Vehicle improvements strategies primarily seek to reduce GHGs by increasing the fuel efficiency of vehicles currently in use. These strategies are aimed at increasing the supply and demand for more fuel-efficient vehicles, and at increasing the fuel efficiency of currently-owned vehicles, either by improving the vehicles themselves or by improving how they are operated. This section also includes strategies that seek to reduce the fuel that is consumed when vehicles are used to perform other functions (e.g., waiting in vehicles for non-traffic reasons or heating or cooling the vehicle).
This review covers the following seven vehicle strategies:
Government may use various market strategies to influence car-buying behavior. For example, feebates seek to increase the demand for fuel-efficient, conventional vehicles among those who are already in the market for a new vehicle. They do this by combining a tax on inefficient vehicles with a subsidy for efficient ones. Scrappage programs seek to increase the demand for new fuel-efficient vehicles among existing car owners who otherwise might not be in the market for a new vehicle. They provide financial incentives for vehicle owners to retire less fuel-efficient vehicles and replace them with more fuel efficient ones, earlier than they would otherwise have. Finally, tax incentives seek to increase the demand for alternative-technology vehicles such as hybrid electric or plug-in electric vehicles that have lower emissions by offering tax breaks to prospective buyers.
Heavy-duty vehicle retrofits and eco-driving strategies could each improve the fuel economy of currently owned vehicles. Heavy-duty vehicle retrofits change the aerodynamics of heavy trucks so that their fuel economy improves. Eco-driving strategies encourage drivers to adopt small changes in driving behaviors that can improve fuel economy.
Finally, encouraging the use of truck stop electrification (TSE) or auxiliary power units (APUs), and implementing anti-idling regulations or campaigns both seek to reduce emissions from idling. TSEs and APUs are on and off-board technologies that allow long-haul truckers to use electricity to heat and cool their vehicles during resting hours, rather than idling their engines. Anti-idling regulations and campaigns seek to discourage private and commercial drivers from idling their vehicles unnecessarily (e.g., to warm vehicles in cold weather or while waiting for passengers or deliveries).
Strategies aimed at increasing vehicle efficiency through supply- and demand-side measures have generally been successful when implemented. Where they have yet to be implemented, modeling research still suggests they would be successful if well designed. Importantly, supply and demand side strategies are likely to interact positively: the fuel efficiency of vehicles in service may be increased by greater amounts and more quickly if both supply- and demand-side policies are implemented together, than if either is implemented alone.
The size of the effect on supply and demand of course varies depending upon the intensity of the incentives and penalties. Similarly, the resistance or acceptance of these strategies also depends on the extent to which they are voluntary or mandatory, on whether they are equitable, and on the size of burdens they place on manufacturers, consumers, and the public.
Strategies aimed at improving the performance of currently-owned vehicles have very different effects because they use different mechanisms to achieve those improvements. Retrofits involve physical modifications to trucks and are effective in reducing GHGs. They may face some opposition if made mandatory, even though they reduce operating costs for operators and payback periods are short. Eco-driving seeks to improve driving and vehicle maintenance behaviors that improve fuel economy and thus can be effective in reducing GHGs. Eco-driving campaigns and training programs face few barriers because eco-driving is voluntary, but the long-term effectiveness of driver instruction programs may be limited as drivers revert to prior habits. TSE and APU could reduce GHGs significantly among long-haul truckers and is well accepted because of the reduced costs to truck operators. Anti-idling regulations can also reduce emissions and have been implemented widely, largely out of concerns about air quality, but their effectiveness varies depending on enforcement.
The GHG effect of strategies that improve fuel economy of the fleet generally depends on the marginal improvement in fuel economy that the strategy achieves and the number of vehicles or consumers that are affected by the strategy. However, two phenomena counteract the GHG reductions from better fuel economy. First, an increase in fuel efficiency is vulnerable to induced demand. Research shows that the decrease in fuel costs from more fuel-efficient vehicles induces people to drive more. This effect has been estimated to be between 10-30% (UKERC, 2007), meaning, for example, that a 10% gain in fuel efficiency may result in a 1-3% increase in VMT. As this suggests, some vehicle strategies interact negatively with TDM strategies that seek to reduce VMT and encourage the use of other modes. Fuel taxes and road pricing-both of which make the act of driving more expensive-can be combined with other strategies that improve vehicle efficiency or transportation system efficiency to inhibit induced demand.
