technologies in response to new CAFE standards. In general, such information helps to avoid “adding” technologies to vehicles that already have the same or a more advanced technology. Examples include valvetrain configuration ( e.g., OHV, SOHC, DOHC), presence of cylinder deactivation, and fuel delivery ( e.g., MPFI, SIDI). To the extent that such engineering characteristics were not available in certification data, EPA staff relied on data published by Ward’s Automotive, supplementing this with information from Internet sites su ch as Motortrend.com and Edmunds.com. NHTSA staff also added some more detailed engineering characteristics ( e.g., type of variable valve timing) using data available fro m ALLDATA® Online. Combined with the certification data, all of this information yielded the MY 2008 baseline vehicle fleet.

After the baseline was created the next step was to project the sales volumes for 2017– 2025 model years. EPA used projected car and truck volumes for this period from Energy Information Administration’s (EIA’s) 2011 Interim Annual Energy Outlook (AEO). 600However, AEO projects sales only at the car and truck level, not at the manufacturer and modelspecific level, which are needed in order to estimate the effects new standards will have on individual manufacturers. Therefore, EPA purchased data from CSM–Worldwide and used their projections of the number of vehicles of each type predicted to be sold by manufacturers in

600 Department of Energy, Energy Information Administra tion, Annual Energy Outlook (AEO) 2011, Early Release.
Available at http://www.eia.gov/forecasts/aeo/. Both agencies regard AEO a credible source not only of such forecasts, but also of many underlying forecasts, including forecasts of the size of the future light vehicle market. The agencies used the early release version of AEO 2011 and confirmed later that changes reflected in the final version were insignificant with respect to the rela tive volumes of passenger cars and light trucks.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 562 of 768 2017–2025. This provided the year-by-year percentages of cars and trucks sold by each manufacturer as well as the percentages of each vehicle segment. Using these percentages normalized to the AEO projected volumes then pr ovided the manufacturer-specific market share and model-specific sales for model years 2011–2016.

The processes for constructing the MY 2008 baseline vehicle fleet and subsequently adjusting sales volumes to construct the MY 20 17–2025 baseline vehicle fleet are presented in detail in Chapter 1 of the Joint Technical Support Document accompanying today’s proposed rule.

NHTSA invites comment on the process used to develop the market forecast, and on whether the agencies should consider alternative approaches to producing a forecast at the level of detail we need for modeling. If commenters wish to offer alternatives, we ask that they address how manufacturers’ future fleets would be defined in terms of specific products, and the sales volumes and technical characteristics ( e.g. , fuel economy, technology content, vehicle weight, and other engineering characteristics) of those products. The agency also invites comment regarding what sensitivity analyses—if any—we should do related to the market forecast. For example, should the agency evaluate the extent to which its analysis is sensitive to projections of the size of the market, manufacturers’ respective market shares, the relative growth of different market segments, and or th e relative growth of the passenger car and light truck markets? If so, how would commenters suggest that we do that?

c. How is the development of the baseline fleet for this rule different from the baseline fleet that NHTSA used for the MY 2012-2016 (May 2010) final rule?

The development of the baseline fleet for this rulemaking utilizes the same procedures used in the development of the baseline fleet for the MY 2012-2016 rulemaking. Compared to that rulemaking, the change in the baseline is much less dramatic – the MY 2012-2016 rulemaking was the first rulemaking in which NHTSA did not use manufacturer product plan data to develop the baseline fleet, 601 so evaluating the difference between the baseline fleet used in the MY 2011 final rule and in the MY 2012-2016 rulemaking was informative at that time regarding some of the major impacts of that switch. In this proposal, we are using basically the same MY 2008 based file as the starting point in the MY 2012-2016 analysis, and simply using an updated AEO forecast and an updated CSM foreca st. Of those, most differences are in input assumptions rather than the basic approach and methodology. These include changes in various macroeconomic assumptions underlying the AEO and CSM forecasts and the use of results obtained by using DOE’s National Energy Modeling System (NEMS) to repeat the AEO 2011

601 The agencies’ reasons for not relying on product plan da ta for the development of the baseline fleet were discussed in the Regulatory Impact Analysis for the MYs 2012-2016 rulemaking and at 74 Fed. Reg. 49487-89. While a baseline developed using publicly and commer cially available sources has both advantages and disadvantages relative to a baseline developed using manuf acturers’ product plans, NHTSA currently concludes, as it did in the course of that prior rulemaking, that the ad vantages outweigh the disadvantages. Commenters generally supported the more transparent approach employed in the MYs 2012-2016 rulemaking.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 563 of 768 analysis without forcing increased passenger car volumes, and without assuming post-MY 2016 increases in the stringency of CAFE standards. 602

Another change in the baseline fleet from the last rulemaking involved our redefinition of the list of manufacturers to account for realignm ent and ownership changes taking place within the industry. The reported results supporting this rulemaking recognize that Volvo vehicles are no longer a part of Ford, but are reported as a separate company, Geely; that Saab vehicles are no longer part of GM, but are reported as part of Spyker which purchased Saab from GM in 2010; and that Chrysler, along with Ferrari and Maserati, are reported as Fiat.

In addition, low volume specialty manufacturers omitted from the analysis supporting the MY 2012-2016 rulemaking have been included in the analysis supporting this rulemaking. These include Aston Martin, Lotus, and Tesla.

d. How is this baseline different quantitatively from the baseline that NHTSA used for the MY 2012-2016 (May 2010) final rule?

As discussed above, the current baseline was developed from adjusted MY 2008 compliance data and covers MY 2017-2025. This section describes, for the reader’s comparison, some of the differences between the current baseline and the MY 2012-2016 CAFE rule baseline. This comparison provides a basis for understanding general characteristics and measures of the difference between the two baselines. The current baseline, while developed using the same methods as the baseline used for MY 2012-2016 rulemaking, reflects updates to the underlying commercially-available forecast of manufacturer and market segment shares of the future passenger car and light truck market. Again, the differences are in input assumptions rather than the basic approach and methodology. It also includes changes in various macroeconomic assumptions underlying the AEO forecasts and the use of the AEO Unforced Reference Case. Another change in the market input data from the last rulemaking involved our redefinition of the list of manufacturers to account for realignment taking place within the industry.

602 Similar to the analyses supporting the MYs 2012-2016 rulemaking, the agencies have used the Energy Information Administration’s (EIA’s) National Energy M odeling System (NEMS) to estimate the future relative market shares of passenger cars and light trucks. However, NEMS methodology includes shifting vehicle sales volume, starting after 2007, away from fleets with lower fuel economy (the light-truck fleet) towards vehicles with higher fuel economies (the passenger car fleet) in orde r to facilitate compliance with CAFE and GHG MYs 2012- 2016 standards. Because we use our market projection as a baseline relative to which we measure the effects of new standards, and we attempt to estimate the industry’s abil ity to comply with new standards without changing product mix, the Interim AEO 2011-projected shift in passenger car market share as a result of required fuel economy improvements creates a circularity. Therefore, for the cu rrent analysis, the agencies developed a new projection of passenger car and light truck sales shares by running scenarios from the Interim AEO 2011 reference case that first deactivate the above-mentioned sales-volume shifting me thodology and then hold po st-2017 CAFE standards constant at MY 2016 levels. Incorporating these change s reduced the projected passenger car share of the light vehicle market by an average of abou t 5 percent during 2017-2025. NHTSA and EPA refer to this as the “Unforced
Reference Case.”DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 564 of 768 Estimated vehicle sales:

The sales forecasts, based on the Energy Information Administration’s (EIA’s) Early Annual Energy Outlook for 2011 (Interim AEO 2011), used in the current baseline indicate that the total number of light vehicles expected to be sold during MYs 2012-2016 is 79 million, or about 15.8 million vehicles annually. NHTSA’s MY 2012-2016 final rule forecast, based on AEO 2010, of the total number of light vehicles likely to be sold during MY 2012 through MY 2016 was 80 million, or about 16 million vehicles annually. Light trucks are expected to make up 37 percent of the MY 2016 baseline market forecast in the current baseline, compared to 34 percent of the baseline market forecast in the MY 2012-2016 final rule. These changes in both the overall size of the light vehicle market and the relative market shares of passenger cars and light trucks reflect changes in the economic fo recast underlying AEO, changes in AEO’s forecast of future fuel prices, and use of the Unforced Reference Case.

Estimated manufacturer market shares:

These changes are reflected below in Table IV.C.1-1, which shows the agency’s sales forecasts for passenger cars and light trucks under the current baseline and the MY 2012-2016 final rule. There has been a general decrease in MY 2016 forecast overall sales (from AEO) and for all manufacturers (reflecting CSM’s forecast of manufacturers’ market shares), with the exception of Chrysler, when the current baseline is compared to that used in the MY 2012-2016 rulemaking. There were no significant shifts in manufacturers’ market shares between the two baselines. The effect of including the low volume specialty manufacturers and accounting for known corporate realignments in the current base line appear to be negligible. For individual manufacturers, there have been shifts in the shares of passenger car and light trucks, as would be expected given that the agency is relying on different underlying assumptions as discussed above and in Chapter 1 of the joint TSD.

TABLE IV.C.1–1—SALES FORECASTS [Production for U.S. sale in MY 2016, thousand units]

MY 2012-2016 Final Rule 603 Current Baseline Manufacturer Passenger Nonpassenger Passenger Nonpassenger

Aston Martin 1

BMW 423 171 383 184

Daimler 271 126 245 136 Fiat/Chrysler 400 462 392 498
Ford 1,559 911 1,393 930 Geely/Volvo 94 50

603 Again, Aston Martin, Alfa Romeo, Ferrari, Maserati, Lotus and Tesla were not included in the baseline of the MY 2012-2016 rulemaking; Volvo vehicles were reported unde r Ford and Saab vehicles were reported under GM; and Chrysler was reported as a separate company whereas now it is reported as part of Fiat and includes Alfa Romeo, Ferrari, and Maserati.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 565 of 768 General Motors 1,514 1,342 1,391 1,444

Honda 930 545 862 588 Hyundai 518 92 489 99

Kia 548 115 512 124

Lotus 0.3

Mazda 420 72 393 78

Mitsubishi 83 55 80 60

Nissan 946 381 869 410

Porsche 33 17 30 18 Spyker/Saab 18 2

Subaru 207 117 236 74

Suzuki 103 20 94 21

Tata 65 42 59 46

Tesla 27 Toyota 2,226 1,077 2,043 1,159 Volkswagen 583 124 528 134
Total 10,832 5,669 10,139 6,055

Estimated achieved fuel economy levels:

The current baseline market forecast shows industry-wide average fuel economy levels somewhat lower in MY 2016 than shown in the baseline market forecast for the MY 2012-2016 rulemaking. Under the current baseline, average fuel economy for MY 2016 is 27.0 mpg, versus 27.3 mpg under the baseline in the MY 2012-2016 rulemaking. The 0.3 mpg change relative to the MY 2012-2016 rulemaking’s baseline is the result of changes in the shares of passenger car and light trucks in the MY 2016 market as noted above – more light trucks generally equals lower average fuel economy – and not the result of changes in the capabilities of the car and truck fleets.

These differences are shown in greater detail below in Table III.A.3-5, which shows manufacturer-specific CAFE levels (not counting FFV credits that some manufacturers expect to earn) from the current baseline versus the MY 2012-2016 rulemaking baseline for passenger cars and light trucks. Table III.A.3-6 shows the combined averages of these planned CAFE levels in the respective baseline fleets. These tables demonstrate that there are no significant differences in CAFE for either passenger cars or light trucks at the manufacturer level between the current baseline and the MY 2012-2016 rulemaking baseline. The differences become more significant at the manufacturer level when combined CAFE levels are considered. Here we see a general decline in CAFE at the manufacturer level due to the increased share of light trucks. Because the agencies have, as for the MY 2012-2016 rulemaking, based this market forecast on vehicles in the MY 2008 fleet, these changes in CAFE levels reflect changes in vehicle mix, not changes in the fuel economy achieved by individual vehicle models.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 566 of 768 TABLE IV.C.1–2— CURRENT BASELINE CAFE LEVELS IN MY 2016 VERSUS MY 2012-2016 RULEMAKING CAFE LEVELS

MY 2012-2016 Final Rule

604 Current Baseline Manufacturer Passenger Non passenger Passenger Non passenger

Aston Martin 18.83

BMW 27.19 23.04 27.19 23.03

Daimler 25.25 21.12 25.50 21.13 Fiat/Chrysler 28.69 22.19 27.74 22.19

Ford 28.14 21.31 28.24 21.32 Geely/Volvo 25.89 21.08

General Motors 28.42 21.45 28.38 21.45

Honda 33.98 25.05 33.83 25.02 Hyundai 32.02 24.30 31.74 24.29

Kia 32.98 23.74 32.70 23.74

Lotus 29.66

Mazda 30.94 26.41 30.77 26.40

Mitsubishi 28.94 23.59 28.86 23.57

Nissan 32.04 22.11 31.98 22.10

Porsche 26.22 19.98 26.22 19.98 Spyker/Saab 26.54 19.79

Subaru 29.44 26.91 29.59 27.37

Suzuki 30.84 23.29 30.77 23.29

Tata 24.58 19.74 24.58 19.71

Tesla 244.00 Toyota 35.33 24.25 35.22 24.26 Volkswagen 28.99 20.23 28.90 20.24 Total/Average 30.73 22.59 30.65 22.56

TABLE IV.C.1–3— CURRENT BASELINE CAFE LEVELS IN MY 2016 VERSUS MY 2012-2016 RULE MAKING CAFE LEVELS (COMBINED)

Manufacturer MY 2012-2016 Final Current Baseline

604 Again, Aston Martin, Alfa Romeo, Ferrari, Maserati, Lotus and Tesla were not included in the baseline of the MY 2012-2016 rulemaking; Volvo vehicles were reported unde r Ford and Saab vehicles were reported under GM; and Chrysler was reported as a separate company whereas now it is reported as part of Fiat and includes Alfa Romeo, Ferrari, and Maserati.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 567 of 768 Rule 605

Aston Martin 18.83

BMW 25.85 25.68

Daimler 23.77 23.75 Fiat/Chrysler 24.79 24.33

Ford 25.17 24.99 Geely/Volvo 23.99
General
Motors 24.66 24.37

Honda 30.03 29.61 Hyundai 30.56 30.18

Kia 30.89 30.46

Lotus 29.66

Mazda 30.18 29.95

Mitsubishi 26.53 26.33

Nissan 28.38 27.97

Porsche 23.74 23.48 Spyker/Saab 25.70

Subaru 28.47 29.03

Suzuki 29.30 29.04

Tata 22.42 22.19

Tesla 244.00 Toyota 30.75 30.27 Volkswagen 26.94 26.60 Total/Average 27.34 27.03

e. How does manufacturer product plan data factor into the baseline used in this rule?

In December 2010, NHTSA requested that manufacturers provide information regarding future product plans, as well as informa tion regarding the context for those plans ( e.g. , estimates of future fuel prices), and estimates of the futu re availability, cost, and efficacy of fuel-saving technologies. 606 The purpose of this request was to acquire updated information regarding vehicle manufacturers’ future product plans to as sist the agency in assessing what corporate

605 Again, Aston Martin, Alfa Romeo, Ferrari, Maserati, Lotus and Tesla were not included in the baseline of the MY 2012-2016 rulemaking; Volvo vehicles were reported unde r Ford and Saab vehicles were reported under GM; and Chrysler was reported as a separate company whereas now it is reported as part of Fiat and includes Alfa Romeo, Ferrari, and Maserati.

606 75 FR 80430DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 568 of 768 CAFE standards should be established for passenger cars and light trucks manufactured in model years 2017 and beyond. The request was being issued in preparation for today’s joint NPRM.

NHTSA indicated that it requested information for MYs 2010-2025 primarily as a basis for subsequent discussions with individual manufacturers regarding their capabilities for the MYs 2017-2025 time frame as it worked to develop today’s NPRM. NHTSA indicated that the information received would supplement other information to be used by NHTSA to develop a realistic forecast of the vehicle market in MY 2017 and beyond, and to evaluate what technologies may feasibly be applied by manufacturers to achieve compliance with potential future standards. NHTSA further indicated that information regarding later model years could help the agency gain a better understanding of how manufacturers' plans through MY 2025 relate to their longer-term expectations regarding foreseeable regulatory requirements, market trends, and prospects for more advanced technologies.

NHTSA also indicated that it would consider information regarding the model years requested when considering manufacturers' planned schedules for redesigning and freshening their products, in order to examine how manufa cturers anticipate tying technology introduction to product design schedules. In addition, the agency requested information regarding manufacturers' estimates of the future vehicle population, and fuel economy improvements and incremental costs attributed to tech nologies reflected in those plans.

Given the importance that responses to this request for comment may have in informing NHTSA's proposed CAFE rulemaking, whether as pa rt of the basis for the standards or as an independent check on them, NHTSA requested that commenters fully respond to each question, particularly by providing information regarding the basis for technology costs and effectiveness estimates.

We have already noted that in past CAFE rulemakings, NHTSA used manufacturers’ product plans—and other information—to build market forecasts providing the foundation for the agency’s rulemaking analysis. This issue has been the subject of much debate over the past several rulemakings since NHTSA began actively working on CAFE again following the lifting of the appropriations riders in 2001. The agency continues to believe that these market forecasts reflected the most technically sound forecasts th e agency could have then developed for this purpose. Because the agency could not disclose confidential business information in manufacturers’ product plans, NHTSA provided summarized information, such as planned CAFE levels and technology ap plication rates, rather than the fuel economy levels and technology content of specific vehicle model types.

In preparing the MY 2012-2016 rule jointly with EPA, however, NHTSA revisited this practice, and concluded that for that rulemaking , it was important that all reviewers have equal access to all details of NHTSA’s analysis. NHTSA provided this level of transparency by releasing not only the agency’s CAFE modeling sy stem, but also by releasing all model inputs and outputs for the agency’s analysis, all of which are available on NHTSA’s website at http://www.nhtsa.gov/fuel-economy. Therefor e, NHTSA worked with EPA, as it did inpreparing for analysis supporting today’s proposal, to build a market forecast based on publiclyand commercially-available sources. NHTSA conti nues to believe that the potential technicalDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 569 of 768 benefits of relying on manufacturers’ plans for future products are outweighed by the transparency gained in building a market forecast that does not rely on confidential business information, but also continues to find product plan information to be an important point of reference for meetings with individual manufacturers. We seek comment on what value manufacturer product plan might have in the future, and whether it continues to be useful to request manufacturer product plans to inform rulemaking analyses, specifically the baseline forecast used in rulemaking analyses.

f. What sensitivity analyses is NHTSA conducting on the baseline?

As discussed below in Section IV.G, when evaluating the potential impacts of new CAFE standards, NHTSA considered the potential that, depending on how the cost and effectiveness of available technologies compare to the price of fuel, manufacturers would add more fuel-saving technology than might be required solely for purposes of complying with CAFE standards. This reflects that agency’s cons ideration that there could, in the future, be at least some market for fuel economy improvements beyond the required MY 2016 CAFE levels. In this sensitivity analysis, this causes some additional technol ogy to applied, more so under baseline standards than under the more stringent standards proposed today by the agency. Results of this sensitivity analysis are summa rized in Section IV.G and in NHTSA’s PRIA accompanying today’s notice.

g. How else is NHTSA considering looking at the baseline for the final rule?

Beyond the sensitivity analysis discussed above, NHTSA is also considering developing and using a vehicle choice model to estimate the extent to which sales volumes would shift in response to changes in vehicle prices and fuel economy levels. As discussed IV.C.4, the agency is currently sponsoring research directed toward developing such a model. If that effort is successful, the agency will consid er integrating the model into the CAFE modeling system and using the integrated system for future analysis of potential CAFE standards. If the agency does so, we expect that the vehicle choice model would impact estimated fleet composition not just under new CAFE standards, but also under baseline CAFE standards.

2. How were the technology inputs developed?

As discussed above in Section II.E, for developing the technology inputs for these proposed MYs 2017–2025 CAFE and GHG standards, the agencies primarily began with the technology inputs used in the MYs 2012-2016 CAFE final rule and in the2010 TAR.. The agencies have also updated information based on newly completed FEV tear down studies and new vehicle simulation work conducted by Ricardo Engineering, both of which were contracted by EPA. Additionally, the agencies relied on a model developed by Argonne National Laboratory to estimate hybrid, plug-in hybrid and electric vehicle battery costs. More detail is available regarding how the agencies developed the technology inputs for this proposal above in Section II.E, in Chapter 3 of the Joint TSD, and in Section V of NHTSA’s PRIA.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 570 of 768 a. What technologies does NHTSA consider?

Section II.E.1 above describes the fuel-saving technologies considered by the agencies that manufacturers could use to improve the fuel economy of their vehicles during MYs 2017- 2025. Many of the technologies described in this section are readily available, well known, and could be incorporated into vehicles once pro duction decisions are made. Other technologies, added for this rulemaking analysis, are considered that are not currently in production, but are beyond the initial research phase, under development and are expected to be in production in the next 5-10 years. As discussed, the technologies considered fall into five broad categories: engine technologies, transmission technologies, ve hicle technologies, electrification/accessory technologies, and hybrid technologies. Tabl e IV.C.2–1 below lists all the technologies considered and provides the abbreviations used for them in the CAFE model, 607 as well as their year of availability, which for purposes of NHTSA’s analysis means the first model year in the rulemaking period that the Volpe model is allowed to apply a technology to a manufacturer’s fleet. 608 Year of availability recogn izes that technologies must achieve a level of technical viability before they can be implemented in the Volpe model, and are thus a means of constraining technology use until such time as it is considered to be technologically feasible. For a more detailed description of each technology and their costs and effectiveness, we refer the reader to Chapter 3 of the Joint TSD and Section V of NHTSA’s PRIA.

T ABLE IV.C.2-1. L IST OF T ECHNOLOGIES IN NHTSA’ S A NALYSIS Technology Model abbreviation Year available
Low Friction Lubricants - Level 1 LUB1 2007 Engine Friction Reduction - Level 1 EFR1 2007 Low Friction Lubricants and Engine Friction Reduction - Level 2 LUB2_EFR2 2017

Variable Valve Timing (VVT) - Coupled Cam Phasing (CCP) on SOHC CCPS 2007

Discrete Variable Valve Lift (DVVL) on SOHC DVVLS 2007 Cylinder Deactivation on SOHC DEACS 2007 Variable Valve Timing (VVT) - Intake Cam Phasing (ICP) ICP 2007

Variable Valve Timing (VVT) - Dual Cam Phasing (DCP) DCP 2007

Discrete Variable Valve Lift (DVVL) on DOHC DVVLD 2007 Continuously Variable Valve Lift (CVVL) CVVL 2007 Cylinder Deactivation on DOHC DEACD 2007 Stoichiometric Gasoline Direct Injection (GDI) SGDI 2007 Cylinder Deactivation on OHV DEACO 2007
Variable Valve Actuation - CCP and DVVL on VVA 2007

607 The abbreviations are used in this section both for brevity and for the reader’s reference if they wish to refer to the expanded decision trees and the model input and out put sheets, which are available in Docket No. NHTSA– 2011–[xxxx] and on NHTSA’s website.

608 A date of 2012 means th e technology can be applied in all model years, while a date of 2020 means the technology can only be applied in model years 2020 through 2025.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 571 of 768 OHV Stoichiometric Gasoline Direct Injection (GDI) on OHV SGDIO 2007

Turbocharging and Downsizing - Level 1 (18 bar BMEP) - Small Displacement TRBDS1_SD 2007

Turbocharging and Downsizing - Level 1 (18 bar BMEP) - Medium Displacement TRBDS1_MD 2007

Turbocharging and Downsizing - Level 1 (18 bar BMEP) - Large Displacement TRBDS1_LD 2007

Turbocharging and Downsizing - Level 2 (24 bar BMEP) - Small Displacement TRBDS2_SD 2012

Turbocharging and Downsizing - Level 2 (24 bar BMEP) - Medium Displacement TRBDS2_MD 2012

Turbocharging and Downsizing - Level 2 (24 bar BMEP) - Large Displacement TRBDS2_LD 2012

Cooled Exhaust Gas Recirculation (EGR) - Level 1 (24 bar BMEP) - Small Displacement CEGR1_SD 2012

Cooled Exhaust Gas Recirculation (EGR) - Level 1 (24 bar BMEP) - Medium Displacement CEGR1_MD 2012

Cooled Exhaust Gas Recirculation (EGR) - Level 1 (24 bar BMEP) - Large Displacement CEGR1_LD 2012

Cooled Exhaust Gas Recirculation (EGR) - Level 2 (27 bar BMEP) - Small Displacement CEGR2_SD 2017

Cooled Exhaust Gas Recirculation (EGR) - Level 2 (27 bar BMEP) - Medium Displacement CEGR2_MD 2017

Cooled Exhaust Gas Recirculation (EGR) - Level 2 (27 bar BMEP) - Large Displacement CEGR2_LD 2017

Advanced Diesel - Small Displacement ADSL_SD 2017 Advanced Diesel - Medium Displacement ADSL_MD 2017 Advanced Diesel - Large Displacement ADSL_LD 2017 6-Speed Manual/Improved Internals 6MAN 2007 High Efficiency Gearbox (Manual) HETRANSM 2017 Improved Auto. Trans. Controls/Externals IATC 2007 6-Speed Trans with Improved Internals (Auto) NAUTO 2007 6-speed DCT DCT 2007 8-Speed Trans (Auto or DCT) 8SPD 2014 High Efficiency Gearbox (A uto or DCT) HETRANS 2017 Shift Optimizer SHFTOPT 2017 Electric Power Steering EPS 2007 Improved Accessories - Level 1 IACC1 2007 Improved Accessories - Level 2 (w/ Alternator Regen and 70% efficient alternator) IACC2 2014

12V Micro-Hybrid (Stop-Start) MHEV 2007 Strong Hybrid - Level 1 SHEV1 2012 Strong Hybrid - Level 2 SHEV2 2017DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 572 of 768 Plug-in Hybrid - 30 mi range PHEV1 2020 Electric Vehicle (Early Adopter) - 75 mile range EV1 2017 Electric Vehicle (Broad Market) - 150 mile range EV4 2017 Mass Reduction - Level 1 MR1 2007 Mass Reduction - Level 2 MR2 2007
Mass Reduction - Level 3 MR3 2007 Mass Reduction - Level 4 MR4 2011 Mass Reduction - Level 5 MR5 2016 Low Rolling Resistance Tires - Level 1 ROLL1 2007 Low Rolling Resistance Tires - Level 2 ROLL2 2017 Low Drag Brakes LDB 2007 Secondary Axle Disconnect SAX 2007 Aero Drag Reduction, Level 1 AERO1 2007 Aero Drag Reduction, Level 2 AERO2 2011

For purposes of this proposal and as discusse d in greater detail in the Joint TSD, NHTSA and EPA built upon the list of technologies used by agencies for the MYs 2017-2025 CAFE and GHG standards. NHTSA and EPA had additional t echnologies to the list that that the agencies expect to be in production during the MYs 2017-2025 timeframe. These new technologies included higher BMEP turbocharged and downsized engines, advanced diesel engines, higher efficiency transmissions, additional mass reduction levels, PHEVs, EVs, etc.

b. How did NHTSA determine the costs and effectiveness of each of these technologies for use in its modeling analysis?

Building on cost estimates developed for the MYs 2012-2016 CAFE and GHG final rule and the 2010 TAR, the agencies incorporated new cost and effectiveness estimates for the new technologies being considered and some of the technologies carried over from the MYs 2012- 2016 final rule and 2010 TAR. This joint work is reflected in Chapter 3 of the Joint TSD and in Section II of this preamble, as summarized be low. For more detailed information on the effectiveness and cost of fuel-saving technologies , please refer to Chapter 3 of the Joint TSD and Section V of NHTSA’s PRIA.

For this proposal the FEV tear down work was expanded to include an 8-speed DCT, a power-split hybrid, which was used to determine a P2 hybrid cost, and a mild hybrid with stopstart technology. Additionally, battery costs have been revised using Argonne National Laboratory’s battery cost model. The model developed by ANL allows users to estimate unique battery pack cost using user customized input se ts for different hybridization applications, such as strong hybrid, PHEV and EV. Based on staff input and public feedback EPA and NHTSA have modified how the indirect costs, using IC Ms, were derived and applied. The updates are discussed at length in Chapter 3 of the Joint TSD and in Chapter 5 of NHTSA’s PRIA.

Some of the effectiveness estimates for technologies applied in MYs 2012-2016 and 2010 TAR have remained the same. However, nearly all of the effectiveness estimates for carryover technologies have been updated based on a newer version of EPA’s lumped parameter model,DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 573 of 768 which was calibrated by the vehicle simulation work performed Ricardo Engineering. The Ricardo simulation study was also used to estimate the effectiveness for the technologies newly considered for this proposal like higher BMEP turbocharged and downsized engine, advanced transmission technologies and P2 Hybrids. While NHTSA and EPA apply technologies differently, the agencies have sought to ensure that the resultant effectiveness of applying technologies is consistent between the two agencies.

NHTSA notes that, in developing technology cost and effectiveness estimates, the agencies have made every effort to hold constant aspects of vehicle performance and utility typically valued by consumers, such as horsepower, carrying capacity, drivability, durability, noise, vibration and harshness (NVH) and towing and hauling capacity. For example, NHTSA includes in its analysis technology cost and effectiveness estimates that are specific to performance passenger cars ( i.e., sports cars), as compared to nonperformance passenger cars. NHTSA seeks comment on the extent to which commenters believe that the agencies have been successful in holding constant these elements of vehicle performance and utility in developing the technology cost and effectiveness estimates.

The agency notes that the technology costs included in this proposal take into account only those associated with the initial build of th e vehicle. Although comments were received to the MYs 2012-2016 rulemaking that suggested there could be additional maintenance required with some new technologies ( e.g. , turbocharging, hybrids, etc.), and that additional maintenance costs could occur as a result. The agency requests comments on this topic and will undertake a more detailed review of these po tential costs for the final rule.

The tables below provide examples of the incremental cost and effectiveness estimates employed by the agency in developing this final rule, according to the decision trees used in the Volpe modeling analysis. Thus, the effectiveness and cost estimates are not absolute to a single reference vehicle, but are incremental to the technology or technologies that precede it.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL574TABLEIV.C.2-2.TECHNOLOGYEFFECTIVENESSESTIMATESEMPLOYED IN THEVOLPEMODEL FORCERTAINTECHNOLOGIESSubcomp. CarCompact CarMidsizeCarLargeCarPerform.Subcomp. CarPerform.Compact CarPerform.MidsizeCarPerform. LargeCarMinivanLTSmallLTMidsizeLTLargeLTVEHICLE TECHNOLOGY INCREMENTAL FUEL CONSUMPTION REDUCTION (-%)Low frictionlubricants(level 1) 0.5 0.5 0.7 0.8 0.5 0.5 0.7 0.8 0.7 0.6 0.7 0.7Engine frictionreduction(level 1) 2.0 2.0 2.6 2.7 2.0 2.0 2.6 2.7 2.6 2.0 2.6 2.4VVT—Dualcam phasing(DCP) 2.0 2.0 2.5 2.7 2.0 2.0 2.5 2.7 2.6 2.0 2.6 2.4Discretevariable valvelift (DVVL) onDOHC 2.8 2.8 3.6 3.9 2.8 2.8 3.6 3.9 3.5 2.8 3.5 3.4Cylinderdeactivation onOHV 4.7 4.7 5.9 6.3 4.7 4.7 5.9 6.3 5.9 4.7 5.9 5.5Stoichiometricgasoline directinjection 1.6 1.6 1.5 1.5 1.6 1.6 1.5 1.5 1.5 1.6 1.5 1.5Turbocharginganddownsizing(level 1) 7.2 7.2 8.3 7.8 7.2 6.7 7.5 7.87.9 7.1 7.9 7.3Turbocharginganddownsizing(level 2) 2.9 2.9 3.5 3.7 2.9 2.9 3.5 3.7 3.4 2.9 3.4 3.4Cooled exhaustgas 3.6 3.6 3.5 3.5 3.6 3.6 3.5 3.5 3.6 3.6 3.6 3.6DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL575recirculation(EGR) – (level1)Cooled exhaustgasrecirculation(EGR) – (level2) 1.0 1.0 1.4 1.4 1.0 1.0 1.4 1.4 1.1 1.0 1.1 1.2AdvancedDiesel 5.5 5.5 2.8 2.9 5.5 5.5 2.8 2.9 3.4 5.3 3.4 3.56-speed auto.trans. withimprovedinternals 1.9 1.9 2.0 2.0 1.9 1.9 2.0 2.0 2.0 2.0 2.0 2.16-speed DCT 4.0 4.0 4.1 3.8 4.0 3.4 4.1 3.8 n/a 3.8 n/a n/aHighEfficiencyGearbox 2.2 2.2 2.7 2.6 2.2 2.2 2.7 2.6 3.1 2.5 3.1 3.7ShiftOptimizer 3.3 3.3 4.1 4.3 3.3 3.3 4.1 4.3 4.1 3.3 4.1 3.9Electric powersteering 1.5 1.5 1.3 1.1 1.5 1.5 1.3 1.1 1.0 1.2 1.0 0.812V microhybrid1.7 1.7 2.1 2.2 1.7 1.7 2.1 2.2 2.09 1.8 2.1 2.1Strong Hybrid(level 2) 10.1 10.1 6.5 6.9 10.1 9.7 6.5 6.8 5.2 10.0 8.2 7.3Plug-in Hybrid40.7 40.740.7 40.7 40.7 40.7 40.740.7 40.7 40.7 40.7 40.7ElectricVehicle (EarlyAdopter) 68.5 68.5 68.5 68.5 68.5 68.5 68.5 68.5 68.5 68.5 68.5 68.5Low RollingResistanceTires (level 1) 1.9 1.9 1.9 1.9 1.9 1.9 1.9 1.9 1.9 1.9 1.9 1.9Low RollingResistance 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL576Tires (level 2)Aero DragReduction(level 1) 2.3 2.3 2.3 2.3 2.3 2.3 2.3 2.3 2.3 2.3 2.3 2.3Aero DragReduction(level 2) 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5TABLEIV.C.2-3.TECHNOLOGYCOSTESTIMATESEMPLOYED IN THEVOLPEMODEL FORCERTAINTECHNOLOGIESSubcomp. CarCompact CarMidsizeCarLargeCarPerform.Subcomp. CarPerform.Compact CarPerform.MidsizeCarPerform. LargeCarMinivanLTSmallLTMidsizeLTLargeLTVEHICLE TECHNOLOGY ICM COSTS PER VEHICLE ($)Nominalbaseline engine(for costpurposes) Inline 4 Inline 4 Inline 4 V6 Inline 4 V6 V6 V8 V6 Inline 4 V6 V8Low frictionlubricants(level 1) 16 16 16 24 16 24 24 32 24 16 24 32Engine frictionreduction(level 1) 60 60 60 90 60 90 90 120 90 60 90 120VVT—Dualcam phasing(DCP) 44 44 44 88 44 88 88 88 88 44 88 88Discretevariable valvelift (DVVL) onDOHC 160 160 160 240 160 240 240 320 240 160 240 320Cylinderdeactivation onOHV 204 204 204 204 204 204 204 204 204 204 204 204DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL577Stoichiometricgasoline directinjection 268 268 268 402 268 402 5402 536 402 268 402 536Turbocharginganddownsizing(level 1) 490 490 490 20 490 20 20 639 20 490 20 639Turbocharginganddownsizing(level 2) 26 26 26 260 26 260 260 439 260 26 260 439Cooled exhaustgasrecirculation(EGR) – (level1) 303 303 303 303 303 303 303 303 303 303 303 303Cooled exhaustgasrecirculation(EGR) – (level2) 520 520 520 (296) 520 (296) (296) (296) (296) 520 (296) (296)AdvancedDiesel 873 873 873 844 873 844 844 1693 844 873 844 16936-speed auto.trans. withimprovedinternals (39) (39) (39)(39) (39) (39) (39) (39) (39) (39) (39) (39)6-speed DCT (107) (107) (107) (73) (107) (73) (73) (73) n/a (107) n/a n/aHighEfficiencyGearbox 248 248 248 248 248 248 248 248 248 248 248 248ShiftOptimizer 2 2 2 2 2 2 2 2 2 2 2 2Electric powersteering 108 108 108 108 108 108 108 108 108 108 108 10812V micro- 322 322 382 411 322 322 382 411 410 363 421 476DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL578hybridStrong Hybrid(level 2) 3526 3526 3705 4261 3526 3526 3705 4261 4677 4057 4332 4464Plug-in Hybrid 10,686 10,686 11,864 15,514 10,686 10,686 11,864 15,514 n/a 14,055 n/a n/aElectricVehicle (EarlyAdopter) 3,001 3,001 3.719 3,998 3,001 3,001 3.719 3,998 n/a 4,580 n/a n/aLow RollingResistanceTires (level 1) 7 7 7 7 7 7 7 7 7 7 7 7Low RollingResistanceTires (level 2) 72 72 72 72 72 72 72 72 72 72 72 72Aero DragReduction(level 1) 48 48 48 48 48 48 48 48 48 48 48 48Aero DragReduction(level 2) 162 162 162 162 162 162 162 162 162 162 162 162DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

579 c. How does NHTSA use these assumptions in its modeling analysis?

NHTSA relies on several inputs and data files to conduct the compliance analysis using the Volpe model, as discussed further below and in Chapter 5 of the PRIA. For the purposes of applying technologies, the Volpe model primarily uses three data files, one that contains data on the vehicles expected to be manufactured in the model years covered by the rulemaking and identifies the appropriate stage within the vehicl e’s life-cycle for the technology to be applied, one that contains data/parameters regarding the available technologies the model can apply, and one that contains economic assumption inputs for calculating the costs and benefits of the standards. The inputs for the first two data files are discussed below.

As discussed above, the Volpe model begins w ith an initial state of the domestic vehicle market, which in this case is th e market for passenger cars and light trucks to be sold during the period covered by the proposed standards. The vehicle market is defined on a year-by-year, model-by-model, engine-by-engine, and transmission-by-transmission basis, such that each defined vehicle model refers to a separately defined engine and a separately defined transmission. Comparatively, EPA’s OME GA model defines the vehicle market using representative vehicles at the vehicle platform level, which are binned into 5 year timeframes instead of year-by-year.

For the current standards, which cover MYs 2017–2025, the light-duty vehicle (passenger car and light truck) market forecast was developed jointly by NHTSA and EPA staff using MY 2008 CAFE compliance data. The MY 2008 compliance data includes about 1,100 vehicle models, about 400 specific engines, and about 200 specific transmissions, which is a somewhat lower level of detail in the repr esentation of the vehicle market than that used by NHTSA in prior CAFE analyses—previous analyses would count a vehicle as “new” in any year when significant technology differences ar e made, such as at a redesign. 609 However, within the limitations of information that can be made available to the public, it provides the foundation for a reasonable analysis of manufacturer-specific co sts and the analysis of attribute-based CAFE standards, and is much greater than the level of detail used by many other models and analyses relevant to light-duty vehicle fuel economy. 610

In addition to containing data about each ve hicle, engine, and transmission, this file contains information for each technology under cons ideration as it pertains to the specific vehicle (whether the vehicle is equipped with it or not), the estimated model year the vehicle is undergoing a refresh or redesign, and information about the vehicle’s subclass for purposes of technology application. In essence, the model considers whether it is appropriate to apply a technology to a vehicle.

609 The market file for the MY 2011 final rule, which incl uded data for MYs 2011–2015, had 5500 vehicles, about 5 times what we are using in this analysis of the MY 2008 certification data.

610 Because CAFE standards apply to the average performan ce of each manufacturer’s fleet of cars and light trucks, the impact of potential standards on individual manufacturer s cannot be credibly estimate d without analysis of the fleets that manufacturers can be expected to produce in the future. Furthermore, because required CAFE levels under an attribute-based CAFE standard depend on manufactu rers’ fleet composition, the stringency of an attributebased standard cannot be predicted without perfo rming analysis at this level of detail.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

580 Is a vehicle already equipped, or can it not be equipped, with a particular technology?

The market forecast file provides NHTSA the ability to identify, on a technology-bytechnology basis, which technologies may already be present (manufactured) on a particular vehicle, engine, or transmission, or which tech nologies are not applicable (due to technical considerations or engineering constraints) to a pa rticular vehicle, engine, or transmission. Theseidentifications are made on a model-by-model, engine-by-engine, and transmission-bytransmission basis. For example, if the market forecast file indicates that Manufacturer X’s Vehicle Y is manufactured with Technology Z, th en for this vehicle Technology Z will be shown as used. Additionally, NHTSA has determined that some technologies are only suitable or unsuitable when certain vehicle, engine, or transmission conditions exist. For example, secondary axle disconnect is only suitable for 4WD vehicles and cylinder deactivation is unsuitable for any engine with fewer than 6 cylinders. Similarly, comments received to the 2008 NPRM indicated that cylinder deactivation could not likely be applied to vehicles equipped with manual transmissions during the rulemaking timeframe, due primarily to the cylinder deactivation system not being able to anticipate gear shifts. The Volpe model employs “engineering constraints” to address issues like these, which are a programmatic method of controlling technology application that is indepe ndent of other constraints. Thus, the market forecast file would indicate that the technology in question should not be applied to the particular vehicle/engine/transmission ( i.e., is unavailable). Since multiple vehicle models may be equipped with an engine or transmission, this may a ffect multiple models. In using this aspect of the market forecast file, NHTSA ensures the Volpe model only applies technologies in an appropriate manner, since before any application of a technology can occur, the model checks the market forecast to see if it is either already present or unavailable. NHTSA seeks comment on the continued appropriateness of the engineering constraints used by the model, and specifically whether many of the technical constraints will be resolved (and therefore the engineering constraints should be changed) give n the increased focus of engineering resources that will be working to solve these technical challenges.

Whether a vehicle can be equipped with a par ticular technology could also theoretically depend on certain technical considerations related to incorporating the technology into particular vehicles. For example, GM commented on the MY 2012-2016 NPRM that there are certain issues in implementing turbocharging and down sizing technologies on full-size trucks, like concerns related to engine knock, drivability, control of boost pressure, packaging complexity, enhanced cooling for vehicles that are designed for towing or hauling, and noise, vibration and harshness. NHTSA stated in response that we believed that such technical considerations are well recognized within the industry and it is standard industry practice to address each during the design and development phases of applying turbocharging and downsizing technologies. The cost and effectiveness estimates used in the final rule for MYs 2012-2016, as well as the cost and effectiveness estimates employed in this NPRM, are based on analysis that assumes each of these factors is addressed prior to production implem entation of the technologies. NHTSA continues to believe that these issues are accounted for by industry, but we seek comment on whether the engineering constraints should be used to address concerns like these (and if so, how), or alternatively, whether some of the things that the agency currently treats as engineering constraints should be (or actually are) accounted for in the cost and effectiveness estimatesDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

581through assumptions like those described above, and whether the agency might be doubleconstraining the application of technology.

Is a vehicle being redesigned or refreshed?

Manufacturers typically plan vehicle changes to coincide with certain stages of a vehicle’s life cycle that are appropriate for th e change, or in this case the technology being applied. In the automobile industry there are two terms that describe when technology changes to vehicles occur: Redesign and refresh ( i.e., freshening). Vehicle redesign usually refers to significant changes to a vehicle’s appearance, shap e, dimensions, and powertrain. Redesign is traditionally associated with the introduction of “new” vehicles into the market, often characterized as the “next generation” of a vehicle, or a new platform. Vehicle refresh usually refers to less extensive vehicle modifications, such as minor changes to a vehicle’s appearance, a moderate upgrade to a powertrain system, or small changes to the vehicle’s feature or safety equipment content. Refresh is traditionally associated with mid-cycle cosmetic changes to a vehicle, within its current generation, to make it appear “fresh.” Vehicle refresh generally occurs no earlier than two years after a vehicle redesign, or at least two years before a scheduled redesign. To be clear, this is a general description of how manufacturers manage their product lines and refresh and redesign cycles but in some cases the timeframes could be shorter and others longer depending on market factors, regula tions, etc. For the majority of technologies discussed today, manufacturers will only be able to apply them at a refresh or redesign, because their application would be significant enough to involve some level of engineering, testing, and calibration work. 611

Some technologies ( e.g., those that require significant revision) are nearly always applied only when the vehicle is expected to be redesign ed, like turbocharging and engine downsizing, or conversion to diesel or hybridization. Other technologies, like cylinder deactivation, electric power steering, and low rolling resistance tires can be applied either when the vehicle is expected to be refreshed or when it is expected to be redesigned, while low friction lubricants, can be applied at any time, regardless of whether a refresh or redesign event is conducted. Accordingly, the model will only apply a technol ogy at the particular point deemed suitable. These constraints are intended to produce results consistent w ith how we assume manufacturers will apply technologies in the future base d on how they have historically implemented new technologies. For each technology under consideration, NHTSA specifies whether it can be applied any time, at refresh/redesign, or only at redesign. The data forms another input to the Volpe model. NHTSA develops redesign and refresh schedules fo r each of a manufacturer’s vehicles included in the analysis, essentially based on the last known redesign year for each vehicle and projected forward using a 5 to 8-year redesign and a 2–3 year refresh cycle, and this data is also stored in the market forecast file. While most vehicles ar e projected to follow a 5-year redesign a few of the niche market or small-volume manufacturer vehicles ( i.e. luxury and performance vehicles) and large trucks are assumed to have 6- to 8-year redesigns based on historic redesign schedules

611 For example, applying material substitution through we ight reduction, or even something as simple as low rolling-resistance tires, to a vehicle will likely require some level of validation and testing to ensure that the vehicle may continue to be certified as compliant with NH TSA’s Federal Motor Vehicle Safety Standards (FMVSS). Weight reduction might affect a vehicle’s crashworthiness; low rolling-resistance tires might change a vehicle’s braking characteristics or how it performs in crash avoidance tests.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

582 and the agency’s understanding of manufacturers’ intentions moving forward. This approach is used because of the nature of the current baseline, which as a single year of data does not contain its own refresh and redesign cycle cues for future model years, and to ensure the complete transparency of the agency’s analysis. We note that this approach is different from what NHTSA has employed previously for determining redesign and refresh schedules, where NHTSA included the redesign and refresh dates in the market forecast file as provided by manufacturers in confidential product plans. Vehicle redesign/refresh assumptions are discussed in more detail in Chapter 5 of the PRIA an d in Chapter 3 of the TSD.

NHTSA has previously received comments sta ting that manufacturers do not necessarily adhere to strict five-year redesign cycles, and may add significant technologies by redesigning vehicles at more frequent intervals, albeit at higher costs. Conversely, other comments received stated that as compared to full-line manufacturers, small-volume manufacturers in fact may have 7 to 8-year redesign cycles. 612 The agency believes that manufacturers can and will accomplish much improvement in fuel economy and GHG reductions while applying technology consistent with their redesign schedules.

Once the model indicates that a technology should be applied to a vehicle, the model must evaluate which technology should be app lied. This will depend on the vehicle subclass to which the vehicle is assigned; what technologies have already been applied to the vehicle ( i.e., where in the “decision tree” the vehicle is); when the technology is first available ( i.e., year of availability); whether the technology is still available ( i.e., “phase-in caps”); and the costs and effectiveness of the technologies being considered. Technology costs may be reduced, in turn, by learning effects and short- vs. long-term ICMs, while technology effectiveness may be increased or reduced by synergistic effects between technologies. In the technology input file, NHTSA has developed a separate set of technology data variables for each of the twelve vehicle subclasses. Each set of variables is referred to as an “input sheet,” so for example, the

612 In the MY 2011 final rule, NHTSA noted that the CAR re port submitted by the Allian ce, prepared by the Center for Automotive Research and EDF, stated that “For a gi ven vehicle line, the time from conception to first production may span two and one-half to five years,” but that “The time from first production (“Job#1”) to the last vehicle off the line (‘‘Balance Out’’) may sp an from four to five years to eight to te n years or more, depending on the dynamics of the market segment.” The CAR report then stated that “At the point of final production of the current vehicle line, a new model with the same badge and similar charact eristics may be ready to take its place, continuing the cycle, or the old model may be dropped in favor of a different product.” See NHTSA–2008–0089–0170.1, Attachment 16, at 8 (393 of pdf). NHTSA explained that this description, which states that a vehicle model will be redesigned or dropped after 4–10 years, was consistent w ith other characterizations of the redesign and freshening process, and supported the 5-year redesign and 2–3 year refresh cycle assumptions used in the MY 2011 final rule.

See id., at 9 (394 of pdf). Given that the situation faced by th e auto industry today is not so wholly different from that in March 2009, when the MY 2011 final rule was published, and given that the commenters did not present information to suggest that these assumptions are unreasonabl e (but rather simply that different manufacturers may redesign their vehicles more or less frequently, as the ra nge of cycles above indicates), NHTSA believes that the assumptions remain reasonable for purposes of this final rule analysis. See also “Car Wars 2009–2012, The U.S. automotive product pipeline,” John Murphy, Research Anal yst, Merrill Lynch research paper, May 14, 2008 and “Car Wars 2010–2013, The U.S. automotive product pipeline,” John Murphy, Research Analyst, Bank of America/Merrill Lynch research paper, July 15, 2009. Available at http://www.autonews.com/assets/PDF/CA66116716.PDF (last accessed October 11, 2011).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

583 subcompact passenger car input sheet holds the technology data that is appropriate for the subcompact subclass. Each input sheet contains a list of technologies available for members of the particular vehicle subclass. The following items are provided for each technology: The name of the technology, its abbreviation, the decision tree with which it is associated, the (first) year in which it is available, the year-by-year cost estimates and effectiveness (fuel consumption reduction) estimates, its applicability and the consumer value loss. The phase-in values and the potential stranded capital costs are common for all vehicle subclasses and are thus listed in a separate input sheet that is referenced for all vehicle subclasses.

To which vehicle subclass is the vehicle assigned?

As part of its consideration of technologi cal feasibility, the agency evaluates whether each technology could be implemented on all ty pes and sizes of vehicles, and whether some differentiation is necessary in applying certain t echnologies to certain types and sizes of vehicles, and with respect to the cost incurred and fuel consumption and CO 2 emissions reduction achieved when doing so. The 2010 NAS Report differentiated technology application using eight vehicle “classes” (4 car classes and 4 truck classes). 613 NAS’s purpose in separating vehicles into these classes was to create groups of “like” vehicles, i.e., vehicles similar in size, powertrain configuration, weight, and consumer use, and for which similar technologies are applicable. NAS also used these vehicle cl asses along with powertrain configurations ( e.g.. 4 cylinder, 6 cylinder or 8 cylinder engines) to determine unique cost and effectiveness estimates for each class of vehicles.

NHTSA similarly differentiates vehicles by “subclass” for the purpose of applying technologies to “like” vehicles and assessing th eir incremental costs and effectiveness. NHTSA assigns each vehicle manufactured in the rulemaking period to one of 12 subclasses: for passenger cars, Subcompact, Subcompact Performance, Compact, Compact Performance, Midsize, Midsize Performance, Large, and Large Performance; and for light trucks, Small SUV/Pickup/Van, Midsize SUV/Pickup/Van, La rge SUV/Pickup/Van, and Minivan. The agency seeks comment on the appropriateness of these 12 subclasses for the MYs 2017-2025 timeframe. The agency is also seeking comment on the continued appropriateness of maintaining separate “performance” vehicle classe s or if as fuel economy stringency increases the market for performance vehicles will decrease.

For this NPRM, NHTSA divides the vehicle fleet into subclasses based on model inputs, and applies subclass-specific estimates, also fr om model inputs, of the applicability, cost, and effectiveness of each fuel-saving technology. The model’s estimates of the cost to improve the fuel economy of each vehicle model thus depend upon the subclass to which the vehicle model is assigned. Each vehicle’s subclass is stored in the market forecast file. When conducting a compliance analysis, if the Volpe model seeks to apply technology to a particular vehicle, it checks the market forecast to see if the technology is available and if the refresh/redesign criteria are met. If these conditions are satisfied, the model determines the vehicle’s subclass from the

613 The NAS classes included two-seater convertibles and coupes; small cars; intermediate and large cars; highperformance sedans; unit-body standard trucks; unit-bo dy high-performance trucks; body-on-frame small and midsize trucks; and bodyDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

584 market data file, which it then uses to reference another input called the technology input file. NHTSA reviewed its methodology for dividing vehicles into subclasses for purposes of technology application that it used in the MY 2011 final rule and for the MYs 2012-2016 rulemaking, and concluded that the same methodology would be appropriate for this NPRM for MYs 2017–2025. Vehicle subclasses are discussed in more detail in Chapter 5 of the PRIA and in Chapter 3 of the TSD.

For the reader’s reference, the subclasses and example vehicles from the market forecast file are provided in the tables below.

P ASSENGER C AR S UBCLASSES E XAMPLE (MY 2008) V EHICLES Class Example vehicles Subcompact Chevy Aveo, Hyundai Accent Subcompact performance Mazda MX-5, BMW Z4 Compact Chevy Cobalt, Nissan Sentra and Altima Compact performance Audi S4, Mazda RX-8 Mid-size Chevy Impala, Toyota Camry, Honda Accord, Hyundai Azera Mid-size performance Chevy Corvette, Ford Mustang (V8), Nissan G37 Coupe Large Audi A8, Cadillac CTS and DTS Large performance Bentley Arnage, Daimler CL600

L IGHT T RUCK S UBCLASSES E XAMPLE (MY 2008) V EHICLES Class Example vehicles Minivans Dodge Caravan, Toyota Sienna Small SUV/Pickup/Van Ford Escape and Ranger, Nissan Rogue Mid-size SUV/Pickup/Van Chevy Colorado, Jeep Wrangler, Toyota Tacoma Large SUV/Pickup/Van Chevy Silverado, Ford E-Series, Toyota Sequoia

What technologies have already been app lied to the vehicle (i.e., where in the “ decision

trees ” is it)?

NHTSA’s methodology for technology analysis evaluates the application of individual technologies and their incremental costs and effe ctiveness. Individual technologies are assessed relative to the prior technology state, which means that it is crucial to understand what technologies are already present on a vehicle in order to determine correct incremental cost and effectiveness values. The benefit of the incremental approach is transparency in accounting, insofar as when individual technologies are added incrementally to individual vehicles, it is clear and easy to determine how costs and effectiveness add up as technology levels increase and explicitly accounting for any synergies that exist between technologies which are already present on the vehicle and new technologies being applied.

To keep track of incremental costs and effectiveness and to know which technology to apply and in which order, the Volpe model’s architecture uses a logical sequence, which NHTSA refers to as “decision trees,” for applying fu el economy-improving technologies to individual vehicles. For purposes of this proposal, NHTSA reviewed the MYs 2012-2016 final rule’s technology sequencing architecture, which was ba sed on the MY 2011 final rule’s decision treesDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

585 that were jointly developed by NHTSA and Ricardo , and, as appropriate, updated the decision trees to include new technologies that have been defined for the MYs 2017-2025 timeframe.

In general, and as described in great detail in Chapter 5 of the current PRIA, 614 each technology is assigned to one of the five following categories based on the system it affects or impacts: engine, transmission, electrification/accessory, hybrid or vehicle. Each of these categories has its own decision tree that the Volpe model uses to apply technologies sequentially during the compliance analysis. The decision trees were designed and configured to allow the Volpe model to apply technologies in a cost-effective, logical order that also considers ease of implementation. For example, software or control logic changes are implemented before replacing a component or system with a completely redesigned one, which is typically a much more expensive and integration intensive option. In some cases, and as appropriate, the model may combine the sequential technologies shown on a decision tree and apply them simultaneously, effectively developing dynamic technology packages on an as-needed basis. For example, if compliance demands indicate, the model may elect to apply LUB, EFR, and ICP on a dual overhead cam engine, if they are not already present, in one single step. An example simplified decision tree for engine technologies is provided below; the other simplified decision trees may be found in Chapter 5 of the PRIA. Expanded decision trees are available in the docket for this NPRM.

[Current simplified engine tree forthcoming]

Each technology within the decision trees has an incremental cost and an incremental effectiveness estimate associated with it, and estimates are specific to a particular vehicle subclass ( see the tables in Chapter 5 of the PRIA). Each technology’s incremental estimate takes into account its position in the decision tree path. If a technology is located further down the decision tree, the estimates for the costs and effectiveness values attributed to that technology are influenced by the incremental estimates of costs and effectiveness values for prior technology applications. In essence, this approach accounts for “in-path” effectivenes s synergies, as well as cost effects that occur between the technologies in the same path. When comparing cost and effectiveness estimates from various sources and those provided by commenters in this and the previous CAFE rulemakings, it is important that the estimates evaluated are analyzed in the proper context, especially as concerns their likely position in the decision trees and other technologies that may be present or missing. No t all estimates available in the public domain or that have been (or will be) offered for the agenci es’ consideration can be evaluated in an “applesto-apples” comparison with those used by the Volpe model, since in some cases the order of application, or included technology content, is inconsistent with that assumed in the decision

tree.

The MY 2011 final rule discus sed in detail the revisions and improvements made to the Volpe model and decision trees during that rulema king process, including the improved handling and accuracy of valve train technology application and the development and implementation of a method for accounting path-dependent correction factors in order to ensure that technologies are evaluated within the proper context. The reader should consult the MY 2011 final rule documents for further information on these modeli ng techniques, all of which continued to be

614 Additional details about technologies are categor ized can be found in the MY 2011 final rule.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

586 utilized in developing this final rule. 615 To the extent that the decision trees have changed for purposes of the MYs 2012-2016 final rule and this NPRM, it was due not to revisions in the order of technology application, but rather to redefinitions of technologies or addition or subtraction of technologies.

Is the next technology ava ilable in this model year?

Some of technologies considered are availa ble on vehicles today, and thus will be available for application (albeit in varying degrees) in the model starting in MY 2017. Other technologies, however, will not become available for purposes of NHTSA’s analysis until later in the rulemaking time frame. When the model is considering whether to add a technology to a vehicle, it checks its year of availability—if the technology is available, it may be added; if it is not available, the model will consider whether to switch to a different decision tree to look for another technology, or will skip to the next vehicle in a manufacturer’s fleet. The year of availability for each technology is provided above in Table IV.C.2–1.

The agency has received comments previously stating that if a technology is currently available or available prior to the rulemaking timeframe that it should be immediately made available in the model. . In response, as discussed above, technology ‘‘availability’’ is not determined based simply on whether the technology exists, but depends also on whether the technology has achieved a level of technical viability that make s it appropriate for widespread application. This depends in turn on component supplier constraints, capital investment and engineering constraints, and manufacturer product cycles, among other things. Moreover, even if a technology is available for application, it may not be available for every vehicle. Some technologies may have considerable fuel economy benefits, but cannot be applied to some vehicles due to technological constraints—for example, cylinder deactivation cannot be applied to vehicles with current 4-cylinder engines (because not enough cylinders are present to deactivate some and continue moving the vehicl e) or on vehicles with manual transmissions within the rulemaking timeframe. The agencies have provided for increases over time to reach the mpg level of the MY 2025 standards precisely because of these types of constraints, because they have a real effect on how quickly manufact urers can apply technology to vehicles in their fleets. NHTSA seeks comment on the appropriateness of the assumed years of availability.

Has the technology reached the phase-in cap for this model year?

Besides the refresh/redesign cycles used in th e Volpe model, which constrain the rate of technology application at the vehicle level so as to ensure a period of stability following any modeled technology applications, the other constraint on technology application employed in NHTSA’s analysis is “phase-in caps.” Unli ke vehicle-level cycle settings, phase-in caps constrain technology application at the vehicle manufacturer level. 616 They are intended to

615 See, e.g., 74 FR 14238–46 (Mar. 30, 2009) for a full discussion of the decision trees in NHTSA’s MY 2011 final rule, and Docket No. NHTSA–2009–0062–0003.1 for an expanded decision tree used in that rulemaking.

616 While phase-in caps are expressed as specific percentages of a manufacturer’s fleet to which a technology may be applied in a given model year, phase-in caps cannot always be applied as precise limits, and the Volpe model in fact allows “override” of a cap in certain circumstances. When only a small portion of a phase-in cap limit remains, or when the cap is set to a very low va lue, or when a manufacturer has a very limited product line, the cap mightDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

587 reflect a manufacturer’s overall resource capacity available for implementing new technologies (such as engineering and development personnel and financial resources), thereby ensuring that resource capacity is accounted for in the modeling process. At a high level, phase-in caps and refresh/redesign cycles work in conjunction with one another to avoid the modeling process outpacing an OEM’s limited pool of available resources during the rulemaking time frame and the years leading up to the rulemaking time frame, especially in years where many models may be scheduled for refresh or redesign. Even though this rulemaking is being proposed 5 years before it takes effect, OEM’s will still be utilizing their limited resources to meet the MYs 2012-2016 CAFE standards. This helps to ensure technolog ical feasibility and economic practicability in determining the stringency of the standards.

NHTSA has been developing the concept of phase-in caps for purposes of the agency’s modeling analysis over the course of the last several CAFE rulemakings, as discussed in greater detail in the MY 2011 final rule, 617 in the MY 2012-2016 final rule and in Chapter 5 of the PRIA and Chapter 3 of the Joint TSD. The MYs 2012-2016 final rule like the MY 2011 final rule employed non-linear phase-in caps (that is, caps that varied from year to year) that were designed to respond to previously received comments on technology deployment.

For purposes of this NPRM for MYs 2017–2025, as in the MY 2011 and MYs 2012-2016 final rules, NHTSA combines phase-in caps for so me groups of similar technologies, such as valve phasing technologies that are applicable to different forms of engine design (SOHC, DOHC, OHV), since they are very similar from an engineering and implementation standpoint. When the phase-in caps for two technologies ar e combined, the maximum total application of either or both to any manufacturer’s fleet is limited to the value of the cap. 618

In developing phase-in cap values for purposes of this NPRM, NHTSA reviewed the MYs 2012-2016 final rule’s phase-in caps, which for the majority of technologies were set to reach 85 or 100 percent by MY 2016, although more advanced technologies like diesels and strong hybrids reach only 15 percent by MY 2016. The phase-in caps used in the MYs 2012- 2016 final were developed to harmonize with EPA’s proposal and consider the fact that manufacturers, as part of the agreements supporting the National Program, appeared to be anticipating higher technology application rates than assumed in prior rules. NHTSA determined that these phase-in caps for MY 2016 were still reasonable and thus used those caps as the starting point for the MYs 2017-2025 phase-in caps. For many of the carryover technologies this means that for MYs 2017-2025 the phase-in caps are assumed to be 100 percent. NHTSA along with EPA used confidential OEM submissions, trade press articles, company publications and press releases to estimate the phase-in caps for the newly defined technologies that will be entering the market just before or during the MYs 2017-2025 time frame. For example,

prevent the technology from being applied at all since any application would cause the cap to be exceeded. Therefore, the Volpe model evaluates an d enforces each phase-in cap constraint after it ha s been exceeded by the application of the technology (as opposed to evaluating it before application), which can result in the described overriding of the cap.

618 See 74 FR at 14270 (Mar. 30, 2009) for further discussion and examples.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

588 advanced cooled EGR engines have a phase-in cap of 3 percent per year through MY 2021 and then 10 percent per year through 2025. The agency seeks comment on the appropriateness of both the carryover phase-in caps and the newly defined ones proposed in this NPRM.

Is the technology less expensive due to learning effects?

In the past two rulemakings NHTSA has explicitly accounted for the cost reductions a manufacturer might realize through learning achieved from experience in actually applying a technology. These cost reductions, due to learni ng effects, were taken into account through two kinds of mutually exclusive learning, “volum e-based” and “time-based.” NHTSA and EPA included a detailed description of the learning effect in the MYs 2012-2016 final rule and the more recent heavy-duty rule. 619

Most studies of the effect of experience or learning on production costs appear to assume that cost reductions begin only after some initia l volume threshold has b een reached, but not all of these studies specify this threshold volume. The rate at which costs decline beyond the initial threshold is usually expressed as the percent re duction in average unit cost that results from each successive doubling of cumulative production volume, sometimes referred to as the learning rate. Many estimates of experience curves do not specify a cumulative production volume beyond which cost reductions would no longer occur, in stead depending on the asymptotic behavior of the effect for learning rates below 100 percent to establish a floor on costs.

In past rulemaking analyses, as noted above, both agencies have used a learning curve algorithm that applied a learning factor of 20 percent for each doubling of production volume. NHTSA has used this approach in analyses supporting recent CAFE rules. In its analyses, EPA has simplified the approach by using an “every two years” based learning progression rather than a pure production volume progression (i.e., after two years of production it was assumed that production volumes would have doubled and, therefore, costs would be reduced by 20 percent). 620

In the MYs 2012-2016 light-duty rule, the agencies employed an additional learning algorithm to reflect the volume-based learning cost reductions that occur further along on the learning curve. This additional learning algorithm was termed “time-based” learning simply as a means of distinguishing this algorithm from the volume-based algorithm mentioned above, although both of the algorithms reflect the volume-based learning curve supported in the

619 76 FR 57106, 57320 (Sept. 15, 2011).

620 To clarify, EPA has simplified the steep portion of the volume learning curve by assuming that production volumes of a given technology will have doubled within two years time. This has been done largely to allow for a presentation of estimated costs during the years of implemen tation, without the need to conduct a feedback loop that ensures that production volumes have indeed doubled. If we were to attempt such a feedback loop, we would need to estimate first year costs, feed t hose into OMEGA, review the resultant technology penetration rate and volume increase, calculate the learned costs, feed those into OMEGA (since lower costs would result in higher penetration rates, review the resultant technology penetration rate and volume increase, etc., until an equilibrium was reached. To do this for the dozens of technologi es considered in our analysis is si mply not feasible. Instead, we have estimated the effects of learning on costs, fed those costs in to OMEGA, and reviewed the resultant penetration rates. The assumption that volumes have doubled after two years is based solely on the assumption that year two sales are of equal or greater number than year one sales and, therefor e, have resulted in a doubling of production. This could be done on a daily basis, a monthly basis, or a yearly basis as we have done.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

589 literature. To avoid confusion, we are now re ferring to this learning algorithm as the “flat portion” of the learning curve. This way, we main tain the clarity that all learning is, in fact, volume-based learning, and that the level of cost reductions depend only on where on the learning curve a technology’s lear ning progression is. We distinguish the flat portion of the curve from the “steep portion” of the curve to indicate the level of learning taking place in the years following implementation of the technology. The agencies have applied the steep portion learning algorithm for those technologies considered to be newer technologies likely to experience rapid cost reductions through manufacturer learning, and the flat portion learning algorithm for those technologies considered to be mature technologies likely to experience only minor cost reductions through manufacturer learning . As noted above, the steep portion learning algorithm results in 20 percent lower costs after two full years of implementation ( i.e. , the MY 2016 costs are 20 percent lower than the MYs 2014 and 2015 costs). Once two steep portion learning steps have occurred (for technologies having the steep portion learning algorithm applied while flat portion learning would begin in year 2 for technologies having the flat portion learning algorithm applied), flat portion learning at 3 percent per year becomes effective for 5 years. Beyond 5 years of learning at 3 percent pe r year, 5 years of learning at 2 percent per year, then 5 at 1 percent per year become effective.

Technologies assumed to be on the steep portion of the learning curve are hybrids and electric vehicles , while no learning is applied to technologies likely to be affected by commodity costs (LUB, ROLL) or that have loosely-define d BOMs (EFR, LDB), as was the case in the MY 2012-2016 final rule. Chapter 3 of the Joint TSD and the PRIA shows the specific learning factors that NHTSA has applied in this anal ysis for each technology, and discusses learning factors and each agency’s use of them further.

Is the technology more or less effective due to synergistic effects?

When two or more technologies are added to a particular vehicle model to improve its fuel efficiency and reduce CO 2 emissions, the resultant fuel consumption reduction may sometimes be higher or lower than the product of the individual effectiveness values for those items. 621 This may occur because one or more technologies applied to the same vehicle partially address the same source (or sources) of engine, driv etrain or vehicle losses. Alternately, this effect may be seen when one technology shif ts the engine operating points, and therefore increases or reduces the fuel consumption reduction achieved by another technology or set of technologies. The difference between the observed fuel consumption reduction associated with a set of technologies and the product of the individual effectiveness values in that set is referred to for purposes of this rulemaking as a “synergy.” Synergies may be positive (increased fuel consumption reduction compared to the product of the individual effects) or negative (decreased fuel consumption reduction). An example of a positive synergy might be a vehicle technology

621 More specifically, the products of th e differences between one and the techno logy-specific levels of effectiveness in reducing fuel consumption. For example, not accounting fo r interactions, if technologies A and B are estimated to reduce fuel consumption by 10 percent ( i.e., 0.1) and 20 percent ( i.e., 0.2) respectively, the “product of the individual effectiveness values” would be 1–0.1 times 1–0.2, or 0.9 times 0.8, which equals 0.72, corresponding to a combined effectiveness of 28 percent rather than the 30 percent obtained by adding 10 percent to 20 percent. The “synergy factors” discussed in this section further adju st these multiplicatively comb ined effectiveness values.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

590 that reduces road loads at highway speeds ( e.g., lower aerodynamic drag or low rolling resistance tires), that could extend the vehicle operating range over which cylinder deactivation may be employed. An example of a negative synergy might be a variable valvetrain system technology,which reduces pumping losses by altering the profile of the engine speed/load map, and a sixspeed automatic transmission, whic h shifts the engine operating points to a portion of the engine speed/load map where pumping losses are less significant.

As the complexity of the technology combinations is increased, and the number of interacting technologies grows accordingly, it becomes increasingly important to account for these synergies. NHTSA and EPA determined synergistic impacts for this proposed rule using EPA’s “lumped parameter” analysis tool, which EPA describes at length in Chapter 3 of the TSD. The lumped parameter tool is a spreadsheet model that represents energy consumption in terms of average performance over the fuel economy test procedure, rather than explicitly analyzing specific drive cycles. The tool begins with an apportionment of fuel consumption across several loss mechanisms and accounts for the average extent to which different technologies affect these loss mechanisms usi ng estimates of engine, drivetrain and vehicle characteristics that are averaged over the 2-cycle CAFE drive cycle. Results of this analysis were generally consistent with those of full-scale vehicle simulation modeling performed in 2010-2011 for EPA by Ricardo, Inc.

For the current rulemaking, NHTSA is using an updated version of lumped parameter tool that incorporates results from simulation modeling performed in 2010-2011 by Ricardo, Inc. NHTSA and EPA incorporate synergistic impacts in their analyses in slightly different manners. Because NHTSA applies technologies indivi dually in its modeling analysis, NHTSA incorporates synergistic effects between pairings of individual technologies. The use of discrete technology pair incremental sy nergies is similar to that in DOE’s National Energy Modeling System (NEMS). 622 Inputs to the Volpe model incorporate NEMS-identified pairs, as well as additional pairs from the set of technologies considered in the Volpe model.

NHTSA notes that synergies that occur within a decision tree are already addressed within the incremental values assigned and therefore do not require a synergy pair to address. For example, all engine technologies take into account incremental synergy factors of preceding engine technologies, and all transmission technologies take into account incremental synergy factors of preceding transmission technologies. These factors are expressed in the fuel consumption improvement factors in the input files used by the Volpe model.

For applying incremental synergy factors in se parate path technologies, the Volpe model uses an input table (see the tables in Chapter 3 of the TSD and in the PRIA) which lists technology pairings and incremen tal synergy factors associated with those pairings, most of which are between engine technologies and tr ansmission/electrification/hybrid technologies. When a technology is applied to a vehicle by the Volpe model, all instances of that technology in the incremental synergy table which match technologies already applied to the vehicle (either

622 U.S. Department of Energy, Energy Information Administration, Transportation Sector Module of the National Energy Modeling System: Model Documentation 2007, May 2007, Washington, DC, DOE/EIAM070(2007), at 29–

30. Available at http://tonto.eia.doe.gov/ftproot/modeldoc/m070(2007).pdf (last accessed Sept. 25, 2011).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

591 pre-existing or previously applied by the Volpe model) are summed and applied to the fuel consumption improvement factor of the technology being applied. Many of the synergies for the strong hybrid technology fuel consumption reductions are included in the incremental value for the specific hybrid technology block since the mode l applies all available electrification, engine and transmission technologies before a pplying strong hybrid technologies.

The U.S. DOT Volpe Center has entered into a contract with Argonne National Laboratory (ANL) to provide full vehicle simulation modeling support for this MYs 2017-2025 rulemaking. While this modeling was not comp leted in time for use in this NPRM, NHTSA intends to use this modeling to validate/update technology effectiveness estimates and synergy factors for the final rulemaking analysis. This simulation modeling will be accomplished using ANL’s full vehicle simulation tool called “A utonomie,” which is the successor to ANL’s Powertrain System Analysis Toolkit (PSAT) simulation tool, and ANL’s expertise with advanced vehicle technologies.

d. Where can readers find more detailed information about NHTSA’s technology analysis?

Much more detailed information is provided in Chapter 5 of the PRIA, and a discussion of how NHTSA and EPA jointly reviewed and updated technology assumptions for purposes of this NPRM is available in Chapter 3 of the TSD. Additionally, all of NHTSA’s model input and output files are now public and available for the reader’s review and consideration. The technology input files can be found in the docket for this NPRM, Docket No. NHTSA–2011– xxxx, and on NHTSA’s website. And finally, because much of NHTSA’s technology analysis for purposes of this final rule builds on the work that was done for the MY 2011 and MYs 2012- 2016 final rules, we refer readers to those documents as well for background information concerning how NHTSA’s methodology for technol ogy application analysis has evolved over the past several rulemakings, both in response to comments and as a result of the agency’s growing experience with this type of analysis. 623

3. How did NHTSA develop its economic assumptions?

NHTSA’s analysis of alternative CAFE standards for the model years covered by this rulemaking relies on a range of forecast variables, economic assumptions, and parameter values. This section describes the sources of these forecasts, the rationale underlying each assumption, and the agency’s choices of specific parameter values. These economic values play a significant role in determining the benefits of alternative CA FE standards, as they have for the last several CAFE rulemakings. Under those alternatives where standards would be established by reference to their costs and benefits, these economic values also affect the levels of the CAFE standards themselves. Some of these variables have more important effects on the level of CAFE standards and the benefits from re quiring alternative increases in fuel economy than do others, and the following discussion places more emphasis on these inputs.

In reviewing these variables and the agency’s estimates of their values for purposes of this proposed rule, NHTSA reconsidered comments it had previously received on the NPRM for

623 74 FR 14233–308 (Mar. 30, 2009).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

592 MYs 2012-16 CAFE standards and to the NOI/Interim Joint TAR, and also reviewed newly available literature. The agency elected to revise some of its economic assumptions and parameter estimates for this rulema king, while retaining others. For the reader’s reference, Table IV.C.3–1 below summarizes the values used to calculate the economic benefits from each alternative.

T ABLE IV.C.3-1. E CONOMIC V ALUES FOR E STIMATING B ENEFITS (2009$)

Fuel Economy Rebound Effect 10% "Gap" between test and on-road MPG for liquid-fueled vehicles 20% “Gap” between test and on-road wall electricity consumption for electric and plug-in hybrid electric vehicles 30%
Value of refueling time per ($ per vehicle-hour) $21.43 Average tank volume refilled during refueling stop 65% Annual annual growth in average vehicle use 2001-30: 1.0% 2031-50: 0.5% Fuel Prices (2017-50 average, $/gallon) Retail gasoline price $3.71 Pre-tax gasoline price $3.35
Economic Benefits from Re ducing Oil Imports ($/gallon) "Monopsony" Component $ 0.00

Price Shock Component $ 0.185 in
2025 Military Security Component $ 0.00
Total Economic Costs ($/gallon) $ 0.185 in
2025 Emission Damage Costs (2020, $/short ton)
Carbon monoxide $ 0 Volatile organic compounds (VOC) $ 1,300 Nitrogen oxides (NO X ) – vehicle use $ 5,500 Nitrogen oxides (NO X ) – fuel production and distribution $ 5,300 Particulate matter (PM 2.5 ) – vehicle use $ 300,000 Particulate matter (PM 2.5 ) – fuel production and distribution $ 250,000 Sulfur dioxide (SO 2 ) $ 32,000

Annual CO 2 Damage Cost (per metric ton) variable depending on discount rate and year (see Table II-9 above for
2017 estimates)
External Costs from Additional Automobile Use ($/vehicle-mile)

Congestion $ 0.056
Accidents $ 0.024DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

593 Noise $ 0.001
Total External Costs $ 0.080 External Costs from Additional Light Truck Use ($/vehicle-mile) Congestion $0.049
Accidents $0.027
Noise $0.001
Total External Costs $0.077 Discount Rates Applied to Future Benefits 3%, 7%

a. Costs of Fuel Economy-Improving Technologies

Building on cost estimates developed for the MYs 2012-2016 CAFE and GHG final rule and the 2010 TAR, the agencies incorporated new cost estimates for the new technologies being considered and some of the technologies carried over from the MYs 2012-2016 final rule and 2010 TAR. This joint work is reflected in Chap ter 3 of the Joint TSD and in Section II of this preamble, as summarized below. For more detailed information on cost of fuel-saving technologies, please refer to Chapter 3 of the Joint TSD and Section V of NHTSA’s PRIA.

The technology cost estimates used in this analysis are intended to represent manufacturers’ direct costs for high-volume prod uction of vehicles with these technologies. NHTSA explicitly accounts for the cost reductions a manufacturer might realize through learning achieved from experience in actually applying a technology, which means that technologies become cheaper over the rulemaking time frame; learning effects are described above and in Chapter 3 of the draft joint TSD and Chapter V of NHTSA’s PRIA. NHTSA notes that, in developing technology cost estimates, the agencies have made every effort to hold constant aspects of vehicle performance a nd utility typically valued by consumers, such as horsepower, carrying capacity, drivability, durability, noise, vibration and harshness (NVH) and towing and hauling capacity. For example, NHTSA includes in its analysis technology cost estimates that are specific to performance passenger cars ( i.e., sports cars), as compared to nonperformance passenger cars. NHTSA seeks comment on the extent to which commenters believe that the agencies have been successful in holding constant these elements of vehicle performance and utility in developing the technology cost estimat es. Additionally, the agency notes that the technology costs included in this proposal take in to account only those associated with the initial build of the vehicle. Although comments were received to the MYs 2012-2016 rulemaking that suggested there could be additional maintena nce required with some new technologies ( e.g. , turbocharging, hybrids, etc.), and that additional maintenance costs could occur as a result. The agency requests comments on this topic and will undertake a more detailed review of these potential costs for the final rule.

Additionally, NHTSA recognizes that manufacturers’ actual costs for employing these technologies include additional outlays for accompanying design or engineering changes to models that use them, development and testing of prototype versions, recalibrating engine operating parameters, and integrating the technology with other attributes of the vehicle. Manufacturers’ indirect costs for employing thes e technologies also include expenses for product development and integration, modifying assembly processes and training assembly workers to install them, increased expenses for operation and maintaining assembly lines, higher initial warranty costs for new technologies, any added expenses for selling and distributing vehiclesDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

594 that use these technologies, and manufacturer and d ealer profit. These indirect costs have been accounted for in this rulemaking through use of ICMs, which have been revised for this rulemaking as discussed above, in Chapter 3 of the draft joint TSD, and in Chapter V of NHTSA’s PRIA.

b. Potential Opportunity Costs of Improved Fuel Economy

An important concern is whether achieving the fuel economy improvements required by the proposed CAFE standards will require manufacturers to modify the performance, carrying capacity, safety, or comfort of some vehicle models. To the extent that it does so, the resulting sacrifice in the value of those models represents an additional cost of achieving the required improvements in fuel economy. (This possibility is addressed in detail in Section IV.G.6.) Although exact dollar values that potential buye rs attach to specific vehicle attributes are difficult to infer, differences in vehicle purcha se prices and buyers’ choices among competing models that feature varying combinations of these characteristics clearly demonstrate that changes in these attributes affect the utility and economic value they offer to potential buyers. 624

NHTSA and EPA have approached this potential problem by developing cost estimates for fuel economy-improving technologies that in clude any additional manufacturing costs that would be necessary to maintain the originally planned levels of performance, comfort, carrying capacity, and safety of any light-duty vehicle model to which those technologies are applied. In doing so, the agencies followed the precedent established by the 2002 NAS Report, which estimated “constant performance and utility” co sts for fuel economy technologies. NHTSA has followed this precedent in its efforts to refine th e technology costs it uses to analyze alternative passenger car and light truck CAFE standards for MYs 2017–2025. Although the agency has reduced its estimates of manufacturers’ costs for most technologies for use in this rulemaking, these revised estimates are still intended to represent costs that would allow manufacturers to maintain the performance, carrying capacity, and u tility of vehicle models while improving their fuel economy.

While we believe that our cost estimates for fuel economy-improving technologies include adequate provisions for accompanying costs that are necessary to prevent any degradation in other vehicle attributes, it is possi ble that they do not include adequate allowance to prevent sacrifices in these attributes on all vehicle models. If this is the case, the true economic costs of achieving higher fuel economy sh ould include the opportunity costs to vehicle owners of any accompanying reductions vehicles’ performance, carrying capacity, and utility, and omitting these will cause the agency’s estimat ed technology costs to underestimate the true economic costs of improving fuel economy.

It would be desirable to estimate explicitly the changes in vehicle buyers’ welfare from the combination of higher prices for new vehicle models, increases in their fuel economy, and

624 See, e.g., Kleit A.N., 1990. “The Effect of Annual Changes in Automobile Fuel Economy Standards.” Journal of Regulatory Economics 2: 151–172 (Docket EPA–HQ–OAR–2009–0472–0015); Berry, Steven, James Levinsohn, and Ariel Pakes, 1995. “Automobile Prices in Market Equilibrium,” Econometrica 63(4): 841–940 (Docket NHTSA–2009–0059–0031); McCarthy, Patrick S., 1996.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

595 any accompanying changes in other vehicle attributes. The net change in buyer’s welfare that results from the combination of these changes would provide a more accurate estimate of the true economic costs for improving fuel economy. The ag ency is in the process of developing a model of potential vehicle buyers’ d ecisions about whether to purchase a new car or light truck and their choices from among the available models, which will allow it to conduct such an analysis. This process is expected to be completed for use in analyzing final CAFE standards for MY 2017-25; in the meantime, Section IV.G.6 below in cludes a detailed analysis and discussion of how omitting possible changes in vehicle attributes other than their prices and fuel economy might affect its estimates of benefits and costs resulting from the standards proposed in this
NPRM.

c. The On-Road Fuel Economy “Gap”

Actual fuel economy levels achieved by light-duty vehicles in on-road driving fall somewhat short of their levels measured under the laboratory-like test conditions used by EPA to establish its published fuel economy ratings for different models. In analyzing the fuel savings from alternative CAFE standards, NHTSA has previously adjusted the actual fuel economy performance of each light truck model downward from its rated value to reflect the expected size of this on-road fuel economy “gap.” On December 27, 2006, EPA adopted changes to its regulations on fuel economy labeling, which were intended to bring vehicles’ rated fuel economy levels closer to their actual on-road fuel economy levels. 625

In its Final Rule, however, EPA estimated that actual on-road fuel economy for light-duty vehicles averages approximately 20 percent lowe r than published fuel economy levels, somewhat larger than the 15 percent shortfall it had previously assumed. For example, if the overall EPA fuel economy rating of a light truck is 20 mpg, EPA estimated that the on-road fuel economy actually achieved by a typical driver of that vehi cle is expected to be only 80 percent of that figure, or 16 mpg (20*.80). NHTSA employed EPA’s revised estimate of this on-road fuel economy gap in its analysis of the fuel savings resulting from alternative CAFE standards evaluated in the MY 2011 final rule.

In the course of developing its CAFE standards for MY 2012-16, NHTSA conducted additional analysis of this issue. The agency used data on the number of passenger cars and light trucks of each model year that were registered for use during calendar years 2000 through 2006, average rated fuel economy for passenger cars and light trucks produced during each model year, and estimates of average miles driven per year by cars and light trucks of different ages. These data were combined to develop estimates of the average fuel economy that the U.S. passenger vehicle fleet would have achieved from 2000 through 2006 if cars and light trucks of each model year achieved the same fuel economy levels in actual on-road driving as they did under test conditions when new.

Table IV.C.3-2 compares NHTSA’s estimates of fleet-wide average fuel economy under test conditions for 2000 through 2006 to the Federal Highway Administration’s (FHWA) published estimates of actual on-road fuel economy achieved by passenger cars and light trucks

625 71 FR 77871 (Dec. 27, 2006).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

596 during each of those years. 626 As it shows, FHWA’s estimates of actual fuel economy for passenger cars ranged from 21-23 percent lower than NHTSA’s estimates of its fleet-wide average value under test conditions over this period, and FHWA’s estimates of actual fueleconomy for light trucks ranged from 16-18 percent lower than NHTSA’s estimates of its fleetwide average value under test conditions. Thus, these results appear to confirm that the 20 percent on-road fuel economy gap represents a reasonable estimate for use in evaluating the fuel savings likely to result from more stringent fuel economy and CO 2 standards in MYs 2017-2025.