Second, some strategies like scrappage programs result in early vehicle replacement. By shortening the life of old vehicles, this results in higher rates of vehicle disposal and higher rates of manufacturing for new vehicles. Both processes may produce significant GHGs, and these life-cycle effects must be included when considering the effect of these supply and demand strategies. While scrappage programs are designed to retire vehicles early, other strategies may have this effect unintentionally or secondarily. For example, feebates are designed to influence the decisions of those who are already in the market for a new vehicle. However, if rebates are large enough, they could induce some consumers to buy new cars when they otherwise would not. This is less likely with other programs, but should still be considered as a possible side effect.
Finally, vehicle strategies have common co-benefits. In reducing the amount of fuel consumed, these strategies also reduce pollution, dependence on oil, and the amount travelers spend on fuel (except in the case of fuel taxes). Those that increase the supply or demand for new fuel-efficient vehicles also advance new vehicle technologies. Aside from fuel taxes, carbon taxes, and cap and trade programs, however, they do not reduce VMT and so they have no obvious effect on community livability, public health from increased use of non-motorized transportation, or congestion. Each strategy review also includes co-benefits other than those reported here that may be unique to the particular strategy.
UKERC (2007). The Rebound Effect: An Assessment Of The Evidence For Economy-Wide Energy Savings From Improved Energy Efficiency, The Technology And Policy Assessment Function Of The UK Energy Research Centre.
Policy: Feebate programs create a monetary incentive for consumers to choose more efficient new vehicles by combining a tax on inefficient vehicles that have higher CO2 emissions with a subsidy for efficient vehicles that have lower CO2 emissions.
Emissions Benefits and Costs: The effect on emissions is sensitive to the design of the policy and cannot be generalized. The implementation costs are low because the tax on low fuel efficiency vehicles funds the subsidy for high fuel efficiency vehicles. Thus, the only cost is administering the program. Those costs are unknown because there are no existing feebate programs in operation, but costs should be within the range of other federal and state vehicle incentive (and 'gas-guzzler' fee) programs.
Implementation Barriers: Several state legislatures have tried unsuccessfully to pass bills establishing feebate programs.
Feebates create a monetary incentive for consumers to choose more efficient new vehicles by combining a tax on inefficient vehicles with a subsidy for efficient ones. Such programs can be implemented in a variety of ways. Feebates can be based either on either fuel efficiency (e.g., EPA estimates of miles per gallon or gallons per mile) or GHG emissions per mile. In the design of a feebate program, a pivot point is chosen where vehicles above that level of fuel efficiency receive a subsidy and those vehicles below it pay a penalty. The penalty increases with declining fuel efficiency and the subsidy increases with increasing fuel efficiency. Feebate programs can also be differentiated within a vehicle class size, so as not to discriminate against larger vehicles, just less efficient ones within each vehicle class (Johnson, 2006).
The policy of implementing a feebate program can be undertaken at the state or federal level. A federal program is likely to be more effective because there are problems with leakage at the state level. Leakage means that residents of a state with a feebate program might go to another state to purchase a low fuel efficiency vehicle while people from other states might travel to the state with the feebate program to purchase high fuel efficiency vehicles. As with other regulatory strategies, it seems unlikely that a state DOT or MPO would have much of a role in implementing a feebate strategy.
This strategy targets buyers of new cars and light-trucks in the region subject to the feebate program, although it is also possible to structure the program in such a way that manufacturers are assessed fees and receive rebates, which are then passed on to consumers (Greene et al., 2005). Technically, a feebate program could be implemented anywhere along the sales chain (i.e., at the manufacturer, dealer, or consumer level). However, Greene, et al. (2005) estimated that 90-95% of the response is due to manufacturers adopting new technology, making the manufacturer level economically efficient. At the same time, this option is likely infeasible for a state-level feebate program.