Table IV.C.3-2 Estimated Fleet-Wide Fuel Ec onomy of Passenger Cars and Light Trucks Compared to Reported Fuel Economy

YEAR PASSENGER CARS LIGHT-DUTY TRUCKS

NHTSA Estimated Test MPG FHWA Reported Actual MPG Percent Difference NHTSA Estimated Test MPG FHWA Reported Actual MPG Percent Difference

2000 28.2 21.9 -22.2% 20.8 17.4 -16.3%
2001 28.2 22.1 -21.7% 20.8 17.6 -15.5%
2002 28.3 22.0 -22.3% 20.9 17.5 -16.2%
2003 28.4 22.2 -21.9% 21.0 17.2 -18.0%
2004 28.5 22.5 -21.1% 21.0 17.2 -18.3%
2005 28.6 22.1 -22.8% 21.1 17.7 -16.3%

2006 28.8 22.5 -21.8% 21.2 17.8 -16.2% Avg., 2000- 2006 28.4 22.2 -22.0% 21.0 17.5 -16.7%

The comparisons reported in this table must be interpreted with some caution, however, because the estimates of annual car and truck use used to develop these estimates are submitted to FHWA by individual states, which use differing definitions of passenger cars and light trucks. (For example, some states classify minivans as ca rs, while others define them as light trucks.) At the same time, while total gasoline consumption can be reasonably estimated from excise tax receipts, separate estimates of gasoline consumption by cars and trucks are not available. For these reasons, NHTSA has chosen not to rely on its separate estimates of the on-road fuel economy gap for cars and light trucks. However, the agency does believe that these results confirm that the 20 percent on-road fuel economy discount represents a reasonable estimate for use in evaluating the fuel savings likely to result from CAFE standards for both cars and light trucks. NHTSA employs this value for vehicles operating on liquid fuels (gasoline, diesel, and gasoline/alcohol blends), and uses it to analyze the impacts of proposed CAFE standards for model years 2017-25 on the use of these fuels.

In their recent TAR, EPA and NHTSA assumed that the overall energy shortfall for the vehicles employing electric drivetrains, includi ng plug-in hybrid and battery-powered electric

626 Federal Highway Administration, Highway Sta tistics, 2000 through 2006 editions, Table VM–1; See http://www.fhwa.dot.gov/policy/ohpi/hss/hsspubs.cfm (last accessed March 1, 2010).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

597 vehicles, is 30 percent. This value was derived from the agencies’ engineering judgment based on the limited available information. During th e stakeholder meetings conducted prior to the technical assessment, confidential business information (CBI) was supplied by several manufacturers which indicated that electrically pow ered vehicles had great er variability in their on-road energy consumption than vehicles powe red by internal combustion engines, although other manufacturers suggested that the on-road/ laboratory differential attributable to electric operation should approach that of liquid fuel operation in the future. Second, data from EPA’s 2006 analysis of the “five cycle” fuel economy label as part of the rulemaking discussed above supported a larger on-road shortfall for vehicles with hybrid-electric drivetrains, partly because real-world driving tends to have higher acceleration/deceleration rates than are employed on the 2-cycle test. This diminishes the fuel economy benefits of regenerative braking, which can result in a higher test fuel economy for hybrids than is achieved under normal on-road conditions. 627 Finally, heavy accessory load, extremely high or low temperatures, and aggressive driving have deleterious impacts of unknown magnitudes on batt ery performance. Consequently, the agencies judged that 30 percent was a reasonable estimate for use in the TAR, and NHTSA believes that it continues to represent the most reliable estimate for use in the current analysis.

One of the most significant factors responsi ble for the difference between test and onroad fuel economy is the use of air conditioning. While the air conditioner is turned off during the FTP and HFET tests, drivers often use air conditioning under warm, humid conditions. The air conditioning compressor can also be engage d during “defrost” operation of the heating system. 628 In the MYs 2012-2016 rulemaking, EPA estimated the impact of an air conditioning system at approximately 14.3 grams CO 2 /mile for an average vehicle without any of the improved air conditioning technologies discussed in that rulemaking. For a 27 mpg (330 g CO 2 /mile) vehicle, this would account for is approximately 20 percent of the total estimated onroad gap (or about 4 percent of total fuel consumption).

In the MY 2012-2016 rule, EPA estimated that 85 percent of MY 2016 vehicles would reduce their tailpipe CO 2 emissions attributable to air cond itioner efficiency by 40 percent through the use of advanced air conditioning technologies, and th at incorporating this change would reduce the average on-road gap by about 2 percent. 629 However, air conditioning-related fuel consumption does not decrease proportionall y as engine efficiency improves, because the engine load due attributable to air conditioner operation is approximately constant across engine efficiency and technology. As a consequence, air conditioning operation represents an increasing percentage of vehicular fuel consumption as engine efficiency increases. 630 Because these two effects are expected approximately to counterbalance each other, NHTSA has elected not to adjust its estimate of the on -road gap for use in this proposal.

627 EPA, Fuel Economy Labeling of Motor Vehicles: Re visions To Improve Calculation of Fuel Economy Estimates; Final Rule, 40 CFR Parts 86 and 600, 71 Fed. Reg. 77872, 77879 (Dec. 27, 2006). Available at http://www.epa.gov/fedrgstr/EPA-AIR/200 6/December/Day-27/a9749.pdf.

628 EPA, Final Technical Support Document: Fuel Economy Labeling of Motor Vehicle Revisions to Improve Calculation of Fuel Economy Estimates , at 70. Office of Transportation and Air Quality EPA420-R-06-017 December 2006, Chapter II, http:// www.epa.gov/fueleconomy/420r06017.pdf.

629 4% of the on-road gap x 40% reduction in air conditioning fuel consumption x 85% of the fleet = ~2%.

630 As an example, the air conditioning load of 14.3 g/mile of CO2 is a smaller percentage (4.3%) of 330 g/mile than 260 (5.4%).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

598 d. Fuel Prices and the Value of Saving Fuel

Future fuel prices are the single most important input into the economic analysis of the benefits of alternative CAFE standards because they determine the value of future fuel savings, which account for approximately 90% of total economic benefits from requiring higher fuel economy. NHTSA relies on the most recent fuel price projections from the U.S. Energy Information Administration’s (EIA) Annual Energy Outlook (AEO) 2011 Reference Case to estimate the economic value of fuel savings projected to result from alternative CAFE standards for MY 2017-25. The AEO 2011 Reference Case fo recasts of gasoline and diesel fuel prices represents EIA’s most up-to-date estimate of the most likely course of future prices for petroleum products. EIA is widely recognized as an impartial and authoritative source of analysis and forecasts of U.S. energy production, consumption, and prices, and its forecasts are widely relied upon by federal agencies for use in regulatory analysis and for other purposes. Its forecasts are derived using EIA’s National Energy Modeling System (NEMS), which includes detailed representations of supply pathways, sources of demand, and their interaction to determine prices for different forms of energy.

As compared to the gasoline prices used in NHTSA’s Final Rule establishing CAFE standards for MY 2012-2016 (which relied on forecasts from AEO 2010), the AEO 2011 Reference Case fuel prices are slightly higher through the year 2020, but slightly lower for most years thereafter. Expressed in constant 2009 dollars, the AEO 2011 Reference Case forecast of retail gasoline prices (which include federal, state, and local taxes) during 2017 is $3.25 per gallon, rising gradually to $3.71 by the year 2035. However, valuing fuel savings over the full lifetimes of passenger cars and light trucks affected by the standards proposed for MYs 2017-25 requires fuel price forecasts that extend through 2060, approximately the last year during which a significant number of MY 2025 vehicles will remain in service. 631 To obtain fuel price forecasts for the years 2036 throug h 2060, the agency assumes that reta il fuel prices will continue to increase after 2035 at the average annual rate (0.7%) projected for 2017-2035 in the AEO 2011 Reference Case. This assumption results in a projected retail price of gasoline that reaches $4.16 in 2050. Over the entire period from 2017-2050, retail gasoline prices are projected to average $3.67, as Table IV.C.3-1 reported previously.

The value of fuel savings resulting from improved fuel economy to buyers of light-duty vehicles is determined by the retail price of fuel, which includes Federal, State, and any local taxes imposed on fuel sales. Because fuel taxes represent transfers of resources from fuel buyers to government agencies, however, rather than real resources that are consumed in the process of supplying or using fuel, NHTSA deducts their value from retail fuel prices to determine the value of fuel savings resulting from more stringent CAFE standards to the U.S. economy.

NHTSA follows the assumptions used by EIA in AEO 2011 that State and local gasoline taxes will keep pace with inflation in nominal terms, and thus rema in constant when expressed in constant dollars. In contrast, EIA assumes that Federal gasoline taxes w ill remain unchanged in nominal terms, and thus decline throughout the forecast period when expressed in constant

631 The agency defines the maximum lifetime of vehicles as the highest age at which more than 2 percent of those originally produced during a model year remain in service. In the case of light trucks, for example, this age has typically been 36 years for recent model years.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

599 dollars. These differing assumptions about the likely future behavior of Federal and State/local fuel taxes are consistent with recent historical experience, which reflects the fact that Federal as well as most State motor fuel taxes are specified on a cents-per-gallon rather than an ad valorem basis, and typically require legislation to change. Subtracting fuel taxes from the retail prices forecast in AEO 2011 results in projected values for saving gasoline of $3.29 per gallon during 2017, rising to $3.48 per gallon by the year 2035, and to $3.65 by the year 2050. Over this entire period, pre-tax gasoline prices ar e projected to average $3.32 per gallon.

EIA also includes forecasts reflecting high and low global oil prices in each year’s complete AEO, which reflect uncer tainties regarding OPEC behavior as well as future levels of oil production and demand. These alternative s cenarios project retail gasoline prices that range from a low of $2.30 to a high of $4.85 per gallon during 2020, and from $2.12 to $5.36 per gallon during 2035 (all figures in 2009 dollars). In conjunction with our assumption that fuel taxes will remain constant in real or inflation- adjusted terms over this period, these forecasts imply pre-tax values of saving fuel ranging from $1.91 to $4.46 per gallon during 2020, and from $1.77 to $5.01 per gallon in 2035 (again, all figures are in constant 2009 dollars). In conducting the analysis of uncertainty in bene fits and costs from alternative CAFE standards required by OMB, NHTSA evaluated the sensitivity of its benefits estimates to these alternative forecasts of future fuel prices; detailed results and discussion of this sensitivity analysis can be found in the agency’s PRIA. Generally, this analysis confirms that the primary economic benefit resulting from the rule—the value of fuel savings—is extremely sensitive to alternative forecasts of future fuel prices.

e. Consumer Valuation of Fuel Economy and Payback Period

In estimating the impacts on vehicle sales th at would result from requiring higher fuel economy, NHTSA continues to assume (as it has done in analyzing previous CAFE standards) that potential vehicle buyers value the resulting fuel savings over only part of the expected lifetime of the vehicles they purchase. The agen cy uses slightly different assumptions about the length of time over which potential vehicle bu yers consider fuel savings from higher fuel economy, and about how they discount those future fuel savings, in different aspects of its analysis. For most purposes, the agency assumes that buyers value fuel savings over the first five years of a new vehicle’s lifetime; the five-year figure represents approximately the current average term of consumer loans to finance the purchase of new vehicles. .

To simulate manufacturers’ assessment of the net change in the value of an individual vehicle model to prospective buyers from improving its fuel economy, NHTSA discounts fuel savings over the first five years of its lifetime using a 7 percent rate. The resulting value is deducted from the technology costs that would be incurred by its manufacturer to improve that model’s fuel economy, in order to determine the change in its value to potential buyers. Since this is also the additional amount its manufact urer could expect to receive when selling the vehicle after improving its fuel economy, this can also be viewed as the “effective cost” of the improvement from its manufacturers’ perspective. The CAFE model uses these estimates of effective costs to identify the sequence in which manufacturers are likely to select individual models for improvements in fuel economy, as well as to identify th e most cost-effective technologies for doing so.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

600 The average of effective cost to its manufacturer for increasing the fuel economy of a model also represents the change in its value fro m the perspective of potential buyers. Under the assumption that manufacturers change the selling price of each model by this amount, its average value also represents the average change in its net or effective price to would-be buyers. NHTSA uses these estimates of the average pr ice increases for new cars and light trucks produced in each model year to estimate the resu lting changes in their to tal sales. The agency also tests the sensitivity of its estimates of change s in effective prices an d total sales of new cars and light trucks to the assumptions that buyers discount future fuel savings using a 3 percent rather than a 7 percent discount rate, and that buyers value fuel savings over only a two-year period instead of over five years. Finally, as part of our sensitivity case analyzing the potential for manufacturers to over-comply with CAFE standards – that is, to produce a lineup of vehicle models whose sales-weighted average fuel economy exceeds that required by prevailing standards – NHTSA used the extreme assumption th at potential buyers value fuel savings only during the first year they expect to own a new vehicle.

The agency notes that these varying assumptions about future time horizons and discount rates for valuing fuel savings are used only to analyze manufacturers’ responses to requiring higher fuel economy and buyers’ behavior in re sponse to manufacturers’ compliance strategies. When estimating the aggregate value to the U.S. economy of fuel savings resulting from alternative increases in CAFE standards—or the “social” value of fuel savings—the agency includes fuel savings over the entire expected lifetimes of vehicles that would be subject to higher standards, rather than over the shorter periods we assume manufacturers employ to represent the preferences of vehicle buyers, or that buyers use to assess changes in the net price or new vehicles.

Valuing fuel savings over vehicles’ entire lifet imes recognizes the savings in fuel costs that subsequent owners of vehicles will experience form higher fuel economy, even if their initial purchasers do not expect to recover the remaining value of fuel savings when they re-sell those vehicles, or for other reasons do not value fuel savings beyond the assumed five-year time horizon. The agency acknowledges that it has not accounted for any effects of increased costs for financing, insuring, or maintaining vehicles w ith higher fuel economy, over either this limited payback period or the full lifetimes of vehicles.

The procedure the agency uses for calculating lifetime fuel savings is discussed in detail in the following section, while alternative assumptions about the time horizon over which potential buyers consider fuel savings in their vehicle purchasing decisions are discussed in more detail in Section IV.G.6 below.

f. Vehicle Survival and Use Assumptions

NHTSA’s analysis of fuel savings and related benefits from adopting more stringent fuel economy standards for MYs 2017-2025 passenger cars and light trucks begins by estimating the resulting changes in fuel use over the entire lifetimes of the affected vehicles. The change in total fuel consumption by vehicles produced during each model year is calculated as the difference between their total fuel use over their li fetimes with a higher CAFE standard in effect,DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

601 and their total lifetime fuel consumption under a baseline in which CAFE standards remained at their 2016 levels. The first step in estimating lifetime fuel consumption by vehicles produced during a model year is to calculate the number expected to remain in service during each year following their production and sale. 632 This is calculated by multip lying the number of vehicles originally produced during a model year by the proportion typically expected to remain in service at their age during each later year, often referred to as a “survival rate.”

As discussed in more detail in Section II.B.3 above and in Chapter 1 of the TSD, to estimate production volumes of passenger cars and light trucks for individual manufacturers, NHTSA relied on a baseline market forecast constructed by EPA staff beginning with MY 2008 CAFE certification data. After constructing a MY 2008 baseline, EPA and NHTSA used projected car and truck volumes for this period from Energy Information Administration’s (EIA’s) Annual Energy Outlook (AEO) 2011 in the NPRM analysis. 633 However, Annual Energy Outlook forecasts only total car and light truck sales, rather than sales at the manufacturer and model-specific level, which the agencies require in order to estimate the effects new standards will have on individual manufacturers. 634

To estimate sales of individual car and light truck models produced by each manufacturer, EPA purchased data from CSM Worldw ide and used its projections of the number of vehicles of each type (car or truck) that will be produced and sold by manufacturers in model years 2011 through 2015. 635 This provided year-by-year estimates of the percentage of cars and trucks sold by each manufacturer, as well as the sales percentages accounted for by each vehicle market segment. (The distributions of car an d truck sales by manufacturer and by market segment for the 2016 model year and beyond were assumed to be the same as CSM’s forecast for the 2015 calendar year.) Normalizing these percentages to the total car and light truck sales volumes projected for 2017 through 2025 in AEO 2011 provided manufacturer-specific market

632 Vehicles are defined to be of age 1 during the calendar year corresponding to the model year in which they are produced; thus for example, model year 2000 vehicles are considered to be of age 1 during calendar year 2000, age 2 during calendar year 2001, and to reach their maximum age of 26 years during calendar year 2025. NHTSA considers the maximum lifetime of vehicles to be the age af ter which less than 2 percent of the vehicles originally produced during a model year remain in service. Applyi ng these conventions to vehicle registration data indicates that passenger cars have a maximum age of 26 years, whil e light trucks have a maximum lifetime of 36 years. See Lu, S., NHTSA, Regulatory Analysis and Evaluation Division, “Vehicle Survivability and Travel Mileage Schedules,” DOT HS 809 952, 8–11 (January 2006). Available at http://www-nrd.nhtsa.dot.gov/Pubs/809952.pdf (last accessed Sept. 26, 2011).

633 Available at http://www.eia.gov/forecasts/aeo/index.cfm (last accessed Sept. 26, 2011). NHTSA and EPA made the simplifying assumption that projected sales of cars and light trucks during each calendar year from 2012 through 2016 represented the likely production volumes for the co rresponding model year. The agency did not attempt to establish the exact correspondence between projected sales during individual calendar years and production volumes for specific model years.

634 Because AEO 2011’s “car” and “truck” classes did not reflect NHTSA’s recent reclassification (in March 2009 for enforcement beginning MY 2011) of many two wheel drive SUVs from the non-passenger ( i.e., light truck) fleet to the passenger car fleet, EPA staff made adjustme nts to account for such vehicles in the baseline.

635 EPA also considered other sources of similar informa tion, such as J.D. Powers, and concluded that CSM was better able to provide forecasts at the requisite leve l of detail for most of the model years of interest.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

602 share and model-specific sales estimates for those model years. The volumes were then scaled to AEO 2011 total volume for each year.

To estimate the number of passenger cars and light trucks originally produced during model years 2017 through 2025 that will remain in use during subsequent years, the agency applied age-specific survival rates for cars and light trucks to its forecasts of passenger car and light truck sales for each of those model years. In 2008, NHTSA updated its previous estimates of car and light truck survival rates using the mo st current registration data for vehicles produced during recent model years, in order to ensure that they reflected recent increases in the durability and expected life spans of cars and light trucks. 636 However, the agency does not attempt to forecast changes in those survival rates over the future.

The next step in estimating fuel use is to cal culate the total number of miles that cars and light trucks remaining in use will be driven each year. To estimate the total number of miles driven by cars or light trucks produced in a model year during each subsequent year, the number projected to remain in use duri ng that year is multiplied by the average number of miles those vehicles are expected to be driven at the age they will have reached in that year. The agency estimated annual usage of cars and light trucks of each age using data from the Federal Highway Administration’s 2001 National House hold Transportation Survey (NHTS). 637 Because these estimates reflect the historically low gasoline pr ices that prevailed at the time the 2001 NHTS was conducted, however, NHTSA adjusted them to account for the effect on vehicle use of the higher fuel prices projected ov er the lifetimes of model year 2017-25 cars and light trucks. Details of this adjustment are provided in Chapter VIII of the FRIA and Chapter 4 of the Joint
TSD.

The estimates of annual miles driven at different vehicle ages derived from the 2001 NHTS were also adjusted to reflect projected futu re growth in average use for vehicles at every age over their lifetimes. Increases in average annual use of cars and light trucks, which have averaged approximately 1 percent annually over the past two decades, have been an important source of historical growth in the total number of miles they are driven each year. To estimate future growth in their average annual use for purposes of this rulemaking, NHTSA calculated the rate of growth in the adjusted mileage schedules derived from the 2001 NHTS that would be necessary for total car and light truck travel to increase at the rate forecast in the AEO 2011 Reference Case. 638 This rate was calculated to be consis tent with future changes in the overall size and age distributions of the U.S. passenger car and light truck fleets that result from the agency’s forecasts of total car and light truck sales and updated survival rates. The resulting growth rate in average annual car and light truck use is approximately 1.0 percent from 2017

636 Lu, S., NHTSA, Regulatory Analysis and Evaluation Division, “Vehicle Survivability and Travel Mileage Schedules,” DOT HS 809 952, 8–11 (January 2006). Available at http://www-nrd.nhtsa.dot.gov/Pubs/809952.pdf (last accessed Sept. 26, 2011). These updated survival rate s suggest that the expected lifetimes of recent-model passenger cars and light trucks are 13.8 and 14.5 years.

637 For a description of the Survey, see http://nhts.ornl .gov/introduction.shtml#2001 (last accessed September 26, 2011).

638 This approach differs from that used in the MY 2011 final rule, where it was assumed that future growth in the total number of cars and light trucks in use resulting from pr ojected sales of new vehicles was adequate by itself to account for growth in total vehicle use, without a ssuming continuing growth in average vehicle use.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

603 through 2035, and declines to 0.5 percent per year thereafter. 639 While the adjustment for future fuel prices reduces average annual mileage at each age from the values derived using the 2001 NHTS, the adjustment for expected future growth in average vehicle use increases it. The net effect of these two adjustments is to increa se expected lifetime mileage for MY 2017-25 passenger cars and light trucks by about 22 percent from the estimates originally derived from the 2001 NHTS.

Finally, the agency estimated total fuel consumption by passenger cars and light trucks remaining in use each year by dividing the total number of miles surviving vehicles are driven by the fuel economy they are expected to achieve under each alternative CAFE standard. Each model year’s total lifetime fuel consumption is the sum of fuel use by the cars or light trucks produced during that model year over its life span. In turn, the savings in lifetime fuel use by cars or light trucks produced during each model year affected by this proposed rule that will result from each alternative CAFE standard is the difference between its lifetime fuel use at the fuel economy level it attains under the Baseline alternative, and its lifetime fuel use at the higher fuel economy level it is projected to achieve under that alternative standard. 640

g. Accounting for the Fuel Economy Rebound Effect

The fuel economy rebound effect refers to the fact that some of the fuel savings expected to result from higher fuel economy, such as an increase in fuel economy required by the adoption of higher CAFE standards, may be offset by additional vehicle use. The increase in vehicle use occurs because higher fuel economy reduces the fuel cost of driving, which is typically the largest single component of the monetary cost of operating a vehicle, and vehicle owners respond to this reduction in operating costs by driving more. Even with their higher fuel economy, this additional driving consumes some fuel , so this effect reduces the fuel savings that result when raising CAFE standards requires manufacturers to improve fuel economy. The rebound effect refers to the fraction of fuel savings expected to result from increased fuel economy that is offset by additional driving. 641

639 While the adjustment for future fuel prices reduces average mileage at each age from the values derived from the 2001 NHTS, the adjustment for expected future growth in average vehicle use increases it. The net effect of these two adjustments is to increase expect ed lifetime mileage by about 18 percen t significantly for both passenger cars and about 16 percent for light trucks.

640 To illustrate these calculations, the agency’s adjustment of the AE O 2009 Revised Reference Case forecast indicates that 9.26 million passenger cars will be produced during 2012, and the agency’s updated survival rates show that 83 percent of these vehicles, or 7.64 million, are projected to remain in service during the year 2022, when they will have reached an age of 10 years. At that age, passenger achieving the fuel economy level they are projected to achieve under the Baseline alternative are driv en an average of about 800 miles, so surviving model year 2012 passenger cars will be driven a total of 82.5 bi llion miles (= 7.64 million surviving vehicles × 10,800 miles per vehicle) during 2022. Summing the results of sim ilar calculations for each year of their 26-year maximum lifetime, model year 2012 passenger cars will be driven a total of 1,395 billion miles under the Baseline alternative. Under that alternative, they are projected to achieve a te st fuel economy level of 32.4 mpg, which corresponds to actual on-road fuel economy of 25.9 mpg (= 32.4 mpg × 80 per cent). Thus their lifetime fuel use under the Baseline alternative is projected to be 53.9 billion gallons (= 1,395 billion miles divided by 25.9 miles per gallon).

641 Formally, the rebound effect is often expressed as the elas ticity of vehicle use with respect to the cost per mile driven. Additionally, it is consistently expressed as a posi tive percentage (rather than as a negative decimal fraction, as this elasticity is normally expressed).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

604 The magnitude of the rebound effect is an important determinant of the actual fuel savings that are likely to result from adopting stricter CAFE standards. Research on the magnitude of the rebound effect in light-duty vehicle use dates to the early 1980s, and generally concludes that a significant rebound effect o ccurs when vehicle fuel efficiency improves. 642 The most common approach to estimating its magnitude has been to analyze survey data on household vehicle use, fuel consumption, fuel pri ces, and other factors affecting household travel behavior to estimate the response of vehicle use to differences in the fuel efficiency of individual vehicles. Because this approach most closely ma tches the definition of the rebound effect, which is the response of vehicle use to differences in fuel economy, the agency regards these studies as likely to produce the most reliable estimates of the rebound effect. Other studies have relied on econometric analysis of annual U.S. data on vehi cle use, fuel efficiency, fuel prices, and other variables to estimate the response of total or average vehicle use to changes in fleet-wide average fuel economy and its effect on fuel cost per mile driven. More recent studies have analyzed yearly variation in vehicle ownership and use, fu el prices, and fuel economy among states over an extended time period in order to measure the response of vehicle use to changing fuel costs per mile. 643

Another important distinction among studies of the rebound effect is whether they assume that the effect is constant, or allow it to vary in response to changes in fuel costs, personal income, or vehicle ownership. Most st udies using aggregate annual data for the U.S. assume a constant rebound effect, although some of th ese studies test whether the effect varies as changes in retail fuel prices or average fuel effi ciency alter fuel cost per mile driven. Studies using household survey data estimate significantly different rebound effects for households owning varying numbers of vehicles, with most concluding that the rebound effect is larger among households that own more vehicles. Fi nally, recent studies using state-level data conclude that the rebound effect varies directly in response to changes in personal income, the degree of urbanization of U.S. citie s, and differences in traffic congestion levels, as well as fuel costs. Some studies conclude that the long-run rebound effect is significantly larger than the immediate response of vehicle use to increased fu el efficiency. Although their estimates of the time required for the rebound effect to reach its long-run magnitude vary, this long-run effect is probably more appropriate for evaluating the fuel savings likely to result from adopting stricter CAFE standards for future model years.

In order to provide a more comprehensive overview of previous estimates of the rebound effect, NHTSA has updated its previous review of published studies of the rebound effect to include those conducted as recently as 2010. The agency performed a detailed analysis of several dozen separate estimates of the long-run rebound effect reported in these studies, which

642 Some studies estimate that the long-run rebound effect is significantly larger than the immediate response to increased fuel efficiency. Although their estimates of the adjustment period required for the rebound effect to reach its long-run magnitude vary, this long-run effect is proba bly more appropriate for evaluating the fuel savings and emissions reductions resulting from stricter sta ndards that would apply to future model years.

643 In effect, these studies treat U.S. states as a data “p anel” by applying appropriate estimation procedures to data consisting of each year’s aver age values of these variables for the separate states.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

605 is summarized in Error! Reference source not found. below. 644 As the table indicates, these estimates range from as low as 7 percent to as high as 75 percent, with a mean value of 23% percent. Both the type of data used and authors’ assumption about whether the rebound effect varies over time have important effects on its estimated magnitude. The 34 estimates derivedfrom analysis of U.S. annual time-series data produce a mean estimate of 18 percent for the longrun rebound effect, while the mean of 23 estimates based on household survey data is considerably larger (31 percent), and the mean of 15 estimates based on pooled state data (23 percent) is close to that for the entire sample. The 37 estimates assuming a constant rebound effect produce a mean of 23 percent, identical to the mean of the 29 estimates reported in studies that allowed the rebound effect to vary in response to fuel prices and fuel economy levels, vehicle ownership, or household income. Updated to reflect the most recent available information on these variables, the mean of these estimates is 19 percent, as Table IV.C.3-3 reports.

T ABLE IV.C.3-3. S UMMARY OF P UBLISHED E STIMATES OF THE R EBOUND E FFECT

Some recent studies provide evidence that the rebound effect has been declining over time. This result appears plausible for two reason s: first, the responsiveness of vehicle use to variation in fuel costs would be expected to decline as they account for a smaller proportion of the total monetary cost of driving, which has been the case until recently. Second, rising personal incomes would be expected to reduce the sensitivity of vehicle use to fuel costs as the time component of driving costs—which is likely to be related to income levels—accounts for a larger fraction the total cost of automobile travel. At the same time, however, rising incomes are strongly associated with higher auto ownershi p levels, which increase households’ opportunities to substitute among vehicles in response to varying fuel prices and differences in their fuel economy levels. This is likely to increase the sensitivity of households’ overall vehicle use to differences in the fuel economy levels of individual vehicles.

644 In some cases, NHTSA derived estimates of the overall rebound effect from more detailed results reported in the studies. For example, where studies estimated differen t rebound effects for households owning different numbers of vehicles but did not report an overall value, the agency computed a weighted average of the reported values using the distribution of households am ong vehicle ownership categories.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

606 Small and Van Dender combined time series data for states to estimate the rebound effect, allowing its magnitude to vary in resp onse to fuel prices, fleet-wide average fuel economy, the degree of urbanization of U. S. cities, and personal income levels. 645 The authors employ a model that allows the effect of fuel cost per mile on vehicle use to vary in response to changes in personal income levels and increasing urbanization of U.S. cities. For the time period 1966-2001, their analysis implied a long-run rebound effect of 22 percent, which is consistent with previously published studies. Continued growth in personal incomes over this period reduces their estimate of the long-run rebound effect during its last five years (1997-2001) to 11 percent, and an unpublished update through 2004 pr epared by the authors reduced their estimate of the long-run rebound effect for the period 2000-2004 to 6 percent. 646

More recently, Hymel, Small and Van Dender extended the previous analysis to include traffic congestion levels in urbanized areas. 647 Although controlling for the effect of congestion on vehicle use increased their estimates of the re bound effect, these authors also found that the rebound effect appeared to be declining over time. For the time period 1966-2004, their estimate of the long-run rebound effect was 24 percent, while for the last year of that period their estimate was 13 percent, significantly above the previous Small and Van Dender estimate of a 6 percent rebound effect for the period 2000-2004.

Recent research by Greene (under contract to EPA) using U.S. national time-series data for the period 1966-2007 lends further support to the hypothesis that the rebound effect is declining over time. 648 Greene found that fuel prices had a statistically significant impact on VMT, yet fuel efficiency did not, and statisti cal testing rejected the hypothesis of equal elasticities of vehicle use with respect to gasoline prices and fuel efficiency. Greene also tested model formulations that allowed the effect of fu el cost per mile on vehicle use to decline with rising per capita income; his preferred form of this model produced estimates of the rebound effect that declined from [XX] percent in [XX] to 12 percent in 2007.

In light of findings from recent research, th e agency’s judgment is that the apparent decline over time in the magnitude of the rebound effect justifies using a value for future analysis that is lower than many historical estimates, which average 15–25 percent. Because the lifetimes of vehicles affected by the alternative CAFE st andards considered in this rulemaking will extend from 2017 until 2060, a value that is at the low end of historical estimates appears to be appropriate. Thus as it elected to do in its previous analysis of the effects of raising CAFE standards for MY 2012-16 cars and light trucks, NHTSA uses a 10 percent rebound effect in its analysis of fuel savings and other benefits from higher CAFE standards for MY 2017-25

645 Small, K. and K. Van Dender, 2007a . “Fuel Efficiency and Motor Vehicle Travel: The Declining Rebound Effect”, The Energy Journal, vol. 28, no. 1, pp. 25-51.

646 Small, K. and K. Van Dender, 2007b. "Long Run Tr ends in Transport Demand, Fuel Price Elasticities and Implications of the Oil Outlook for Transport Policy," OECD/ITF Joint Transport Research Centre Discussion Papers 2007/16, OECD, International Transport Forum.

647 Hymel, Kent M., Kenneth A. Small, and Kurt Van Dender, “Induced demand and rebound effects in road transport,” Transportation Research Part B: Methodologi cal, Volume 44, Issue 10, December 2010, Pages 1220- 1241, ISSN 0191-2615, DOI: 10.1016/j.trb.2010.02.007.

648 Greene, David, “Rebound 2007: Analysis of National Li ght-Duty Vehicle Travel Statistics,” February 9, 2010. This paper has been accepted for an upcoming special issu e of Energy Policy, although the publication date has not yet been determined.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

607 vehicles. Recognizing the wide range of uncerta inty surrounding its correct value, however, the agency also employs estimates of the rebound effect ranging from 5 to 15 percent in its sensitivity testing. The 10 percent figure is at the low end of those reported in almost all previous research, and it is also below most estim ates of the historical and current magnitude of the rebound effect developed by NHTSA. However, other recent research—particularly that conducted by Small and Van Dender and by Greene—suggests that the magnitude of the rebound effect has declined over time, and is likely to continue to do so. As a consequence, NHTSA concluded that a value at the low end of the historic al estimates reported here is likely to provide a more reliable estimate of its magnitude during the future period spanned by NHTSA’s analysis of the impacts of this rule. The 10 percent estimate lies between the 10–30 percent range of estimates for the historical rebound effect reported in most previous research, and is at the upper end of the 5–10 percent range of estimates for the future rebound effect reported in recent studies. In summary, the 10 percent value was not derived from a single estimate or particular study, but instead represents a compromise betw een historical estimates and projected future estimates. Chapter 4.2.5 of the Joint TSD review s the relevant literature and discusses in more depth the reasoning for the rebound value used here.

h. Benefits From Increased Vehicle Use

The increase in vehicle use from the rebound effect provides additional benefits to their users, who make more frequent trips or travel fart her to reach more desirable destinations. This additional travel provides benefits to drivers and their passengers by improving their access to social and economic opportunities away from home. As evidenced by their decisions to make more frequent or longer trips when improved fuel economy reduces their costs for driving, the benefits from this additional travel exceed the costs drivers and passengers incur in traveling these additional distances.

The agency’s analysis estimates the economic benefits from increased rebound-effect driving as the sum of fuel costs drivers incur plus the consumer surplus they receive from the additional accessibility it provides. 649 NHTSA estimates the value of the consumer surplus provided by added travel as one-half of the product of the decline in fuel cost per mile and the resulting increase in the annual number of miles driven, a standard approximation for changes in consumer surplus resulting from small changes in prices. Because the increase in travel depends on the extent of improvement in fuel economy, the value of benefits it provides differs among model years and alternative CAFE standards.

i. The Value of Increased Driving Range

Improving vehicles’ fuel economy may also increase their driving range before they require refueling. By extending the upper limit of the range vehicles can travel before refueling

649 The consumer surplus provided by added travel is estimate d as one-half of the product of the decline in fuel cost per mile and the resulting increase in the annual number of miles driven.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

608 is needed, the per-vehicle average number of refueli ng trips per year is expected to decline. This reduction in refueling frequency provides a time savings benefit to owners. 650

NHTSA estimated a number of parameters regarding consumers’ refueling habits using newly-available observational and interview data from a 2010-2011 NASS study conducted at fueling stations throughout the nation. A (non-exhaustive) list of key parameters derived from this study is as follows: average number of gallon s of fuel purchased, length of time to refuel and pay, length of time to drive to the fueling sta tion, primary reason for refueling, and number of adult vehicle occupants.

Using these and other parameters (detailed explanation of parameters and methodology provided in Chapter VIII of NHTSA’s PRIA), NHTSA estimated the decrease in number of refueling cycles for each model year’s fleet attributable to improvements in actual on-road MPG resulting from the proposed CAFE standards. NHTSA acknowledges – and adjusts for – the fact that many refueling trips occur for reasons other than a low reading on the gas gauge (for example, many consumers refuel on a fixed schedule). NHTSA separately estimated the value of vehicle-hour refueling time and applied this to the projected decrease in number of refueling cycles to estimate the aggregate fleet-wide value of refueling time savings for each year that a given model year’s vehicles are expected to remain in service.

j. Added Costs From Congestion, Crashes and Noise

Increased vehicle use associated with the re bound effect also contributes to increased traffic congestion, motor vehicle accidents, and highway noise. To estimate the economic costs associated with these consequences of added driving, NHTSA applies estimates of per-mile congestion, accident, and noise costs caused by increased use of automobiles and light trucks developed previously by the Federal Highway Administration. 651 These values are intended to measure the increased costs resulting from added congestion and the delays it causes to other drivers and passengers, property damages and injuries in traffic accidents, and noise levels contributed by automobiles and light trucks. NH TSA previously employed these estimates in its analysis accompanying the MY 2011 final CAFE rule, as well as in its analysis of the effects of higher CAFE standards for MY 2012-16. After reviewing the procedures used by FHWA to develop them and considering other available esti mates of these values, the agency continues to find them appropriate for use in this final rule . The agency multiplies FHWA’s estimates of permile costs by the annual increases in automobile and light truck use from the rebound effect to yield the estimated increases in congestion, accident, and noise externality costs during each future year.

k. Petroleum Consumption and Import Externalities

i. Changes in Petroleum Imports

650 If manufacturers respond to improved fuel economy by reducing the size of fuel tanks to maintain a constant driving range, the resulting cost saving will presumab ly be reflected in lower vehicle sales prices.

651 These estimates were developed by FHWA for use in its 1997 Federal Highway Cost Allocation Study; See http://www.fhwa.dot.gov/policy/hcas/final/index.htm (last accessed March 1, 2010).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

609 Based on a detailed analysis of differences in fuel consumption, petroleum imports, and imports of refined petroleum products among alternative scenarios presented in AEO 2011, NHTSA estimates that approximately 50 percent of the reduction in fuel consumption resulting from adopting higher CAFE standards is likely to be reflected in reduced U.S. imports of refined fuel, while the remaining 50 percent would reduce domestic fuel refining. 652 Of this latter figure, 90 percent is anticipated to reduce U.S. imports of crude petroleum for use as a refinery feedstock, while the remaining 10 percent is expected to reduce U.S. domestic production of crude petroleum. 653 Thus on balance, each 100 gallons of fuel saved as a consequence of higher CAFE standards is anticipated to reduce total U.S. imports of crude petroleum or refined fuel by 95 gallons. 654

ii. Benefits from Reducing U.S. Petroleum Imports

U.S. consumption and imports of petroleum products impose costs on the domestic economy that are not reflected in the market price for crude petroleum, or in the prices paid by consumers of petroleum products such as gasoline. These costs include (1) higher prices for petroleum products resulting from the effect of U.S. petroleum demand on the world oil price;(2) the risk of disruptions to the U.S. economy caused by sudden reductions in the supply of imported oil to the U.S.; and (3) expenses for maintaining a U.S. military presence to secure imported oil supplies from unstable regions, and for maintaining the strategic petroleum reserve (SPR) to cushion against resulting price increases. 655 Reducing these costs by lowering U.S. petroleum imports represents another source of be nefits from stricter CAFE standards and the savings in consumption of petroleum-based fuels that would result from higher fuel economy. Higher U.S. imports of crude oil or refined petroleum products increase the magnitude of these external economic costs, thus increasing the true economic cost of supplying transportation fuels above their market prices. Conversely, loweri ng U.S. imports of crude petroleum or refined fuels by reducing domestic fuel consumption can reduce these external costs, and any reduction in their total value that results from improved fuel economy represents an economic benefit of more stringent CAFE standards, in addition to the value of saving fuel itself.

652 Differences in forecast annual U.S. imports of crude pe troleum and refined products among the Reference, High Oil Price, and Low Oil Price scenarios analyzed in EIA’s Annual Energy Outlook 2011 range from 35-74percent of differences in projected annual gasoline and diesel fu el consumption in the U.S. These differences average 53percent over the forecast period spanned by AEO 2011.

653 Differences in forecast annual U.S. imports of crude petroleum among the Reference, High Oil Price, and Low Oil Price scenarios analyzed in EIA’s Annual Energy Outlook 2011 ( range from 67-104 percent of differences in total U.S. refining of crude petroleum, and average 90 percent over the forecast period spanned by AEO 2011.

654 This figure is calculated as 50 gallons + 50 gallons*90% = 50 gallons + 45 gallons = 95 gallons.

655 See, e.g., Bohi, Douglas R. and W. David Montgomery (1982). Oil Prices, Energy Security, and Import Policy Washington, DC: Resources for the Future, Johns Hopkins University Press; Bohi, D.R., and M.A. Toman (1993). “Energy and Security: Externalities and Policies,” Ener gy Policy 21:1093– 1109 (Docket NHTSA–2009–0062–24); and Toman, M.A. (1993). “The Economics of Energy Security: Theory, Evidence, Policy,” in A.V. Kneese and J.L. Sweeney, eds. (1993) (Docket NHTSA–2009–0062–23). Han dbook of Natural Resource and Energy Economics, Vol. III. Amsterdam: North-Holland, pp. 1167–1218.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

610 The first component of the external costs imposed by U.S. petroleum consumption and imports (often termed the “monopsony cost” of U.S. oil imports), measures the increase in payments from domestic oil consumers to foreign oil suppliers beyond the increased purchase price of petroleum itself that results when increas ed U.S. import demand raises the world price of petroleum. 656 However, this monopsony cost or premium represents a financial transfer from consumers of petroleum products to oil producers, and does not entail the consumption of real economic resources. Thus the decline in its value that occurs when reduced U.S. demand for petroleum products causes a decline in global petroleum prices produces no savings in economic resources globally or domestically, although it does reduce the value of the financial transfer from U.S. consumers of petroleum products to foreign suppliers of petroleum. Accordingly, NHTSA’s analysis of the benefits from adopting proposed CAFE standards for MY 2017–2025 cars and light trucks excludes the reduced value of monopsony payments by U.S. oil consumers that would result from lower fuel consumption.

The second component of external costs imposed by U.S. petroleum consumption and imports reflects the potential costs to the U.S. economy from disruptions in the supply of imported petroleum. These costs arise because interruptions in the supply of petroleum products reduces U.S. economic output, as well as because fi rms are unable to adjust prices, output levels, and their use of energy, labor and other inputs smoothly and rapidly in response to the sudden changes in prices for petroleum products that are caused by interruptions in their supply. Reducing U.S. petroleum consumption and imports lowers these potential costs, and the amount by which it does so represents an economic benefit in addition to the savings in fuel costs that result from higher fuel economy. NHTSA estimates and includes this value in its analysis of the economic benefits from adopting higher CAFE standards for MY 2017–2025 cars and light trucks.

The third component of external costs imposed by U.S. petroleum consumption and imports includes expenses for maintaining a U.S. military pr esence to secure imported oil supplies from unstable regions, and for maintaining the strategic petroleum reserve (SPR) to cushion against resulting price increases. NHTSA r ecognizes that potential national and energy security risks exist due to the possibility of tens ion over oil supplies. Much of the world’s oil and gas supplies are located in countries facing social, economic, and demographic challenges, thus making them even more vulnerable to potential local instability. Because of U.S. dependence on oil, the military could be called on to protect energy resources through such measures as securing shipping lanes from foreign oil fields. Thus, to the degree to which the proposed rules reduce reliance upon imported energy supplies or promotes the development of technologies that can be deployed by either consumers or the nation’s defense forces, the United States could expect benefits related to national security, reduced energy costs, and increased energy supply. Although NHTSA recognizes that there clearly is a benefit to the United States from reducing dependence on foreign oil, we have been unable to calculate the monetary benefit that the United States will receive from the improv ements in national security expected to result from this program. We have therefore included only the macroeconomic disruption portion of the energy security benefits to estimate the monetary value of the total energy security benefits of this program. We have calculated energy security in very specific terms, as the reduction of

656 The reduction in payments from U.S. oil purchasers to dom estic petroleum producers is not included as a benefit, since it represents a transfer that o ccurs entirely within the U.S. economy.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

611 both financial and strategic risks caused by potential sudden disruptions in the supply of imported petroleum to the U.S. Reducing the am ount of oil imported reduces those risks, and thus increases the nation’s energy security.

Similarly, while the costs for building a nd maintaining the SPR are more clearly attributable to U.S. petroleum consumption and im ports, these costs have not varied historically in response to changes in U.S. oil import levels. Thus the agency has not attempted to estimate the potential reduction in the cost for maintainin g the SPR that might result from lower U.S. petroleum imports, or to include an estimate of this value among the benefits of reducing petroleum consumption through higher CAFE standards.

In analyzing benefits from its recent actions to increase light truck CAFE standards for model years 2005–07 and 2008–11, NHTSA relied on a 1997 study by Oak Ridge National Laboratory (ORNL) to estimate the value of reduced economic externalities from petroleum consumption and imports. 657 More recently, ORNL updated its estimates of the value of these externalities, using the analytic framework developed in its original 1997 study in conjunction with recent estimates of the variables and parameters that determine their value. 658 The updated ORNL study was subjected to a detailed peer review commissioned by EPA, and ORNL’s estimates of the value of oil import externalitie s were subsequently revised to reflect their comments and recommendations of the peer reviewers. 659 Finally, at the request of EPA, ORNL has repeatedly revised its estimate s of external costs from U.S. oil imports to reflect changes in the outlook for world petroleum prices, as well as continuing changes in the structure and characteristics of global petroleum supply and demand.

As the preceding discussion indicates, NHTSA’s analysis of benefits from adopting higher CAFE standards includes only the re duction in economic disruption costs that is anticipated to result from reduced consumption of petroleum-based fuels and the associated decline in U.S. petroleum imports. ORNL’s updated analysis reports that this benefit, which is in addition to the savings in costs for producing fuel itself, is most likely to amount to $0.185 per gallon of fuel saved by requiring MY 2017-25 cars and light trucks to achieve higher fuel economy. However, considerable uncertainty surrounds this estimate, and ORNL’s updated analysis also indicates that a range of values extending from a low of $0.091 per gallon to a high of $0.293 per gallon should be used to reflect this uncertainty.

l. Air Pollutant Emissions

657 Leiby, Paul N., Donald W. Jones, T. Randall Curlee, and Russell Lee, Oil Imports: An Assessment of Benefits and Costs, ORNL–6851, Oak Ridge National Laboratory, November 1, 1997. Available at http://www.esd.ornl.gov/eess/energy_a nalysis/files/ORNL6851.pdf (last accessed October 11, 2011).

658 Leiby, Paul N. “Estimating the Energy Security Bene fits of Reduced U.S. Oil Imports,” Oak Ridge National Laboratory, ORNL/TM–2007/028, Revised July 23, 2007. Available at http://www.esd.ornl.gov/eess/energy_analysis/files/Le iby2007%20Estimating%20the%20Energy%20Security%20B
enefits%20of%20Reduced%2 0U.S.%20Oil%20Imports%2 0ornl-tm-2007-028%20rev20 07Jul25.pdf (last accessed October 11, 2011).

659 Peer Review Report Summary: Estimating the Energy Security Benefits of Reduced U.S. Oil Imports, ICF, Inc., September 2007. Available at Docket No. NHTSA–2009–0059–0160.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

612 i. Changes in Criteria Air Pollutant Emissions

Criteria air pollutants include carbon monoxide (CO), hydrocarbon compounds (usually referred to as “volatile organic compounds,” or VOC), nitrogen oxides (NO X ), fine particulate matter (PM 2.5 ), and sulfur oxides (SO X ). These pollutants are emitted during vehicle storage and use, as well as throughout the fuel production and distribution system. While reductions in domestic fuel refining, storage, and distributi on that result from lower fuel consumption will reduce emissions of these pollutants, additional vehicle use associated with the fuel economy rebound effect will increase their emissions. Th e net effect of stricter CAFE standards on total emissions of each criteria pollutant depends on the relative magnitudes of reductions in its emissions during fuel refining and distribution, and increases in its emissions resulting from additional vehicle use. Because the relationship between emissions in fuel refining and vehicle use is different for each criteria pollutant, the net effect of fuel savings from the proposed standards on total emissions of each pollutant is likely to differ.

With the exception of SO 2 , NHTSA calculated annual emissi ons of each criteria pollutant resulting from vehicle use by multiplying its estimates of car and light truck use during each year over their expected lifetimes by per-mile emission rates for each vehicle class, fuel type, model year, and age. These emission rates were developed by U.S. EPA using its Motor Vehicle Emission Simulator (MOVES 2010a). 660 Emission rates for SO 2 were calculated by NHTSA using average fuel sulfur content estimates suppli ed by EPA, together with the assumption that the entire sulfur content of fuel is emitted in the form of SO 2

. 661 Total SO 2 emissions under each alternative CAFE standard were calculated by ap plying the resulting emission rates directly to estimated annual gasoline and diesel fuel use by cars and light trucks.

Changes in emissions of criteria air pollutants re sulting from alternative increases in CAFE standards for MY 2017–2025 cars and light trucks are calculated from the differences between emissions under each alternative increase in CAFE standards, and emissions under the baseline alternative.

Emissions of criteria air pollutants also o ccur during each phase of fuel production and distribution, including crude oil extraction and tran sportation, fuel refining, and fuel storage and transportation. NHTSA estimates the reductions in criteria pollutant emissions from producing and distributing fuel that would occur under a lternative CAFE standards using emission rates obtained by EPA from Argonne National Laboratories’ Greenhouse Gases and Regulated Emissions in Transportation (GREET) model, wh ich provides estimates of air pollutant emissions that occur in different phases of fuel production and distribution 662, 663 EPA modified

660 The MOVES model assumes that the per-mile rates at which these pollutants are emitted are determined by EPA regulations and the effectiveness of catalytic after-treatment of engine exhaust emissions, and are thus unaffected by changes in car and light truck fuel economy.

661 These are 30 and 15 parts per million (ppm, measured on a mass basis) for gasoline and diesel respectively, which produces emission rates of 0.17 grams of SO 2 per gallon of gasoline and 0.10 grams per gallon of diesel.

662 Argonne National Laboratories, The Greenhouse Gas and Regulated Emissions from Transportation (GREET) Model, Version 1.8, June 2007, available at http://www.transportation.anl.gov/mode ling_simulation/GREET/index.html (last accessed October 11, 2011).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

613 the GREET model to change certain assumptions about emissions during crude petroleum extraction and transportation, as well as to upda te its emission rates to reflect adopted and pending EPA emission standards.

The resulting emission rates were applied to the agency’s estimates of fuel consumption under alternative CAFE standards to develop es timates of total emissions of each criteria pollutant during fuel production and distribution. The agency then employed the estimates of the effects of changes in fuel consumption on domestic and imported sources of fuel supply discussed previously to calculate the effects of reductions in fuel use on changes in imports of refined fuel and domestic refining. NHTSA’s an alysis assumes that reductions in imports of refined fuel would reduce criteria pollutant emissi ons during fuel storage and distribution only. Reductions in domestic fuel refining using impo rted crude oil as a feedstock are assumed to reduce emissions during fuel refining, storage, and distribution. Finally, reduced domestic fuel refining using domestically-produced crude oil is assumed to reduce emissions during all four phases of fuel production and distribution. 664

Finally, NHTSA calculated the net changes in domestic emissions of each criteria pollutant by summing the increases in emissions projected to result from increased vehicle use, and the reductions anticipated to result from lo wer domestic fuel refining and distribution. 665 As indicated previously, the effect of adopting hi gher CAFE standards on total emissions of each criteria pollutant depends on the relative magnit udes of the resulting reduction in emissions from fuel refining and distribution, and the increas e in emissions from additional vehicle use. Although these net changes vary significantly among individual criteria pollutants, the agency projects that on balance, adopting higher CAFE standards for MY 2017-25 cars and light trucks would reduce emissions of all criteria ai r pollutants except carbon monoxide (CO).

The net changes in direct emissions of fine particulates (PM 2.5 ) and other criteria pollutants that contribute to the formation of “secondary” fine particulates in the atmosphere (such as NO X , SO X , and VOCs) are converted to economic values using estimates of the reductions in health damage costs per ton of emissions of each pollutant that is avoided, which were developed by EPA. These savings represent the estimated reductions in the value of damages to human health resulting from lower atmospheric concentrations and population exposure to air pollution that occur when emissions of each pollutant that contributes to

663 Emissions that occur during vehicle refueling at retail gasoline stations (primarily evaporative emissions of volatile organic compounds, or VOCs) are already accounted fo r in the “tailpipe” emission factors used to estimate the emissions generated by increased light truck use. GREET estimates emissions in each phase of gasoline production and distribution in mass per unit of gasoline ener gy content; these factors are then converted to mass per gallon of gasoline using the average energy content of gasoline.

664 In effect, this assumes that the distances crude oil travel s to U.S. refineries are approximately the same regardless of whether it travels from domestic oilfields or import termin als, and that the distances that gasoline travels from refineries to retail stations are approximately the same as those from import terminals to gasoline stations. We note that while assuming that all changes in upstream emissions result from a decrease in petroleum production and transport, our analysis of downstream criteria pollutant impacts assumes no change in the composition of the gasoline fuel supply.

665 All emissions from increased vehicle use are assumed to occur within the U.S., since CAFE standards would apply only to vehicles produced for sale in the U.S.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

614 atmospheric PM 2.5 concentrations are reduced. The value of reductions in the risk of premature death due to exposure to fine particulate pollution (PM 2.5 ) account for a majority of EPA’s estimated values of reducing criteria pollutant emissions, although the value of avoiding other health impacts is also included in these estimates.

These values do not include a number of unquantified benefits, such as reduction in the welfare and environmental impacts of PM 2.5 pollution, or reductions in health and welfare impacts related to other criteria air pollutants (ozone, NO 2 , and SO 2 ) and air toxics. EPA estimates different per-ton values for reducing emissions of PM and other criteria pollutants from vehicle use than for reductions in emissions of those same pollutants during fuel production and distribution. 666 NHTSA applies these separate values to its estimates of changes in emissions from vehicle use and from fuel production and distribution to determine the net change in total economic damages from emissions of these pollutants.

EPA projects that the per-ton values for redu cing emissions of criteria pollutants from both mobile sources (including motor vehicles) and stationary sources such as fuel refineries and storage facilities will increase over time. These pr ojected increases reflect rising income levels, which are assumed to increase affected individuals’ willingness to pay for reduced exposure to health threats from air pollution, as well as future population growth, which increases population exposure to future levels of air pollution.

ii. Reductions in CO 2 Emissions

Emissions of carbon dioxide and other gr eenhouse gases (GHGs) occur throughout the process of producing and distributing transportation fuels, as well as from fuel combustion itself. Emissions of GHGs also occur in generating electricity, which NHTSA’s analysis anticipates will account for an increasing share of energy consumption by cars and light trucks produced in the model years that would be subject to their proposed rules. By reducing the volume of fuel consumed by passenger cars and light truc ks, higher CAFE standards will reduce GHG emissions generated by fuel use, as well as throughout the fuel supply system. Lowering these emissions is likely to slow the projected pace and reduce the ultimate extent of future changes in the global climate, thus reducing future economic damages that changes in the global climate are expected to cause. By reducing the probability th at climate changes with potentially ca tastrophic economic or environmental impacts will occur, lowering GHG emissions may also result in economic benefits that exceed the resulting reduc tion in the expected future economic costs caused by more gradual changes in the earth’s climatic systems.

Quantifying and monetizing benefits from reducing GHG emissions is thus an important step in estimating the total econom ic benefits likely to result from establishing higher CAFE standards. Because carbon dioxide emissions account for nearly 95 percent of total GHG emissions that result from fuel combustion during vehicle use, NHTSA’s analysis of the effect of higher CAFE standards on GHG emissions focuses mainly on estimating changes in emissions of CO 2 . The agency estimates emissions of CO 2 from passenger car and light truck use by

666 These reflect differences in the typical geographic distribut ions of emissions of each pollutant, their contributions
to ambient PM 2.5 concentrations, pollution levels (predominantly those of PM 2.5 ), and resulting changes in population exposure.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

615 multiplying the number of gallons of each type of fuel (gasoline and diesel) they are projected to consume under alternative CAFE standards by the quantity or mass of CO 2 emissions released per gallon of fuel consumed. This calculation assumes that the entire carbon content of each fuel is converted to CO 2 emissions during the combustion process.

NHTSA estimates emissions of CO 2 that occur during fuel production and distribution using emission rates for each stage of this process (feedstock production and transportation, fuel refining and fuel storage and distribution) derived from Argonne National Laboratories’ Greenhouse Gases and Regulated Emissions in Tran sportation (GREET) model. For liquid fuels, NHTSA converts these rates to a per-gallon basi s using the energy content of each fuel, and multiplies them by the number of gallons of each type of fuel produced and consumed under alternative standards to estimate total CO 2 emissions from fuel production and distribution. GREET supplies emission rates for electricity ge neration that are expressed as grams of CO 2 per unit of energy, so these rates are simply multiplied by the estimates of electrical energy used to charge the on-board storage batteries of plug-in hybri d and battery electric vehicles. As with all other effects of alternative CAFE standards, the reduction in CO 2 emissions resulting from each alternative increase in standards is measured by the difference in total emissions from producing and consuming fuel energy used by MY 2017-25 cars and light trucks with those higher CAFE standards in effect, and total CO 2 emissions from supplying and using fuel energy consumed under the baseline alternative. Unlike criteria pollutants, the agency’s estimates of CO 2 emissions include those occurring in domestic fuel production and consumption, as well as in overseas production of petroleum and refined fuel fo r export to the U.S. Overseas emissions are included because GHG emissions throughout the world contribute equally to the potential for changes in the global climate.

iii. Economic Value of Reductions in CO 2 Emissions

NHTSA takes the economic benefits from reducing CO 2 emissions into account in developing and analyzing the alternative CAFE standards it has considered for MY 2017-25. Because research on the impacts of climate change does not produce direct estimates of the economic benefits from reducing CO 2 or other GHG emissions, these benefits are assumed to be the “mirror image” of the estimated incremental costs resulting from increases in emissions. Thus the benefits from reducing CO 2 emissions are usually measured by the savings in estimated economic damages that an equivalent increase in emissions would otherwise have caused. The agency does not include estimates of the economic benefits from reducing GHGs other than CO 2 in its analysis of alternative CAFE standards.

NHTSA estimates the value of the reductions in emissions of CO 2 resulting from adopting alternative CAFE standards using a measure referred to as the “social cost of carbon,” abbreviated SCC. The SCC is intended to provide a monetary measure of the additional economic impacts likely to result from changes in the global climate that would result from an incremental increase in CO 2 emissions. These potential effects include changes in agricultural productivity, the economic damages caused by adverse effects on human health, property losses and damages resulting from rising sea levels, and the value of ecosystem services. The SCC is expressed in constant dollars per additional metric ton of CO 2 emissions occurring during aDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

616 specific year, and is higher for more distant future years because the damages caused by an additional ton of emissions increase with larger concentrations of CO 2 in the earth’s atmosphere.

Reductions in CO 2 emissions that are projected to result from lower fuel production and consumption during each year over the lifetimes of MY 2017-25 cars and light trucks are multiplied by the estimated SCC appropriate for that year to determine the economic benefit from reducing emissions during that year. The ne t present value of these annual benefits is calculated using a discount rate that is consistent with that used to develop the estimate of each SCC estimate. This calculation is repeated for the reductions in CO 2 emissions projected to result from each alternative increase in CAFE standards.

NHTSA’s evaluates the economic benefits from reducing CO 2 emissions using estimates of the SCC developed by an interagency working group convened for the specific purpose of developing new estimates for use by U.S. Federal agencies in regulatory evaluations. The group’s purpose in developing new estimates of the SCC was to allow Federal agencies to incorporate the social benefits of reducing CO 2 emissions into cost-benefit analyses of regulatory actions that have relatively modest impacts on cumulative global emissions, as most Federal regulatory actions can be expected to have. NHTSA previously relied on the SCC estimates developed by this interagency group to analyze the alternative CAFE standards it considered for MY 2012-16 cars and light trucks, as well as the fuel efficiency standards it adopted for MY 014-18 heavy-duty vehicles.

The interagency group convened on a regular basis over the period from June 2009 through February 2010, to explore technical literature in relevant fields and develop key inputs and assumptions necessary to generate estimates of the SCC. Agencies participating in the interagency process included the Environmental Protection Agency and the Departments of Agriculture, Commerce, Energy, Transportation, and Treasury. This process was convened by the Council of Economic Advisers and the Office of Management and Budget, with active participation and regular input from the Council on Environmental Quality, National Economic Council, Office of Energy and Climate Change, and Office of Science and Technology Policy.

The interagency group’s main objective was to develop a range of SCC values using clearly articulated input assumptions grounded in the existing scientific and economic literatures, in conjunction with a range of models that empl oy different representations of climate change and its economic impacts. The group clearly acknowledged the many uncertainties that its process identified, and recommended that its estimates of the SCC should be updated periodically to incorporate developing knowledge of the science and economics of climate impacts. Specifically, it set a preliminary goal to revisit the SCC values within two years, or as substantial improvements in understanding of the science and economics of climate impacts and updated models for estimating and valuing these impacts become available. The group ultimately selected four SCC values for use in federal regulatory analyses. Three values were based on the average of SCC estimates developed using three different climate economic models (referred to as integrated assessment models), using discount rates of 2.5, 3, and 5 percent. The fourth value, which represents the 95 th percentile SCC estimate from the co mbined distribution of values generated by the three models at a 3 percent disco unt rate, represents the possibility of possibilityDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

617 of higher-than-expected impacts from the accumulation of GHGs in the earth’s atmosphere, and the consequently larger economic damages.

Table IV.C.3–2 summarizes the interagency group’s estimates of the SCC during various future years, which the agency has updated to 2009 dollars to correspond to the other values it uses to estimate economic benefits from the a lternative CAFE standards considered in this
NPRM. 667

T ABLE IV.C.3-2. S OCIAL C OST OF CO 2 E MISSIONS FOR S ELECTED F UTURE Y EARS (2009$

PER METRIC TON )

Discount Rate 5% 3% 2.5% 3%

Source Average of estimates 95 t h percentile estimate
2012 $5.28 $23.06 $37.53 $70.14
2015 $5.93 $24. 58 $39.57 $74.03
2020 $7.01 $27.10 $42.98 $83.17
2025 $8. 53 $30.43 $47.28 $93.11
2030 $10.05 $33.75 $51.58 $103.06
2035 $11.57 $37.08 $55.88 $113.00
2040 $13.09 $40.40 $60.19 $122.95
2045 $14.63 $43. 34 $63.59 $131.66
2050 $16.18 $46.27 $66.99 $140.37

As Table IV.C.3–2 shows, the four SCC estimates selected by the interagency group for use in regulatory analyses are $5, $23, $38, and $70 per metric ton (in 2009 dollars) for emissions occurring in the year 2012. The value that the interagency group centered its attention on is the average SCC estimate developed using different models and a 3 percent discount rate, or $23 per metric ton in 2012. To capture the uncertainties involved in regulatory impact analysis, however, the group emphasized the importance of considering the full range of estimated SCC values. As the table also shows, the SCC estimates also rise over time; for example, the average SCC at the 3 percent discount rate increases to $27 per metric ton of CO 2 by 2020 and reaches $46 per metric ton of CO 2 in 2050.

Details of the process used by the interagency group to develop its SCC estimates, complete results including year-by-year estimates of each of the four values, and a thorough discussion of their intended use and limitations is provided in the document Social Cost of Carbon for Regulatory Impact Analysis Under Executive Order 12866, Interagency Working Group on Social Cost of Carbon, United States Government, February 2010. 668

667 The SCC estimates reported in the table assume that the damages resulting from increased emissions are constant for small departures from the baseline emissions forecast incorporated in each estimate, an approximation that is reasonable for policies with projected effects on CO 2 emissions that are small relative to cumulative global
emissions.

668 This document is available in the docket for this rulemaking (NHTSA–2009–0059).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

618 m. Discounting Future Benefits and Costs

Discounting future fuel savings and other benefits accounts for the reduction in their value when they are deferred until some future date, rather than received immediately. The value of benefits that are not ex pected to occur until the future is lower partly because people value current consumption more highly than equivalent consumption at some future date – stated simply, they are impatient – and partly because they expect their living standards to be higher in the future, so additional consumption will improve th eir well-being by more today than it will in the future. The discount rate expresses the per cent decline in the value of these benefits—as viewed from today’s perspective—for each year they are deferred into the future. In evaluating the benefits from alternative increases in CAFE standards for MY 2017–2025 passenger cars and light trucks, NHTSA primarily employs a discount rate of 3 percent per year, but in accordance with OMB guidance, also presents these benefit and cost estimates using a 7 percent discount

rate.

While it presents results that reflect both discount rates, NHTSA believes that the 3 percent rate is more appropriate for discounting future benefits from increased CAFE standards, because the agency expects that most or all of vehicle manufacturers’ costs for complying with higher CAFE standards will ultimately be reflect ed in higher selling prices for their new vehicle models. By increasing sales prices for new cars and light trucks, CAFE regulations will thus primarily affect vehicle purchases and other private consumption decisions. Both economic theory and OMB guidance on discounting indicate that the future benefits and costs of regulations that mainly affect private consumptio n should be discounted at consumers’ rate of time preference. 669

Current OMB guidance also indicates that save rs appear to discount future consumption at an average real (that is, adjusted to remove the effect of inflation) rate of about 3 percent when they face little risk about the future. Since the real interest rate that savers require to persuade them to defer consumption into the future represents a reasonable estimate of consumers’ rate of time preference, NHTSA believes that the 3 percent rate is appropriate for discounting projected future benefits and costs resulting from higher CAFE standards.

Because there is some uncertainty about wh ether vehicle manufacturers will completely recover their costs for complying with higher CA FE standards by increasing vehicle sales prices, however, NHTSA also presents benefit and cost es timates discounted using a higher rate. To the extent that manufacturers are unable to recover their costs for meeting higher CAFE standards by increasing new vehicle prices, th ese costs are likely to displa ce other investment opportunities available to them. OMB guidance indicates that the real economy-wide opportunity cost of capital is the appropriate discount rate to apply to future benefits and costs when the primary effect of a regulation is “...to displace or alter th e use of capital in the private sector,” and OMB estimates that this rate currently averages about 7 percent. 670 Thus the agency’s analysis of alternative increases in CAFE standards for MY 2017-25 cars and light trucks also reports benefits and costs discounted at a 7 percent rate.

669 Id.

670 Office of Management and Budget, Circular A–4, “Regulatory Analysis,” September 17, 2003, 33. Available at http://www.whitehouse.gov/omb/circulars/a004/a-4.pdf (last accessed Sept. 26, 2011).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

619 One important exception to the agency’s use of 3 percent and 7 percent discount rates is arises in discounting benefits from reducing CO 2 emissions over the lifetimes of MY 2017–2025 cars and light trucks to their present values. In order to ensure consistency in the derivation and use of the interagency group’s estimates of the unit values of reducing CO 2 emissions (or SCC), the benefits from reducing CO 2 emissions during each future year are discounted using the same “intergenerational” discount rates that were used to derive each of the alternative values. . As indicated in Table IV.C.3–4 above, these rates are 2.5 percent, 3 percent, and 5 percent depending on which estimate of the SCC is being employed. 671

n. Accounting for Uncertainty in Benefits and Costs

In analyzing the uncertainty surrounding its estimates of benefits and costs from alternative CAFE standards, NHTSA considers a lternative estimates of those assumptions andparameters likely to have the largest effect. These include the projected costs of fuel economyimproving technologies and their anticipated effectiveness in reducing fuel consumption, forecasts of future fuel prices, the magnitude of the rebound effect, the reduction in external economic costs resulting from lower U.S. oil imports, and the discount rate applied to future benefits and costs. The range for each of these variables employed in the uncertainty analysis was previously identified in the sections of this notice discussing each variable.

The uncertainty analysis was conducted by assuming either independent normal or beta probability distributions for each of these variab les, using the low and high estimates for each variable as the values between which 90 percent of observed values are expected to fall. Each trial of the uncertainty analysis employed a set of values randomly drawn from these probability distributions, under the assumption that the value of each variable is independent from those of the others. In cases where the data on the po ssible distribution of parameters was relatively sparse, making a choice of distributions difficult, a beta distribution is commonly employed to give more weight to both tails than would be th e case had a normal distribution been employed. Benefits and costs of each alternative standard were estimated using each combination of variables, and a total of nearly 40,000 trials were used to estimate the likely range of estimated benefits and costs for each alternative standard.

o. Where can readers find more information about the economic assumptions?

Much more detailed information is provided in Chapter VIII of the PRIA, and a discussion of how NHTSA and EPA jointly re viewed and updated economic assumptions for purposes of this final rule is available in Chapte r 4 of the draft Joint TSD. In addition, all of NHTSA’s model input and output files are now publ ic and available for the reader’s review and

671 The fact that the 3 percent discount ra te used by the interagency group to deri ve its central estimate of the SCC is identical to the 3 percent short-term or “intra-generational” discount rate used by NHTSA to discount future benefits
other than reductions in CO 2 emissions is coincidental, and should not be interpreted as a required condition that must be satisfied in future rulemakings.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

620 consideration. The economic input files can be found in the docket for this proposed rule, NHTSA–2011–[xxxx], and on NHTSA’s website. 672

Finally, because much of NHTSA’s economic analysis for purposes of this final rule builds on the work that was done for the final rule establishing CAFE standards for MYs 2012- 16, we refer readers to that document as well. It contains valuable background information concerning how NHTSA’s assumptions regardin g economic inputs for CAFE analysis have evolved over the past several rulemakings, both in response to comments and as a result of the agency’s growing experience with this type of analysis. 673

4. How does NHTSA use the assumptions in its modeling analysis?

In developing today’s proposed CAFE standards, NHTSA has made significant use of results produced by the CAFE Compliance and Effects Model (commonly referred to as “the CAFE Model” or “the Volpe model”), which DOT’s Volpe National Transportation Systems Center developed specifically to support NHTSA’s CAFE rulemakings. The model, which has been constructed specifically for the purpose of analyzing potential CAFE standards, integrates the following core capabilities:

(1) Estimating how manufacturers could apply technologies in response to new fuel economy standards, (2) Estimating the costs that would be incurred in applying these technologies, (3) Estimating the physical effects resulting from the application of these technologies, such as changes in travel demand, fuel consumption, and emissions of carbon dioxide and criteria pollutants, and (4) Estimating the monetized societal benefits of these physical effects.

An overview of the model follows below. Separate model documentation provides a detailed explanation of the functions the model performs, the calculations it performs in doing so, and how to install the model, construct inputs to the model, and interpret the model’s outputs. Documentation of the model, along with model installation files, source code, and sample inputs are available at NHTSA’s Web site. The model documentation is also available in the docket for today’s proposed rule, as are inputs for and out puts from analysis of today’s proposed CAFE standards.

a. How does the model operate?

As discussed above, the agency uses the Volpe model to estimate how manufacturers could attempt to comply with a given CAFE standard by adding technology to fleets that the agency anticipates they will produce in future model years. This exercise constitutes a simulation of manufacturers’ decisions regarding compliance with CAFE standards.

This compliance simulation begins with the following inputs: (a) the baseline and reference market forecast discussed above in Section IV.C.1 and Chapter 1 of the TSD, (b)

672 See http://www.nhtsa.gov/fuel-economy

673 74 FR 14308–14358 (Mar. 30, 2009).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

621 technology-related estimates discussed above in Section IV.C.2 and Chapter 3 of the TSD, (c) economic inputs discussed above in Section IV.C.3 and Chapter 4 of the TSD, and (d) inputs defining baseline and potential new CAFE standards. For each manufacturer, the model applies technologies in a sequence that follows a defined engineering logic (“decision trees” discussed in the MY 2011 final rule and in the model documenta tion) and a cost-minimiz ing strategy in order to identify a set of technologies the manufact urer could apply in response to new CAFE standards. 674 The model applies technologies to each of the projected individual vehicles in a manufacturer’s fleet, considering the combined effect of regulatory and market incentives. Depending on how the model is exercised, it wi ll apply technology until one of the following

occurs:

(1) The manufacturer’s fleet achieves compliance 675 with the applicable standard, and continuing to add technology in the current model year would be attractive neither in terms of stand-alone ( i.e. , absent regulatory need) cost effectiveness nor in terms of facilitating compliance in future model years; 676 (2) The manufacturer “exhausts” 677 available technologies; or (3) For manufacturers estimated to be willing to pay civil penalties, the manufacturer reaches the point at which doi ng so would be more cost-effective (from the manufacturer’s perspective) than adding further technology. 678

674 NHTSA does its best to remain scrupulously neutral in the application of technologies through the modeling analysis, to avoid picking technology “winners.” The tech nology application methodology has been reviewed by the agency over the course of several rulemakings, and co mmenters have been generally supportive of the agency’s approach. See

, e.g., 74 FR 14238–14246 (Mar. 30, 2009).

675 The model has been modified to provide the abili ty—as an option—to account for credit mechanisms ( i.e. , carryforward, carry-back, transfers, and trades) when determin ing whether compliance has been achieved. For purposes of determining maximum feasible CAFE standards, NHTSA cannot consider these mechanisms, and exercises the CAFE model without enabling these options.

676 In preparation for the MY2012-2016 rulemaking, the model was modified in order to apply additional technology in early model years if doing so will facilitate compliance in later model years. This is designed to simulate a manufacturer’s decision to plan for CAFE obligations se veral years in advance, which NHTSA believes better replicates manufacturers’ actual behavior as compared to the year-by-year evaluation which EPCA would otherwise require.

677 In a given model year, the model ma kes additional technologies available to each vehicle model within several constraints, including (a) whether or not the technology is applicable to the vehicle model’s technology class, (b) whether the vehicle is undergoing a redesign or freshening in the given model year, (c) whether engineering aspects of the vehicle make the technology unavailable ( e.g., secondary axle disconnect cannot be applied to two-wheel drive vehicles), and (d) whether technology application re mains within “phase in caps” constraining the overall share of a manufacturer’s fleet to which the technology can be added in a given model year. Once enough technology is added to a given manufacturer’s fleet in a given model year that these constraints make further technology application unavailable, technologies are “e xhausted” for that manufacturer in that model year.

678 This possibility was added to the model to account fo r the fact that under EPCA/EISA, manufacturers must pay fines if they do not achieve compliance with applicable CAFE standards. 49 U.S.C. 32912(b). NHTSA recognizes
that some manufacturers will find it more cost-effective to pay fines than to achieve compliance, and believes that to
assume these manufacturers would exhaust available techno logies before paying fines would cause unrealistically high estimates of market penetration of expensive technol ogies such as diesel engines and strong hybrid electric vehicles, as well as correspondingly inflated estimates of both the costs and benefits of any potential CAFE standards. NHTSA thus includes the possibility of manufac turers choosing to pay fines in its modeling analysis in order to achieve what the agency beli eves is a more realistic simulation of manufacturer decision-making. UnlikeDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

622 As discussed below, the model has also been modified in order to—as an option—apply more technology than may be necessary to achieve compliance in a given model year, or to facilitate compliance in later model years. Th is ability to simulate “voluntary overcompliance” reflects the potential that manufacturers will apply some technologies to so me vehicles if doing so would be sufficiently inexpensive compared to the expected reduction in owners’ outlays for fuel.

The model accounts explicitly for each model year, applying most technologies when vehicles are scheduled to be redesigned or fres hened, and carrying forward technologies between model years. The CAFE model accounts explicitly for each model year because EPCA requires that NHTSA make a year-by-year determination of the appropriate level of stringency and then set the standard at that level, while ensuring ratable increases in average fuel economy. 679 The multiyear planning capability and (optional) simulation of “voluntary overcompliance” and EPCA credit mechanisms increase the model’s ability to simulate manufacturers’ real-world behavior, accounting for the fact that manufacturers will seek out compliance paths for several model years at a time, while accommodating the year-by-year requirement.

The model also calculates the costs, effects, a nd benefits of technologies that it estimates could be added in response to a given CAFE standard. 680 It calculates costs by applying the cost estimation techniques discussed above in Section IV.C.2, and by accounting for the number of affected vehicles. It accounts for effects such as changes in vehicle travel, changes in fuel consumption, and changes in greenhouse gas and criteria pollutant emissions. It does so by applying the fuel consumption estimation techniques also discussed in Section IV.C.2, and the vehicle survival and mileage accumulation forecasts, the rebound effect estimate and the fuel properties and emission factors discussed in Section IV.C.3. Considering changes in travel demand and fuel consumption, the model estimates the monetized value of accompanying benefits to society, as discussed in Section IV.C.3. The model calculates both the undiscounted and discounted value of benefits that accrue over time in the future.

The Volpe model has other capabilities that facilitate the development of a CAFE standard. The integration of (a) compliance simulation and (b) the calculation of costs, effects, and benefits facilitates analysis of sensitivity of results to model inputs. The model can also be used to evaluate many ( e.g., 200 per model year) potential levels of stringency sequentially, and

flex-fuel and other credits, NHTSA is not barred by statut e from considering fine-payment in determining maximum feasible standards under EPCA/EISA. 49 U.S.C. 32902(h).

679 49 U.S.C. 32902(a) states that at least 18 months before the beginning of each model year, the Secretary of Transportation shall prescribe by regulation average fuel economy standards for automobiles manufactured by a manufacturer in that model year, and that each standard shall be the maximum feasible average fuel economy level that the Secretary decides the manufactur ers can achieve in that year. NHTSA has long interpreted this statutory language to require year-by-year assessment of manufacturer capabilities. 49 U.S.C. 32902(b)(2)(C) also requires that standards increase ratably between MY 2011 and MY 2020.

680 As for all of its other rulemakings, NHTSA is required by Executive Order 12866 (as amended by Executive Order 13563) and DOT regulations to analyze the costs and benefits of CAFE standards. Executive Order 12866, 58 FR 51735 (Oct. 4, 1993); DOT Order 2100.5, “Regulatory Policies and Procedures,” 1979, available at http://regs.dot.gov/rulemakingrequirements.htm (last accessed February 21, 2010).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

623 identify the stringency at which specific criteria are met. For example, it can identify the stringency at which net benefits to society are maximized, the stringency at which a specified total cost is reached, or the stringency at which a given average required fuel economy level is attained. This allows the agency to compare more easily the impacts in terms of fuel savings, emissions reductions, and costs and benefits of ach ieving different levels of stringency according to different criteria. The model can also be used to perform uncertainty analysis ( i.e., Monte Carlo simulation), in which input estimates are varied randomly according to specified probability distributions, such that the uncertainty of key measures ( e.g., fuel consumption, costs, benefits) can be evaluated.

b. Has NHTSA considered other models?

As discussed in the most recent CAFE rulemaking, while nothing in EPCA requires NHTSA to use the Volpe model, and in principle, NHTSA could perform all of these tasks through other means, the model’s capabilities have greatly increased the agency’s ability to rapidly, systematically, and reproducibly conduct key analyses relevant to the formulation and evaluation of new CAFE standards. 681

NHTSA notes that the Volpe model not only has been formally peer-reviewed and tested and reviewed through three rulemakings, but also has some features especially important for the analysis of CAFE standards under EPCA/EISA. Among these are the ability to perform year-byyear analysis, and the ability to account for engi neering differences between specific vehicle models.

EPCA requires that NHTSA set CAFE standards for each model year at the level that would be “maximum feasible” for that year. 682 Doing so requires the ability to analyze each model year and, when developing regulations covering multiple model years, to account for the interdependency of model years in terms of the appropriate levels of stringency for each one. Also, as part of the evaluation of the economic practicability of the standards, as required by EPCA, NHTSA has traditionally assessed the annual costs and benefits of the standards. In response to comments regarding an early version of the CAFE model, DOT modified the CAFE model in order to account for dependencies between model years and to better represent manufacturers’ planning cycles, in a way that st ill allowed NHTSA to comply with the statutory requirement to determine the appropriate level of the standards for each model year.

The Volpe model is also able to account for important engineering differences between specific vehicle models, and to thereby reduce the risk of applying technologies that may be incompatible with or already present on a give n vehicle model. By combining technologies incrementally and on a model-by-model basis, the CAFE model is able to account for important engineering differences between vehicle models and avoid unlikely technology combinations

681 75 FR 25598-25599.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

624 The Volpe model also produces a single vehicl e-level output file that, for each vehicle model, shows which technologies were present at the outset of modeling, which technologies were superseded by other technologies, and which technologies were ultimately present at the conclusion of modeling. For each vehicle, the same file shows resultant changes in vehicle weight, fuel economy, and cost. This provides for efficient identification, analysis, and correction of errors, a task with which the public can now assist the agency, since all inputs and outputs are public.

Such considerations, as well as those related to the efficiency with which the Volpe model is able to analyze attribute-based CAFE standards and changes in vehicle classification, and to perform higher-level analysis such as stringency estimation (to meet predetermined criteria), sensitivity analysis, and uncertainty analys is, lead the agency to conclude that the model remains the best available to the agency for the purposes of analyzing potential new CAFE standards.

c. What changes has DOT made to the model?

Between promulgation of the MY 2012-2016 CAFE standards and today’s proposal regarding MY 2017-2025 standards, the Volpe model has been revised to make some minor improvements, and to add some significant new cap abilities: (1) accounting for electricity used to charge electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs), (2) accounting for use of ethanol blends in flexible-fue l vehicles (FFVs), (3) accounting for costs ( i.e. , “stranded capital”) related to early replacement of t echnologies, (4) accounting for previously-applied technology when determining the extent to which a manufacturer could expand use of the technology, (5) applying technology-specific estimates of changes in consumer value, (6) simulating the extent to which manufacturers might utilize EPCA’s provisions regarding generation and use of CAFE credits, (7) applying estimates of fuel economy adjustments (andaccompanying costs) reflecting increases in air conditioner efficiency, (8) reporting privatelyvalued benefits, (9) simulating the extent to which manufacturers might voluntarily apply technology beyond levels needed for compliance with CAFE standards, and (10) estimating changes in highway fatalities attributable to any applied reductions in vehicle mass. These capabilities are described below, and in great er detail in the CAFE model documentation. 683

To support evaluation of the effects electric vehicles (EVs) and plug-in hybrid vehicles (PHEVs) could have on energy consumption and associated costs and environmental effects, DOT has expanded the Volpe model to estimate the amount of electricity that would be required to charge these vehicles (accounting for the potential that PHEVs can also run on gasoline). The model calculates the cost of this electricity, as well as the accompanying upstream criteria pollutant and greenhouse gas emissions.

Similar to this expansion to account for the potential the PHEVs can be refueled with gasoline or recharged with electricity, DOT has expanded the Volpe model to account for the potential that other flexible-fuel vehicles can be operated on multiple fuels. In particular, the model can account for ethanol FFVs consuming E85 or gasoline, and to report consumption of both fuels, as well as corresponding costs and upstream emissions.

683 [Add reference to model documentation.]DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

625 Among the concerns raised in the past regarding how technology costs are estimated has been one that stranded capital costs be considered. Capital becomes “stranded” when capital equipment is retired or its use is discontinued before the equipment has been fully depreciated and the equipment still retains some value or usef ulness. DOT has modified the CAFE model to, if specified for a given technology, when that technology is replaced by a newly applied technology, apply a stream of costs representing the stranded capital cost of the replaced technology. This cost is in addition to the cost for producing the newly applied technology in the first year of production.

As documented in prior CAFE rulemakings, the CAFE model applies “phase-in caps” to constrain technology application at the vehicle manuf acturer level. They are intended to reflect a manufacturer’s overall resource capacity available for implementing new technologies (such as engineering and development personnel and financial resources), thereby ensuring that resource capacity is accounted for in the modeling process. This helps to ensure technological feasibility and economic practicability in determining the st ringency of the standards. When the MY 2012- 2016 rulemaking analysis was completed, the model performed the relevant test by comparing a given phase-in cap to the amount ( i.e. , the share of the manufacturer’s fleet) to which the technology had been added by the model. DOT has since modified the CAFE model to take into account the extent to which a given manufacturer has already applied the technology ( i.e. , as reflected in the market forecast specified as a mo del inputs), and to apply the relevant test based on the total application of the technology.

The CAFE model requires inputs defining the technology-specific cost and efficacy ( i.e.

, percentage reduction of fuel consumption), and has, to date, effectively assumed that these input values reflect application of the technology in a manner that holds vehicle performance and utility constant. Considering that some technolo gies may, nonetheless, offer owners greater or lesser value (beyond that related to fuel outlays, which the model calculates internally based on vehicle fuel type and fuel economy), DOT has modified the CAFE model to accept and apply technology-specific estimates of any value gain realized or loss incurred by vehicle purchasers. 684

For the MY 2012-2016 CAFE rulemaking analysis, DOT modified the CAFE model to accommodate specification and accounting for credits a manufacturer is assumed to earn by producing flexible fuel vehicles (FFVs). Although NHTSA cannot consider such credits when determining maximum feasible CAFE standards, the agency presented an analysis that included FFV credits, in order to communicate the extent to which use of such credits might cause actual costs, effects, and benefits to be lower than estimated in NHTSA’s formal analysis. As DOT explained at the time, it was unable to account for other EPCA credit mechanisms, because attempts to do so had been limited by complex interactions between those mechanisms and the multiyear planning aspects of the CAFE model. DOT has since modified the CAFE model to provide the ability to account for any or all of the following flexibilities provided by EPCA: FFV credits, credit carry-forward and carry-back (between model years), credit transfers (between passenger car and light truck fleets), a nd credit trades (between manufacturers). The

684 For example, a value gain could be specified for a tec hnology expected to improve ride quality, and a value loss could be specified for a technology expected to reduce vehicle range.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

626 model accounts for EPCA-specified limitati ons applicable to these flexibilities ( e.g. , limits on the amount of credit that can be transferred between passenger car and light truck fleets). These capabilities in the model provide a basis for mo re accurately estimating costs, effects, and benefits that may actually result from new CAFE standards. Insofar as some manufacturers actually do earn and use CAFE credits, this provides NHTSA with the ability to examine outcomes more realistically than EPCA allows for purposes of setting new CAFE standards.

NHTSA is today proposing CAFE standards reflecting EPA’s proposal to change fuel economy calculation procedures such that a ve hicle’s fuel consumptio n improvement will be accounted for if the vehicle has technologies that reduce the amount of energy needed to power the air conditioner. To facilitate analysis of these standards, DOT has modified the CAFE model to account for these adjustments, based on input s specifying the average amount of improvement anticipated, and the estimated average cost to apply the underlying technology.

Considering that past CAFE rulemakings indi cate that most of the benefits of CAFE standards are realized by vehicle owners, DOT has modified the CAFE model to estimate not just social benefits, but also private benefits. The model accommodates separate discount rates for these two valuation methods ( e.g. , a 3% rate for social benefits with a 7% rate for private benefits). When calculating private benefits, the model includes changes in outlays for fuel taxes (which, as economic transfers, are excluded from social benefits) and excludes changes in economic externalities ( e.g. , monetized criteria pollutant and greenhouse gas emissions).