Feebates aim to encourage consumers to purchase more fuel efficient vehicles. Determining the effect on an individual consumer's choice and the savings achieved from that choice is difficult given the many assumptions that must be made. The literature on U.S. and EU feebate programs is largely theoretical, due to a lack of implementation on which to build empirical evaluations. Unfortunately, the literature does not offer a consensus on design specifications or impacts. One can expect, however, that a program with steeper penalties (and, subsequently, steeper incentives) would result in more fuel savings. The quantitative studies that have considered the effectiveness of feebates have used models of consumer and manufacturer response to estimate the effects of applying incentives through a feebate program. There is consensus that manufacturers are likely to respond to a feebate by adding technology to their vehicle offerings, and that only a small portion of savings is likely to come from a shift to smaller vehicles (mix shifting).
Effects are sensitive to the design of the feebate program as well as to the level at which the program is implemented (i.e., state vs. federal). A lower pivot point and stricter feebate schedule will likely lead to greater reductions of GHGs. However, due to the multiplicity of design possibilities, the findings of specific studies as data points are presented below:
As with fuel economy standards, most estimates of the net cost of feebates are negative because consumers will benefit from lower operating costs. As noted below, given uncertainty in fuel prices, consumers' time preferences, and their valuing of preferences for certain vehicle attributes, the cost could also be positive. The cost of administering the program is unknown because there are no functioning feebate programs, but it is unlikely to be much different than other vehicle incentive programs. It is possible that the costs of the program could be recovered from the fees paid, before rebates are awarded.
The uncertainty in the estimates of costs and effectiveness results not from the quantity or quality of the studies, but from the lack of comparability across them. The specification and schedule of a feebate program must be very explicit, and each study in the literature essentially evaluates a different program (often under different assumptions). It is difficult, if not impossible, to definitively determine the GHG savings or cost of a generic feebate program; these programs and studies cannot be generalized to that degree. Furthermore, consumers' savings are based on estimated payback periods and assumptions about how consumers value fuel savings over time. This valuation will affect how consumers respond to the feebate incentives and influence the mix of vehicles and their relative efficiencies within each class of vehicle.
The cost of implementing a feebate program should be within the range of other federal and state vehicle incentive (and 'gas-guzzler' fee) programs.
At the national level, much of the institutional capacity used to administer fuel economy programs could be used to administer a feebate program. However, at the state level, this capacity does not currently exist and would likely need to rely on EPA estimates of fuel economy-for Corporate Average Fuel Economy (CAFE) compliance-or regulatory agencies would need to develop new capacity for testing vehicle offerings. Furthermore, implementing a feebate at the manufacturer level, rather than at the consumer level, requires regulatory authority that a state agency may not currently have.
A survey in the EU (de Haan et al., 2009) found that feebate systems were among the most accepted policy measures (scoring as high as purely informational measures, like energy labeling). This may not translate to similar consumer acceptance in the U.S. Several state legislatures have tried unsuccessfully to pass bills establishing feebate programs, suggesting that there may be challenges in such programs. Concerns have been voiced that feebates are another form of tax and that offering some consumers rebates while others are taxed is unfair (Johnson, 2006).
Manufacturers who sell more fuel-efficient cars and trucks will benefit more from a feebate program than firms that still primarily sell larger trucks. This may affect social acceptance, since it would seem to disadvantage domestic automakers that, until very recently, have largely focused on larger vehicles.
Greene et al. (2005) estimated that the net social cost from a feebate program would be between $2 billion and $12 billion dollars, depending on design and payback periods. Society would have a net benefit under most designs coming from fuel savings from increased fuel economy; therefore, higher fuel prices make programs to increase fuel economy more cost effective for consumers. According to the study, at gas prices below $2/gallon, consumers can still save up to $2,000 over the life of the vehicle for a well-designed program. This estimate is sensitive to assumptions about payback periods and long-term valuations.