Since 2003, the CAFE model (and its predecessors) have provided the ability to estimate the extent to which a manufacturer with a history of paying civil penalties allowed under EPCA might decide to add some fuel-saving technol ogy, but not enough to comply with CAFE standards. In simulating this decision-maki ng, the model considers the cost to add the technology, the calculated reductio n in civil penalties, and the calculated present value (at the time of vehicle purchase) of the change in fuel outlays over a specified “payback period” ( e.g. , 5 years). For a manufacturer assumed to be willin g to pay civil penalties, the model stops adding technology once paying fines becomes more attractive than continuing to add technology, considering these three factors. As an extensio n of this simulation approach, DOT has modified the CAFE model to, if specified, simulate the potential that a manufacturer would add more technology than required for purposes of compliance with CAFE standards. When set to operatein this manner, the model will continue to apply technology to a manufacturer’s CAFEcompliant fleet until applying further technology w ill incur more in cost than it will yield in calculated fuel savings over a specified “payback period” that is set separately from the payback period applicable until compliance is achieved. In its analysis supporting MY 2012-2016 standards adopted in 2010, NHTSA estimated the extent to which reductions in vehicle mass might lead to changes in the number of highway fatalities occurring over the useful life of the MY 2012-2016 fleet. NHTSA performed these calculations outside the CAFE model (using vehicle-specific mass reduction calculations from the model), based on agency analysis of relevant highway safety data. DOT has since modified the CAFE model to perform these calculations, using an analytical structure indicat ed by an update to the underlying safety analysis. The model also applies an input value indicating the economic value of a statistical life, and includes resultant bene fits (or disbenefits) in the calcu lation of total social benefits.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

627 In comments on recent NHTSA rulemakings, some reviewers have suggested that the Volpe model should be modified to estimate the extent to which new CAFE standards would induce changes in the mix of vehicles in the new vehicle fleet. NHTSA agrees that a “market shift” model, also called a consumer vehicle choice model, could provide useful information regarding the possible effects of potential new CAFE standards. NHTSA has contracted with the Brookings Institution (which has subcontracted with researchers at U.C. Davis, U.C. Irvine) to develop a vehicle choice model estimated at the vehicle configuration level that can be implemented as part of DOT’s CAFE model. As discussed further in Section V of the PRIA, past efforts by DOT staff demonstrated that a ve hicle could be added to the CAFE model, but did not yield credible coefficients specifying such a model. If a suitable and credibly calibrated vehicle choice model becomes available in time—w hether through the Brookings-led research or from other sources, DOT may integrate a vehicle choice model into the CAFE model, and may also docket an impacts analysis following the NPRM (ideally during the designated comment period), to allow the public to see and commen t on the difference in results with and without simulation of vehicle choice impacts.

NHTSA anticipates this integration of a vehi cle choice model would be structurally and operationally similar to the integration we implem ented previously. As under the version applied in support of today’s announcement, the CAFE model would begin with an agency-estimated market forecast, estimate to what extent ma nufacturers might apply additional fuel-saving technology to each vehicle model in consideration of future fuel prices and baseline or alternative CAFE standards and fuel prices, and calculate resultant changes in the fuel economy (and possibly fuel type) and price of individual ve hicle models. With an integrated market share model, the CAFE model would then estimate how the sales volumes of individual vehicle models would change in response to changes in fuel economy levels and prices throughout the light vehicle market, possibly taking into account interactions with the used vehicle market. Having done so, the model would replace the sales estimates in the original market forecast with those reflecting these model-estimated shifts, repeating the entire modeling cycle until converging on a stable solution.

Based on past experience, we anticipate that this recursive simulation will be necessary to ensure consistency between sales volumes and modeled fuel economy standards, because achieved CAFE levels depend on sales mix and, under attribute-based CAFE standards, required CAFE levels also depend on sales mix. NHTSA anticipates, therefore, that application of a market share model would impact estimates of all of the following for a given schedule of CAFE standards: overall market volume, manufacturer market shares and product mix, required and achieved CAFE levels, technology application ra tes and corresponding incurred costs, fuel consumption, greenhouse gas and criteria polluta nt emissions, changes in highway fatalities, and economic benefits.

Past testing by DOT/NHTSA staff did not indicate major shifts in broad measures ( e.g. , in total costs or total benefits), but that testing emphasized shorter modeling periods ( e.g. , 1-5 model years) and less stringent standards than refl ected in today’s proposal. Especially without knowing the characteristics of a future vehicle c hoice model, it is difficult to anticipate the potential degree to which its inclusion would impact analytical outcomes.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

628 NHTSA invites comment on the above changes to the CAFE model. The agency’s consideration of any alternativ e approaches will be facilitated by specific recommendations regarding implementation within the model’s ove rall structure. NHTSA also invites comment regarding above-mentioned prospects for inclusion of a vehicle choice model. The agency’s consideration will be facilitated by specific inform ation demonstrating that inclusion of such a model would lead to more realistic estimates of co sts, effects, and benefits, or that inclusion of such a model would lead to less realistic estimates.

d. Does the model set the standards?

Since NHTSA began using the Volpe model in CAFE analysis, some commenters have interpreted the agency’s use of the model as the way by which the agency chooses the maximum feasible fuel economy standards. As the agency explained in its most recent CAFE rulemaking, this is incorrect. 685 Although NHTSA currently uses the Volpe model as a tool to inform its consideration of potential CAFE standards, the Volpe model does not determine the CAFE standards that NHTSA proposes or promulgates as final regulations. The results it produces are completely dependent on inputs selected by NHTSA, based on the best available information and data available in the agency’s estimation at th e time standards are set. Ultimately, NHTSA’s selection of appropriate CAFE standards is governed and guided by the statutory requirements of EPCA, as amended by EISA: NHTSA sets the standard at the maximum feasible average fuel economy level that it determines is achievabl e during a particular model year, considering technological feasibility, economic practicabilit y, the effect of other standards of the Government on fuel economy, and the need of the nation to conserve energy.

e. How does NHTSA make the model available and transparent?

Model documentation, which is publicly available in the rulemaking docket and on NHTSA’s website, explains how the model is installed, how the model inputs (all of which are available to the public) 686 and outputs are structured, and how the model is used. The model can be used on any Windows-based personal computer with Microsoft Office 2003 or 2007 and the Microsoft .NET framework installed (the latter available without charge from Microsoft). The executable version of the model and the underlying source code are also available at NHTSA’s Web site. The input files used to conduct the core analysis documented in this final rule are available in the public docket. With the mode l and these input files, anyone is capable of independently running the model to repeat, evaluate, and/or modify the agency’s analysis.

Because the model is available on NHTSA’s web site, the agency has no way of knowing how widely the model has been used. The agency is, however, aware that the model has been used by other federal agencies, vehicle manufactur ers, private consultants, academic researchers, and foreign governments. Some of these individuals have found the model complex and challenging to use. Insofar as the model’s sole purpose is to help DOT staff efficiently analyze potential CAFE standards, DOT has not expended significant resources trying to make the model as “user friendly” as commercial software intended for wide use. However, DOT wishes to

685 75 FR 25600.

686 We note, however, that files from any supplemental anal ysis conducted that relied in part on confidential manufacturer product plans cannot be made pub lic, as prohibited under 49 CFR part 512.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

629 facilitate informed comment on the proposed standa rds, and encourages reviewers to contact the agency promptly if any difficulties using the model are encountered.

NHTSA arranged for a formal peer review of an older version of the model, has responded to reviewers’ comments, and has considered and responded to model-related comments received over the course of four CAFE rulemakings. In the agency’s view, this steady and expanding outside review over the course of nearly a decade of model development has helped DOT to significantly strengthen the model’s capabilities and technical quality, and has greatly increased transparency, such that all model code is publicly available, and all model inputs and outputs are publicly available in a form that should allow reviewers to reproduce the agency’s analysis. NHTSA is currently preparing arrangements for a formal peer review of the current CAFE model. Depending on the schedul e for that review, DOT will consider possible model revisions and, as feasible, attempt to make any appropriate revisions before performing analysis supporting final CAFE standards for MY 2017 and beyond. Depending on timing and resources, NHTSA may also docket an impacts analysis following the NPRM, to allow the public to see and comment on the difference in model results when revisions to the model are implemented.

D. Statutory Requirements

1. EPCA, as Amended by EISA

a. Standard Setting

EPCA, as amended by EISA, contains a number of provisions regarding how NHTSA must set CAFE standards. NHTSA must establ ish separate CAFE standards for passenger cars and light trucks 687 for each model year, 688 and each standard must be the maximum feasible that NHTSA believes the manufacturers can achieve in that model year. 689 When determining the maximum feasible level achievable by the manufacturers, EPCA requires that the agency consider the four statutory factors of technologi cal feasibility, economic practicability, the effect of other motor vehicle standards of the Government on fuel economy, and the need of the United States to conserve energy. 690 In addition, the agency has the authority to and traditionally does consider other relevant factors, such as the effect of the CAFE standards on motor vehicle safety. The ultimate determination of what standards can be considered maximum feasible involves a weighing and balancing of these factors, and the balance may shift depending on the information before the agency about the expected circumstances in the model years covered by the rulemaking. Always in conducting that balancing, however, the implication of the “maximum feasible” requirement is that it calls for setting a standard that exceeds what might be the minimum requirement if the agency determines that the manufacturers can achieve a higher

687 49 U.S.C. 32902(b)(1).

688 49 U.S.C. 32902(a).

689 Id

. 690 49 U.S.C. 32902(f).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

630 level, and that the agency’s decision support the overarching purpose of EPCA, energy conservation. 691

Besides the requirement that standards be maximum feasible for the fleet in question, EPCA/EISA also contains several other requirement s. The standards must be attribute-based and expressed in the form of a mathematical function – NHTSA has thus far based standards on vehicle footprint, and for this rulemaking has expressed them in the form of a constrained linear function that generally sets higher (more stringent) mpg targets for smaller-footprint vehicles and lower (less stringent) mpg targets for larger-footp rint vehicles. Second, the standards are subject to a minimum requirement regarding stringency: they must be set at levels high enough to ensure that the combined U.S. passenger car and light truck fleet achieves an average fuel economy level of not less than 35 mpg not later than MY 2020. 692 Third, between MY 2011 and MY 2020, the standards must “increase ratably” in each model year. 693 This requirement does not have a precise mathematical meaning, particularly because it must be interpreted in conjunction with the requirement to set the standa rds for each model year at the level determined to be the maximum feasible leve l for that model year. Generall y speaking, the requirement for ratable increases means that the annual increases should not be disproportionately large or small in relation to each other. The second and third requirements no longer apply after MY 2020, at which point standards must simply be maximum feasible. And fourth, EISA requires NHTSA to issue CAFE standards for “at least 1, but not more than 5, model years.” 694 This issue is discussed in section IV.B. above.

The following sections discuss the statutory factors behind “maximum feasible” in more detail.

i. Statutory Factors Considered in Determining the Achievable Level of Average Fuel Economy

As none of the four factors is defined in EPCA and each remains interpreted only to a limited degree by case law, NHTSA has consider able latitude in interpreting them. NHTSA interprets the four statutory factors as set forth below.

(1) Technological Feasibility

“Technological feasibility” refers to whet her a particular technology for improving fuel economy is available or can become available for commercial application in the model year for which a standard is being establis hed. Thus, the agency is not lim ited in determining the level of new standards to technology that is already be ing commercially applied at the time of the rulemaking. It can, instead, set technology-forcing standards, i.e., ones that make it necessary for manufacturers to engage in research and development in order to bring a new technology to

691 Center for Biological Diversity v. NHTSA, 538 F.3d 1172, 1197 (9th Cir. 2008) (“Whatever method it uses, NHTSA cannot set fuel economy standards that are contrary to Congress’ purpose in enacting the EPCA – energy conservation.”).

692 49 U.S.C. 32902(b)(2)(A).

693 49 U.S.C. 32902(b)(2)(C).

694 49 U.S.C. 32902(b)(3)(B).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

631 market. There are certain technologies that the agency has considered for this rulemaking, for example, that we know to be in the research phase now but which we are fairly confident can be commercially applied by the rulemaking timeframe, and very confident by the end of the rulemaking timeframe. It is important to re member, however, that while the technological feasibility factor may encourage the agency to look toward more technology-forcing standards, and while this could certainly be appropriate given EPCA’s overarching purpose of energy conservation depending on the rulemaking, that factor must also be balanced with the other of the four statutory factors. Thus, while “technolo gical feasibility” can drive standards higher by assuming the use of tec hnologies that are not yet commercial, “maximum feasible” is still also defined in terms of economic practicability, for example, which might caut ion the agency against basing standards (even fairly distant future standards) entirely on such technologies. By setting standards at levels consistent with an analysis that assumes the use of these nascent technologies at levels that seem reasonable, the agency believes a more reasonable balance is ensured. Nevertheless, as the “maximum feasible” balanc ing may vary depending on the circumstances at hand for the model years in which the standards are set, the extent to which technological feasibility is simply met or plays a more dynamic role may also shift.

(2) Economic Practicability

“Economic practicability” refers to whether a standard is one “within the financial capability of the industry, but not so stringent as to” lead to “adverse economic consequences, such as a significant loss of jobs or the un reasonable elimination of consumer choice.” 695 The agency has explained in the past that this factor can be especially important during rulemakings in which the automobile industry is facing significantly adverse economic conditions (with corresponding risks to jobs). Consumer acceptability is also an element of economic practicability, one which is partic ularly difficult to gauge during times of uncertain fuel prices. 696 In a rulemaking such as the present one, looking out into the more distant future, economic practicability is a way to consider the uncertainty surrounding future market conditions and consumer demand for fuel economy in addition to other vehicle attributes. In an attempt to ensure the economic practicability of attribute-based standards, NHTSA considers a variety of factors, including the annual rate at which manufacturers can increase the percentage of their fleet that employ a particular type of fuel-savin g technology, the specific fleet mixes of different manufacturers, and assumptions about the cost of the standards to consumers and consumers’ valuation of fuel economy, among other things.

At the same time, however, the law does not preclude a CAFE standard that poses considerable challenges to any individual manufacturer. The Conference Report for EPCA, as enacted in 1975, makes clear, and the case law affirms, “(A) determination of maximum feasible average fuel economy should not be keyed to the single manufacturer which might have the most difficulty achieving a given level of average fuel economy.” 697 Instead, the agency is compelled

695 67 FR 77015, 77021 (Dec. 16, 2002).

696 See

, e.g., Center for Auto Safety v. NHTSA (CAS) , 793 F.2d 1322 (D.C. Cir. 1986) (Administrator’s consideration of market demand as component of economic practicability found to be reasonable); Public Citizen v. NHTSA , 848 F.2d 256 (Congress established broad guidelines in the fuel economy statute; agency’s decision to set lower standard was a reasonable accommodation of conflicting policies).

697 CEI–I, 793 F.2d 1322, 1352 (DC Cir. 1986).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

632 “to weigh the benefits to the nation of a higher fuel economy standard against the difficulties of individual automobile manufacturers.” 698 The law permits CAFE standards exceeding the projected capability of any particular manufactur er as long as the standard is economically practicable for the industry as a whole. Thus , while a particular CAFE standard may pose difficulties for one manufacturer, it may also pres ent opportunities for another. NHTSA has long held that the CAFE program is not necessarily intended to maintain the competitive positioning of each particular company. Rather, it is intended to enhance the fuel economy of the vehicle fleet on American roads, while protecting motor ve hicle safety and being mindful of the risk to the overall United States economy.

Consequently, “economic practicability” must be considered in the context of the competing concerns associated with different levels of standards. Prior to the MY 2005–2007 rulemaking, the agency generall y sought to ensure the economic practicability of standards in part by setting them at or near the capabilit y of the “least capable manufacturer” with a significant share of the market, i.e., typically the manufacturer whose vehicles are, on average, the heaviest and largest. In th e first several rulemakings establishing attribute-based standards, the agency applied marginal cost benefit analysis. This ensured that the agency’s application of technologies was limited to those that would pay for themselves and thus should have significant appeal to consumers. We note that for this rulemaking, the agency can and has limited its application of technologies to those that are proj ected to be cost-effectiv e within the rulemaking time frame, with or without the use of such analysis.

Whether the standards maximize net benefits has thus been a touchstone, albeit a controversial one, in the past for NHTSA’s consideration of economic practicability. Executive Order 12866, as amended by Executive Order 13563, states that agencies should “select, in choosing among alternative regulatory approaches, those approaches that maximize net benefits...,” but NHTSA does not interpret this gui deline as mandating that the agency choose standards that maximize net benefits, according to our analysis, if the agency determines that the maximum feasible balancing for a particular rulemaking points to another level. 699 Moreover, while the agency’s consideration of economic pr acticability has previously been informed by marginal cost benefit analysis, the fact that standards are cost-beneficial is not the only consideration for economic practicability. Expected availability of capital to make investments in new technologies matters; manufacturers’ expected ability to sell vehicles with new technologies matters; and so forth. Economic practicability is a complex factor, and like the other factors must also be considered in the context of the overall balancing and EPCA’s overarching purpose of energy conservation. Depending on the conditions of the industry and the assumptions used in the agency’s analysis of alternative stringencies, NHTSA could well find that standards that maximize net benefits, or th at are higher or lower, could be economically practicable, and thus maximum feasible.

(3) The Effect of Other Motor Vehicle Standards of the Government on Fuel Economy

698 Id

. 699 See 70 Fed. Reg. at 51435 (Aug. 30, 2005); CBD v. NHTSA , 538 F.3d at 1197 (9 th Cir. 2008).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

633 “The effect of other motor vehicle standards of the Government on fuel economy,” involves an analysis of the effects of compliance with emission, safety, noise, or damageability standards on fuel economy capability and thus on average fuel economy. In previous CAFE rulemakings, the agency has said that pursuant to this provision, it considers the adverse effects of other motor vehicle standards on fuel economy. It said so because, from the CAFE program’s earliest years 700 until present, the effects of such co mpliance on fuel economy capability over the history of the CAFE program have been negative ones. In those instances in which the effects are negative, NHTSA has said that it is called upon to “mak[e] a straightforward adjustment to the fuel economy improvement projections to account for the impacts of other Federal standards, principally those in the areas of emission control, occupant safety, vehicle damageability, and vehicle noise. However, only the unavoidable consequences should be accounted for. The automobile manufacturers must be expected to adopt those feasible methods of achieving compliance with other Federal standards which minimize any adverse fuel economy effects of those standards.” 701 For example, safety standards that have the effect of increasing vehicle weight lower vehicle fuel economy capability and thus decrease the level of average fuel economy that the agency can determine to be feasible.

The “other motor vehicle standards” consideration has thus in practice functioned in a fashion similar to the provision in EPCA, as or iginally enacted, for adjusting the statutorilyspecified CAFE standards for MY 1978–1980 passengers cars. 702 EPCA did not permit NHTSA to amend those standards based on a finding that the maximum feasible level of average fuel economy for any of those three years was greater or less than the standard specified for that year. Instead, it provided that the agency could only reduce the standards and only on one basis: if the agency found that there had been a Federal standards fuel economy reduction, i.e., a reduction in fuel economy due to changes in the Federal vehicle standards, e.g., emissions and safety, relative to the year of enactment, 1975.

The “other motor vehicle standards” provision is broader than the Federal standards fuel economy reduction provision. Although the effects analyzed to date under the “other motor vehicle standards” provision have been negative, there could be circumstances in which the effects are positive. In the event that the agency encountered such circumstances, it would be required to consider those positive effects. For example, if chan ges in vehicle safety technology led to NHTSA’s amending a safety standard in a way that permits manufacturers to reduce the weight added in complying with that standard, th at weight reduction would increase vehicle fuel economy capability and thus increase the level of average fuel economy that could be determined to be feasible.

In the wake of Massachusetts v. EPA and of EPA’s endangerment finding, granting of a waiver to California for its motor vehicle GHG standards, and its own establishment of GHG standards, NHTSA is confronted with the issue of how to treat those standards under EPCA/EISA, such as in the context of the “oth er motor vehicle standards” provision. To the

700 42 FR 63184, 63188 (Dec. 15, 1977). See also 42 FR 33534, 33537 (Jun. 30, 1977).

701 42 FR 33534, 33537 (Jun. 30, 1977).

702 That provision was deleted as obsolete when EPCA was codified in 1994.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

634 extent the GHG standards result in increases in fuel economy, they would do so almost exclusively as a result of inducing manufacturers to install the same types of technologies used by manufacturers in complying with the CAFE standards.

Comment is requested on whether and in what way the effects of the California and EPA standards should be considered under EPCA/EISA, e.g. , under the “other motor vehicle standards” provision, consistent with NHTSA ’s independent obligation under EPCA/EISA to issue CAFE standards. The agency has already considered EPA’s proposal and the harmonization benefits of the National Program in developing its own proposal.

(4) The Need of the United States To Conserve Energy

“The need of the United States to conserve energy” means “the consumer cost, national balance of payments, environmental, and foreign policy implications of our need for large quantities of petroleum, especially imported petroleum.” 703 Environmental implications principally include those associated with reduct ions in emissions of criteria pollutants and CO 2

. A prime example of foreign policy implications are energy independence and energy security

concerns.

(a) Fuel Prices and the Value of Saving Fuel

Projected future fuel prices are a critical i nput into the preliminary economic analysis of alternative CAFE standards, because they determine the value of fuel savings both to new vehicle buyers and to society, which is related to the consumer cost (or rather, benefit) of our need for large quantities of petroleum. In this rule, NHTSA relies on fuel price projections from the U.S. Energy Information Administration’s (EIA) most recent Annual Energy Outlook (AEO) for this analysis. Federal government agencies generally use EIA’s projections in their assessments of future energy-related policies.

(b) Petroleum Consumption and Import Externalities

U.S. consumption and imports of petroleum products impose costs on the domestic economy that are not reflected in the market price for crude petroleum, or in the prices paid by consumers of petroleum products such as gasoline. These costs include (1) higher prices for petroleum products resulting from the effect of U.S. oil import demand on the world oil price; (2) the risk of disruptions to the U.S. economy caused by sudden reductions in the supply of imported oil to the U.S.; and (3) expenses for maintaining a U.S. military presence to secure imported oil supplies from unstable regions, and for maintaining the strategic petroleum reserve (SPR) to provide a response option should a disr uption in commercial oil supplies threaten the U.S. economy, to allow the United States to me et part of its International Energy Agency obligation to maintain emergency oil stocks, and to provide a national defense fuel reserve. Higher U.S. imports of crude oil or refined petroleum products increase the magnitude of these external economic costs, thus increasing the true economic cost of supplying transportation fuels

703 42 FR 63184, 63188 (1977).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

635 above the resource costs of producing them. Conversely, reducing U.S. imports of crude petroleum or refined fuels or reducing fuel consumption can reduce these external costs.

(c) Air Pollutant Emissions

While reductions in domestic fuel refining an d distribution that result from lower fuel consumption will reduce U.S. emis sions of various pollutants, additional vehicle use associated with the rebound effect 704 from higher fuel economy will increa se emissions of th ese pollutants. Thus, the net effect of stricter CAFE standards on emissions of each pollutant depends on the relative magnitudes of its reduced emissions in fu el refining and distribution, and increases in its emissions from vehicle use. 705 Fuel savings from stricter CAFE standards also result in lower emissions of CO 2 , the main greenhouse gas emitted as a result of refining, distribution, and use of transportation fuels. Reducing fuel consumpt ion reduces carbon dioxide emissions directly, because the primary source of transportation-related CO 2 emissions is fuel combustion in internal combustion engines.

NHTSA has considered environmental issues, both within the context of EPCA and the National Environmental Policy Act, in making decisions about the setting of standards from the earliest days of the CAFE program. As courts of appeal have noted in three decisions stretching over the last 20 years, 706 NHTSA defined the “need of the Nation to conserve energy” in the late 1970s as including “the consumer cost, national balance of payments, environmental, and foreign policy implications of our need for large qua ntities of petroleum, especially imported petroleum.” 707 In 1988, NHTSA included climate change concepts in its CAFE notices and prepared its first environmental assessment addressing that subject. 708 It cited concerns about climate change as one of its reasons for limiting the extent of its reduction of the CAFE standard for MY 1989 passenger cars. 709 Since then, NHTSA has considered the benefits of reducing tailpipe carbon dioxide emissions in its fuel eco nomy rulemakings pursuant to the statutory requirement to consider the nation’s need to conserve energy by reducing fuel consumption.

ii. Other Factors Considered by NHTSA

The agency historically has considered the potential for adverse safety consequences in setting CAFE standards. This practice is recognized approvingly in case law. As the courts have recognized, “NHTSA has always examined the safety consequences of the CAFE standards in its overall consideration of relevant factors since its earliest rulemaking under the CAFE program.” Competitive Enterprise Institute v . NHTSA, 901 F.2d 107, 120 n. 11 (DC Cir. 1990) (“ CEI I” )

704 The “rebound effect” refers to the tendency of drivers to drive their vehicles more as the cost of doing so goes down, as when fuel economy improves.

705 See Section IV.G below for NHTSA’s evaluation of this effect.

706 Center for Auto Safety v. NHTSA , 793 F.2d 1322, 1325 n. 12 (D.C. Cir. 1986); Public Citizen v. NHTSA , 848 F.2d 256, 262–3 n. 27 (D.C. Cir. 1988) (noting that “NHTSA itself has interpreted the factors it must consider in setting CAFE standards as including environmental effects”); and Center for Biological Diversity v. NHTSA , 538 F.3d 1172 (9 th Cir. 2007).

707 42 FR 63184, 63188 (Dec. 15, 1977) (emphasis added).

708 53 FR 33080, 33096 (Aug. 29, 1988).

709 53 FR 39275, 39302 (Oct. 6, 1988).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

636 (citing 42 FR 33534, 33551 (June 30, 1977)). The courts have consistently upheld NHTSA’s implementation of EPCA in this manner. See, e.g., Competitive Enterprise Institute v. NHTSA, 956 F.2d 321, 322 (DC Cir. 1992) (“ CEI II” ) (in determining the maximum feasible fuel economy standard, “NHTSA has always taken passenger safety into account.”) (citing CEI I, 901 F.2d at 120 n. 11); Competitive Enterprise Institute v. NHTSA, 45 F.3d 481, 482–83 (DC Cir. 1995) (“ CEI III ”) (same); Center for Biological Diversity v. NHTSA, 538 F.3d 1172, 1203–04 (9th Cir. 2008) (upholding NHTSA’s analysis of ve hicle safety issues associated with weight in connection with the MY 2008–11 light truck CAFE rule). Thus, in evaluating what levels of stringency would result in maximum feasible st andards, NHTSA assesses the potential safety impacts and considers them in balancing the st atutory considerations and to determine the maximum feasible leve l of the standards.

Under the universal or “flat” CAFE standard s that NHTSA was previously authorized to establish, manufacturers were encouraged to respond to higher standards by building smaller, less safe vehicles in order to “balance out” the larger, safer vehicles that the public generally preferred to buy, which resulted in a higher mass differential between the smallest and the largest vehicles, with a correspondingly greater risk to safety. Under the attribute-based standards being proposed today, that risk is reduced because building smaller vehicles would tend to raise a manufacturer’s overall CAFE obligation, rather than only raising its fleet average CAFE, and because all vehicles are required to continue improving their fuel economy. In prior rulemakings, NHTSA limited the application of mass reduction in our modeling analysis to vehicles over 5,000 lbs GVWR, 710 but for purposes of today’s proposed standards, NHTSA has revised its modeling analysis to allow some application of mass reduction for most types of vehicles, although it is concentrated in the largest and heaviest vehicles, because we believe that this is more consistent with how manufacturers will actually respond to the standards. However, as discussed above, NHTSA does not mandate the use of any particular technology by manufacturers in meeting the standards. More information on the approach to modeling manufacturer use of mass reduction is available in Chapter 3 of the draft Joint TSD and in Section V of the PRIA; and the estimated safety impacts that may be due to the proposed MY 2017-2025 CAFE standards are described in section IV.G below.

iii. Factors that NHTSA is Prohibited from Considering

EPCA also provides that in determining the level at which it should set CAFE standards for a particular model year, NHTSA may not consider the ability of manufacturers to take advantage of several EPCA provisions that faci litate compliance with the CAFE standards and thereby reduce the costs of compliance. 711 As discussed further below, manufacturers can earn compliance credits by exceeding the CAFE standards and then use those credits to achieve compliance in years in which their measured average fuel economy falls below the standards. Manufacturers can also increase their CAFE levels through MY 2019 by producing alternative fuel vehicles. EPCA provides an incentive for producing these vehicles by specifying that their fuel economy is to be determined using a speci al calculation procedure that results in those vehicles being assigned a high fuel economy level.

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

711 49 U.S.C. 32902(h).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

637 The effect of the prohibitions against consider ing these statutory flexibilities in setting the CAFE standards is that the flexibilities remain voluntarily-employed measures. If the agency were instead to assume manufacturer use of thos e flexibilities in setting new standards, that assumption would result in higher standards and thus tend to require manufacturers to use those flexibilities. By keeping NHTSA from including them in our stringency determination, the provision ensures that the statutory credits re main described above remain true compliance flexibilities.

On the other hand, NHTSA does not believe th at flexibilities other than those expressly identified in EPCA are similarly prohibited from being included in the agency’s determination of what standards would be maximum feasible. In order to better meet EPCA’s overarching purpose of energy conservation, the agency is therefore consid ering manufacturers’ ability to increase the calculated fuel economy levels of their vehicles through A/C efficiency improvements, as proposed by EPA, in the proposed CAFE stringency levels for passenger cars and light trucks for MYs 2017-2025. NHTSA woul d similarly consider manufacturers’ ability to raise their fuel economy using off-cycle technologi es as potentially relevant to our determination of maximum feasible CAFE standards, but because we and EPA do not believe that we can yet reasonably predict an average amount by whic h manufacturers will take advantage of this opportunity, it did not seem reasonable for the proposed standards to include it in our stringency determination at this time. We expect to re -evaluate whether and how to include off-cycle credits in determining maximum feasible sta ndards as the off-cycle technologies and how manufacturers may be expected to employ them become better defined in the future.

Additionally, because we interpret the prohibi tion against including the defined statutory credits in our determination of maximum feasible standards as ap plying only to the flexibilities expressly identified in 49 U.S.C. 32902(h), NHTSA must, for the fi rst time in this rulemaking, determine how to consider the fuel economy of dual-fueled automobiles after the statutory credit sunsets in MY 2019. Once there is no statutory cr edit to protect as a compliance flexibility, it does not seem reasonable to NHTSA to continue to interpret the statute as prohibiting the agency from setting maximum feasible levels at a higher standard, if possible, by considering the fuel economy of dual-fueled automobiles as measured by EPA. The overarching purpose of EPCA is better served by interpreting 32902(h)(2) as moot once the statutory credits provided for in 49 U.S.C. 32905 and 32906 have expired.

49 U.S.C. 32905(b) and (d) states that the special fuel economy measurement prescribed by Congress for dual-fueled automobiles applies only “in model years 1993 through 2019.” 49 U.S.C. 32906(a) also provides that the section 32905 calcu lation will sunset in 2019, as evidenced by the phase-out of the allowable increase due to that credit; it is clear that the phaseout of the allowable increase in a manufacturer’s CAFE levels due to use of dual-fueled automobiles relates only to the special statutory calculation (and not to other ways of incorporating the fuel economy of dual-fueled automobiles into the manufacturer’s fleet calculation) by virtue of language in section 32906(b), which states that “in applying subsection (a) [ i.e. , the phasing out maximum increase], the Administrator of the Environmental Protection Agency shall determine the increase in a manufacturer’s average fuel economy attributable to dual fueled automobiles by subtracting from the manufacturer’s average fuel economy calculatedDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

638 under section 32905(e) the number equal to what the manufacturer’s average fuel economy would be if it were calculated by the formula under section 32904(a)(1)....” By referring back to the special statutory calculation, Congress make s clear that the phase-out applies only to increases in fuel economy attributable to dual-fueled automobiles due to the special statutory calculation in sections 32905(b) and (d). Similarly, we interpret Congress’ statement in section 32906(a)(7) that the maximum increase in fuel ec onomy attributable to dual-fueled automobiles is “0 miles per gallon for model years after 2019” within the context of the introductory language of section 32906(a) and the language of section 32906(b), which, again, refers clearly to the statutory credit, and not to dual-fueled automobiles generally. It would be an absurd result if the phase-out of the credit meant that manufacturers would be effectively penalized, in CAFE compliance, for building dual-fueled automobiles like plug-in hybrid electric vehicles, which may be important “bridge” vehicles in helping consumers move toward full electric vehicles.

NHTSA has therefore considered the fuel ec onomy of plug-in hybrid electric vehicles (the only dual-fueled automobiles that we predict in significant numbers in MY 2020 and beyond; E85-capable FFVs are not predicted in great numbers after the statutory credit sunsets, and we do not have sufficient information about potential dual-fueled CNG/gasoline vehicles to make reasonable estimates now of their numbers in that time frame in determining the maximum feasible level of the MY 2020-2025 CAFE standards for passenger cars and light trucks.

iv. Determining the Level of the Standards by Balancing
the Factors

NHTSA has broad discretion in balancing the above factors in determining the appropriate levels of average fuel economy at which to set the CAFE standards for each model year. Congress “specifically delegated the process of setting * * * fuel economy standards with broad guidelines concerning the factors that the agency must consider.” 712 The breadth of those guidelines, the absence of any statutorily prescribed formula for balancing the factors and other considerations, the fact that the relative weight to be given to the various factors may change from rulemaking to rulemaking as the underlying facts change, and the fact that the factors may often be conflicting with respect to whether they militate toward higher or lower standards give NHTSA broad discretion to decide what weight to give each of the competing policies and concerns and then determine how to balance them. The exercise of that discretion is subject to the necessity of ensuring that NHTSA’s balancing does not undermine the fundamental purpose of EPCA, energy conservation, 713 and as long as that balancing reasonably accommodates “conflicting policies that were committed to the agency’s care by the statute.” 714 The balancing of the factors in any given rulemaking is highly dependent on the factual and policy context of that rulemaking and the agency’s assumptions about the factual and policy context during the time frame covered by the standards at issue. Given the changes over time in facts bearing on assessment of the various factors, such as thos e relating to economic conditions, fuel prices, and the state of climate change science, the agency recognizes that what was a reasonable balancing of competing statutory priorities in one rulemaking may or may not be a reasonable balancing of

712 Center for Auto Safety v. NHTSA, 793 F.2d 1322, 1341 (C.A.D.C. 1986).

713 Center for Biological Diversity v. NHTSA, 538 F.3d 1172, 1195 (9th Cir. 2008).

714 CAS , 1338 (quoting Chevron U.S.A., Inc. v. Natural Resources Defense Council, Inc., 467 U.S. 837, 845).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

639 those priorities in another rulemaking. 715 Nevertheless, the agency retains substantial discretion under EPCA to choose among reasonable alternatives.

EPCA neither requires nor precludes the use of any type of cost-benefit analysis as a tool to help inform the balancing process. As di scussed above, while NHTSA used marginal costbenefit analysis in the first two rulemakings to establish attribute-based CAFE standards, it was not required to do so and is not required to continue to do so. Regardless of what type of analysis is or is not used, considerations relating to costs and benefits remain an important part of CAFE standard setting.

Because the relevant considerations and factors can reasonably be balanced in a variety of ways under EPCA, and because of uncertainties associated with the many technological and cost inputs, NHTSA considers a wide variety of alternative sets of standards, each reflecting different balancing of those policies and concerns , to aid it in discerning reasonable outcomes. Among the alternatives providing for an increase in the standards in this rulemaking, the alternatives range in stringency from a set of standards that increase, on average, 2 percent annually to a set of standards that increase, on average, 7 percent annually.

v. Other Standards

(1) Minimum Domestic Passenger Car Standard

The minimum domestic passenger car standard was added to the CAFE program through EISA, when Congress gave NHTSA explicit au thority to set universal standards for domestically-manufactured passenger cars at the level of 27.5 mpg or 92 percent of the average fuel economy of the combined domestic and import passenger car fleets in that model year, whichever was greater. 716 This minimum standard was intended to act as a “backstop,” ensuring that domestically-manufactured passenger cars reached a given mpg level even if the market shifted in ways likely to reduce overall fleet mpg. Congress was silent as to whether the agency could or should develop similar backstop standards for imported passenger cars and light trucks. NHTSA has struggled with this question since EISA was enacted.

NHTSA has proposed minimum standards fo r domestically-manufactured passenger cars in Section IV.E below, but we also seek comment on whether to consider, for the final rule, the possibility of minimum standards for imported passenger cars and light trucks. Although we are not proposing such standards, we believe it may be prudent to explore this concept again given the considerable amount of time between now and 2017-2025 (particularly the later years), and the accompanying uncertainty in our market forecast and other assumptions, that might make such minimum standards relevant to help en sure that currently-expected fuel economy improvements occur during that time frame. To help commenters’ c onsideration of this question, Section IV.E presents illustrative leve ls of minimum standards for those other fleets.

The minimum domestic passenger car standard was added to the CAFE program through EISA, when Congress gave NHTSA explicit au thority to set universal standards for

715 CBD v. NHTSA, 538 F.3d 1172, 1198 (9th Cir. 2008).

716 49 U.S.C. 32902(b)(4).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

640 domestically-manufactured passenger cars at the le vel explained above. This minimum standard was intended to act as a “backstop,” ensuring that domestically-manufactured passenger cars reached a given mpg level even if the market shifted in ways likely to reduce overall fleet mpg. Congress was silent as to whether the agency co uld or should develop similar backstop standards for imported passenger cars and light trucks. NHTSA has struggled with this question since EISA was enacted.

In the MY 2011 final rule, facing comments split fairly evenly between support and opposition to additional backstop standards, NHTSA noted Congress’ silence with respect to minimum standards for imported passenger cars a nd light trucks and “accept[ed] at least the possibility that . . . [it] could be reasonably interp reted as permissive rather than restrictive,” but concluded based on the record for that rulemaking as a whole that additional minimum standards were not necessary for MY 2011, given the lack of leadtime for manufacturers to change their MY 2011 vehicles, the apparently-growing public preference for smaller vehicles, and the antibacksliding characteristics of the footprint-based curves. 717

In the MYs 2012-2016 final rule where NHTSA declined to set minimum standards for imported passenger cars and light trucks, the agency did so not because we believed that we did not have authority to do so, but because we believed that our assumptions about the future fleet mix were reliable within the rulemaking time frame , and that backsliding was very unlikely and would not be sufficient to warrant the regulatory burden of additional minimum standards for those fleets. 718 NHTSA also expressed concern about the possibility of additional minimum standards imposing inequitable regulatory burdens of the kind that attribute-based standards sought to avoid, stating that:

Unless the backstop was at a very weak level, above the high end of this range, then some percentage of manufacturers would be above the backstop even if the performance of the entire industry remains fu lly consistent with the emissions and fuel economy levels projected for the final standards. For these manufacturers and any other manufacturers who were above the backstop, the objectives of an attribute-based standard would be compromised and unnecessary costs would be imposed. This could directionally impose increased costs for some manufacturers. It would be difficult if not impossible to establish the level of a backstop standard such that costs are likely to be imposed on manufacturers only when there is a failure to achieve the projected reductions across the industry as a whole. An example of this kind of industry-wide situation could be when there is a significant shift to larger vehicles across the industry as a whole, or if there is a general market shift from cars to trucks. The problem the agencies are concerned about in those circumstances is not with respect to any single manufacturer, but rather is based on concerns over shifts across the fleet as a whole, as compared to shifts in one manufacturer’s fl eet that may be more than offs et by shifts the other way in another manufacturer’s fleet. However, in th is respect, a traditional backstop acts as a manufacturer-specific standard. 719

717 74 FR at 14412 (Mar. 30, 2009).

718 75 Fed. Reg. 25324, at 25368-70 (May 7, 2010).

719 Id . at 25369.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

641 NHTSA continues to believe that the risk of additional minimum standards imposing inequitable regulatory burdens on certain manufacturers is real, but at the same time, we recognize that given the time frame of the current rulemaking, the agency cannot be as certain about the unlikelihood of future market changes. Depending on the price of fuel and consumer preferences, the “kind of industry-wide situation” described in the MYs 2012-2016 rule is possible in the 2017-2025 time frame, particularly in the later years.

Because the agency does not have sufficient information at this time regarding what tradeoffs might be associated with additional mi nimum standards, specifically, whether the risk of backsliding during MYs 2017-2025 sufficiently outweighs the possibility of imposing inequitable regulatory burdens on certain manufacturers, we are seeking comment in this NPRM on these issues but not proposing additional mini mum standards at this time. We also seek comment on how to structure additional minimum standards ( e.g. , whether they should be flat or attribute-based, and if the latter, how that wo uld work), and at what level additional minimum standards should potentially be set. The tables in Section IV.E provide an illustration of what levels the additional minimum standards would require if the agency followed the same 92 percent guideline required by EISA for domestically-manufactured passenger cars.

(2) Alternative standards for certain manufacturers

Because EPCA states that standards must be set for “...automobiles manufactured by manufacturers,” and because Congress provid ed specific direction on how small-volume manufacturers could obtain exemptions from the passenger car standards, NHTSA has long interpreted its authority as pertaining to setting st andards for the industry as a whole. Prior to this NPRM, some manufacturers raised with NHTSA the possibility of NHTSA and EPA setting alternate standards for part of the industry that me t certain (relatively low) sales volume criteria – specifically, that separate standards be set so that “intermediate-size,” limited-line manufacturers do not have to meet the same levels of stringen cy that larger manufactur ers have to meet until several years later. These manufacturers argued that the same level of standards would not be technologically feasible or economically practicable in the same time frame for them, due to their inability to spread compliance burden acros s a larger product lineup, and difficulty in obtaining fuel economy-improving technolog ies quickly from suppli ers. NHTSA seeks comment on whether or how EPCA, as amended by EISA, could be interpreted to allow such alternate standards for certain parts of the industry.

2. Administrative Procedure Act

To be upheld under the “arbitrary and capricious” standard of judicial review in the APA, an agency rule must be rational, based on consideration of the relevant factors, and within the scope of the authority delegated to the agency by the statute. The agency must examine the relevant data and articulate a satisfactory explanation for its action including a “rational connection between the facts found and the choice made.” Burlington Truck Lines, Inc. v. United States, 371 U.S. 156, 168 (1962).

Statutory interpretations included in an agency’s rule are subjected to the two-step analysis of Chevron, U.S.A., Inc. v. Natural Resources Defense Council, 467 U.S. 837, 104 S.Ct.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

642 2778, 81 L.Ed.2d 694 (1984). Under step one, wher e a statute “has directly spoken to the precise question at issue,” id. at 842, 104 S.Ct. 2778, the court and the agency “must give effect to the unambiguously expressed intent of Congress,” id. at 843, 104 S.Ct. 2778. If the statute is silent or ambiguous regarding the specific question, the court proceeds to step two and asks “whether the agency’s answer is based on a perm issible construction of the statute.” Id.

If an agency’s interpretation differs from the one that it has previously adopted, the agency need not demonstrate that the prior position was wrong or even less desirable. Rather, the agency would need only to demonstrate that its new position is consistent with the statute and supported by the record, and acknowledge that this is a depa rture from past positions. The Supreme Court emphasized this recently in FCC v. Fox Television, 129 S.Ct. 1800 (2009). When an agency changes course from earlier regulations, “the requirement that an agency provide reasoned explanation for its action woul d ordinarily demand that it display awareness that it is changing position,” but “need not demonstrate to a court’s satisfaction that the reasons for the new policy are better than the reasons for the old one; it suffices that the new policy is permissible under the statute, that there ar e good reasons for it, and that the agency believes it to be better, which the conscious change of course adequately indicates.” 720 The APA also requires that agencies provide notice and comment to the public when proposing regulations, 721 as we are doing here today.

3. National Environmental Policy Act

As discussed above, EPCA requires the agency to determine what level at which to set the CAFE standards for each model year by c onsidering the four factors of technological feasibility, economic practicability, the eff ect of other motor vehicle standards of the Government on fuel economy, and the need of the United States to conserve energy. NEPA directs that environmental considerations be inte grated into that process. To accomplish that purpose, NEPA requires an agency to compare the potential environmental impacts of its proposed action to those of a reasonable range of alternatives.

To explore the environmental consequences in depth, NHTSA has prepared a draft environmental impact statement (“EIS”). The purpose of an EIS is to “provide full and fair discussion of significant environmental impacts a nd [to] inform decisionmakers and the public of the reasonable alternatives which would avoid or minimize adverse impacts or enhance the quality of the human environment.” 40 CFR 1502.1.

NEPA is “a procedural statute th at mandates a process rather than a particular result.” Stewart Park & Reserve Coal., Inc. v. Slater, 352 F.3d at 557. The agency’s overall EIS-related obligation is to “take a ‘hard look’ at the environmental consequences before taking a major action.” Baltimore Gas & Elec. Co. v. Natural Res. Def. Council, Inc., 462 U.S. 87, 97, 103 S.Ct. 2246, 76 L.Ed.2d 437 (1983). Significantly, “[i]f the adverse environmental effects of the proposed action are adequately identified and evalua ted, the agency is not constrained by NEPA from deciding that other values outweigh the environmental costs.” Robertson v. Methow Valley Citizens Council, 490 U.S. 332, 350, 109 S.Ct. 1835, 104 L.Ed.2d 351 (1989).

720 Ibid., 1181.

721 5 U.S.C. 553.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

643 The agency must identify the “environmentally preferable” alternative, but need not adopt it. “Congress in enacting NEPA * * * did not require agencies to elevate environmental concerns over other appropriate considerations.” Baltimore Gas and Elec. Co. v. Natural Resources Defense Council, Inc., 462 U.S. 87, 97 (1983). Instead, NEPA requires an agency to develop alternatives to the proposed action in preparing an EIS. 42 U.S.C. 4332(2)(C)(iii). The statute does not command the agency to favor an environmentally preferable course of action, only that it make its decision to proceed with the action after taking a hard look at environmental

consequences.

E. What are the proposed CAFE standards?

1. Form of the Standards

Each of the CAFE standards that NHTSA is proposing today for passenger cars and light trucks is expressed as a mathematical function that defines a fuel economy target applicable to each vehicle model and, for each fleet, establishes a required CAFE level determined by computing the sales-weighted harmonic average of those targets. 722

As discussed above in Section II.C, NHTSA has determined passenger car fuel economy targets using a constrained linear function defined according to the following formula:

1

1 1

, , TARGET

MIN MAX c FOOTPRINT d a b     
         

Here, TARGET is the fuel economy target (i n mpg) applicable to vehicles of a given footprint (FOOTPRINT, in square feet), b and a are the function’s lower and upper asymptotes (also in mpg), respectively, c is the slope (in gallons per mile per square foot) of the sloped portion of the function, and d is the intercept (in gallons per mile) of the sloped portion of the function (that is, the value the sloped portion would take if extended to a footprint of 0 square feet. The MIN and MAX functions take the minimum and maximum, respectively of the included values.

NHTSA is proposing, consistent with the standards for MYs 2011-2016, that the CAFE level required of any given manufacturer be determined by calculating the production-weighted harmonic average of the fuel economy targets applicable to each vehicle model:

722 Required CAFE levels shown here are estimated re quired levels based on NHTSA’s current projection of
manufacturers’ vehicle fleets in MYs 2017–2025. Actual re quired levels are not determined until the end of each model year, when all of the vehicles produced by a manufacturer in that model year are known and their compliance obligation can be determined with certainty. The target curv es, as defined by the constrained linear function, and as embedded in the function for the sales-weighted harmonic av erage, are the real “standards” being proposed today.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

644 ܧܨܣܥ ௗ௜௥௘௨௥௘௤ ൌ ∑ ܱܰܫܶܥܷܦܴܱܲ ௜ ௜ ∑ ܱܰܫܶܥܷܦܴܱܲ ௜ ܶܧܩܴܣܶ ௜ ௜

PRODUCTION i is the number of units produced for sale in the United States of each i th unique footprint within each model type, produced for sale in the United States, and TARGET i is the corresponding fuel economy target (according to the equation shown above and based on the corresponding footprint), and the summations in the numerator and denominator are both performed over all unique footprint and model type combinations in the fleet in question.

The proposed standards for passenger cars are, therefore, specified by the four coefficients defining fuel economy targets:

a = upper limit (mpg) b = lower limit (mpg)

c = slope (gallon per mile per square foot) d

= intercept (gallon per mile)

For light trucks, NHTSA is proposing to define fuel economy targets in terms of a mathematical function under which the target is the maximum of values determined under each of two constrained linear functions. The second of these establishes a “floor” reflecting the MY 2016 standard, after accounting for estimated adju stments reflecting increased air conditioner efficiency. This prevents the target at any f ootprint from declining betw een model years. The resultant mathematical function is as follows:

ܶܧܩܴܣܶ

ൌ ܣܯܺ ൮ 1

ܰܫܯ ቂ ܺܣܯ ቀ ݀, ൅ ܰܶܫܱܱܴܶܲܨ ൈ ܿ 1

ܽ ቁ

, 1 ܾ ቃ , 1

ܰܫܯ ൤ ܺܣܯ ቀ ݄, ൅ ܰܶܫܱܱܴܶܲܨ ൈ ݃ 1

݁ ቁ

, 1 ݂ ൨ ൲

The proposed standards for light trucks are, th erefore, specified by the eight coefficients defining fuel economy targets:

a = upper limit (mpg) b = lower limit (mpg)

c = slope (gallon per mile per square foot) d

= intercept (gallon per mile)

e = upper limit (mpg) of “floor” f

= lower limit (mpg) of “floor”

g

= slope (gallon per mile per square foot) of “floor” h = intercept (gallon per mile) of “floor”

2. Passenger Car Standards for MYs 2017–2025

For passenger cars, NHTSA is proposing CAFE standards defined by the followingDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

645 coefficients during MYs 2017–2025:

T ABLE IV.E.2–1—C OEFFICIENTS D EFINING P ROPOSED MY S 2017–2025 F UEL E CONOMY T ARGETS F OR P ASSENGER C ARS

Coefficient 2017 2018 2019 2020 2021 2022 2023 2024 2025

a (mpg) 42.50 42.94 43.39 43.84 44.29 44.75 45.21 45.68 46.16
b (mpg) 31.83 32.16 32.49 32.82 33.16 33.50 33.84 34.19 34.55

c (gpm/sf) 0.00053 0.00052 0.00052 0.00051 0.00051 0.00050 0.00050 0.00049 0.00049
d (gpm) 0.00196 0.00193 0.00191 0.00188 0.00186 0.00183 0.00181 0.00179 0.00176

For reference, the coefficients defining the MYs 2012-2016 passenger car standards are also provided below:

T ABLE IV.E.2–2—C OEFFICIENTS D EFINING F INAL MY S 2012–2016 F UEL E CONOMY T ARGETS F OR P ASSENGER C ARS

Coefficient 2012 2013 2014 2015 2016

a (mpg) 36.18 37.16 38.31 40.06 42.03
b (mpg) 28.09 28.67 29.35 30.37 31.49

c (gpm/sf) 0.00053 0.00053 0.00053 0.00053 0.00053
d (gpm) 0.00588 0.00515 0.00434 0.00320 0.00203

Also for reference, the following table presents the coefficients based on 2-cycle CAFE only for easier comparison to the MYs 2012-2016 coefficients presented above. We emphasize, again, that the coefficients in Table IV.E.2-1 define the proposed standards.

T ABLE IV.E.2–3—C OEFFICIENTS B ASED O NLY ON 2-C YCLE CAFE FOR MY S 2017–2025
P ASSENGER C ARS

Coefficient 2017 2018 2019 2020 2021 2022 2023 2024 2025

a (mpg) 42.57 44.09 45.66 47.44 49.42 51.66 54.01 56.47 59.04
b (mpg) 32.06 33.21 34.39 35.73 37.22 38.92 40.69 42.54 44.47

c (gpm/sf) 0.00051 0.00050 0.00048 0.00046 0.00044 0.00042 0.00040 0.00039 0.00037
d (gpm) 0.00246 0.00237 0.00229 0.00221 0.00212 0.00203 0.00194 0.00185 0.00177

Section II.C above and Chapter 2 of the draft Joint TSD discusses how the coefficients in Table IV.E.2-1 were developed for this proposed rule. The proposed coefficients result in the footprint-dependent targets shown graphically below for MYs 2017-2025. The MY 2012-2016 final standards are also shown for comparison.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL646FIGUREIV.E.1—FUELECONOMYTARGETS FORMYS2012–2016AND2017–2025PASSENGERCARS2025303540455055606530 35 40 45 50 55 60 65 70 75 80

Fuel Economy Target (mpg)Footprint (sf)20252024202320222021202020192018201720162015201420132012DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

647 As discussed, the CAFE levels ultimately required of individual manufacturers will depend on the mix of vehicles they produce for sale in the United States. Based on the market forecast of future sales that NHTSA has used to examine today’s proposed CAFE standards, the agency currently estimates that the target curves shown above will result in the following average required fuel economy levels for individual manufacturers during MYs 2017–2025 (an updated estimate of the average required fuel economy level under the final MY 2016 standard is also shown for comparison): 723

T ABLE IV.E.2–4—E STIMATED A VERAGE F UEL E CONOMY R EQUIRED U NDER F INAL MY 2016 AND P ROPOSED MY S 2017–2025 CAFE S TANDARDS F OR P ASSENGER C ARS

Manufacturer 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
Aston Martin 38.2 40.5 41.9 43.5 45.2 47.2 49.4 51.7 54.1 56.6
BMW 37.3 39.4 40.9 42.4 44.1 46.0 48.1 50.4 52.7 55.2 Daimler 35.9 37.8 39.1 40.5 42.2 44.0 46.1 48.2 50.4 52.8 Chrysler/Fiat 724 36.6 39.2 40.7 42.2 43.7 45.7 48.0 50.2 52.7 55.1 Ford 37.1 39.1 40.6 42.1 43.7 45.6 47.7 49.9 52.3 54.7 Geely (Volvo) 36.6 38.8 40.3 41.7 43.4 45.3 47.4 49.6 51.9 54.4 General Motors 36.9 39.3 40.7 42.3 43.9 45.8 48.0 50.2 52.6 55.1 Honda 38.3 40.5 42.0 43.6 45.3 47.3 49.5 51.7 54.2 56.7 Hyundai 38.2 40.3 41.8 43.4 45.1 47.1 49.3 51.5 54.0 56.5
Kia 37.9 40.0 41.5 43.1 44.8 46.7 48.9 51.2 53.6 56.1
Lotus 41.1 43.6 45.2 46.9 48.7 50.8 53.2 55.7 58.3 61.1 Mazda 38.3 40.5 41.9 43.5 45.2 47.1 49.2 51.5 54.0 56.6
Mitsubishi 38.7 41.1 42.6 44.2 45.9 47.9 50.1 52.5 54.9 57.5 Nissan 37.7 39.7 41.2 42.7 44.4 46.3 48.4 50.7 53.1 55.5 Porsche 41.1 43.6 45.2 46.9 48.7 50.8 53.2 55.7 58.3 61.1 Spyker (Saab) 38.3 40.6 42.1 43.6 45.3 47.3 49.5 51.8 54.2 56.8
Subaru 39.3 41.7 43.2 44.8 46.6 48.6 50.9 53.3 55.8 58.4 Suzuki 40.8 43.3 44.9 46.5 48.4 50.5 52.8 55.3 57.9 60.6 Tata (Jaguar, Rover) 34.7 36.8 38.1 39.6 41.1 42.9 44.9 47.0 49.2 51.5
Tesla 41.1 43.6 45.2 46.9 48.7 50.8 53.2 55.7 58.3 61.1 Toyota 38.4 40.7 42.2 43.8 45.5 47.5 49.7 52.0 54.4 57.0
VW 725 38.9 41.2 42.7 44.2 46.0 48.0 50.2 52.6 55.0 57.6 Average 37.8 40.0 41.4 43.0 44.7 46.6 48.8 51.0 53.5 56.0

Because a manufacturer’s required average fuel economy level for a model year under

723 In the May 2010 final rule establishing MY 2016 standa rds for passenger cars and light trucks, NHTSA estimated that the required fuel economy levels for passenger car s would average 37.8 mpg under the MY 2016 passenger car standard. Based on the agency’s current forecast of th e MY 2016 passenger car market, NHTSA again estimates that the average required fuel economy level fo r passenger cars will be 37.8 mpg in MY 2016.

724 For purposes of CAFE compliance, “Chrysler/Fiat” is assumed to include Ferrari and Maserati in addition to the larger-volume Chrysler and Fiat brands.

725 For purposes of CAFE compliance, VW is assumed to include Audi-Bentley, Bugatti, and Lamborghini, along with the larger-volume VW brand.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

648 the final standards will be based on its actual production numbers in that model year, its official required fuel economy level will not be known until the end of that model year. However, because the targets for each vehicle footprint will be established in advance of the model year, a manufacturer should be able to estimate its required level accurately. Readers should remember that the mpg levels describing the “estimated required standards” shown throughout this section are not necessarily the ultimate mpg level with wh ich manufacturers will have to comply, for the reasons explained above, and that the mpg level designated as “estimated required” is exactly that, an estimate.

Additionally, again for re ference, the following table presents estimated mpg levels based on 2-cycle CAFE for easier comparison to the MYs 2012-2016 standards.

T ABLE IV.E.2–5—E STIMATED A VERAGE F UEL E CONOMY R EQUIRED U NDER F INAL MY

2016 AND U SING 2-C YCLE CAFE FOR MY S 2017-2025 F OR P ASSENGER C ARS

Manufacturer 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
Aston Martin 38.2 39.6 41.0 42.4 44.1 45.9 48.0 50.2 52.5 54.9
BMW 37.3 38.6 40.0 41.4 43.0 44.8 46.8 49.0 51.2 53.5 Daimler 35.9 37.0 38.2 39.6 41.2 42.9 44.9 46.9 49.0 51.2 Chrysler/Fiat 726 36.6 38.3 39.7 41.2 42.7 44.6 46.7 48.8 51.2 53.5 Ford 37.1 38.3 39.7 41.1 42.7 44.4 46.5 48.6 50.8 53.1 Geely (Volvo) 36.6 38.0 39.4 40.8 42.4 44.1 46.1 48.2 50.5 52.8
General Motors 36.9 38.4 39.8 41.3 42.9 44.7 46.7 48.8 51.1 53.4 Honda 38.3 39.6 41.1 42.5 44.2 46.0 48.1 50.3 52.6 55.0 Hyundai 38.2 39.5 40.9 42.3 44.0 45.8 47.9 50.1 52.4 54.8 Kia 37.9 39.2 40.6 42.0 43.7 45.5 47.6 49.7 52.0 54.4
Lotus 41.1 42.6 44.1 45.7 47.4 49.4 51.7 54.0 56.5 59.0 Mazda 38.3 39.6 41.0 42.5 44.1 45.9 47.9 50.1 52.4 54.8 Mitsubishi 38.7 40.1 41.6 43.1 44.8 46.6 48.8 51.0 53.3 55.7 Nissan 37.7 38.9 40.3 41.7 43.3 45.1 47.2 49.3 51.5 53.9 Porsche 41.1 42.6 44.1 45.7 47.4 49.4 51.7 54.0 56.5 59.0 Spyker (Saab) 38.3 39.7 41.1 42.6 44.2 46.1 48.2 50.3 52.6 55.0
Subaru 39.3 40.7 42.2 43.7 45.4 47.3 49.5 51.7 54.1 56.5 Suzuki 40.8 42.2 43.8 45.3 47.1 49.1 51.3 53.6 56.1 58.6 Tata (Jaguar, Rover) 34.7 36.0 37.3 38.6 40.1 41.8 43.7 45.7 47.7 49.9
Tesla 41.1 42.6 44.1 45.7 47.4 49.4 51.7 54.0 56.5 59.0 Toyota 38.4 39.8 41.2 42.7 44.4 46.2 48.3 50.5 52.8 55.2
VW 727 38.9 40.2 41.7 43.1 44.8 46.7 48.9 51.1 53.4 55.8 Average 37.8 39.1 40.5 42.0 43.6 45.4 47.5 49.6 51.9 54.3

726 For purposes of CAFE compliance, “Chrysler/Fiat” is assumed to include Ferrari and Maserati in addition to the larger-volume Chrysler and Fiat brands.

727 For purposes of CAFE compliance, VW is assumed to include Audi-Bentley, Bugatti, and Lamborghini, along with the larger-volume VW brand.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

649 3. Minimum Domestic Passenger Car Standards

EISA expressly requires each manufacturer to meet a minimum fuel economy standard for domestically manufactured passenger cars in addition to meeting the standards set by NHTSA. According to the statute (49 U.S.C. 32902(b)(4)), the minimum standard shall be the greater of (A) 27.5 miles per gallon; or (B) 92 percent of the average fuel economy projected by the Secretary for the combined domestic and nondomestic passenger automobile fleets manufactured for sale in the United States by all manufacturers in the model year. The agency must publish the projected minimum standards in the Federal Register when the passenger car standards for the model year in question are promulgated. As a practical matter, as standards for both cars and trucks continue to rise over time , 49 U.S.C. 32902(b)(4)(A) will likely eventually cease to be relevant.

As discussed in the final rule establishing the MYs 2012-2016 CAFE standards, because 49 U.S.C. 32902(b)(4)(B) states that the minimum domestic passenger car standard shall be 92 percent of the projected average fuel economy for the passenger car fleet, “which projection shall be published in the Federal Register when the st andard for that model year is promulgated in accordance with this section,” NHTSA interprets EISA as indicating that the minimum domestic passenger car standard should be based on the agency’s fleet assumptions when the passenger car standard for that year is promulgated.

However, we note that we do not read this language to preclude any change, ever, in theminimum standard after it is first promulgated for a model year. As long as the 18-month leadtime requirement of 49 U.S.C. 32902(a) is resp ected, NHTSA believes that the language of the statute suggests that the 92 percent should be determined anew any time the passenger car standards are revised. This issue will be particularly relevant for the current rulemaking, given the considerable leadtime involved and the necessity of a mid-term review for the MYs 2022- 2025 standards. We seek comment on this interpretation, and on whether or not the agency should consider instead for MYs 2017-2025 designating the minimum domestic passenger car standards proposed here as “estimated,” just as the passenger car standards are “estimated,” and waiting until the end of each model year to finalize the 92 percent mpg value.

We note also that in the MYs 2012-2016 final rule, we interpreted EISA as indicating that the 92 percent minimum standard should be based on the estimated required CAFE level rather than, as suggested by the Alliance, the estimated achieved CAFE level (which would likely be lower than the estimated required level if it reflected manufacturers’ use of dual-fuel vehicle credits under 49 U.S.C. 32905, at least in the context of the MYs 2012-2016 standards). NHTSA continues to believe that this interpretation is appropriate.

Based on NHTSA’s current market forecast, the agency’s estimates of these minimum standards under the proposed MYs 2017-2025 CAFE standards (and, for comparison, the final MY 2016 minimum domestic passenger car standard) are summarized below in Table IV.E.3–1.

T ABLE IV.E.3–1—E STIMATED M INIMUM S TANDARD F OR D OMESTICALLY M ANUFACTURED P ASSENGER C ARS U NDER F INAL MY 2016 AND P ROPOSED MY S 2017–2025DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

650 CAFE S TANDARDS F OR P ASSENGER C ARS

2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

34.7 36.8 38.1 39.6 41.1 42.9 44.9 47.0 49.2 51.5

Again, for the reader’s reference, the following table the following table presents estimated mpg levels based on 2-cycle CAFE for easier comparison to the MYs 2012-2016 standards.

T ABLE IV.E.3–2—E STIMATED M INIMUM S TANDARD F OR D OMESTICALLY

M ANUFACTURED P ASSENGER C ARS U NDER F INAL MY 2016 AND U SING 2-C YCLE CAFE O NLY

FOR MY S 2017–2025 P ASSENGER C ARS

2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

34.7 35.9 37.2 38.6 40.1 41.7 43.7 45.6 47.7 49.9

As discussed in Section IV.D above, NHTSA is also seeking comment on whether to consider, for the final rule, the possibility of mi nimum standards for imported passenger cars and light trucks. Although we are not proposing such standards, we believe it may be prudent to explore this concept again given the considerable amount of time between now and 2017-2025 (particularly the later years), and the accompanying uncertainty in our market forecast and otherassumptions, that might make such minimum standards relevant to help ensure that currentlyexpected fuel economy improvements occur during that time frame. To help commenters’ consideration of this question, illustrative levels of minimum standards for those other fleets are presented below.

T ABLE IV.E.3–3—I LLUSTRATIVE E STIMATED M INIMUM S TANDARD F OR I MPORTED P ASSENGER C ARS U NDER P ROPOSED MY S 2017–2025 CAFE S TANDARDS F OR P ASSENGER C ARS

2017 2018 2019 2020 2021 2022 2023 2024 2025

36.8 38.1 39.6 41.1 42.9 44.9 47.0 49.2 51.5

T ABLE IV.E.3–4—I LLUSTRATIVE E STIMATED M INIMUM S TANDARD F OR L IGHT T RUCKS

U NDER P ROPOSED MY S 2017–2025 CAFE S TANDARDS F OR L IGHT T RUCKS

2017 2018 2019 2020 2021 2022 2023 2024 2025

27.1 27.6 28.1 28.7 30.7 32.1 33.7 35.4 37.1

NHTSA emphasizes again that we are not proposing additional minimum standards for imported passenger cars and light trucks at this time, but we may consider including them in the final rule if it seems reasonable and appropriate to do so based on the information provided by commenters and the agency’s analysis. NHTSA also may wait until we are able to observe potential market changes during the implementation of the MYs 2012-2016 standards andDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

651 consider additional minimum standards in a fu ture rulemaking action. Any additional minimum standards for MYs 2022-2025 that may be set in the future would, like the primary standards, be subject to the mid-term review discussed in S ection IV.B above, and potentially revised at that time.

4. Light Truck Standards

For light trucks, NHTSA is proposing CAFE standards defined by the following coefficients during MYs 2017–2025:

T ABLE IV.E.4–1—C OEFFICIENTS D EFINING P ROPOSED MY S 2017–2025 F UEL E CONOMY T ARGETS F OR L IGHT T RUCKS

Coefficient 2017 2018 2019 2020 2021 2022 2023 2024 2025

a (mpg) 43.61 45.21 46.87 48.74 50.83 53.21 55.71 58.32 61.07
b (mpg) 32.65 33.84 35.07 36.47 38.02 39.79 41.64 43.58 45.61

c (gpm/sf) 0.00051 0.00050 0.00048 0.00046 0.00044 0.00042 0.00040 0.00039 0.00037
d (gpm) 0.00190 0.00181 0.00173 0.00164 0.00155 0.00146 0.00137 0.00129 0.00121

e (mpg) 42.06 42.06 42.06 42.06 42.06 42.06 42.06 42.06 42.06 f (mpg) 31.51 31.51 31.51 31.51 31.51 31.51 31.51 31.51 31.51

g

(gpm/sf) 0.00053 0.00053 0.00053 0.00053 0.00053 0.00053 0.00053 0.00053 0.00053
h (gpm) 0.00201 0.00201 0.00201 0.00201 0.00201 0.00201 0.00201 0.00201 0.00201

For reference, the coefficients defining the MYs 2012-2016 light truck standards (which did not include a “floor” term defined by coefficients e , f

, g , and h ) are also provided below:

T ABLE IV.E.4–2—C OEFFICIENTS D EFINING F INAL MY S 2012–2016 F UEL E CONOMY T ARGETS F OR L IGHT T RUCKS

Coefficient 2012 2013 2014 2015 2016

a (mpg) 36.18 37.16 38.31 40.06 42.03
b (mpg) 28.09 28.67 29.35 30.37 31.49

c (gpm/sf) 0.00053 0.00053 0.00053 0.00053 0.00053
d (gpm) 0.00588 0.00515 0.00434 0.00320 0.00203

The proposed coefficients result in the f ootprint-dependent targets shown graphically below for MYs 2017-2025. MYs 2012-2016 final standards are shown for comparison.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL652FIGUREIV.E.1—FUELECONOMYTARGETS FORMYS2012–2016AND2017–2025LIGHTTRUCKS2025303540455055606530 35 40 45 50 55 60 65 70 75 80

Fuel Economy Target (mpg)Footprint (sf)20252024202320222021202020192018201720162015201420132012DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 653 of 768 Also for reference, the following table presents the coefficients based on 2-cycle CAFE only for easier comparison to the MYs 2012-2016 coefficients presented above. We emphasize, again, that the coefficients in Table IV.E.2-1 define the proposed standards.

T ABLE IV.E.4–3—C OEFFICIENTS B ASED O NLY ON 2-C YCLE CAFE FOR MY S 2017–2025
L IGHT T RUCKS

Coefficient 2017 2018 2019 2020 2021 2022 2023 2024 2025

a (mpg) 35.53 36.37 37.01 37.91 40.43 42.29 44.24 46.28 48.42
b (mpg) 24.74 24.74 24.74 24.74 24.74 25.74 26.93 28.17 29.47

c (gpm/sf) 0.00055 0.00054 0.00053 0.00051 0.00048 0.00046 0.00044 0.00042 0.00040
d (gpm) 0.00566 0.00553 0.00543 0.00530 0.00497 0.00475 0.00454 0.00434 0.00415

Again, given these targets, the CAFE leve ls required of individual manufacturers will depend on the mix of vehicles they produce for sale in the United States. Based on the market forecast NHTSA has used to examine today’s proposed CAFE standards, the agency currently estimates that the targets shown above will result in the following average required fuel economy levels for individual manufacturers during MYs 2017–2025 (an updated estimate of the average required fuel economy level under the final MY 2016 standard is shown for comparison): 728

T ABLE IV.E.4–4—E STIMATED A VERAGE F UEL E CONOMY R EQUIRED U NDER F INAL MY 2016 AND P ROPOSED MY S 2017–2025 CAFE S TANDARDS F OR L IGHT T RUCKS

Manufacture

r 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

Aston Martin - - - - - - - - - -
BMW 30.2 30.6 31.4 32.1 32.9 35.1 36.7 38.4 40.2 42.1 Daimler 29.1 29.1 29.6 30.2 30.9 32.9 34.5 36.1 37.8 39.5

Chrysler/Fiat

729 29.0 29.6 30.2 30.8 31.6 33.7 35.3 37.0 38.8 40.7 Ford 28.0 28.4 29.0 29.4 29.9 31.8 33.3 35.0 36.8 38.6 Geely (Volvo) 30.5 31.1 32.1 32.7 33.5 35.8 37.5 39.3 41.2 43.1
General 27.4 28.1 28.7 29.2 29.8 31.9 33.4 35.1 36.8 38.6

728 In the May 2010 final rule establishing MYs 2012-2016 standards for passenger cars and light trucks, NHTSA estimated that the required fuel economy levels for light trucks would average 28.8 mpg under the MY 2016 light truck standard. Based on the agency’s current forecast of the MY 2016 light truck market, NHTSA again estimates that the required fuel economy levels will average 28.8 mpg in MY 2016. However, th e agency’s market forecast reflects less of a future market shift away from light trucks than reflected in the agency’s prior ma rket forecast; as a result, NHTSA currently estim ates that the combined ( i.e. , passenger car and light truck) average required fuel economy in MY 2016 will be 33.8 mpg, 0. 3 mpg lower than the agency’s earlier estimate of 34.1 mpg. The agency has made no changes to MY 2016 standards and project s no changes in fleet-specific average requirements (although within-fleet market shifts could, under an attribute-based standard, produced such changes).

729 For purposes of CAFE compliance, “Chrysler/Fiat” is assumed to include Ferrari and Maserati in addition to the larger-volume Chrysler and Fiat brands.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 654 of 768 Motors Honda 30.4 31.0 31.8 32.4 33.2 35.5 37.1 38.9 40.8 42.7 Hyundai 30.7 31.3 32.1 32.8 33.6 35.9 37.6 39.4 41.3 43.2 Kia 29.5 30.0 30.6 31.2 32.0 34.2 35.8 37.5 39.3 41.1
Lotus - - - - - - - - - - Mazda 31.5 31.9 32.9 33.5 34.3 36.5 38.1 39.8 41.8 43.8 Mitsubishi 31.7 32.6 33.5 34.2 35.1 37.5 39.3 41.1 43.1 45.2 Nissan 29.1 29.6 30.3 30.9 31.6 33.5 35.1 36.9 38.7 40.6
Porsche 29.8 30.3 31.2 31.8 32.6 34.8 36.5 38.2 40.0 41.9 Spyker (Saab) 30.5 31.2 32.1 32.8 33.6 35.9 37.6 39.4 41.3 43.3 Subaru 31.9 33.0 34.0 34.7 35.5 38.0 39.8 41.7 43.6 45.7 Suzuki 31.4 32.2 33.2 33.9 34.7 37.1 38.9 40.7 42.7 44.7 Tata (Jaguar, Rover) 31.3 32.1 33.1 33.8 34.6 37.0 38.8 40.6 42.6 44.6 Tesla - - - - - - - - - - Toyota 29.1 29.7 30.4 31.0 31.6 33.8 35.4 37.1 39.0 40.9
VW 730 29.2 29.5 30.1 30.8 31.5 33.5 35.1 36.7 38.5 40.3 Average 28.8 29.4 30.0 30.6 31.2 33.3 34.9 36.6 38.5 40.3

As discussed above with respect to the proposed passenger cars standards, we note that a manufacturer’s required light truck fuel economy level for a model year under the ultimate final standards will be based on its actual production numbers in that model year.

Additionally, again for reference, the following table presents estimated mpg levels based on 2-cycle CAFE for easier comparison to the MYs 2012-2016 standards.

T ABLE IV.E.4–5—E STIMATED A VERAGE F UEL E CONOMY R EQUIRED U NDER F INAL MY

2016 AND U SING 2-C YCLE CAFE FOR MY S 2017-2025 F OR L IGHT T RUCKS

Manufacturer 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
Aston Martin - - - - - - - - - -
BMW 30.2 30.1 30.7 31.3 32.0 34.1 35.7 37.3 39.0 40.8 Daimler 29.1 28.6 29.0 29.5 30.2 32.1 33.5 35.0 36.6 38.3 Chrysler/Fiat 731 29.0 29.1 29.6 30.0 30.8 32.8 34.3 35.9 37.6 39.4 Ford 28.0 28.0 28.4 28.8 29.2 31.0 32.4 34.0 35.7 37.4 Geely (Volvo) 30.5 30.6 31.3 31.9 32.6 34.8 36.4 38.1 39.9 41.7
General Motors 27.4 27.7 28.1 28.5 29.1 31.1 32.5 34.1 35.7 37.4 Honda 30.4 30.5 31.0 31.6 32.3 34.5 36.1 37.7 39.5 41.3 Hyundai 30.7 30.8 31.4 31.9 32.7 34.9 36.5 38.1 39.9 41.8 Kia 29.5 29.5 29.9 30.4 31.2 33.3 34.8 36.4 38.1 39.8
Lotus - - - - - - - - - -

730 For purposes of CAFE compliance, VW is assumed to include Audi-Bentley, Bugatti, and Lamborghini, along with the larger-volume VW brand.

731 For purposes of CAFE compliance, “Chrysler/Fiat” is assumed to include Ferrari and Maserati in addition to the larger-volume Chrysler and Fiat brands.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 655 of 768 Mazda 31.5 31.3 32.1 32.7 33.4 35.4 37.0 38.6 40.4 42.3 Mitsubishi 31.7 32.0 32.7 33.3 34.1 36.4 38.1 39.8 41.6 43.6 Nissan 29.1 29.2 29.7 30.2 30.8 32.7 34.1 35.8 37.6 39.3 Porsche 29.8 29.8 30.5 31.0 31.8 33.9 35.4 37.1 38.8 40.6 Spyker (Saab) 30.5 30.7 31.4 32.0 32.7 34.9 36.5 38.2 40.0 41.8
Subaru 31.9 32.4 33.1 33.7 34.5 36.8 38.5 40.3 42.2 44.1 Suzuki 31.4 31.7 32.4 33.0 33.8 36.0 37.7 39.4 41.3 43.2 Tata (Jaguar, Rover) 31.3 31.5 32.3 32.9 33.7 35.9 37.6 39.3 41.2 43.1
Tesla - - - - - - - - - - Toyota 29.1 29.2 29.8 30.3 30.8 32.9 34.4 36.0 37.8 39.5
VW 732 29.2 29.0 29.5 30.0 30.7 32.7 34.1 35.7 37.3 39.1 Average 28.8 29.0 29.4 29.9 30.4 32.5 33.9 35.6 37.3 39.0

F. How do the proposed standards fulfill NHTSA’s statutory obligations?

1. What are NHTSA’s statutory obligations?

As discussed above in Section IV.D, NHTSA sets CAFE standards under EPCA, as amended by EISA, and is also subject to the APA and NEPA in developing and promulgating CAFE standards.

NEPA requires the agency to develop and c onsider the findings of an Environmental Impact Statement (EIS) for “major Federal actio ns significantly affecting the quality of the human environment.” NHTSA has determined that this action is such an action and therefore that an EIS is necessary, and has accordingly prepared a Draft EIS to inform its development and consideration of the proposed standards. The agency has evaluated the environmental impacts of a range of regulatory alternatives in our proposal, and integrated the results of that consideration into our balancing of the EPCA/EISA factors, as discussed below.

The APA and relevant case law requires our rulemaking decision to be rational, based on consideration of the relevant factors, and with in the scope of the authority delegated to the agency by EPCA/EISA. The relevant factors are those required by EPCA/EISA and the additional factors approved in case law as ones historically considered by the agency in determining the maximum feasible CAFE standards, such as safety. The statute requires us to set standards at the maximum feasible level for passenger cars and light trucks for each model year, and the agency tentatively concludes that the standards, if adopted as proposed, would satisfy this requirement. NHTSA has careful ly examined the relevant data and other considerations, as discussed below in our explanation of our tentative conclusion that the proposed standards are the maximum feasible levels for those model years based on our evaluation of the information before us for this NPRM.

732 For purposes of CAFE compliance, VW is assumed to include Audi-Bentley, Bugatti, and Lamborghini, along with the larger-volume VW brand.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 656 of 768 As discussed in Section IV.D, EPCA/EISA requires that NHTSA establish separate passenger car and light truck standards at “the maximum feasible average fuel economy level that it decides the manufacturers can achieve in that model year,” based on the agency’s consideration of four statutory factors: techno logical feasibility, economic practicability, the effect of other standards of the Government on fuel economy, and the need of the nation to

conserve energy. 733 NHTSA has developed definitions for these terms over the course of multiple CAFE rulemakings 734 and determines the appropriate weight and balancing of the terms given the circumstances in each CAFE rulemaking. For MYs 2011–2020, EPCA further requires that separate standards for passenger cars and for light trucks be set at levels high enough to ensure that the CAFE of the industry-wide combined fleet of new passenger cars and light trucks reaches at least 35 mpg not later than MY 2020. For model years after 2020, standards need simply be set at the maximum feasible level.

The agency thus balances the relevant factors to determine the maximum feasible level of the CAFE standards for each fleet, in each model year. The next section discusses how the agency balanced the factors for this proposal, and why we believe the proposed standards are the maximum feasible.

2. How did the agency balance the factors for this NPRM?

There are numerous ways that the relevant fact ors can be balanced (and thus weight given to each factor) depending on the agency’s policy priorities and on the information before the agency regarding any given model year, and the agency therefore considered a range of alternatives that represent di fferent regulatory options that we thought were potentially reasonable for purposes of this rulemaking. For this proposal, the regulatory alternatives considered in the agency’s analysis include several alternatives for fuel economy levels that increase annually, on average, at set rates – specifically, 2 %/year, 3 %/year, 4 %/year, 5 %/year, 6 %/year, and 7 %/year. 735 Analysis of these various rates of increase effectively encompasses the entire range of fuel economy improvements that, based on information currently available to

733 As explained in Section IV.D, EPCA also provides that in determining the level at which it should set CAFE standards for a particular model year, NHTSA may not cons ider the ability of manufacturers to take advantage of several statutory provisions that facilitate compliance wi th the CAFE standards and thereby reduce the costs of compliance. Specifically, in determining the maximum feas ible level of fuel economy for passenger cars and light trucks, NHTSA cannot consider the fuel economy benefits of “dedicated” alternative fuel vehicles (like battery electric vehicles or natural gas vehicles), must consider dual-fueled automobiles to be operated only on gasoline or diesel fuel (at least through MY 2020), and may not consider the ability of manufacturers to use, trade, or transfer credits. This provision limits, to some extent, the fu el economy levels that NHTSA can find to be “maximum feasible” – if NHTSA cannot consider the fuel economy of electric vehicles, for example, NHTSA cannot set standards predicated on manufacturers’ usage of electric vehicles to meet the standards.

734 These factors are defined in Section IV.D; for brevity, we do not repeat those definitions here.

735 This is an approach similar to th at used by the agency in the MY 201 2-2016 rulemaking, in which we also considered several alternatives that increased annually, on average, at 3%, 4 %, 5 %, 6 % and 7 %/year. The “percent-per-year” alternatives in this proposal are somewhat different from those considered in the MY 2012-2016 rulemaking, however, in terms of how the annual rate of increase is applied. For this proposal, the stringency curves are themselves advanced directly by the annual increase am ount, without reference to any yearly changes in the fleet mix. In the 2012-2016 rule, the annual increases for the st ringency alternatives reflected the estimated required fuel economy of the fleet which accounted for both the changes in the target curves and changes in the fleet mix.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 657 of 768 the agency, could conceivably fall within the statutory boundary of “maximum feasible” standards. The regulatory alternatives also include two alternatives based on benefit-cost criteria, one in which standards would be set at the point where net benefits would be maximized for each fleet in each year (MNB), and another in which standards would be set at the point at which total costs would be most nearly equal to total benefits for each fleet in each year (TC=TB), 736 as well as the preferred alternative, which is within the range of the other alternatives. These alternatives are discusse d in more detail in Chapter III of the PRIA accompanying this NPRM, which also contains an extensive analysis of the relative impacts of the alternatives in terms of fuel savings, costs (both per-vehicle and aggregate), carbon dioxide emissions avoided, and many other metrics. Because the agency could conceivably select any of the regulatory alternatives above, all of which fall between 2 %/year and 7 %/year, inclusive, the Draft EIS that accompanies this proposal analyzes these lower and upper bounds as well as the preferred alternative. Additionally, the Draf t EIS analyzes a “No Action Alternative,” which assumes that, for MYs 2017 and beyond, NHTSA woul d set standards at the same level as MY 2016. The No Action Alternative provides a ba seline for comparing the environmental impacts of the other alternatives.

NHTSA believes that this approach clearly communicates the level of stringency of each alternative and allows us to id entify alternatives that represent different ways to balance NHTSA’s statutory factors under EPCA/EISA. Each of the listed alternatives represents, in part, a different way in which NHTSA could conceivably balance different policies and considerations in setting the standards that achieve the maximum feasible levels. For example, the 2% Alternative, the least stringent alternative, would represent a balancing in which economic practicability – which include concerns about ava ilability of technology, capital, and consumer preferences for vehicles built to meet the future standards – weighs more heavily in the agency’s consideration, and the need of the nation to conserve energy would weigh less heavily. In contrast, under the 7% Alternative, one of the most stringent, the need of the nation to conserve energy – which includes energy conservation a nd climate change considerations – would weigh more heavily in the agency’s consideration, and technological feasibility and economic practicability would weigh less heavily. Balancing and assessing the feasibility of different alternative can also be influenced by differe nces and uncertainties in the way in which key economic factors ( e.g. , the price of fuel and the social cost of carbon) and technological inputs could be assessed and estimated or valued. While NHTSA believes that our analysis conducted in support of this NPRM uses the best and most transparent technology-related inputs and economic assumption inputs that the agencies could derive for MYs 2017-2025, we recognize that there is uncertainty in these inputs, and the balancing could be different if, for example, the inputs are adjusted in response to new information.

This is the first CAFE rulemaking in which th e agency has looked this far into the future, which makes our traditional approach to balancing more challenging than in past (even recent past) rulemakings. NHTSA does not presently believe, for example, that technological feasibility as the agency defines it is as constraining in this rulemaking as it has been in the past

736 We included the MNB and TC=TB alternatives in part for the reference of commenters familiar with NHTSA’s past several CAFE rulemakings – these alternatives represen t balancings carefully consider ed by the agency in past rulemaking actions as potentially maximum feasible – and because Executive Orders 12866 and 13563 focus attention on an approach that maximizes net benefits.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 658 of 768 in light of the time frame of this rulemaking. “Technological feasibility” refers to whether a particular method of improving fuel economy can be available for commercial application in the model year for which a standard is being established. In nearer-term rulemakings like many of the previous CAFE rulemakings, it has been more difficult for the agency to say that the most advanced technologies would be available for commercial application in the model years for which standards were being established. For th is rulemaking, which is longer term, NHTSA has considered all types of technologies that improve real-world fuel economy, including airconditioner efficiency and other off-cycle t echnology, PHEVs, EVs, and highly-advanced internal combustion engines not yet in production, but all of which the agencies’ expect to be commercially applicable by the rulemaking time frame. On the one hand, we recognize that some technologies that currently have limited commercial use cannot be deployed on every vehicle model in MY 2017, or even necessarily in MY 2025, but require a realistic schedule for widespread commercialization to be feasible. On the other hand, however, the agency expects, based on our analysis, that all of the alternatives could narrowly be considered as technologically feasible, in that they could be achieved based on the existence or projected future existence of technologies that could be incorporated on future vehicles, and enable any of the alternatives to be achieved on a technical basis alone if the leve l of resources that might be required practically to implement the technologies is not considered. If all alternatives are at least theoretically technologically feasible in the MY 2017-2025 timeframe, and the need of the nation is best served by pushing standards as stringent as possible, then the agency might be inclined to select the alternative that results in the very most stringent standards considered.

However, the agency must also consider what is required to practically implement technologies, which is part of economic prac ticability, and to which the most stringent alternatives give little weight. “Economic pract icability” refers to whether a standard is one “within the financial capability of the industry, but not so stringent as to lead to “adverse economic consequences, such as a significant loss of jobs or the unreasonable elimination of consumer choice.” Consumer acceptability is also an element of economic practicability, one which is particularly difficult to gauge during times of uncertain fuel prices. 737 In a rulemaking such as the present one, dete rmining economic practicability re quires consideration of the uncertainty surrounding relatively distant future market conditions and consumer demand for fuel economy in addition to other vehicle attribut es. In an attempt to evaluate the economic practicability of attribute-based standards, NHTSA includes a variety of factors in its analysis, including the annual rate at which manufacturers can increase the percentage of their fleet that employ a particular type of fuel-saving tech nology, the specific fleet mixes of different manufacturers, and assumptions about the cost of the standards to consumers and consumers’ valuation of fuel economy, among other things. Ensuring that a reasonable amount of lead time exists to make capital investments and to devote the resources and time to design and prepare for commercial production of a more fuel efficient fleet is also relevant to the agency’s consideration of economic practicability. Yet there are so me aspects of economic practicability that the agency’s analysis is not able to capture at this time – the computer model that we use to analyze alternative standards does not account for all aspects of uncertainty, in part because the agency

737 See

, e.g., Center for Auto Safety v. NHTSA (CAS) , 793 F.2d 1322 (D.C. Cir. 1986) (Administrator’s consideration of market demand as component of economic practicability found to be reasonable); Public Citizen v. NHTSA , 848 F.2d 256 (Congress established broad guidelines in the fuel economy statute; agency’s decision to set lower standard was a reasonable accommodation of conflicting policies).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 659 of 768 cannot know what we cannot know. The agency must thus account for uncertainty in the context of economic practicability as best as we can based on the entire record before us.

Both technological feasibility and economic practicability enter into the agency’s determination of the maximum feasible levels of stringency, and economic practicability concerns may cause the agency to decide that standards that might be technologically feasible are, in fact, beyond maximum feasible. Standa rds that require aggressive application of and widespread deployment of advanced technologies could raise serious issues with the adequacy of time to coordinate such significant changes with manufacturers’ redesign cycles, as well as with the availability of engineering resources to deve lop and integrate the technologies into products, and the pace at which capital costs can be incurred to acquire and integrate the manufacturing and production equipment necessary to increase the production volume of the technologies. Moreover, the agency must consider whether consumers would be likely to accept a specific technological change under consideration, and how the cost to the consumer of making that change might affect their acceptance of it. The agency maintains, as it has in prior CAFE rulemakings, that there is an important distin ction between considerations of technological feasibility and economic practicability. As explained above, a given level of performance may be technologically feasible ( i.e. , setting aside economic constraints) for a given vehicle model. However, it would not be economically practicable to require a level of fleet average performance that assumes every vehicle will in th e first year of the standards perform at the highest technologically feasible level, because manufacturers do not have unlimited access to the financial resources or may not practically be able to hire enough engineers, build enough facilities, and install enough tooling.

NHTSA therefore believes, based on the information currently before us, that economic practicability concerns render certain standards th at might otherwise be technologically feasible to be beyond maximum feasible within the meaning of the statute for the 2017-2025 standards. Our analysis indicated that technologies seem to exist to meet the stringency levels required by future standards under [all, or many? Still evalua ting] of the regulatory alternatives; but it also indicated that manufacturers would not be able to apply those technologies quickly enough, given their redesign cycles, and the level of th e resources that would be required to implement those technologies widely across their products, to meet all applicable standards in every model year under some of the alternatives.

Another consideration for economic practicabilit y is incremental per-vehicle increases in technology cost. In looking at the incremental technology cost results from our modeling analysis, the agency saw that in progressing from alternatives with lower stringencies to alternatives with higher stringencies, technolo gy cost increases (perhaps predictably) at a progressively higher rate, until the model projects that manufacturers are unable to comply with the increasing standards and enter (or deepen) non-compliance. Table IV.F.1 and Table IV.F.2 show estimated cumulative lifetime fuel savings and estimated average vehicle cost increase for passenger cars and light trucks. The results show that there is a significant increase in technology cost between the 4% alternatives and the 5% alternatives.

T ABLE IV.F.1. E STIMATED P ASSENGER C AR C UMULATIVE L IFETIME F UEL S AVINGS AND A VERAGE V EHICLE C OST I NCREASEDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 660 of 768 Cumulative

Lifetime

Fuel Savings
2017-2021

(billion gallons) Average Vehicle

Cost Increase in
2021 (2009 $) Cumulative Lifetime

Fuel Savings
2017-2025

(billion gallons) Average Vehicle

Cost Increase in
2025 (2009 $)
2% 20 $446 54 $690 3% 29 $764 79 $1,343 MNB 51 $1,067 103 $1,391
Preferred Alternative 37 $1,171 98 $2,015 4% 39 $1,214 103 $2,190 TC=TB 58 $1,615 129 $2,559 5% 48 $1,601 123 $2,924 6% 54 $1,804 133 $3,152 7% 57 $1,877 137 $3,279

T ABLE IV.F.2. E STIMATED L IGHT T RUCK C UMULATIVE L IFETIME F UEL S AVINGS AND A VERAGE V EHICLE C OST I NCREASE

Cumulative

Lifetime

Fuel Savings
2017-2021

(billion gallons) Average Vehicle

Cost Increase in
2021 (2009 $) Cumulative Lifetime

Fuel Savings
2017-2025

(billion gallons) Average Vehicle

Cost Increase in
2025 (2009 $)
2% 20 $523 49 $720 3% 29 $961 70 $1,309
Preferred Alternative 21 $910 63 $1,544 4% 37 $1,570 88 $2,384 MNB 56 $2,222 114 $3,327 TC=TB 57 $2,238 115 $3,563 5% 46 $2,154 106 $3,445 6% 51 $2,329 112 $3,555 7% 53 $2,442 115 $3,677

Thus, if technological feasibility and the n eed of the nation are not particularly limiting in a given rulemaking, then maximum feasible standards would be represented by the mpg levelsDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 661 of 768 that we could require of the industry to improve fuel economy before we reach a tipping point that presents risk of significantly adverse economi c consequences. Standards that are lower thanthat point would likely not be maximum feasible, because such standards would leave fuelsaving technologies on the table unnecessarily; st andards that are higher than that point would likely be beyond what the agency would consider economically practicable, and therefore beyond what we would consider maximum feasible, even if they might be technologically feasible or better meet the need of the nation to conserve energy. The agency does not believe that standards are balanced if they weight one or two factors so heavily as to ignore another.

We explained above that part of the way that we try to evaluate economic practicability is through a variety of model inputs, such as phase-in caps (the annual rate at which manufacturers can increase the percentage of their fleet that employ a particular type of fuel-saving technology) and redesign schedules to account for needed lead time. These inputs limit how much technology can be applied to a manufacturer’s fleet in the agency’s analysis attempting to simulate a way for the manufacturer to comply with standards set under different regulatory alternatives. If the limits (and technology co st-effectiveness) prevent enough manufacturers from meeting the required levels of stringency, the agency may decide that the standards under consideration may not be economically practicable. The difference between the required fuel economy level that applies to a manufacturer’s fleet and the level of fuel economy that the agency projects the manufacturer would achieve in that year, based on our analysis, is called a “compliance shortfall.” 738

We underscore again that the modeling anal ysis does not dictate the “answer,” it is merely one source of information among others that aids the agency’s balancing of the standards. These considerations, shortfalls and increases in incremental technology costs, do not entirely define economic practicability, but we believe they are symptomatic of it. In looking at the projected compliance shortfall results from our modeling analysis, the agency preliminarily concluded, based on the information before us at the time, that for both passenger car and for light trucks, the MNB and TC=TB alternatives, and the 5%, 6% and 7% alternatives did not appear to be economically practicable, and were thus likely beyond maximum feasible levels for MYs 2017-2025. In other words, despite the theo retical technological feasibility of achieving these levels, various manufacturers would likely l ack the financial and engineering resources and sufficient lead time to do so. The analysis showed for the passenger car 5% alternative, there were significant compliance shortfalls for Chrysler in MY 2025, Ford in MYs 2021 and 2023- 2025, GM in MYs 2022 and 2024-2025, Mazda in MYs 2021 and 2024-2025, and Nissan in MY 2025. For light trucks, the analysis showed the 5% alternative had significant compliance shortfalls for Chrysler in MYs 2022-2025, Ford in MY 2025, GM in MYs 2023-2025, Kia in MY 2025, Mazda in MYs 2022 and 2025, and Nissan in MYs 2023-2025. However, the 4%, 3% and 2% alternatives did not appear, based on shortfalls, to be beyond the level of economic practicability, and thus appeared potentially to be within the range of alternatives that might yet be maximum feasible.

738 The agency’s modeling estimates how the application of technologies could increase vehicle costs, reduce fuel consumption, and reduce CO 2 emissions, and affect other factors. As CAFE standards are performance-based, NHTSA does not mandate that specific technologies be used for compliance. CAFE modeling, therefore projects one way that manufacturers could comply. Manufacturers may choose a different mix of technologies based on their unique circumstances and products.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 662 of 768 T ABLE IV.F.3. E STIMATED P ASSENGER C AR C OMPLIANCE S HORTFALL FOR THE 5%/Y EAR A LTERNATIVE (MPG)

Estimated Compliance Shortfall for Passenger Car (mpg)

2017 2018 2019 2020 2021 2022 2023 2024 2025 Chrysler - - - - - - - 0.6 2.8
Ford - - - 0.3 2.4 0.6 2.2 3.9 6.6
General Motors - - - - - 2.3 0.3 1.7 3.7
Honda - - - - - - - - 0.3 Hyundai - - - - - - - - -

Kia - - - - - - - - -
Mazda - - - - 1.9 - - 1.6 1.9
Nissan - - - - - - - - 1.4 Toyota - - - - - - - - -

T ABLE IV.F.4. E STIMATED L IGHT T RUCK C OMPLIANCE S HORTFALL FOR THE 5%/Y EAR A LTERNATIVE (MPG)

Estimated Compliance Shortfall for Light Truck (mpg)

2017 2018 2019 2020 2021 2022 2023 2024 2025 Chrysler - - - - - 1.7 1.0 3.2 1.0
Ford - - - - - - - 0.6 2.3
General Motors - - - - - 0.2 1.8 2.6 2.7

Honda - - - - - - - - 0.2 Hyundai - - - - - - 0.6 - -
Kia - - - - - - - - 2.1
Mazda - - - - - 1.0 - - 2.1
Nissan - - - - - - 1.1 2.1 4.6 Toyota - - - - - - - - -

The preliminary analysis referred to above, in which the agency tentatively concluded that the 5%, 6%, 7%, MNB, and TC=TB alternativ es were likely beyond the level of economic practicability based on the information available to the agency at the time, was conducted following the first SNOI and prior to the second SNOI – thus, between the end of 2010 and July 2011. The agencies stated in the first SNOI th at we had not conducted sufficient analysis at the time to narrow the range of potential stringenci es that had been discussed in the initial NOI and in the Interim Joint TAR, and that we would be conducting more analyses and continuing extensive dialogue with stakeholders in the comi ng months to refine our proposal. Based on our initial consideration of how the factors might be bala nced to determine the maximum feasible standards to propose for MYs 2017-2025 ( i.e. , where technological feasibility did not appear toDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 663 of 768 be particularly limiting and the need of the na tion would counsel for choosing more stringent alternatives, but economic practicability posed significant limitations), NHTSA’s preliminary analysis indicated that the alternatives including up to 4% per year for cars and 4% per year for trucks should reasonably remain under consideration.

With that preliminary estimate of 4%/year for cars and trucks as the upper end of the range of alternatives that should reasonably remain under consideration for MYs 2017-2025, the agencies began meeting again intensely with stakeholders, including many individual manufacturers, between June 21, 2011 and July 27, 2011 to determine whether additional information would aid NHTSA in further consideration. Beginning in the June 21, 2011 meeting, NHTSA and EPA presented the 4% alternative target curves as a potential concept along with preliminary program fl exibilities and provisions, in or der to get feedback from the manufacturer stakeholders. Manufacturer stakeh olders provided comments, much of which was confidential business information, which included projections of how they might comply with concept standards, the challenges that they expected, and their recommendations on program stringency and provisions. 739

Regarding passenger cars, several manufacturers shared projections that they would be capable of meeting stringency levels simila r to NHTSA’s preliminary CAFE modeling projections for the 4% alternative in MY 2020 or in 2021, with some of those arguing that they faced challenges in the earlier years of that period with meeting a constant 4% rate throughout the entire period. Some manufacturers shared projections that they could comply with stringencies that ramped up, increasing more slowly in MY 2017 and then progressively increasing through MY 2021. Most manufactur ers provided limited projections beyond MY 2021, although some stated that they could meet the agency’s concept stringency targets in MY 2025. Manufacturers generally suggested that the most significant challenges to meeting a constant 4% (or faster) year-over-year increase in the passenger car standards related to their ability to implement the new technologies quickly enough to achieve the required levels, given their need to implement fuel economy improvements in both the passenger car and light truck fleets concurrently; challenges related to the cadence of redesign and refresh schedules; the pace at which new technology can be implemented considering economic factors such as availability of engineering resources to develop and integrat e the technologies into products; and the pace at which capital costs can be incurred to acquire and integrate the manufacturing and production equipment necessary to increase the production volume of the technologies. Manufacturers often expressed concern that the 4% levels could require greater numbers of advanced technology vehicles than they thought they would be able to sell in that time frame, given their belief that the cost of some technologies was much higher than the agencies had estimated and their observations of current consumer acceptance of and willingness to pay for advanced technology vehicles that are available now in the marketplace. A number of manufacturers argued that they did not believe that they coul d create a sustainable business ca se under passenger car standards that increased at the rate required by the 4% alternative.

Regarding light trucks, most manufacturers expr essed significantly greater concerns over the 4% alternative for light trucks than for passenger cars. Many manufacturers argued that

739 Feedback from these stakeholder meetings is summarized in section IV.B and documents that are referenced in that section.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 664 of 768 increases in light truck standard stringency shou ld be slower than increases in passenger car standard stringency, based on, among other things, the greater payload, cargo capacity and towing utility requirements of light trucks, and what they perceived to be lower consumer acceptance of certain (albeit not all) advanced technologies on light trucks. Many manufacturers also commented that redesign cycles are longer on trucks than they are on passenger cars, which reduces the frequency at which significant changes can be made cost-effectively to comply with increasing standards, and that the significan t increases in stringency in the MY 2012-2016

program 740 in combination with redesign schedules wo uld not make it possible to comply with the 4% alternative in the earliest years of the MY 2017-2025 program, such that only significantly lower stringencies in those years would be feasible in their estimation. As for cars, most manufacturers provided limited projections beyond MY 2021. Manufacturers generally stated that the most significant challenges to meeting a constant 4% (or faster) year-over-year increase in the light truck standards were similar to what they had described for passenger cars as enumerated in the paragraph above, but were compounded by concerns that applying technologies to meet the 4% alternative standa rds would result in trucks that were more expensive and provided less utility to consumers. As was the case for cars, manufacturers argued that their technology cost estimates were higher than the agencies’ and consumers are less willing to accept/pay for some advanced technologies in trucks, but manufacturers argued that these concerns were more significant for trucks than for cars, and that they were not optimistic that they could recoup the costs through higher prices for vehicles with the technologies that would be needed to comply with the 4% alternative. Given their concerns about having to reduce utility and raise truck prices, and about th eir ability to apply tec hnologies quickly enough given the longer redesign periods for trucks, a number of manufacturers argued that they did not believe that they could create a sustainable business case under light truck standards that increased at the rate required by the 4% alternative.

Other stakeholders, such as environmental an d consumer groups, consistently stated that stringent standards are technically achievable and crit ical to important national interests, such as improving energy independence, reducing climate change, and enabling the domestic automobile industry to remain competitive in the global market. Labor interest s stressed the need to carefully consider economic impacts and the op portunity to create and support new jobs, and consumer advocates emphasized the economic and practical benefits to consumers of improved fuel economy and the need to preserve consumer choice. In addition, a number of stakeholders stated that the standards under development shoul d not have an adverse impact on safety.

NHTSA, in collaboration with EPA and in coordination with CARB, carefully considered the inputs received from all stakeholders, co nducted additional independent analyses, and deliberated over the feedback received on the agencies’ analyses. NHTSA considered individual manufacturers’ redesign cycles and, where availabl e, the level of technologies planned for their future products that improve fuel economy, as well as some estimation of the resources that would likely be needed to support those plans and the potential future standards. The agency also considered whether we agreed that there could conceivably be compromises to vehicle utility depending on the technologies chosen to meet the potential new standards, and whether a

740 Some manufacturers indicated that their light truck fl eet fuel economy would be below what they anticipated their required fuel economy level would be in MY 2016, and th at they currently expect that they will need to employ available flexibilities to comply with that standard.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 665 of 768 change in the cadence of the rate at which standards increase could provide additional opportunity for industry to develop and implement technologies that would not adversely affect utility. NHTSA considered feedback on cons umer acceptance of some advanced technologies and consumers’ willingness to pay for improved fuel economy. In addition, the agency carefully considered whether manufacturer assertions about potential uncertainties in the agency’s technical, economic, and consumer acceptance assumptions and estimates were potentially valid, and if so, what the potential effects of these uncertainties might be on economic practicability.

Regarding passenger cars, after considering this feedback from stakeholders, the agency considered further how it thought the factors should be balanced to determine the maximum feasible passenger car standards for MYs 2017-2025. Based on that reconsideration of the information before the agency and how it informs our balancing of the factors, NHTSA tentatively concludes that the points raised may indicate that the agency’s preliminary analysis supporting consideration of standards that increased up to 4%/year may not have captured fully the level of uncertainty that surrounds economic practicability in these future model years. Nevertheless, while we believe there may be some uncertainty, we do not agree that it is nearly as significant as a number of manufacturers maintained, especially for passenger cars. The most persuasive information received from stakeholde rs for passenger cars concerned practicability issues in the first phase of the MY 2017-2025 standards. We therefore tentatively conclude that the maximum feasible stringency levels for passenger cars are only slightly different from the 4%/year levels suggested as the high end preliminarily considered by the agency; increasing on average 3.7%/year in MYs 2017-2021, and on average 4.5%/year in MYs 2022-2025. For the overall MY 2017-2025 period, the maximum feasible stringency curves increase on average at 4.1%/year, and our analysis indicates that the costs and benefits attributable to the 4% alternative and the preferred alternative for passenger cars are very similar: the preferred alternative is 4.4 percent less expensive for manufacturers than the 4% alternative (estimated total costs are $115 billion for the preferred alternative and $122 b illion for the 4% alternative), and achieves only $14 billion less in total benefits than the 4% alte rnative (estimated total benefits are $302 billion for the preferred alternative and $316 billion fo r the 4% alternative), a very small difference given that benefits are spread across the entire lifet imes of all vehicles subject to the standards. The analysis also shows that the lifetime cumula tive fuel savings is only 5 percent higher for the 4% alternative than the preferred alternative (the estimated fuel savings is 98 billion gallons for the preferred alternative, and 103 billion gallons for the 4% alternative). At the same time, the increase in average vehicle cost in MY 2025 is 8 percent higher for the 4% alternative (the estimated cost increase for the average vehicle is $2,015 for the preferred alternative, and $2,190 for the 4% alternative). The rates of increase in stringency for each model year are summarized in Table IV.F.3 and Table IV.F.4. NHTSA emphasizes that under 49 U.S.C. 32902(b), the standards must be maximum feasible in each model year without reference to other model years, but we believe that the small amount of progressiveness in the proposed standards for MYs 2017-2021, which has very little effect on total bene fits attributable to the proposed passenger car standards, will help to enable the continuation of, or increases in, research and development into the more advanced technologies that will enable greater stringency increases in MYs 2022- 2025, and help to capture the considerable fuel savings and environmental benefits similar to the 4% alternative beginning in MY 2025. We are concerned that requiring manufacturers to invest that capital to meet higher standards in MYs 2017-2021, rather than allowing them to increase fuel economy in those years slightly more slowly, would reduce the levels that would be feasibleDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 666 of 768 in the second phase of the program by diverting research and development resources to those earlier model years. Thus, after considerable deliberation with EPA and consultation with CARB, NHTSA selected the preferred alternative as the maximum feasible alternative for MYs 2017-2025 passenger cars based on consideration of inputs from manufacturers and the agency’s independent analysis, which reaches the stringency levels of the 4% alternative in MY 2025, but has a slightly slower ramp up rate in the earlier years.

T ABLE IV.F.5. A NNUAL R ATE O F I NCREASE IN THE S TRINGENCY OF THE P REFERRED A LTERNATIVE FOR E ACH M ODEL Y EAR

Model Year Passenger Car Light Truck
2017 3.6% 0.6%
2018 3.6% 2.1%
2019 3.6% 1.7%
2020 3.7% 2.0%
2021 4.2% 6.4%
2022 4.5% 4.5%
2023 4.4% 4.7%
2024 4.5% 4.7%

2025 4.5% 4.6%

T ABLE IV.F.6. A NNUAL R ATE O F I NCREASE IN THE S TRINGENCY OF THE P REFERRED A LTERNATIVE O VER V ARIOUS P ERIODS

Model Years Passenger Car Light Truck

2017-2021 3.7% 2.6%
2022-2025 4.5% 4.6%

2017-2025 4.1% 3.5%

Regarding light trucks, while NHTSA does not agree with the manufacturer’s overall cost assessments and believe that our technology cost and effectiveness assumptions should allow the most capable manufacturers to preserve all necessary vehicle utility, the agencies do believe there is merit to some of the concerns raised in stakeholder feedback. Specifically, concerns about longer redesign schedules for trucks, compounded by the need to invest simultaneously in raising passenger car fuel economy, may not have been fully captured in our preliminary analysis. This could lead manufacturers to implem ent technologies that do not maintain vehicle utility, based on the cadence of the standards under the 4% alternative. A number of manufacturers repeatedly stated, in providing feedback, that the MYs 2012-2016 standards for trucks, while feasible, required significant investment to reach the required levels, and that given the redesign schedule for trucks, that level of investment throughout the entire MYs 2012-2025 time period was not sustainable. Based on the confidential business information that manufacturers provided to us, we believe that this point may be valid. If the agency pushesDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 667 of 768 CAFE increases that require considerable sustaine d investment at a faster rate than industry redesign cycles, adverse economic consequences could ensue. The best information that the agency has at this time, therefore, indicates that requiring light truck fuel economy improvements at the 4% annual rate could create potentially severe economic consequences.

Thus, evaluating the inputs from stakeholders and the agency’s independent analysis, the agency also considered further how it thought the factors should be balanced to determine the maximum feasible light truck standards for MYs 2017-2025. Based on that consideration of the information before the agency and how it informs our balancing of the factors, NHTSA tentatively concludes that 4%/year CAFE stringency increases for light trucks in MYs 2017-2021 are likely beyond maximum feasible, and in fact, in the earliest model years of the MY 2017- 2021 period, that the 3%/year and 2%/year alternatives for trucks are also likely beyond maximum feasible. NHTSA therefore tentatively co ncludes that the preferred alternative, which would in MYs 2017-2021 increase on average 2.6%/year, and in MYs 2022-2025 would increase on average 4.6%/year, is the maximum feasible level that the industry can reach in those model years. For the overall MY 2017-2025 period, the maximum feasible stringency curves would increase on average 3.5%/year. The rates of increase in stringency for each model year are summarized in Table IV.F.3 and Table IV.F.4. Our analysis indicates that the preferred alternative has 48 percent lower cost than the 4% alternative (estimated total costs are $43 billion for the preferred alternative and $82 billion for the 4% alternative) , and the total benefits of the preferred alternative are 28 per cent lower ($76 billion lower) than the 4% alternative (estimated total benefits are $193 billio n for the preferred alternative and $269 billion for the 4% alternative), spread across the entire lifetimes of all vehicles subject to the standards. The analysis also shows that the lifetime cumulative fuel savings is 28 percent higher for the 4% alternative than the preferred alternative (the es timated fuel savings is 63 billion gallons for the preferred alternative, and 88 billion gallons for the 4% alternative). At the same time, the increase in average vehicle cost in MY 2025 is 35 percent higher for the 4% alternative (the estimated cost increase for the average vehicle is $1,544 for the preferred alternative, and $2,384 for the 4% alternative). While these differences are larger than for passenger cars, NHTSA believes that standards set at these levels for th ese model years will help address concerns raised by manufacturer stakeholders and reduce the risk for adverse economic consequences, while at the same time ensuring most of the substan tial improvements in fuel efficiency initially envisioned over the entire period and supported by other stakeholders. NHTSA believes that these stringency levels, along with the provisions for incentives for advanced technologies to encourage their development and implementation, and the agencies’ expectation that some of the uncertainties surrounding consumer acceptance of new technologies in light trucks should have resolved themselves by that time frame based on consumers’ experience with the advanced technologies, will enable these increases in stringency over the entire MY 2017-2025 period. Although, as stated above, the light truck standards must be maximum feasible in each model year without reference to other model years, we be lieve that standards set at the stated levels for MYs 2017-2021 and the incentives fo r advanced technol ogies for pickup trucks will create the best opportunity to ensure that the MY 2022-2025 standards are economically practicable, and avoid adverse consequences. The first phase of light truck standards, in that respect, acts as a kind of bridge to the second phase, in which industry should be able to realize considerable additional improvements in fuel economy.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 668 of 768 The proposed standards also account for the effect of EPA’s standards, in light of the agencies’ close coordination and the fact that both sets of standards were developed together to harmonize as part of the National Program. Given the close relationship between fuel economy and CO 2 emissions, and the efforts NHTSA and EPA have made to conduct joint analysis and jointly deliberate on information and tentative conclusions, 741 the agencies have sought to harmonize and align their proposed standards to the greatest extent possible, consistent with their respective statutory authorities. In comparing th e proposed standards, the agencies’ stringency curves are equivalent, except for the fact that the stringency of EPA’s proposed passenger car standards reflect the ability to improve GHG emissions through reductions in A/C system refrigerant leakage and the use of lower GWP refrigerants (direct A/C improvements), 742 and that EPA provides incentives for PHEV, EV and FCV vehicles, which NHTSA does not provide because statutory incentives have already been defined for these technologies. The stringency of NHTSA’s proposed standards for passenger cars for MYs 2017-2025 align with the stringency of EPA’s equivalent standards when these differences are considered. 743 NHTSA is proposing the preferred alternative based on the tentative dete rmination of maximum feasibility as described earlier in the section, but, based on efforts NHTSA and EPA have made to conduct joint analysis and jointly deliberate on inform ation and tentative conclusions, NHTSA has also aligned the proposed CAFE standards with EPA’s proposed standards.

Thus, consistent with President Obama’s announcement on July 29, 2011, and with the August 9, 2011 SNOI, NHTSA has tentatively concluded that the standards represented by the preferred alternative are the maximum feasible st andards for passenger cars and light trucks in MYs 2017-2025. We recognize that higher standards would help the need of the nation to conserve more energy and might potentially be technologically feasible (in the narrowest sense) during those model years, but based on our analysis and the evidence presented by the industry, we tentatively conclude that higher standards would not represent the proper balancing for MYs 2017-2025 cars and trucks. We tentatively conclude that the correct balancing recognizes economic practicability concerns and the inevitable uncertainty in setting st andards farther in the future than in past rulemakings, and sets standa rds at the levels that the agency is proposing in this NPRM. 744 In the same vein, lower standards might be less burdensome on the industry, but considering the environmental impacts of the different regulatory alternatives as required under

741 NHTSA and EPA conducted joint analysis and jointly deliberated on information and tentative conclusions related to technology cost, effectiveness, manufacturers’ capability to implement technologies, the cadence at which manufacturers might support the implementation of tech nologies, economic factors, and the assessment of comments from manufacturers.

742 As these A/C system improvements do not influence fuel economy, the stringency of NHTSA’s preferred alternatives do not reflect the avai lability of these technologies.

743 We note, however, that the alignment is based on the a ssumption that manufacturers im plement the same level of direct A/C system improvements as EPA currently forecasts for those model years, and on the assumption of PHEV, EV, and FCV penetration at specific levels. If a manufactur er implements a higher level of direct A/C improvement technology and/or a higher penetration of PHEVs, EVs and FCVs, then NHTSA’s proposed standards would effectively be more stringent than EPA’s. Conversely, if a manufacturer implements a lower level of direct A/C improvement technology and/or a lower penetration of PHEVs, EVs and FCVs, then EPA’s proposed standards would effectively be more stringent than NHTSA’s.

744 We underscore that the agency’s tentative decision re garding what standards would be maximum feasible for MYs 2017-2025 is made with reference to the rulemaking time frame and circumstances of this proposal. Each CAFE rulemaking (indeed, each stage of any given CAFE rulemaking) presents the agency with new information that may affect how we balance the relevant actors.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 669 of 768 NEPA and the need of the nation to conserve energy, we do not believe they would have represented the appropriate balancing of the relevant factors, because they would have left technology, fuel savings, and emissions re ductions on the table unnecessarily, and not contributed as much as possible to reducing our nation’s energy security and climate change concerns. Standards set at the proposed levels for MYs 2017-2021 will help to enable further research and development into the more advanced fuel economy-improving technologies to provide a bridge to more stringent standards in MYs 2022-2025, and enable significant fuel savings and environmental benefits throughout the program, and particularly substantial benefits in the later years of the program and beyond. In full consideration of all of the information currently before the agency, we have weighed the statutory factors carefully and selected proposed passenger car and light truck standards that we believe are the maximum feasible for
MYs 2017-2025.

G. Impacts of the Proposed CAFE Standards

1. How will these standards improve fuel economy and reduce GHG emissions for MY 2017–2025 vehicles?

As discussed above, the CAFE level required under an attribute-based standard depends on the mix of vehicles produced for sale in the U.S. Based on the market forecast that NHTSA and EPA have used to develop and analyze the proposed CAFE and CO2 emissions standards, NHTSA estimates that the proposed new CAFE standards would lead average required fuel consumption (fuel consumption is the inverse of fuel economy) levels to increase by an average of 4.0 percent annually through MY 2025, reaching a combined average fuel economy requirement of 49.6 mpg in that model year:

T ABLE IV.G.1-1. E STIMATED R EQUIRED A VERAGE F UEL E CONOMY ( MPG ) UNDER THE P ROPOSED S TANDARDS

– MY S 2017-2021

Model Year 2017 2018 2019 2020 2021 Passenger cars 40.0 41.4 43.0 44.7 46.6 Light trucks 29.4 30.0 30.6 31.2 33.3 Combined 35.3 36.4 37.5 38.8 40.9

T ABLE IV.G.1-2. E STIMATED R EQUIRED A VERAGE F UEL E CONOMY ( MPG ) UNDER THE P ROPOSED S TANDARDS

– MY S 2022-2025

Model Year 2022 2023 2024 2025 Passenger cars 48.8 51.0 53.5 56.0 Light trucks 34.9 36.6 38.5 40.3
Combined 42.9 45.0 47.3 49.6

If manufacturers apply technology only as far as necessary to comply with CAFE standards, NHTSA estimates that, setting aside f actors the agency cannot consider for purposesDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 670 of 768 of determining maximum feasible CAFE standards, 745 average achieved fuel economy levels would correspondingly increase through MY 2025, but that manufacturers would, on average, under-comply 746 in some model years and over-comply 747 in others, reaching a combined average fuel economy of 47.4 mpg (taking into account estimated adjustments reflecting improved air conditioner efficiency) in MY 2025:

T ABLE IV.G.1-3. E STIMATED A CHIEVED A VERAGE F UEL E CONOMY ( MPG ) UNDER THE P ROPOSED S TANDARDS

– MY S 2017-2021

Model Year 2017 2018 2019 2020 2021 Passenger cars 39.5 41.7 43.5 45.3 47.1 Light trucks 29.6 30.7 32.5 33.7 35.6 Combined 35.2 36.9 38.8 40.4 42.3

T ABLE IV.G.1-4. E STIMATED A CHIEVED A VERAGE F UEL E CONOMY ( MPG ) UNDER THE P ROPOSED S TANDARDS

– MY S 2022-2025

Model Year 2022 2023 2024 2025 Passenger cars 48.2 49.4 51.3 52.6 Light trucks 36.5 37.5 38.5 39.5 Combined 43.4 44.6 46.1 47.4

Setting aside the potential to produce a dditional EVs (or, prior to MY 2020, PHEVs) or take advantage of EPCA’s provisi ons regarding CAFE credits, NHTSA estimates that today’s proposed standards could increase achieved fuel economy levels by average amounts of up to 0.5 mpg during the few model years leading into MY 2017, as manufacturers apply technology during redesigns leading into model years covered by today’s new standards. 748 As

745 49 U.S.C. 32902(h) states that NHTSA may not consider the fuel economy of dedicated alternative fuel vehicles, the alternative-fuel portion of dual-fueled automobile fuel economy, or th e ability of manufacturers to earn and use credits for over-compliance, in determining the ma ximum feasible stringency of CAFE standards.

746 “Under-compliance” with CAFE standard s can be mitigated either through use of FFV credits, use of existing or “banked” credits, or through fine payment. Although, as mentioned above, NHTSA cannot consider availability of statutorily-provided credits in setting standards, NHTSA is not prohibited from considering fine payment. Therefore, the estimated achieved CAFE levels presented here include the assumption that Aston Martin, BMW, Daimler ( i.e., Mercedes), Geely ( i.e. , Volvo), Lotus, Porsche, Spyker ( i.e. , Saab), and, Tata ( i.e., Jaguar and Rover), and Volkswagen will only apply technology up to the point that it would be less expensive to pay civil penalties.

747 In NHTSA’s analysis, “over-complianc e” occurs through multi-year planning: manufacturers apply some “extra” technology in early model years ( e.g., MY 2014) in order to carry that tech nology forward and thereby facilitate compliance in later model years ( e.g., MY 2016).

748 This outcome is a direct result of revisions, made to DOT’s CAFE model in preparation for the MY 2012-2016 rule, to simulate “multiyear planning” effects—that is , the potential that manufacturers will apply “extra” technology in one model year if doing so will be sufficien tly advantageous with respect to the ability to comply with CAFE standards in later model years. For example, fo r today’s rulemaking analysis, NHTSA has estimated that Ford will redesign the F-150 pickup truck in MY 2015, and again in MY 2021. As explained in Chapter V of the PRIA, NHTSA’s expects that many technol ogies would be applied as part of a vehicle redesign. Therefore, in NHTSA’s analysis, if Ford does not anticipate ensuing standards when redesigning the MY 2015 F-150, Ford may find it more difficult to comply with light truck standa rd during MY 2016-2020. Through simulation of multiyearDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 671 of 768 shown below, these “early” fuel economy increases yield corresponding reductions in fuel consumption and greenhouse gas emissions, and incur corresponding increases in technology outlays.

Within the context EPCA requires NHTSA to apply for purposes of determining maximum feasible stringency of CAFE standards ( i.e. , setting aside EVs, pre-MY 2020 PHEVs, and all statutory CAFE credit provisions), NHTSA estimates that these fuel economy increases would lead to fuel savings totaling 161 billio n gallons during the useful lives of vehicles manufactured in MYs 2017–2025 and the few MYs preceding MY 2017:

T ABLE IV.G.1-5. E STIMATED F UEL S AVED ( BILLION GALLONS ) UNDER THE P ROPOSED S TANDARDS

Model

year Pre2017 2017 2018 2019 2020 2021 2022 2023 2024 2025 Total

PC 3 2 5 7 9 11 12 14 16 18 98
LT 1 1 2 4 6 8 9 10 11 12 63 Combined 4 3 7 11 15 19 21 24 27 30 161

The agency also estimates that these new CAFE standards would lead to corresponding reductions of CO 2 emissions totaling 1,989 million metric tons (mmt) during the useful lives of vehicles sold in MYs 2017–2025 and the few MYs preceding MY 2017:

T ABLE IV.G.1-6. C ARBON D IOXIDE E MISSIONS A VOIDED ( MMT ) UNDER THE P ROPOSED S TANDARDS

Model

year Pre2017 2017 2018 2019 2020 2021 2022 2023 2024 2025 Total

PC 37 23 57 83 111 135 154 179 208 243 1,230
LT 6 7 22 53 72 96 107 119 128 149 759 Combined 44 29 79 137 183 231 261 297 337 392 1,989

2. How will these standards improve fleet-wide fuel economy and reduce GHG emissions beyond MY 2025?

Under the assumption that CAFE standards at least as stringent as those being proposed today for MY 2025 would be established for subsequent model years, the effects of the proposed standards on fuel consumption and GHG emissions will continue to increase for many years. This will occur because over time, a growing frac tion of the U.S. light-duty vehicle fleet will be comprised of cars and light trucks that meet at least the MY 2025 standard. The impact of the new standards on fuel use and GHG emissions would therefore continue to grow through

planning effects, NHTSA’s analysis indicates that Ford could apply more technology to the MY 2015 F-150 if standards continue to increase after MY 2016 than Ford ne ed apply if standards remain unchanged after MY 2016, and that this additional technology would yield further fu el economy improvements of up to 1.3 mpg, depending on pickup configuration.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 672 of 768 approximately 2060, when virtually all cars and ligh t trucks in service will have met standards as stringent as those established for MY 2025.

As Table IV.G.2–1 shows, NHTSA estimates that the fuel economy increases resulting from the proposed standards will lead to reductio ns in total fuel consumption by cars and light trucks of 3 billion gallons during 2020, increasing to 41 billion gallons by 2060. Over the period from 2017, when the proposed standards would be gin to take effect, through 2050, cumulative fuel savings would total 1,112 billion ga llons, as Table IV.G.2–1 also indicates.

T ABLE IV.G.2-1. R EDUCTION IN F LEET -W IDE F UEL U SE ( BILLION GASOLINE GALLON EQUIVALENTS ) UNDER THE P ROPOSED S TANDARDS

Calendar

year 2020 2030 2040 2050 2060 Total, 2017-2060
PC 1.5 11.8 19.4 22.8 25.9 691.9
LT 1.4 8.8 11.4 13.1 14.8 428.1 Combined 2.9 20.5 30.7 35.8 40.7 1,112.0

The energy security analysis conducted for this rule estimates that the world price of oil will fall modestly in response to lower U.S. demand for refined fuel. One potential result of this decline in the world price of oil would be an increase in the consumption of petroleum products outside the U.S., which would in turn lead to a modest increase in emissions of greenhouse gases, criteria air pollutants, and airborne toxi cs from their refining and use. While additional information would be needed to analyze this “leakage effect” in detail, NHTSA provides a sample estimate of its poten tial magnitude in its Draft EIS. 749 This analysis indicates that the leakage effect is likely to offset only a very small fraction of the reductions in fuel use and emissions projected to result from the rule.

As a consequence of these reductions in fl eet-wide fuel consumption, the agency also estimates that the new CAFE standards for MYs 2017–2025 would lead to corresponding reductions in CO 2 emissions from the U.S. light-duty vehicle fleet. Specifically, NHTSA estimates that total annual CO 2 emissions associated with passenger car and light truck use in the U.S. use would decline by 26 million metric tons (mmt) in 2020 as a consequence of the new CAFE standards, as Table IV.G.2–2 reports. The table also shows that the this annual reduction is estimated to grow to nearly 362 million metric tons by the year 2060, and will total nearly 10 billion metric tons over the period from 2017, wh en the proposed standards would take effect, through 2060.

T ABLE IV.G.2-2. R EDUCTION IN F LEET -W IDE C ARBON D IOXIDE E MISSIONS ( MMT ) FROM

P ASSENGER C AR AND L IGHT T RUCK U SE UNDER THE P ROPOSED S TANDARDS

Calendar

year 2020 2030 2040 2050 2060 Total, 2017-2060 PC 13.6 104.3 171.9 202.3 229.9 6,147.9

749 [cite DEIS]DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 673 of 768 LT 12.1 78.0 101.2 116.3 132.0 3813.7 Combined 25.6 182.2 273.2 318.6 361.9 9,961.7

These reductions in fleet-wide CO 2 emissions, together with corresponding reductions in other GHG emissions from fuel production and us e, would lead to small but significant reductions in projected changes in the future global climate. These changes, based on analysis documented in the draft Environmental Impact Statement (EIS) that informed the agency’s decisions regarding this proposal, are summarized in Table IV.G.2–3 below.

T ABLE IV.G.2-2. E FFECTS OF R EDUCTION IN F LEET -W IDE C ARBON D IOXIDE E MISSIONS ( MMT ) ON P ROJECTED C HANGES IN G LOBAL C LIMATE [ TO BE COMPLETED ]

Measure Units Date Projected change in measure

No action With proposed standards Difference

Atmospheric CO2 concentration Ppm 2100

Increase in global mean surface temperature °C 2100

Sea level rise Cm 2100 Global mean precipitation % change from 1980-1999 avg. 2090

3. How will these proposed standards impact non-GHG emissions and their associated effects?

Under the assumption that CAFE standards at least as stringent as those proposed for MY 2025 would be established for subsequent model years, the effects of the new standards on air quality and its associated health effects will continue to be felt over the foreseeable future. This will occur because over time a growing fraction of the U.S. light-duty vehicle fleet will be comprised of cars and light trucks that meet the MY 2025 standard, and this growth will continue until approximately 2060.

Increases in the fuel economy of light-duty vehicles required by the new CAFE standards will cause a slight increase in the number of miles they are driven, through the fuel economy “rebound effect.” In turn, this increase in vehi cle use will lead to increases in emissions of criteria air pollutants and some airborne toxics, since these are products of the number of miles vehicles are driven.

At the same time, however, the projected reductions in fuel production and use reported in Table IV.G.2–1 and 2-2 above will lead to co rresponding reductions in emissions of these pollutants that occur during fuel production and distribution (“upstream” emissions). For most of these pollutants, the reduction in upstream emissions resulting from lower fuel production andDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 674 of 768 distribution will outweigh the in crease in emissions from vehicle use, resulting in a net decline in their total emissions. 750

Tables IV.G.3–1a and 3–1b report estimated reductions in emissions of selected criteria air pollutants (or their chemical precursors) a nd airborne toxics expected to result from the proposed standards during calendar year 2030. By that date, cars and light trucks meeting the MY 2025 CAFE standards will account for the majo rity of light-duty vehicle use, so these reductions provide a useful index of the long-term impact of the final standards on air pollution and its consequences for human health. In the tables below, positive values indicate increases in emissions, while negative values indicate reductions.

T ABLE IV.G.3-1 A

. P ROJECTED C HANGES IN E MISSIONS OF C RITERIA A IR P OLLUTANTS

FROM P ASSENGER C AR AND L IGHT T RUCK U SE ( CALENDAR YEAR 2030; TONS )

Vehicle class Source of emissions Criteria air pollutant

Nitrogen

oxides (NO X ) Particulat

e matter (PM 2.5 ) Sulfur oxides (SO X ) Volatile organic compounds

(VOC)

Passenger cars Vehicle use Fuel production and distribution All sources 13,163 -19.133 -5971 -284 -2,101 -2,386 -2,601 -7,995 -10,597 -1,080 -42,354 -43,434

Light trucks Vehicle use Fuel production and distribution All sources 2,437 -14,794 -12,357 80 -1,633 -1,553 -1,674 -7,432 -9,106 859 -24,807 -23,948

Total Vehicle use Fuel production and distribution All sources 15,600 -33,928 -18,328 -204 -3,735 -3,939 -4,275 -15,427 -19,702 -221 -67,161 -67,381

T ABLE IV.G.3-1 B

. P ROJECTED C HANGES IN E MISSIONS OF A IRBORNE T OXICS FROM

P ASSENGER C AR AND L IGHT T RUCK U SE ( CALENDAR YEAR 2030; TONS )

Vehicle class Source of emissions Toxic air pollutant

Benzene 1,3- Butadiene Formaldehyde

Passenger

cars Vehicle use Fuel production and distribution All sources -166 -186

-352 -3 -1.6

-4.6 373
-55

319 Light trucks Vehicle use 19 5 38

750 As stated elsewhere, while the agen cy’s analysis assumes that all changes in upstream emissions result from a decrease in petroleum production and transport, the anal ysis of non-GHG emissions in future calendar years also assumes that retail gasoline composition is unaffected by this rule; as a result, th e impacts of this rule on downstream non-GHG emissions (more specifically , on air toxics) may be underestimated. See also Section III.G above for more information.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 675 of 768 Fuel production and distribution All sources -110

-91 -1.2

3.9 -40

-2

Total Vehicle use Fuel production and distribution All sources -147 -296

-443 2.1 -2.8

-0.7 412 -95

317

In turn, the reductions in emissions reported in Tables IV.G.3–1a and 3–1b are projected to result in significant declines in the adverse health effects that result from population exposure to these pollutants. Table IV.G.3–2 reports the estimated reductions in selected PM 2.5 -related human health impacts that are expected to result from reduced population exposure to unhealthful atmospheric concentrations of PM 2.5 . The estimates reported in Table IV.G.3–2, based on analysis documented in the draft Environmental Impact Statement (EIS) that informed the agency’s decisions regarding this proposed rule, are derived from PM 2.5 -related dollar-perton estimates that reflect the quantifiable reduct ions in health impacts likely to result from reduced population exposure to particular matter (PM 2.5 ). They do not include all health impacts related to reduced exposure to PM, nor do they include any reductions in health impacts resulting from lower population exposure to other criteria air pollutants (particularly ozone) and air toxics.

However, emissions changes and dollar-per-ton estimates alone are not necessarily a good indication of local or regional air quality and health impacts, as there may be localized impacts associated with this rulemaking, because the atmospheric chemistry related to ambient concentrations of PM 2.5 , ozone, and air toxics is very complex. Full-scale photochemical modeling would provide the necessary spatial an d temporal detail to more completely and accurately estimate the changes in ambient levels of these pollutants and their associated health and welfare impacts. EPA intends to conduct such modeling for purposes of the final rule, but it was not available in time to inform these proposed standards or to be included in the DEIS. See Section III.G above for EPA’s description of the air quality modeling it conducted for calendar year 203? to capture this variability.

T ABLE IV.G.3-2. P ROJECTED R EDUCTIONS IN H EALTH I MPACTS FROM E XPOSURE TO C RITERIA A IR P OLLUTANTS D UE TO P ROPOSED S TANDARDS ( CALENDAR YEAR 2030) [ TO BE

COMPLETED ]

Health impact Measure Projected reduction (2030) Mortality (ages 30 and older) premature deaths per year Chronic bronchitis cases per year Emergency room visits for asthma number per year Work loss workdays per year

4. What are the estimated costs and benefits of these proposed standards?

NHTSA estimates that the proposed stan dards could entail significant additional technology beyond the levels that could be applied under baseline CAFE standards ( i.e. , theDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 676 of 768 application of MY 2016 CAFE st andards to MYs 2017-2025). This additional technology will lead to increases in costs to manufacturers and ve hicle buyers, as well as fuel savings to vehicle buyers. Also, as discussed above, NHTSA estim ates that today’s proposed standards could induce manufacturers to apply technology during redesigns leading into model years covered by today’s new standards, and to incur corresponding increases in technology outlays.

In order to pay for this additional technology (and, for some manufacturers, civil penalties), NHTSA estimates that the cost of an average passenger car and light truck will increase relative to levels resulting from co mpliance with baseline (MY 2016) standards by $236–$2,170 and $70–$1,581, respectively, during MYs 2017–2025. The following tables summarize the agency’s estimates of average cost increases for each manufacturer’s passenger car, light truck, and overall fleets (with co rresponding averages for the industry):

T ABLE IV.G.4-1 A

. A VERAGE P ASSENGER C AR I NCREMENTAL C OST I NCREASES ($) UNDER P ROPOSED S TANDARDS

– MY S 2017-2021
Manufacturer MY 2017 MY 2018 MY 2019 MY 2020 MY 2021 Average 236 492 690 931 1,237 Aston Martin 84 161 249 343 453
BMW 79 158 238 332 427 Daimler (Mercedes) 73 150 226 330 429 Fiat (Chrysler) 341 860 857 1,454 1,560 Ford 461 813 964 1,221 1,901 Geely (Volvo) 79 158 238 331 476 General Motors 280 681 893 1,368 1,740 Honda 135 452 527 559 1,156 Hyundai 314 354 674 703 965 Kia 166 242 533 1,044 1,389
Lotus 90 178 266 365 480 Mazda 636 909 876 1,343 1,320 Mitsubishi 79 485 571 809 1,111 Nissan 249 403 895 1,039 1,151 Porsche 93 175 269 362 479 Spyker (Saab) 84 161 244 337 440 Subaru 84 156 490 976 1,052 Suzuki 624 612 1,920 1,951 1,907 Tata (Jaguar, Rover) 104 175 254 331 477 Tesla 2 2 2 2 2 Toyota 131 409 618 835 1,033 Volkswagen 79 162 244 311 408

T ABLE IV.G.4-1 B

. A VERAGE P ASSENGER C AR I NCREMENTAL C OST I NCREASES ($) UNDER P ROPOSED S TANDARDS

– MY S 2022-2025
Manufacturer MY 2022 MY 2023 MY 2024 MY 2025 Average 1,407 1,682 2,062 2,170DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 677 of 768 Aston Martin 574 700 832 970 BMW 552 679 903 1,024 Daimler (Mercedes) 532 770 888 1,351 Fiat (Chrysler) 1,614 2,268 2,870 2,725 Ford 2,115 2,814 3,319 3,063 Geely (Volvo) 591 795 1,169 1,290 General Motors 1,734 2,197 2,562 2,874 Honda 1,265 1,523 1,607 1,754 Hyundai 1,518 1,598 2,205 2,095 Kia 1,505 1,687 1,671 1,839 Lotus 612 738 881 1,035 Mazda 1,843 2,147 2,529 2,503 Mitsubishi 1,196 1,303 1,748 3,869 Nissan 1,628 1,774 2,292 2,324 Porsche 583 721 870 1,027 Spyker (Saab) 566 694 832 975 Subaru 1,164 1,280 2,067 3,261 Suzuki 1,895 2,002 3,857 3,368 Tata (Jaguar, Rover) 753 1,025 1,138 1,258 Tesla 2 2 2 2 Toyota 1,115 1,102 1,528 1,599 Volkswagen 588 729 897 1,189

T ABLE IV.G.4-2 A

. A VERAGE L IGHT T RUCK I NCREMENTAL C OST I NCREASES ($) UNDER P ROPOSED S TANDARDS

– MY S 2017-2021
Manufacturer MY 2017 MY 2018 MY 2019 MY 2020 MY 2021 Average 70 208 426 671 924 Aston Martin - - - - -
BMW 36 81 149 285 474 Daimler (Mercedes) 44 61 93 218 324 Fiat (Chrysler) 295 294 336 1,179 1,300 Ford 28 305 308 420 1,296 Geely (Volvo) 7 63 101 144 271 General Motors (4) 185 549 1,091 1,111 Honda 308 313 484 538 871 Hyundai 188 196 714 712 696 Kia 60 73 176 306 1,005
Lotus - - - - - Mazda 1 472 452 487 496 Mitsubishi 262 286 279 314 2,464 Nissan 26 41 337 486 835 Porsche 1 84 109 153 274 Spyker (Saab) 7 105 148 192 320 Subaru 114 454 1,015 993 1,018 Suzuki 293 301 1,667 1,638 1,860DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 678 of 768 Tata (Jaguar, Rover) 18 74 117 161 290 Tesla - - - - - Toyota 1 191 396 413 601 Volkswagen 7 69 350 358 492

T ABLE IV.G.4-2 B

. A VERAGE L IGHT T RUCK I NCREMENTAL C OST I NCREASES ($) UNDER P ROPOSED S TANDARDS

– MY S 2022-2025
Manufacturer MY 2022 MY 2023 MY 2024 MY 2025 Average 1,056 1,239 1,399 1,581 Aston Martin - - - - BMW 867 958 1,095 1,148 Daimler (Mercedes) 1,181 1,264 1,318 1,352 Fiat (Chrysler) 1,339 1,631 1,705 1,994 Ford 1,335 1,823 1,853 1,935 Geely (Volvo) 551 1,001 1,095 1,147 General Motors 1,175 1,335 1,409 1,787 Honda 1,285 1,312 1,328 1,384 Hyundai 1,201 1,185 1,688 1,665 Kia 988 1,174 1,158 1,205
Lotus - - - - Mazda 479 977 1,430 1,365 Mitsubishi 2,417 2,366 2,330 2,262 Nissan 1,194 1,258 1,455 1,664 Porsche 372 744 835 900 Spyker (Saab) 413 556 660 765 Subaru 1,055 1,044 1,850 1,753 Suzuki 1,946 1,916 1,995 2,274 Tata (Jaguar, Rover) 389 489 593 703 Tesla - - - - Toyota 603 764 1,092 1,240 Volkswagen 580 769 1,179 1,203

T ABLE IV.G.4-3 A

. A VERAGE I NCREMENTAL C OST I NCREASES ($) BY M ANUFACTURER

UNDER P ROPOSED S TANDARDS

– MY S 2017-2021 Manufacturer MY 2017 MY 2018 MY 2019 MY 2020 MY 2021 Average 175 389 596 840 1,127 Aston Martin 84 161 249 343 453
BMW 66 135 214 319 439 Daimler (Mercedes) 66 130 195 303 403 Fiat (Chrysler) 319 583 608 1,327 1,443 Ford 301 628 735 947 1,697 Geely (Volvo) 56 127 194 272 412 General Motors 143 436 721 1,230 1,429 Honda 194 407 513 553 1,068 Hyundai 288 322 683 705 910DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 679 of 768 Kia 141 201 447 874 1,303
Lotus 90 178 266 365 480 Mazda 528 830 801 1,191 1,174 Mitsubishi 146 413 467 636 1,583 Nissan 173 285 717 867 1,054 Porsche 68 152 230 313 430 Spyker (Saab) 75 153 228 316 423 Subaru 92 232 622 980 1,044 Suzuki 559 552 1,873 1,894 1,898 Tata (Jaguar, Rover) 60 124 185 247 384 Tesla 2 2 2 2 2 Toyota 77 322 532 675 864 Volkswagen 65 142 267 321 425

T ABLE IV.G.4-3 B

. A VERAGE I NCREMENTAL C OST I NCREASES ($) BY M ANUFACTURER

UNDER P ROPOSED S TANDARDS

– MY S 2022-2025
Manufacturer MY 2022 MY 2023 MY 2024 MY 2025 Average 1,285 1,531 1,840 1,975 Aston Martin 574 700 832 970 BMW 635 752 956 1,057 Daimler (Mercedes) 693 894 993 1,351 Fiat (Chrysler) 1,488 1,978 2,354 2,412 Ford 1,853 2,495 2,859 2,716 Geely (Volvo) 578 857 1,147 1,248 General Motors 1,461 1,782 2,012 2,356 Honda 1,271 1,460 1,526 1,645 Hyundai 1,454 1,514 2,101 2,010 Kia 1,392 1,575 1,561 1,705 Lotus 612 738 881 1,035 Mazda 1,602 1,945 2,341 2,313 Mitsubishi 1,615 1,669 1,944 3,336 Nissan 1,496 1,617 2,040 2,129 Porsche 533 726 862 1,000 Spyker (Saab) 545 676 809 947 Subaru 1,138 1,225 2,017 2,921 Suzuki 1,904 1,987 3,533 3,180 Tata (Jaguar, Rover) 572 761 879 1,000 Tesla 2 2 2 2 Toyota 919 975 1,368 1,468 Volkswagen 586 737 955 1,192

These cost estimates reflect the potential that a given manufacturer’s efforts to minimize overall regulatory costs could focus technology wher e the most fuel can be saved at the least cost, and not necessarily, for example, where the cost to add technology would be smallestDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 680 of 768 relative to baseline production costs. Therefore, if average incremental vehicle cost increases (including any civil penalties) are measured as increases relative to baseline prices (estimated by adding baseline costs to MY 2008 prices), the agency’s analysis shows relative cost increases declining as baseline vehicle price increases. Figure IV.G.4-1 shows the trend for MY 2025, for vehicles with estimated baseline prices up to $100,000:

F IGURE IV.G.4-1. E STIMATED I NCREMENTAL C OST I NCREASES IN MY 2025

If manufacturers pass along these costs rather than reducing profits, and pass these costs along where they are incurred rather than “cross-subsidizing” among products, the quantity of vehicles produced at different price levels woul d change. Figure IV.G.4-2 illustrates these effects for the MY 2025 passenger car fleet. In the MY 2008-based market forecast developed jointly by EPA and NHTSA, production ( i.e. , as shares of the market) of vehicles offered in the $17,500-$25,000 price range declines somewhat by MY2 025, and production of less expensive vehicles increases. Under the no-action alternative ( i.e. , continuation of the baseline MY 2016 standards), the agency’s analysis shows modest production declines in the $15,000-$17,500 price range, modest production increases in the $22,500-$25,000 and $30,000-$35,000 ranges, and smaller production changes in other price ranges. However, under the proposed standards, the agency’s analysis shows production of passenger cars under $15,000 falling to less than 1% of the market (versus 6% of the market under the baseline standards), and shows production of vehicles in the $15,000-$17,500 range declining considerably:DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 681 of 768 F IGURE IV.G.4-2. E STIMATED P ASSENGER C AR P RICE D ISTRIBUTION IN MY 2025

Figure IV.G.4-3 illustrates corresponding e ffects for the MY 2025 light truck fleet, for which MY 2008 vehicle prices we re distributed in a manner notably different from those of passenger cars (relative to that of passenger cars, production of light trucks is far lower at the lowest and highest price levels, and is more con centrated in the “upper middle” price bands). In the MY 2008-based market forecast developed jointly by EPA and NHTSA, production ( i.e. , as shares of the market) of vehicles offered in MY2025 declines relative to MY 2008 production in the $20,000-$22,500 and $25,000-$27,500 ranges, and increases in the $30,000-$35,000 range. Under the no-action alternative ( i.e. , continuation of the baseline MY 2016 standards), the agency’s analysis shows modest production declines in some price ranges ($20,000-$25,000 and $27,500-$30,000), modest production increas es other ranges ($25,500-$27,500, $30,000- $35,000, and $45,000-$55,000 ranges, and smaller production changes in other price ranges. However, under the proposed standards, the agency’s analysis shows production of light trucks under $25,000 falling to about 8% of the market (versus 22% of the market under the baseline standards):

F IGURE IV.G.4-3. E STIMATED L IGHT T RUCK P RICE D ISTRIBUTION IN MY 2025DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 682 of 768 Figure IV.G.4-4 illustrates resultant effects for the overall MY 2025 light vehicle fleet. In the MY 2008-based market forecast developed jointly by EPA and NHTSA, production ( i.e.

, as shares of the market) of vehicles offered in MY 2025 increases somewhat relative to MY 2008 production in the $12,500-$17,500 range, declines somewhat in the $25,000-$27,500 range, and changes more slightly in other price ra nges. Under the no-action alternative ( i.e. , continuation of the baseline MY 2016 standards), the agency’s analysis shows small production decreases in the $15,000-$17,500 range, small increases in the $30,000-$35,000 range, and slight changes in other price ranges. However, under the proposed standards, the agency’s analysis shows production of light vehicles under $17,500 falling by about half:

F IGURE IV.G.4-4. E STIMATED F LEET -W IDE P RICE D ISTRIBUTION IN MY 2025DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 683 of 768 This shift in production, away from the lo west priced segments of the new vehicle market, may create marketing challenges for manufacturers that are active in those segments. We recognize, of course, that many manufacturers do in fact cross-subsidize to some extent, and take losses on some vehicles while continuing to make profits from others. NHTSA has no evidence to indicate that manufacturers will shift produc tion plans in the manner described above, but nevertheless believes that this issue is worth monitoring in the market going forward.

As mentioned above, these estimated costs derive primarily from the additional application of technology under the proposed st andards. The following three tables summarize the incremental extent to which the agency estimates technologies could be added to the passenger car, light truck, and overall fleets in each model year in response to the proposed standards. Percentages reflect the technology’s additional application in the market, relative to the estimated application under baseline standards ( i.e. , application of MY 2016 standards through MY 2025), and are negative in cases where one technology is superseded ( i.e., displaced) by another. For example, the agency estimates that manufacturers could apply many improvements to transmissions ( e.g. , dual clutch transmissions, denoted below by “DCT”) through MY 2025 under baseline standards. However, the agency also estimates that manufacturers could apply even more advanced hi gh efficiency transmissions (denoted below by “HETRANS”) under the proposed standards, a nd that these transmissions would supersede DCTs and other transmission advances. Therefore, as shown in the following three tables, the incremental application of DCTs under the proposed standards is negative.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 684 of 768 T ABLE IV.G.4-4. I NCREMENTAL A PPLICATION OF T ECHNOLOGIES TO P ASSENGER C AR F LEET UNDER P ROPOSED S TANDARDS

– MY S 2017-2025 Technology 2017 2018 2019 2020 2021 2022 2023 2024 2025
LUB1 7% 16% 16% 16% 16% 16% 16% 16% 16% EFR1 22% 28% 28% 28% 27% 28% 28% 28% 28% LUB2_EFR2 1% 11% 22% 31% 40% 42% 44% 47% 50%
CCPS 0% 2% 6% 6% 6% 6% 6% 6% 6%
DVVLS 0% 0% 0% 0% 0% 0% 0% 0% 0% DEACS 0% 0% 0% (0%) (0%) (0%) (1%) (1%) (1%) ICP (0%) (0%) (0%) (0%) (0 %) (0%) (0%) (0%) (0%)
DCP 8% 9% 9% 11% 19% 19% 18% 18% 17%
DVVLD 8% 14% 19% 24% 28% 34% 33% 33% 33% DEACD 0% 0% 0% (0%) (0%) (0%) (0%) (0%) (0%)
SGDI 10% 15% 22% 27% 35% 42% 45% 55% 56% DEACO (0%) (0%) (1%) (2%) (2%) (2%) (2%) (2%) (2%)
VVA 0% 0% 0% 0% 0% 0%
SGDIO 0% 0% 1% 2% 2% 2% 2% 2% 2% TRBDS1_SD 6% 8% 9% 11% 15% 12% 9% 6% 2% TRBDS1_MD 2% 2% 3% 3% 3% 2% (1%) (6%) (7%) TRBDS1_LD (0%) (0%) (0%) (0%) (0%) (0%) (0%) (0%) (0%) TRBDS2_SD 0% 0% 2% 2% 1% 2% 2% 0% (0%) TRBDS2_MD (2%) (2%) (2%) (3%) (2%) (2%) (2%) (3%) (3%) TRBDS2_LD CEGR1_SD 1% 2% 2% 4% 8% 16% 18% 29% 35% CEGR1_MD 3% 5% 7% 9% 6% 8% 9% 11% 11% CEGR1_LD 0% 0% 0% 0% (0%) (0%) (0%) (0%) (0%) CEGR2_SD 0% 0% 0% 1% 2% 4% 4% CEGR2_MD 2% 4% 4% 6% 7% 5% CEGR2_LD 0% 1% 1% 2% 2% 2% 2% 2% 1% ADSL_SD 0% 1% 2% 2% 2% 2% 2% 3% ADSL_MD 1% 1% 1% 1% 1% 2% 3% 4% ADSL_LD 0% 0% 6MAN 1% 1% 0% (1%) (1%) (1%) (1%) (1%) (1%)
HETRANSM 0% 1% 2% 4% 5% 6% 6% 6% 7% IATC (1%) (1%) (1%) (1 %) (1%) (1%) (1%) (1%) NAUTO (3%) (4%) (5%) (6%) (6%) (6%) (6%) (6%) (6%) DCT (7%) (18%) (29%) (34%) (42%) (44%) (45%) (46%) (47%) 8SPD 1% 1% (2%) (8%) (10%) (12%) (12%) (14%) (16%)
HETRANS 7% 21% 31% 41% 47% 53% 52% 50% 51%
SHFTOPT 11% 27% 42% 53% 64% 67% 65% 62% 59%
EPS 8% 10% 14% 19% 30% 32% 35% 34% 34%
IACC1 12% 14% 16% 24% 37% 40% 42% 48% 48%
IACC2 10% 15% 21% 31% 50% 53% 60% 65% 65% MHEV 3% 7% 12% 22% 29% 35% 36% 38% 36%DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 685 of 768 SHEV1 SHEV1_2 0% 0% 0% 0% 0% 0% 0% 1%
SHEV2 0% 0% 0% 0% 3% 6% 8%
PHEV1 1% 1% 2% 3% 4%
MR1 8% 14% 14% 14% 14% 14% 15% 14% 14%
MR2 0% 13% 25% 28% 28% 30% 30% 30% 29% MR3 1% 4% 6% 8% 8% 8% 9% 9% 10%
MR4 2% 4% 4% 6% 6% 7% 8% 10% 10%
MR5 0% 2% 2% 3% 4% 4% 5% 6% 7%
ROLL1 2% 2% 2% 2% 2% 2% 2% 2% ROLL2 5% 23% 34% 44% 57% 66% 67% 68% 68%
LDB 1% 2% 2% 2% 2% 3% 3% 3% 3% SAX (0%) (0%) (0%) (0%) 0% 0% 0%
AERO1 3% 3% 3% 3% 3% 3% 3% 3% AERO2 5% 14% 27% 34% 45% 52% 52% 52% 51%

T ABLE IV.G.4-5. I NCREMENTAL A PPLICATION OF T ECHNOLOGIES TO L IGHT T RUCK F LEET

UNDER P ROPOSED S TANDARDS

– MY S 2017-2025 Technology 2017 2018 2019 2020 2021 2022 2023 2024 2025
LUB1
EFR1 0% 0% 0% 0% 0% 0% LUB2_EFR2 2% 6% 16% 29% 43% 58% 79% 88% 89% CCPS (0%) (0%) (0%) (1%) (1%) (1%)
DVVLS 1% 1% 1% 0% 1% 1% 1% 1% 1% DEACS 0% 0% 0% 0% (2%) (3%) (3%) (3%) (3%)
ICP
DCP 1% 1% 1% 1% 1% 4% 5% 5% 3%
DVVLD 0% 1% 3% 3% 9% 10% 11% 16% 14% DEACD (1%) (1%) (2%) (2%) (2%) (2%) (2%)
SGDI 1% 1% 5% 5% 18% 24% 26% 33% 33% DEACO (1%) (6%) (7%) (6%) (8%) (8%) (9%)
VVA 2% 2% 2% 2% 2% 2% 2% SGDIO 0% 0% 0% 5% 6% 6% 7% 7% 8% TRBDS1_SD (0%) (0%) (0%) (0%) (0%) (0%) (0%) TRBDS1_MD 1% (2%) 1% (4%) 2% 1% (5%) (8%) (13%) TRBDS1_LD 0% 0% 0% 0% 0% 0% (0%) TRBDS2_SD (0%) (0%) (0%) 2% 2% 4% 4% TRBDS2_MD TRBDS2_LD CEGR1_SD 0% 0% 0% 0% 1% 2% 4% CEGR1_MD 0% 3% 4% 13% 17% 20% 27% 34% 38% CEGR1_LD CEGR2_SD CEGR2_MD 0% 0% 0% 0% 0%DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 686 of 768 CEGR2_LD 0% 0% 1% 1% 4% 7% 8% 8% 8% ADSL_SD 0% 0% 0% 0% 0% ADSL_MD 2% 2% 2% 2% 2% 2% 4% ADSL_LD 0% 6MAN (0%) (0%) (0%) (0%) (0%) (0%) (0%)
HETRANSM 0% 1% 1% 1% 2% 2% 2% 2% 2% IATC (1%) (1%) (1%) (1%) (1%) (1%) (1%) NAUTO (5%) (10%) (19%) (20%) (26%) (26%) (26%) (25%) (25%) DCT (3%) (9%) (10%) (11%) (11%) (12%) (12%) (12%) (12%) 8SPD 4% 1% (10%) (16%) (27%) (27%) (29%) (30%) (34%)
HETRANS 1% 19% 36% 53% 61% 61% 62% 62% 67%
SHFTOPT 6% 18% 37% 49% 73% 79% 80% 81% 81%
EPS 2% 4% 14% 26% 32% 45% 57% 62% 62%
IACC1 2% 3% 7% 14% 19% 23% 30% 38% 41% IACC2 1% 7% 17% 32% 41% 52% 65% 72% 75%
MHEV 0% 0% 0% 7% 8% 8% 13% 17% 18% SHEV1_2 0% 0% 0% 0% 1% 1%
SHEV2
PHEV1
MR1 5% 5% 10% 12% 14% 14% 14% 14% 14%
MR2 1% 12% 33% 42% 51% 56% 58% 58% 59%
MR3 1% 4% 6% 16% 28% 39% 51% 68% 81%
MR4 1% 1% 1% 3% 10% 12% 16% 22% 41%
MR5 0% 0% 1% 5% 7% 24%
ROLL1 0% 0% 0% 0% 0% 0% 0% ROLL2 2% 14% 32% 49% 61% 72% 76% 82% 82%
ROLL3 LDB (0%) 1% 2% 8% 15% 23% 29% 32% 40%
SAX 1% 4% 4% 5% 6% 9% 13% 19% 29%
AERO1
AERO2 10% 15% 32% 37% 37% 39% 39% 40% 40%

T ABLE IV.G.4-6. I NCREMENTAL A PPLICATION OF T ECHNOLOGIES TO O VERALL F LEET

UNDER P ROPOSED S TANDARDS

– MY S 2017-2025 Technology 2017 2018 2019 2020 2021 2022 2023 2024 2025
LUB1 4% 10% 10% 10% 10% 10% 11% 11% 10%
EFR1 14% 18% 18% 18% 18% 18% 18% 19% 19% LUB2_EFR2 2% 9% 20% 30% 41% 48% 56% 61% 63% CCPS 0% 1% 4% 4% 4% 4% 4% 4% 4%
DVVLS 0% 0% 0% 0% 1% 1% 1% 1% 1% DEACS 0% 0% 0% (0%) (1%) (1%) (1%) (1%) (1%) ICP (0%) (0%) (0%) (0%) (0%) (0%) (0%) (0%) (0%)
DCP 5% 6% 6% 7% 13% 14% 14% 14% 12%
DVVLD 5% 9% 13% 17% 21% 26% 26% 27% 27% DEACD 0% 0% (0%) (0%) (1%) (1%) (1%) (1%) (1%)DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 687 of 768 SGDI 7% 10% 15% 19% 29% 36% 38% 47% 49% DEACO (0%) (0%) (1%) (3%) (4%) (4%) (4%) (4%) (4%)
VVA 1% 1% 1% 1% 1% 1% 1%
SGDIO 0% 0% 1% 3% 4% 3% 4% 4% 4% TRBDS1_SD 4% 5% 6% 7% 10% 8% 6% 4% 1% TRBDS1_MD 2% 1% 2% 0% 3% 2% (3%) (6%) (9%) TRBDS1_LD (0%) (0%) (0%) (0%) (0%) (0%) (0%) (0%) (0%) TRBDS2_SD 0% 0% 1% 1% 1% 2% 2% 2% 1% TRBDS2_MD (1%) (1%) (1%) (2%) (2%) (2%) (2%) (2%) (2%) CEGR1_SD 1% 1% 2% 3% 6% 10% 12% 20% 25% CEGR1_MD 2% 4% 6% 10% 10% 12% 15% 19% 20% CEGR1_LD 0% 0% 0% 0% (0%) (0%) (0%) (0%) (0%) CEGR2_SD 0% 0% 0% 1% 1% 3% 3% CEGR2_MD 1% 3% 3% 4% 5% 4% CEGR2_LD 0% 1% 1% 2% 3% 4% 4% 4% 4% ADSL_SD 0% 1% 1% 1% 2% 2% 2% 2% ADSL_MD 1% 1% 1% 1% 1% 2% 2% 4% ADSL_LD 0% 0% 6MAN 0% 0% 0% (0%) (0%) (1%) (1%) (1%) (1%)
HETRANSM 0% 1% 2% 3% 4% 4% 5% 5% 5% IATC (1%) (1%) (1%) (1%) (1%) (1%) (1%) (1%) NAUTO (4%) (6%) (10%) (11%) (13%) (13%) (13%) (13%) (12%) DCT (5%) (15%) (22%) (26%) (31%) (33%) (33%) (35%) (35%) 8SPD 2% 1% (5%) (11%) (16%) (17%) (18%) (19%) (22%)
HETRANS 5% 20% 33% 45% 52% 56% 55% 54% 56% SHFTOPT 9% 24% 40% 52% 67% 71% 70% 69% 66%
EPS 6% 8% 14% 21% 31% 37% 42% 43% 43%
IACC1 8% 10% 13% 20% 31% 34% 38% 44% 46%
IACC2 7% 12% 20% 31% 47% 53% 62% 68% 69% MHEV 2% 4% 8% 17% 21% 25% 28% 31% 30% SHEV1_2 0% 0% 0% 0% 0% 0% 1% 1%
SHEV2 0% 0% 0% 0% 2% 4% 6%
PHEV1 0% 1% 1% 2% 3% MR1 7% 11% 13% 14% 14% 14% 14% 14% 14%
MR2 0% 13% 28% 33% 36% 39% 40% 39% 39%
MR3 1% 4% 6% 11% 15% 19% 23% 29% 33%
MR4 2% 3% 3% 5% 8% 9% 11% 14% 20%
MR5 0% 1% 1% 2% 3% 3% 5% 6% 13%
ROLL1 1% 1% 2% 2% 2% 2% 2% 2%
ROLL2 4% 20% 33% 46% 59% 68% 70% 73% 73%
LDB 1% 1% 2% 4% 7% 10% 12% 13% 15%
SAX 0% 2% 1% 2% 2% 3% 5% 7% 10%
AERO1 2% 2% 2% 2% 2% 2% 2% 2%
AERO2 7% 15% 29% 35% 42% 47% 47% 48% 48%DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 688 of 768 Based on the agencies’ estimates of manufacturers’ future sales volumes, and taking into account early outlays attributable to multiyear planning effects (discussed above), the cost increases associated with this a dditional application of technology will lead to a total of nearly $158 billion in incremental outlays during MY s 2017–2025 (and model years leading up to MY 2017) for additional technology attrib utable to the proposed standards:

T ABLE IV.G.4-7 A

. I NCREMENTAL T ECHNOLOGY O UTLAYS ($M) UNDER P ROPOSED S TANDARDS

– MY S 2017-2021
Earlier MY2017 MY2018 MY2019 MY2020 MY2021 Total 3,860 2,634 5,805 8,893 12,819 17,476 Aston Martin - 0 0 0 0 0
BMW - 6 6 11 27 37 Daimler (Mercedes) - 4 5 6 21 21 Fiat (Chrysler) 496 266 462 465 1,039 1,121 Ford 760 621 1,294 1,506 1,984 3,591 Geely (Volvo) - 0 1 2 2 8 General Motors 1,008 403 1,270 2,161 3,784 4,421 Honda 195 340 685 858 933 1,852 Hyundai 158 214 235 504 530 701 Kia 107 59 83 186 367 556
Lotus - 0 0 0 0 0 Mazda 355 161 266 260 391 392 Mitsubishi 26 10 40 39 57 158 Nissan 184 228 360 899 1,111 1,391
Porsche - 0 1 1 0 1 Spyker (Saab) - 0 0 0 0 0 Subaru 38 9 42 147 280 281 Suzuki 233 63 61 208 216 221 Tata (Jaguar, Rover) 3 3 3 3 3 8 Tesla - 0 0 0 0 0 Toyota 297 244 984 1,586 2,051 2,697 Volkswagen 0 1 7 52 21 18

Passenger cars 3,426 2,231 4,640 6,536 9,087 12,302 Light trucks 434 403 1,165 2,357 3,733 5,175 Combined 3,860 2,634 5,805 8,893 12,819 17,476

T ABLE IV.G.4-7 B

. I NCREMENTAL T ECHNOLOGY O UTLAYS ($M) UNDER P ROPOSED S TANDARDS

– MY S 2022-2025 ( AND TOTAL THROUGH MY 2025)
MY2022 MY2023 MY2024 MY2025 Total Total 20,146 24,248 29,582 32,072 157,537 Aston Martin 0 0 0 0 0
BMW 95 93 163 152 589 Daimler (Mercedes) 115 170 171 307 821 Fiat (Chrysler) 1,182 1,567 1,832 1,872 10,302DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 689 of 768 Ford 3,946 5,418 6,218 5,838 31,176 Geely (Volvo) 20 51 88 86 259 General Motors 4,509 5,529 6,298 7,534 36,917 Honda 2,258 2,632 2,814 3,122 15,690 Hyundai 1,142 1,204 1,731 1,699 8,119 Kia 604 691 699 785 4,137 Lotus 0 (0) (0) (0) (0) Mazda 547 698 827 793 4,690 Mitsubishi 156 153 183 363 1,185 Nissan 2,018 2,218 2,867 2,984 14,260 Porsche (1) 3 3 3 11 Spyker (Saab) 0 1 1 1 3 Subaru 287 286 534 917 2,821 Suzuki 225 225 428 396 2,277 Tata (Jaguar, Rover) 21 34 35 36 149
Tesla 0 0 0 0 0 Toyota 2,959 3,182 4,498 4,872 23,370 Volkswagen 62 94 191 314 761

Passenger cars 14,205 17,318 21,804 23,257 114,805 Light trucks 5,941 6,930 7,778 8,815 42,731 Combined 20,146 24,248 29,582 32,072 157,537

NHTSA notes that these estimates of the economic costs for meeting higher CAFE standards omit certain potentially important categories of costs, and may also reflect underestimation (or possibly overestimation) of some costs that are included. For example, although the agency’s analysis is intended—with very limited exceptions 751 —to hold vehicle performance, capacity, and utility constant when applying fuel-saving technologies to vehicles, the analysis imputes no cost to any actual reducti ons in vehicle performance, capacity, and utility that may result from manufacturers’ efforts to comply with the proposed CAFE standards. Although these costs are difficult to estimate accurately, they nonetheless represent a notable category of omitted costs if they have not been adequately accounted for in the cost estimates. Similarly, the agency’s estimates of net benefi ts for meeting higher CAFE standards includes estimates of the economic value of potential change s in motor vehicle fatalities that could result from reductions in the size or weight of vehicles, but not of changes in non-fatal injuries that could result from reductions in vehicle size and/or weight.

Finally, while NHTSA is confident that the cost estimates are the best available and appropriate for purposes of this proposed rule, it is possible that the agency may have underestimated or overestimated manufacturers’ direct costs for applying some fuel economy technologies, or the increases in manufacturer’s indirect costs associat ed with higher vehicle

751 For example, the agencies have assumed no cost chan ges due to our assumption that HEV towing capability is not maintained; due to potential drivability issues with th e P2 HEV; and due to potential drivability and NVH issues with the shift optimizer.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 690 of 768 manufacturing costs. In either case, the tec hnology outlays reported here will not correctly represent the costs of meeting higher CAFE st andards. Similarly, NHTSA’s estimates of increased costs of congestion, accidents, and no ise associated with added vehicle use are drawn from a 1997 study, and the correct magnitude of these values may have changed since they were developed. If this is the case, the costs of incr eased vehicle use associated with the fuel economy rebound effect will differ from the agency’s estimates in this analysis. Thus, like the agency’s estimates of economic benefits, estimates of total compliance costs reported here may underestimate or overestimate the true economic costs of the proposed standards.

However, offsetting these costs, the achieved increases in fuel economy will also produce significant benefits to society. Most of these be nefits are attributable to reductions in fuel consumption; fuel savings are valued using for ecasts of pretax prices in EIA’s reference case forecast from AEO 2011. The total benefits also include other benefits and dis-benefits, examples of which include the social values of reductions in CO 2 and criteria pollutant emissions, the value of additional travel (induced by the rebound effect), an d the social costs of additional congestion, accidents, and noise attrib utable to that additional travel. The PRIA accompanying today’s proposed rule presents a detailed analysis of the rule’s specific benefits.

As Tables IV.G.4–8a and 8b show, NHTSA estimates that at the discount rates of 3 percent prescribed in OMB guidance for regulatory analysis, the present value of total benefits from the proposed CAFE standards over the lifetimes of MY 2017–2025 (and, accounting for multiyear planning effects discussed above, model years leading up to MY 2017) passenger cars and light trucks will be $496 billion.

T ABLE IV.G.4-8 A

. P RESENT V ALUE OF B ENEFITS ($ B ) UNDER P ROPOSED S TANDARDS U SING 3 P ERCENT D ISCOUNT R ATE

– MY S 2017-2021 752

Earlier MY 2017 MY 2018 MY 2019 MY 2020 MY 2021
PC 10 6 14 20 27 34
LT 1 2 6 13 17 24 Combined 10 8 20 33 44 58

T ABLE IV.G.4-8 B

. P RESENT V ALUE OF B ENEFITS ($ B ) UNDER P ROPOSED S TANDARDS U SING 3 P ERCENT D ISCOUNT R ATE

– MY S 2022-2025 ( AND TOTAL THROUGH MY 2025)
MY 2022 MY 2023 MY 2024 MY 2025 Total
PC 38 44 52 58 302
LT 28 31 34 38 193 Combined 66 75 86 95 496

Tables IV.G.4–9a and 9b report that the present value of total benefits from requiring cars and light trucks to achieve the fuel economy levels specified in the proposed CAFE standards for

752 Unless otherwise indicated, all tables in Section IV re port benefits calculated usin g the Reference Case input assumptions, with future benefits resulting from reducti ons in carbon dioxide emissions discounted at the 3 percent rate prescribed in the interagency guidance on the social cost of carbon.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 691 of 768 MYs 2017–25 will be $403 billion when discounted at the 7 percent rate also required by OMB guidance. Thus the present value of fuel savings and other benefits over the lifetimes of the vehicles covered by the proposed standards is $93 billion—or about 19 percent—lower when discounted at a 7 percent annual rate than when discounted using the 3 percent annual rate. 753

T ABLE IV.G.4-9 A

. P RESENT V ALUE OF B ENEFITS ($ B ) UNDER P ROPOSED S TANDARDS U SING 7 P ERCENT D ISCOUNT R ATE

– MY S 2017-2021
Earlier MY 2017 MY 2018 MY 2019 MY 2020 MY 2021
PC 8 5 11 16 22 28
LT 1 1 5 10 14 19 Combined 10 6 16 27 36 47

T ABLE IV.G.4-9 B

. P RESENT V ALUE OF B ENEFITS ($ B ) UNDER P ROPOSED S TANDARDS U SING 7 P ERCENT D ISCOUNT R ATE

– MY S 2022-2025 ( AND TOTAL THROUGH MY2025)
MY 2022 MY 2023 MY 2024 MY 2025 Total
PC 32 36 42 47 248
LT 22 25 27 30 155 Combined 54 61 70 78 403

For both the passenger car and light truck fleets, NHTSA estimates that the benefits of today’s proposed standards will exceed the corresponding costs in every model year, so that the

net social benefits from requiring higher fuel ec onomy—the difference between the total benefits that result from higher fuel economy and the tech nology outlays required to achieve it—will be substantial. Because the technology outlays required to achieve the fuel economy levels required by the proposed standards are incurred during the model years when the vehicles are produced and sold, however, they are not subject to discounting, so that their present value does not depend on the discount rate used. Thus the net benefits of the proposed standards differ depending on whether the 3 percent or 7 percent discount rate is used, but only because the choice of discount rates affects the present value of total benefits, and not that of technology

costs.

As Tables IV.G.4–10a and 10b show, over the lifetimes of the affected (MY 2017–2025, and MYs leading up to MY 2017) vehicles, the agency estimates that when the benefits of the proposed standards are discounted at a 3 percent ra te, they will exceed the costs of the proposed standards by $338 billion:
T ABLE IV.G.4-10 A

. P RESENT V ALUE OF N ET B ENEFITS ($ B ) UNDER P ROPOSED

S TANDARDS U SING 3 P ERCENT D ISCOUNT R ATE

– MY S 2017-2021
Earlier MY 2017 MY 2018 MY 2019 MY 2020 MY 2021
PC 6 4 9 14 18 21
LT 1 1 5 10 14 19 Combined 7 5 14 24 32 40

753 For tables that report total or net benefits using a 7 percent discount rate, future benefits from reducing carbon dioxide emissions are discounted at 3 percent in order to main tain consistency with the discount rate used to develop the reference case estimate of the soci al cost of carbon. All other future benefits reported in these tables are discounted using the 7 percent rate.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 692 of 768 T ABLE IV.G.4-10 B

. P RESENT V ALUE OF N ET B ENEFITS ($ B ) UNDER P ROPOSED S TANDARDS U SING 3 P ERCENT D ISCOUNT R ATE

– MY S 2022-2025 ( AND TOTAL THROUGH MY 2025)
MY 2022 MY 2023 MY 2024 MY 2025 Total
PC 24 26 30 35 188
LT 22 24 26 29 151 Combined 46 50 56 63 338

As indicated previously, when fuel savings and other future benefits resulting from the proposed standards are discounted at the 7 percent rate prescribed in OMB guidance, they are $93 billion lower than when the 3 percent discount rate is applied. Because technology costs are not subject to discounting, using the higher 7 pe rcent discount rate reduces net benefits by exactly this same amount. Nevertheless, Tables IV.G.4–11a and 11b show that the net benefits from requiring passenger cars and light trucks to achieve higher fuel economy are still substantial even when future benefits ar e discounted at the higher ra te, totaling $246 billion over MYs 2017–25. Net benefits are thus about 28 percent lower when future benefits are discounted at a 7 percent annual rate than at a 3 percent rate.

T ABLE IV.G.4-11 A

. P RESENT V ALUE OF N ET B ENEFITS ($ B ) UNDER P ROPOSED

S TANDARDS U SING 7 P ERCENT D ISCOUNT R ATE

– MY S 2017-2021
Earlier MY 2017 MY 2018 MY 2019 MY 2020 MY 2021
PC 5 3 7 10 13 15
LT 0 1 4 8 10 14 Combined 5 4 10 18 23 29

T ABLE IV.G.4-11 B

. P RESENT V ALUE OF N ET B ENEFITS ($ B ) UNDER P ROPOSED S TANDARDS U SING 7 P ERCENT D ISCOUNT R ATE

– MY S 2022-2025 ( AND TOTAL THROUGH MY 2025)
MY 2022 MY 2023 MY 2024 MY 2025 Total
PC 17 19 21 24 133
LT 16 18 19 21 113 Combined 34 36 40 46 246

NHTSA’s estimates of economic benefits from establishing higher CAFE standards are subject to considerable uncertainty. Most important, the agency’s estimates of the fuel savings likely to result from adopting higher CAFE standards depend critically on the accuracy of the estimated fuel economy levels that will be achieved under both the baseline scenario, which assumes that manufacturers will continue to co mply with the MY 2016 CAFE standards, and under alternative increases in the standards that apply to MYs 2017–25 passenger cars and light trucks. Specifically, if the agency has underestimated the fuel economy levels that manufacturers would have achieved under the baseline scenario—or is too optimistic about the fuel economy levels that manufacturers will act ually achieve under the proposed standards—its estimates of fuel savings and the resulting economic benefits attributable to this rule will be too large.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 693 of 768 Another major source of potential overestimatio n in the agency’s estimates of benefits from requiring higher fuel economy stems from its reliance on the Reference Case fuel price forecasts reported in AEO 2011. Although NHTSA believes that these forecasts are the most reliable that are available, they are nevertheless significantly higher than the fuel price projections reported in most previous editions of EIA’s Annual Energy Outlook, and reflect projections of world oil prices that are well above forecasts issued by other firms and government agencies. If the future fuel prices projected in AEO 2011 prove to be too high, the agency’s estimates of the value of future fuel savings—the major component of benefits from this rule—will also be too high.