There are currently no feebate programs in the U.S., though several states (notably Connecticut and Massachusetts) have tried to develop feebate programs recently. Washington, D.C. has implemented a variable vehicle registration fee which charges heavy vehicles more than the standard rate and hybrids half the standard rate. In Europe, France's environment ministry has proposed a feebate based on CO2 emissions (Langer, 2005). The only actual automotive feebate program in the U.S., Canada, or the EU was implemented in Ontario, Canada, in 1991 and there are no quantitative studies of it, though it is generally considered to be ineffective because of its particular design: the program covered too few high-emitting vehicles (only 12% of all models) and used incentives of $75-100, too small to influence behavior (Langer, 2005). Canada's 2007 federal budget had funds allocated to create a prototype feebate program in Ottawa, but the program suffered from some of the same design flaws as the Ontario program In 2007, only ten vehicle models were subject to the feebate-making it easy for consumers to avoid the penalty. The program was also implemented immediately, without providing the lead-time that industry needs to adopt new technology. Leakage to the U.S. is also a concern for Canada, since the U.S. has no similar program in place. Canada is currently revising its feebate program and studying various implementation schemes (Banerjee, 2007).
Further investigation of this policy requires detailed modeling of consumer demand for fuel economy that considers the impact of fuel prices, and the emerging national fuel economy program. While this is not a recommendation for near-term research, it would be a valuable area of future research. In the near term, it would be valuable to assess the social barriers to feebate programs that have been considered in the U.S.
Banerjee, Robin (2007). Deals on Wheels: An Analysis of the New Federal Auto Feebate, C.D. Howe Institute, No. 108, November.
Davis, W.B., Levine, M.D., Train, K., Duleep, K.G. (1995). Effects of Feebates on Vehicle Fuel Economy, Carbon Dioxide Emissions, and Consumer Surplus, DOE/PO-0031. Office of Policy, US Department of Energy.
de Haan, P.; Mueller, M. G. and Scholz, R. W. (2009). How much do incentives affect car purchases? Agent-based microsimulation of consumer choice of new cars - Part II: Forecasting effects of feebates based on energy-efficiency Energy Policy, 37, pp. 1083-1094.
Greene, D. L.; Patterson, P. D.; Singh, M. and Li, J. (2005). Feebates, rebates and gas-guzzler taxes: a study of incentives for increased fuel economy Energy Policy, 33, pp. 757-775.
Greene, David L. (2009). Feebates, footprints and highway safety, Transportation Research Part D, vol. 14, pp. 375 - 384.
Johnson, K. C. (2006). Feebates: an effective regulatory instrument for cost-constrained environmental policy Energy Policy, 34, pp. 3965-3976.
Koopman, G.J. (1995). Policies to reduce CO2 emissions from cars in Europe: a partial equilibrium analysis. Journal of Transport Economics and Policy 30 (1), pp. 53-70.
Langer, T. (2005). Vehicle efficiency incentives: an update on feebates for statesAmerican Council for an Energy-Efficient Economy.
McManus, W. S. (2007). Economic analysis of feebates to reduce greenhouse gas emissions from light vehicles for California University of Michigan Transportation Research Institute.
Policy: Scrappage programs provide financial incentives for vehicle owners to retire less fuel efficient vehicles and replace them with more fuel efficient ones, earlier than they would otherwise have.
Emissions Benefits and Costs: This is uncertain. While scrappage programs may reduce GHG emissions due to vehicle replacement, the life-cycle emissions from early vehicle replacement are typically unaccounted for but likely reduce this effect. The CARS program ('Cash for Clunkers') offers one estimate of $333/MTCO2, without accounting for life-cycle emissions.
Implementation Barriers: Scrappage programs could be prohibitively expensive for smaller states or regions.
Scrappage rates for modern vehicles are very low in the first three or four years of life, and most early scrappage is the result of traffic accidents. In later years, vehicles may additionally be scrapped due to reduced reliability, increasing maintenance costs, or preference for alternatives (Greenspan and Cohen, 1999). Any program designed to accelerate this process may be referred to as a scrappage program.