However, it is also possible that NHTSA’s estimates of economic benefits from establishing higher CAFE standards under estimate the true economic benefits of the fuel savings those standards would produce. If the AEO 2011 forecast of fuel prices proves to be too low, for example, NHTSA will have undere stimated the value of fuel sa vings that will result from adopting higher CAFE standards for MY 2017–25. As another example, the agency’s estimate of benefits from reducing the threat of economic damages from disruptions in the supply of imported petroleum to the U.S. applies to calendar year 2020. If the magnitude of this estimate would be expected to grow after 2015 in response to increases in U.S. petroleum imports, growth in the level of U.S. economic activity, or increases in the likelihood of disruptions in the supply of imported petroleum, the agency may have underestimated the benefits from the reduction in petroleum imports expected to result from adopting higher CAFE standards.

NHTSA’s benefit estimates could also be too low because they exclude or understate the economic value of certain potentially significant categories of benefits from reducing fuel consumption. As one example, EPA’s estimates of the economic value of reduced damages to human health resulting from lower exposure to criteria air pollutants includes only the effects of reducing population exposure to PM 2.5 emissions. Although this is likely to be the most significant component of health benefits from redu ced emissions of criteria air pollutants, it excludes the value of reduced damages to human health and other impacts resulting from lower emissions and reduced population exposure to other criteria air pollutants, including ozone and nitrous oxide (N 2 O), as well as to airborne toxics. EPA’s estimates exclude these benefits because no reliable dollar-per-ton estimates of the health impacts of criteria pollutants other than
PM 2.5 or of the health impacts of airborne toxics were available to use in developing estimates of these benefits.

Similarly, the agency’s estimate of the value of reduced climate-related economic damages from lower emissions of GHGs excludes many sources of potential benefits from reducing the pace and extent of global climate change. 754 For example, none of the three models used to value climate-related economic damages includes those resulting from ocean acidification or loss of species and wildlife. Th e models also may not adequately capture certain other impacts, including potentially abrupt change s in climate associated with thresholds that

754 Social Cost of Carbon for Regulatory Impac t Analysis Under Executive Order 12866, Interagency Working Group on Social Cost of Carbon, United States Govern ment, February 2010. Available in Docket No. NHTSA–

2009–0059.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 694 of 768 govern climate system responses, interregional inte ractions such as global security impacts of extreme warming, or limited near-term substitutability between damage to natural systems and increased consumption. Including monetized estimates of benefits from reducing the extent of climate change and these associated impacts would increase the agency’s estimates of benefits from adopting higher CAFE standards.

The following tables present itemized costs and benefits for the combined passenger car and light truck fleets for each model year affected by the proposed standards and for all model years combined, using both discount rates prescribed by OMB regulatory guidance. Tables IV.G.4–12a and 12b report technology outlays, each separate component of benefits (including costs associated with additional driving due to the rebound effect, labeled “dis-benefits”), the total value of benefits, and net benefits using the 3 percent discount rate. (Numbers in parentheses represent negative values.)

T ABLE IV.G.4-12 A

. P RESENT V ALUE OF N ET B ENEFITS ($ B ) UNDER P ROPOSED

S TANDARDS U SING 3 P ERCENT D ISCOUNT R ATE

– MY S 2017-2021
Earlier MY 2017 MY 2018 MY 2019 MY 2020 MY 2021
Costs Technology costs 3.9 2.6 5.8 8.9 12.8 17.5
Benefits Savings in lifetime fuel expenditures 9.8 6.8 16.8 28.0 37.7 49.0

Consumer surplus from additional driving 0.0 0.0 0.1 0.3 0.4 0.6

Value of savings in refueling time 0.5 0.4 0.7 1.0 1.4 1.9

Reduction in petroleum market externalities 0.5 0.4 0.9 1.5 2.0 2.6

Reduction in climate-related damages from lower CO 2 emissions 755 1.0 0.7 1.8 3.0 4.0 5.3

Reduction in highway fatalities from changes in vehicle mass (0.6) (0.0) 0.0 (0.1) (0.1) (0.1)

Reduction in health damage costs from

755 Using the central value of $22 per metric ton for the SCC, and discounting future benefits from reduced CO 2 emissions at a 3 percent annual rate. Additionally, we not e that the $22 per metric ton value for the SCC applies to calendar year 2010, and increases over time. See the interagency guidance on SCC for more information.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 695 of 768 lower emissions of criteria air pollutants:
CO - - - - - -
VOC 0.0 0.0 0.0 0.0 0.1 0.1
NO X 0.0 0.0 0.0 0.0 0.1 0.1

PM 0.2 0.1 0.3 0.5 0.7 0.9
SO X 0.1 0.1 0.3 0.4 0.6 0.7
Dis-benefits from increased driving: Congestion costs (0.6) (0.4) (0.8) (1.2) (1.7) (2.2) Noise costs (0.0) (0.0) (0.0) (0.0) (0.0) (0) Crash costs (0.3) (0.2) (0.4) (0.6) (0.8) (1.0) Total benefits 11.0 7.9 19.7 33.0 44.4 57.9 Net benefits 6.7 5.3 13.9 23.9 31.6 40.4

T ABLE IV.G.4-12 B

. P RESENT V ALUE OF N ET B ENEFITS ($ B ) UNDER P ROPOSED S TANDARDS U SING 3 P ERCENT D ISCOUNT R ATE

– MY S 2022-2025 AND T OTAL FOR A LL MY S MY 2022 MY 2023 MY 2024 MY 2025 Total
Costs Technology costs 20.1 24.3 21.8 29.6 158
Benefits Savings in lifetime fuel expenditures 56.1 63.1 72.2 80.5 420

Consumer surplus from additional driving 0.7 0.9 1.1 1.3 5.6

Value of savings in refueling time 2.1 2.3 2.7 2.7 15.7

Reduction in petroleum market externalities 2.9 3.2 3.7 4.1 21.7

Reduction in climaterelated damages from lower CO 2 emissions 6.1 7.0 8.1 9.1 46.0

Reduction in highway fatalities from changes in vehicle mass (0.0) (0.0) (0.0) (0.0) (0.4)

Reduction in health damage costs from lower emissions of criteria air pollutants:
CO - - - - -
VOC 0.1 0.1 0.1 0.1 0.6
NO X 0.1 0.1 0.1 0.1 0.7

PM 1.0 1.2 1.3 1.5 7.7
SO X 0.8 0.9 0.9 1.0 5.8DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 696 of 768 Dis-benefits from increased driving: Congestion costs (2.5) (2.7) (3.2) (3.4) (18.6) Noise costs (0.1) (0.1) (0.1) (0.1) (0.4) Crash costs (1.2) (1.3) (1.5) (1.6) (8.7) Total benefits 66.1 74.4 85.4 95.3 495.7
Net benefits 46.0 50.4 63.6 65.7 337.7

Similarly, Tables IV.G.4–13a and 13b below report technology outlays, the individual components of benefits (including “dis-benefits” resulting from addition al driving) and their total, and net benefits, using the 7 percent discount rate. (Again, numbers in parentheses represent negative values.)

T ABLE IV.G.4-13 A

. P RESENT V ALUE OF N ET B ENEFITS ($ B ) UNDER P ROPOSED

S TANDARDS U SING 7 P ERCENT D ISCOUNT R ATE

– MY S 2017-2021
Earlier MY 2017 MY 2018 MY 2019 MY 2020 MY 2021
Costs Technology costs 3.9 2.6 5.8 8.9 12.8 17.5
Benefits Savings in lifetime fuel expenditures 7.8 5.4 13.3 22.2 29.9 38.9

Consumer surplus from additional driving 0.0 0.0 0.1 0.2 0.3 0.5

Value of savings in refueling time 0.4 0.3 0.6 0.8 1.1 1.5

Reduction in petroleum market externalities 0.4 0.3 0.7 1.2 1.6 2.0

Reduction in climate-related damages from lower CO 2 emissions 756 1.0 0.7 1.8 2.9 4.0 5.3

Reduction in highway fatalities from changes in vehicle mass (0.1) (0.0) 0.0 (0.1) (0.0) (0.1)

Reduction in health damage costs from lower emissions of criteria air

756 Using the central value of $22 per metric ton for the SCC, and discounting future benefits from reduced CO 2 emissions at a 3 percent annual rate. Additionally, we not e that the $22 per metric ton value for the SCC applies to calendar year 2010, and increases over time. See the interagency guidance on SCC for more information.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 697 of 768 pollutants:
CO - - - - - -
VOC 0.0 0.0 0.0 0.0 0.0 0.1
NO X 0.0 0.0 0.0 0.0 0.1 0.1

PM 0.1 0.1 0.2 0.4 0.6 0.7
SO X 0.1 0.1 0.2 0.3 0.5 0.6 Dis-benefits from increased driving: Congestion costs (0.4) (0.3) (0.6) (1.0) (1.3) (1.8) Noise costs (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) Crash costs (0.2) (0.1) (0.3) (0.5) (0.6) (0.8) Total benefits 9.1 6.5 16.0 26.4 36.2 47.0 Net benefits 5.2 3.9 10.2 17.5 23.4 29.5

T ABLE IV.G.4-13 B

. P RESENT V ALUE OF N ET B ENEFITS ($ B ) UNDER P ROPOSED S TANDARDS U SING 7 P ERCENT D ISCOUNT R ATE

– MY S 2022-2025 AND T OTAL FOR A LL MY S MY 2022 MY 2023 MY 2024 MY 2025 Total
Costs Technology costs 20.1 24.2 29.6 32.1 158.0
Benefits Savings in lifetime fuel expenditures 44.5 50.1 57.5 64.1 333.5

Consumer surplus from additional driving 0.6 0.7 0.9 1.0 4.4

Value of savings in refueling time 1.7 1.8 2.2 2.2 12.6

Reduction in petroleum market externalities 2.3 2.6 3.0 3.3 17.4

Reduction in climaterelated damages from lower CO 2 emissions 6.1 7.0 8.1 9.1 45.9

Reduction in highway fatalities from changes in vehicle mass (0.0) (0.0) (0.0) (0.0) (0.4)

Reduction in health damage costs from lower emissions of criteria air pollutants:
CO - - - - -
VOC 0.1 0.1 0.1 0.1 0.5
NO X 0.1 0.1 0.1 0.1 0.6

PM 0.8 0.9 1.0 1.2 6.2
SO X 0.6 0.7 0.7 0.8 4.6 Dis-benefits from increased driving:DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 698 of 768 Congestion costs (2.0) (2.2) (2.5) (2.7) (14.9) Noise costs (0.0) (0.0) (0.0) (0.0) (0.3) Crash costs (0.9) (1.0) (1.2) (1.3) (7.0) Total benefits 53.9 60.8 69.9 77.9 403.1 Net benefits 33.8 36.6 40.3 45.8 245.1

These benefit and cost estimates do not re flect the availability and use of certain flexibility mechanisms, such as compliance credits and credit trading, because EPCA prohibits NHTSA from considering the effect s of those mechanisms in settin g CAFE standards. However, the agency noted that, in reality, manufacturers were likely to rely to some extent on flexibility mechanisms and would thereby reduce the cost of complying with the proposed standards to a meaningful extent.

As discussed in the PRIA, NHTSA has performed an analysis to estimate costs and benefits taking into account EPCA’s provisions regarding EVs, PHEVs produced before MY 2020, FFV credits, and other CAFE credit provisions. Accounting for these provisions indicates that achieved fuel economies would be 0.5–1.6 mpg lower than when these provisions are not considered (for comparison, see Table IV.G.1–2 above):

T ABLE IV.G.4-14 A

. A VERAGE A CHIEVED F UEL E CONOMY ( MPG ) UNDER P ROPOSED S TANDARDS

– MY S 2017-2021 ( WITH EPCA AFV AND CREDIT PROVISIONS )
MY 2017 MY 2018 MY 2019 MY 2020 MY 2021 Passenger cars 38.8 40.5 42.6 44.5 46.1 Light trucks 29.0 30.1 31.9 33.1 35.0 Combined 34.5 36.0 38.0 39.7 41.5

T ABLE IV.G.4-14 B

. A VERAGE A CHIEVED F UEL E CONOMY ( MPG ) UNDER P ROPOSED S TANDARDS

– MY S 2022-2025 ( WITH EPCA AFV AND CREDIT PROVISIONS )
MY 2022 MY 2023 MY 2024 MY 2025 Passenger cars 47.2 48.9 50.5 52.8 Light trucks 35.7 36.7 37.6 38.3 Combined 42.5 43.9 45.3 46.9

As a result, NHTSA estimates that, when EPCA AFV and credit provisions are taken into account, fuel savings will total 153 billion gallons—5.6 percent less than the 161.0 billion gallons estimated when these flexibilities are not considered:

T ABLE IV.G.4-15 A

. F UEL S AVED ( BILLION GALLONS ) UNDER P ROPOSED S TANDARDS

– MY S 2017-2021 ( WITH EPCA AFV AND CREDIT PROVISIONS )
Earlier MY 2017 MY 2018 MY 2019 MY 2020 MY 2021
PC 3 2 4 6 8 10
LT 0 1 2 4 6 8 Combined 4 3 6 10 14 18DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 699 of 768 T ABLE IV.G.4-15 B

. F UEL S AVED ( BILLION GALLONS ) UNDER P ROPOSED S TANDARDS

– MY S 2022-2025 ( WITH EPCA AFV AND CREDIT PROVISIONS )
MY 2022 MY 2023 MY 2024 MY 2025 Total
PC 11 14 16 19 94
LT 8 9 10 11 59 Combined 20 23 26 30 153

The agency similarly estimates CO 2 emissions reductions will total 1,833 million metric tons (mmt), 8.0 percent less than the 1,993 mmt estimated when these EPCA provisions are not considered: 757

T ABLE IV.G.4-16 A

. A VOIDED C ARBON D IOXIDE E MISSIONS ( MMT ) UNDER P ROPOSED S TANDARDS

– MY S 2017-2021 ( WITH EPCA AFV AND CREDIT PROVISIONS )
Earlier MY 2017 MY 2018 MY 2019 MY 2020 MY 2021
PC 39 23 42 69 93 130
LT 6 7 20 44 60 84 Combined 45 30 62 113 153 215

T ABLE IV.G.4-16 B

. A VOIDED C ARBON D IOXIDE E MISSIONS ( MMT ) UNDER P ROPOSED S TANDARDS

– MY S 2022-2025 ( WITH EPCA AFV AND CREDIT PROVISIONS )
MY 2022 MY 2023 MY 2024 MY 2025 Total PC 150 183 217 258 1,205
LT 94 106 115 123 659 Combined 245 289 332 381 1,864

This analysis further indicates that signi ficant reductions in outlays for additional technology will result when EPCA’s AFV and credit provisions are taken into account. Tables IV.G.4–17a and 17b below show that, total technology costs are estimated to decline to $138 billion as a result of manufacturers’ use of thes e provisions, or about 14 percent less than the $161 billion estimated when excluding these flexibilities:

T ABLE IV.G.4-17 A

. I NCREMENTAL T ECHNOLOGY O UTLAYS ($ BILLION ) UNDER P ROPOSED S TANDARDS

– MY S 2017-2021 ( WITH EPCA AFV AND CREDIT PROVISIONS )
Earlier MY 2017 MY 2018 MY 2019 MY 2020 MY 2021
PC 1 2 3 6 8 11
LT 0 0 1 2 3 5 Combined 2 2 4 8 11 15

T ABLE IV.G.4-17 B

. I NCREMENTAL T ECHNOLOGY O UTLAYS ($ BILLION ) UNDER P ROPOSED S TANDARDS

– MY S 2022-2025 ( WITH EPCA AFV AND CREDIT PROVISIONS )

757 Differences in the application of diesel engines and plug -in hybrid electric vehicles lead to differences in the percentage changes in fuel consumption and carbon dioxid e emissions between the with- and without-credit cases.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 700 of 768 MY 2022 MY 2023 MY 2024 MY 2025 Total
PC 12 16 19 22 100
LT 5 6 7 7 37 Combined 17 22 26 29 138

Because NHTSA’s analysis indicated that th ese EPCA provisions will modestly reduce fuel savings and related benefits, the agency’s es timate of the present value of total benefits will be $471 billion when discounted at a 3 percent a nnual rate, as Tables IV.G.4–18a and 18b below report. This estimate of total benefits is $30 bill ion, or 6.0 percent, lower than the $497 billion reported previously for the analysis that excluded these provisions:

T ABLE IV.G.4-18 A

. P RESENT V ALUE OF B ENEFITS ($ BILLION ) UNDER P ROPOSED S TANDARDS U SING A 3 P ERCENT D ISCOUNT R ATE

– MY S 2017-2021 ( WITH EPCA AFV AND

CREDIT PROVISIONS )
Earlier MY 2017 MY 2018 MY 2019 MY 2020 MY 2021
PC 10 6 11 18 25 31
LT 1 2 5 12 17 23 Combined 11 8 17 31 42 54

T ABLE IV.G.4-18 B

. P RESENT V ALUE OF B ENEFITS ($ BILLION ) UNDER P ROPOSED S TANDARDS U SING A 3 P ERCENT D ISCOUNT R ATE

– MY S 2022-2025 ( WITH EPCA AFV AND

CREDIT PROVISIONS )
MY 2022 MY 2023 MY 2024 MY 2025 Total
PC 35 42 49 58 287
LT 26 29 32 35 184 Combined 61 72 82 93 471

Similarly, NHTSA estimates that the present value of total benefits will decline modestly from its previous estimate when future fuel savings and other benefits are discounted at the higher 7 percent rate. Tables IV.G.4–19a and 19b report that the present value of benefits from requiring higher fuel economy for MY 2017–25 cars and light truc ks will total $383 billion when discounted using a 7 percent rate, about $24 billion (5.9 percent) below the previous $404 billion estimate of total benefits when FFV credits were not permitted:

T ABLE IV.G.4-19 A

. P RESENT V ALUE OF B ENEFITS ($ BILLION ) UNDER P ROPOSED S TANDARDS U SING A 7 P ERCENT D ISCOUNT R ATE

– MY S 2017-2021 ( WITH EPCA AFV AND

CREDIT PROVISIONS )
Earlier MY 2017 MY 2018 MY 2019 MY 2020 MY 2021
PC 8 5 9 15 20 25
LT 0 1 4 10 13 19 Combined 9 7 14 25 34 44

T ABLE IV.G.4-19 B

. P RESENT V ALUE OF B ENEFITS ($ BILLION ) UNDER P ROPOSED S TANDARDS U SING A 7 P ERCENT D ISCOUNT R ATE

– MY S 2022-2025 ( WITH EPCA AFV AND

CREDIT PROVISIONS )DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 701 of 768 MY 2022 MY 2023 MY 2024 MY 2025 Total
PC 29 35 40 48 2235
LT 21 24 26 28 148 Combined 50 58 67 76 383

Although the discounted present value of total benefits will be modestly lower when EPCA AFV and credit provisions are taken into account, the agency estimates that these provisions will reduce net benefits by a smaller proportion. As Tables IV.G.4–20a and 20b show, the agency estimates that these will reduce net benefits from the proposed CAFE standards to $334 billion from the previously-reported estimate of $335 billion without those credits, or by only about 2.1 percent.

T ABLE IV.G.4-20 A

. P RESENT V ALUE OF N ET B ENEFITS ($ BILLION ) UNDER P ROPOSED S TANDARDS U SING A 3 P ERCENT D ISCOUNT R ATE

– MY S 2017-2021 ( WITH EPCA AFV AND

CREDIT PROVISIONS )
Earlier MY 2017 MY 2018 MY 2019 MY 2020 MY 2021
PC 10 5 8 13 17 20
LT 0 1 4 10 14 19 Combined 10 6 13 23 30 39

T ABLE IV.G.4-20 B

. P RESENT V ALUE OF N ET B ENEFITS ($ BILLION ) UNDER P ROPOSED S TANDARDS U SING A 3 P ERCENT D ISCOUNT R ATE

– MY S 2022-2025 ( WITH EPCA AFV AND

CREDIT PROVISIONS )
MY 2022 MY 2023 MY 2024 MY 2025 Total
PC 23 26 30 36 187
LT 21 23 26 28 147 Combined 44 50 56 64 334

Similarly, Tables IV.G.4–21a and 21b immediately below show that NHTSA estimates manufacturers’ use of EPCA AFV and credit provi sions will reduce net benefits from requiring higher fuel economy for MY 2017–25 cars and light trucks only very slightly—to $241 billion— if a 7 percent discount rate is applied to future benefits. This estimate is $1 billion—or 0.4 percent—lower than the previously-reported $242 billion estimate of net benefits without the availability of EPCA AFV and credit provisions using that same discount rate.

T ABLE IV.G.4-21 A

. P RESENT V ALUE OF N ET B ENEFITS ($ BILLION ) UNDER P ROPOSED S TANDARDS U SING A 7 P ERCENT D ISCOUNT R ATE

– MY S 2017-2021 ( WITH EPCA AFV and credit provisions)
Earlier MY 2017 MY 2018 MY 2019 MY 2020 MY 2021
PC 7 3 6 10 12 15
LT 1 1 3 8 10 14 Combined 8 5 9 17 23 29DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 702 of 768 T ABLE IV.G.4-21 B

. P RESENT V ALUE OF N ET B ENEFITS ($ BILLION ) UNDER P ROPOSED S TANDARDS U SING A 7 P ERCENT D ISCOUNT R ATE

– MY S 2022-2025 ( WITH EPCA AFV and credit provisions)
MY 2022 MY 2023 MY 2024 MY 2025 Total
PC 17 19 21 26 135
LT 16 18 19 21 111 Combined 32 36 41 47 246

The agency has performed several sensitivity analyses to examine important assumptions. We examine sensitivity with respect to the following economic parameters:

1) The price of gasoline: The main analysis ( i.e. , the Reference Case) uses the AEO 2011 Reference Case estimate for the price of gasoline. In this se nsitivity analysis we examine the effect of using the AEO 2011 High Price Case or Low Price Case forecast estimates instead.

2) The rebound effect: The main analysis uses a rebound effect of 10 percent to project increased miles traveled as the cost per mile driven decreases. In the sensitivity analysis, we examine the effect of using a 5, 15, or 20 percent rebound effect instead.

3) The value of CO 2 benefits: The main analysis uses $22.00 per ton discounted at a 3 percent discount rate to quantify the benefits of reducing CO 2 emissions and $0.174 per gallon to quantify the benefits of reducing fuel consumption. In the sensitivity analysis, we examine the following values and discount rates applied only to the social cost of carbon to value carbon benefits, considering low, high, and very high valuations of approximately $5, $36, and $67 per ton, respectively with regard to the benefits of reducing CO 2 emissions. 758 These are the 2010 values, which increase over time. These values can be translated into cents per gallon by multiplying by 0.0089, 759 giving the following values:

($4.86 per ton CO 2 ) x 0.0089 = $0.043 per gallon discounted at 5% ($22.00 per ton CO 2 ) x 0.0089 = $0.196 per gallon discounted at 3% (used in the main analysis) ($36.13 per ton CO 2 ) x 0.0089 = $0.322 per gallon discounted at 2.5% And a 95 th percentile estimate of ($66.88 per ton CO 2 ) x 0.0089 = $0.595 per gallon discounted at 3%

4) Military security: The main analysis does not assign a value to the military security benefits of reducing fuel consumption. In th e sensitivity analysis, we examine the impact of using a value of 12 cents per gallon instead.

758 The low, high, and very high valuations of $5, $36, and $67 are rounded for brevity; the exact values are $4.86, $36.13, and $66.88, respectively.
759 The molecular weight of Carbon (C) is 12, the molecular weight of Oxygen (O) is 16, thus the molecular weight

of CO 2 is 44. 1 gallon of gas weighs 2,819 grams, of that 2,433 grams are carbon. One ton of CO 2 /One ton of C (44/12)* 2433grams C/gallon *1 ton/1000kg * 1 kg/1000g = (44 * 2433*1*1) / (12*1*1000 * 1000) = 0.0089. Thus, one ton of CO 2 *0.0089 = 1 gallon of gasoline.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 703 of 768 5) Consumer Benefit: The main analysis assumes there is no loss in consumer surplus with vehicles that have an increase in price and higher fuel economy. This sensitivity analysis assumes that there is a 25, or 50 percent lo ss in consumer surplus – equivalent to the assumption that consumers will only value the calculated benefits they will achieve at 75, or 50 percent, respectively, of their main analysis estimates.

6) Battery cost: The agency conduc ted a sensitivity analysis of ba ttery costs in relation to HEV, PHEV, and EV batteries. For HEV batt eries, sensitivity analysis was performed with a +/- 10 percent variation in cost pe r kWh, while sensitivity analyses involving PHEV and EV batteries utilized alternate ranges contingent on the type of battery cathode (see chapter X for additional detail). PHEV and EV battery costs ranged between -20 percent and +35 percent in this sensitivity analysis.

7) Mass reduction cost: A sensitivity analysis was performed examin ing the impact of vehicle mass reduction that could feasibly be accomplished with a +/- 40 percent impact on vehicle cost.

8) Market-driven baseline: The baseline for the central analysis is based on the MY 2016 CAFE standards and assumes that manufact urers will make no changes in the fuel economy from that level through MY 2025. A sensitivity analysis was performed to simulate potential increases in fuel economy over the compliance level required if MY 2016 standards were to remain in place. Th e assumption is that the market would drive manufacturers to put technologies into their vehicles that they believe consumers would value and be willing to pay for. Using pa rameter values consistent with the central analysis, the agency simulated the market-driven baseline by applying a payback period of one year for purposes of calculating the value of future fuel savings when simulating whether manufacturers would apply additional technology to an already CAFE-compliant fleet. In other words we assumed that manufacturers that were above their MY 2016 CAFE level would compare the cost to consumers to the fuel savings in the first year of operation and decide to voluntarily apply those technologies to their vehicles when benefits for the first year exceeded costs for the consumer. For a manufacturer’s fleet that that has not yet achieved compliance with CAFE standards, the agency continued to apply a five-year payback period. In other wo rds, for this sensitivity analysis the agency assumed that manufacturers that have not ye t met CAFE standards for future model years will apply technology as if buyers were willi ng to pay for the technologies as long as the fuel savings throughout the first five years of vehicle ownership exceeded their costs. Once having complied with those standards, however, manufacturers are assumed to consider making further improvements in fuel economy as if buyers were only willing to pay for fuel savings to be realized during the first year of vehicle ownership.

9) [Cost reduction based on learning: A sensitivity analysis will be performed on the cost impact should increased manufacturing volume of proposed fuel economy related technologies lead to a decrease in manufacturers’ per-item costs. This sensitivity analysis will look at both high and low learning rates.]DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 704 of 768 Varying each of these four parameters in isolation results in 9 additional economic scenarios, in addition to the Reference case. These are listed in Table IV.G.4–22 below, together with two additional scenarios that use combinations of these parameters that together produce the lowest and highest benefits.

T ABLE IV.G.4-22. S ENSITIVITY A NALYSES E VALUATED IN NHTSA’ S PRIA

Name Fuel
Price Discount Rate Rebound Effect SCC Military Security

Reference Reference 3% 10% $22 0¢/gal High Fuel Price High 3% 10% $22 0¢/gal
Low Fuel Price Low 3% 10% $22 0¢/gal
5% Rebound Effect Reference 3% 5% $22 0¢/gal
15% Rebound Effect Reference 3% 15% $22 0¢/gal
20% Rebound Effect Reference 3% 20% $22 0¢/gal 12¢/gal Military Security Value Reference 3% 10% $22 12¢/gal
$5/ton CO 2 Value Reference 3% 10% $5 0¢/ g al
$36/ton CO 2 Value Reference 3% 10% $36 0¢/gal
$67/ton CO 2 Value Reference 3% 10% $67 0¢/gal
50% Consumer Benefit Reference 3% 10% $22 0¢/gal

75% Consumer Benefit Reference 3% 10% $22 0¢/gal Low Battery Cost Reference 3% 10% $22 0¢/gal High Battery Cost Reference 3% 10% $22 0¢/gal
Low Mass Reduction Reference 3% 10% $22 0¢/gal High Mass Reduction Reference 3% 10% $22 0¢/gal Market-Driven Baseline Reference 3% 10% $22 0¢/gal Low Learning Rate Reference 3% 10% $22 0¢/gal High Learning Rate Reference 3% 10% $22 0¢/gal

The basic results of this sensitivity analysis are contained in Chapter X of the PRIA, but several selected findings are as follows:

1) Varying the economic assumptions has almost no impact on achieved mpg. High mass reduction cost and a market-based baseline are the only parameters that impact achieved mpg. None of these alter the outcome by more than 0.1 mpg for either fleet. 2) Varying the economic assumptions has, at most, a small impact on per-vehicle costs, fuel saved, and CO 2 emissions reductions, with none of the variations impacting the outcomes by more than 10 percent from their central analysis levels with the exception being the sensitivity involving a 20 percent rebound effect. 3) The largest change resulting from varying eco nomic parameters is on net benefits. Changing the fuel price forecast to the AEO 2011 High Price Case forecast impacts netDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 705 of 768 benefits by a combined +43.3%, while the AEO 2011 Low Price Case forecast reduces net benefits by -48.8%. Other large impacts on net benefits occurred with the 20 percent rebound effect (-31.2%), valuing benefits at 50 and 75 percent (-61.8% and -30.9%, respectively), and valuing the reduction in CO 2 emissions at $67/ton (+27.9%). 4) Even if consumers value the benefits achieved at 50% of the main analysis assumptions, total benefits still exceed costs.

Regarding the lower fuel savings and CO 2 emissions reductions predicted by the sensitivity analysis as fuel price increases, wh ich initially may seem counterintuitive, we note that there are some counterbalancing factors occurri ng. As fuel price increases, people will drive less and so fuel savings and CO 2 emissions reductions may decrease.

In addition, the agency analyzed the impact that having a retail price equivalent (RPE) factor of 1.5 for all technologies would have on the various alternatives instead of using the indirect cost methodology (ICM) resulting in an overall price increase multiplier from variable cost of 1.2 to 1.25, with special attention be ing paid to the preferred alternative and the maximum net benefit alternative. Table IV.G.4 -23a shows the impact on the MY 2025 achieved mpg level for passenger cars and light trucks by changing the cost markup factors used in the Volpe model. Having a higher cost for tec hnologies limits how many technologies are cost effective. Table IV.G.4-23b shows the impact on the MY 2025 achieved mpg level for passenger cars and light trucks if NAS cost es timates are used in conjunction with the ICM method in place of the cost estimates used in the main analysis. Table IV.G.4-24 shows the impact on per-vehicle technology cost, total ne t benefits, total fuel savings, and total CO 2 reduction for the preferred alternative compari ng the preferred alternative using the ICM method with main analysis cost estimates to the RPE method, as well as the ICM method using main analysis cost estimates to the ICM method using NAS cost estimates.

T ABLE IV.G.4-23 A

. A CHIEVED MPG L EVEL , MY 2025, C OMPARING D IFFERENT C OST M ARK

- UP M ETHODOLOGIES (3% D ISCOUNT R ATE )

ICM Method (Main Analysis

Costs) RPE Method (Main Analysis

Costs) Difference (mpg) Passenger Cars

Preferred Alternative 52.6 52.3 -0.3

Max Net Benefits 49.6 48.9 -0.7 Light trucks

Preferred Alternative 39.5 39.4 -0.1

Max Net Benefits 44.1 43.6 -0.5

T ABLE IV.G.4-23 B

. A CHIEVED MPG LEVEL , MY 2025, C OMPARING ICM M ETHOD WITH M AIN A NALYSIS C OSTS VS

. NAS C OSTS (3% D ISCOUNT R ATE )DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 706 of 768 ICM Method (Main Analysis

Costs) ICM Method (NAS Cost Estimates) Difference (mpg) Passenger Cars

Preferred Alternative 52.6 52.2 -0.4

Max Net Benefits 49.6 48.7 0.9 Light trucks

Preferred Alternative 39.5 39.0 -0.5

Max Net Benefits 44.1 43.5 -0.6

T ABLE IV.G.4-24. S ENSITIVITY A NALYSES (A CHIEVED MPG , P ER -V EHICLE C OST , N ET B ENEFITS , F UEL S AVED , & CO 2 E MISSIONS R EDUCED )

Cost Method and Set of Cost Estimates MY 2025 Achieved
mpg Average
MY 2025 Per-Vehicle Technology Cost MY 2017- 2025 Net Benefits, Discounted 3%, in Billions of $ MY 2017- 2025 Fuel Saved, in Billions of Gallons MY 2017- 2025 CO2 Emissions Reduced,
in mmT Passenger Cars ICM w/Main Analysis
Costs 52.6 $2,170 $181 95 1,193 RPE w/Main Analysis
Costs 52.3 $2,665 $160 95 1,215

ICM w/NAS Costs 52.2 $2,989 $142 96 1,228 Light trucks ICM w/Main Analysis
Costs 39.5 $1,585 $149 62 753 RPE w/Main Analysis
Costs 39.4 $2,056 $136 62 799

ICM w/NAS Costs 39.0 $2,455 $124 60 660

For today’s rulemaking analysis, the agency has also performed a sensitivity analysis where manufacturers are allowed to voluntarily apply more technology than would be required to comply with CAFE standards for each model year. Manufacturers are assumed to do so as long as applying each additional technology woul d increase vehicle prod uction costs (including markup) by less than it would reduce buyers’ fuel costs during the first year they own the vehicle. This analysis makes use of the “voluntary overcompliance” simulation capability DOT has recently added to its CAFE model. This capability, which is discussed further above in section IV.C.4.c and in the CAFE model documentation, is a logical extension of the model’sDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 707 of 768 simulation of some manufacturers’ decisions to respond to EPCA by paying civil penalties once additional technology becomes economically unattractive. It attempts to simulate manufacturers’ responses to buyers’ demands fo r higher fuel economy levels than prevailing CAFE standards would require when fuel costs are sufficiently high, and technologies that manufacturers have not yet fully utilized are available to improve fuel economy at relatively low

costs.

NHTSA performed this analysis because some stakeholders commenting on the recentlypromulgated standards for medium- and heavy- duty vehicles indicated that it would be unrealistic for the agency to assume that in the absence of new regulations, technology and fuel economy would not improve at all in the future. In other words, these stakeholders argued that market forces are likely to result in some fuel economy improvements over time, as potential vehicle buyers and manufacturers respond to changes in fuel prices and in the availability and costs of technologies to increase fuel economy. NHTSA agrees that, in principle, its analysis should estimate a potential that manufacturer s will apply technology as if buyers place some value on fuel economy improvements. Considering current uncertainties discussed below regarding the degree to which manufacturers will do so, the agency currently judges it appropriate to conduct its central rulemaking an alysis without attemptin g to simulate these effects. Nonetheless, the agency believes that voluntary overcompliance is sufficiently plausible that corresponding sensitivity analysis is warranted.

NHTSA performed this analysis by simulating potential overcompliance under the noaction alternative, the preferred alternative, and other regulatory alternatives. In doing so, the agency used all the same parameter values as in the agency’s central analysis, but applied a payback period of one year for purposes of calculating the value of future fuel savings whensimulating whether a manufacturer would apply additional technology to an already CAFEcompliant fleet. For technologies applied to a manufacturer’s fleet that has not yet achieved compliance with CAFE standards, the agency continued to apply a five-year payback period.

In other words, for this sensitivity analysis the agency assumed that manufacturers that have not yet met CAFE standards for future model years will apply technology as if buyers were willing to pay for fuel savings throughout the fi rst five years of vehicle ownership. Once having complied with those standards, however, manufacturers are assumed to consider making further improvements in fuel economy as if buyers were only willing to pay for fuel savings to be realized during the first year of vehicle owners hip. This reflects the agency’s assumptions for this sensitivity analysis, that (1) civil penalties, though legally available, carry a stigma that manufacturers will strive to avoid, and that (2) having achieved compliance with CAFE standards, manufacturers will avoid competitive risks entailed in charging higher prices for vehicles that offer additional fuel economy, rather than offering additional performance or utility.

Since CAFE standards were first introduced, some manufacturers have consistently exceeded those standards, and the industry as a whole has consistently overcomplied with both the passenger car and light truck standards. Although the combined average fuel economy of cars and light trucks declined in some years, this resulted from buyers shifting their purchases from passenger cars to light trucks, not from underc ompliance with either standard. Even with those declines, the industry still overcomplied with both passenger car and light truck standards.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 708 of 768 In recent years, between MYs 1999 and 2009, fuel economy overcompliance has been increasing on average for both the passenger car and the light truck fleets. NHTSA considers it impossible to say with certainty why past fuel economy levels have followed their observed path . If the agency could say with certainty how fuel economy would have changed in the absence of CAFE standards, it might be able to answer th is question; however, NHTSA regards this “counterfactual” case as simply unknowable.

NHTSA has, however, considered other releva nt indications regarding manufacturers’ potential future decisions. Published research regarding how vehicle buyers have previously viewed fuel economy suggests that they have only a weak quantitative understanding of the relationship between fuel economy and future fuel outlays, and that potential buyers value fuel economy improvements by less than theoretical present-value calculations of lifetime fuel savings would suggest. These findings are genera lly consistent with manufacturers’ confidential and, in some cases, public statements. Manu facturers have tended to communicate not that buyers absolutely “don’t care” about fuel economy, but that buyers have, in the past, not been willing to pay the full cost of most fuel economy improvements. Manufacturers have also tended to indicate that sustained high fuel prices w ould provide a powerful incentive for increased fuel economy; this implies that manufacturers believe buyers are willing to pay for some fuel economy increases, but that buyers ’ willingness to do so depends on their expectations for future fuel prices. In their confidential statements to the agency, manufacturers have also tended to indicate that in their past product planning processes, they have assumed buyers would only be willing to pay for technologies that "break ev en” within a relatively short time—generally the first two to four years of vehicle ownership.

NHTSA considers it not only f easible but appropriate to simulate such effects by calculating the present value of fuel savings over some “payback period.” The agency also believes it is appropriate to assume that specific improvements in fuel economy will be implemented voluntarily if manufacturers’ costs for adding the technology necessary to implement them to specific models would be lower than potential buyers’ willingness to pay for the resulting fuel savings. This approach takes fu el costs directly into account, and is therefore responsive to manufacturers’ statements regarding the role that fuel prices play in influencing buyers’ demands and manufacturers’ planning processes. Under this approach, a short payback period can be employed if manufacturers are expected to act as if buyers place little value on fuel economy. Conversely, a longer payback period can be used if manufacturers are expected to act as if buyers will place comparatively greater value on fuel economy.

NHTSA cannot be certain to what extent vehicl e buyers will, in the future, be willing to pay for fuel economy improvements, or to what extent manufacturers would, in the future, voluntarily apply more technology than needed to comply with fuel economy standards. The agency is similarly hopeful that future vehicl e buyers will be more willing to pay for fuel economy improvements than has historically been the case. In meetings preceding today’s proposed standards, two manufacturers stated they expected fuel economy to increase two percent to three percent per year after MY 2016, absent more stringent regulations. And in August 2010, one manufacturer stated its combined fleet would achieve 50 mpg by MY 2025, supporting that at a minimum some manufact urers believe that exceeding fuel economy standards will provide them a competitive advantage. The agency is hopeful that future vehicleDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 709 of 768 buyers will be better-informed than has historical ly been the case, in part because recentlypromulgated requirements regard ing vehicle labels will provide clearer information regarding fuel economy and the dollar value of resulting fuel savings. The agency is similarly hopeful that future vehicle buyers will be more willing to pay for fuel economy improvements than past buyers. In meetings preceding today’s proposed standards, many manufacturers indicated significant shifts in their product pl ans—shifts consistent with expect ations that compared to past buyers, future buyers will “care more” about fuel economy.

Nevertheless, considering the uncertainties mentioned above, NHTSA continues to consider it appropriate to conduct its central ru lemaking analysis in a manner that ignores the possibility that in the future, manufacturers wi ll voluntarily apply more technology than the minimum necessary to comply with CAFE standard s. Also, in conducting its sensitivity analysis to simulate voluntary overcompliance with the proposed standards, the agency has applied the extremely conservative assumption that when considering whether to employ “extra” technology, manufacturers will act as if buyers’ value the resulting savings in fuel costs only during their first year of ownership ( i.e. , as if a 1-year payback period applies).

Results of the agency’s analysis simulating this potential for voluntary overcompliance are summarized below. Compared to results from the agencies’ central analysis presented above, differences are greatest for the baseline scenario ( i.e. , the No-Action Alternative), under which CAFE standards remain unchanged after MY 2016. These results also suggest, as the agency would expect, that because increasingly stringent standards require progressively more technology than the market will demand, the likelihood of voluntary overcompliance will decline with increasing stringency. Achieved fuel eco nomy levels under baseline standards are as follows:

T ABLE IV.G.4-23 A

. A VERAGE A CHIEVED F UEL E CONOMY ( MPG ) UNDER B ASELINE S TANDARDS

– MY S 2017-2021 ( INCLUDING VOLUNTARY OVERCOMPLIANCE )
MY 2017 MY 2018 MY 2019 MY 2020 MY 2021
PC 37.2 37.6 37.9 38.1 38.2
LT 28.8 29.1 29.3 29.3 29.4 Combined 33.6 34.0 34.3 34.4 34.6

T ABLE IV.G.4-23 B

. A VERAGE A CHIEVED F UEL E CONOMY ( MPG ) UNDER B ASELINE S TANDARDS

– MY S 2022-2025 ( INCLUDING VOLUNTARY OVERCOMPLIANCE )
MY 2022 MY 2023 MY 2024 MY 2025
PC 38.2 38.3 38.4 38.5
LT 29.5 29.7 29.8 30.3 Combined 34.6 34.8 35.0 35.3

With no change in standards after MY 2016, while combined average fuel economy is the same in MY 2017 both with and without simulated voluntary overcompliance, differences grow over time, reaching 0.9 mpg in MY 2025. In other words, without simulating voluntary overcompliance, the agency estimated that combined average achieved fuel economy would reach 35.0 mpg in MY 2025, whereas the agency estimates that it would reach 35.9 mpg in that year if voluntary overcompliance occurred..DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 710 of 768 In contrast, the effect on achieved fuel economy levels of allowing voluntary overcompliance with the proposed standards was minimal. Allowing manufacturers to overcomply with the proposed standards for MY 2025 led to combined average achieved fuel economy levels within 0.1 mpg of levels of values obtained without simulating voluntary overcompliance (see tables IV.G.1-1 AND IV.G.1-2):

T ABLE IV.G.4-24 A

. A VERAGE A CHIEVED F UEL E CONOMY ( MPG ) UNDER P ROPOSED S TANDARDS

– MY S 2017-2021 ( INCLUDING VOLUNTARY OVERCOMPLIANCE )
MY 2017 MY 2018 MY 2019 MY 2020 MY 2021 Passenger cars 38.7 40.7 42.6 44.3 45.8 Light trucks 29.5 30.7 32.6 33.8 35.6 Combined 35.1 36.9 38.9 40.5 42.3

T ABLE IV.G.4-24 B

. A VERAGE A CHIEVED F UEL E CONOMY ( MPG ) UNDER P ROPOSED S TANDARDS

– MY S 2022-2025 ( INCLUDING VOLUNTARY OVERCOMPLIANCE )
MY 2022 MY 2023 MY 2024 MY 2025 Passenger cars 48.3 49.5 51.4 52.8 Light trucks 36.6 37.7 38.6 39.6 Combined 43.5 44.7 46.3 47.6

As a result, NHTSA estimates that, when th e potential for voluntary overcompliance is taken into account, fuel savings attributable to more stringent standards will total 151 billion gallons—5.6 percent less than the 161 billi on gallons estimated when potential voluntary overcompliance is not taken into account,

T ABLE IV.G.4-25 A

. F UEL S AVED ( BILLION GALLONS ) UNDER P ROPOSED S TANDARDS

– MY S 2017-2021 ( INCLUDING VOLUNTARY OVERCOMPLIANCE )
Earlier MY 2017 MY 2018 MY 2019 MY 2020 MY 2021 Passenger cars 3 2 4 6 8 10 Light trucks 0 0 2 4 5 7 Combined 3 3 6 10 14 18

T ABLE IV.G.4-25 B

. F UEL S AVED ( BILLION GALLONS ) UNDER P ROPOSED S TANDARDS

– MY S 2022-2025 ( INCLUDING VOLUNTARY OVERCOMPLIANCE )
MY 2022 MY 2023 MY 2024 MY 2025 Total Passenger cars 12 13 16 18 94 Light trucks 8 9 10 10 57 Combined 20 23 26 28 151

The agency is not projecting, however, that fuel consumption will be greater when voluntary overcompliance is taken into account. Rather, under today’s proposed standards, the agency’s analysis shows virtually identical fuel consumption (0.2 percent less over the useful lives of MY 2017-2025 vehicles) when potential voluntary overcompliance is taken into account. Simulation of voluntary overcompliance, theref ore, does not reduce the agency’s estimate ofDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 711 of 768 future fuel savings. Rather it changes the attr ibution of those fuel savings to the proposed standards, because voluntary overcompliance attributes some of the fuel savings to the market. The same holds for the attribution of costs, other effects, and monetized benefits—inclusion of voluntary overcompliance does not necessarily change their amounts, but it does attribute some of each cost, effect, or benefit to the workings of the market, rather than to the proposed standards.

The agency similarly estimates CO 2 emissions reductions attri butable to today’s proposed standards will total 1,849 million metric tons (mmt), 6.6 percent less than the 1,993 mmt estimated when potential voluntary overcompliance is not taken into account: 760

T ABLE IV.G.4-26 A

. A VOIDED C ARBON D IOXIDE E MISSIONS ( MMT ) UNDER P ROPOSED S TANDARDS

– MY S 2017-2021 ( INCLUDING VOLUNTARY OVERCOMPLIANCE )
Earlier MY 2017 MY 2018 MY 2019 MY 2020 MY 2021 Passenger cars 38 24 54 80 105 126 Light trucks 6 4 19 44 61 84 Combined 43 28 73 124 167 211

T ABLE IV.G.4-26 B

. A VOIDED C ARBON D IOXIDE E MISSIONS ( MMT ) UNDER P ROPOSED S TANDARDS

– MY S 2022-2025 ( INCLUDING VOLUNTARY OVERCOMPLIANCE )
MY 2022 MY 2023 MY 2024 MY 2025 Total Passenger cars 145 174 205 239 1,190 Light trucks 96 106 113 126 659 Combined 242 280 318 364 1,849

Conversely, this analysis indicates slight ly greater outlays for additional technology under the proposed standards when potential voluntary overcompliance is taken into account. This increase is attributable to slight incr eases in technology application when potential voluntary overcompliance is taken into account. Tables IV.G.4–27a and 27b below show that total technology costs attributable to today’ s proposed standards are estimated to increase? to $164 billion, or 1.2 percent more than the $160 billion estimated when potential voluntary overcompliance was not taken into account:

T ABLE IV.G.4-27 A

. I NCREMENTAL T ECHNOLOGY O UTLAYS ($ BILLION ) UNDER P ROPOSED S TANDARDS

– MY S 2017-2021 ( INCLUDING VOLUNTARY OVERCOMPLIANCE )
Earlier MY 2017 MY 2018 MY 2019 MY 2020 MY 2021 Passenger cars 3 2 5 7 9 12 Light trucks 0 0 1 2 4 5 Combined 4 3 6 9 13 18

T ABLE IV.G.4-27 B

. I NCREMENTAL T ECHNOLOGY O UTLAYS ($ BILLION ) UNDER P ROPOSED S TANDARDS

– MY S 2022-2025 ( INCLUDING VOLUNTARY OVERCOMPLIANCE )

760 Differences in the application of diesel engines and plug -in hybrid electric vehicles lead to differences in the incremental percentage changes in fuel consumption and carbon dioxide emissions.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 712 of 768 MY 2022 MY 2023 MY 2024 MY 2025 Total Passenger cars 14 18 22 24 117 Light trucks 6 7 8 9 43
Combined 20 25 30 33 160

Because NHTSA’s analysis indicated that voluntary overcompliance with baseline standards will slightly reduce the share of fuel savings attributable to today’s standards, the agency’s estimate of the present value of total benefits will be $465 billion when discounted at a 3 percent annual rate, as Tables IV.G.4–28a and 28b following report. This estimate of total benefits is $28 billion, or about 5.6 percent, lower than the $497 billion reported previously for the analysis in which potential voluntary overcompliance was not taken into account:

T ABLE IV.G.4-28 A

. P RESENT V ALUE OF B ENEFITS ($ BILLION ) UNDER P ROPOSED S TANDARDS U SING A 3 P ERCENT D ISCOUNT R ATE

– MY S 2017-2021 ( INCLUDING VOLUNTARY

OVERCOMPLIANCE )
Earlier MY 2017 MY 2018 MY 2019 MY 2020 MY 2021 Passenger cars 10 7 13 20 26 32 Light trucks 1 1 5 12 16 22 Combined 11 8 18 31 42 54

T ABLE IV.G.4-28 B

. P RESENT V ALUE OF B ENEFITS ($ BILLION ) UNDER P ROPOSED S TANDARDS U SING A 3 P ERCENT D ISCOUNT R ATE

– MY S 2022-2025 ( INCLUDING VOLUNTARY

OVERCOMPLIANCE )
MY 2022 MY 2023 MY 2024 MY 2025 Total Passenger cars 37 42 49 55 290 Light trucks 26 29 31 32 176 Combined 62 70 80 88 465

Similarly, when accounting for potential voluntary overcompliance, NHTSA estimates that the present value of total benefits will declin e from its previous estimate when future fuel savings and other benefits are discounted at the higher 7 percent rate. Tables IV.G.4–29a and 29b report that the present value of benefits from requiring higher fuel economy for MY 2017– 25 cars and light trucks will total $379 billion when discounted using a 7 percent rate, about $22 billion (or 5.4 percent) below the previous $404 b illion estimate of total benefits when potential voluntary overcompliance is not taken into account:

T ABLE IV.G.4-29 A

. P RESENT V ALUE OF B ENEFITS ($ BILLION ) UNDER P ROPOSED S TANDARDS U SING A 7 P ERCENT D ISCOUNT R ATE

– MY S 2017-2021 ( INCLUDING VOLUNTARY

OVERCOMPLIANCE )
Earlier MY 2017 MY 2018 MY 2019 MY 2020 MY 2021 Passenger cars 8 5 11 16 21 26 Light trucks 1 1 4 9 13 18 Combined 9 6 15 25 34 44DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 713 of 768 T ABLE IV.G.4-29 B

. P RESENT V ALUE OF B ENEFITS ($ BILLION ) UNDER P ROPOSED S TANDARDS U SING A 7 P ERCENT D ISCOUNT R ATE

– MY S 2022-2025 ( INCLUDING VOLUNTARY

OVERCOMPLIANCE )
MY 2022 MY 2023 MY 2024 MY 2025 Total Passenger cars 30 34 41 46 237 Light trucks 21 23 25 26 141
Combined 51 57 65 72 379

Based primarily on the reduction of benefits attributable to the proposed standards when voluntary overcompliance is taken into account, the agency estimates, as shown in tables IV.G.4–30a and 30b, that net benefits from the proposed CAFE standards will be $305 billion— or 8.7 percent -- less than the previously-reported estimate of $335 billion, which did not incorporate the potential for voluntary overcompliance.

T ABLE IV.G.4-30 A

. P RESENT V ALUE OF N ET B ENEFITS ($ BILLION ) UNDER P ROPOSED S TANDARDS U SING A 3 P ERCENT D ISCOUNT R ATE

– MY S 2017-2021 ( INCLUDING VOLUNTARY

OVERCOMPLIANCE )
Earlier MY 2017 MY 2018 MY 2019 MY 2020 MY 2021 Passenger cars 6 4 8 13 16 20 Light trucks 1 1 4 9 13 17 Combined 7 5 12 22 29 37

T ABLE IV.G.4-30 B

. P RESENT V ALUE OF N ET B ENEFITS ($ BILLION ) UNDER P ROPOSED S TANDARDS U SING A 3 P ERCENT D ISCOUNT R ATE

– MY S 2022-2025 ( INCLUDING VOLUNTARY

OVERCOMPLIANCE )
MY 2022 MY 2023 MY 2024 MY 2025 Total Passenger cars 22 24 27 31 172 Light trucks 20 21 23 23 133 Combined 42 46 50 55 305

Similarly, Tables IV.G.4–31a and 31b immediately below show that NHTSA estimates voluntary overcompliance could reduce net benefits attributable to today’s proposed standards to $219 billion if a 7 percent discount rate is applied to future benefits. This estimate is $24 billion—or 9.9 percent—lower than the previously -reported $242 billion estimate of net benefits when potential voluntary overcompliance is not taken into account, using that same discount

rate.

T ABLE IV.G.4-31 A

. P RESENT V ALUE OF N ET B ENEFITS ($ BILLION ) UNDER P ROPOSED

S TANDARDS U SING A 7 P ERCENT D ISCOUNT R ATE

– MY S 2017-2021 ( INCLUDING VOLUNTARY

OVERCOMPLIANCE )
Earlier MY 2017 MY 2018 MY 2019 MY 2020 MY 2021 Passenger cars 8 3 6 9 12 14 Light trucks 1 1 3 7 9 13
Combined 5 4 9 16 21 26DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 714 of 768 T ABLE IV.G.4-31 B

. P RESENT V ALUE OF N ET B ENEFITS ($ BILLION ) UNDER P ROPOSED S TANDARDS U SING A 7 P ERCENT D ISCOUNT R ATE

– MY S 2022-2025 ( INCLUDING VOLUNTARY

OVERCOMPLIANCE )
MY 2022 MY 2023 MY 2024 MY 2025 Total Passenger cars 16 17 18 22 120 Light trucks 15 16 17 17 98 Combined 30 33 35 39 219

As discussed above, these reductions in fuel savings and avoided CO 2 emissions (and correspondingly, in total and net benefits) attributable to today’s proposed standards, do not indicate that fuel consumption and CO 2 emissions will be higher when potential voluntary overcompliance with standards is taken into accoun t than when it is set aside. Rather, these reductions reflect differences in attribution; when potential voluntary overcompliance is taken into account, portions of the avoided fuel consumption and CO 2 emissions (and, correspondingly, in total and net benefits) are effectively attributed to the actions of the market, rather than to the proposed CAFE standards.

NHTSA invites comment on this sensitivit y analysis, in partic ular regarding the following questions:

 Is it reasonable to assume that, having achieved compliance with CAFE standards, a manufacturer might consider further fuel economy improvements, depending on technology costs and fuel prices?

 If so, does the agency’s approach—comparing technology costs to the present value of fuel savings over some payback period—provide a reasonable means to simulate manufacturers’ decisions? DOT’s consideration of any alternative methods will be facilitated by specific suggestions regardi ng their integration into DOT’s CAFE model.

 Is it appropriate to assume different effective payback periods before and after compliance has been achieved? Why, or why not?

 What payback period is (or, if more than one , are) most likely to reflect manufacturers’ decisions regarding technology application through MY2025?

For more detailed inform ation regarding NHTSA’s sensitivity analyses for this proposed rule, please see Chapter X of NHTSA’s PRIA.

5. How would these proposed standards impact vehicle sales?

The effect of this rule on sales of new vehicles depends partly on how potential buyers evaluate and respond to its effects on vehicle pr ices and fuel economy. The rule will make new cars and light trucks more expensive, as manufacturers attempt to recover their costs for complying with the rule by raising vehicle prices , which by itself would discourage sales. At theDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 715 of 768 same time, the rule will require manufacturers to improve the fuel economy of at least some of their models, which will lower their operating costs.

However, this rule will not change the way that potential buyers evaluate improved fuel economy. If some consumers find it difficult to es timate the value of future fuel savings and to correctly compare it with the increased cost of purchasing higher fuel economy (possibilities discussed below in Section IV.G.6)—or if they simply have low values of saving fuel—this rule will not change that situation, so it is unlikely to lead them to purchase more fuel-efficient models that they do now. To the extent that other consumers more completely or correctly account for the value of fuel savings and the co sts of acquiring higher fuel economy in their purchasing decisions, they will al so continue to do so, and they are likely to view models with improved fuel economy as more attractive purchases than those manufacturers currently offer. The effect of this rule on sales of new vehicles will depend on which form of behavior is more widespread.

If consumers are satisfied with the combinations of fuel economy levels and prices that current models offer, we would expect some to decide that the higher prices of new models no longer justify purchasing them, even though they offer higher fuel economy. Other potential buyers may decide to purchase the same vehicles they would have before the rule took effect, or if manufacturers no longer offer those models, to shift their purchases to models offering other attributes. Thus, if consumer preferences dete rmine the amount of fuel economy offered in vehicles, sales of new models would decline, regardless of whether “consumer-side” failures in the market for fuel economy currently lead buyers to under-invest in fuel economy, because this rule will not remedy the sources of that behavior.

In general, the agency expects that the net ef fect of this rule will be to reduce sales of new vehicles, or leave them unchanged. If consumers are satisfied with the combinations of fuel economy levels and prices that current models offer, we would expect some to decide that the higher prices of those models no longer justify purchasing them, even though they offer higher fuel economy. Other potential buyers may decide to purchase the same vehicle they would have before the rule took effect, or to shift their purc hases to models offering other attributes. Thus sales of new models would decline, regardless of whether “consumer-side” failures in the market for fuel economy currently lead buyers to under- invest in fuel economy, because this rule will not remedy the sources of that behavior.

However, if some market failure on the producer or supply side currently inhibits manufacturers from offering increases in fuel economy that would increase their sales or profits—for example, if producers have underestimated the demand for fuel economy, or do not compete vigorously to provide as much fuel economy as buyers would prefer—then the new standards would make vehicles more attractive to many buyers, and their sales should increase (potential explanations for such producer market failures are discussed in Section IV.G.6 below). The methodology NHTSA used to estimate the impact of the proposed rule on vehicle sales in effect assumes that this latter situation prevails. That is, the agency implicitly assumes that some market failure leads manufacturers not to supply vehicles with higher fuel economy, despite potential buyers’ willingness to pay sufficiently hi gher prices for them to make it profitable for manufacturers to produce them. This assumption implies that by requiring manufacturers toDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 716 of 768 produce vehicles featuring higher fuel economy than they otherwise would, the proposed rule will lead to increases in sales of MY 2017-25 cars and light trucks.

NHTSA examined the potential impact of highe r vehicle prices on sales on an industrywide basis for passenger cars and light trucks separately. However, the analysis conducted for this rule does not have the precision to examine ef fects on individual manufacturers or different vehicle classes. Although it is relatively stra ightforward, the agency’s analysis relies on a number of simplifying assumptions, which are detailed below.

There is broad consensus in the economic literature that the price elasticity for demand for new automobiles is approximately -1.0. 761 Thus, every one percent increase in the average price of a new vehicle w ill reduce their sales by one percent. Estimates of price elasticities typically assume no perceived changes in the quality of the product, but in this case, vehicle price increases result from adding technologies that improve fuel economy. If consumers did not attach any value to improved fuel economy and considered only the increase in price in their purchasing decisions, then the estimated impact of higher prices on sales could be estimated directly using this price elasticity. However, NHTSA believes that consumers do attach some value to improved fuel economy, because it reduces the operating costs of the vehicles. NHTSA also believes that the proposed standards are likel y to affect their costs for purchasing, owning, and operating vehicles in ways other than simply reducing their fuel costs. The agency has attempted to estimate the changes in these other cost components that would result from the proposed standards, and to include these in its analysis of changes in vehicle sales.

One critical question is how much of their costs for improving fuel economy to meet the proposed standards manufacturers will be able to recover from vehicle buyers through higher prices. The ability of manufacturers to pass their compliance costs on to consumers depends upon the extent of competition among manufacturers, and the sensitivity of demand for new vehicles to changes in their prices. 762 NHTSA’s analysis of sales impacts assumes that manufacturers will be able to pass all of their costs to improve fuel economy on to consumers. To the extent that NHTSA has accurately predicted the price of gasoline and consumers’ reactions, and manufacturers are able to pass on all of these costs to consumers, then the agency’s sales and employment impact analyses are reasonable.

On the other hand, if manufacturers’ ability to increase prices is limited by competitive conditions in the new car market, then the impact on sales would be limited, although manufacturers’ profit levels would fall as they absorbed part of their costs for increasing fuel economy. Losses in sales would be predicted to occur only if consumers fail to value fuel economy improvements by as much as they would be required to pay for higher fuel economy in the form of higher vehicle prices. Conversely, if fu el prices rise beyond the projected levels used

761 Kleit, A.N. (1990). “The Effect of Annual Ch anges in Automobile Fuel Economy Standards,” Journal of Regulatory Economics, vol. 2, pp 151–172 (Docket EPA–HQ–OAR–2009 –0472–0015); Bordley, R. (1994). “An Overlapping Choice Set Model of Automotive Price Elasticities,” Transportation Research B, vol 28B, no 6, pp 401–408 (Docket NHTSA–2009–0059–0153); McCarthy, P.S. (1996). “Market Price and Income Elasticities of New Vehicle Demands,” The Review of Economics and Statistics, vol. LXXVII, no. 3, pp. 543–547 (Docket NHTSA–2009–0059–0039).

762 Gron, Ann and Swenson, Deborah, 2000, “Cost Pass-Through in the U.S. Automobile Market,” The Review of Economics and Statistics, 82: 316–324. (Docket EPA–HQ–OAR–2009–0472–0007).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 717 of 768 in this analysis, consumers’ valuation of improved fuel economy could potentially increase beyond that estimated here, which could result in higher sales levels than the agency projects.

To estimate the average value consumers place on fuel savings at the time they consider purchasing a vehicle, NHTSA assumes that the average buyer considers the fuel savings they would receive from higher fuel economy over a 5 year time frame. NHTSA chose 5 years because this is the average length of time of a financing agreement. 763 The present value of these savings was calculated using a 3 percent discount rate. NHTSA used the AEO 2011 Reference Case forecast of retail fuel prices, since these re flect the prices that buyers of MY 2017-25 cars and light trucks are expected to pay. For example, buyers of MY 2020 cars and light trucks are expected to value fuel savings from the higher fu el economy levels this rule would require those vehicles to achieve at retail prices over the five years from 2020 through 2024. Fuel savings were calculated over the first 5 years of each model years’ lifetime and discounted back to their present values as of the year they would be purchased.

NHTSA believes that consumers may consider several other factors over the 5 year horizon when contemplating the purchase of a new vehicle, and the agency incorporated these factors into its calculations to represent how in creases in technology costs and vehicle purchase prices might affect consumers’ buying considerati ons. First, consumers are likely to consider the additional sales taxes they will be required to pay when they purchase a mo re expensive vehicle. NHTSA examined individual states’ sales tax rates on new vehicle purchases during 2007, and weighted them by each state’s population to arrive at a national weighted-average sales tax rate of 5.5 percent.

Second, NHTSA considered a dditional insurance costs over the 5 year period. More expensive vehicles will require more expensive collision and comprehensive ( e.g., theft) car insurance. Collision and comprehensive insurance are the components of insurance costs that depend on the insured vehicle’s value. The increase in insurance costs is estimated from the average value of collision plus comprehensive insurance as a proportion of the average new vehicle price. The Insurance Information Institut e provides the average value of collision plus comprehensive insurance in 2006 as $448. 764 This is compared to an average purchase price for new light vehicles of $24,033 during 2006. 765 Dividing the insurance cost by the average price of a new vehicle gives th e proportion of comprehensive plus collision insurance as 1.86 percent of the price of a vehicle. If we assume that th is premium is proportional to the new vehicle’s price, then purchasers pay about 1.86 percent of the new vehicle’s for insurance each year over the five year period we are considering. Discounting those insurance costs back to its present value using a 3 percent rate indicates that the pr esent value of the component of insurance costs that vary with vehicle price is equal to 8.5 pe rcent of the vehicle’s in itial purchase price.

763 National average financing terms for au tomobile loans are available from the Board of Governors of the Federal Reserve System G.19 “Consumer Finance” release. See http://www.federalreserve.gov/releases/g19/ (last accessed October 11, 2011).

764 Insurance Information Institute, 2008, “Average Expenditures for Auto Insurance By State, 2004–2008.” Available at http://www.iii.org/media/facts/statsbyissue/auto/ (last accessed October 12, 2011).

765 $29,678/$26,201 = 1.1327 * $22,651 = $25,657 average price for light trucks. In 2006, passenger cars were 54 percent of the on-road fleet and light trucks were 46 percent of the on-road fleet, resulting in an average light vehicle price for 2006 of $24,033.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 718 of 768 Third, NHTSA considered the fact that ap proximately 70 percent of new vehicle buyers take out loans to finance their purchases. Currently, the average new vehicle loan is for approximately 5 years at a 6 percent rate. 766 At these terms, the average person taking a loan will pay 16 percent more for their vehicle over the fi rst 5 years of ownership than will a consumer paying cash to purchase the same vehicle. 767 Discounting the additional 3.2 percent (16 percent/5 years) annual financing expense over the 5 years using a 3 percent mid-year discount

rate 768 results in a discounted present value of 14.87 percent higher for those taking a loan. Multiplying that by the proportion (70 percent) of consumers who use loans to finance their purchases means that the average consumer would pay 10.2 percent more than the vehicle’s retail price.

Fourth, NHTSA considered the residual value (or resale value) of the vehicle after 5 years and expressed this as a percentage of its price when purchased new. In other words, if the price of the vehicle increases to reflect its ma nufacturer’s costs for improving its fuel economy, its resale value is assumed to increase proportionately. The average resale price of a vehicle after 5 years is about 35 percent of its original purchase price. 769 Discounting its residual value after 5 years back to the date of purchase using a 3 percent discount rate gives a present value of its expected residual value that is equal to 30.6 pe rcent of the vehicle’s price when purchased new.

NHTSA then adds these four components of increased costs together. At a 3 percent discount rate, the buyer expects to recover 30.6 percent of the vehicle’s initial price upon resale, but in the meantime will pay 5.5 percent more for taxes, 8.5 percent more in insurance, and 10.2 percent more to finance its purchase at current terms. Summing these components indicates that the buyer of a new vehicle expects on balance to recover an amount having a present value equal to 6.48 percent of the higher price for purchasing a more fuel-efficient new vehicle. Thus, the increase in the vehicle’s purchase price is mu ltiplied by 0.9352 (=1-0.0648) to determine the “effective” increase in its initial cost that re sults when higher CAFE standards require its manufacturer to increase its fuel economy. Subtracting the present value of fuel savings over the first five years of its lifetime from its higher ini tial cost determines the overall net change in its value to potential buyers. Applying the elasticity of demand for new vehicle purchases to the average net change in new vehicles’ values provides an estimate of the resulting change in their total sales during each model year affected by the proposed standards.

The following tables show the estimated impacts on sales of passenger cars and light trucks expected to result from the proposed standards, using a 3 percent discount rate and a 7 percent discount rate. For all model years except MY 2012, NHTSA anticipates an increase in sales, because it anticipates that potential buyers will value the increases in fuel economy the standards require for these model years by more than the effective increase in the average new vehicle’s price.

766 New car loan rates in 2007 averaged about 7.8 percent at commercial banks and 4.5 percent at auto finance companies, so their averag e is close to 7 percent.

767 Based on http://www.bankrate.com auto loan calculator for a 5 year loan at 6 percent.

768 For a 3 percent discount rate, the summation of 3.2 percent × 0.9853 in year one, 3.2 × 0.9566 in year two, 3.2 × 0.9288 in year three, 3.2 × 0.9017 in year 4, and 3.2 × 0.8755 in year five.

769 Consumer Reports, August 2008, “What That Car Really Costs to Own.” Available at http://www.consumerreports.org/cro/cars/car-prices/what-th at-car-really-costs-to-own- 4-08/overview/what-that-carreally-costs-to-own-ov.htm (last accessed October 12, 2011).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 719 of 768 T ABLE IV.G.5-1 A

. P OTENTIAL I MPACT ON S ALES , P ASSENGER C ARS , L IGHT T RUCKS , AND C OMBINED , 3 PERCENT D ISCOUNT R ATE

– MY S 2017-2021
MY 2017 MY 2018 MY 2019 MY 2020 MY 2021 Passenger cars 57,308 91,938 145,078 172,188 186,766 Light trucks 18,849 57,496 134,079 178,355 245,520 Combined 76,157 149,433 279,157 350,544 432,286

T ABLE IV.G.5-1 B

. P OTENTIAL I MPACT ON S ALES , P ASSENGER C ARS , L IGHT T RUCKS , AND C OMBINED , 3 PERCENT D ISCOUNT R ATE

– MY S 2022-2025
MY 2022 MY 2023 MY 2024 MY 2025 Passenger cars 213,300 196,883 208,579 278,324 Light trucks 275,012 306,096 335,477 369,023 Combined 488,312 502,979 544,056 647,347

T ABLE IV.G.5-2 A

. P OTENTIAL I MPACT ON S ALES , P ASSENGER C ARS , L IGHT T RUCKS , AND C OMBINED , 7 PERCENT D ISCOUNT R ATE

– MY S 2017-2021
MY 2017 MY 2018 MY 2019 MY 2020 MY 2021 Passenger cars 37,213 58,255 91,398 100,771 107,688 Light trucks 11,722 45,442 111,856 147,745 202,114 Combined 48,935 103,697 203,254 248,515 309,803

T ABLE IV.G.5-2 B

. P OTENTIAL I MPACT ON S ALES , P ASSENGER C ARS , L IGHT T RUCKS , AND C OMBINED , 7 PERCENT D ISCOUNT R ATE

– MY S 2022-2025
MY 2022 MY 2023 MY 2024 MY 2025 Passenger cars 118,358 86,293 69,875 161,321 Light trucks 226,933 259,752 280,561 305,213 Combined 345,291 346,046 350,435 466,534

The estimates provided in the tables above are meant to be illustrative, rather than to provide a definitive prediction. When viewed at the industry-wide level, they give a general indication of the potential impact on vehicle sale s. As the sales projections show, the overall impact of the rule on new car and light truck sale s is expected to be positive, and to grow over the model years subject to the rule. Because the fuel savings associated with this rule are expected to exceed the technology costs, the effec tive prices of vehicles (the adjusted increase in technology cost less the present value of fuel savi ngs over five years) to consumers will fall, and consumers are expected to buy more new vehicles. In other words, the lower net cost of the vehicles is projected to lead to an increase in sales for both cars and trucks.

As discussed above, this result depends on the assumption that more fuel efficient vehicles yielding net consumer benefits over their first five years would not otherwise be offered, due to market failures on the part of vehicle manufacturers. However, vehicle models that achieve the fuel economy targets prescribed by today’s proposal are already available, and consumers do not currently purchase a combination of them that meets the fuel economy levels this rule requires. This suggests that the rule may not result in an increase in vehicle sales,DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 720 of 768 because it does not alter how consumers currently make decisions about which models to purchase. Under the previous uniform standard, however, vehicles achieving higher fuel economy were typically smaller than other models, and manufacturers’ efforts to comply with uniform standards could leave consumers who wanted larger vehicles without satisfactory options. The footprint-based standard used in more recent rulemakings provides different targets for different sizes of vehicles.

In addition, this analysis has not accounted for a number of factors that might affect consumer vehicle purchases, such as chan ging market conditions, changes in vehicle characteristics that might accompany improvements in fuel economy, or consumers considering a shorter “payback period” for fuel economy than the five years assumed in this analysis. If consumers use a shorter payback period, sales w ill increase by less than estimated here, and could even decline, while the increase in sales is likely to be larger than reported here if consumers use longer payback periods. Because th is is an aggregate analysis, some individual consumers—particularly those who drive less than the average values used in this analysis—will receive lower net benefits from the increases in fuel economy this rule requires, while others (including those who drive more than estimated he re) will realize even greater savings. These complications, which have not been taken into account in our analysis, add considerable uncertainty to our estimates of changes in vehicle sales resulting from this rule.

6. Potential Unquantified Consumer Welfare Impacts of the Proposed Standards

There are two viewpoints for evaluating the costs and benefits of the increase in CAFE standards: the private perspective of vehicle buyers themselves on the higher fuel economy levels that the rule would require, and the economy-wide or “social” perspective on the costs and benefits of requiring higher fuel economy. In order to appreciate how these viewpoints may diverge, it is important to distinguish between co sts and benefits that are “private” and costs and benefits that are “social,” The agency’s analysis of benefits and costs from requiring higher fuel efficiency, presented above, includes several categories of benefits (identified as “social benefits”) that are not limited to automobile purchasers, and that extend throughout the U.S. economy. Examples of these benefits include redu ctions in the energy security costs associated with U.S. petroleum imports, and in the economic damages expected to result from climate change. In contrast, other categories of benefits —principally future fuel savings projected to result from higher fuel economy —will be experi enced exclusively by the initial purchasers and subsequent owners of vehicle models whos e fuel economy manufacturers elect to improve (“private benefits”).

Although the economy-wide or “social” benefits from requiring higher fuel economy represent an important share of the total economic benefits from raising CAFE standards, NHTSA estimates that benefits to vehicle buyers themselves will significantly exceed vehicle manufacturers’ costs for complying with the stricter fuel economy standards this rule establishes. Since the agency also assumes that the costs of new technologies manufacturers will employ to improve fuel economy will ultimately be borne by vehicle buyers in the form of higher purchase prices, NHTSA concludes that the benefits to potential vehicle buyers from requiring higher fuel efficiency will far outweigh the costs they will be required to pay to obtain it.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 721 of 768 As an illustration, Tables IV.G.6–1a and 1b report the agency’s estimates of the average lifetime values of fuel savings for MY 2017–2025 passenger cars and light trucks calculated using projected future retail fuel prices. The table compares NHTSA’s estimates of the average lifetime value of fuel savings for cars and light tr ucks to the price increases it expects to occur as manufacturers attempt to recover their costs for complying with increased CAFE standards. As the table shows, the agency’s estimates of the pr esent value of lifetime fuel savings (discounted using the OMB-recommended 3% rate) substantially outweigh projected vehicle price increases for both cars and light trucks in every model year, even under the assumption that all of manufacturers’ technology outlays are passed on to buyers in the form of higher selling prices for new cars and light trucks. By model year 2025, NHTSA projects that average lifetime fuel savings will exceed the average price increase by more than $2,800 for cars, and by more than $4,400 for light trucks.

T ABLE IV.G.6-1 A

. V ALUE OF L IFETIME F UEL S AVINGS VS

. V EHICLE P RICE I NCREASES

– MY S 2017-2021

Fleet Measure Model year
2017 2018 2019 2020 2021

Passenger cars Value of fuel savings $601 $1,106 $1,758 $2,300 $2,775 Average price increase $168 $342 $551 $783 $1,005
Difference $433 $764 $1,207 $1,517 $1,770

Light trucks Value of fuel savings $289 $905 $2,066 $2,802 $3,835 Average price increase $62 $184 $386 $576 $820
Difference $228 $721 $1,680 $2,226 $3,015

T ABLE IV.G.6-1 B

. V ALUE OF L IFETIME F UEL S AVINGS VS

. V EHICLE P RICE I NCREASES

– MY S 2022-2025

Fleet Measure Model year
2022 2023 2024 2025

Passenger cars Value of fuel savings $3,124 $3,669 $4,148 $4,794 Average price increase $1,135 $1,468 $1,708 $1,929
Difference $1,989 $2,201 $2,440 $2,865

Light trucks Value of fuel savings $4,263 $4,829 $5,319 $5,687 Average price increase $921 $1,071 $1,193 $1,241
Difference $3,341 $3,759 $4,126 $4,446

The comparisons above immediately raise the question of why current vehicle purchasing patterns do not already result in average fuel economy levels approaching those that this rule would require, and why raising CAFE standards should be necessary to increase the fuel economy of new cars and light trucks. They also raise the question of whether it is appropriate to assume that manufacturers would not elect to provide higher fuel economy even in the absence of increases in CAFE standards, since the comparisons in Tables IV.G.6–1a and 1b suggest that doing so would increase the market value (and thus the selling prices) of many new vehicle models by far more than it would raise the cost of producing them. Thus, increasing fuelDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 722 of 768 economy would be expected to increase sales of new vehicles and manufacturers’ profits. More specifically, why would potential buyers of new vehicles hesitate to purchase models offering higher fuel economy, when doing so would produce the substantial economic returns illustrated by the comparisons presented in Tables IV.G.6–1a and 1b? And why would manufacturers voluntarily forego opportunities to increase the attractiveness, value, and competitive positioning of their car and light truck models—and thus their own profits—by improving their fuel economy?

One explanation for why this si tuation might persist is that the market for vehicle fuel economy does not appear to work perfectly, in which case properly designed CAFE standards would be expected to increase consumer welfare. Some of these imperfections might stem from standard market failures, such as limited availability of information to consumers about the value of higher fuel economy. In contrast, others might reflect phenomena observed elsewhere in the field of behavioral economics, including inadequate consumer attention to long-term savings, or a lack of salience of relevant benefits (such as fuel savings, or time savings associated with refueling) to consumers at the time they make purchasing decisions. Both theoretical and empirical research suggests that many consum ers are unwilling to make energy-efficient investments even when those investments app ear to pay off in the relatively short-term. 770 This research is in line with related findings that c onsumers may undervalue benefits or costs that are less salient, or that they will realize only in the future. 771

Previous research provides some support for the agency’s conclusion that the benefits buyers will receive from requiring manufactur ers to increase fuel economy outweigh the costs they will pay to acquire those benefits, even if private markets have not provided that amount of fuel economy. This research identifies aspects of normal behavior that may explain the market not providing vehicles whose higher fuel economy appears to offer an attractive economic return. For example, consumers’ understandable aversion to the prospect of losses (“loss aversion”) may exaggerate their sense of uncertainty about the value of future fuel savings. This heightened sense of uncertainty may make purchasing a more fuel-efficient vehicle seem unattractive to some potential buyers , even when doing so is likely to be a sound economic decision. As an illustration, Greene et al. (2009) calculate that the expected net present value of increasing the fuel economy of a passenger car from 28 to 35 miles per gallon falls from $405 when calculated using standard net present value calculations, to nearly zero when uncertainty regarding future cost savings and buyers’ reluctance to accept the risk of losses are taken into account. 772

770 Jaffe, A. B., and Stavins, R. N. (1994). The Energy Paradox and the Diffusion of Conservation Technology. Resource and Energy Economics, 16(2); see Hunt Alcott a nd Nathan Wozny, Gasoline Prices, Fuel Economy, and the Energy Paradox (2009), available at http://web. mit.edu/allcott/www/Allcott%20and%20Wozny%202010%20- %20Gasoline%20Prices,%20Fuel%20Economy,%20and%20th e%20Energy%20Paradox.pdf (last accessed Sept. 26, 2011).

771 Hossain, Janjim, and John Morgan (2009). “ * * * Pl us Shipping and Handling: Revenue (Non)Equivalence in Field Experiments on eBay,” Advances in Economic Analys is and Policy vol. 6; Barber, Brad, Terrence Odean, and Lu Zheng (2005). “Out of Sight, Out of Mind: The Effects of Expenses on Mutual Fund Flows,” Journal of Business vol. 78, no. 6, pp. 2095–2020.

772 Greene, D., J. German, and M. Delucchi (2009). “Fue l Economy: The Case for Market Failure” in Reducing Climate Impacts in the Transportation Sector, Sperling, D., and J. Cannon, eds. Springer Science. Surprisingly, the authors find that uncertainty regarding the future price of gasoline appears to be less important than uncertainty surrounding the expected lifetimes of new vehicles. (Docket NHTSA–2009–0059–0154).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 723 of 768 The well-known finding that as gas prices rise, consumers show more willingness to pay for fuel-efficient vehicles is not necessarily inco nsistent with the possibility that many consumers undervalue potential savings in gasoline costs and fuel economy when purchasing new vehicles. In ordinary circumstances, such costs may be a relatively “shrouded” attribute in consumers’ decisions, in part because the savings from purchasing a more fuel efficient vehicle are cumulative and extend over a significant period of time. At the same time, it may be difficult for potential buyers to disentangle the cost of purch asing a more fuel-efficient vehicle from its overall purchase price, or to isolate the value of higher fuel economy form accompanying differences in other vehicle attri butes. This possibility is consistent with recent evidence to the effect that many consumers are willing to pay less than $1 upfront to obtain a $1 reduction in the discounted present value of future gasoline costs. 773

Some research suggests that the market’s ap parent unwillingness to provide more fuel efficient vehicles stems from consumers’ inability to value future fuel savings correctly. For example, Larrick and Soll (2008) find evidence that consumers do not understand how to translate changes in fuel economy, which is de nominated in miles per gallon, into resulting changes in fuel consumption, measured for example in gallons per month or year. 774 Sanstad and Howarth (1994) argue that consumers often resort to imprecise but convenient rules of thumb to compare vehicles that offer different fuel economy ratings, and that this can cause many buyers to underestimate the value of fuel savings, particularly from significant increases in fuel

economy. 775 If the behavior identified in these studies is widespread, then the agency’s estimates suggesting that the benefits to vehicle owners from requiring higher fuel economy significantly exceed the costs of providing it may be consistent with private markets not providing that fuel economy level.

Another possible factor in the observation that the average vehicle buyer will experience large fuel savings from the proposed higher CAFE standards even though the average fuel economy of vehicles currently purchased falls well short of the new standards is that the values of future savings from higher fuel economy vary widely among potential vehicle buyers, but on average are lower than those the agency estimates. The expected savings from purchasing a vehicle with higher fuel economy vary widely am ong individuals, because their uses of vehicles differ widely, differences in their driving styles affect the fuel economy they expect to achieve, or they simply have varying expectations about future fuel prices and the value of saving fuel. These potential differences suggest that buyers with high valuations of increased fuel economy

may already purchase vehicle models that offer it, while those with lower values of fuel economy emphasize other vehicle attributes in th eir purchasing decisions. If these differences cause the average buyer to value the fuel savings resulting from the higher fuel economy levels this rule would require at less than the average fi gure incorporated in the agency’s analysis, they may partly explain why the average fuel economy of new vehicles currently falls short of the proposed standards.

773 See, e.g., Alcott and Wozny.

774 Larrick, R. P., and J.B. Soll (2008). “The MPG illusion” Science 320: 1593–1594.

775 Sanstad, A., and R. Howarth (1994). “ ‘Normal’ Mark ets, Market Imperfections, and Energy Efficiency.” Energy Policy 22(10): 811–818.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 724 of 768 Unless the agency has overestimated their average value, however, the fact that the value of fuel savings varies among potential buyers cannot explain why typical buyers do not currently purchase what appear to be cost- saving increases in fuel economy. A possible explanation for this situation is that the effects of differing fuel economy levels are relatively modest when compared to those provided by other, more prominent features of new vehicles, such as passenger and cargo-carrying capacity, performance, or safety. In this situation, it may simply not be in many shoppers’ interest to spend the time and effort necessary to determine the economic value of higher fuel economy, to isolat e the component of a new vehicle’s selling price that is related to its fuel economy, and compare thes e two. (This possibility is consistent with the view that fuel economy is a relatively “shrouded” attribute, and one that is often bundled with other attributes in ways that make it difficult to isolate.) In this case, the agency’s estimates of the average value of fuel savings that will result from requiring cars and light trucks to achieve higher fuel economy may be correct, yet those savings may not be large enough to lead a sufficient number of buyers to purchase vehicles with higher fuel economy to raise average fuel economy above its current levels.

Defects in the market for cars and light trucks could also lead manufacturers to undersupply fuel economy, even in cases where many buyers were willing to pay the increased prices necessary to compensate manufacturers for providing it. To be sure, the market for new automobiles as a whole exhibits a great deal of competition. But this apparently vigorous competition among manufacturers may not extend to the provision of some individual vehicle attributes. Incomplete or “asymmetric” access to information about vehicle attributes such as fuel economy—whereby manufacturers of new cars and light trucks or sellers of used models have more complete knowledge about vehicles’ actual fuel economy performance than is available to their potential buyers—may also prev ent sellers of new or used vehicles from being able to capture its full value. In this situation, the level of fuel efficiency provided in the markets for new or used vehicles might remain persistent ly lower than that demanded by well-informed potential buyers.

Constraints on the combinations of fuel economy, carrying capacity, and performance that manufacturers can offer in individual vehi cle models using current technologies undoubtedly limit the range of fuel economy available within certain vehicle classes, particularly those including larger vehicles. However, it is also po ssible that deliberate decisions by manufacturers of cars and light trucks further limit the range of fuel economy available to buyers within individual vehicle market segments, such as large automobiles, SUVs, or minivans. Manufacturers may deliberately limit the range of fuel economy levels they offer in those market segments (by choosing not to invest in fuel economy and investing instead in providing a range of other vehicle attributes) because they underestimate the premiums that prospective buyers of those models are willing to pay for improved fuel economy, and thus mistakenly believe it will be unprofitable for them to offe r more fuel-efficient models within those segments. Of course, this possibility is most realistic if it is also assumed that buyers are imperfectly informed, or if fuel economy savings are not sufficiently salient to shoppers in those particular market segments. As an illustration, once a potential buyer has de cided to purchase a mi nivan, the range of highway fuel economy ratings among current models extends from 22 to 28 mpg, while theirDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 725 of 768 combined city and highway ratings extend only from 18 to 20 mpg. 776 If this phenomenon is widespread, the average fuel efficiency of their entire new vehicle fleet could remain below the levels that potential buyers de mand and are willing to pay for.

Another possible explanation for the paradox posed by buyers’ apparent unwillingness to invest in higher fuel economy when it appears to offer such large financial returns is that NHTSA’s estimates of benefits and costs from requiring manufacturers to improve fuel efficiency do not match potential buyers’ assessment of the likely benefits and costs from purchasing models with higher fuel economy ratings. This could occur because the agency’s underlying assumptions about some of the factors that affect the value of fuel savings differ from those made by potential buyers, because NHTSA has used different estimates for some components of the benefits from saving fuel than do buyers, or simply because the agency has failed to account for some potential costs of achieving higher fuel economy.

For example, buyers may not value increased fuel economy as highly as the agency’s calculations suggest, because they have shorter time horizons than the full vehicle lifetimes NHTSA uses in these calculations, or because th ey discount future fuel savings using higher rates than those prescribed by OMB for evalua ting Federal regulations. Potential buyers may also anticipate lower fuel prices in the future than those forecast by the Energy Information Administration, or may expect larger differen ces between vehicles’ MPG ratings and their own actual on-road fuel economy than the 20 percent gap (30 percent for HEVs) the agency estimates.

To illustrate the first of these possibilities, Table IV.G.6–2 shows the effect of differing assumptions about vehicle buyers’ time horizons on their assessment of the value of future fuel savings. Specifically, the table reports the value of fuel savings consumers might consider when purchasing a MY 2025 car or light truck that feat ures the higher fuel economy levels required by the proposed rule, when those fuel savings are evaluated over different time horizons. The table then compares these values to the agency’s esti mates of the increases in these vehicles’ prices that are likely to result from the standards proposed for MY 2025. This table shows that when fuel savings are evaluated over the average lifetime of a MY 2025 car (approximately 14 years) or light truck (about 16 years), their present value (discounted at 3 percent) exceeds the estimated average price increase by more than $2,500 for cars and by almost $3,900 for light trucks.

If buyers are instead assumed to consider fuel savings over only a 10-year time horizon, Table IV.G.6-2 shows that this reduces the difference between the present value of fuel savings and the projected price increase for a MY 2025 car to about $1,800, and to about $2,900 for a MY 2025 light truck. Finally, Table VI.G.6–2 shows that if buyers consider fuel savings only over the length of time for which they typically finance new car purchases (slightly more than 5 years during 2011), the value of fuel savings exceeds the estimated increase in the price of a MY 2025 car by only about $200, while the corresponding difference is reduced to slightly more than $1,200 for a MY 2025 light truck.

776 This is the range of comb ined city and highway fuel economy levels from lowest (Toyota Sienna AWD) to highest (Honda Odyssey) available for model year 2 010; http://www.fueleconomy.gov/feg/bestworstEPAtrucks.htm (last accessed September 26, 2011).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 726 of 768 T ABLE IV.G.6-2. V ALUE OF F UEL S AVINGS C ONSIDERED BY B UYERS VS

. V EHICLE P RICE I NCREASES WITH A LTERNATIVE A SSUMPTIONS ABOUT V EHICLE B UYER T IME H ORIZONS

Vehicle Measure Value Over Alternative Time Horizons (3% Discount Rate)

Average Lifetime 10 Years Average Loan
Term

MY 2025 Passenger Car Fuel Savings $4,431 $3,707 $2,149
Price Increase $1,929 $1,929 $1,929

Difference $2,502 $1,778 $220

MY 2025

Light Truck Fuel Savings $5,114 $4,107 $2,451
Price Increase $1,241 $1,241 $1,241

Difference $3,873 $2,866 $1,210

Potential vehicle buyers may also discount fu ture fuel future savings using higher rates than those typically used to evaluate Federal regulations. OMB guidance prescribes that future benefits and costs of regulations that mainly aff ect private consumption d ecisions, as will be the case if manufacturers’ costs for complying with higher fuel economy standards are passed on to vehicle buyers, should be discounted using a consumption rate of time preference. 777 OMBestimates that savers currently discount future consumption at an average real or inflationadjusted rate of about 3 percent when they face little risk about its likely level, which makes it a reasonable estimate of the consumption rate of time preference.

However, vehicle buyers may view the value of future fuel savings that results from purchasing a vehicle with higher fuel economy as risky or uncertain, or they may instead discount future consumption at rates reflecting their costs for financing the higher capital outlays required to purchase more fuel-efficient models. In either case, buyers comparing models with different fuel economy ratings are likely to disc ount the future fuel savings from purchasing one that offers higher fuel economy at rates well above the 3% assumed in NHTSA’s evaluation.

Table IV.G.6–3 shows the effects of higher discount rates on vehicle buyers’ evaluation of the fuel savings projected to result from the CAFE standards proposed in this NPRM, again using MY 2025 passenger cars and light trucks as an example. As Table IV.G.6–2 showed previously, average future fuel savings discounted at the OMB 3 percent consumer rate exceed the agency’s estimated price increases by more than $2,500 for MY 2025 passenger cars and by almost $3,900 for MY 2025 light trucks. If vehicle buyers instead discount future fuel savings at the typical new-car loan rate prevailing during 2010 (approximately 5.2 percent), however, these differences decline to slightly more than $2,000 for cars and $3,200 for light trucks, as Table IV.G.6–3 illustrates. This is a pl ausible alternative assumption, because buyers are likely to finance the increases in purchase prices resulting from compliance with higher CAFE standards as part of the process of financing the vehicle purchase itself.

777 Office of Management and Budget, Circular A–4, “Regulatory Analysis,” September 17, 2003, 33. Available at http://www.whitehouse.gov/omb/assets/regulatory_matters_pdf/a-4.pdf (last accessed Sept. 26, 2010).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 727 of 768 Finally, as the table also shows, discounting future fuel savings using a consumer credit card rate (which averaged almost 14 percent during 2010) reduces these differences to less than $800 for a MY 2025 passenger car and about $1,700 for the typical MY 2025 light truck. Even at these significantly higher discount rates, howev er, the table shows that the private net benefits from purchasing new vehicles with the levels of fuel economy this rule would require—rather than those that would result from simply exte nding the MY 2016 CAFE standards to apply to future model years—remain large.

T ABLE IV.G.6-3. V ALUE OF F UEL S AVINGS C ONSIDERED BY B UYERS VS

. V EHICLE P RICE I NCREASES WITH A LTERNATIVE A SSUMPTIONS ABOUT C ONSUMER D ISCOUNT R ATES

Vehicle Measure Value at Alternative Discount Rates

OMB

consumer rate (3%) New car loan rate (5.2%) 778 OMB investment rate (7%) Consumer credit card rate (13.8%) 779

MY 2025

passenger car Fuel savings $4,431 $3,952 $3,660 $2,709
Price increase $1,929 $1,929 $1,929 $1,929
Difference $2,502 $2,023 $1,731 $780

MY 2025 light
truck Fuel savings $5,114 $4,455 $3,998 $2,952
Price increase $1,241 $1,241 $1,241 $1,241
Difference $3,873 $3,214 $2,757 $1,711

Some evidence also suggests directly that vehicle buyers may employ combinations of high discount rates and short time horizons in th eir purchase decisions. For example, consumers surveyed by Kubik (2006) reported that fuel savings would have to be adequate to pay back the additional purchase price of a more fuel-efficient vehicle in less than 3 years to persuade them to purchase it, and that even over this short time horizon they were likely to discount fuel savings using credit card-like rates. 780 Combinations of a shorter time horizon and a higher discount rate could further reduce—or potentially even eliminate—the difference between the value of fuel savings and the agency’s estimates of increases in vehicle prices. One plausible combination would be for buyers to discount fuel savings ove r the term of a new car loan, using the interest rate on that loan as a discount rate. Doing so would reduce the amount by which future fuel savings exceed the estimated increase in the prices of MY 2025 vehicles considerably further, to about $130 for passenger cars and $1,400 for light trucks.

As these comparisons illustrate, reasonable alternative assumptions about how consumers might evaluate future fuel savings, the major private benefit from requiring higher fuel economy,

778 Interest rates on 48-month new vehicle loans made by commercial banks during 2010 averaged 6.21%, while new car loan rates at auto fi nance companies averaged 4,26%; See Board of Governors of the Federal Reserve System, Federal Reserve Statistical Release G.19, Consumer Credit. Available at http://www.federalreserve.gov/releases/g19/Cu rrent (last accessed September 27, 2011).

779 The average rate on consumer credit card accounts at commercial banks during 2010 was 13.78%; See Board of Governors of the Federal Reserve System, Federal Re serve Statistical Release G.19, Consumer Credit. Available at http ://www.federalreserve.gov/releases/g19/Current (last accessed September 27, 2011).

780 Kubik, M. (2006). Consumer Views on Transportation and Energy. Second Edition. Technical Report: National Renewable Energy Laboratory. Available at Docket No. NHTSA–2009–0059–0038.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 728 of 768 can significantly affect the benefits they consid er when deciding whether to purchase more fuelefficient vehicles. Readily imaginable combina tions of shorter time horizons, higher discount rates, and lower expectations about future fuel prices or annual vehicle use and fuel savings could make potential buyers hesitant—or perhap s even unwilling—to purcha se vehicles offering the increased fuel economy levels this proposed rule would require manufacturers to provide in future model years. Thus, vehicle buyers’ assessment of the benefits and costs of this proposal in their purchase decisions may differ markedly from NHTSA’s estimates.

If consumers’ views about critical variables su ch as future fuel prices or the appropriate discount rate differ sufficiently from the assumptions used by the agency, some or perhaps many potential vehicle buyers might conclude that the value of fuel savings and other benefits from higher fuel economy they are considering are not sufficient to justify the increase in purchase prices they expect to pay. In conjunction with the possibility that manufacturers misinterpret potential buyers’ willingness to pay for improved fuel economy, this might explain why the current choices among available models do not result in average fuel economy levels approaching those this rule would require.

Another possibility is that achieving the fu el economy improvements required by stricter fuel economy standards might lead manufacturers to forego planned future improvements in performance, carrying capacity, safety, or other features of their vehicle models that provide important sources of utility to their owners, even if it is technologically feasible to have both improvements in those other features and improved fuel economy. Although the specific economic values that vehicle buyers attach to i ndividual vehicle attributes such as fuel economy, performance, passenger- and cargo-carrying capacity, or other features are difficult to infer from vehicle prices or buyers’ choices among competi ng models, changes in vehicle attributes can significantly affect the overall utility that vehicles offer to potential buyers. Thus if requiring manufacturers to provide higher fuel economy leads them to sacrifice improvements in these or other highly-valued attributes, potential buyers are likely to view these sacrifices as an additional cost of improving fuel economy. If those attribut es are of sufficient value, or if the range of vehicles offered ensures that vehicles with thos e attributes will continue to be offered, then vehicle buyers will still have the opportunity to ch oose those attributes, though at increased cost compared to models without the fuel economy improvements.

As indicated in its previous discussion of technology costs, NHTSA has approached this potential problem by attempting to develop cost estimates for fuel economy-improving technologies that include allowan ces for any additional costs that would be necessary to maintain the reference fleet (or baseline) levels of performance, comfort, capacity, or safety of light-duty vehicle models to which those technologies are applied. In doing so, the agency followed the precedent established by the 2002 NAS Report on improving fuel economy, which estimated “constant performance and utility” costs for t echnologies that manufacturers could employ to increase the fuel efficiency of cars or light truc ks. Although NHTSA has revised its estimates of manufacturers’ costs for some technologies signifi cantly for use in this rulemaking, these revised estimates are still intended to represent costs that would allow manufacturers to maintain the performance, safety, carrying cap acity, and utility of vehicle models while improving their fuel economy, in the majority of cases. The agency’s continued specification of footprint-basedDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 729 of 768 CAFE standards also addresses this concern, by establishing less demanding fuel economy targets for larger cars and light trucks.

Finally, vehicle buyers may simply prefer the choices of vehicle models they now have available to the combinations of price, fuel economy, and other attributes that manufacturers are likely to offer when required to achieve the higher overall fuel economy levels proposed in this NPRM. This explanation assumes that auto make rs decide to change vehicle attributes other than price and fuel economy in response to this rule. If this is the case, their choices among models—and even some buyers’ decisions about whether to purchase a new vehicle—will respond accordingly, and their responses to these new choices will reduce their overall welfare. Some may buy models with combinat ions of price, fuel efficiency, and other attributes that they consider less desirable than those they would otherwise have purchased, while others may simply postpone buying a new vehicle. It leaves open the question, though, why auto makers would change those other vehicle characteristics if co nsumers liked them as they were; as noted, the assumption of “constant performance and utility” built into the cost estimates means that these changes are not necessary.

As the foregoing discussion makes clear, the agency cannot offer a complete answer to the question of why the apparently large differences between its estimates of private benefits from requiring higher fuel economy and the costs of supplying it would not result in higher fuel economy for new cars and light trucks in the absence of this rule. One explanation is that these estimates are reasonable, but that for the reasons outlined above, the market for fuel economy is not operating efficiently. NHTSA believes the ex isting literature offers some support for the view that various failures in the market for fuel economy prevent it from providing an economically desirable outcome, which implies that on balance there are likely to be substantial private gains from the proposed rule. The agen cy will continue to investigate new empirical literature addressing this question as it become s available, and seeks comment on this issue.

NHTSA acknowledges the possibility that it ha s incorrectly characterized the impact on the market of the CAFE standards this rule prop oses, and that this could cause its estimates of benefits and costs to misrepresent the effects of the proposed rule. To recognize this possibility, this section presents an alternative accounting of the benefits and costs of CAFE standards for MYs 2017–2025 passenger cars and light trucks and discusses its implications. Table IV.G.6–4 displays the economic impacts of the rule as viewed from the perspective of potential buyers.

As the table shows, the proposed rule’s total benefits to vehicle buyers (line 4) consist of the value of fuel savings over vehicles’ full lifetimes at retail fuel prices (line 1), the economic value of vehicle occupants’ savings in refueling time (line 2), and the economic benefits from added rebound-effect driving (line 3). As the zero entries in line 5 of the table suggest, no losses in consumer welfare from changes in vehicle attributes (other than those from increases in vehicle prices) are assumed to occur. Thus there is no reduction in the total private benefits to vehicle owners, so that net private benefits to vehicle buyers (line 6) are equal to total private benefits (reported previously in line 4).

As Table IV.G.6–4 also shows, the decline in fuel tax revenues (line 7) that results from reduced fuel purchases is a transfer of funds between consumers and government and is thus notDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 730 of 768 a social cost. 781 (Thus the sum of lines 1 and 7 equals the savings in fuel production costs that was reported previously as the value of fuel savings at pre-tax prices in the agency’s previous accounting of benefits and costs.) Lines 8 and 9 of Table IV.G.6–4 report the value of reductions in air pollution and climate-related externalities resulting from lower emi ssions of criteria air pollutants and GHGs during fuel production and consumption, while line 10 reports the savings in energy security externalities to the U.S. economy from reduced consumption and imports of petroleum and refined fuel. Line 12 reports th e costs of increased congestion delays, accidents, and noise that result from additional driving due to the fuel economy rebound effect. Net external benefits from the proposed CAFE standards (line 13) are thus the sum of the change in fuel tax revenues, the reduction in environmental and energy security externalities, and increased external costs from added driving.

Line 14 of Table IV.G.6–4 shows manufacturer s’ technology outlays for meeting higher CAFE standards for passenger cars and light trucks, which represent the principal private and social cost of requiring higher fuel economy. Th e net social benefits (line 15 of the table) resulting from the proposed rule consist of the sum of private (line 6) and external (line 13) benefits, minus technology costs (line 14). As expected, the figures reported in line 15 of the table are identical to those reported previously in Table IV.G.4-10.

Table IV.G.6–4 highlights several important features of this rule’s economic impacts. First, comparing the rule’s net private (line 6) and external (line 13) benefits makes it clear that a very large proportion of the proposed rule’s benefits would be experienced by vehicle buyers, while the small remaining fraction would be experienced throughout the remainder of the U.S. economy. In turn, the vast majority of private benefits resulting from the higher fuel economy levels the proposed rule would require stem from fuel savings to vehicle buyers. Net external benefits from the proposed rule are expected to be small, because the value of reductions in environmental and energy security externalities is likely almost exactly offset by the increased costs associated with added vehicle use. As a consequence, the net social benefits of the rule mirror almost exactly its net private benefits to vehicle buyers, under the assumption that manufacturers will recover their technology outla ys for achieving higher fuel economy by raising new car and light truck prices. Once again, this result highlights the extreme importance of accounting for any other effects of the rule on the economic welfare of vehicle buyers.

T ABLE IV.G.6-4 A

. P RIVATE , S OCIAL , AND T OTAL B ENEFITS AND C OSTS OF MY S 2017- 2021 CAFE S TANDARDS

– P ASSENGER C ARS P LUS L IGHT T RUCKS (3% DISCOUNT RATE )

Entry Model Year
2017 2018 2019 2020 2021 1. Value of fuel savings (at retail prices) $7.7 $16.1 $29.1 $39.4 $50.9 2. Savings in refueling time $0.4 $0.7 $1.1 $1.5 $1.8 3. Consumer surplus from added driving $0.0 $0.1 $0.3 $0.4 $0.5

781 Strictly speaking, fuel taxes represent a transfer of res ources from consumers of fuel to government agencies and not a use of economic resources. Reducing the volume of fuel purchases simply reduces the value of this transfer, and thus cannot produce a real economic cost or benefit. Re presenting the change in fuel tax revenues in effect as an economy-wide cost is necessary to of fset the portion of fuel savings included in line 1 that represents savings in fuel tax payments by consumers. This prevents the savi ngs in tax revenues from being counted as a benefit from the economy-wide perspective.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 731 of 768 4. Total private benefits (= 1 + 2 + 3) $8.1 $16.9 $30.5 $41.3 $53.2 5. Reduction in private benefits from changes in other vehicle attributes $0.0 $0.0 $0.0 $0.0 $0.0 6. Net private benefits (= 4 + 5) $8.1 $16.9 $30.5 $41.3 $53.2 7. Change in fuel tax revenues ($0.8) ($1.7) ($3.1) ($4.1) ($5.2) 8. Reduced health damages from criteria emissions $0.2 $0.5 $0.9 $1.2 $1.6 9. Reduced climate damages from CO 2 emissions $0.7 $1.5 $2.8 $3.8 $4.9 10. Reduced energy security externalities $0.4 $0.8 $1.4 $1.8 $2.4 11. Reduction in externalities (= 8 + 9 + 10) $1.3 $2.8 $5.1 $6.9 $8.9 12. Increased costs of congestion, etc. ($0.5) ($1.0) ($1.9) ($2.4) ($3.0) 13. Net external benefits (= 7 + 11 + 12) ($0.0) $0.1 $0.1 $0.3 $0.7 14. Technology costs ($2.0) ($4.4) ($7.7) ($11.3) ($15.2) 15. Net social benefits (= 6 + 13 – 14) $6.0 $12.5 $22.9 $30.3 $38.7

T ABLE IV.G.6-4 B

. P RIVATE , S OCIAL , AND T OTAL B ENEFITS AND C OSTS OF MY S 2022- 2025 AND T OTAL MY S 2017-2025 CAFE S TANDARDS

– P ASSENGER C ARS P LUS L IGHT T RUCKS

Entry Model Year

2022 2023 2024 2025 Total,2017-
2025 1. Value of fuel savings (at retail fuel prices) $57.9 $67.7 $76.9 $87.8 $433.4 2. Savings in refueling time $2.0 $2.1 $2.3 $2.5 $14.3 3. Consumer surplus from added driving $0.6 $1.0 $1.3 $1.8 $6.1 4. Total private benefits (= 1 + 2 + 3) $60.5 $70.9 $80.5 $92.1 $453.8 5. Reduction in private benefits from changes in other vehicle attributes $0.0 $0.0 $0.0 $0.0 $0.0 6. Net private benefits (= 4 +52) $60.5 $70.9 $80.5 $92.1 $453.8 7. Change in fuel tax revenues ($5.9) ($6.8) ($7.7) ($8.7) ($44.2) 8. Reduced health damages from criteria emissions $1.8 $2.1 $2.3 $2.5 $13.2 9. Reduced climate damages from CO 2 emissions $5.7 $6.7 $7.7 $8.9 $42.6 10. Reduced energy security externalities $2.7 $3.1 $3.5 $4.1 $20.1 11. Reduction in externalities (= 8 + 9 + 10) $10.2 $11.9 $13.6 $15.4 $76.0 12. Increased costs of congestion, etc. ($3.4) ($4.1) ($4.6) ($5.5) ($26.5) 13. Net external benefits (= 7 + 11 + 12) $0.9 $0.9 $1.3 $1.1 $5.3 14. Technology costs ($17.4) ($22.2) ($26.0) ($29.4) ($135.6) 15. Net social benefits (= 6 + 13 – 14) $43.9 $49.6 $55.7 $63.8 $323.5DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 732 of 768 As discussed in detail previously, NHTSA beli eves that the aggregate benefits from this proposed rule amply justify its total costs, but it remains possible that the agency has overestimated the role of fuel savings to buye rs and subsequent owners of the cars and light trucks to which the higher CAFE standards it proposes would apply. It is also possible that the agency has failed to develop cost estimates that do not require manufacturers to make changes in vehicle attributes as part of their efforts to achieve higher fuel economy. To acknowledge these possibilities, NHTSA has examined their potential impact on its estimates of the proposed rule’s benefits and costs. This analysis, which ap pears in Chapter VIII of the Preliminary RIA accompanying this proposed rule, shows the rule’s economic impacts under alternative assumptions about the private benefits from higher fuel economy, and the value of potential changes in other vehicle attributes. We seek comment on that analysis and the discussion above.

7. What other impacts (quantitative and unquantifiable) will these proposed standards have?

In addition to the quantified benefits and costs of fuel economy standards, the final standards will have other impacts that we have not quantified in monetary terms. The decision on whether or not to quantify a particular impact depends on several considerations:

• How likely is it to occur, and can the magnitude of the impact reasonably be attributed to the outcome of this rulemaking? • Would quantification of its physical magnitude or economic value help NHTSA and the public evaluate the CAFE standard s that may be set in rulemaking? • Is the impact readily quantifiable in physical terms? • If so, can it readily be translated into an economic value? • Is this economic value likely to be material? • Can the impact be quantified with a sufficiently narrow range of uncertainty so that the estimate is useful?

NHTSA expects that this rulemaking will ha ve a number of genuine, material impacts that have not been quantified due to one or more of these considerations. In some cases, further research may yield estimates that are useful for future rulemakings.

Technology Forcing

The proposed rule will improve the fuel economy of the U.S. new vehicle fleet, but it will also increase the cost (and presumably, the pri ce) of new passenger cars and light trucks built during MYs 2017–2025. We anticipate that the cost, scope, and duration of this rule, as well as the steadily rising standards it requires, will cause automakers an d suppliers to devote increased attention to methods of improving vehicle fuel economy.

This increased attention will stimulate add itional research and engineering, and we anticipate that, over time, innovative approaches to reducing the fuel consumption of light duty vehicles will emerge. These innov ative approaches may reduce the cost of the proposed rule in its later years, and also increase the set of feasible technologies in future years. We have attempted to estimate the effect of learning ef fects on the costs of producing known technologiesDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 733 of 768 within the period of the rulemaking, which is one way that technologies become cheaper over time, and may reflect innovations in application and use of existing technologies to meet theproposed future. However, we have not attempted to estimate the extent to which not-yetinvented technologies will appear, either within the time period of the current rulemaking or that might be available after MY 2016. NHTSA seeks comment on whether there are quantifiable costs and benefits associated with the potent ial technology forcing effects of the proposed standards, and if so, how the agency should cons ider attempting to account for them in the final rule analysis.

Effects on Vehicle Maintenance, Operation, and Insurance Costs

Any action that increases the cost of new vehi cles will subsequently make such vehicles more costly to maintain, repair, and insure. In general, this effect can be expected to be a positive linear function of vehicle costs. The propo sed rule is estimated to raise vehicle costs by over $900 by 2025, and for some manufacturers costs will increase by as much as $1,000– $1,800. Depending on the retail price of the vehicle, this could represent a significant increase in the overall vehicle cost and subsequently increase insurance rates, operation costs, and maintenance costs. Comprehensive insurance costs are likely to be directly related to price increases, but liability premiums will go up by a smaller proportion because the bulk of liability coverage reflects the cost of personal injury. The impact on operation and maintenance costs is less clear, because the maintenance burden and useful life of each technology are not known. However, one of the common consequences of using more complex or innovative technologies is a decline in vehicle reliability and an increase in maintenance costs. Th ese costs ar e borne in part by vehicle manufacturers (through warranty costs, which are included in the indirect costs of production), and in part by vehicle owners. NHTSA believes that this effect is difficult to quantify for purposes of this proposed rule, but we seek comment on how we might attempt to do so for the final rule.

Effects on Vehicle Miles Traveled (VMT)

While NHTSA has estimated the impact of the rebound effect on the use of MY 2017-25 vehicles, we have not estimated how a change in new vehicle sales would impact aggregatevehicle use. Changes in new vehicle sales may be accompanied by complex but difficult-toquantify effects on overall vehicle use and its composition by vehicle type and age, because the same factors affecting sales of new vehicles are al so likely to influence their use, as well as how intensively older vehicles are used and when they are retired from service. These changes may have important consequences for total fleet-wide fuel consumption. NHTSA believes that this effect is difficult to quantify for purposes of this proposed rule, but we seek comment on how we might attempt to do so for the final rule, if comm enters agree that attempting quantification of this effect could be informative.

Effect on Composition of Passenger Car and Light Truck Sales

To the extent that manufacturers pass on costs to buyers by raising prices for new vehicle models, they may distribute these price increases across their model lineups in ways that affect the composition of their total sales. . To the extent that changes in the com position of sales occur,DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 734 of 768 this could affect fuel savings to some degree. However, NHTSA’s view is that the scope for such effects is relatively small, since most ve hicles will to some extent be impacted by the standards. Compositional effects might be im portant with respect to compliance costs for individual manufacturers, but are unlikely to be material for the rule as a whole.

NHTSA is continuing to develop methods of estimating the effects of these proposed standards on the sales of individual vehicle models, and plans to apply these methods in analyzing the impacts of its final CAFE standards for MY 2017-25. In the meantime, the agency seeks comment on the possibility that significant shifts in the composition of new vehicle sales by type or model could occur, the potential effects of such shifts on fuel consumption and fuel savings from the proposed standards, and methods for analyzing the potential extent and patterns of shifts in sales.

Effects on the Used Vehicle Market

The effect of this rule on the lifetimes, use, and retirement dates of older vehicles will be related to its effects on new vehicle prices, the fuel efficiency of new vehicle models, and total sales of new vehicles. Elsewhere in this anal ysis, NHTSA estimates that vehicle sales will increase, because the value of fuel savings resulting from improved fuel efficiency to the typical potential buyer of a new vehicle will outweigh th e average increase in new models’ costs. Under these circumstances, sales of new vehicles will ri se, while retirement rates of used vehicles are likely to increase slightly. This will cause th e “turnover” of the vehicle fleet—that is, the retirement of used vehicles and their replacemen t by new models—to accelerate slightly, thus accentuating the anticipated effect of the rule on fleet-wide fuel consumption and CO 2 emissions. However, if potential buyers value future fuel savings resulting from the increased fuel efficiency of new models at le ss than the increase in their average selling price, sales of new vehicles would decline, as would the rate at whic h used vehicles are retired from service. This effect will slow the replacement of used vehicles by new models, and thus partly offset the anticipated effects of the proposed rules on fuel use and emissions. NHTSA believes that this effect is difficult to quantify for purposes of this proposed rule, but we seek comment on methods for analyzing the effects on the use and retirement of older vehicles resulting from changes in new vehicle prices, fuel economy, fuel prices, etc., and how the agency could consider analyzing this issue for the final rule.

Impacts of Changing Fuel Composition on Costs, Benefits, and Emissions

EPAct, as amended by EISA, creates a Renewable Fuels Standard that sets targets for greatly increased usage of renewable fuels over th e next decade. The law requires fixed volumes of renewable fuels to be used—volumes that are not linked to actual usage of transportation fuels.

Ethanol and biodiesel (in the required volume s) may increase or decrease the cost of blended gasoline and diesel, depending on crude oil prices and tax subsidies offered forrenewable fuels. The potential extra cost of renewable fuels would be borne through a crosssubsidy: the price of every gallon of blended gasoline could rise sufficiently to pay for any extra cost of using renewable fuels in these blends. However, if the price of gasoline or dieselDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 735 of 768 increases enough, the consumer could actually realize a savings through the increased usage of renewable fuels. By reducing total fuel consumption, the CAFE standards proposed in this rule could tend to increase any necessary cross-subsidy per gallon of fuel, and hence raise the market price of transportation fuels, while there would be no change in the volume or cost of renewable fuels used.

These effects are indirectly incorporated in NHTSA’s analysis of the proposed CAFE rule because they are reflected in EIA’s projections of future gasoline and diesel prices in the Annual Energy Outlook, which incorporates in its baseline both a Renewable Fuel Standard and an CAFE standards.

The net effect of incorporating an RFS then might be to slightly reduce the benefits of the rule because affected vehicles might be driven slightly less if the RFS makes blended gasoline relatively more expensive, and because fuels bl ended with more ethanol emit slightly fewer greenhouse gas emissions per gallon. In addition, there might be corresponding benefit losses from the induced reduction in VMT. All of these effects are difficult to estimate, because of uncertainty in future crude oil prices, uncertainty in future tax policy, and uncertainty about how petroleum marketers will actually comply with the RFS, but they are likely to be small, because the cumulative deviation from baseline fuel consum ption induced by the final rule will itself be small.

Distributional Effects

The agency’s analysis of the proposed rule reports impacts only as nationwide aggregate or per-vehicle average values. NHTSA also shows the effects of the EIA high and low fuel price forecasts on the aggregate benefits in its sensitivit y analysis. Generally, this proposed rule would have its largest effects on individuals who purchase new vehicles produced during the model years it would affect (2017-25). New vehicle buyers who drive more than the agency’s estimates of average vehicle use will experi ence larger fuel savings and eco nomic benefits th an the average values reported in this NPRM, while those w ho drive less than our average estimates will experience smaller fuel savings and benefits. NHT SA believes that this effect is difficult to quantify for purposes of this proposed rule, but we seek comment on how we might attempt to do so for the final rule, if commenters agree that attempting quantification of this effect could be informative.

H. Vehicle Classification

Vehicle classification, for purposes of th e CAFE program, refers to whether NHTSA considers a vehicle to be a passenger car or a light truck, and thus subject to either the passenger car or the light truck standards. 782 As NHTSA explained in the MY 2011 rulemaking and in the MYs 2012-2016 rulemaking, vehicle classification is based in part on EPCA/EISA, and in part on NHTSA’s regulations. EPCA categorizes so me light 4-wheeled vehicles as “passenger automobiles” (cars) and the balance as “non-passenger automobiles” (light trucks). EPCA

782 For the purpose of the MYs 2012-2016 standards and this NPRM for the MYs 2017–2025 standards, EPA has agreed to use NHTSA’s regulatory definitions for dete rmining which vehicles would be subject to which CO 2 standards.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 736 of 768 defines passenger automobiles as any automobile (other than an automobile capable of offhighway operation) which NHTSA decides by ru le is manufactured primarily for use in the transportation of not more than 10 individuals. 783 NHTSA created regulatory definitions for passenger automobiles and light trucks, found at 49 CFR Part 523, to guide the agency and manufacturers in classifying vehicles.

Under EPCA, there are two general groups of automobiles that qualify as non-passenger automobiles or light trucks: (1 ) those defined by NHTSA in its regulations as other than passenger automobiles due to their having de sign features that indicate they were not manufactured “primarily” for transporting up to te n individuals; and (2) those expressly excluded from the passenger category by statute due to their capability for off-highway operation, regardless of whether they might have been manufactured primarily for passenger transportation. 784 49 CFR 523 directly tracks those two broad groups of non-passenger automobiles in subsections (a) and (b), respec tively. We note that NHTSA tightened the definition of light truck in the MY 2011 rulemaking to ensure that only vehicles that actually have 4WD will be classified as off-highway vehicles by reason of having 4WD (to prevent 2WD SUVs that also come in a 4WD “version” from qualifying automatically as “off-road capable” simply by reason of the existence of the 4WD version), which resulted in the reclassification of over 1 million vehicles from the truck fleet to the car fleet.

Since the original passage of EPCA, and consistently through the passage of EISA, Congress has expressed its intent that differen t vehicles with different characteristics and capabilities should be subject to different CAFE standards in two ways: first, through whether a vehicle is classified as a passenger car or as a light truck, and second, by requiring NHTSA to set separate standards for passenger cars and for light trucks. 785 Creating two categories of vehicles and requiring separate standards for each, however, can lead to two issues which may either detract from the fuel savings that the program is able to achieve, or increase regulatory burden for manufacturers simply because they are trying to meet market demand. Specifically,

1) If the stringency of the standards that NHTSA establishes seems to favor either cars or trucks, manufacturers may have incentive to change their vehicles’ characteristics in order to recl assify them and average them into the “easier” fleet; and 2) “Like” vehicles, such as the 2WD and 4WD versions of the same CUV, may have generally similar fuel economy-achieving capabilities, but different targets due to differences in the car and truck curves.

783 EPCA 501(2), 89 Stat. 901, codified at 49 U.S.C. 32901(a).

784 49 U.S.C. 32901(a)(18). The statute refers both to vehicles that are 4WD and to vehicles over 6,000 lbs GVWR as potential candidates for off-road capabi lity, if they also meet the “significan t feature . . . designed for off-highway operation” as defined by the Secretary. We note that we consider “AWD” vehicles as 4WD for purposes of this determination—they send power to all wheels of the vehicl e all the time, while 4WD vehicles may only do so part of the time, which appears to make them equal candidates for off-road capability given other necessary characteristics. We also underscore, as we have in the past, that despite comments in prior rulemakings suggesting that any vehicle that appears to be manufactured “primarily” for transporti ng passengers must be classified as a passenger car, the statute as currently written clearly provides that vehicl es that are off-highway capable are not passenger cars.

785 See

, e.g. , discussion of legislative history in 42 Fed. Reg. 38362, 38365-66 (Jul. 28, 1977).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 737 of 768 NHTSA recognizes that manufacturers may have an incentive to classify vehicles as light trucks if the fuel economy target for light trucks with a given footprint is less stringent than the target for passenger cars with the same footprint. This is often the case given the current fleet. Because of characteristics like 4WD and towing and hauling capacity (and correspondingly, although not necessarily, heavier weight), the ve hicles in the current light truck fleet are generally less capable of achieving higher fuel ec onomy levels as compared to the vehicles in the passenger car fleet. 2WD SUVs are the vehicles th at could be most readily redesigned so that they can be “moved” from the passenger car to the light truck fleet. A manufacturer could do this by adding a third row of seats, for example, or boosting GVWR over 6,000 lbs for a 2WD SUV that already meets the gr ound clearance requirements for “o ff-road capability.” A change like this may only be possible during a vehicle redesign, but since vehicles are redesigned, on average, every 5 years, at least some manufacturers could possibly choose to make such changes before or during the model years covered by this rulemaking, either because of market demands or because of interest in changing the vehicle’s classification.

NHTSA continues to believe that the definitions as they currently exist are consistent with the text of EISA and with Congress’ original intent. However, the time frame of this rulemaking is longer than any CAFE rulemaking that NHTSA has previously undertaken, and no one can predict with certainty how the market will change between now and 2025. The agency therefore has less assurance than in prior rulemakings that manufacturers will not have greater incentives and opportunities during that time frame to make more deliberate redesign efforts to move vehicles out of the car fleet and into the truck fleet in order to obtain the lower target, and potentially reducing overall fuel savings. Recognizing this possibility, we seek comment on how best to avoid it while still cla ssifying vehicles appropriately based on their characteristics and capabilities.

One of the potential options that we explored in the MYs 2012-2016 rulemaking for MYs 2017 and beyond was changing the definition of light truck to remove paragraph (5) of 49 CFR 523.5(a), which allows vehicles to be classified as light trucks if they have three or more rows of seats that can either be removed or folded flat to allow greater cargo-carrying capacity. NHTSA has received comments in the past arguing that vehicl es with three or more rows of seats, unless they are capable of transporting more than 10 in dividuals, should be classified as passenger cars rather than as light trucks because they would not need to have so many seats if they were not intended primarily to carry passengers.

NHTSA recognizes that there are arguments both for and against maintaining the definition as currently written for MYs 2017 and be yond. The agency continues to believe that three or more rows of seats that can be removed or folded flat is a reasonable proxy for a vehicle’s ability to provide expanded cargo space, consistent with the agency’s original intent in developing the light truck defini tions that expanded cargo space is a fundamentally “truck-like” characteristic. Much of th e public reaction to this definition, wh ich is mixed, tends to be visceral and anecdotal – for example, for parents with mini vans and multiple children, the ability of seats to fold flat to provide more room for child-related cargo may have been a paramount consideration in purchasing the vehicle, while for CUV owners with cramped and largely unused third rows, those extra seats may seem to have sp rung up entirely in resp onse to the regulation, rather than in response to the consumer’s n eed for utility. If we believe, for the sake ofDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 738 of 768 argument, that the agency’s decision might be reasonable from both a policy and a legal perspective whether we decided to change the defi nition or to leave it alone, the most important questions in making the decision become (1) whether removing 523.5(a)(5), and thus causing vehicles with three or more rows to be classified as passenger cars in the future, will save more fuel, and (2) if more fuel will be saved, at what cost.

In considering these questions in the MYs 2012-2016 rulemaking, NHTSA conducted an analysis in the final rule to attempt to consider the impact of moving these vehicles. We identified all of the 3-row vehicles in the baseline (MY 2008) fleet, 786 and then considered whether any could be properly classified as a light truck under a different provision of 49 CFR 523.5—about 40 vehicles were classifiable under § 523.5(b) as off-highway capable. We then transferred those remaining 3-row vehicles from th e light truck to the passenger car input sheets for the Volpe model, re-estimated the relative stringency of the passenger car and light truck standards, shifted the curves to obtain the same overall average required fuel economy as under the final standards, and ran the model to evaluate potential impacts (in terms of costs, fuel savings, etc.) of moving these vehicles. The agency’s hypothesis had been that moving 3-row vehicles from the truck to the car fleet would tend to bring the achieved fuel economy levels down in both fleets—the car fleet achieved levels could theoretically fall due to the introduction of many more vehicles that are relatively heav y for their footprint and thus comparatively less fuel economy-capable, while the truck fleet achieve d levels could theoretically fall due to the characteristics of the vehicles remaining in the fleet (4WDs and pickups, mainly) that are often comparatively less fuel economy-capable than 3-row vehicles, although more vehicles would be subject to the relatively more stringent passenger car standards, assuming the curves were not refit to the data.

As the agency found, however, moving the vehicles reduced the stringency of the passenger car standards by approximately 0.8 mpg on average for the five years of the rule, and reduced the stringency of the light truck standards by approximately 0.2 mpg on average for the five years of the rule, but it also resulted in approximately 676 million fewer gallons of fuel consumed (equivalent to about 1 percent of the reduction in fuel consumption under the final standards) and 7.1 mmt fewer CO2 emissions (equivalent to about 1 percent of the reduction in CO2 emissions under the final standards) over the lifetime of the MYs 2012–2016 vehicles. This result was attributable to slight differences (due to rounding precision) in the overall average required fuel economy levels in MYs 2012–2014, and to the retention of the relatively high lifetime mileage accumulation (compared to “trad itional” passenger cars) of the vehicles moved from the light truck fleet to the passenger car fleet. The net effect on technology costs was approximately $200 million additional spending on technology each year (equivalent to about 2 percent of the average increase in annual technology outlays under the final standards). Assuming manufacturers would pass that cost forw ard to consumers by increasing vehicle costs, NHTSA estimated that vehicle pri ces would increase by an average of approximately $13 during MYs 2012–2016. With less fuel savings and higher costs, and a substantial disruption to the industry, removing 523.5(a)(5) did not seem advisable in the context of the MYs 2012-2016 rulemaking.

786 Of the 430 light trucks models in the fleet, 175 of these had 3 rows.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 739 of 768 Looking forward, however, and given the considerable uncertainty regarding the incentive to reclassify vehicles in the MYs 2017 and beyond timeframe, the agency believes that a fresh look at this question is warranted. One important point to note in the comparative analysis in the MYs 2012-2016 rulemaking is that, due to time constraints, the agency did not attempt to refit the respective fleet target curves or to change the intended required stringency in MY 2016 of 34.1 mpg for the combined fleets. If we had refitted curves, considering the vehicles in question, we might have obtained a somewhat steeper passenger car curve, and a somewhat flatter light truck curve, which could have affected the agency’s findings.

There are several ways to analyze the impact of removing 523.5(a)(5) and moving vehicles accordingly from the light truck fleet to the passenger car fleet. The agency could: [analysis forthcoming, but could include:] 1) Move the vehicles and not refit curves or change stringency 2) Move the vehicles and refit curves, but not change stringency 3) Move the vehicles and refit curves and change stringency

The results from any of these methods would be somewhat speculative; for example, the agencies continue to use the same MY 2008 baseline used in the MYs 2012-2016 rulemaking, which may have limited utility for predicting re latively small changes (moving only 40 vehicles, as noted above) in the fleet makeup during the rulemaking timeframe.

[Results forthcoming]

The agency emphasizes that we are not proposing to remove 523.5(a)(5) at this time, but are simply seeking comment on the analysis above. We expect to update this analysis for the final rule, and based on the results we may consider making this change for the final rule, or at some point in a future rulemaking.

Another potential option that we explored in the MYs 2012-2016 rulemaking for MYs 2017 and beyond was classifying “like” vehicles together. Many commenters objected in the rulemaking for the MY 2011 standards to NHTSA’s regulatory separation of “like” vehicles. Industry commenters argued that it was technol ogically inappropriate for NHTSA to place 4WD and 2WD versions of the same SUV in separate classes. They argued that the vehicles are the same, except for their drivetrain features, thus giving them similar fuel economy improvement potential. They further argued that all SUVs shou ld be classified as light trucks. Environmental and consumer group commenters, on the other hand, argued that 4WD SUVs and 2WD SUVs that are “off-highway capable” by virtue of a GVWR above 6,000 pounds should be classified as passenger cars, since they are primarily used to transport passengers. In the MY 2011 rulemaking, NHTSA rejected both of these sets of arguments. NHTSA concluded that 2WD SUVs that were neither “off-highway capable” nor possessed “truck-like” functional characteristics were appropriately classified as pa ssenger cars. At the same time, NHTSA also concluded that because Congress explicitly de signated vehicles with GVWRs over 6,000 pounds as “off-highway capable” (if they meet the ground clearance requirements established by the agency), NHTSA did not have authority to move these vehicles to the passenger car fleet.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 740 of 768 NHTSA continues to believe that this would not be an appropriate solution for addressing either the risk of gaming or perceived regulatory inequity going forward. As explained in the MYs 2012-2016 final rule, with regard to the fi rst argument, that “like” vehicles should be classified similarly ( i.e., that 2WD SUVs should be classified as light trucks because, besides their drivetrain, they are “like” the 4WD version that qualifies as a light truck), NHTSA continues to believe that 2WD SUVs that do not meet any part of the existing regulatory definition for light trucks should be classified as passenger cars. However, NHTSA recognizes the additional point raised by industry co mmenters in the MY 2011 rulemaking that manufacturers may respond to this tighter classi fication by ceasing to build 2WD versions of SUVs, which could reduce fuel savings. In resp onse to that point, NHTSA stated in the MY 2011 final rule that it expects that manufacturer decisions about whether to continue building 2WD SUVs will be driven in much greater m easure by consumer demand than by NHTSA’s regulatory definitions. If it appears, in the course of the next several model years, that manufacturers are indeed responding to the CAFE regulatory definitions in a way that reduces overall fuel savings from expected levels, it may be appropriate for NHTSA to review this question again. At this time, however, since so little time has passed since our last rulemaking action, we do not believe that we have enough information about changes in the fleet to ascertain whether this is yet ripe for consideration. We seek comment on how the agency might go about reviewing this question as more information about manufacturer behavior is accumulated over time.

I. Compliance and Enforcement

1. Overview

NHTSA’s CAFE enforcement program is largely established by statute—unlike the CAA, EPCA, as amended by EISA, is very prescrip tive with regard to enforcement. EPCA and EISA also clearly specify a number of flexibilitie s that are available to manufacturers to help them comply with the CAFE standards. Some of those flexibilities are constrained by statute – for example, while Congress required that NHTSA allow manufacturers to transfer credits earned for over-compliance from their car fleet to their truck fleet and vice versa, Congress also limited the amount by which manufacturers co uld increase their CAFE levels using those transfers. 787 NHTSA believes Congress balanced the energy-saving purposes of the statute against the benefits of certain flexibilities and incentives and intentionally placed some limits on certain statutory flexibilities and incentives. With that goal in mind, of maximizing compliance flexibility while also implementing EPCA/EISA’s overarching purpose of energy conservation as fully as possible, NHTSA has done its best in crafting the credit transfer and trading regulations authorized by EISA to ensure that total fuel savings are preserved when manufacturers exercise their statutorily-provided compliance flexibilities.

Furthermore, to achieve the level of standards described in this proposal for the 2017– 2025 program, NHTSA expects automakers to continue increasing the use of innovative and advanced technologies as they evolve. Additional incentive programs may encourage early adoption of these innovative and advanced technologies and help to maximize both compliance flexibility and energy conservation. These incentive programs for CAFE compliance would not

787 See 49 U.S.C. 32903(g).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 741 of 768 be under NHTSA’s EPCA/EISA authority, but under EPA’s EPCA authority – as discussed in more detail below and in Section III of th is preamble, EPA measures and calculates manufacturer compliance with the CAFE standards, and it would be in the calculation of fuel economy levels that additional incentives would most appropriately be applied, as a practical matter. Specifically, to be included in the CA FE program, EPA is proposing: 1) fuel economy performance adjustments due to improvements in air conditioning system efficiency; 2) utilization of “game changing” technologies in stalled on full size pick-up trucks including hybridization; and 3) installation of “off-cycle” technologies. In addition, for model years 2020 and later, EPA is proposing calculation methods for dual-fueled vehicles, to fill the gap left in EPCA/EISA by the expiration of the dual-fuel incentive. A more thorough description of the basis for the new incentive programs can be found in Section III.

The following sections explain how NHTSA determines whether manufacturers are in compliance with the CAFE standards for each model year, and how manufacturers may address potential non-compliance situations through the use of compliance flexibilities or fine payment. The following sections also explain, for the read er’s reference, the proposed new incentives and calculations, but we also refer readers to Sectio n III.C for EPA’s explanation of its authority and more specific detail regarding these proposed changes to the CAFE program.

2. How does NHTSA determine compliance?

a. Manufacturer Submission of Data and CAFE Testing by EPA

NHTSA begins to determine CAFE compliance by reviewing projected estimates in preand mid-model year reports submitted by manufacturers pursuant to 49 CFR part 537, Automotive Fuel Economy Reports. 788 Those reports for each compliance model year are submitted to NHTSA by December of the calendar year prior to the corresponding subsequentmodel year (for the pre-model year report) and in July of the given model year (for the midmodel year report). NHTSA has already received pre-and mid-model year reports from manufacturers for MY 2011. NHTSA uses these reports for reference to help the agency, and the manufacturers who prepare them, anticipate potentia l compliance issues as early as possible, and help manufacturers plan compliance strategies. NHTSA also uses the reports for auditing and testing purposes, which helps manufacturers correct errors prior to the end of the model year and facilitates acceptance of their final CAFE report by EPA. In addition, NHTSA issues reports to the public twice a year that provide a summary of manufacturers’ fleet fuel economy projected performances using pre- and mid model year data. Currently, NHTSA receives manufacturers’ CAFE reports in paper form. In order to facilitate submission by manufacturers, NHTSA amended part 537 to allow for electronic submission of the pre- and mid-model year CAFE reports in 2010 (see 75 FR 25324). Electronic reports are optional and must be submitted in a pdf format. NHTSA proposes to modify these provisions in this NPRM, as described below, in order to eliminate hardcopy submissions and help the agency more readil y process and utilize the electronically-submitted data.

788 49 CFR part 537 is authorized by 49 U.S.C. 32907.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 742 of 768 Throughout the model year, NHTSA audits manufacturers’ reports and conducts vehicle testing to confirm the accuracy of track width and wheelbase measurements as a part of its footprint validation program, 789 which helps the agency understand better how manufacturers may adjust vehicle characteristics to change a vehicle’s footprint measurement, and thus its fuel economy target. NHTSA resolve discrepancies w ith the manufacturer prio r to the end of the calendar year corresponding to the respective model year with the primary goal of manufacturers submitting accurate final reports to EPA. NHTSA makes its ultimate determination of a manufacturer’s CAFE compliance obligation based on official reported and verified CAFE data received from EPA. Pursuant to 49 U.S.C. 32904(e), EPA is responsible for calculating manufacturers’ CAFE values so that NHTSA can determine compliance with its CAFE standards. The EPA-verified data is based on any considerations from NHTSA testing, its own vehicle testing, and final model year data submitted by manufacturers to EPA pursuant to 40 CFR 600.512. A manufacturer’s final model year report must be submitted to EPA no later than 90 days after December 31 st of the model year. EPA test procedures including those used to establish the new incentive fuel economy performance values for model year 2017 to 2025 vehicles are contained in sections 40 CFR Part 600 and 40 CFR Part 86.

b. NHTSA Then Analyzes EPA-Certified CAFE Values for Compliance

NHTSA’s determination of CAFE compliance is fairly straightforward: after testing, EPA verifies the data submitted by manufacturers and issues final CAFE reports sent to manufacturers and to NHTSA in a pdf format betw een April and October of each year (for the previous model year), and NHTSA then identifies the manufacturers’ compliance categories (fleets) that do not meet the applicable CAFE fleet standards. NHTSA plans to construct a new, more automated database system in the near future to store manufacturer data and the EPA data. The new database is expected to simplify data submissions to NHTSA, improve the quality of the agency’s data, expedite public reporting, improve audit verifications and testing, and enable more efficient tracking of manufacturers’ CAFE credits with greater transparency.

NHTSA uses the verified data from EPA to compare fleet average standards with performance. A manufacturer complies with NHTSA’s fuel economy standard if its fleet average performance is greater than or equal to its required standard, or if it is able to use available compliance flexibilities to resolve its non-compliance difference. NHTSA calculates a cumulative credit status for each of a manufactur er’s vehicle compliance categories according to 49 U.S.C. 32903. If a manufacturer’s compliance category exceeds the applicable fuel economy standard, NHTSA adds credits to the account for that compliance category. The amount of credits earned in a given year are determined by multiplying the number of tenths of an mpg by which a manufacturer exceeds a standard for a particular category of automobiles by the total volume of automobiles of that category manufactured by the manufacturer for that model year.Credits may be used to offset shortfalls in other model years, subject to the three year “carryback” and five-year “carry-forward” limitations specified in 49 U.S.C. 32903(a); NHTSA does not have authority to allow credits to be carried forward or back for periods longer than that specified in the statute. A manufacturer ma y also transfer credits to another compliance

789 See http://www.nhtsa.gov/DOT/NHTSA/Vehicle%20Saf ety/Test%20Procedures/Associated%20Files/TP-537- 01.pdfDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 743 of 768 category, subject to the limitations specified in 49 U.S.C. 32903(g)(3), or trade them to another manufacturer. The value of each credit received via trade or transfer, when used for compliance, is adjusted using the adjustment factor described in 49 CFR 536.4, pursuant to 49 U.S.C. 32903(f)(1).

If a manufacturer’s vehicles in a particular compliance category fall below the standard fuel economy value, NHTSA will provide written notification to the manufacturer that it has not met a particular fleet standard. The manufacturer will be required to confirm the shortfall and must either submit a pl an indicating it will allocate existing credits, or if it does not have sufficient credits available in that fleet, how it wi ll earn, transfer and/or acquire credits, or pay the appropriate civil penalty. The manufacturer must submit a plan or payment within 60 days of receiving agency notification. Credit allocation plans received from the manufacturer will be reviewed and approved by NHTSA. NHTSA will ap prove a credit allocation plan unless it finds the proposed credits are unavaila ble or that it is unlikely that the plan will result in the manufacturer earning sufficient credits to offset the subject credit shortfall. If a plan is approved, NHTSA will revise the manufacturer’s credit account accordingly. If a plan is rejected, NHTSA will notify the manufacturer and request a revised plan or payment of the appropriate fine.

In the event that a manufacturer does not comply with a CAFE standard even after the consideration of credits, EPCA provides for the assessment of civil penalties. The Act specifies a precise formula for determining the amount of civil penalties for noncompliance. 790 The penalty, as adjusted for inflation by law, is $5.50 for each tenth of a mpg that a manufacturer’s average fuel economy falls short of the standard for a given model year multiplied by the total volume of those vehicles in the affected fleet ( i.e., import or domestic passenger car, or light truck), manufactured for that model year. The amount of the penalty may not be reduced except under the unusual or extr eme circumstances specified in the statute. All penalties are paid to the U.S. Treasury and not to NHTSA itself.

Unlike the National Traffic and Motor Vehicl e Safety Act, EPCA does not provide for recall and remedy in the event of a noncompliance. The presence of recall and remedy provisions 791 in the Safety Act and their absence in EPCA is believed to arise from the difference in the application of the safety standards and CAFE standards. A safety standard applies to individual vehicles; that is, each vehicle must possess the requisite equipment or feature that must provide the requisite type and level of performance. If a vehicle does not, it is noncompliant. Typically, a vehicle does not entirely lack an item or equipment or feature. Instead, the equipment or features fails to perform adequately. Recalling th e vehicle to repair or replace the noncompliant equipment or feature can usually be readily accomplished.

In contrast, a CAFE standard applies to a manufacturer’s entire fleet for a model year. It does not require that a particular individual vehicle be equipped with any particular equipment or feature or meet a particular level of fuel economy. It does require that the manufacturer’s fleet, as a whole, comply. Further, although under th e attribute-based approach to setting CAFE standards fuel economy targets are established for individual vehicles based on their footprints,

790 See 49 U.S.C. 32912.

791 49 U.S.C. 30120, Remedies for defects and noncompliance.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 744 of 768 the vehicles are not required to comply with those targets on a model-by-model or vehicle-byvehicle basis. However, as a practical matter, if a manufacturer chooses to design some vehicles so they fall below their target levels of fuel economy , it will need to design other vehicles so they exceed their targets if the manufacturer’s overall fl eet average is to meet the applicable standard. Thus, under EPCA, there is no such thi ng as a noncompliant vehicle, only a noncompliant fleet. No particular vehicle in a noncompliant fleet is any more, or less, noncompliant than any other vehicle in the fleet.

After enforcement letters are sent, NHTSA continues to monitor receipt of credit allocation plans or civil penalty payments that are due within 60 days from the date of receipt of the letter by the vehicle manufacturer, and takes further action if the manufacturer is delinquent in responding. If NHTSA receives and approves a manufacturer’s carryback plan to earn future credits within the following three years in order to comply with current regulatory obligations, NHTSA will defer levying fines for non-complian ce until the date(s) when the manufacturer’s approved plan indicates that credits will be earned or acquired to achieve compliance, and upon receiving confirmed CAFE data from EPA. If the manufacturer fails to acquire or earn sufficient credits by the plan dates, NHTSA will initia te compliance proceedings. 49 CFR part 536 contains the detailed regulations governing the use and application of CAFE credits authorized by 49 U.S.C. 32903.

3. What compliance flexibilities are available under the CAFE program and how do manufacturers use them?

There are three basic flexibilities outlined by EPCA/EISA that manufacturers cancurrently use to achieve compliance with CAFE standards beyond applying fuel economyimproving technologies: (1) Building dual- and al ternative-fueled vehicles; (2) banking (carryforward and carry-back), trading, and transferring credits earned for exceeding fuel economy standards; and (3) paying civil penalties. We not e that while these flexibility mechanisms will reduce compliance costs to some degree for most manufacturers, 49 U.S.C. 32902(h) expressly prohibits NHTSA from considering the availability of statutorily-established credits (either for building dual- or alternative-fueled vehicles or from accumulated transfers or trades) in determining the level of the standards. Thus, NHTSA may not raise CAFE standards because manufacturers have enough of those credits to meet higher standards. This is an important difference from EPA’s authority under the CAA, which does not contain such a restriction, and which allows EPA to set higher standards as a result.

a. Dual- and Alternative-Fueled Vehicles

As discussed at length in prior rulemakings, EPCA encourages manufacturers to build alternative-fueled and dual- (or flexible-) fueled vehicles by providing special fuel economy calculations for “dedicated” (that is, 100 percent) alternative fueled vehicles and “dual-fueled” (that is, capable of running on either the alternative fuel or gasoline/diesel) vehicles. Consistent with the overarching purpose of EPCA/EISA, these statutory incentives help to reduce petroleum usage and thus improve our nation’s energy security. Per EPCA, the fuel economy of a dedicated alternative fuel vehicle is determined by dividing its fuel economy in equivalent milesDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 745 of 768 per gallon of gasoline or diesel fuel by 0.15. 792 Thus, a 15 mpg dedicated alternative fuel vehicle would be rated as 100 mpg.

For dual-fueled vehicles, EPA measures the vehicle’s fuel economy rating by determining the average of the fuel economy on gasoline or diesel and the fuel economy on the alternative fuel vehicle divided by 0.15. 793 This calculation procedure, provided in EPCA, turns a dual-fueled vehicle that averages 25 mpg on gaso line or diesel into a 40 mpg vehicle for CAFE purposes. This assumes that (1) the vehicle operates on gasoline or diesel 50 percent of the time and on alternative fuel 50 percent of the time; (2) fuel economy while operating on alternative fuel is 15 mpg (15/.15 = 100 mpg); and (3) fuel economy while operating on gas or diesel is 25 mpg. Thus:

CAFE FE = 1/{0.5/(mpg gas) + 0.5/(mpg alt fuel)} = 1/{0.5/25 + 0.5/100} = 40 mpg

In the case of natural gas, EPA’s calculation is performed in a similar manner. The fuel economy is the weighted average while operating on natural gas and operating on gas or diesel. The statute specifies that 100 cubic feet (ft 3 ) of natural gas is equivalent to 0.823 gallons of gasoline. The CAFE fuel economy while operating on the natural gas is determined by dividing its fuel economy in equivalent miles per gallon of gasoline by 0.15. 794 Thus, if a vehicle averages 25 miles per 100 ft 3 of natural gas, then:

CAFE FE = (25/100) * (100/.823)*(1/0.15) = 203 mpg

Congress extended the dual-fueled vehicle incentive in EISA for dual-fueled automobiles through MY 2019, but provided for its phase-out between MYs 2015 and 2019. 795 The maximum fleet fuel economy increase attributable to this statutory incentive is thus as follows:

Model year mpg increase
MYs 1993-2014............ ......................... 1.2
MY 2015........................ ..................... 1.0
MY 2016........................ ..................... 0.8
MY 2017........................ ..................... 0.6
MY 2018........................ ..................... 0.4
MY 2019........................ ..................... 0.2

792 49 U.S.C. 32905(a).

793 49 U.S.C. 32905(b).

794 49 U.S.C. 32905(c).

795 49 U.S.C. 32906(a). NHTSA notes that the incentive for dedi cated alternative-fuel automobiles, automobiles that run exclusively on an alternative fuel, at 49 U.S.C. 32905(a), was not phased-out by EISA. We note additionally and for the reader’s reference that EPA will be treating dual- and alternative-fueled vehicles under its GHG program similarly to the way EP CA/EISA provides for CAFE through MY 2015, but for MY 2016, EPA established CO 2 emission levels for alternative fuel ve hicles based on measurement of actual CO2 emissions during testing, plus a manufacturer demonstrat ion that the vehicles are actually being run on the alternative fuel. The manufacturer would then be allowed to weight the gasoline and alternative fuel test results based on the proportion of actual usage of both fuel s. Because EPCA/EISA provides the explicit CAFE measurement methodology for EPA to use for dedicated ve hicles and dual-fueled vehicles through MY 2019, we explained in the MYs 2012-2016 final rule that the CAFE pr ogram would not require that vehicles manufactured for the purpose of obtaining the credit actually be run on the alternative fuel.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 746 of 768 After MY 2019....................................... 0

49 CFR part 538 codifies in regulation the statutory alternative-fueled and dual-fueled automobile manufacturing incentive. For purposes of consistency with the statute and to implement our intent in the MYs 2012-2016 rule, NHTSA is updating 49 CFR 538.9 to incorporate the 49 U.S.C. 32906(a) phase-out of the statutory incentive described above.

Given that the statutory incentive for dual-fuel ed vehicles in 49 U.S.C. 32906 and the measurement methodology specified in 49 U.S.C. 32905(b) and (d) expire in MY 2019, the question becomes, how should the fuel economy of dual-fueled vehicles be determined for CAFE compliance in MYs 2020 and beyond? NHTSA and EPA believe that the expiration of the dual-fueled vehicle measurement methodology in the statute leaves a gap to be filled, to avoid the absurd result of dual-fueled vehicles’ fuel economy being measured like that of conventional gasoline vehicles. If the overarchin g purpose of the statute is energy conservation and reducing petroleum usage, the agencies believe that that goal is best met by continuing to reflect through CAFE calculations the reduced petroleum usage that dual-fueled vehicles achieve.

As discussed in more detail in Section III.B.10, for MYs 2020 and beyond, to fill the gap left by the expiration of the statutory CAFE measurement methodology for dual-fueled vehicles, EPA is proposing to harmonize with the approach it uses under the GHG program to measure the emissions of dual-fueled vehicles, to reflect the real-world percentage of usage of alternative fuels by dual-fueled vehicles, but also to contin ue to incentivize the use of certain alternative fuels in dual-fueled vehicles as appropriate under EPCA/EISA to reduce petroleum usage. Specifically, for MYs 2020 and beyond, EPA will calculate the fuel economy test values for a plug-in hybrid electric vehicle (PHEV, that runs on both gasoline and electricity) and for CNGgasoline vehicles on both the alternative fuel an d on gasoline, but rather than assuming that the dual-fueled vehicle runs on the alternative fuel 50 percent of the time as the current statutory measurement methodology requires, EPA will inst ead use the Society of Automotive Engineers (SAE) “utility factor” methodology (based on vehicle range on the alternative fuel and typical daily travel mileage) to determine the assumed percentage of operation on gasoline/diesel and percentage of operation on the alternative fuel for those vehicles. Using the utility factor, rather than making an a priori assumption about the amount of alternative fuel used by dual-fueled vehicles, recognizes that once a consumer has paid several thousand dollars to be able to use a fuel that is considerably cheaper than gasoline or diesel, it is very likely that the consumer will seek to use the cheaper fuel as much as possib le. Consistent with this approach, however, EPA is not proposing to extend the utility factor method to flexible fueled vehicles (FFVs) that use E– 85 and gasoline, since there is not a significant cost differential between an FFV and conventional gasoline vehicle and historically c onsumers have only fueled these vehicles with E85 a very small percentage of the time. Therefore, EPA is proposing for CAFE compliance in MYs 2020 and beyond to continue treatment of E85 and other FFVs as finalized in the MY 2016 GHG program, based on actual usage of the alternative fuel which represents a real-world reduction attributed to alternative fuels.

Additionally, to avoid manufacturers buildin g only dedicated alternative fuel vehicles (which may be harder to refuel in some instances) because of the continued statutory 0.15 CAFEDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 747 of 768 divisor under 49 U.S.C. 32905(a) and the calculation for EV fuel economy under 49 U.S.C. 32904, and declining to build dual-fueled vehicles which might not get a similar bonus, EPA is proposing to use the Petroleum Equivalency Factor (PEF) and a 0.15 divisor for calculating the fuel economy of PHEVs’ electrical operation and for natural gas operation of CNG-gasoline vehicles. This is consistent with the statutory approach for dedicated alternative fuel vehicles, and continues to incentivize the usage of alternative fuels and reduction of petroleum usage, but when combined with the utility factor approach described above, does not needlessly over

incentivize their usage – it gives credit for what is used, and does not give credit for what is not used. Because it does not give credit for what is not used, EPA would propose that manufacturers may increase their calculated fleet fuel economy for dual-fueled vehicles by an unlimited amount using these flexibilities.

As an example, for MYs 2020 and beyond, the calculation procedure for a dual-fueled vehicle that uses both gasoline and CNG could re sult in a combined fuel economy value of 150 mpg for CAFE purposes. This assumes that (1) the “utility factor” for the alternative fuel is found to be 95 percent, and so the vehicle operates on gasoline for the remaining 5 percent of the time; (2) fuel economy while operating on natural gas is 203 mpg [(25/100) * (100/.823)*(1/0.15)] as shown above utilizing the PEF and the .15 incentive factor; and (3) fuel economy while operating on gasoline is 25 mpg. Thus:

CAFE FE = 1/{0.05/(mpg gas) + 0.95/(mpg CNG)} = 1/{0.05/25 + 0.95/203} = 150 mpg

The agencies seek comment on this approach.

b. Credit Trading and Transfer

As part of the MY 2011 final rule, NHTSA created 49 CFR part 536 for credit trading and transfer. Part 536 implements the provisio ns in EISA authorizing NHTSA to establish by regulation a credit trading program and directing it to establish by regula tion a credit transfer

program. 796 Since its enactment, EPCA has permitted manufacturers to earn credits for exceeding the standards and to carry those credits backward or forward. EISA extended the “carry-forward” period from three to five model years, and left the “carry-back” period at three model years. Under part 536, credit holders (i ncluding, but not limited to, manufacturers) will have credit accounts with NHTSA, and will be able to hold credits, use them to achieve compliance with CAFE standards, transfer them between compliance categories, or trade them. A credit may also be cancelled before its expiration date, if the credit holder so chooses. Traded and transferred credits are subject to an “adjustment factor” to ensure total oil savings are preserved, as required by EISA. 797 EISA also prohibits credits earned before MY 2011 from being transferred, so NHTSA has developed several regulatory restrictions on trading and transferring to facilitate Congress’ intent in this regard. As discussed above, EISA establishes a

796 Congress required that DOT establish a credit “transfe rring” regulation, to allow individual manufacturers to move credits from one of their fleets to another ( e.g., using a credit earned for exceeding the light truck standard for compliance with the domestic passenger car standard). Congress allowed DOT to establish a credit “trading” regulation, so that credits may be bought and sold between manufacturers and other parties.

797 NHTSA is proposing to revise the VMT estimates used in the credit adjustment factor for consistency with EPA starting in 2017.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 748 of 768 “cap” for the maximum increase in any compliance category attributable to transferred credits: for MYs 2011–2013, transferred credits can only be used to increase a manufacturer’s CAFE level in a given compliance category by 1.0 mpg; for MYs 2014–2017, by 1.5 mpg; and for MYs 2018 and beyond, by 2.0 mpg. No changes are proposed for these Part 536 provisions.

c. Payment of Civil Penalties

If a manufacturer’s average miles per gallon for a given compliance category (domestic passenger car, imported passenger car, light truck) falls below the applicable standard, and the manufacturer cannot make up the difference by using credits earned or acquired, the manufacturer is subject to penalties. The penalty, as mentioned, is $5.50 for each tenth of a mpg that a manufacturer’s average fuel economy falls short of the standard for a given model year, multiplied by the total volume of those vehicles in the affected fleet, manufactured for that model year. NHTSA has collected $794,921,139.50 to date in CAFE penalties, the largest ever being paid by DaimlerChrysler for its MY 2006 import passenger car fleet, $30,257,920.00. For their MY 2009 fleets, six manufacturers paid CAFE fi nes for not meeting an applicable standard— Fiat, which included Ferrari, Maserati, and Alfa Romeo; Daimler (Mercedes-Benz); Porsche; and Tata (Jaguar Land Rover)—for a total of $9,148,425.00. As mentioned above, civil penalties paid for CAFE non-compliance go to the U.S. Treasury, and not to DOT or NHTSA.

NHTSA recognizes that some manufacturers may use the option to pay civil penalties asa CAFE compliance flexibility—presumably, when paying civil penalties is deemed more costeffective than applying additional fuel economy-improving technology, or when adding fuel economy-improving technology would fundamentally change the characteristics of the vehicle in ways that the manufacturer believes its targ et consumers would not accept. NHTSA has no authority under EPCA/EISA to prevent manufacturers from turning to payment of civil penalties if they choose to do so. This is another important difference from EPA’s authority under the CAA, which allows EPA to revoke a manufacturer’s certificate of conformity that permits it to sell vehicles if EPA determines that the manufacturer is in non-compliance, and does not permit manufacturers to pay fines in lieu of compliance with applicable standards.

NHTSA has grappled repeatedly with the issue of whether civil penalties are motivational for manufacturers, and whether raising them would increase manufacturers’ compliance with the standards. EPCA authorizes increasing the civil penalty very slightly up to $10.00, exclusive of inflationary adjustments, if NHTSA decides that the increase in the penalty “will result in, or substantially further, substantial energy cons ervation for automobiles in the model years in which the increased penalty may be imposed; and will not have a substantial deleterious impact on the economy of the United States, a State, or a region of a State.” 49 U.S.C. 32912(c).

To support a decision that increasing the penalty would result in “substantial energy conservation” without having “a substantial deleterious impact on the economy,” NHTSA would likely need to provide some reasonably certain qua ntitative estimates of the fuel that would be saved, and the impact on the economy, if the penalty were raised. Comments received on this issue in the past have not explained in clear quantitative terms what the benefits and drawbacks to raising the penalty might be. Additionally, it may be that the range of possible increase that the statute provides, i.e., up to $10 per tenth of a mpg, is in sufficient to result in substantialDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 749 of 768 energy conservation, although changing this would require an amendment to the statute by Congress. NHTSA continues to seek to gain information on this issue and requests that commenters wishing to address this issue please prov ide, as specifically as possible, estimates of how raising or not raising the penalty amount will or will not substantially raise energy conservation and impact the economy.

4. What new incentives are being added to the CAFE program for MYs 2017- 2025?

All of the CAFE compliance incentives discussed below are being proposed by EPA under its EPCA authority to calculate fuel economy levels for individual vehicles and for fleets. Because they are EPA proposals, we refer the reader to Section III for more details, as well as Chapter 5 of the draft Joint TSD for more in formation on the precise mechanics of the incentives, but we present them here in summary form so that the reader may understand more comprehensively what compliance options are proposed to be available for manufacturers for meeting the MYs 2017-2025 CAFE standards.

a. “Game Changing” technologies for full size pick-up trucks

EPA is proposing to adopt two new types of incentives for improving the fuel economy performance of full size pickup trucks. The first incentive would provide a credit to manufacturers that employ significant quantities of hybridization on full size pickup trucks. The second incentive would provide a performance-based incentive for full size pickup trucks that achieve a significant reduction in fuel consumption as compared to the applicable fuel economy target for the vehicle in question. These incentiv es are proposed due to the significant difficulty of large trucks, including full size pickup trucks, in meeting CAFE standards while still maintaining the levels of utility to which consumers have become accustomed, which require higher payload and towing capabilities and greater cargo volumes than other light-duty vehicles. Technologies that provide substantial fuel economy benefits are often not attractive to manufacturers of large trucks due to these tradeo ffs in utility purposes, and therefore have not been taken advantage of to the same extent as they have in other vehicle classes. The goal of these incentives is to facilitate the applicati on of these “game changing” technologies for large pickups, both to save more fuel and to help provide a bridge for industry to more stringent lighttruck standards in MYs 2022-2025 – as manufacturers gain experience with applying more fuelsaving technology for these vehicles and consumers become more accustomed to certain advanced technologies in pickup trucks, the agencies anticipate that higher CAFE levels will be more feasible for the fleet as a whole. 798 In the context of the CAFE program, these incentives would be used as an adjustment to a full si ze pickup truck’s fuel economy performance. The same vehicle would not be allowed to receive an adjustment to its calculated fuel economy for both the hybridization incentive and the performance-based incentive, to avoid double-counting.

To accommodate the proposed changes to the CAFE program, NHTSA is proposing to adopt new definitions into regulation, 49 CFR 523, “Vehicle Classification.” Part 523 was

798 NHTSA is not prohibited from considering this availa bility of this incentive in determining the maximum feasible levels of stringency for the light truck standard s, because it is not one of the statutory flexibilities enumerated in 49 U.S.C. 32902(h).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 750 of 768 established by NHTSA to include its regulatory de finitions for passenger automobiles and trucks and to guide the agency and manufacturers in cl assifying vehicles. NHTSA proposes to add a definition in Part 523.2 defining the characteristic s that identify full size pickup trucks. NHTSA believes that the definition is needed to help explain to readers which characteristics of full size pickup truck make them eligible to gain fuel economy improvement values allowed after a manufacturer meets either a minimum penetrati on of hybridized technologies or has other technologies that significantly reduce fuel consumption. The proposed improvement would be available on a per-vehicle basis for mild and stro ng HEVs, as well as for other technologies that significantly improve the efficiency of full sized pickup trucks. The proposed definition would specify that trucks meeting an overall bed width and length as well as a minimum towing or payload capacity could be qualified as full si ze pickup trucks. NHTSA is also proposing to modify Part 523 to include definitions for mild and strong hybrid electric full size pickup trucks.

i. Pickup Truck Hybridization

One proposed incentive would provide an adjustment to the fuel economy of a manufacturer’s full size pickup trucks if the manufacturer employs certain defined hybrid technologies on defined significant quantities of its full size pickup trucks. After meeting the minimum production percentages, manufacturers woul d gain an adjustment to the fuel economy performance for each “mild” or “strong” hybrid full size pickup truck it produces. Manufacturers producing mild hybrid pickup trucks, as defined in Chapter 5 of the draft Joint TSD, would gain the incentive by applying mild hybrid technology to at least 30 percent of the company’s full sized pickups produced in MY 2017, which would increase each year up to at least 80 percent of the company’s full size pickups produced in MY 2021, after which point the adjustment is no longer applicable. For strong hybrids, also defined in Chapter 5 of the draft Joint TSD, the strong hybrid technology must be applied to at least 10 percent of a company’s full sized pickup production in each year for model years 2017-2025. The fuel economy adjustment for each mild hybrid full size pickup would be a decrease in measured fuel consumption of 0.0011gal/mi; for each strong hybrid full size pickup, the decrease in measured fuel consumption would be 0.0023 gal/mi. Th ese adjustments are consistent with the GHG credits under EPA’s program of 10 g/mi CO 2 for mild hybrid pickups and 20 g/mi CO 2 for strong hybrid pickups. The specified adjustment in the fuel consumption performance would then be subtracted from the fuel consumption performance te st result of each applicable hybrid vehicle, and the resultant then reciprocated to determine the improved adjusted fuel economy performance of each vehicle. EPA would use the adjusted fuel economy of each hybrid vehicle weighted to its production sales volume to determine the harmonic average fuel economy performance of the manufacturer’s fleet.

ii. Performance-based incentive for full-size pickups

Another proposed incentive for full size pickup trucks would provide an adjustment to the fuel economy of a manufacturer’s full sized pickup truck if it achieves a fuel economy performance level significantly above the CAFE target for that footprint. This incentive recognizes that not all manufacturers may wish to pursue hybridization for their pickup trucks, but still rewards them for applying fuel-saving technologies above and beyond what they might otherwise do. The fuel economy adjustment for each full size pickup that exceeds its applicableDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 751 of 768 footprint curve target by 15 percent would be a decrease in measured fuel consumption of 0.0011gal/mi; for each full size pickup that exceeds its applicable footprint curve target by 20 percent, the decrease in measured fuel consumption would be 0.0023 gal/mi. These adjustments are consistent with the GHG credits under EPA’s program of 10 g/mi CO 2 and 20 g/mi CO 2 , respectively, for beating the applicable CO 2 targets by 15 and 20 percent, respectively.

The 0.0011 gal/mi performance-based adjustment would be available for MYs 2017 to 2021, and a vehicle meeting the requirement in a given model year would continue to receive the credit until MY 2021 – that is, the credit remains appl icable to that vehicle model if the target is exceeded in only one model year – unless its fuel consumption increases. The 0.0023 gal/mi adjustment would be available for a maximum of 5 years within model years 2017-2025, provided the vehicle model’s fuel consumption does not increase. As explained above for the hybrid incentive, the decrease in each vehicle’s fuel consumption performance would be converted to an adjusted fuel economy performance and then averaged to determine the manufacturer’s CAFE fleet average value.

b. A/C efficiency-improving technologies

Air conditioning (A/C) use places excess load on an engine, which results in additional fuel consumption. A number of methods related to the A/C system components and their controls can be used to improve A/C system efficiencies. Starting in MY 2017, EPA is proposing to allow manufacturers to include fuel consumption reductions resulting from the use of improved A/C systems in their CAFE calculat ions. This will more accurately account for achieved real-world fuel economy improvements due to improved A/C technologies, and better fulfill EPCA’s overarching purpose of energy c onservation. EPA is not proposing to allow manufacturers to claim CAFE-related benefits fo r reducing A/C leakage or switching to an A/C refrigerant with a lower global warming poten tial, because while these improvements reduce GHGs consistent with the purpose of the CAA, they do not improve fuel economy and thus are not relevant to the CAFE program.

The improvements that manufacturers would likely use to increase A/C efficiency would focus primarily, but not exclusively, on the compressor, electric motor controls, and system controls which reduce load on the A/C system (such as reduced “reheat” of the cooled air and increased of use re-circulated cabin air).

Fuel consumption improvement values for CAFE resulting from A/C efficiency improvements would be quantified using a two-step process, the same as for the related CO 2 credits for EPA’s GHG program. First, the vehicle with the improved A/C system would be tested in accordance with EPA testing guidelines, and compared with the baseline fuel consumption value for that vehicle. Second, the difference between the baseline fuel consumption value and the value for the vehicl e with improved A/C technologies would be calculated, which would determine the fuel cons umption improvement value. A maximum fuel consumption improvement value of 0.000563 gal/mi for cars and 0.000586 gal/mi for trucks would be available to manufacturers. 799 Throughout this section, we discuss these values in

799 The maximum credit and fuel consumption improvement values represent the full 42 percent improvement in A/C emissions that the agencies estimate is feasible through the use of improved A/C technologies. The credits andDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 752 of 768 terms of fuel consumption, even though ultimate CAFE compliance is determined in miles per gallon rather than in gallons per mile. Conver ting to miles per gallon might assist the reader accustomed to thinking in those terms, but w ould actually complicate the discussion since fuel economy, unlike CO 2 /fuel consumption, is not linear, and fuel economy values would be inversely related to CO 2 reductions.

EPA is proposing three different test approaches : (1) an idle test; (2) an idle test with displacement weighting; and (3) the “A/C 17 test.” Manufacturers would be allowed to use any of those three tests to measure A/C-related CO 2 emissions from vehicles with improved A/C systems, which would be translated to fuel consumption to establish the ratio between the baseline vehicle and the improved-A/C vehicle to determine the value of the fuel consumption improvement. The three test procedures are described briefly below.

i. What are the proposed testing approaches?

The first test, the “idle test,” is the same as the test that EPA finalized for A/C efficiency improvements under the GHG program in the MYs 2012-2016 final rule. The idle test method measures CO 2 in grams per minute (g/min) while the vehicl e is stationary and idling. In the idle test method, baseline vehicle emissions are not tested. Emissions of the vehicle with improved A/C are compared to a pre-determined baseline emissions level. 800 The fuel consumption performance is determined using the following equation: grams CO 2 /mi = 1/mpg * 8,887.

The second test, the “modified idle test,” uses th e same test method as is used in the idle test, but includes a correction factor for engine displacement. Engine displacement is not accounted for in the idle only test described above. This alternative is being proposed because a study conducted by EPA in which 29 vehicles were tested on the idle test showed that vehicles with smaller displacement engines ha ve a higher idle test result (in CO 2 g/min) than those with larger displacement engines. Having the option of taking displacement into account will help manufacturers account more accurately for improvements in A/C systems.

The third test, the “A/C 17 test,” is a more ex tensive test than the idle test and has four elements. Unlike the idle test, it includes two drive cycles, US03 and the highway fuel economy cycle, which capture steady state and transient opera ting conditions. It also includes a solar soak period to measure the energy required to cool down a car that has been sitting in the sun, as well as a pre-conditioning cycle. The A/C 17 test cycle will be able to capture improvements in all areas related to efficient operation of a vehicle’ s A/C system. Unlike the other tests, the AC 17 test cycle measures CO 2 emissions in grams per mile (g/mi), and requires that baseline emissions be measured in addition to emissions from vehicl es with improved A/C systems, unlike the idle test where baseline emissions are pre-determined by EPA.

fuel consumption improvement values in Table IV.I.1 a dd up to more than the maximum allowable credit and fuel consumption improvement value. This is because some technologies act on the same inefficiencies in the A/C system and thus using two such technologies together would not yield additive fuel consumption reductions.

800 EPA conducted idle tests on 29 vehicles to establish fleet average A/C related CO 2 emissions. In testing, average car and truck A/C CO 2 emissions equaled 21.3 grams per minute.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 753 of 768 Manufacturers then use the results of the test ing approaches described above to determine the total available fuel consumption improvement value they can receive. The following section describes how that value is estimated.

ii. How are fuel consumption improvement values then estimated?

Using idle test results :

Taking the measured test results in CO 2 g/min, if the idle test result is 14.9 g/min or lower, manufactures may claim a pre-defined maximum fuel consumption improvement value. Manufacturers look up the technologies they have installed on their vehicles (shown in column 1 of Table IV.I.1) and take the corresponding pre-defined improvement value (columns 3 and 4 for cars and trucks, respectively). If a manufacturer uses more than one technology for a given vehicle model, the A/C fuel consumption improvement value for each technology can be added, but the maximum improvement value possible is limited to 0.000563 gal/mi for cars, and 0.000586-gal/mi for trucks. 801

For vehicles with an idle test result between 14.9 g/min and 21.3 g/min, manufacturers are eligible for a partial fuel consumption improvement value, using the following formula:

Where:

TCV = the total CO 2 credit value that can be claimed by the manufacturer

TCV1 = the maximum CO 2 credit value available, equal to the sum of the reduction for the A/C technologies used, and

ITP = the increase in CO 2 emissions shown on the idle test.

Finally, if the vehicle has a test result highe r than 21.3 g/min, it would receive zero fuel consumption improvement value.

Using results from the displacement-weighted idle test :

801 The maximum credit and fuel consumption improvement values represent the full 42% improvement in A/C emissions that the agencies estimate is feasible through the use of improved A/C technologies. The credits and fuel consumption improvement values in Table IV.I.1 add up to more than the maximum allowable credit and fuel consumption improvement value. This is because some technologies act on the same inefficiencies in the A/C system and thus using two such technologies together would not yield additive C02 and fuel consumption reductions.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 754 of 768 For an air conditioning system to be eligible to generate fuel consumption improvement values, the increased CO 2 emissions as a result of the operation of that air conditioning system determined according to the idle test procedure must be less than the value calculated by the following equation and rounded to the nearest tenth of gram per minute:

െ 20.5 ൌ ݈݀݋݄ݏ݁ݎ ݄ܶݐݏ݈݀݁ ܶ݁ܫ ሺ ݐ݈ܽܿ݉݁݊݌ݏ݅ܦ ൈ 1.58 ሻ

If the increased CO 2 emissions determined from the idle test procedure is less than or equal to the Idle Test Threshold , the total fuel consumption im provement value that can be claimed by the manufacturer shall be determined by summing the maximum value in Table IV.I.1. If the increased CO 2 emissions determined from the idle test procedure is greater than the Idle Test Threshold but less than the Idle Test Threshold plus 6.4, the total fuel consumption improvement value that can be claimed by the manufacturer shall be as determined according to the following formula:

ܶܥܸ ൌ ܶܥܸ ଵ ൈ ൤ 1 െ ൬ ܶܶܫ െ ܶܲܫ

6.4 ൰൨

Where:

TCV = the total CO 2 credit value that can be claimed;

TCV 1 = the sum of the CO 2 credits for the technologies used in the A/C system;

ITP = the increased CO 2 emissions determined from the idle test procedure in 40 CFR 86.165–14; and

ITT = the Idle Test Threshold resulting from the use of the idle test threshold equation.

T ABLE IV.I.1. E FFICIENCY I MPROVING A/C T ECHNOLOGIES AND I MPROVEMENT V ALUES [ STILL TO BE FINALIZED ]

Technology Description A/C Fuel Consumption Reduction (% of total A/C improvement) Car A/C Fuel Efficiency Improvement Value (gals/mi) Truck A/C Fuel Efficiency Improvement Value (gals/mi)Reduced reheat, with externallycontrolled, variable-displacement

compressor 30% 0.000169 ( 30% of 5.0 g/mi impact ) 0.000248 ( 30% of 7.2 g/mi impact )Reduced reheat, with externallycontrolled, fixed-displacement or pneumatic variable displacement

compressor 20% 0.000113 0.000158

Default to recirculated air with 30% 0.000169 0.000248DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 755 of 768 closed-loop control of the air supply (sensor feedback to control interior air quality) whenever the outside ambient temperature is 75 °F or higher 802Default to recirculated air with openloop control of the air supply (no sensor feedback) whenever the outside ambient temperature is 75 °F or higher 803 20% 0.000113 0.000156

Blower motor control which limit wasted electrical energy (e.g. pulsewidth modulated power controller) 15% 0.000090 0.000124

Internal heat exchanger (or suction line heat exchanger) 20% 0.000113 0.000156

Using results from the A/C 17 test :

Manufacturers would take the A/C 17 test result on the new vehicle and compare that with the result from a baseline vehicle without A/C efficiency-improving technologies to demonstrate that less fuel is consumed from A/C operation with the improved A/C system. The fuel consumption improvement value is calculated in a same way as it is in the idle test.