Scrappage programs provide financial incentives for vehicle owners to retire older-and likely less efficient-vehicles earlier than they would under normal circumstances. They are often referred to as voluntary accelerated vehicle retirement (VAVR) programs, but have been known by more colorful names like vehicle scrappage, buy-back, or, more recently, 'cash-for-clunkers' programs (Dill, 2004). The objective of VAVR programs is to substitute cleaner, more efficient vehicles for older, less efficient ones and accelerate the transformation in the population of registered vehicles that occurs naturally over longer periods of time.
Typically, these programs have been conceived to reduce conventional air pollutants like carbon monoxide, oxides of nitrogen, volatile organic compounds, and particulates emitted when vehicles burn fossil fuels. For these purposes, an improvement can be realized by replacing an old vehicle essentially with any newer vehicle. A number of countries have implemented age-based scrappage programs. For example, France's program began in 2007. It initially limited retirement to cars over fifteen years old and then expanded it in 2008 to cars over 10 years old. A program in the UK ran from 2009 to 2010 and limited incentives to vehicles over 10 years of age (Lorentziadis and Vournas, 2011).
However, to reduce CO2 emissions, 'newness' alone is not enough: the replacement vehicle must have a better fuel economy than the replaced vehicle. Therefore, merely encouraging owners to replace older vehicles with newer ones may not have the desired effect unless the program explicitly accounts for the change in fuel economy between the old and new vehicles.
For example, the recent Car Allowance Rebate System (CARS), more commonly referred to as 'cash-for-clunkers,' targeted not just older cars, but older cars with an EPA estimated combined city/ highway fuel economy of 18 mpg or less (NHTSA, 2009). Moreover, it specified that the new vehicle must have a combined fuel economy of 22 mpg. The actual value of the incentive was determined by the fuel economy difference between the 'clunker' and the new vehicle, and greater fuel economy increases received larger incentives. Incentives were between $3500 and $4500 in most cases, though some manufacturers and new car dealers provided additional financial incentives to spur demand during a challenging year for auto retailers. A detailed description of the incentive structure is available from a recent NHTSA report (NHTSA, 2009).
Other countries have also incorporated emissions requirements into their scrappage programs. In order to qualify for incentives, for example, France's program now requires that new cars purchased to replace old vehicles emit, at most, 160g/km (equivalent to 0.57 lbs/mile). Spain's program begin in 2008 and limits emissions to 149g/km (0.53 lbs/mi), and Portugal to 140g/km (0.50 lbs/mi) (European Automobile Manufacturers Association, 2010).
One subtle but important aspect of these programs is the life-cycle implications of scrapping vehicles earlier than would otherwise occur. That is, the emissions benefit gained from scrappage must also offset the emissions that are produced from the manufacture of the new vehicle. Kim et al. (2003) find that, for mid-size model year cars in 2000 and beyond, trading in a 7-14 year old vehicle minimizes conventional pollutants, but that a vehicle must be at least 18 years old to sufficiently offset the GHG emissions from prematurely manufacturing the new vehicle. Emissions may also result from the scrappage process. This has implications for VAVR programs, which may encourage much newer vehicle trade-ins, and indicates that policy makers should take a longer view of emissions than those originating at the tailpipe.
A VAVR program could be implemented at the national level by a federal agency, like the 2009 CARS program ("cash-for-clunkers") or by DOTs and even MPOs, like the BAAQMD Vehicle Buy Back Program in the San Francisco Bay Area region.
VAVR programs to improve GHG emissions target owners of cars with poor fuel economy. Typically, these inefficient vehicles are older, but a program specifically designed to reduce tailpipe CO2 emissions could conceivably target relatively recent model year vehicles with poor fuel economy. For example, a program could provide incentives for people to trade-in very large SUVs (above 8,500 lbs) for either more efficient SUVs or passenger cars; this would have a greater CO2 benefit than simply replacing an old fuel-efficient vehicle with a new one. However, if life-cycle CO2 emissions are the measure of effectiveness, then only owners of still-older vehicles should be targeted (e.g., 18 years for the case of mid-size cars in model year 2000 and beyond). In either case, the target group is current vehicle owners using inefficient vehicles. Additionally, there is some concern of 'free ridership' in the program, where some portion of incentives go to vehicle owners who intend to retire their vehicles anyway.
The literature evaluating specific VAVR programs to reduce GHG emissions is sparse, since VAVR programs are not typically used to achieve greenhouse gas reductions. Moreover, there is currently no generally accepted approach to estimating GHG savings-with some studies using the fuel cycle (and tailpipe) emissions (NHTSA, 2009), others using a full life-cycle perspective (Kim et al., 2003, 2004), and others considering only the incremental increase in average fuel economy of new vehicles under a VAVR program (Sivak and Schoettle, 2009). Additionally, embedded within each of these estimates are important, but contentious, assumptions about VMT (for both the new vehicle and the vehicle it replaced), useful life, and the timing of new vehicle purchases in absence of the program.
Using survey data from the BAAQMD program and a pilot program in Southern California, Dill (2004) estimated that the average scrapped vehicle would have lasted between 1.8 and 3.2 more years in private ownership had the scrappage program not been in effect. However, as with other incentive-based programs, the specific effect on an individual's decision to replace a car could not be reliably quantified given the influence of other factors and variations in preferences. Moreover, the per-person effects once a person has chosen to replace a vehicle are also difficult to quantify because this depends on the change in fuel economy between the retired vehicles and the new vehicles replacing them, as well as the driving behavior for each vehicle. For example, replacing a seldom-driven vehicle with a vehicle that will be driven extensively may lead to more CO2 emissions despite the increase in fuel economy between the vehicles. The EPA has estimated a rebound effect of 10%, meaning that 10% of the fuel savings expected to result from an increase in economy is offset by additional fuel use. Given this, it is not possible to calculate per-person CO2 effects in a general sense. The CARS program conducted a survey to estimate the average additional length of time a retired vehicle would have been driven in the absence of the program. The average estimate was 2.87, which is within Dill's (2004) range of 1.8 to 3.2 years.
Estimating the aggregate emissions reduction from a VAVR program requires making many assumptions, which are described under 'Key Assumptions.' The NHTSA CARS report (2009) suggests that the recent "cash for clunkers" program led to changes that will reduce greenhouse gas emissions by nine million MTCO2e over the next 25 years. The estimated impact is based on the difference in fuel consumption between the population of registered vehicles with and without the CARS program, looking ahead to the end of the useful vehicle lives of the new cars and trucks purchased with the aid of the CARS incentives. The estimate attempts to account for both the changes in average fuel economy and travel behavior but does not consider life-cycle emissions, which would likely reduce this benefit.
The CARS program was of rather short duration, running only for two months in the summer of 2009, and it was the first of its kind at the national level in the U.S. Sivak and Schoettle (2009) found that the CARS program led to an increase in the average fuel economy of new vehicle purchases of 0.6 mpg and 0.7 mpg in July and August, respectively. They do not attempt to calculate GHG reductions resulting from this change in fuel economy, since this would require many additional assumptions about vehicle usage both before and after replacement.
There are few estimates of the cost of these programs (and, aside from the literature described, almost no estimates of CO2 reductions from their implementation). According to NHTSA, the CARS program saved CO2 emissions at a cost of about $333 per MTCO2e reduced over the estimated 25-year life of the vehicles purchased under the program (NHTSA, 2009). This cost includes both the direct subsidies to new car buyers and the administrative costs of operating the program, but the emissions benefit does not take into account life-cycle emissions from vehicle replacement. Life-cycle emissions would reduce the emissions benefit and result in a higher cost per unit of reduction.
Assumptions about driving behavior, both of the retired vehicle and the vehicle chosen to replace it, strongly influence estimates of program effectiveness.
In sum, estimating the competing impacts of these factors requires making assumptions about complex issues about which there is little agreement in the literature.