Fuel consumption improvement values due to the improved A/C technologies are derived using the approaches described above. Under the NHTSA CAFE program the fuel consumption improvement values are subtracted from the s ubject vehicle’s fuel consumption performance value determined from the required CAFE program 2-cycle test results. The resultant would then be reciprocated to determine the improved adjusted fuel economy performance value for the subject vehicle. EPA would use the adjusted fu el economy value of each vehicle weighted to its production sales volume to determine the harmonic average fuel economy performance, CAFE value, of the manufacturer’s fleet. Although the form of the NHTSA program standard is in miles per gallon, in Table IV.I.1 values are presented in terms of gallons per mile for transparency to the reader.

The agencies seek comment on the proposal to allow manufacturers to estimate fuel consumption reductions from the use of A/C efficiency-improving technologies and to apply these reductions to their CAFE calculations.

c. Off-cycle technologies and adjustments

For MYs 2012-2016, EPA provided an optional credit for new and innovative “off-cycle” technologies that reduce vehicle CO 2 emissions, but for which the CO 2 reduction benefits are not

802 Deviations from this temperature are allowe d if accompanied by an engineering analysis.

803 Deviations from this temperature are allowe d if accompanied by an engineering analysis.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 756 of 768 recognized under the 2-cycle test procedure used to determine compliance with the fleet average standards. The off-cycle credit option was inte nded to encourage the introduction of off-cycle technologies that achieve real-world benefits. Th e off-cycle credits were to be determined using the 5-cycle methodology currently used to determine fuel economy label values, which EPA established to better represent real-world fact ors impacting fuel economy, including higher speeds and more aggressive driving, colder temperature operation, and the use of air conditioning. A manufacturer must determine whether the benefit of the technology could be captured using the 5-cycle test; if this determin ation is affirmative, the manufacture must follow the 5-cycle procedures to determine the CO 2 reductions. If the manufacturer finds that the technology is such that the benefit is not adequately captured using the 5-cycle approach, then the manufacturer would have to develop a robust methodology, subject to EPA approval, to demonstrate the benefit and determine the appropriate CO 2 gram per mile credit. The demonstration program must be robust, verifiable, and capable of demonstrating the real-world emissions benefit of the technology with st rong statistical significan ce. The non-5-cycle approach includes an opportunity for public comment as part of the approval process.

EPA has been encouraged by automakers’ inte rest in off-cycle credits since the program was finalized and believes that extending the program to MY 2017 and beyond may continue to encourage automakers to invest in off-cycle techno logies that could have the benefit of realizing additional reductions in the light-duty fleet over the longer-term. Therefore, EPA is proposing to extend the off-cycle credits pr ogram to 2017 and later model years. EPA is also proposing, under its EPCA authority, to make available a comparable off-cycle technology incentive under the CAFE program beginning in MY 2017. However, instead of manufacturers gaining credits as done under the GHG program, a direct adjustme nt would be made to the manufacturer’s fuel economy performance value.

Starting with MY 2017, manufacturers may generate fuel economy improvements by applying technologies listed on the pre-defined and pre-approved technology list provided in Table IV.I.2. These credits would be verified a nd approved as part of certification, with no prior approval process needed. This new option should significantly simplify the program for manufacturers and provide certainty that improvement values may be generated through the use of pre-approved technologies. For improvement s from technologies not on the pre-defined list, EPA is proposing to clarify the step-by-step ap plication process for demonstration of fuel consumption reductions and approval.

T ABLE IV.I.2. O FF

- CYCLE TECHNOLOGIES AND PROPOSED IMPROVEMENT VALUES FOR

PASSENGER CARS AND LIGHT TRUCKS

Technology Improvement value for passenger cars(gal/mi) Improvement value for light trucks (gal/mi) High Efficiency Exterior Lighting 0.000124 0.000124 Engine Heat Recovery 0.000778 0.000778
Solar Roof Panels 0.000338 0.000338
Active Grill Shutters 0.000113 0.000113 Active Suspension LoweringDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 757 of 768 Engine Start-Stop 0.000326 0.000506 Electric Heater Circulation Pump 0.000123 0.000169 Active Transmission Warm-Up 0.000203 0.000203 Active Engine Warm-Up 0.000203 0.000203
Solar Control 0.000338 0.000338 High Efficiency Exterior Lighting 0.0001 0.0001 Engine Heat Recovery 0.0001 0.0001
Solar Roof Panels 0.0003 0.0003
Active Grill Shutters 0.0001 0.0001 Active Suspension Lowering Engine Start-Stop 0.0003 0.0005 Electric Heater Circulation Pump 0.0001 0.0002 Active Transmission Warm-Up 0.0002 0.0002 Active Engine Warm-Up
Solar Control 0.0002 0.0002

An example of technologies that could be us ed to generate off-cycle improvements are those that reduce electrical load and as a result, fuel consumption. The 2-cycle test does not require that all electrical components be turned on during testing. Headlights, for example, are always turned off during testing. Turning the headlights on during normal driving will add an additional load on the vehicle’s electrical system and will affect fuel economy. More efficient electrical systems or technologies that offset electrical loads wi ll have a real-world impact on fuel economy but are not captured in the 2-cycle test. Therefore, technologies that reduce or offset electrical loads related to the operation or safety of the vehicle should merit consideration for off-cycle improvements. Reducing the electrical load on a vehicle by 100W will result in an average of 0.000337 gallons/mile reduction in fuel consumption over the course of a 2-cycle test, or 0.00042 gallons/mile over a 5-cycle test. To determine the off-cycle benefit of certain 100W electrical load reduction technologies, the benefit of the technology on the 2-cycle test is subtracted from the benefit of the technology on the 5-cycle test. This determines the actual benefit of the technology not realized in the 2-cycle test methodology, which in this case is0.000416 gal/mi minus 0.000337 gal/mi, or 0.000078 gal/mi. This method will avoid doublecounting the benefit of the electrical load reduction, which is already counted on the 2-cycle test.

Regardless of whether the off-cycle technology fuel consumption benefit is obtained from the table (columns 2 or 3) above or is based on an approved testing protocol as indicated in the preceding example, under the CAFE program the benefit or credit is treated as an adjustment and subtracted from the subject vehicle’s fuel consumption performance value determined from the required CAFE program 2-cycle test results. The resultant would then be reciprocated to determine the improved adjusted fuel economy performance value for the subject vehicle. EPA would use the adjusted fuel economy value of each vehicle weighted to its production sales volume to determine the harmonic average fuel economy performance, CAFE value, of the manufacturer’s fleet.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 758 of 768 Since one purpose of the off-cycle improvement incentive is to encourage market penetration of the technologies (see 75 FR at 25438), EPA is proposing to require minimum penetration rates for non-hybrid based listed technologies as a cond ition for generating improvements from the list as a way to further encourage their widespread adoption by MY 2017 and later. At the end of the model year for which the off-cycle improvement is claimed, manufacturers would need to demonstrate that production of vehicles equipped with the technologies for that model year exceeded the per centage thresholds in order to receive the listed improvement. EPA proposes to set the threshold at 10 percent of a manufacturer’s overall combined car and light truck production for all t echnologies not specific to HEVs. 10 percent would seem to be an appropriate threshold as it would encourage manufacturers to develop technologies for use on larger volume models an d bring the technologies into the mainstream. For solar roof panels and electric heat circul ation pumps, which are HE V-specific, EPA is not proposing a minimum penetration rate threshold for credit generation. Hybrids may be a small subset of a manufacturer’s fleet, less than 10 percent in some cases, and EPA does not believe that establishing a threshold for hybrid-bas ed technologies would be useful and could unnecessarily complicate the introduction of these technologies. The agencies request comments on applying this type of threshold, the appropriateness of 10 percent as the threshold for listed technologies that are not HEV-specific, and the proposed treatment of hybrid-based technologies.

Because the proposed improvements are based on limited data, however, and because some uncertainty is introduced when credits are provided based on a general assessment of offcycle performance as opposed to testing on the individual vehicle models, as part of the incentive EPA is proposing to cap the amount of improvement a manufacturer could generate using the above list to 0.001125 gal/mile per year on a combined car and truck fleet-wide average basis. The cap would not apply on a vehicle model basi s, allowing manufacturers the flexibility to focus off-cycle technologi es on certain vehicle models and generate improvements for that vehicle model in excess of 0.001125 gal/mile. If manufacturers wish to generate improvements in excess of the 0.001125 gal/mile limit using listed technologies, they could do so by generating necessary data and going through the approval process.

For more details on the testing protocols used for determining off-cycle technology benefits and the step-by-step EPA review and a pproval process refer to Section III.C.5.b.iii and

v.

5. Other CAFE enforcement issues

e. Electronic Reporting

Pursuant to 49 CFR part 537, manufacturers submit pre-model year fuel economy reports to NHTSA by December 31 st prior to the model year, and mid-model year reports by July 31 st of the model year. Manufacturers may also provide supplemental reports whenever changes are needed to a previously submitted CAFE report. NHTSA receives both non-confidential and confidential versions of reports, the basic diff erence being the inclusion of projected upcoming production sales volumes in reports seeking confidentiality. Manufacturers must include a request for confidentiality, in accordance with 49 CFR part 512, along with the report for whichDRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 759 of 768 confidential treatment is sought. 804 Manufacturers may submit reports either in paper form or electronically to a secure e-mail address, cafe@dot.gov, that allows for the safe handling of confidential materials. All electronic submis sions submitted to the CAFE email must be provided in a pdf format. NHTSA added electronic reporting to the 2012-2016 CAFE rule as an approach to simplify reporting for manufacturers and NHTSA alike. Currently, most manufacturers submit both electronic and paper reports. 805

NHTSA is proposing to modify its reporting requirements to receive all CAFE reports in electronic format, thereby eliminating the requirement for paper submissions. In the revised requirements, a manufacturer could either submit its reports on a CD-ROM or through the existing email procedures. Under the proposal, the contents of the CD must include the manufacturer’s request for confidentiality, the cover letter, and any other supporting documents in a pdf format. Any data included in the report must be provided in a Microsoft Excel spreadsheet format. The same approach is also proposed for submitting information by email. NHTSA emphasizes that submitting reports to the CAFE email address is completely voluntary, but if the option is selected, the manufacturer must follow the normal deadline dates as specified in 49 CFR 537.5. NHTSA believes that receiving CAFE data through electronic reports would be a significant improvement, improving the quality of its CAFE data, simplifying enforcement activities ( e.g. , auditing the data), and helping to expe dite the tracking and reporting of CAFE credits. The agency also plans to eventually develop an XML schema for submitting CAFE reports electronically that will av ailable through its website. Ultimately, the XML schema would be used as part of the new database system NHTS A plans to construct in the future to store its CAFE data. NHTSA seeks comments on the appropriateness of ending paper submissions, as well as information on any other electronic format s that should be considered for submissions.

f. Reporting of how a vehicle is classified as a light truck

As part of the reporting provisions in 49 CFR part 537, NHTSA requires manufacturers to provide information on some, but not all, of the functions and features that a manufacturer uses to classify an automobile as a light truck. The required data is distributed throughout the report, making it difficult for the agency to clearly and easily determine exactly what functions or features a manufacturer is actually using to make this determination. For example, related to the functions specified in 49 CFR 523.5(a) a nd discussed in Section IV.H above, manufacturers must provide the vehicles’ passenger and cargo carrying volumes, 806 and identify whether their vehicles are equipped with three rows of seats that can be removed or folded flat for expanded cargo carrying purposes or if the vehicle includes temporary living quarters. 807 Manufacturers are not required to identify whether the vehicles can transport more than 10 persons or if the vehicles are equipped with an open cargo bed. Related to the functions specified in Section 523.5(b), for each model type classified as an automobile capable of off-highway operation, manufacturers are required to provide the five suspension parameter measurements and indicate

804 Pursuant to Part 537.12, NHTSA’s Office of Chief Counsel normally grants confidentiality to reports with projected production sales volumes until after the model year ends.

805 For model year 2011, NHTSA received electronic mid-mode l year reports from 12 manuf acturers. Each of the manufacturers also provided hardcopy reports.

806 49 CFR 537.7(c)(4)(xvi)(B).

807 49 CFR 537.7(c)(4)(xvii) and (xviii).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 760 of 768 the existence of 4-wheel drive, 808 but they are not required to identify a vehicle’s GVWR, which is necessary for off-road determination when the vehicle is not equipped with 4-wheel drive. NHTSA proposes to eliminate the language requesting vehicle attribute information in Sections 537.7(c)(4)(xvi)(A)(3) to (6) and (B)( 3) to (6) and to relocate that language into a revised Section 537.7(c)(5) to include identification of all the functions and features that can be used by a manufacturer for making a light truck classificati on determination. By incorporating all the requirements into one section, the agency believes the cla ssification process will become significantly more accurate and efficient. NHTSA seeks comment on this proposed change.

g. Base Tire Definition

Beginning in model year 2011, manufacturer s of light trucks and passenger cars are required to use vehicle footprint to determine the CAFE standards applicable to each of their vehicle fleets. To determine the appropriate footprint-based standards, a manufacturer must calculate each vehicle’s footprint value, which is the product of the vehicle track width and wheelbase dimensions. Vehicle track width dimensions are determined with a vehicle equipped with “base tires,” 809 which NHTSA defines as the tire specified as standard equipment by a manufacturer on each vehicle configuration of a model type.

NHTSA is concerned that the definition for “b ase tire” is insufficiently descriptive, and may lead to inconsistencies among manufacturers and a possible avenue for gaming of the required standards. In meetings relating to CAFE enforcement, manufacturers have stated that various approaches in selecting base tires exist due to differences in the tires considered as standard equipment. 810 Standard equipment is defined by EPA regulation as those features or equipment which are marketed on a vehicle over which the purchaser can exercise no choice, 811 but NHTSA regulations have no comparable definition. NHTSA considered whether adding a definition for “standard equipment” would clarify and strengthen the NHTSA regulations, but manufactures indicated that the definition of standard equipment provided by EPA does not effectively prevent differences in their interpreta tions. Some manufacturers, for example, view the base tire as the tire equipped as standard equipment for each trim level of a model type, as each trim level has standard equipment over which the purchaser cannot exercise a choice. This view can allow multiple base tires and footprint values within each model type: a manufacturer may have two vehicle configurations for a particular model type, with each configuration having three trim levels with different standard tires size s. In that scenario, the model type could have 6 different trim level vehicle configurations, each having three or more unique footprint values with slightly different targets. The additiona l target fuel economy values could allow the manufacturer to reduce its required fleet standard despite a vehicle model type not having any inherent differences in physical feature between ve hicle configurations other than the tire sizes. Other manufacturers, in contrast, avoid designati ng multiple base tires and choose the standard tire equipped on the most basic vehicle configuration of a model type, even if the most basic

808 49 CFR 537.7(c)(5).

809 See 49 CFR 523.2.

810 NHTSA has confirmed these differences in approach for the designating base tire exist through review of manufacturer-submitted CAFE reports.

811 In the EPA regulation 40 CFR 600.002-08, standard equipment means those features or equipment which are marketed on a vehicle over which the purchaser can exercise no choice.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 761 of 768 vehicle is rarely or never actually sold. In this scenario, the tires being used to derive a manufacturer fleet standard are not the same size tire equipped on the representative number of vehicles being sold. Yet others designate the base tire as the tire most commonly installed on a model type having the highest production volume. This approach most realistically reflects the manufacturer’s sales production fleet and eliminates the gaming that can occur from selecting multiple base tires.

To attempt to reconcile the varied approaches for designation and avoid gaming, NHTSA is proposing to modify its definition for base tire in 49 CFR 523.2. The proposed modification changes the definition of the base tire by dropping the reference to “standard equipment” and adding a reference to the “the tire installed by the vehicle manufacturer that is used on the highest production sales volume of vehicles within the configuration.” This modification should ensure that the tires installed on the vehicle most commonly sold within a vehicle configuration become the basis for setting a manufacturer’s fuel economy standards, thereby reducing a manufacturer’s ability to game the classification of its vehicles. Specifying one approach will also reduce inconsistencies and confusion for both the agency and the manufacturers. NHTSA seeks comments on this approach, as well as other approaches that could be used for selecting the base tire(s).

h. Confirming Target and Fleet Standards

NHTSA requires manufacturers to provide reports containing fleet and model type CAFE standards and projections of expected performance results for each model year. 812 The footprint, track width and wheelbase values are provided fo r each vehicle configuration within the model types making up the manufacturer’s fleets, along with other model type-specific information. Because this information is organized by vehicle configuration, instead of by each vehicle with a unique model type and footprint combination, it is not in the format needed to calculate performance standards. EPA, in contrast, requires manufacturers to provide all of the information necessary to calculate footprint va lues and CAFE standards. EPA provides an additional calculator (in the form of an Excel spreadsheet), which all manufacturers use and submit as part of their end-of-the-year reports, which includes the appropriate breakdown of footprint values for calculating standards.

Since NHTSA only requires a breakdown of foot print values by vehicle configurations, instead of by each unique model type and footprint combination, NHTSA is currently unable to verify manufacturers’ reported target standards. By standardizing with EPA’s requirements for reported data, NHTSA would both simplify manufacturer reporting efforts and gain the necessary information for calculating attribute-based CAFE standards. Therefore, NHTSA is proposing to eliminate the language requesting information in Sections 537.7(c)(4)((xvi)(A)(3)- (6) and (B)(3)-(6), and to relocate that language into a revised Section 537.7(b)(3).

NHTSA requests comment on this proposed change.

J. Regulatory notices and analyses

812 49 CFR 537.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 762 of 768 1. Executive Order 12866, Executive Order 13563, and DOT Regulatory Policies and Procedures

Executive Order 12866, “Regulatory Planning and Review” (58 FR 51735, Oct. 4, 1993), as amended by Executive Order 13563, “Improving Regulation and Regulatory Review” (76 FR 3821, Jan. 21, 2011), provides for making dete rminations whether a regulatory action is “significant” and therefore subject to OMB review and to the requirements of the Executive Order. The Order defines a “significant regulatory act ion” as one that is likely to result in a rule that may:

1) Have an annual effect on the economy of $100 million or more or adversely affect in a material way the economy, a sector of the economy, productivity, competition, jobs, the environment, public health or safety, or State, local, or Tribal governments or communities; 2) Create a serious inconsistency or otherw ise interfere with an action taken or planned by another agency; 3) Materially alter the budgetary impact of entitlements, grants, user fees, or loan programs or the rights and obligations of recipients thereof; or 4) Raise novel legal or policy issues arisi ng out of legal mandates, the President’s priorities, or the principles set forth in the Executive Order.

The rulemaking proposed in this NPRM will be economically significant if adopted. Accordingly, OMB reviewed it under Executive Order 12866. The rule, if adopted, would also be significant within the meaning of the Department of Transportation’s Regulatory Policies and Procedures.

The benefits and costs of this proposal are described above. Because the proposed rule would, if adopted, be economically significant under both the Department of Transportation’s procedures and OMB guidelines, the agency has prepared a Preliminary Regulatory Impact Analysis (PRIA) and placed it in the docket and on the agency’s website. Further, pursuant to Circular A-4, we have prepared a formal probabilis tic uncertainty analysis for this proposal. The circular requires such an analysis for complex rules where there are large, multiple uncertainties whose analysis raises technical challenges or where effects cascade and where the impacts of the rule exceed $1 billion. This proposal meets these criteria on all counts.

2. National Environmental Policy Act

NHTSA has initiated the Environmental Impact Statement (EIS) process under the National Environmental Policy Act (NEPA), 42 U.S.C. 4321-4347, and implementing regulations issued by the Council on Environm ental Quality (CEQ), 40 CFR part 1500, and NHTSA, 49 CFR part 520. On May 10, 2011, NHTSA published a notice of intent to prepare an EIS for this rulemaking and requested scoping comments. (76 FR 26996). The notice invited Federal, State, and local agencies, Indian tribes , and the public to participate in the scoping process and to help identify the environmental issues and reasonable alternatives to be examined in the EIS. The scoping notice also provided information about the proposed standards, the alternatives NHTSA expects to consider its NEPA analysis, and the scoping process.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 763 of 768 Concurrently with this NPRM, NHTSA is releasing a Draft Environmental Impact Statement (DEIS). NHTSA prepared the DEIS to analyze and disclose the potential environmental impacts of the proposed MY 2017-2025 CAFE standards for the total fleet of passenger cars and light trucks and reasonable alternative standards for the NHTSA CAFE program pursuant to the CEQ regulations implementing NEPA, DOT Order 5610.1C, and NHTSA regulations. The DEIS compares the po tential environmental impacts of alternative mile per gallon (mpg) levels that will be consid ered by NHTSA for the final rule. It also analyzes direct, indirect, and cumulative impacts and analyzes impacts in proportion to their significance.

The DEIS also describes potential environmental impacts to a variety of resources. Resources that may be affected by the proposed action and alternatives include water resources, biological resources, land use and development, safety, hazardous materials and regulated wastes, noise, socioeconomics, and environmental justice. These resource areas were assessed qualitatively in the DEIS.

Throughout the DEIS, NHTSA has relied extensively on findings of the United Nations Intergovernmental Panel on Climate Change (IPCC), the U.S. Climate Change Science Program (CCSP), and EPA. Our discussion relies heavily on the most recent, thoroughly peer-reviewed, and credible assessments of global and U.S. climate change: the IP CC Fourth Assessment Report ( Climate Change 2007 ), EPA’s Endangerment and Cause or Contribute Findings for Greenhouse Gases under Section 202(a) of the Clean Air Act and the accompanying Technical Support Document (TSD), and CCSP and National Science and Technology Council reports that include the Scientific Assessment of the Effects of Global Change on the United States and Synthesis and Assessment Products. The DEIS c ites these sources and the studies they review frequently.

Because of the link between the transpor tation sector and GHG emissions, NHTSA recognizes the need to consider the possible imp acts on climate and global climate change in the analysis of the effects of thes e fuel economy standards. NHTS A also recognizes the difficulties and uncertainties involved in such an impact analysis. Accordingly, consistent with CEQ regulations on addressing incomplete or unava ilable information in environmental impact analyses, NHTSA has reviewed existing credible sc ientific evidence that is relevant to this analysis and summarized it in the DEIS. NHTSA has also employed and summarized the results of research models generally accepted in the scientific community.

Although the alternatives have the potential to decrease GHG emissions substantially, they do not prevent climate change, but only result in reductions in the anticipated increases in
CO 2 concentrations, temperature, precipitation, and sea level. They would also, to a small degree, delay the point at which certain temperature increases and other physical effects stemming from increased GHG emissions would o ccur. As discussed below, NHTSA presumes that these reductions in climate effects will be re flected in reduced impacts on affected resources.

The main direct and indirect effects resulting from the different alternatives analyzed in the DEIS are as follows:DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 764 of 768 [to be filled in]

3. Regulatory Flexibility Act

Pursuant to the Regulatory Flexibility Act (5 U.S.C. 601 et seq ., as amended by the Small Business Regulatory Enforcement Fairness Act (SBREFA) of 1996), whenever an agency is required to publish a notice of rulemaking for any proposed or final rule, it must prepare and make available for public comment a regulatory flexibility analysis that describes the effect of the rule on small entities ( i.e. , small businesses, small organizations, and small governmental jurisdictions). The Small Business Administration ’s regulations at 13 CFR part 121 define a small business, in part, as a business entity “whi ch operates primarily with in the United States.” 13 CFR 121.105(a). No regulatory flexibility analysis is required if the head of an agency certifies the rule will not have a significant ec onomic impact of a substantial number of small entities.

I certify that the proposed rule would not have a significant economic impact on a substantial number of small entities. The follo wing is NHTSA’s statement providing the factual basis for the certification (5 U.S.C. 605(b)).

If adopted, the proposal would directly aff ect nineteen large single stage motor vehicle manufacturers. 813 The proposal would also affect [how many?] small domestic single stage motor vehicle manufacturers, [Saleen and Tesla and perhaps others]. 814 According to the Small Business Administration’s sm all business size standards ( see 13 CFR 121.201), a single stage automobile or light truck manufacturer (NAI CS code 336111, Automobile Manufacturing; 336112, Light Truck and Utility Vehicle Manufacturing) must have 1,000 or fewer employees to qualify as a small business. [All companies] have fewer than 1,000 employees and make fewer than 1,000 vehicles per year. We believe that the rulemaking would not have a significant economic impact on these small vehicle manuf acturers because under 49 CFR part 525, passenger car manufacturers making fewer than 10, 000 vehicles per year can petition NHTSA to have alternative standards set for those manufacturers. Tesla [and other EV mfrs, possibly VIA, Amp, Coda, Fisker, Wheego] produces only elect ric vehicles with fuel economy values far beyond those proposed today, so we would not expect them to need a petition for relief. Saleen [and other companies if applicable] modifies a very small number of vehicles produced by one of the large single-scale manufacturers, and currently does not meet the generally-applicable passenger car CAFE standards, nor is it anticipated to be able to meet the standards proposed today. However, Saleen [and other mfrs, need to check Mosler, Panoz, Shelby American Inc., Carbon Motors (police cars, ther efore already exempted )] already petitions the agency for relief under Part 525. If the standard is raised, it has no meaningful impact on Saleen [and other mfrs], because it must still go through the same process to petition for relief. Given that there is already

813 BMW, Daimler (Mercedes), Fiat/Chrysler (which also includes Ferrari and Maserati for CAFE compliance purposes), Ford, Geely (Volvo), General Motors, Honda, Hyunda i, Kia, Lotus, Mazda, Mitsubishi, Nissan, Porsche, Subaru, Suzuki, Tata (Jaguar Land Rover), Toyota, and Volkswagen/Audi.

814 The Regulatory Flexibility Act onl y requires analysis of small domestic manufacturers. These are the only passenger car manufacturers we know of, [fill in], and no light truck manufacturers.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 765 of 768 a mechanism for handling small businesses, which is the purpose of the Regulatory Flexibility Act, a regulatory flexibility analysis was not prepared.

4. Executive Order 13132 (Federalism)

Executive Order 13132 requires NHTSA to develop an accountable process to ensure “meaningful and timely input by State and local officials in the development of regulatory policies that have federalism implications.” 815 The Order defines the term “Policies that have federalism implications” to include regulations that have “substantial direct effects on the States, on the relationship between the national government and the States, or on the distribution of power and responsibilities among the various levels of government.” Under the Order, NHTSA may not issue a regulation that has federalism implications, that imposes substantial direct compliance costs, and that is not required by statute, unless the Federal government provides the funds necessary to pay the direct compliance costs incurred by State and local governments, or NHTSA consults with State and local officials ear ly in the process of developing the proposed regulation.

NHTSA solicits comment on this proposed act ion from State and local officials. The agency believes that it is unnece ssary to address the question of preemption further at this time because of the consistent and coordinated Federal standards that would apply nationally under the proposed National Program.

5. Executive Order 12988 (Civil Justice Reform)

Pursuant to Executive Order 12988, “Civil Justice Reform,” 816 NHTSA has considered whether this rulemaking would have any retroactive effect. This proposed rule does not have any retroactive effect.

6. Unfunded Mandates Reform Act

Section 202 of the Unfunded Mandates Reform Act of 1995 (UMRA) requires Federal agencies to prepare a written assessment of the costs, benefits, and other effects of a proposed or final rule that includes a Federal mandate likely to result in the expenditure by State, local, or tribal governments, in the aggregate, or by the private sector, of more than $100 million in any one year (adjusted for inflation with base year of 1995). Adjusting this amount by the implicit gross domestic product price deflator for 2009 results in $134 million (109.729/81.606 = 1.34). Before promulgating a rule for which a written statement is needed, section 205 of UMRA generally requires NHTSA to identify and consider a reasonable number of regulatory alternatives and adopt the least costly, most cost -effective, or least burdensome alternative that achieves the objectives of the rule. The provisions of section 205 do not apply when they are inconsistent with applicable law. Moreover, section 205 allows NHTSA to adopt an alternative other than the least costly, most cost-effective, or least burdensome alternative if the agency publishes with the final rule an explanati on of why that alternative was not adopted.

815 64 FR 43255 (Aug. 10, 1999).

816 61 FR 4729 (Feb. 7, 1996).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 766 of 768 This proposed rule will not result in the expenditure by State, local, or tribal governments, in the aggregate, of more than $134 million annually, but it will result in the expenditure of that magnitude by vehicle manufacturers and/or their suppliers. In developing this proposal, NHTSA considered a variety of alternative average fuel economy standards lower and higher than those proposed. NHTSA is stat utorily required to set standards at the maximum feasible level achievable by manufacturers based on its consideration and balancing of relevant factors, and has tentatively concluded that the proposed fuel economy standards are the maximum feasible standards for the passenger car and light truck fleets for MYs 2017-2025 in light of the statutory considerations.

7. Regulation Identifier Number

The Department of Transportation assigns a regulation identifier number (RIN) to each regulatory action listed in the Unified Agenda of Federal Regulations. The Regulatory Information Service Center publishes the Unified Agenda in April and October of each year. You may use the RIN contained in the heading at the beginning of this document to find this action in the Unified Agenda.

8. Executive Order 13045

Executive Order 13045 817 applies to any rule that: (1) is determined to be economically significant as defined under E.O. 12866, and (2) concerns an environmental, health, or safety risk that NHTSA has reason to believe may have a disproportionate effect on children. If the regulatory action meets both crit eria, we must evaluate the environmental, health, or safety effects of the proposed rule on children, and explain why the proposed regulation is preferable to other potentially effective and reasonably foreseeable alternatives considered by us.

Chapter 5 of NHTSA’s DEIS notes that br eathing PM can cause respiratory ailments, heart attack, and arrhythmias (Dockery et al. 1993, Samet et al . 2000, Pope et al. 1995, 2002, 2004, Pope and Dockery 2006, Dominici et al. 2006, Laden et al. 2006, all in Ebi et al . 2008). Populations at greatest risk could include children, the elderly, and those with heart and lung disease, diabetes (Ebi et al. 2008), and high blood pressure (Künzli et al. 2005, in Ebi et al

. 2008). Chronic exposure to PM could decrease lifespan by 1 to 3 years (Pope 2000, in American Lung Association 2008). Increasing PM concentrations are expected to have a measurable adverse impact on human health (Confalonieri et al. 2007).

Additionally, the DEIS notes that substantial morbidity and childhood mortality has been linked to water- and food-borne diseases. Climate change is projected to alter temperature and the hydrologic cycle through changes in precipitation, evaporation, transpiration, and water storage. These changes, in turn, potentially affect water-borne and food-borne diseases, such as salmonellosis, campylobacter, leptospirosis, and pathogenic species of vibrio. They also have a direct impact on surface water availability and water quality. It has been estimated that more than 1 billion people in 2002 did not have access to adequate clean water (McMichael et al

. 2003, in Epstein et al. 2006). Increased temperatures, greater evaporation, and heavy rain events have been associated with adverse impacts on drinking water through increased waterborne

817 62 FR 19885 (Apr. 23, 1997).DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 767 of 768 diseases, algal blooms, and toxins (Chorus and Bartram 1999, Levin et al . 2002, Johnson and Murphy 2004, all in Epstein et al . 2006). A seasonal signature has been associated with waterborne disease outbreaks (EPA 2009b). In the United States, 68 percent of all water-borne diseases between 1948 and 1994 were observed after heavy rainfall events (Curriero et al . 2001a, in Epstein et al . 2006).

Climate change could further impact a pathogen by directly affecting its lifecycle (Ebi et al . 2008). The global increase in the frequency, intensity, and duration of red tides could be linked to local impacts already associated with climate change (Harvell et al . 1999, in Epstein et al . 2006); toxins associated with red tide directly affect the nervous system (Epstein et al . 2006).

Many people do not report or seek medical at tention for their ailments of water-borne or food-borne diseases; hence, the number of actual cases with these diseases is greater than clinical records demonstrate (Mead et al . 1999, in Ebi et al . 2008). Many of the gastrointestinal diseases associated with water-borne and food-borne diseases can be self-limiting; however, vulnerable populations include young children, those with a compromised immune system, and the elderly.

Thus, as detailed in the DEIS, NHTSA has evaluated the environmental, health, and safety effects of the proposed rule on children. The DEIS also explains why the proposed regulation is preferable to other potentially ef fective and reasonably foreseeable alternatives considered by the agency.

9. National Technology Transfer and Advancement Act

Section 12(d) of the National Technology Transfer and Advancement Act (NTTAA) requires NHTSA to evaluate and use existing voluntary consensus standards in its regulatory activities unless doing so would be in consistent with applicable law ( e.g. , the statutory provisions regarding NHTSA’s vehicle safety authority) or otherwise impractical. 818

Voluntary consensus standards are technical standards developed or adopted by voluntaryconsensus standards bodies. Technical standards are defined by the NTTAA as “performancebased or design-specific technical specification and related management systems practices.” They pertain to “products and processes, such as size, strength, or technical performance of a product, process or material.”

Examples of organizations generally regarded as voluntary consensus standards bodies include the American Society for Testing and Materials (ASTM), the Society of Automotive Engineers (SAE), and the American National Sta ndards Institute (ANSI). If NHTSA does not use available and potentially applicable voluntary consensus standards, we are required by the Act to provide Congress, through OMB, an explanation of the reasons for not using such standards.

There are currently no voluntary consensus standards relevant to today’s proposed CAFE standards.

818 15 U.S.C. 272.DRAFT – DELIBERATIVE – PRIVILEGED AND CONFIDENTIAL

Page 768 of 768 10. Executive Order 13211

Executive Order 13211 819 applies to any rule that: (1) is determined to be economically significant as defined under E.O. 12866, and is likely to have a significant adverse effect on the supply, distribution, or use of energy; or (2) that is designated by the Administrator of the Office of Information and Regulatory Affairs (OIRA) as a significant regulatory action. If the regulatory action meets either criterion, we must evaluate the adverse energy effects of the proposed rule and explain why the proposed regulation is preferable to other potentially effective and reasonably foreseeable alternatives considered by us.

The proposed rule seeks to establish passenger car and light truck fuel economy standards that will reduce the consumption of petroleum a nd will not have any adverse energy effects. Accordingly, this proposed rulemaking action is not designated as a significant energy action.

11. Department of Energy Review

In accordance with 49 U.S.C. 32902(j)(1), we submitted this proposed rule to the Department of Energy for review. That Department did not make any comments that we have not addressed. [Pending conclusion of review, of course]

12. Plain Language

Executive Order 12866 requires each agency to write all rules in plain language. Application of the principles of plain language includes consideration of the following questions:

 Have we organized the material to suit the public’s needs?

 Are the requirements in the rule clearly stated?

 Does the rule contain technical jargon that isn’t clear?

 Would a different format (grouping and order of sections, use of headings, paragraphing) make the rule easier to understand?

 Would more (but shorter) sections be better?

 Could we improve clarity by adding tables, lists, or diagrams?

 What else could we do to make the rule easier to understand?

If you have any responses to these questions, please include them in your comments on this proposal.

13. Privacy Act

Anyone is able to search the electronic form of all comments received into any of our dockets by the name of the individual subm itting the comment (or signing the comment, if submitted on behalf of an organization, business, labor union, etc.). You may review DOT’s complete Privacy Act statement in the Federal Register (65 FR 19477-78, April 11, 2000) or you may visit http://www.dot.gov/privacy.html.

819 66 FR 28355 (May 18, 2001).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Below is a summary of interagency working comments received during EO 12866 and EO 13563 review of the draft rule “Joint Rulemaking to Establish Light-Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average Fuel Economy Standards”. They are for your consideration and are subject to further policy review.

1.Interagency commenters recommend that the agen cies include the following text in NHTSA’s uncertainty analysis section where NTHSA describes technology cost uncertainty:

“We did not explicitly model learning rate uncerta inty in this analysis; however, the technology cost uncertainty could be derived from uncertainty in learning rates. We explicitly request comment on whether learning rate uncertainty should be explicitly modeled, separate from technology cost uncertainty, in the probabilis tic uncertainty analysis accompanying the final rules.”

2. Interagency commenters also recommend that NHTSA include the following edits in the RIA:

U.S. Department Of Transportation National Highway Traffic Safety Administration



## Preliminary Regulator y Impact Analysis Formatted: Tab stops: 4.3", LeftSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review. 

# Corporate Average Fuel Economy
for MY 2017-MY 2025 Passenger Cars and Light Trucks

Office of Regulatory Analysis and Evaluation National Center for Statistics and Analysis

October 2011Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.



### TABLE OF CONTENTS

EXECUTIVE SUMMARY ............................................................................................................ 4

I. INTRODUCTION ................................................................................................................ 4 5

II. NEED OF THE NATION TO CONSERVE ENERGY ....................................................... 47

III. BASELINE AND ALTERNATIVES ................................................................................. 52

IV. IMPACT OF OTHER GOVERNMENTAL VEHICLE STANDARDS ON FUEL

ECONOMY ....................................................................................................................... ........... 94

V. FUEL ECONOMY ENHANCING TECHNOLOGIES AND THE VOLPE MODEL ...... 103

VI. MANUFACTURER CAFE CAPABILITIES ................................................................... 104

VII. COST AND SALES IMPACTS ..................................................................................... 260

VIII. BENEFITS FROM IMPROVED FUEL ECONOMY ................................................... 313

IX. IMPACT OF WEIGHT REDUCTION ON SAFETY ......... Error! Bookmark not defined.

X. NET BENEFITS AND SENSITIVITY ANALYSES ........... Error! Bookmark not defined.

XI. FLEXIBILITIES IN MEETING THE STANDARD ........... Error! Bookmark not defined.

XII. PROBABILISTIC UNCERTAINTY ANALYSIS............ Error! Bookmark not defined.

XIII. REGULATORY FLEXIBILITY ACT AND UNFUNDED MANDATES REFORM ACT

ANALYSIS .................................................................................... Error! Bookmark not defined.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.



### EXECUTIVE SUMMARY

This Preliminary Regulatory Impact Analysis (PRIA) has been prepared by the National Highway Traffic Safety Administration (NHTSA) to inform the agency’s consideration of proposed Corporate Average Fuel Economy (CAFE) standards for passenger cars and light trucks for model years (MYs) 2017 through 2025. NHTSA is required to set CAFE standards by the Energy Policy and Conservation Act of 1975 (EPCA), as amended by the Energy Independence and Security Act of 2007 (EISA). NHTSA does not have discretion not to set CAFE standards each model year for passenger cars and light trucks. CAFE standards must be set at least 18 months prior to the beginning of the model year; must be “attribute-based and defined by a mathematical function;” and must be set at the maximum feasible level that NHTSA determines manufacturers can reach for that fleet in that model year, among other requirements.
See 49 U.S.C. 32902 and Section IV.D of the preamble that this PRIA accompanies for more information.

This assessment examines the costs and benefits of improving the fuel economy of passenger cars and light trucks for MYs 2017-2025, and also the costs and benefits of improving the fuel economy of those vehicles at alternative rates of increase (both higher and lower) during those model years. As part of that examination, it in cludes a discussion of the technologies that can improve fuel economy, analysis of the potential impact on retail prices, safety, lifetime fuel savings and their value to consumers, and other societal benefits such as improved energy security and reduced emissions of pollutants and greenhouse gases. 1

As explained above, EISA requires NHTSA to se t attribute-based CAFE standards that are based on a mathematical function. The MY 2017-2025 CAFE standards for passenger cars and light trucks are based on vehicle footprint, as were the standards for MYs 2012-2016. 2 The mathematical function or “curve” representing the footprint-based standards is a constrained linear function that provides a separate fuel economy target for each vehicle footprint, generally with more stringent targets for smaller vehicles and less stringent targets for larger vehicles. Different parameters for the continuous mathematical function are derived. Individual manufacturers will be required to comply with a single fuel economy level that is based on the distribution of its production for that year among the footprints of its vehicles. Although a manufacturer’s compliance obligation is determined in the same way for both passenger cars and light trucks, the footprint target curves for th e different fleets are established with different continuous mathematical functions that are intended to be specific to the vehicles’ design capabilities, to reflect the statutory requirement th at the standards are supposed to be “maximum feasible” for each fleet separately.

1 This analysis does not contain NHTSA’s assessment of the potential environmental im pacts of the final rule for purposes of the National Environmental Policy Act (NEPA), 42 U.S.C. 4321-4347, which is contained in the agency’s Draft Environmental Impact Statem ent (DEIS) accompanying the proposed rule.
2 Vehicle Footprint is defined as the wheelbase (the distan ce from the center of the front axle to the center of the rear axle) times the average track width (the distance betw een the centerline of the tires) of the vehicle (in square feet).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

In order to evaluate the costs and benefits of the rule, a baseline prediction of the fuel economy and mix of vehicles that would be sold in MY s 2017 to 2025 in the absence of the rule was constructed. As was done for the MY 2012-2016 final rule, a baseline was developed using each manufacturer’s MY 2008 fleet as represented in CA FE certification data available to EPA. In order to conduct this analysis, we assume that similar vehicles will be produced through MY 2025 and technologies are added to this baseline fleet to determine what mpg levels could be achieved by the manufacturers in the MYs 2017-2025 timeframe. The main analysis includes a “flat” baseline, for which we assume that manufacturers would have made no fuel economy improvements above the MY 2016 CAFE standards. In the sensitivity analysis section, we examine an alternative baseline, for which we assume that manufacturers would meet market demand for slightly higher fuel economy levels in light of higher real prices of fuel and given the new fuel economy labeling rule that was promulgated earlier this year and would supply technologies that have a consumer payback (defined by fuel savings exceed retail price increases) in one year or less. NHTSA seeks comment on which of these baselines is a better prediction of what would occur if the proposed rule were not adopted, or whether the baseline should include a more fuel efficient mix of vehicles that incorporates all fuel economy improvements that consumers value more than they cost.

NHTSA has examined nine alternatives, including six that are defined as annual percentage improvements over the baseline – 2%/year, 3%/year, 4%/year, 5%/year, 6%/year, and 7%/year. In addition to those six are what NHTSA has called the “Preferred Alternative,” which represents the standards that the agency is proposing for MYs 2017-2025; the “Maximum Net Benefits” alternative, which Executive Orders 12866 and 13563 encourage the agency to choose unless statutory considerations mandate otherwise; and the “Total Costs Equal Total Benefits” alternative. Looking at the “req uired” mpg levels in Table 3a and 3b, the “Preferred Alternative” for passenger cars would require fuel economy levels that are generally between the 3 and 4 percent annual increase alternatives, although the percentage increase varies from year to year. The “Preferred Alternative” for light trucks starts at less than the 2% alternative in MY 2017 and increases to between the 3 and 4 percent alternative in MY 2025. The “Maximum Net Benefits” alternative is based upon the agency’s assessment of the availability of technologies and a marginal cost/benefit analysis. In this cas e the agency continues to include additional technologies in its analysis until the marginal cost of adding the next technology exceeds the marginal benefit. The “Maximum Net Benefit” for passenger cars would require levels that are higher than the “Preferred Alternative” in MYs 2017 through 2022, but then falls below the preferred alternative levels in MY 2023-25. The “Maximum Net Benefit” required mpg level for light trucks is higher in ever y year than the levels in the “Preferred Alternative.” The “Total Costs Equal Total Benefits” alternative represents an increase in the standard to a point where essentially total costs of the t echnologies added together over the baseline added equals total benefits over the baseline. In this analysis, fo r brevity, at times it is labeled “TC = TB.” The “TC = TB” levels are higher than the “Preferred” alternative levels in all years.

The agency performed a variety of sensitivity analyses to examine the variability of the CAFE model’s results to certain economic assumptions. Sensitivity analyses were performed on the following:Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

1) The price of gasoline: The main analysis uses the Reference Case AEO 2011 estimate for the price of gasoline; we study the effect of using the AEO 2011 Low and High Price Cases on the model results. 2) The rebound effect: The main analysis uses a rebound effect of 10 percent to project increased miles traveled as the cost per mile decreases. In the sensitivity analysis, we examine the effect of using a 5, 15, or 20 percent rebound effect. 3) The value of CO 2 benefits: The main analysis uses an initial value of $22 per ton to quantify the benefits of reducing CO2 emissions. Sensitivity analysis surrounding this assumption considers the use of alternate base values of $5, $36, and $67. 3 4) The military security component: The main analysis does not assign a value to the military security benefits of reducing fuel consumption. In the sensitivity analysis, we examine the impact of using a value of 12 cents per gallon instead. 5) Consumer benefit: The main analysis assumes there is no loss in consumer surplus with vehicles that have an increase in pr ice and higher fuel economy. This sensitivity analysis assumes that there is a 25, or 50 percent loss in consumer surplus – equivalent to the assumption that consumer s will only value the calculated benefits they will achieve at 75, or 50 pe rcent, respectively, of their main analysis estimates. 6) ICM and RPE cost methods: The main analysis uses the ICM cost method with an overall markup factor of 1.2 to 1.25. The retail price equivalent (RPE) cost method results in higher cost estimates for each of the technologies, as it uses a markup factor of 1.5. Sensitivity analysis involving th e RPE method was conducted. The agency also performed a sensitivity analysis using the ICM method, but with NAS estimates of technology costs. 7) Technology costs with NAS cost estimat es: The agency conducted a sensitivity analysis in which the ICM cost method of the main analysis was combined with alternate estimates of technology costs derived from the 2011 NAS report 4 . Note that NAS estimates of technology costs were available for approximately only half of the technology inputs; for technologies lacking NAS cost estimates the agency substituted main analysis cost estimates in the context of this sensitivity analysis. 8) Battery cost: The agency conducted a sensitivit y analysis of battery costs in relation to HEV, PHEV, and EV batteries. For HEV batteries, sensitivity analysis was performed with a +/- 10 percent variation in cost per kWh, while sensitivity analyses involving PHEV and EV batteries utilized alte rnate ranges contingent on the type of battery cathode (see chapter X for additional detail). PHEV and EV battery costs ranged between -20 percent and +35 per cent in this sensitivity analysis. 9) Mass reduction cost: A sensitivity analysis was performed examin ing the impact of vehicle mass reduction that could feasibly be accomplished with a +/- 40 percent impact on vehicle cost.

The agency also performed a probabilistic uncerta inty analysis on the model results of the proposed preferred alternative, as mandated by OMB Circular A-4. Over all nine MYs (2017-

3 These values are rounded to the nearest dollar; the valu es used in the sensitivity analysis are unrounded. The unrounded values are presented in Chapter X.

4 Committee on the Assessment of Technologies for Im proving Light-Duty Vehicle Fuel Economy; National Research Council. “Assessment of Fuel Economy Technologies for Light-Duty Vehicles” (2011). Available at http://www.nap.edu/catalog.php?record_id=12924Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

2025), the higher CAFE standards will produce ne t benefits ranging from $XX billion to $YY billion. There is at least a ZZ percent certainty that higher CAFE standards will produce a net societal benefit in each of the model years covered by this rule. This analysis is presented in detail in Chapter XII [Forthcoming].

The MYs 2017-2025 proposed CAFE standards, like the MYs 2012-2016 CAFE standards, are being proposed jointly with the Environmental Protection Agency (EPA), which is concurrently proposing greenhouse gas (GHG) standards for the same vehicles for the same model years. The joint proposal would extend the National Program established for MYs 2012-2016 for these additional future model years. In working together to develop the next round of standards for MYs 2017-2025, NHTSA and EPA are building on the success of the first phase of the National Program to regulate fuel economy and GHG emissions from U.S. light-duty vehicles, which established the strong and coordinated standards for model years (MY) 2012-2016. As for the MYs 2012-2016 rulemaking, collaboration with Ca lifornia Air Resources Board (CARB) and with industry and other stakeholders has b een a key element in developing the agencies’ proposed rules. Continuing the National Program would ensure that all manufacturers can build a single fleet of U.S. vehicles that would satisfy all requirements under both programs as well as under California’s program, helping to reduce costs and regulatory complexity while providing significant energy security and environmental benefits. The coordinated program being proposed would achieve important reductions of fuel consumption and GHG emissions from passenger cars and light trucks, based on technologies that either are commercially available or that the agencies project will be commercially available in the rulemaking timeframe and that can be incorporated at a reasonable cost. Cons istent with Executive Order 13563, this proposal was developed with early consultation with stakeholders, employs flexible regulatory approaches to reduce burdens, maintains freedom of choice for the public, and helps to harmonize federal and state regulations. Because the agencies ar e collaborating on the National Program, however, it is important to note throughout this analysis that there is significant overlap in costs and benefits for NHTSA’s CAFE program and EPA’s GHG program, and therefore combined program costs and benefits are not a sum of the two individual programs.

Table 1 presents the total costs (technology and social), benefits, and net benefits for NHTSA’s proposed CAFE levels by alternative. The values in Table 1 display the total costs for all MY 2017-2025 vehicles and the benefits and net benefits represent the impacts of the standards over the full lifetimes of the vehicles projected to be sold during model years 2017 – 2025.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 1 NHTSA’s Estimated 2017-2025 Model Year Costs, Benefits, and Net Benefits 5 under the Preferred Alternative CAFE Standards (Billions of 2009 Dollars)

3% Discount Rate
Costs $162.8
Benefits $486.4
Net Benefits $323.5

7% Discount Rate
Costs $157.5
Benefits $395.5
Net Benefits $238.0

Table 2 shows the overall analysis summary of costs, benefits, and net benefits for the nine model years by alternative for the combined light duty fleet. Table 4 shows the agency’s projection of the estimated actual harmonic average that would be achieved by the manufacturers, assuming that some manufacturers will pay fines ra ther than meet the required levels. Table 3 shows the estimated required levels . All of the tables in this analysis compare the flat MY 2016 baseline to the projected achieved harmonic average. Additionally all of the tables in the Executive Summary and in the analysis as a whole use the central value for the Social Cost of Carbon (SCC), which is the aver age SCC across models at the 3 percent discount rate. The SCC is discussed in more detail in Chapter VIII. For purposes of capturing the uncertainties involved in regulatory impact analysis, we emphasize the importance and value of considering the full range of SCC values.

Costs : Costs were estimated based on the specific technologies that were applied to improve each manufacturer’s fuel economy up to their achieved level under each alternative or fines that would be assessed. Table 5 provides the cost an d fine estimates on an average per-vehicle basis, and Table 6 provides those estimates (including so cial costs and excluding fines) on a fleet-wide basis in millions of dollars.

Benefits : Benefits are determined mainly from fuel savings over the lifetime of the vehicle, but also include externalities such as reductions in criteria pollutants. The agency uses a 3 percentand 7 percent discount rate to value intra-generational future benefits and costs. Intergenerational 6 benefits from future carbon dioxide reductions are discounted at 3 percent in the main analysis, even when intra-generational benefits are discounted at 7 percent. Sensitivity analyses in Chapter X analyze other inter-generational discount rates that accompany alternative

5 In Table 1, and throughout this regulatory impact analysis , discounting is applied to all costs and benefits with the exception of technology costs.

6 Inter-generational benefits, which include reductions in the expected future economic damages caused by increased global temperatures, a rise in sea le vels, and other projected impacts of cl imate change, are anticipated to extend over a period from approximately fifty to two hundred or mo re years in the future, and will thus be experienced primarily by generations that are not now living.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

estimates of the social cost of carbon. Table 7 provides those estimates on an industry-wide basis at a 3 percent discount rate and Table 10 provi des the estimates at a 7 percent discount rate.

Net Benefits : Tables 8 and 11 compare total net benefits of each alternative at the 3 percent and 7 percent discount rates, respectively.

Fuel Savings : Table 12 shows the lifetime fuel savings in millions of gallons.

Table 2 Total Costs, Benefits, and Net Benefits Passenger Cars and Light Trucks MY 2017-2025 Combined (Millions of 2009 Dollars)

3% Discount Rate
Costs Benefits Net Benefits
Preferred Alternative $162,828 $486,370 $323,542
2% Annual Increase $75,992 $309,583 $233,591
3% Annual Increase $136,427 $456,700 $320,273
4% Annual Increase $209,818 $571,395 $361,577
5% Annual Increase $296,596 $672,856 $376,260
6% Annual Increase $367,293 $743,051 $375,758
7% Annual Increase $419,263 $794,971 $375,708
Max Net Benefits $267,471 $633,921 $366,450
Total Cost = Total Benefit $323,500 $713,000 $389,500

7% Discount Rate
Costs Benefits Net Benefits
Preferred Alternative $157,500 $395,455 $237,955
2% Annual Increase $72,655 $251,425 $178,770
3% Annual Increase $131,562 $370,819 $239,256
4% Annual Increase $203,761 $463,786 $260,025
5% Annual Increase $289,140 $546,327 $257,187
6% Annual Increase $358,386 $603,203 $244,816
7% Annual Increase $408,834 $645,158 $236,323
Max Net Benefits $226,762 $475,201 $248,439
Total Cost = Total Benefit $314,786 $578,120 $263,334Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 3a Alternative CAFE Levels Estimated Required Average for the Passenger Car Fleet, in mpg 7

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY
2021 Passenger Cars
Preferred Alternative 40.0 41.4 43.0 44.7 46.6
2% Annual Increase 39.4 40.2 41.1 41.9 42.8
3% Annual Increase 39.8 41.1 42.4 43.7 45.1
4% Annual Increase 40.2 41.9 43.7 45.6 47.5

5% Annual Increase 40.6 42.8 45.2 47.6 50.2

6% Annual Increase 41.1 43.8 46.7 49.7 53.0
7% Annual Increase 41.5 44.8 48.2 51.9 56.0 Max Net Benefits (3% Discount Rate) 43.6 45.7 46.9 48.1 48.6 Max Net Benefits (7% Discount Rate) 43.6 45.5 46.7 48.1 48.6 Total Cost = Total Benefit (3% Discount Rate) 44.8 46.7 48.1 49.6 50.7

Total Cost = Total Benefit (7% Discount Rate) 44.8 46.7 48.1 49.6 50.7

Alternative MY
2022 MY
2023 MY
2024 MY
2025 Passenger Cars
Preferred Alternative 48.8 51.0 53.5 56.0

2% Annual Increase 43.7 44.6 45.5 46.5
3% Annual Increase 46.5 48.0 49.5 51.1
4% Annual Increase 49.6 51.7 53.9 56.3

5% Annual Increase 52.9 55.8 58.8 62.0
6% Annual Increase 56.5 60.2 64.2 68.5
7% Annual Increase 60.4 65.1 70.2 75.7 Max Net Benefits (3% Discount Rate) 48.9 49.4 50.4 51.2 Max Net Benefits (7% Discount Rate) 48.9 49.4 50.2 50.7 Total Cost = Total Benefit (3% Discount Rate) 53.1 55.0 57.1 58.9 Total Cost = Total Benefit (7% Discount Rate) 53.1 55.0 57.1 58.9

7 The choice of a 3 or 7 percent discount rate can impact the results of the Max Net Benefits and Total Cost = Total Benefits scenarios. The results of all other scenarios are not impacted by choice of discount rate. Results for both 3 and 7 percent discount rates are therefore presented for both Max Net Benefits and Total Cost = Total Benefit scenarios.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 3b Alternative CAFE Levels Estimated Required Average for the Light Truck Fleet, in mpg

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY
2021 Light Trucks
Preferred Alternative 29.4 30.0 30.6 31.2 33.3
2% Annual Increase 30.1 30.8 31.6 32.1 32.8

3% Annual Increase 30.4 31.5 32.6 33.5 34.6
4% Annual Increase 30.6 32.1 33.6 35.0 36.5
5% Annual Increase 30.9 32.8 34.7 36.5 38.5

6% Annual Increase 31.3 33.5 35.8 38.1 40.7

7% Annual Increase 31.6 34.2 37.0 39.8 43.0 Max Net Benefits (3% Discount Rate) 34.0 35.8 38.1 39.4 40.7 Max Net Benefits (7% Discount Rate) 32.8 34.6 36.4 37.6 39.1 Total Cost = Total Benefit (3% Discount Rate) 34.2 36.0 37.9 39.6 40.7

Total Cost = Total Benefit (7% Discount Rate) 34.3 36.0 37.9 39.4 40.7

Alternative MY
2022 MY
2023 MY
2024 MY
2025 Light Trucks
Preferred Alternative 34.9 36.6 38.5 40.3
2% Annual Increase 33.5 34.3 35.1 35.8

3% Annual Increase 35.7 36.9 38.2 39.4
4% Annual Increase 38.1 39.8 41.6 43.4
5% Annual Increase 40.6 42.9 45.4 47.9

6% Annual Increase 43.4 46.3 49.5 52.8
7% Annual Increase 46.4 50.1 54.2 58.4 Max Net Benefits (3% Discount Rate) 41.6 42.7 44.4 45.6 Max Net Benefits (7% Discount Rate) 39.5 39.9 40.7 41.2 Total Cost = Total Benefit (3% Discount Rate) 41.3 43.6 45.6 47.1 Total Cost = Total Benefit (7% Discount Rate) 41.3 43.6 45.6 47.1Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 3c Alternative CAFE Levels Estimated Required Average for the Combined Fleet, in mpg

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY
2021 Passenger Cars & Light Trucks
Preferred Alternative 35.3 36.4 37.5 38.8 40.9
2% Annual Increase 35.4 36.2 37.1 37.9 38.7

3% Annual Increase 35.7 37.0 38.2 39.5 40.8
4% Annual Increase 36.1 37.7 39.4 41.2 43.0
5% Annual Increase 36.4 38.5 40.7 43.0 45.4

6% Annual Increase 36.8 39.4 42.1 44.9 47.9
7% Annual Increase 37.2 40.3 43.5 46.9 50.6 Max Net Benefits (3% Discount Rate) 39.5 41.5 43.3 44.6 45.5 Max Net Benefits (7% Discount Rate) 38.9 40.8 42.4 43.8 44.8 Total Cost = Total Benefit (3% Discount Rate) 40.2 42.1 43.9 45.5 46.7

Total Cost = Total Benefit (7% Discount Rate) 40.3 42.1 43.9 45.5 46.7

Alternative MY
2022 MY
2023 MY
2024 MY
2025 Passenger Cars & Light Trucks
Preferred Alternative 42.9 45.0 47.3 49.6

2% Annual Increase 39.5 40.4 41.4 42.3
3% Annual Increase 42.1 43.5 45.0 46.5
4% Annual Increase 44.9 46.9 49.1 51.2

5% Annual Increase 47.9 50.6 53.5 56.5
6% Annual Increase 51.1 54.6 58.4 62.4
7% Annual Increase 54.6 59.0 63.8 69.0 Max Net Benefits (3% Discount Rate) 46.1 46.9 48.2 49.2 Max Net Benefits (7% Discount Rate) 45.1 45.7 46.5 47.1 Total Cost = Total Benefit (3% Discount Rate) 48.3 50.5 52.6 54.4 Total Cost = Total Benefit (7% Discount Rate) 48.3 50.5 52.6 54.4Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 3d Estimated Required Preferre d Alternative CAFE Levels Projected Achieved Harmonic Average fo r the Fleet, in gallons per 100 miles

MY
2017 MY
2018 MY
2019 MY
2020 MY
2021 Passenger Cars 2.5018 2.4129 2.3258 2.2390 2.1453 Light Trucks 3.4001 3.3285 3.2707 3.2037 2.9994
Combined 2.8325 2.7462 2.6644 2.5791 2.4452
MY
2022 MY
2023 MY
2024 MY
2025 Passenger Cars 2.0493 1.9590 1.8705 1.7869 Light Trucks 2.8637 2.7286 2.5994 2.4795

Combined 2.3319 2.2218 2.1148 2.0161Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 4a Alternative CAFE Levels Projected Achieved Harmonic Average for the Passenger Car Fleet, in mpg 8

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY
2021 Passenger Cars
Preferred Alternative 38.8 40.5 42.6 44.5 46.1
2% Annual Increase 38.1 39.4 40.7 41.8 42.6

3% Annual Increase 38.5 40.3 42.1 43.7 44.9
4% Annual Increase 39.0 41.1 43.1 45.2 46.6
5% Annual Increase 39.7 42.0 44.3 46.7 48.4

6% Annual Increase 40.4 43.0 45.5 48.6 50.1

7% Annual Increase 40.7 43.4 46.1 49.0 50.5 Max Net Benefits (3% Discount Rate) 41.7 43.0 44.4 45.7 46.9 Max Net Benefits (7% Discount Rate) 41.7 43.0 44.5 45.8 46.8 Total Cost = Total Benefit (3% Discount Rate) 42.0 43.7 45.2 46.8 48.5

Total Cost = Total Benefit (7% Discount Rate) 42.0 43.7 45.3 46.8 48.6

Alternative MY
2022 MY
2023 MY
2024 MY
2025 Passenger Cars
Preferred Alternative 47.2 48.9 50.5 52.8

2% Annual Increase 43.2 43.7 44.4 45.2

3% Annual Increase 45.8 46.6 47.7 49.1
4% Annual Increase 47.6 48.9 51.2 52.7

5% Annual Increase 50.3 52.1 54.1 56.8

6% Annual Increase 52.0 53.5 56.8 60.2
7% Annual Increase 51.7 53.7 59.5 63.0 Max Net Benefits (3% Discount Rate) 47.3 47.9 48.6 49.3 Max Net Benefits (7% Discount Rate) 47.2 47.8 48.4 49.1 Total Cost = Total Benefit (3% Discount Rate) 49.5 51.7 53.6 55.2 Total Cost = Total Benefit (7% Discount Rate) 49.5 51.8 53.6 55.2

8 The choice of a 3 or 7 percent discount rate can impact the results of the Max Net Benefits and Total Cost = Total Benefits scenarios. The results of al l other scenarios are not impacted by choice of discount rate. Results for both 3 and 7 percent discount rates are therefore presented for both Max Net Benefits and Total Cost = Total Benefit scenarios.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 4b Alternative CAFE Levels Projected Achieved Harmonic Average for the Light Truck Fleet, in mpg

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY
2021 Light Trucks
Preferred Alternative 29.0 30.1 31.9 33.1 35.0

2% Annual Increase 29.4 30.4 31.7 32.4 33.3
3% Annual Increase 29.8 31.0 32.9 34.1 35.7

4% Annual Increase 30.3 31.8 33.9 35.5 37.2

5% Annual Increase 30.7 32.4 34.7 36.7 38.6
6% Annual Increase 31.1 33.1 35.7 37.7 39.3
7% Annual Increase 31.5 33.4 36.1 38.5 40.0 Max Net Benefits (3% Discount Rate) 32.5 33.8 35.8 37.4 39.4 Max Net Benefits (7% Discount Rate) 31.7 33.2 35.1 36.4 37.9 Total Cost = Total Benefit (3% Discount Rate) 32.5 33.9 35.9 37.7 39.6

Total Cost = Total Benefit (7% Discount Rate) 32.6 33.9 35.8 37.6 39.6

Alternative MY
2022 MY
2023 MY
2024 MY
2025 Light Trucks
Preferred Alternative 35.7 36.7 37.6 38.3
2% Annual Increase 33.6 34.0 34.6 35.2

3% Annual Increase 36.4 36.9 37.6 38.3

4% Annual Increase 38.3 39.4 40.3 41.3
5% Annual Increase 39.7 40.7 42.6 44.0
6% Annual Increase 40.4 41.3 43.2 44.7

7% Annual Increase 41.6 42.9 45.2 46.4 Max Net Benefits (3% Discount Rate) 40.0 41.0 42.2 43.8 Max Net Benefits (7% Discount Rate) 38.3 39.2 39.8 40.0 Total Cost = Total Benefit (3% Discount Rate) 40.2 41.5 43.1 44.7 Total Cost = Total Benefit (7% Discount Rate) 40.2 41.7 42.9 44.5Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 4c Alternative CAFE Levels Projected Achieved Harmonic Average for the Combined Fleet, in mpg

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY
2021 Passenger Cars & Light Trucks
Preferred Alternative 34.5 36.0 38.0 39.7 41.5

2% Annual Increase 34.4 35.6 37.0 37.9 38.8
3% Annual Increase 34.7 36.3 38.3 39.8 41.2

4% Annual Increase 35.3 37.2 39.3 41.2 42.8
5% Annual Increase 35.8 37.9 40.3 42.6 44.4
6% Annual Increase 36.4 38.8 41.4 44.1 45.7

7% Annual Increase 36.7 39.2 42.0 44.7 46.3 Max Net Benefits (3% Discount Rate) 37.8 39.2 40.9 42.4 44.0 Max Net Benefits (7% Discount Rate) 37.4 38.8 40.6 42.0 43.2 Total Cost = Total Benefit (3% Discount Rate) 38.0 39.5 41.4 43.1 45.0

Total Cost = Total Benefit (7% Discount Rate) 38.0 39.5 41.4 43.1 45.0

Alternative MY
2022 MY
2023 MY
2024 MY
2025 Passenger Cars & Light Trucks
Preferred Alternative 42.5 43.9 45.3 46.9
2% Annual Increase 39.3 39.8 40.6 41.3
3% Annual Increase 42.0 42.7 43.7 44.9
4% Annual Increase 43.9 45.1 46.9 48.3
5% Annual Increase 46.0 47.6 49.6 51.8

6% Annual Increase 47.3 48.6 51.4 54.0

7% Annual Increase 47.7 49.5 53.8 56.3 Max Net Benefits (3% Discount Rate) 44.5 45.3 46.2 47.3 Max Net Benefits (7% Discount Rate) 43.7 44.5 45.1 45.7 Total Cost = Total Benefit (3% Discount Rate) 45.8 47.7 49.5 51.2 Total Cost = Total Benefit (7% Discount Rate) 45.8 47.8 49.5 51.1Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 4d Preferred Alternative CAFE Levels Projected Achieved Harmonic Average fo r the Fleet, in gallons per 100 miles

MY
2017 MY
2018 MY
2019 MY
2020 MY
2021 Passenger Cars 2.5800 2.4685 2.3464 2.2465 2.1680

Li g ht Trucks 3.4455 3.3247 3.1343 3.0237 2.8566

Combined 2.8986 2.7802 2.6287 2.5205 2.4098
MY
2022 MY
2023 MY
2024 MY
2025 Passenger Cars 2.1176 2.0441 1.9800 1.8929 Light Trucks 2.7989 2.7214 2.6562 2.6127

Combined 2.3540 2.2754 2.2066 2.1311Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 5a Average Incremental Technology Costs or Fines Per Vehicle 9 Passenger Cars (2009 Dollars)

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY
2021 Passenger Cars
Preferred Alternative $180 $366 $589 $831 $1,072

2% Annual Increase $70 $174 $272 $357 $427

3% Annual Increase $121 $293 $466 $649 $819

4% Annual Increase $226 $491 $700 $957 $1,167

5% Annual Increase $369 $687 $937 $1,288 $1,600

6% Annual Increase $544 $946 $1,244 $1,879 $2,143

7% Annual Increase $604 $1,073 $1,420 $1,952 $2,300 Max Net Benefits (3% Discount Rate) $1,002 $1,110 $1,199 $1,282 $1,379 Max Net Benefits (7% Discount Rate) $1,000 $1,102 $1,201 $1,282 $1,367 Total Cost = Total Benefit (3% Discount Rate) $901 $1,104 $1,270 $1,419 $1,650

Total Cost = Total Benefit (7% Discount Rate) $901 $1,115 $1,279 $1,429 $1,651

Alternative MY
2022 MY
2023 MY
2024 MY
2025 Passenger Cars
Preferred Alternative $1,217 $1,568 $1,826 $2,049

2% Annual Increase $483 $544 $640 $716

3% Annual Increase $919 $1,032 $1,192 $1,379

4% Annual Increase $1,319 $1,571 $2,042 $2,097

5% Annual Increase $2,045 $2,582 $2,962 $3,127

6% Annual Increase $2,712 $3,040 $3,845 $3,896

7% Annual Increase $2,651 $3,327 $5,031 $4,892 Max Net Benefits (3% Discount Rate) $1,390 $1,432 $1,516 $1,502 Max Net Benefits (7% Discount Rate) $1,376 $1,423 $1,491 $1,471 Total Cost = Total Benefit (3% Discount Rate) $1,862 $2,376 $2,743 $2,639 Total Cost = Total Benefit (7% Discount Rate) $1,860 $2,376 $2,730 $2,630

9 The choice of a 3 or 7 percent discount rate can impact the results of the Max Net Bene fits and Total Cost = Total Benefits scenarios. The results of all other scenarios are not impacted by choice of discount rate. Results for both 3 and 7 percent discount rates are therefore presented for both Max Net Benefits and Total Cost = Total Benefit scenarios.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 5b Average Incremental Technology Costs or Fines Per Vehicle Light Trucks (2009 Dollars)

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY
2021 Light Trucks
Preferred Alternative $62 $186 $389 $580 $832

2% Annual Increase $128 $223 $334 $416 $472

3% Annual Increase $208 $358 $552 $744 $947

4% Annual Increase $339 $540 $854 $1,224 $1,583

5% Annual Increase $463 $784 $1,175 $1,669 $2,096

6% Annual Increase $692 $1,123 $1,593 $2,073 $2,444

7% Annual Increase $879 $1,283 $1,730 $2,406 $2,712 Max Net Benefits (3% Discount Rate) $1,289 $1,485 $1,726 $2,161 $2,507 Max Net Benefits (7% Discount Rate) $972 $1,194 $1,409 $1,636 $1,847 Total Cost = Total Benefit (3% Discount Rate) $1,287 $1,523 $1,767 $2,238 $2,559

Total Cost = Total Benefit (7% Discount Rate) $1,294 $1,509 $1,756 $2,221 $2,570

Alternative MY
2022 MY
2023 MY
2024 MY
2025 Light Trucks
Preferred Alternative $935 $1,092 $1,220 $1,277

2% Annual Increase $504 $544 $620 $690

3% Annual Increase $1,042 $1,116 $1,224 $1,325

4% Annual Increase $1,792 $2,013 $2,197 $2,284

5% Annual Increase $2,345 $2,602 $3,191 $3,374

6% Annual Increase $2,735 $2,981 $3,671 $3,921

7% Annual Increase $3,315 $3,763 $4,506 $4,503 Max Net Benefits (3% Discount Rate) $2,609 $2,777 $3,107 $3,250 Max Net Benefits (7% Discount Rate) $1,878 $1,998 $2,105 $2,027 Total Cost = Total Benefit (3% Discount Rate) $2,659 $3,076 $3,524 $3,588 Total Cost = Total Benefit (7% Discount Rate) $2,684 $3,123 $3,447 $3,550Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 5c Average Incremental Technology Costs or Fines Per Vehicle Combined (2009 Dollars)

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY
2021 Passenger Cars & Light Trucks
Preferred Alternative $136 $300 $517 $743 $988

2% Annual Increase $92 $192 $294 $378 $443

3% Annual Increase $153 $317 $497 $683 $864

4% Annual Increase $268 $509 $755 $1,051 $1,313

5% Annual Increase $403 $723 $1,022 $1,423 $1,774

6% Annual Increase $599 $1,010 $1,369 $1,947 $2,248

7% Annual Increase $705 $1,149 $1,531 $2,112 $2,445 Max Net Benefits (3% Discount Rate) $1,108 $1,247 $1,388 $1,592 $1,775 Max Net Benefits (7% Discount Rate) $990 $1,135 $1,276 $1,406 $1,535 Total Cost = Total Benefit (3% Discount Rate) $1,043 $1,256 $1,448 $1,708 $1,969

Total Cost = Total Benefit (7% Discount Rate) $1,046 $1,259 $1,450 $1,708 $1,974

Alternative MY
2022 MY
2023 MY
2024 MY
2025 Passenger Cars & Light Trucks
Preferred Alternative $1,119 $1,406 $1,623 $1,793

2% Annual Increase $490 $544 $633 $707

3% Annual Increase $961 $1,061 $1,203 $1,361

4% Annual Increase $1,483 $1,722 $2,094 $2,159

5% Annual Increase $2,149 $2,589 $3,039 $3,209

6% Annual Increase $2,720 $3,020 $3,787 $3,905

7% Annual Increase $2,881 $3,476 $4,855 $4,763 Max Net Benefits (3% Discount Rate) $1,813 $1,891 $2,050 $2,080 Max Net Benefits (7% Discount Rate) $1,550 $1,620 $1,697 $1,655 Total Cost = Total Benefit (3% Discount Rate) $2,139 $2,615 $3,005 $2,953 Total Cost = Total Benefit (7% Discount Rate) $2,146 $2,631 $2,970 $2,935Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 6a Incremental Total Costs by Societal Perspective 10 , by Alternative Passenger Cars, 3% Discount Rate (Millions of 2009 Dollars)

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY 2021 Passenger Cars
Preferred Alternative $2,128 $4,204 $6,850 $9,804 $12,565

2% Annual Increase $859 $2,084 $3,325 $4,448 $5,394

3% Annual Increase $1,466 $3,454 $5,568 $7,830 $9,803

4% Annual Increase $2,646 $5,589 $8,063 $11,106 $13,561

5% Annual Increase $4,242 $7,686 $10,625 $14,651 $17,982

6% Annual Increase $6,065 $10,211 $13,581 $21,235 $24,332

7% Annual Increase $6,836 $11,662 $15,500 $21,445 $25,048

Max Net Benefits $10,883 $11,853 $12,970 $14,350 $15,894

Total Cost = Total Benefit $9,595 $11,832 $13,532 $15,604 $18,350

Alternative MY
2022 MY
2023 MY
2024 MY
2025 9-Year Total Passenger Cars
Preferred Alternative $14,462 $18,931 $22,391 $26,213 $117,547

2% Annual Increase $6,198 $7,077 $8,468 $9,805 $47,658

3% Annual Increase $11,204 $12,765 $14,956 $17,868 $84,914

4% Annual Increase $15,545 $18,853 $25,136 $26,857 $127,354

5% Annual Increase $23,681 $30,955 $36,059 $40,433 $186,314

6% Annual Increase $31,511 $35,851 $47,229 $50,367 $240,382

7% Annual Increase $28,190 $36,530 $61,996 $63,932 $271,139

Max Net Benefits $16,446 $17,370 $18,881 $19,544 $138,191

Total Cost = Total Benefit $20,832 $28,557 $34,114 $34,561 $186,975

10 “Societal perspective” includes technology costs and societal costs, but does not include payment of civil penalties by manufacturers in lieu of compliance with the CAFE standards.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 6b Incremental Total Costs by Societal Perspective, by Alternative Light Trucks, 3% Discount Rate (Millions of 2009 Dollars)

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY 2021 Light Trucks
Preferred Alternative $447 $1,289 $2,721 $4,028 $5,784

2% Annual Increase $918 $1,536 $2,355 $2,938 $3,428

3% Annual Increase $1,462 $2,433 $3,783 $5,076 $6,525

4% Annual Increase $2,355 $3,572 $5,547 $7,891 $10,208

5% Annual Increase $3,137 $4,979 $7,384 $10,421 $13,227

6% Annual Increase $4,550 $7,010 $9,829 $12,755 $15,080

7% Annual Increase $5,694 $7,956 $10,654 $14,646 $16,480

Max Net Benefits $8,100 $9,180 $10,497 $13,217 $15,502

Total Cost = Total Benefit $8,064 $9,316 $10,709 $13,591 $15,774

Alternative MY
2022 MY
2023 MY
2024 MY
2025 9-Year Total Light Trucks
Preferred Alternative $6,493 $7,482 $8,306 $8,731 $45,281

2% Annual Increase $3,698 $3,966 $4,492 $5,002 $28,333

3% Annual Increase $7,201 $7,644 $8,337 $9,052 $51,514

4% Annual Increase $11,584 $12,815 $13,911 $14,582 $82,464

5% Annual Increase $14,820 $16,012 $19,622 $20,679 $110,283

6% Annual Increase $16,601 $17,705 $21,072 $22,309 $126,911

7% Annual Increase $19,561 $21,876 $25,935 $25,322 $148,124

Max Net Benefits $16,157 $17,158 $19,026 $20,442 $129,280

Total Cost = Total Benefit $16,353 $18,808 $21,530 $22,379 $136,525Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 6c Incremental Total Costs by Societal Perspective, by Alternative Combined, 3% Discount Rate

(Millions of 2009 Dollars)

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY 2021 Passenger Cars & Light Trucks
Preferred Alternative $2,575 $5,492 $9,571 $13,832 $18,349

2% Annual Increase $1,777 $3,620 $5,680 $7,386 $8,822

3% Annual Increase $2,928 $5,887 $9,351 $12,907 $16,328

4% Annual Increase $5,000 $9,161 $13,611 $18,997 $23,769

5% Annual Increase $7,379 $12,665 $18,008 $25,072 $31,209

6% Annual Increase $10,615 $17,221 $23,409 $33,990 $39,411

7% Annual Increase $12,530 $19,617 $26,155 $36,091 $41,527

Max Net Benefits $18,983 $21,034 $23,467 $27,566 $31,396

Total Cost = Total Benefit $17,659 $21,148 $24,241 $29,195 $34,124

Alternative MY
2022 MY
2023 MY
2024 MY
2025 9-Year Total Passenger Cars & Light Trucks
Preferred Alternative $20,955 $26,413 $30,696 $34,944 $162,828

2% Annual Increase $9,896 $11,043 $12,960 $14,807 $75,992

3% Annual Increase $18,405 $20,409 $23,293 $26,920 $136,427

4% Annual Increase $27,128 $31,667 $39,046 $41,439 $209,818

5% Annual Increase $38,501 $46,967 $55,681 $61,112 $296,596

6% Annual Increase $48,112 $53,556 $68,301 $72,676 $367,293

7% Annual Increase $47,751 $58,406 $87,931 $89,254 $419,263

Max Net Benefits $32,603 $34,528 $37,907 $39,986 $267,471

Total Cost = Total Benefit $37,185 $47,364 $55,644 $56,940 $323,500Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 7a Present Value of Lifetime Societal Benefits 11 , by Alternative Passenger Cars, (3% Discount Rate) (Millions of 2009 Dollars)

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY 2021 Passenger Cars
Preferred Alternative $6,705 $12,261 $19,694 $26,613 $32,674
2% Annual Increase $3,630 $7,588 $11,924 $15,715 $18,847
3% Annual Increase $5,497 $11,312 $17,587 $23,512 $28,031
4% Annual Increase $7,920 $14,866 $21,752 $29,043 $34,291
5% Annual Increase $10,963 $18,416 $26,110 $34,366 $40,276
6% Annual Increase $13,715 $21,855 $30,058 $40,613 $45,922
7% Annual Increase $15,125 $23,789 $32,438 $42,060 $47,527
Max Net Benefits $19,217 $22,208 $26,558 $30,914 $35,760
Total Cost = Total Benefit $20,255 $24,397 $29,245 $34,405 $40,958

Alternative MY
2022 MY
2023 MY
2024 MY
2025 9-Year Total Passenger Cars
Preferred Alternative $37,652 $45,196 $52,508 $62,186 $295,490

2% Annual Increase $21,650 $24,487 $28,724 $32,976 $165,541

3% Annual Increase $32,229 $36,404 $42,077 $48,999 $245,647

4% Annual Increase $39,238 $45,006 $54,952 $61,816 $308,884

5% Annual Increase $47,837 $55,550 $63,701 $74,115 $371,335

6% Annual Increase $53,501 $60,052 $72,173 $84,248 $422,137

7% Annual Increase $52,568 $60,911 $80,241 $91,814 $446,475

Max Net Benefits $38,249 $41,466 $45,834 $49,915 $310,120

Total Cost = Total Benefit $45,539 $54,712 $62,807 $69,677 $381,994

11 These benefits are considered from a “societal persp ective” because they include externalities. They are distinguished from a consumer perspective, because cons umers generally would not think about the value of carbon dioxide, energy security, etc.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 7b Present Value of Lifetime Societal Benefits, by Alternative Light Trucks, (3% Discount Rate) (Millions of 2009 Dollars)

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY 2021 Light Trucks
Preferred Alternative $1,882 $5,737 $12,771 $17,564 $24,357
2% Annual Increase $3,859 $6,932 $11,915 $14,752 $17,822
3% Annual Increase $5,433 $9,903 $16,721 $21,361 $26,743
4% Annual Increase $8,013 $13,119 $20,242 $26,194 $31,930
5% Annual Increase $9,543 $15,436 $23,257 $30,164 $36,720
6% Annual Increase $11,533 $18,146 $26,582 $33,258 $38,685
7% Annual Increase $13,043 $19,368 $28,008 $35,898 $40,790
Max Net Benefits $17,328 $20,943 $26,779 $32,628 $39,151
Total Cost = Total Benefit $17,403 $21,175 $27,097 $33,186 $39,484

Alternative MY
2022 MY
2023 MY
2024 MY
2025 9-Year Total Light Trucks
Preferred Alternative $27,236 $30,819 $33,935 $36,577 $190,880

2% Annual Increase $19,346 $20,842 $23,050 $25,524 $144,042

3% Annual Increase $29,458 $31,192 $33,685 $36,559 $211,053

4% Annual Increase $35,952 $39,176 $42,165 $45,720 $262,511

5% Annual Increase $40,507 $43,591 $48,913 $53,391 $301,522

6% Annual Increase $42,249 $45,040 $50,254 $55,165 $320,913

7% Annual Increase $46,035 $49,761 $55,798 $59,795 $348,496

Max Net Benefits $41,557 $44,502 $47,889 $53,025 $323,801

Total Cost = Total Benefit $41,599 $45,693 $50,109 $55,259 $331,006Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 7c Present Value of Lifetime Societal Benefits, by Alternative Combined, (3% Discount Rate)

(Millions of 2009 Dollars)

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY 2021 Passenger Cars & Light Trucks
Preferred Alternative $8,587 $17,999 $32,466 $44,177 $57,031
2% Annual Increase $7,488 $14,520 $23,838 $30,467 $36,669
3% Annual Increase $10,930 $21,214 $34,307 $44,873 $54,774
4% Annual Increase $15,932 $27,985 $41,993 $55,236 $66,221
5% Annual Increase $20,506 $33,851 $49,366 $64,530 $76,996
6% Annual Increase $25,248 $40,001 $56,641 $73,871 $84,607
7% Annual Increase $28,168 $43,157 $60,446 $77,957 $88,318
Max Net Benefits $36,544 $43,151 $53,337 $63,542 $74,910
Total Cost = Total Benefit $37,658 $45,572 $56,342 $67,591 $80,442

Alternative MY
2022 MY
2023 MY
2024 MY
2025 9-Year Total Passenger Cars & Light Trucks
Preferred Alternative $64,888 $76,016 $86,443 $98,764 $486,370

2% Annual Increase $40,997 $45,329 $51,774 $58,500 $309,583

3% Annual Increase $61,687 $67,596 $75,762 $85,557 $456,700

4% Annual Increase $75,190 $84,182 $97,117 $107,537 $571,395

5% Annual Increase $88,344 $99,142 $112,615 $127,506 $672,856

6% Annual Increase $95,750 $105,093 $122,427 $139,413 $743,051

7% Annual Increase $98,603 $110,673 $136,039 $151,610 $794,971

Max Net Benefits $79,806 $85,968 $93,723 $102,940 $633,921

Total Cost = Total Benefit $87,139 $100,405 $112,916 $124,936 $713,000Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 8a Present Value of Net Total Benefits 12 by Alternative Passenger Cars, (3% Discount Rate) (Millions of 2009 Dollars)

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY 2021 Passenger Cars
Preferred Alternative $4,577 $8,058 $12,844 $16,809 $20,109

2% Annual Increase $2,771 $5,504 $8,598 $11,267 $13,453

3% Annual Increase $4,030 $7,858 $12,019 $15,682 $18,228

4% Annual Increase $5,274 $9,277 $13,688 $17,937 $20,731

5% Annual Increase $6,722 $10,729 $15,485 $19,715 $22,294

6% Annual Increase $7,650 $11,643 $16,478 $19,378 $21,591

7% Annual Increase $8,289 $12,128 $16,938 $20,614 $22,480

Max Net Benefits $8,333 $10,355 $13,588 $16,564 $19,866

Total Cost = Total Benefit $10,660 $12,565 $15,714 $18,801 $22,608

Alternative MY
2022 MY
2023 MY
2024 MY
2025 9-Year Total Passenger Cars
Preferred Alternative $23,190 $26,265 $30,117 $35,974 $177,944

2% Annual Increase $15,453 $17,410 $20,256 $23,171 $117,882

3% Annual Increase $21,025 $23,640 $27,121 $31,131 $160,733

4% Annual Increase $23,693 $26,153 $29,817 $34,959 $181,529

5% Annual Increase $24,156 $24,595 $27,642 $33,683 $185,021

6% Annual Increase $21,990 $24,201 $24,944 $33,881 $181,755

7% Annual Increase $24,378 $24,382 $18,245 $27,882 $175,336

Max Net Benefits $21,803 $24,095 $26,953 $30,372 $171,929

Total Cost = Total Benefit $24,707 $26,155 $28,693 $35,116 $195,019

12 This table is from a societal perspective, thus, civil pe nalties are deleted from the cost s because they are a transfer payment (from manufacturers to the U.S. Treasury).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 8b Present Value of Net Total Benefits by Alternative Light Trucks, (3% Discount Rate) (Millions of 2009 Dollars)

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY 2021 Light Trucks
Preferred Alternative $1,435 $4,449 $10,050 $13,536 $18,573

2% Annual Increase $2,941 $5,395 $9,560 $11,815 $14,393

3% Annual Increase $3,971 $7,470 $12,938 $16,285 $20,217

4% Annual Increase $5,658 $9,548 $14,694 $18,303 $21,722

5% Annual Increase $6,405 $10,457 $15,873 $19,743 $23,493

6% Annual Increase $6,983 $11,136 $16,753 $20,503 $23,605

7% Annual Increase $7,349 $11,412 $17,354 $21,251 $24,310

Max Net Benefits $9,228 $11,762 $16,282 $19,411 $23,648

Total Cost = Total Benefit $9,339 $11,859 $16,388 $19,595 $23,710

Alternative MY
2022 MY
2023 MY
2024 MY
2025 9-Year Total Light Trucks
Preferred Alternative $20,743 $23,337 $25,630 $27,846 $145,599

2% Annual Increase $15,648 $16,876 $18,558 $20,522 $115,709

3% Annual Increase $22,257 $23,548 $25,348 $27,507 $159,540

4% Annual Increase $24,369 $26,362 $28,254 $31,138 $180,047

5% Annual Increase $25,687 $27,579 $29,291 $32,712 $191,239

6% Annual Increase $25,648 $27,336 $29,183 $32,856 $194,003

7% Annual Increase $26,474 $27,885 $29,863 $34,473 $200,372

Max Net Benefits $25,400 $27,344 $28,863 $32,583 $194,521

Total Cost = Total Benefit $25,246 $26,885 $28,579 $32,881 $194,481Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 8c Present Value of Net Total Benefits by Alternative Combined, (3% Discount Rate)

(Millions of 2009 Dollars)

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY 2021 Passenger Cars & Light Trucks
Preferred Alternative $6,012 $12,506 $22,894 $30,345 $38,682

2% Annual Increase $5,712 $10,899 $18,158 $23,081 $27,847

3% Annual Increase $8,001 $15,328 $24,957 $31,966 $38,445

4% Annual Increase $10,932 $18,824 $28,383 $36,239 $42,453

5% Annual Increase $13,127 $21,186 $31,358 $39,458 $45,787

6% Annual Increase $14,633 $22,779 $33,231 $39,881 $45,196

7% Annual Increase $15,638 $23,540 $34,291 $41,866 $46,790

Max Net Benefits $17,561 $22,117 $29,870 $35,975 $43,514

Total Cost = Total Benefit $19,998 $24,424 $32,102 $38,396 $46,318

Alternative MY
2022 MY
2023 MY
2024 MY
2025 9-Year Total Passenger Cars & Light Trucks
Preferred Alternative $43,933 $49,603 $55,747 $63,820 $323,542

2% Annual Increase $31,101 $34,286 $38,814 $43,693 $233,591

3% Annual Increase $43,282 $47,188 $52,469 $58,637 $320,273

4% Annual Increase $48,062 $52,515 $58,071 $66,098 $361,577

5% Annual Increase $49,842 $52,174 $56,933 $66,394 $376,260

6% Annual Increase $47,638 $51,537 $54,126 $66,736 $375,758

7% Annual Increase $50,852 $52,267 $48,108 $62,355 $375,708

Max Net Benefits $47,203 $51,440 $55,816 $62,954 $366,450

Total Cost = Total Benefit $49,953 $53,041 $57,271 $67,996 $389,500Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 9a Incremental Total Costs by Societal Perspective 13 , by Alternative Passenger Cars, 7% Discount Rate (Millions of 2009 Dollars)

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY 2021 Passenger Cars
Preferred Alternative $2,043 $4,052 $6,609 $9,482 $12,193

2% Annual Increase $814 $1,993 $3,182 $4,261 $5,166

3% Annual Increase $1,396 $3,313 $5,347 $7,542 $9,480

4% Annual Increase $2,544 $5,396 $7,789 $10,756 $13,163

5% Annual Increase $4,100 $7,450 $10,295 $14,241 $17,550

6% Annual Increase $5,907 $9,969 $13,249 $20,732 $23,748

7% Annual Increase $6,637 $11,368 $15,109 $20,921 $24,442

Max Net Benefits $10,606 $11,514 $12,729 $14,021 $15,357

Total Cost = Total Benefit $9,358 $11,671 $13,284 $15,270 $17,920

Alternative MY
2022 MY
2023 MY
2024 MY
2025 9-Year Total Passenger Cars
Preferred Alternative $14,038 $18,392 $21,781 $25,453 $114,044

2% Annual Increase $5,938 $6,785 $8,128 $9,416 $45,683

3% Annual Increase $10,834 $12,352 $14,502 $17,327 $82,093

4% Annual Increase $15,095 $18,322 $24,471 $26,085 $123,621

5% Annual Increase $23,087 $30,209 $35,224 $39,356 $181,511

6% Annual Increase $30,730 $34,966 $46,071 $48,877 $234,247

7% Annual Increase $27,513 $35,636 $60,459 $62,017 $264,102

Max Net Benefits $15,857 $16,829 $18,078 $18,655 $133,645

Total Cost = Total Benefit $20,297 $27,815 $33,101 $33,430 $182,146

13 “Societal perspective” includes technology costs and so cietal costs, but does not include civil penalties.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 9b Incremental Total Costs by Societal Perspective, by Alternative Light Trucks, 7% Discount Rate (Millions of 2009 Dollars)

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY 2021 Light Trucks
Preferred Alternative $428 $1,237 $2,601 $3,858 $5,547

2% Annual Increase $878 $1,471 $2,243 $2,799 $3,259

3% Annual Increase $1,405 $2,337 $3,622 $4,867 $6,261

4% Annual Increase $2,268 $3,450 $5,364 $7,647 $9,920

5% Annual Increase $3,035 $4,850 $7,186 $10,163 $12,906

6% Annual Increase $4,429 $6,854 $9,601 $12,472 $14,754

7% Annual Increase $5,560 $7,786 $10,406 $14,334 $16,130

Max Net Benefits $6,089 $7,298 $8,569 $9,928 $11,348

Total Cost = Total Benefit $7,911 $9,054 $10,375 $13,199 $15,485

Alternative MY
2022 MY
2023 MY
2024 MY
2025 9-Year Total Light Trucks
Preferred Alternative $6,231 $7,188 $7,981 $8,385 $43,456

2% Annual Increase $3,515 $3,771 $4,274 $4,762 $26,973

3% Annual Increase $6,913 $7,343 $8,012 $8,710 $49,470

4% Annual Increase $11,261 $12,484 $13,555 $14,192 $80,140

5% Annual Increase $14,465 $15,627 $19,188 $20,210 $107,629

6% Annual Increase $16,256 $17,325 $20,629 $21,818 $124,139

7% Annual Increase $19,117 $21,380 $25,334 $24,686 $144,733

Max Net Benefits $11,610 $12,429 $13,093 $12,752 $93,117

Total Cost = Total Benefit $16,159 $18,573 $20,462 $21,422 $132,640Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 9c Incremental Total Costs by Societal Perspective, by Alternative Combined, 7% Discount Rate

(Millions of 2009 Dollars)

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY 2021 Passenger Cars & Light Trucks
Preferred Alternative $2,471 $5,289 $9,211 $13,340 $17,740

2% Annual Increase $1,692 $3,465 $5,426 $7,060 $8,424

3% Annual Increase $2,801 $5,649 $8,968 $12,409 $15,741

4% Annual Increase $4,812 $8,846 $13,153 $18,403 $23,083

5% Annual Increase $7,135 $12,299 $17,480 $24,404 $30,456

6% Annual Increase $10,336 $16,823 $22,850 $33,204 $38,502

7% Annual Increase $12,197 $19,154 $25,515 $35,255 $40,572

Max Net Benefits $16,695 $18,812 $21,298 $23,949 $26,706

Total Cost = Total Benefit $17,269 $20,725 $23,659 $28,469 $33,405

Alternative MY
2022 MY
2023 MY
2024 MY
2025 9-Year Total Passenger Cars & Light Trucks
Preferred Alternative $20,269 $25,580 $29,762 $33,838 $157,500

2% Annual Increase $9,453 $10,556 $12,402 $14,178 $72,655

3% Annual Increase $17,748 $19,695 $22,514 $26,037 $131,562

4% Annual Increase $26,356 $30,805 $38,026 $40,277 $203,761

5% Annual Increase $37,552 $45,836 $54,412 $59,566 $289,140

6% Annual Increase $46,986 $52,291 $66,700 $70,695 $358,386

7% Annual Increase $46,630 $57,015 $85,793 $86,703 $408,834

Max Net Benefits $27,467 $29,258 $31,171 $31,407 $226,762

Total Cost = Total Benefit $36,456 $46,388 $53,563 $54,851 $314,786Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 10a Present Value of Lifetime Societal Benefits 14 , by Alternative Passenger Cars, (7% Discount Rate) (Millions of 2009 Dollars)

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY 2021 Passenger Cars
Preferred Alternative $5,471 $10,012 $16,110 $21,767 $26,748
2% Annual Increase $2,962 $6,200 $9,752 $12,855 $15,432
3% Annual Increase $4,488 $9,239 $14,382 $19,231 $22,944
4% Annual Increase $6,462 $12,128 $17,779 $23,741 $28,053
5% Annual Increase $8,943 $15,027 $21,339 $28,088 $32,951
6% Annual Increase $11,189 $17,832 $24,563 $33,195 $37,572
7% Annual Increase $12,338 $19,416 $26,515 $34,383 $38,880
Max Net Benefits $15,644 $17,978 $21,959 $25,539 $29,034
Total Cost = Total Benefit $16,523 $20,087 $24,064 $28,269 $33,656

Alternative MY
2022 MY
2023 MY
2024 MY
2025 9-Year Total Passenger Cars
Preferred Alternative $30,851 $37,012 $43,039 $51,015 $242,027

2% Annual Increase $17,743 $20,080 $23,583 $27,091 $135,697

3% Annual Increase $26,403 $29,850 $34,536 $40,236 $201,310

4% Annual Increase $32,137 $36,861 $45,053 $50,724 $252,938

5% Annual Increase $39,172 $45,530 $52,248 $60,841 $304,140

6% Annual Increase $43,810 $49,180 $59,141 $69,096 $345,579

7% Annual Increase $43,045 $49,881 $65,736 $75,275 $365,470

Max Net Benefits $31,048 $33,891 $37,122 $40,423 $252,638

Total Cost = Total Benefit $37,457 $44,979 $51,424 $57,104 $313,562

14 These benefits are considered from a “societal persp ective” because they include externalities. They are distinguished from a consumer perspective, because cons umers generally would not think about the value of carbon dioxide, energy security, etc.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 10b Present Value of Lifetime Societal Benefits, by Alternative Light Trucks, (7% Discount Rate) (Millions of 2009 Dollars)

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY 2021 Light Trucks
Preferred Alternative $1,508 $4,602 $10,227 $14,100 $19,554
2% Annual Increase $3,086 $5,548 $9,542 $11,828 $14,305
3% Annual Increase $4,344 $7,934 $13,386 $17,134 $21,459
4% Annual Increase $6,406 $10,506 $16,212 $21,018 $25,624
5% Annual Increase $7,629 $12,357 $18,622 $24,201 $29,481
6% Annual Increase $9,218 $14,521 $21,272 $26,669 $31,037
7% Annual Increase $10,424 $15,499 $22,411 $28,784 $32,728
Max Net Benefits $11,276 $14,961 $19,855 $23,304 $27,198
Total Cost = Total Benefit $14,006 $16,716 $21,462 $26,358 $31,638

Alternative MY
2022 MY
2023 MY
2024 MY
2025 9-Year Total Light Trucks
Preferred Alternative $21,890 $24,784 $27,308 $29,457 $153,429

2% Annual Increase $15,550 $16,770 $18,541 $20,557 $115,728

3% Annual Increase $23,661 $25,071 $27,096 $29,424 $169,509

4% Annual Increase $28,883 $31,489 $33,920 $36,791 $210,848

5% Annual Increase $32,549 $35,046 $39,347 $42,955 $242,187

6% Annual Increase $33,932 $36,191 $40,408 $44,376 $257,624

7% Annual Increase $36,958 $39,962 $44,842 $48,079 $279,688

Max Net Benefits $28,739 $30,950 $32,504 $33,776 $222,563

Total Cost = Total Benefit $33,439 $37,036 $39,941 $43,961 $264,558Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 10c Present Value of Lifetime Societal Benefits, by Alternative Combined, (7% Discount Rate)

(Millions of 2009 Dollars)

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY 2021 Passenger Cars & Light Trucks
Preferred Alternative $6,980 $14,614 $26,337 $35,866 $46,302
2% Annual Increase $6,048 $11,748 $19,294 $24,683 $29,737
3% Annual Increase $8,832 $17,172 $27,768 $36,365 $44,403
4% Annual Increase $12,868 $22,633 $33,992 $44,758 $53,677
5% Annual Increase $16,572 $27,384 $39,962 $52,290 $62,432
6% Annual Increase $20,407 $32,354 $45,836 $59,864 $68,609
7% Annual Increase $22,763 $34,915 $48,926 $63,167 $71,609
Max Net Benefits $26,920 $32,939 $41,814 $48,843 $56,232
Total Cost = Total Benefit $30,529 $36,803 $45,526 $54,627 $65,294

Alternative MY
2022 MY
2023 MY
2024 MY
2025 9-Year Total Passenger Cars & Light Trucks
Preferred Alternative $52,741 $61,797 $70,346 $80,472 $395,455

2% Annual Increase $33,293 $36,850 $42,123 $47,648 $251,425

3% Annual Increase $50,063 $54,921 $61,633 $69,660 $370,819

4% Annual Increase $61,020 $68,350 $78,972 $87,515 $463,786

5% Annual Increase $71,721 $80,576 $91,595 $103,796 $546,327

6% Annual Increase $77,742 $85,371 $99,549 $113,472 $603,203

7% Annual Increase $80,003 $89,843 $110,578 $123,354 $645,158

Max Net Benefits $59,787 $64,841 $69,626 $74,199 $475,201

Total Cost = Total Benefit $70,896 $82,016 $91,365 $101,064 $578,120Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 11a Present Value of Net Total Benefits 15 by Alternative Passenger Cars, (7% Discount Rate) (Millions of 2009 Dollars)

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY 2021 Passenger Cars
Preferred Alternative $3,428 $5,960 $9,501 $12,285 $14,555

2% Annual Increase $2,148 $4,207 $6,569 $8,594 $10,266

3% Annual Increase $3,091 $5,926 $9,036 $11,689 $13,464

4% Annual Increase $3,918 $6,732 $9,990 $12,985 $14,890

5% Annual Increase $4,843 $7,577 $11,045 $13,847 $15,401

6% Annual Increase $5,282 $7,863 $11,315 $12,463 $13,824

7% Annual Increase $5,701 $8,047 $11,406 $13,462 $14,438

Max Net Benefits $5,038 $6,464 $9,230 $11,518 $13,677

Total Cost = Total Benefit $7,165 $8,416 $10,780 $12,999 $15,736

Alternative MY
2022 MY
2023 MY
2024 MY
2025 9-Year Total Passenger Cars
Preferred Alternative $16,814 $18,620 $21,258 $25,562 $127,983

2% Annual Increase $11,805 $13,295 $15,455 $17,676 $90,014

3% Annual Increase $15,569 $17,499 $20,034 $22,909 $119,217

4% Annual Increase $17,042 $18,540 $20,582 $24,639 $129,317

5% Annual Increase $16,085 $15,322 $17,024 $21,485 $122,629

6% Annual Increase $13,080 $14,215 $13,070 $20,220 $111,332

7% Annual Increase $15,532 $14,246 $5,278 $13,258 $101,368

Max Net Benefits $15,191 $17,062 $19,044 $21,769 $118,993

Total Cost = Total Benefit $17,160 $17,164 $18,323 $23,674 $131,416

15 This table is from a societal perspective, thus, civil pe nalties are deleted from the cost s because they are a transfer payment.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 11b Present Value of Net Total Benefits by Alternative Light Trucks, (7% Discount Rate) (Millions of 2009 Dollars)

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY 2021 Light Trucks
Preferred Alternative $1,080 $3,365 $7,625 $10,241 $14,007

2% Annual Increase $2,208 $4,077 $7,299 $9,029 $11,047

3% Annual Increase $2,939 $5,597 $9,765 $12,267 $15,198

4% Annual Increase $4,138 $7,056 $10,848 $13,371 $15,704

5% Annual Increase $4,594 $7,508 $11,437 $14,039 $16,575

6% Annual Increase $4,788 $7,667 $11,671 $14,197 $16,283

7% Annual Increase $4,864 $7,713 $12,005 $14,450 $16,598

Max Net Benefits $5,187 $7,663 $11,286 $13,376 $15,850

Total Cost = Total Benefit $6,095 $7,662 $11,087 $13,159 $16,153

Alternative MY
2022 MY
2023 MY
2024 MY
2025 9-Year Total Light Trucks
Preferred Alternative $15,658 $17,596 $19,326 $21,072 $109,972

2% Annual Increase $12,035 $12,999 $14,267 $15,795 $88,756

3% Annual Increase $16,747 $17,728 $19,084 $20,714 $120,039

4% Annual Increase $17,623 $19,005 $20,365 $22,598 $130,708

5% Annual Increase $18,083 $19,419 $20,159 $22,745 $134,558

6% Annual Increase $17,675 $18,865 $19,779 $22,558 $133,485

7% Annual Increase $17,841 $18,582 $19,508 $23,393 $134,955

Max Net Benefits $17,129 $18,520 $19,412 $21,024 $129,446

Total Cost = Total Benefit $17,280 $18,463 $19,479 $22,539 $131,918Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 11c Present Value of Net Total Benefits by Alternative Combined, (7% Discount Rate)

(Millions of 2009 Dollars)

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY 2021 Passenger Cars & Light Trucks
Preferred Alternative $4,509 $9,325 $17,126 $22,526 $28,563

2% Annual Increase $4,356 $8,284 $13,869 $17,623 $21,313

3% Annual Increase $6,031 $11,523 $18,800 $23,956 $28,662

4% Annual Increase $8,056 $13,788 $20,838 $26,356 $30,594

5% Annual Increase $9,437 $15,084 $22,481 $27,886 $31,976

6% Annual Increase $10,071 $15,531 $22,986 $26,661 $30,107

7% Annual Increase $10,565 $15,760 $23,411 $27,912 $31,036

Max Net Benefits $10,225 $14,128 $20,516 $24,894 $29,527

Total Cost = Total Benefit $13,260 $16,077 $21,867 $26,158 $31,889

Alternative MY
2022 MY
2023 MY
2024 MY
2025 9-Year Total Passenger Cars & Light Trucks
Preferred Alternative $32,472 $36,217 $40,584 $46,634 $237,955

2% Annual Increase $23,841 $26,294 $29,722 $33,470 $178,770

3% Annual Increase $32,316 $35,226 $39,118 $43,623 $239,256

4% Annual Increase $34,664 $37,544 $40,947 $47,238 $260,025

5% Annual Increase $34,169 $34,740 $37,182 $44,230 $257,187

6% Annual Increase $30,756 $33,080 $32,849 $42,777 $244,816

7% Annual Increase $33,373 $32,828 $24,785 $36,651 $236,323

Max Net Benefits $32,320 $35,582 $38,455 $42,792 $248,439

Total Cost = Total Benefit $34,440 $35,627 $37,802 $46,213 $263,334Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 12a Millions of Gallons of Fuel Saved 16 Passenger Cars Undiscounted Over the Lifetime of the Model Year

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY 2021 Passenger Cars
Preferred Alternative 2,103 3,807 6,057 8,113 9,999
2% Annual Increase 1,140 2,364 3,683 4,806 5,701
3% Annual Increase 1,723 3,509 5,391 7,151 8,551

4% Annual Increase 2,483 4,628 6,703 8,914 10,531

5% Annual Increase 3,432 5,743 8,057 10,649 12,600
6% Annual Increase 4,389 6,997 9,478 12,944 14,486
7% Annual Increase 4,750 7,539 10,161 13,351 14,952 Max Net Benefits (3% Discount Rate) 6,109 7,069 8,343 9,611 10,985 Max Net Benefits (7% Discount Rate) 6,096 7,014 8,435 9,689 10,884 Total Cost = Total Benefit (3% Discount Rate) 6,486 7,755 9,172 10,739 12,672

Total Cost = Total Benefit (7% Discount Rate) 6,486 7,820 9,234 10,793 12,724

Alternative MY
2022 MY
2023 MY
2024 MY
2025 9-Year Total Passenger Cars
Preferred Alternative 11,429 13,803 15,942 19,010 90,262
2% Annual Increase 6,499 7,293 8,478 9,716 49,680
3% Annual Increase 9,744 10,916 12,585 14,748 74,319

4% Annual Increase 11,948 13,717 16,718 18,867 94,508

5% Annual Increase 14,964 17,462 19,880 23,269 116,056

6% Annual Increase 16,898 18,940 22,687 26,504 133,323
7% Annual Increase 16,447 19,123 25,360 28,965 140,647 Max Net Benefits (3% Discount Rate) 11,649 12,517 13,716 14,952 94,952 Max Net Benefits (7% Discount Rate) 11,527 12,458 13,523 14,720 94,346 Total Cost = Total Benefit (3% Discount Rate) 14,008 16,954 19,350 21,548 118,686

Total Cost = Total Benefit (7% Discount Rate) 14,063 17,022 19,335 21,532 119,008

16 The choice of a 3 or 7 percent discount rate can impact the results of the Max Net Benefits and Total Cost = Total Benefits scenarios. The results of all other scenarios are not impacted by choice of discount rate. Results for both 3 and 7 percent discount rates are therefore presented for both Max Net Benefits and Total Cost = Total Benefit scenarios.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 12b Millions of Gallons of Fuel Saved Light Trucks Undiscounted Over the Lifetime of the Model Year

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY 2021 Light Trucks
Preferred Alternative 604 1,828 4,074 5,504 7,591

2% Annual Increase 1,250 2,229 3,804 4,669 5,579

3% Annual Increase 1,760 3,164 5,326 6,703 8,330
4% Annual Increase 2,590 4,236 6,493 8,265 10,094
5% Annual Increase 3,088 5,054 7,520 9,607 11,682
6% Annual Increase 3,753 5,977 8,651 10,675 12,439
7% Annual Increase 4,257 6,367 9,083 11,511 13,085 Max Net Benefits (3% Discount Rate) 5,621 6,824 8,702 10,457 12,505 Max Net Benefits (7% Discount Rate) 4,580 6,042 7,948 9,279 10,696 Total Cost = Total Benefit (3% Discount Rate) 5,632 6,984 8,837 10,710 12,685

Total Cost = Total Benefit (7% Discount Rate) 5,669 6,886 8,763 10,630 12,695

Alternative MY
2022 MY
2023 MY
2024 MY
2025 9-Year Total Light Trucks
Preferred Alternative 8,409 9,440 10,311 11,030 58,791
2% Annual Increase 5,990 6,399 7,048 7,728 44,697

3% Annual Increase 9,096 9,570 10,248 11,085 65,282

4% Annual Increase 11,277 12,271 13,082 14,089 82,398
5% Annual Increase 12,768 13,664 15,262 16,548 95,193
6% Annual Increase 13,493 14,274 15,758 17,187 102,207

7% Annual Increase 14,648 15,727 17,488 18,677 110,842 Max Net Benefits (3% Discount Rate) 13,231 14,052 14,962 16,508 102,862 Max Net Benefits (7% Discount Rate) 11,178 11,956 12,445 12,814 86,937 Total Cost = Total Benefit (3% Discount Rate) 13,310 14,520 15,762 17,245 105,685

Total Cost = Total Benefit (7% Discount Rate) 13,348 14,649 15,605 17,035 105,280Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 12c Millions of Gallons of Fuel Saved Combined Undiscounted Over the Lifetime of the Model Year

Alternative MY
2017 MY
2018 MY
2019 MY
2020 MY 2021 Passenger Cars & Light Trucks
Preferred Alternative 2,707 5,635 10,131 13,616 17,590

2% Annual Increase 2,390 4,594 7,487 9,475 11,280
3% Annual Increase 3,484 6,673 10,718 13,855 16,881
4% Annual Increase 5,073 8,864 13,196 17,178 20,625
5% Annual Increase 6,521 10,797 15,577 20,256 24,282
6% Annual Increase 8,142 12,975 18,130 23,620 26,925

7% Annual Increase 9,006 13,906 19,245 24,862 28,036 Max Net Benefits (3% Discount Rate) 11,730 13,893 17,045 20,069 23,490 Max Net Benefits (7% Discount Rate) 10,677 13,056 16,382 18,968 21,581 Total Cost = Total Benefit (3% Discount Rate) 12,119 14,739 18,009 21,450 25,357

Total Cost = Total Benefit (7% Discount Rate) 12,155 14,706 17,997 21,423 25,419

Alternative MY
2022 MY
2023 MY
2024 MY
2025 9-Year Total Passenger Cars & Light Trucks
Preferred Alternative 19,837 23,244 26,253 30,040 149,054
2% Annual Increase 12,489 13,692 15,526 17,444 94,377

3% Annual Increase 18,841 20,485 22,833 25,833 139,601
4% Annual Increase 23,225 25,988 29,800 32,956 176,906
5% Annual Increase 27,732 31,126 35,142 39,817 211,250

6% Annual Increase 30,391 33,214 38,445 43,690 235,531
7% Annual Increase 31,095 34,850 42,848 47,641 251,490 Max Net Benefits (3% Discount Rate) 24,880 26,569 28,678 31,460 197,814 Max Net Benefits (7% Discount Rate) 22,705 24,414 25,967 27,533 181,283 Total Cost = Total Benefit (3% Discount Rate) 27,318 31,474 35,113 38,793 224,371

Total Cost = Total Benefit (7% Discount Rate) 27,411 31,671 34,940 38,567 224,289Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Breakdown of costs and benefits for the preferred alternative

Tables 13 and 14 provide a breakdown of the costs and benefits for the preferred alternative using a 3 percent and 7 percent discount rate, respectively.

Table 13 Preferred Alternative Cost and Benefit Estimates, 3% Discount Rate

Passenger Cars and Light Trucks Combined (Millions of 2009 Dollars)

MY
2017 MY
2018 MY
2019 MY 2020 MY 2021 Technology Costs ($2,036) ($4,435) ($7,661) ($11,281) ($15,219)

Social Costs and Benefits

Lifetime Fuel Expenditures (Pretax) $6,842 $14,356 $26,019 $35,257 $45,709

Consumer Surplus from Additional Driving $41 $116 $258 $394 $538

Refueling Time Value $353 $674 $1,132 $1,542 $1,756

Petroleum Market Externalities $367 $762 $1,369 $1,839 $2,375 Congestion Costs ($356) ($689) ($1,215) ($1,649) ($2,034)
Accident Costs ($163) ($322) ($572) ($783) ($974)

Noise Costs ($7) ($13) ($23) ($31) ($39) Fatality Costs $13 $34 ($97) $37 $19

CO2 $712 $1,510 $2,765 $3,791 $4,938

CO $0 $0 $0 $0 $0

VOC $9 $18 $34 $46 $67

NOX $19 $40 $67 $90 $84

PM $113 $237 $431 $576 $797

SOX $104 $216 $388 $517 $665
Net Social Benefits $8,048 $16,941 $30,556 $41,626 $53,901

Net Total Benefits $6,012 $12,506 $22,894 $30,345 $38,682Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 13 (Continued)

MY 2022 MY 2023 MY 2024 MY 2025 9-Year Total Technology Costs ($17,444) ($22,194) ($25,994) ($29,354) ($135,618)

Social Costs and Benefits

Lifetime Fuel Expenditures (Pretax) $51,976 $60,860 $69,202 $79,053 $389,274 Consumer Surplus from Additional Driving $643 $1,035 $1,256 $1,818 $6,100

Refueling Time Value $1,956 $2,110 $2,323 $2,458 $14,305

Petroleum Market Externalities $2,680 $3,135 $3,544 $4,058 $20,129 Congestion Costs ($2,296) ($2,761) ($3,102) ($3,707) ($17,809)
Accident Costs ($1,097) ($1,331) ($1,494) ($1,764) ($8,500)

Noise Costs ($44) ($53) ($59) ($70) ($338) Fatality Costs $54 $32 $28 $26 $146

CO2 $5,676 $6,699 $7,696 $8,850 $42,638

CO $0 $0 $0 $0 $0

VOC $76 $95 $110 $132 $588

NOX $90 $120 $126 $150 $787

PM $910 $1,096 $1,258 $1,396 $6,814

SOX $752 $759 $853 $773 $5,027
Net Social Benefits $61,377 $71,797 $81,741 $93,174 $459,160

Net Total Benefits $43,933 $49,603 $55,747 $63,820 $323,542Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 14 Preferred Alternative Cost and Benefit Estimates, 7% Discount Rate

Passenger Cars and Light Trucks Combined (Millions of 2009 Dollars)

MY
2017 MY
2018 MY
2019 MY 2020 MY 2021 Technology Costs ($2,036) ($4,435) ($7,661) ($11,281) ($15,219)

Social Costs and Benefits

Lifetime Fuel Expenditures (Pretax) $5,433 $11,381 $20,622 $27,943 $36,238

Consumer Surplus from Additional Driving $33 $93 $205 $313 $428

Refueling Time Value $283 $540 $907 $1,234 $1,403

Petroleum Market Externalities $294 $609 $1,094 $1,469 $1,897

Congestion Costs ($286) ($552) ($974) ($1,320) ($1,629)
Accident Costs ($131) ($257) ($458) ($626) ($778)

Noise Costs ($5) ($10) ($18) ($25) ($31) Fatality Costs $13 $34 ($97) $37 $19

CO2 $712 $1,510 $2,765 $3,791 $4,938

CO $0 $0 $0 $0 $0

VOC $7 $15 $28 $37 $54

NOX $16 $33 $56 $74 $71

PM $92 $192 $349 $466 $642

SOX $83 $173 $310 $413 $531
Net Social Benefits $6,545 $13,759 $24,787 $33,807 $43,782

Net Total Benefits $4,509 $9,325 $17,126 $22,526 $28,563Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table 14 (Continued)

MY 2022 MY 2023 MY 2024 MY 2025 9-Year Total Technology Costs ($17,444) ($22,194) ($25,994) ($29,354) ($135,618)

Social Costs and Benefits

Lifetime Fuel Expenditures (Pretax) $41,250 $48,326 $55,013 $62,934 $309,140 Consumer Surplus from Additional Driving $512 $820 $997 $1,449 $4,848

Refueling Time Value $1,563 $1,686 $1,856 $1,964 $11,436

Petroleum Market Externalities $2,141 $2,504 $2,833 $3,248 $16,089 Congestion Costs ($1,839) ($2,208) ($2,481) ($2,969) ($14,257)
Accident Costs ($877) ($1,062) ($1,193) ($1,410) ($6,793)

Noise Costs ($35) ($42) ($47) ($56) ($270) Fatality Costs $54 $32 $28 $26 $146

CO2 $5,676 $6,699 $7,696 $8,850 $42,638

CO $0 $0 $0 $0 $0

VOC $61 $76 $88 $105 $470

NOX $76 $98 $103 $122 $649

PM $732 $874 $1,002 $1,108 $5,457

SOX $601 $607 $683 $617 $4,018
Net Social Benefits $49,916 $58,410 $66,578 $75,988 $373,573

Net Total Benefits $32,472 $36,217 $40,584 $46,634 $237,955Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.



### I. INTRODUCTION

The purpose of this study is to analyze the effects of the proposal that would extend the National Program of Federal and corporate average fuel economy (CAFE) standards and greenhouse gas (GHG) emissions standards to model years (MYs) 2017-2025 for passenger cars and light trucks. Under this joint rulemaking, NHTSA is proposing CAFE standards under Energy Policy Conservation Act of 1975, as amended by the Energy Independence and Security Act of 2007 (EISA), and EPA is proposing GHG emissions standards under the Clean Air Act (CAA). This study includes a discussion of the technologies that can improve fuel economy, the potential impacts on retail prices, safety, the discounted lifetime net benefits of fuel savings, and the potential gallons of fuel saved, among other things.

In working together to develop the next round of standards for MYs 2017-2025, NHTSA and EPA are building on the success of the first phase of the National Program to regulate fuel economy and GHG emissions from U.S. light-duty vehicles, which established the coordinated standards for model years (MY) 2012-2016. 17 Continuing the National Program would ensure that all manufacturers can build a single fleet of U.S. vehicles that would satisfy all requirements under both programs as well as under California’s program, helping to reduce costs and regulatory complexity while providing significant energy security and environmental benefits. President Obama announced plans for these proposed rules on July 29, 2011 and NHTSA and EPA issued a Supplemental Notice of Intent (N OI) outlining the agencies’ plans for proposing the MY 2017-2025 standards and program. 18 The State of California and thirteen auto manufacturers representing over 90 percent of U.S. vehicle sales provided letters of support for the program concurrent with the Supplemental NOI. 19 The United Auto Workers (UAW) also supported the announcement. 20 As envisioned in the Presidential announcement and Supplemental NOI, the proposal sets forth proposed MYs 2017-2025 standards as well as detailed supporting analysis for those standards an d regulatory alternatives for public review and

comment.

One aspect of this phase of the National Program that is unique for NHTSA, however, is that the passenger car and light truck CAFE standards for MYs 2022-2025 must be conditional, while EPA’s (and also California’s) standards for t hose model years will be legally binding when adopted in this round. EISA requires NHTSA to issue CAFE standards for “at least 1, but not more than 5, model years.” 21 To maintain the harmonization benefits of the National Program, NHTSA will therefore propose and adopt standard s for all 9 model years from 2017-2025, but the last 4 years of standards will be conditiona l. The passenger car and light truck CAFE standards for MYs 2022-2025 will be determined with finality in a subsequent, de novo notice and comment rulemaking conducted in full comp liance with EPCA/EISA and other applicable

17 Final Rule published in the Federal Register on May 7, 2010 (75FR 25324).

18 76 FR 48758 (August 9, 2011).

19 Commitment letters are available at http://www.epa.gov/otaq/climate/regulations.htm and at http://www.nhtsa.gov/fuel-economy (last accessed Aug. 24, 2011).

20 The UAW’s support was expressed in a statement on July 29, 2011, which can be found at http://www.uaw.org/articles/ua w-supports-administration- proposal-light-duty-vehicl e-cafe-and-greenhouse-gasemissions-r (last accessed September 19, 2011)

21 49 U.S.C. 32902(b)(3)(B).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

law – beyond simply reviewing the analysis and findings in the present rulemaking to see whether they are still accurate and applicable, and taking a fresh look at all relevant factors based on the best and most current information available at that future time.

To facilitate that future rulemaking, NHTSA and EPA will conduct a comprehensive mid-term evaluation. Up to date information will be de veloped and compiled for the evaluation, through a collaborative, robust, and transparent process, in cluding notice and comment. The agencies fully expect to conduct the mid-term evaluation in close coordination with the California Air Resources Board (CARB), consistent with the agencies’ commitment to maintaining a single national framework for regulation of fuel economy and GHG emissions. 22

The majority of the analysis contained in th is document reflects the impacts that NHTSA believes would result from manufacturers increa sing the fuel economy of their vehicles in order to meet the stringency levels required under the different regulatory alternatives. In assessing these impacts, NHTSA assumes

1) That some manufacturers will continue, as th ey have done historically, not to meet the standards and instead pay civil penaltie s for non-compliance, as permitted by EPCA;

2) That manufacturers do not use dedicated alternative fuel vehicles, dual-fueled alternative fuel vehicles (through MY 2020), or credits earned for over-compliance to meet the required mpg levels, as directed by 49 U.S.C. 32902(h);

3) That manufacturers do use A/C efficiency improvements and off-cycle technology improvements to meet the standards.

These assumptions make up the “estimated required” analysis. NHTSA analyzes the impacts of manufacturers’ use of statutory fl exibilities and other regulatory b onuses and adjustments to fuel economy as part of its “estimated achieved” analysis, which is presented in Chapter XI.

Throughout this document, confidential information is presented in brackets [ ].

22 The agencies also fully expect that any adjustments to the standards as a result of the mid-term evaluation process from the levels enumerated in the current rulemaking will be made with the participation of CARB and in a manner that continues the harmonization of st ate and Federal vehicle standards.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.



### II. NEED OF THE NATION TO CONSERVE ENERGY

The Energy Policy and Conservation Act (EPCA) states that:

“When deciding maximum feasible average fuel economy ... the Secretary of Transportation shall consider technological feasibility, economic practicability, the effect of other motor vehicle standards of the Government on fuel economy, and the need of the United States to conserve energy.” 23

Thus, EPCA specifically directs the Department to balance the technological and economic challenges related to fuel economy with the Nation’s need to conserve energy. The concerns about energy security and the effects of energy prices and supply on National economic well-being that led to the enactment of EPCA persist today. The demand for petroleum grew in the U.S. up through the year 2005, peaking at 20.8 million barrels per day, and has since declined to an average of 18.8 million barrels per day in 2009. 24 World demand, however, is expected to continue to rise until 2035. 25

Since 1970, there have been a series of events that suggest that the behavior of petroleum markets is a matter for public concern.

 Average annual crude oil prices rose from $68 per barrel in 2007 to $95 per barrel in 2008, having peaked at $129 per barrel in July 2008. Prices declined to $37 per barrel in January 2009, but then rose to $113 per barrel in April 2011. 26 As recently as 1998, crude prices averaged about $13 per barrel. 27 Gasoline prices more than tripled during this ten-year period, from an annual average of $1.07 in 1998 to $3.30 in 2008. As the price of oil bounces up and down, the price of gasoline also rises and falls, hitting an average of $3.71 in July of 2011. 28

 U.S. domestic petroleum production stood at 10 million barrels per day in 1975, rose slightly to 10.6 million barrels per day in 1985, and by 2009 had declined to 7.3 million barrels per day. 29 Domestic production is predicted to increase through 2035.

 Between 1975 and 2005, U.S. petroleum consum ption increased from 16.3 million barrels per day to 20.8 million barrels per day. 30 In 2009, vehicle miles traveled and consumption fell compared to the 2005 levels.

23 49 U.S.C. § 32902(f)

24 U.S. Department of Energy, Energy Information Administration, International Energy Statistics, Total Petroleum Consumption. See http://www.eia.gov/cfapps/ipdbproject/IEDIndex3.cfm?tid=5&pid=5&aid=2 (last accessed, August 30, 2011).

25 U.S Department of Energy, Energy Information Administration, International Energy Outlook 2010

. See http://www.eia.gov/oiaf/ieo/highlights.html (last accessed August 30, 2011).

26 U.S. Department of Energy, Energy Information Administration, Short-Term Energy Outlook , U.S. Refiner Average Acquisition Cost per Barrel of Crude Oil. See http://www.eia.gov/emeu/st eo/pub/cf_query/index.cfm (last accessed August 30, 2011).

27 Ibid.

28 U.S. Department of Energy, Energy Information Administration, Weekly Retail and Gasoline Diesel Prices

. See http://www.eia.gov/dnav/pet/pet_pri_gnd_dcus_nus_m.htm (last accessed, August 30, 2011).

29 U.S. Department of Energy, Energy Information Administration, Monthly Energy Review, July 2011

. See http://www.eia.gov/totalenergy/data/monthly/pdf/sec3_3.pdf (last accessed August 30, 2011).

30 U.S. Department of Energy, Energy Information Administration, Monthly Energy Review, July 2011

. See http://www.eia.gov/totalenergy/data/monthly/pdf/sec3_7.pdf (last accessed August 30, 2011).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

 Net petroleum imports accounted for 51.5 percent of U.S. domestic petroleum consumption in 2009. 31 Worldwide oil demand is fairly inelastic: declining prices do not induce large increases in consumption, while higher prices do not significantly restrain consumption. For example, the price of unleaded regular gasoline rose from an average of $2.57 in 2006 to $3.25 in 2008 (a 26.5 percent increase) 32 and vehicle miles traveled decreased by 1.3 percent. 33 Within the United States, demand for gasoline, diesel, and jet fuel within the transportation sector is particularly inelastic.

 Demand for oil is projected to increase significantly worldwide in the next several decades, resulting in upward oil cost pressure. Between 2007 and 2035, total world petroleum consumption is expected to grow from 86.1 to 110.6 million barrels per day. 34

 Foreign oil production facilities, refineries, and supply chains have been disrupted from time to time, either by wars, political action by oil producers, civil unrest, or natural disasters.

 High oil prices, sometimes induced by disruptions in oil markets, have often coincided with rising inflation and subsequent economic recessions.

 Greenhouse gas emissions from the consumption of petroleum have become a subject of increasing public policy concern, both in the United States and internationally. Greenhouse gases in general and carbon dioxide in particular have not thus far been subject to National regulation. Studies by multiple sources suggest that rising atmospheric concentrations of greenhouse gases will damage human health and welfare. 35 There is a direct linkage between the consumption of fossil energy and emission s of the greenhouse gas carbon dioxide, as essentially all of the carbon in hydrocarbon fuels is oxidized into carbon dioxide when the fuel is combusted. Reducing U.S. fossil petroleum consumption will generally induce a proportional reduction in carbon dioxide emissions.

Energy is an essential input to the U.S. economy, and having a strong economy is essential to maintaining and strengthening our National security. Secure, reliable, and affordable energy sources are fundamental to economic stability and developm ent. Rising energy demand poses a challenge to energy security, given increased reliance on global energy markets. As noted above, approximately half of the petroleum consumed in the U.S. is imported.

Conserving energy, especially reducing the Nation’s dependence on petroleum, benefits the U.S. in several ways. Improving energy efficiency has benefits for economic growth and the environment, as well as other benefits, such as reducing pollution and improving security of energy supply. More specifically, reducing total petroleum use decreases our economy’s vulnerability to oil price shocks.

31 Ibid.

32 U.S. Department of Energy, Energy Information Administration, Weekly Retail and Gasoline Diesel Prices

. See http://www.eia.gov/dnav/pet/pet_pri_gnd_dcus_nus_m.htm (last accessed, August 30, 2011).

33 U.S. Department of Transportation, Federal Highway Administration, Office of Highway Policy Information, Quick Find: Vehicle Miles of Travel , Table VM-2 (2006 and 2008). Available at http://www.fhwa.dot.gov/policyinforma tion/quickfinddata/qftravel.cfm (last accessed August 30, 2011).

34 U.S. Department of Energy, Energy Information Administration, International Energy Outlook 2010 , Table A5 (p. 150). Available at http://www.eia.gov/oiaf/i eo/pdf/0484%282010%29.pdf (last accessed August 30, 2011).

35 IPCC 2007: Climate Change 2007: Synthesis Report: Contributions of Working Groups I, II, and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, [Core writing team, Pachauri, R.K. and Reisinger, A. 9eds.)] (Published by the Intergovernmental Panel on Climate Change, 2008). A vailable at http://www.ipcc.ch/pdf/assessme nt-report/ar4/syr/ar4_syr.pdf (last accessed August 30, 2011).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Reducing dependence on oil imports from regions with uncertain conditions enhances our energy security and can reduce the flow of oil profits to certain states no w hostile to the U.S.

This CAFE Notice of Proposed Rulemaking encourages conservation of petroleum for transportation by the application of broader use of fuel saving technologies, resulting in more fuel-efficient vehicles, i.e. , vehicles requiring less fuel consumption per unit mile.

Table II-1 presents historical trend data and projections of the production and consumption of petroleum. Increases in domestic petroleum production are expected through 2035 as technological advances further the economic recoverability of oil from conventional and unconventional resources. Despite the projected increase in domestic production, by 2035 the U.S. is expected to remain reliant on foreign sources for over 40 percent of its oil needs.

Although not shown in Ta ble II-1, the U.S. petroleum consumpti on is equivalent to U.S. petroleum supply. The Energy Information Administration’s measure of U.S. petroleum supply exceeds the sum of domestic production and net imports because the EIA’s measure of total supply includes renewable fuel and oxygenate plant net production, refinery and blender net production, changes in suppliers’ reserve stocks, and adjustments for crude oil, fuel ethanol, motor gasoline blending components, and distillate fuel oil.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table II-1
Petroleum Production and Supply (Million Barrels per Day)

Domestic
Petroleum Production 36 Net Petroleum Imports 37 U.S.
Petroleum Consumption 38 World Petroleum Consumption 39 Net Imports as a Share of U.S. Consumption 40

1975 10.0 5.8 16.3 56.2 35.8%
1985 10.6 4.3 15.7 60.1 27.3%
1995 8.3 7.9 17.7 70.1 44.5%
2005 6.9 12.5 20.8 84.1 60.3%
2009 7.3 9.7 18.8 84.3 51.5%

DOE Predictions 41,42

2015 8.0 9.8 20.4 88.7 48.1%
2025 8.6 9.1 21.0 97.6 43.2%
2035 8.9 8.9 21.9 110.6 40.5%

36 U.S. Department of Energy, Energy Information Administration, Monthly Energy Review, July 2011

. See http://www.eia.gov/totalenergy/data/monthly/pdf/sec3_3.pdf (last accessed August 30, 2011).

37 Ibid.

38 Ibid.

39 U.S. Department of Energy, Energy Information Administration, International Energy Statistics, Total Petroleum Consumption. See http://www.eia.gov/cfapps/ipdbproject/IEDIndex3.cfm?tid=5&pid=5&aid=2 (last accessed, August 30, 2011).

40 U.S. Department of Energy, Energy Information Administration, Monthly Energy Review, July 2011

. See http://www.eia.gov/totalenergy/data/monthly/pdf/sec3_7.pdf (last accessed July 29, 2011).

41 Source of Predictions of Domestic Petroleum Pr oduction, Net Petroleum Imports, and U.S. Petroleum Consumption: U.S. Department of Energy, Energy Information Administration, Annual Energy Outlook 2011 , Table A11 (p. 137). Available at http://www.eia.gov/forecasts/aeo/pdf/0383%282011%29.pdf (last accessed August 30, 2011).

42 Source of Predictions of World Petroleum Consumption: U.S. Department of Energy, Energy Information Administration, International Energy Outlook 2010 , Table A5 (p. 150). Available at http://www.eia.gov/oiaf/ieo/pdf/0484%282010%29.pdf (last accessed August 30, 2011).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table II-2 shows that light vehicle petroleum consumption made up 74.1 percent of all transportation petroleum consumption in 2009. Therefore, reductions in light vehicle petroleum consumption resulting from increases in CAFE fuel economy standards will substantively support the Nation’s efforts to conserve energy.

Table II-2

Petroleum
Transportation Consumption by Mode (Thousand Barrels per Day) 43

Passenger Cars Light
Trucks Total Light Vehicles Total Transportation Light Vehicles as % of
Trans.
1975 4,836 1,245 6,081 8,472 71.8%
1985 4,665 1,785 6,450 9,536 67.6%

1995 4,440 2,975 7,415 11,346 65.4%
2005 5,050 3,840 8,890 14,020 63.4%
2009 4,662 4,019 8,681 11,708 74.1%

43 U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Transportation Energy Data Book, Table 1.13. Available at http://cta.ornl.gov/ data/chapter1.shtml (last accessed August 30, 2011).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

III. BASELINE AND ALTERNATIVES

A. The Baseline Vehicle Fleet

1. Why establish a baseline vehicle fleet?

In order to calculate the impacts of the final rule , it is necessary to estimate the composition of the future vehicle fleet absent the final CAFE standards in order to conduct comparisons. EPA in consultation with NHTSA developed a comparison fleet in two parts. The first step was to develop a baseline fleet based on model year 2008 data. The baseline 2008-based fleet is created in order to track the volumes and types of fuel economy-improving technologies which are already present in today’s fleet. Creating a baseline 2008-based fleet helps to keep, to some extent, the agencies’ models from adding technologies to vehicles that already have these technologies, which would result in “double counting” of technologies’ costs and benefits. The second step was to project the baseline 2008-based fleet sales into MYs 2017-2025. This is called the reference fleet, and it represents an attempt to predict the fleet that would exist in MYs 2017-2025 absent any change from current regulations without the MYs 2012-2016 rule . The third step was to add technologies to that fleet such that each manufacturer’s average car and truck CO 2 levels are in compliance with their MY 2016 CAFE standards. This final “reference fleet” is the light duty fleet estimated to exist in MYs 2017-2025 without the final CAFE standards proposed in this rule, assuming that manufacturers would not make fuel economy improvements beyond what is required by the MY 2016 standards . All of the agency’s estimates of fuel economy improvements, costs, and societal impacts are developed in relation to the respective reference fleets.

2. How was the baseline 2008-based vehicle fleet developed?

The baseline that EPA developed in consultation with NHTSA for the 2012-2016 final rule was comprised of model year 2008 CAFE compliance data (specifically, individual vehicles with sales volumes disaggregated at the level of specific engine/transmission combinations) submitted by manufacturers to EPA, in part because full MY 2009 data was not available at the time. For this NPRM, the agencies chose again to use MY 2008 vehicle data as the basis of the baseline fleet, but for different reasons than in the 2012-2016 final rule. First, MY 2008 is now the most recent model year for which the industry had what the agencies would consider to be “normal” sales. Complete MY 2009 data is now available for the industry, but the agencies believe that the model year was disrupted by the economic downturn and the bankruptcies of both General Motors and Chrysler. CAFE compliance data show s that there was a significant reduction in the number of vehicles sold by both companies and by the industry as a whole. These abnormalities led the agencies to conclude that MY 2009 data was likely not representative for projecting the future fleet for purposes of this analysis. And second, while MY 2010 data is likely more representative for projecting the fu ture fleet, it was not complete and available in time for it to be used for the NPRM analysis. Therefore, for purposes of the NPRM analysis, the agencies chose to use MY 2008 CAFE compliance data for the baseline since it was the latest, most representative transparent data set that we had available. More details about how the agencies constructed this baseline fleet can be found in Chapter 1.2 of the Joint TSD. However, the agencies plan to use the MY 2010 data, if availa ble, to develop an updated market forecast forSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

use in the final rule. If and when the MY 2010 data becomes available, the agencies will place a copy of this data into each agencies’ docket. Additionally, time and resources permitting, one or both agencies may also docket an impacts analysis following the NPRM, to allow the public to see and comment on the difference in results using baselines developed using the MY 2010 data rather than the MY 2008 data.

3. How was the projected MY 2017-2025 fleet (the reference fleet) developed?

EPA and NHTSA have based the projection of total car and total light truck sales for MYs 2017- 2025 on projections made by the Department of Energy’s Energy Information Administration (EIA). EIA publishes a mid-term projection of national energy use called the Annual Energy Outlook (AEO). This projection utilizes a numbe r of technical and econometric models which are designed to reflect both economic and regulatory conditions expected to exist in the future. In support of its projection of fuel use by light -duty vehicles, EIA projects sales of new cars and light trucks.

EPA and NHTSA have based the projection of total car and light truck sales on the most recent projections available made by the Energy Information Administration (EIA). EIA publishes a projection of national energy use annually called the Annual Energy Outlook (AEO). 44 EIA published its Early Annual Energy Outlook for 2011 in December 2010. EIA released updated data to NHTSA in February (Interim AEO). The final release of AEO for 2011 came out in April 2011, but by that time EPA/NHTSA had already prepared modeling runs for potential 2017-2025 standards using the interim data release to NHTSA. EPA and NHTSA will use the newest version of AEO available in projecting the reference fleet for the final rule.

Similar to the analyses supporting the MYs 2012-2016 rulemaking, the agencies have used the Energy Information Administration’s (EIA’s) National Energy Modeling System (NEMS) to estimate the future relative market shares of passenger cars and light trucks. However, NEMS methodology includes shifting vehicle sales volume , starting after 2007, away from fleets with lower fuel economy (the light-truck fleet) towards vehicles with higher fuel economies (the passenger car fleet) in order to facilitate co mpliance with CAFE and GHG MYs 2012-2016 standards.

Because we use our market projection as a baseline relative to which we measure the effects of new standards, and we attempt to estimate the industry’s ability to comply with new standards without changing product mix (i.e., we analyze the effects of the proposed rules assuming manufacturers will not change fleet composition as a compliance strategy, as opposed to changes that might happen due to market forces), the In terim AEO 2011-projected shift in passenger car market share as a result of required fuel economy improvements creates a circularity. Therefore, for the current analysis, the agencies developed a new projection of passenger car and light truck sales shares by running scenarios from the Interi m AEO 2011 reference case that first deactivate the above-mentioned sales-volume shifting methodology and then hold post-2017 CAFE

44 Department of Energy, Energy Information Administra tion, Annual Energy Outlook (AEO) 2011, Early Release. Available at http://www.eia.gov/forecasts/aeo / (last accessed Aug. 15, 2011).Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

standards constant at MY 2016 levels. This is referred to as the Unforced Reference Case. Incorporating these changes reduced the projected passenger car share of the light vehicle market by an average of about 5% during 2017-2025.

In 2017, car and light truck sales are projected to be 8.4 and 7.4 million units, respectively. While the total level of sales of 15.8 million units is similar to pre-2008 levels, the fraction of car sales in 2017 and beyond is projected to be higher than in the 2000-2007 timeframe. Note that EIA’s definition of cars and trucks follows that used by NHTSA prior to the MY 2011 CAFE final rule. The MY 2011 CAFE final rule reclassified approximately 1 million 2-wheel drive sport utility vehicles from the truck fleet to the car fleet.

In addition to a shift towards more car sales, sa les of segments within both the car and truck markets have also been changing and are expected to continue to change in the future. Manufacturers are continuing to introduce more crossover models which offer much of the utility of SUVs but use more car-like designs and unibody structures. In order to reflect these changes in fleet makeup, EPA and NHTSA used a custom long range forecast purchased from CSM Worldwide (CSM). CSM Worldwide (CSM) is a well-known industry analyst, that provided the forecast used by the agencies for the 2012-2016 final rule. NHTSA and EPA decided to use the forecast from CSM for several reasons. One, CSM uses a ground up approach (e.g., looking at the number of plants and capacity for specific en gines, transmissions, and vehicles) for their forecast, which the agencies believe is a robust forecasting approach. Two, CSM agreed to allow us to publish their high level data, on which the forecast is based, in the public domain. Three, the CSM forecast covered all the timeframe of greatest relevance to this analysis (2017-2025 model years). Four, it provided projections of ve hicle sales both by manufacturer and by market segment. And five, it utilized market segmen ts similar to those used in the EPA emission certification program and fuel economy guide, such that the agencies could include only the vehicle types covered by the proposed standards.

The agencies combined the CSM forecast with data from other sources to create the reference fleet projections. The process of producing the 2017-2025 reference fleet involved combining the baseline fleet with the projection data. Th is was a complex multistep procedure, which is described below and in more detail in Chapter 1 of the Joint TSD. This procedure is the same as that used for the 2012-2016 rule.

We then projected the CSM forecasts for relative sales of cars and trucks by manufacturer and by market segment onto the total sales estimates of AEO 2011. Tables III.A.3-1 and III.A.3-2 show the resulting projections for the reference 2025 model year and compare these to actual sales that occurred in baseline 2008 model year. Both tables show sales using the traditional definition of cars and light trucks.

Table III A.3-1 Annual Sales of Light-Duty Vehicles by Manufacturer in 2008 and Estimated for 2025

Cars Light Trucks TotalSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

2008 MY 2025 MY 2008 MY 2025 MY 2008 MY 2025 MY
Aston Martin 1,370 1,182 1,370 1,182
BMW 291,796 405,256 61,324 145,409 353,120 550,665
Daimler 208,195 340,719 79,135 101,067 287,330 441,786 Fiat/Chrysler 542,003 381,829 1,119,397 394,070 1,661,400 775,899
Ford 654,539 989,401 1,116,354 1,235,185 1,770,893 2,224,586 Geely/Volvo 55,600 88,039 42,797 55,657 98,397 143,696
General Motors 1,350,211 1,395,849 1,744,977 1,802,094 3,095,188 3,197,943
Honda 899,498 1,233,439 612,281 664,579 1,511,779 1,898,018 Hyundai 270,293 479,443 120,734 365,943 391,027 845,386
Kia 145,863 260,649 135,589 199,787 281,452 460,436

Lotus 252 316 252 316
Mazda 191,326 250,553 111,220 117,619 302,546 368,172
Mitsubishi 76,701 54,092 24,028 55,600 100,729 109,692
Nissan 653,121 895,341 370,294 545,889 1,023,415 1,441,229
Porsche 18,909 40,696 18,797 11,219 37,706 51,915 Spyker/Saab 21,706 23,130 4,250 3,475 25,956 26,605
Subaru 85,629 230,101 112,952 101,592 198,581 331,692
Suzuki 68,720 96,728 45,938 27,800 114,658 124,528
Tata 9,596 65,418 55,584 56,805 65,180 122,223
Tesla 800 31,974 800 31,974 Toyota 1,143,696 1,942,012 1,067,804 1,376,057 2,211,500 3,318,069 Volkswagen 291,483 630,163 26,999 154,284 318,482 784,447
Total 6,981,307 9,836,330 6,870,454 7,414,129 13,851,761 17,250,459

Table III A.3-2 Annual Sales of Light-Duty Vehicles by Market Segment in 2008 and Estimated for 2025 Cars Light Trucks

2008 MY 2025 MY 2008 MY 2025 MY Full-Size Car 829,896 245,355 Full-Size Pickup 1,332,335 1,002,806 Luxury Car 1,048,341 1,637,410 Mid-Size Pickup 452,013 431,272
Mid-Size Car 2,103,108 2,713,078 Full-Size Van 33,384 88,572
Mini Car 617,902 1,606,114 Mid-Size Van 719,529 839,452
Small Car 1,912,736 2,826,190 Mid-Size MAV* 110,353 548,457 Specialty Car 469,324 808,183 Small MAV 231,265 239,065
Full-Size SUV* 559,160 46,978Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Mid-Size SUV 436,080 338,849
Small SUV 196,424 71,827
Full-Size CUV* 264,717 671,665
Mid-Size CUV 923,165 1,259,483
Small CUV 1,612,029 1,875,703
Total Sales** 6,981,307 9,836,330 6,870,454 7,414,129
* MAV – Multi-Activity Vehicle, SUV – Sport Utility Vehicle, CUV – Crossover Utility Vehicle
**Total Sales are based on the classic Car/Truck definition.

Determining which traditionally-defined trucks will be defined as cars for purposes of this analysis using the revised definition estab lished by NHTSA for MYs 2011 and beyond requires more detailed information about each vehicle model. This is described in greater detail in Chapter 1 of the TSD.

The forecasts obtained from CSM provided estimates of car and truck sales by segment and by manufacturer, but not by manufacturer for each ma rket segment. Therefore, NHTSA and EPA needed other information on which to base these mo re detailed projected market splits. For this task, the agencies used as a starting point each manufacturer’s sales by market segment from model year 2008, which is the baseline fleet. B ecause of the larger number of segments in the truck market, the agencies used slightly different methodologies for cars and trucks. The first step for both cars and trucks was to break down each manufacturer’s 2008 sales according to the market segment definitions used by CSM. For example, the agencies found that Ford’s cars sales in 2008 were broken down as shown in Table III A.3-3:

Table III A.3-3 Breakdown of Ford’s 2008 Car Sales Full-size cars 160,857 units

Mid-size Cars 170,399 units

Small/Compact Cars 180,249 units

Subcompact/Mini Cars None

Luxury cars 87,272 units

Specialty cars 110,805 units

EPA and NHTSA then adjusted each manufacturer’s sales of each of its car segments (and truck segments, separately) so that the manufacturer’s total sales of cars (and trucks) matched the total estimated for each future model year based on AEO and CSM forecasts. For example, as indicated in Table III A. 3-3, Ford’s total car sales in 2008 were 709,583 units, while theSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

agencies project that they will increase to 1,222,532 units by 2025. This represents an increase of 72.3 percent. Thus, the agencies increased the 2008 sales of each Ford car segment by 72.3 percent. This produced estimates of future sales which matched total car and truck sales per AEO and the manufacturer breakdowns per CSM. However, the sales splits by market segment would not necessarily match those of CSM (shown for 2025 in Table III A.3-1). In order to adjust the market segment mix for car s, the agencies first adjusted sales of luxury, specialty and other cars. Since the total sales of cars for each manufacturer were already set, any changes in the sales of one car segment had to be compensated by the opposite change in another segment. For the luxury, specialty and other car segments, it is not clear how changes in sales would be compensated. For example, if luxury car sales decreased, would sales of full-size cars increase, mid-size cars, and so on? The agencies have assumed that any changes in the sales of cars within these three segments were compensated for by proportional changes in the sales of the other four car segments. For example, for 2025, the figures in Table III.A.3-2 indicate that luxury car sales in 2025 are 1,633,410 units. Luxury car sales are 1,048,341 units in 2008. However, after adjusting 2008 car sales by the change in total car sales for 2025 projected by EIA and a change in manufacturer market share per CSM, luxury car sales decreased to 1,539,165 units. Thus, overall for 2025, luxury car sales had to increase by 98,245 units or 6 percent. The agencies accordingly increased the luxury car sales by each manufacturer by thispercentage. The absolute decrease in luxury car sales was spread across sales of full-size, midsize, compact and subcompact cars in proportion to each manufacturer’s sales in these segments in 2008. The same adjustment process was used for specialty cars and the “other cars” segment defined by CSM.

The agencies used a slightly different approach to adjust for changing sales of the remaining four car segments. Starting with full-size cars, the agencies again determined the overall percentage change that needed to occur in future year full-si ze car sales after 1) adjusting for total sales per AEO 2010, 2) adjusting for manufacturer sales mix per CSM and 3) adjusting the luxury, specialty and other car segments, in order to meet the segment sales mix per CSM. Sales of each manufacturer’s large cars were adjusted by this percentage. However, instead of spreading this change over the remaining three segments, the agencies assigned the entire change to mid-size vehicles. The agencies did so because the CSM data followed the trend of increasing volumes of smaller cars while reducing volumes of larger cars. If a consumer had previously purchased a full-size car, we thought it unlikely that their next purchase would decrease by two size categories, down to a subcompact. It seemed more reasonable to project that they would drop one vehicle size category smaller. Thus, the cha nge in each manufacturer’s sales of full-size cars was matched by an opposite change (in absolute units sold) in mid-size cars.

The same process was then applied to mid-size cars, with the change in mid-size car sales being matched by an opposite change in compact car sales. This process was repeated one more time for compact car sales, with changes in sales in this segment being ma tched by the opposite change in the sales of subcompacts. The overall result was a projection of car sales for model years 2017-2025--the reference fleet--which matched the total sales projections of the AEO forecast and the manufacturer and segment splits of the CSM forecast.

As mentioned above, the agencies applied a slightly different process to truck sales, because the agencies could not confidently project how the ch ange in sales from one segment preferentiallySummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

went to or came from another particular segmen t. Some trend from larger vehicles to smaller vehicles would have been possible. However, the CSM forecasts indicated large changes in total sport utility vehicle, multi-activity vehicle and cross-over sales which could not be connected. Thus, the agencies applied an iterative, but stra ightforward process for ad justing 2008 truck sales to match the AEO and CSM forecasts. The first three steps were exactly the same as for cars. EPA and NHTSA broke down each manufacturer’s truck sales into the truck segments as defined by CSM. The agencies then adjusted all manufacturers’ truck segment sales by the same factor so that total truck sales in each model year matched AEO projections for truck sales by model year. The agencies then adjusted each manufacturer’s truck sales by segment proportionally so that each manufacturer’s percentage of total truck sales matched that forecast by CSM. This again left the need to adjust truck sales by segment to match the CSM forecast for each model year.

In the fourth step, the agencies adjusted the sales of each truck segment by a common factor so that total sales for that segment matched the combination of the AEO and CSM forecasts. For example, projected sales of large pickups across all manufacturers were 932,610 units in 2025 after adjusting total sales to match AEO’s forecast and adjusting each manufacturer’s truck sales to match CSM’s forecast for the breakdown of sales by manufacturer. Applying CSM’s forecast of the large pickup segment of truck sales to AEO’s total sales forecast indicated total large pickup sales of 1,002,086 units. Thus, we increased each manufacturer’s sales of large pickups by 7 percent. The agencies applied the same type of adjustment to all the other truck segments at the same time. The result was a set of sales projections which matched AEO’s total truck sales projection and CSM’s market segment forecast. However, after this step, sales by manufacturer no longer met CSM’s forecast. Thus, we repeated step three and adjusted each manufacturer’s truck sales so that they met CSM’s forecast. The sales of each truck segment (by manufacturer) were adjusted by the same factor. The resultin g sales projection matched AEO’s total truck sales projection and CSM’s manufacturer forecast, but sales by market segment no longer met CSM’s forecast. However, the difference between the sales projections after this fifth step was closer to CSM’s market segment forecast than it was after step three. In other words, the sales projection was converging to the desired result. The agencies repeated these adjustments, matching manufacturer sales mix in one step and then market segment in the next a total of 19 times. At this point, we were able to ma tch the market segment splits exactly and the manufacturer splits were within 0.1 percent of our goal, which is well within the needs of this analysis.

The next step in developing the reference fleets was to characterize the vehicles within each manufacturer-segment combination. In large part , this was based on the characterization of the specific vehicle models sold in 2008 -- i.e. , the vehicles comprising the baseline fleet. EPA and NHTSA chose to base our estimates of detailed vehicle characteristics on 2008 sales for several reasons. One, these vehicle characteristics are not confidential and can thus be published here for careful review by interested parties. Two, because it is constructed beginning with actual sales data, this vehicle fleet is limited to vehicle models known to satisfy consumer demands in light of price, utility, performance, safety, and other vehicle attributes.

As noted above, the agencies gathered most of the information about the 2008 baseline vehicle fleet from EPA’s emission certification and fuel economy database. The data obtained from this source included vehicle production volume, fuel economy, engine size, number of engineSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

cylinders, transmission type, fuel type, etc. EPA’s certification database does not include a detailed description of the types of fuel economy-improving/CO 2 -reducing technologies considered in this final rule. Thus, the agen cies augmented this description with publicly available data which includes more complete technology descriptions from Ward’s Automotive Group. 45 In a few instances when required vehicle information (such as vehicle footprint) was not available from these two sources, the agencies obtained this information from publicly accessible internet sites such as Motortrend.com and Edmunds.com. 46

The projections of future car and truck sales described above apply to each manufacturer’s sales by market segment. The EPA emissions certification sales data are available at a much finer level of detail, essentially vehicle configuration. As mentioned above, the agencies placed each vehicle in the EPA certification database into one of the CSM market segments. The agencies then totaled the sales by each manufacturer for each market segment. If the combination of AEO and CSM forecasts indicated an increase in a given manufacturer’s sales of a particular market segment, then the sales of all the individual vehi cle configurations were adjusted by the same factor. For example, if the Prius represented 30 percent of Toyota’s sales of compact cars in 2008 and Toyota’s sales of compact cars in 2025 was projected to double by 2025, then the sales of the Prius were doubled, and the Prius sales in 2025 remained 30 percent of Toyota’s compact car sales.

For the final rule, the agencies intend to use a more recent version of EIAs AEO, and we also will consider using MY 2010 for the baseline, and potentially an updated future market forecast.

4. How is the development of the baseline fleet for this rule different from the baseline fleet that NHTSA used for the MY 2012-2016 (May 2010) final rule?

The development of the baseline fleet for this ru lemaking utilizes the same procedures used in the development of the baseline fleet for the MY 2012-2016 rulemaking. Unlike that rulemaking we are not making the radical change from using product plan based data to public data. We are using an updated AEO forecast and an updated CSM forecast, but are using basically the same MY 2008 based file as the starting point. Most di fferences are in input assumptions rather than the basic approach and methodology. These include changes in various macro economic assumptions underlying the AEO and CSM forecasts and the use of the AEO Unforced Reference Case.

Another change in the market input data from the last rulemaking involved our redefinition of the list of manufacturers to account for realignment taking place within the industry. The reported results supporting this rulemaking recognize the fact that Volvo vehicles are no longer a part of Ford, but are reported as a separate company, Geely; that Saab vehicles are no longer part of GM, but are reported as part of Spyker; and that Chrysler, along with Ferrari and Maserati are reported as Fiat.

45 Note that WardsAuto.com is a fee-based service, but all information is public to subscribers.

46 Motortrend.com and Edmunds.com are free, no-fee internet sites.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

In addition low volume, specialty manufacturers omitted from the analysis supporting the MY 2012-2016 rulemaking have been included in the analysis supporting this rulemaking. These include Aston Martin, Lotus and Tesla.

The agencies’ reasons for not relying on product plan data for the development of the baseline fleet were discussed in the Regulatory Impact Analysis 47 for the MY 2012-MY 2016 rulemaking and are summarized below. The agencies coul d find no compelling reas on for abandoning the approach used in that rulemaking in developing the baseline fleet for the current rulemaking. The RIA discusses the advantages and disadvantages of the market forecast approach used by the agencies. Two major disadvantages were noted as follows. First, the agencies’ current market forecast includes some vehicles for which manufacturers have announced plans for elimination or drastic production cuts. However, although the ag encies recognize that these specific vehicles will be discontinued, we continue to include them in the market forecast because they are useful as a surrogate for successor vehicles that may appear in the rulemaking time frame to replace the discontinued vehicles in that market segment.

Second, the agencies’ market forecast does not include several MY 2009 or 2010 vehicles, such as the Honda Insight, the Hyundai Genesis and the Toyota Venza and some forthcoming vehicle models, such as the Chevrolet Volt, since the st arting point for defining specific vehicle models in the reference fleet was Model Year 2008. It has been suggested that the agencies’ omission of known future vehicles and technologies in the reference fleet causes inaccuracies. Because the agencies’ analysis examines the costs and bene fits of progressively adding technology to manufacturers’ fleets, the omission of future vehicles and technologies primarily affects how much additional technology (and, therefore, how much incremental cost and benefit) is available relative to the point at which the agencies’ exam ination of potential new standards begins. Thus, in fact, the omission only reflects the referen ce fleet, rather than the agencies’ conclusions regarding how stringent the standards should be. Considering the incremental nature of the agencies’ analysis, and the counterbalancing as pects of potentially omitted technology in the reference fleet, the agencies believe their dete rmination of the stringency of new standards has not been impacted by any such omissions. However, omitting the known future vehicles and technologies may lead to an overstatement of the benefits and costs of the rule. For example, in the 2008-baseline assumption we assume the profitable technologies to place on MY2017-2025 vehicles are not provided by manufacturers. Such technologies include some transmission technologies such as the “6sp DCT-dry”, which we forecast actually have negative costs for the manufacturer.

There are several advantages to the approach used by the agencies in developing the reference fleet for this rulemaking. Most importantly, the market forecast is transparent. The information sources used to develop the market forecast are all either in the public domain or available commercially. Another s ignificant advantage of the market forecast is the agencies ’ ability to assess more fully the incremental costs and benefits of the proposed standards

. In addition, by developing baseline and reference fleets from common sources, the agencies have been able to

47 Final Regulatory Impact Analysis, Corporate Average Fu el Economy for MY 2012-MY 2016 Passenger Cars and Light Trucks, Office of Regulatory Analysis and Evaluation a nd National Center for Statistics and Analysis, National Highway Traffic Safety Ad ministration , U.S. Department of Transportation, March 2010. http://www.nhtsa.gov/staticfiles/rulemaking/ pdf/cafe/CAFE_2012-2016_FRIA_04012010.pdfSummary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

avoid some errors—perhaps related to interpretation of requests—that have been observed in past responses to NHTSA’s requests for product plan data. An additional advantage of the approach used for this proposal is a consistent projection of the change in fuel economy and CO 2 emissions across the various vehicles from the application of new technology. With the approach used for this rulemaking, the baseline market data comes from actual vehicles (on the road today) which have actual fuel economy test data (in contrast to manufacturer estimates of future product fuel economy) – so there is no question what is the basis for the fuel economy or CO 2 performance of the baseline market data as it is. However, the agencies recognize the additional information about future contained in manufacturers’ confidential data and have compared these plans to the projected baseline to ensure that they are consistent.

The agencies have carefully considered these ad vantages and disadvantages of using a market forecast derived from public and commercial sources rather than from manufacturers’ product plans, and we believe that the advantages outweigh the disadvantages for the purpose of proposing standards for model years 2017-2025

.

5. How is this baseline different quantitatively from the baseline that NHTSA used for the MY 2012-2016 (May 2010) final rule?

As discussed above, the current baseline was developed from adjusted MY 2008 compliance data and covers MY 2017-2025. This section describes, for the reader’s comparison, some of the differences between the current baseline and the MY 2012-2016 CAFE rule baseline. This comparison provides a basis for understanding general characteristics and measures of the difference between the two baselines. The curr ent baseline, while developed using the same methods as the baseline used for MY 2012-2016 rulemaking, reflects updates to the underlying commercially-available forecast of manufacturer and market segment shares of the future light vehicle market. The differences are in input a ssumptions rather than the basic approach and methodology. It also includes changes in various macro economic assumptions underlying the AEO forecasts and the use of the AEO Unforced Re ference Case. Another change in the market input data from the last rulemaking involved our redefinition of the list of manufacturers to account for realignment taking place within the industry.

Estimated vehicle sales :

The sales forecasts, based on the Energy Information Administration’s (EIA’s) Early Annual Energy Outlook for 2011 (Interim AEO 2011), used in the current baseline indicate that the total number of light vehicles expected to be sold during MYs 2012-2016 is 79 million, or about 15.8 million vehicles annually. NHTSA’s MY 2012-2016 final rule forecast, based on AEO 2010, of the total number of light vehicles likely to be sold during MY 2012 through MY 2016 was 80 million, or about 16 million vehicles annually. Light trucks are expected to make up 37 percent of the MY 2016 baseline market forecast in the current baseline, compared to 34 percent of the baseline market forecast in the MY 2012-2016 final rule. These changes in both the overall size of the light vehicle market and the relative market shares of passenger cars and light trucks reflect changes in the economic forecast underlying AEO, changes in AEO’s forecast of future fuel prices, and use of the Unforced Reference Case.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Estimated manufacturer market shares :

These changes are reflected below in Table III A.5-1, which shows the agency’s sales forecasts for passenger cars and light trucks under the current baseline and the MY 2012-2016 final rule. There has been a general decrease in MY 2016 fo recast overall sales and for all manufacturers, with the exception of Chrysler, when the current baseline is compared to that used in the MY 2012-2016 rulemaking. There were no significan t shifts in manufacturers’ market shares between the two baselines. The effect of including the low volume specialty manufacturers and accounting for known corporate realignments in the current baseline appear to be negligible. There has been a shift in the shares of passenger and non passenger vehicles as would be expected given that the agency is relying on different underlying assumptions as discussed above and in Chapter 1 of the joint TSD.

Table III A.5-1. Sales Forecasts (Production for U.S. Sale in MY 2016, Thousand Units)
MY 2012-2016 Final
Rule 48 Current Baseline

Manufacturer Passenger Car Light Truck Passenger Car Light Truck

Aston Martin 1

BMW 423 171 383 184

Daimler 271 126 245 136 Fiat/Chrysler 400 462 392 498
Ford 1,559 911 1,393 930 Geely/Volvo 94 50
General Motors 1,514 1,342 1,391 1,444

Honda 930 545 862 588 Hyundai 518 92 489 99

Kia 548 115 512 124

Lotus 0.3

Mazda 420 72 393 78

Mitsubishi 83 55 80 60

Nissan 946 381 869 410

Porsche 33 17 30 18 Spyker/Saab 18 2

Subaru 207 117 236 74

48 Again, Aston Martin, Alfa Romeo, Ferrari, Maserati, Lotu s and Tesla were not included in the baseline of the MY 2012-2016 rulemaking; Volvo vehicles were reported under Ford and Saab vehicles were reported under GM; and Chrysler was reported as a separate company whereas now it is reported as part of Fiat and includes Alfa Romeo, Ferrari, and Maserati.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Suzuki 103 20 94 21

Tata 65 42 59 46

Tesla 27 Toyota 2,226 1,077 2,043 1,159 Volkswagen 583 124 528 134
Total 10,832 5,669 10,139 6,055

Estimated achieved fuel economy levels : The current baseline market forecast shows industry-wide average fuel economy levels somewhat lower in MY 2016 than shown in the baseline market forecast for the MY 2012-2016 rulemaking. Under the current baseline, average fuel economy for MY 2016 is 27.0 mpg, versus 27.3 mpg under the baseline in the MY 2012-2016 rulemaking. The 0.3 mpg change relative to the MY 2012-2016 rulemaking’s baseline is the result of changes in the shares of passenger and non passenger vehicles in the MY 2016 market as noted above.

These differences are shown in greater detail below in Table III A.5-1, which shows manufacturer-specific CAFE levels (not counting FFV credits that some manufacturers expect to earn) from the current baseline versus the MY 2012-2016 rulemaking baseline for passenger cars and light trucks. Table III A.5-2 shows the combined averages of these planned CAFE levels in the respective baseline fleets. These tables demonstrate that there are no significant differences in CAFE for passenger or non passenger vehicles at the manufacturer level between the current baseline and the MY 2012-2016 rulemaking baseline. The differences become more significant at the manufacturer level when combined CAFÉ levels are considered. Here we see a general

decline in CAFE at the manufacturer level due to the increased share of light trucks. Because the agencies have, as for the MY 2012-2016 rulemaking, based this market forecast on vehicles in the MY 2008 fleet, these changes in CAFE levels reflect changes in vehicle mix, not changes in the fuel economy achieved by individual vehicle models.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table III A.5-2. Current Baseline CAFE Levels in MY 2016 versus MY 2012-2016 Rule Making CAFE Levels (Passenger Car and Light Truck)
MY 2012-2016 Final Rule 49 Current Baseline

Manufacturer Passenger Car Light Truck Passenger Car Light Truck

Aston Martin 18.83

BMW 27.19 23.04 27.19 23.03

Daimler 25.25 21.12 25.50 21.13 Fiat/Chrysler 28.69 22.19 27.74 22.19

Ford 28.14 21.31 28.24 21.32 Geely/Volvo 25.89 21.08

General Motors 28.42 21.45 28.38 21.45

Honda 33.98 25.05 33.83 25.02 Hyundai 32.02 24.30 31.74 24.29

Kia 32.98 23.74 32.70 23.74

Lotus 29.66

Mazda 30.94 26.41 30.77 26.40

Mitsubishi 28.94 23.59 28.86 23.57

Nissan 32.04 22.11 31.98 22.10

Porsche 26.22 19.98 26.22 19.98 Spyker/Saab 26.54 19.79

Subaru 29.44 26.91 29.59 27.37

Suzuki 30.84 23.29 30.77 23.29

Tata 24.58 19.74 24.58 19.71

Tesla 244.00 Toyota 35.33 24.25 35.22 24.26 Volkswagen 28.99 20.23 28.90 20.24 Total/Average 30.73 22.59 30.65 22.56

49 Again, Aston Martin, Alfa Romeo, Ferrari, Maserati, Lotu s and Tesla were not included in the baseline of the MY 2012-2016 rulemaking; Volvo vehicles were reported under Ford and Saab vehicles were reported under GM; and Chrysler was reported as a separate company whereas now it is reported as part of Fiat and includes Alfa Romeo, Ferrari, and Maserati.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

Table III A.5-3. Current Baseline CAFE Levels in MY 2016 versus MY 2012-2016 Rule Making CAFE Levels (Combined)

Manufacturer MY 2012-2016 Final
Rule 50 Current Baseline

Aston Martin 18.83

BMW 25.85 25.68

Daimler 23.77 23.75 Fiat/Chrysler 24.79 24.33

Ford 25.17 24.99 Geely/Volvo 23.99
General Motors 24.66 24.37

Honda 30.03 29.61 Hyundai 30.56 30.18

Kia 30.89 30.46

Lotus 29.66

Mazda 30.18 29.95

Mitsubishi 26.53 26.33

Nissan 28.38 27.97

Porsche 23.74 23.48 Spyker/Saab 25.70

Subaru 28.47 29.03

Suzuki 29.30 29.04

Tata 22.42 22.19

Tesla 244.00 Toyota 30.75 30.27 Volkswagen 26.94 26.60 Total/Average 27.34 27.03

6. How does manufacturer product plan data factor into the baseline used in this final rule?

In December 2010, NHTSA requested that manufacturers provide information regarding future product plans, as well as information regarding the context for those plans (e.g., estimates of

50 Again, Aston Martin, Alfa Romeo, Ferrari, Maserati, Lotu s and Tesla were not included in the baseline of the MY 2012-2016 rulemaking; Volvo vehicles were reported under Ford and Saab vehicles were reported under GM; and Chrysler was reported as a separate company whereas now it is reported as part of Fiat and includes Alfa Romeo, Ferrari, and Maserati.Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

future fuel prices), and estimates of the future availability, cost, and efficacy of fuel-saving technologies. 51 The purpose of this request was to acquire updated information regarding vehicle manufacturers' future product plans to assist the ag ency in assessing what corporate average fuel economy (CAFE) standards should be established for passenger cars and light trucks manufactured in model years 2017 and beyond. The request was being issued in preparation for today’s joint Notice of Proposed Rulemaking regarding future CAFE and greenhouse gas (GHG) standards.

To assist the agency in analyzing potential CAFE standards for MYs 2017 and beyond, NHTSA requested any updates to product plans previously provided by vehicle manufacturers, as well as production data through the recent past, including data about engines, transmissions, vehicle mass reduction technologies, and hybrid tec hnologies for MY 2010 through MY 2025 passenger cars and light trucks and the assumptions underlying those plans.

NHTSA indicated that it requested information for MYs 2010-2025 primarily as a basis for subsequent discussions with individual manuf acturers regarding their capabilities for the MYs 2017-2025 time frame as it worked to develop today’s NPRM. NHTSA indicated that the information received would supplement other information to be used by NHTSA to develop a realistic forecast of the vehicle market in MY 2017 and beyond, and to evaluate what technologies may feasibly be applied by manufacturers to achieve compliance with potential future standards. NHTSA further indicated that information regarding later model years could help the agency gain a better understanding of how manufacturers' plans through MY 2025 relate to their longer-term expectations regarding foreseeable regulatory requirements, market trends, and prospects for more advanced technologies (s uch as HCCI engines, dual loop cooled EGR, plug-in hybrid, electric, and fuel cell vehicles, among others).

NHTSA also indicated that it would consider in formation regarding the model years requested when considering manufacturers' planned schedules for redesigning and freshening their products, in order to examine how manufacturers anticipate tying technology introduction to product design schedules. In addition, the agency requested information regarding manufacturers' estimates of the future vehicle population, and fuel economy improvements and incremental costs attributed to tech nologies reflected in those plans.

Given the importance that responses to this request for comment may have in informing NHTSA's proposed CAFE rulemaking, whether as part of the basis for the standards or as an independent check on them, NHTSA requested that commenters fully respond to each question, particularly by providing information regarding the basis for technology costs and effectiveness estimates.

Although NHTSA practice has typically been to request product plan information reaching several years beyond the end of the anticipated rulemaking time frame in order to provide this context, many manufacturers submitting comments in the past have provided relatively little detail in response for those later model years. Considering past responses to these requests, NHTSA expected that most manufacturers' product plans would be well defined through

51 75 FR 80430Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

approximately 2015, somewhat less defined through approximately 2020, and thereafter, increasingly fluid and open to change. As NHT SA and EPA are working jointly to consider standards that cover MYs 2017-2025, we requested that manufacturers provide as much information as they can, spanning as many of these model years as feasible, and also summarize major sources of uncertainty. For example, if a manufacturer's plans depend significantly on fuel prices, we requested that the manufacturer indicat e which fuel prices they have assumed, as well as what general differences in product plans could be expected given significantly lower or higher future fuel prices. Also, as fuel eco nomy regulations are not defined beyond MY 2016, and GHG regulations currently do not change after MY 2016, it is expected that product plan information may be based on requirements continuing to reflect MY 2016 levels through MY 2025. However, if other assumptions have been used, NHTSA requested those assumptions be provided.

In addition, NHTSA noted that it would share the information submitted in response to this notice with the Environmental Protection Agency (EPA), and that doing so would facilitate NHTSA's and EPA's consideration of the appropria te factors to be used in establishing fuel economy and GHG standards, respectively, for MY 2017 and beyond. Both agencies must ensure that confidential information that is sh ared is protected from disclosure in accordance with their regulations and practices in this area.

In response to NHTSA’s request, Chrysler, Ford, General Motors, Mazda, Mitsubishi, and Porsche submitted product plans in February 20 11. These plans contain detailed estimates— including fuel economy levels, technology conten t, other engineering characteristics, and sales volumes—of the fleets these manufacturers plan to produce for sale in the U.S. in the future. Three of these manufacturers provided plans thro ugh MY 2016; among the other manufacturers, plans extended through MYs 2015, 2020, and 2025. NHTSA believes these manufacturers’ submitted product plans reflect significant expenditu re of effort and attention to detail. Before preparing today’s NPRM, NHTSA met with these manufacturers (and others) to discuss their capabilities, and the information provided in these product plans helped the agency to prepare for and more effectively question these manufacturers.

For CAFE rulemakings through March 2010 (in that case, for MY 2011), NHTSA used manufacturers’ product plans—and other information—to build market forecasts providing the foundation for the agency’s rulemaking analysis. The agency continues to believe that these market forecasts reflected the most technically sound forecasts the agency could have then developed for this purpose. Because the agency could not disclose confidential business information in manufacturers’ product plans, NHTSA provided summarized information, such as planned CAFE levels and technology application rates, rather than the fuel economy levels and technology content of specific vehicle model types.

In preparing the MY 2012-2016 rule jointly with EPA, NHTSA revisited this practice, and concluded that for that rulemaking, it was importa nt that all reviewers have equal access to all details of NHTSA’s analysis. NHTSA provided this level of transparency by releasing not only the agency’s CAFE modeling system (a.k.a. “the Volpe model”), but also by releasing all model inputs and outputs for the agency’s analysis. Th erefore, NHTSA worked with EPA, as it did in preparing for analysis supporting today’s proposal, to build a market forecast based on publicly-Summary of Interagency Working Comments Received on Draft rule under EO 12866 review. Subject to further policy review.

and commercially-available sources. NHTSA conti nues to believe that the potential technical benefits of relying on manufacturers’ plans for future products are outweighed by the transparency gained in building a market forecast that does not rely on confidential business information.

7. How else is NHTSA considering look ing at the baseline for the final rule final rule?

NHTSA is also considering developing and using a vehicle choice model to estimate the extent to which sales volumes would shift in response to changes in vehicle prices and fuel economy levels. As discussed Chapter V, the agency is currently sponsoring research directed toward developing such a model. If that effort is successful, the agency will consider integrating the model into the CAFE modeling system and using th e integrated system for future analysis of potential CAFE standards. If the agency does so, we expect that the vehicle choice model would impact estimated fleet composition not just unde r new CAFE standards, but also under baseline CAFE standards.

NHTSA has also developed an alternative “market-driven” baseline which assumes that manufacturers may adopt some fuel-saving measures beyond what is required by the MY 2016 rule. This baseline, discussed in Section X, be low, assumes that manufacturers will compare the cost of fuel-saving technologies to consumers to th e fuel savings in the first year of operation and decide to voluntarily apply those technologies to their vehicles when benefits for the first year exceeded costs for the consumer. NHTSA seeks comment on whether this baseline more accurately predicts the likely state of the market in MY 2017 to 2025 than the flat baseline assumption, or whether even more fuel technologies would be likely to be adopted in the absence of the proposed rule.