Implementing agencies, at the federal, state, or local level, provide direct subsidies to consumers who are scrapping their vehicles (or possibly credits toward a new vehicle with the retirement of an older one). These costs can be significant, but can be estimated. These programs are likely to have a fixed amount of funding available for incentives, and scrappage programs can be designed to obtain the largest reductions with those resources. For example, the CARS program operated for nearly two months. This was based not on a fixed timeframe but on the time needed to distribute the budgeted incentives to new vehicle buyers. In addition to the cost of the actual incentives, programs will face administrative costs. The CARS program, for example, also resulted in $100 million in administrative costs. Major costs were transaction and voucher processing (estimated at $40 million for processing 20,000 dealer registrations and up to 250,000 transactions) and CARS information technology infrastructure (estimated at $30 million). These costs were high because of the short time frame for development. Other significant costs included education and outreach ($3 million), and program staffing, travel, and general administration ($4.6 million) (NHTSA, 2009).
Smaller entities (MPOs or DOTs) implementing a VAVR program must ensure that retired vehicles are registered within their jurisdiction to avoid subsidizing another state or region's GHG reduction agenda. Nonetheless, there is no guarantee that vehicles purchased under this program will remain in that jurisdiction throughout their useful life.
Although these programs have been acceptable for improving air quality, it is unknown whether a VAVR program to reduce GHG emissions would be similarly acceptable. However, the CARS program was well received in the sense that the initial funds allocated to the program were fully used within the first several days of the program-leading to an additional $2 billion supplement. A longer term program might meet with resistance as the total cost increases over time. Low-income individuals may benefit from this kind of strategy because they disproportionately own older vehicles. On the other hand, programs such as these could also drive up costs for used cars, which could adversely affect this population.
None that are known to us at this time.
There are currently no retirement programs in the U.S. designed to reduce GHG emissions. Prior finite programs and the existing program in the San Francisco Bay Area likely achieve small reductions in GHG. There are a number of programs in Europe that include a GHG mitigation component (e.g., Germany, Spain, Portugal, Ireland, and France).
There are no studies about the life-cycle carbon implications of VAVR programs and this warrants further study. There is an opportunity to use an experimental design with a scrappage program to quantify the causal relationship between the incentive and the consumer's vehicle scrappage decision making.
Dill, Jennifer. (2004). Estimating emissions reductions from accelerated vehicle retirement programs, Transportation Research Part D, 81, pp. 87-106.
European Automobile Manufacturers Association, (2010). Fleet Renewal Schemes in 2010. As of May 17, 2011: http://www.acea.be/index.php/news/news_detail/fleet_renewal_schemes_soften_the_impact_of_the_recession/.
Greenspan, Alan and Darrel Cohen. (1999). Motor Vehicle Stocks, Scrappage, and Sales, The Review of Economics and Statistics, August, 81(3), pp. 369-383.
Kim, H.C., Keoleian, G.A., Grande, D.E., and Bean, J.C. (2003). Life Cycle Optimization of Automobile Replacement: Model and Application, Environmental Science and Technology, 27, 5407-5413.
Kim, H.C. Ross, M.H., Keoleian, G.A., (2004). Optimal fleet conversion policy from a life cycle perspective, Transportation Research Part D, 9, 229-249.
Lorentziadis, P.L, Vournas, S.G. (2011). 'A quantitative model of accelerated vehicle-retirement induced by subsidy,' European Journal of Operational Research, Volume 211, Issue 3, pp. 623-629.
National Cooperative Highway Research Program. (1997). Improving Transportation Data for Mobile Source Emission Estimates, Transportation Research Board.
National Highway Traffic Safety Administration (2009). Consumer Assistance to Recycle and Save Act of 2009: Report to Congress U.S. Department of Transportation.
Office of Transportation and Air Quality. (2009). Light-Duty automotive technology and fuel economy trends: 1975 through 2009 United States Environmental Protection Agency.
Sivak, Michael and Brandon Schoettle. (2009). The Effect of the "Cash for Clunkers" Program on the Overall Fuel Economy of Purchased New Vehicles, Transportation Research Institute, University of Michigan, UMTRI-2009-34.
Small, Kenneth A. and Van Dender, Kurt. (September, 2009). 'The Effect of Improved Fuel Economy on Vehicle Miles Traveled: Estimating the Rebound Effect Using U.S. State Data, 1966-2001,' Policy and Economics.
Policy: Monetary incentives in the form of rebates or tax credits can be offered for purchases of alternatively fueled, fuel-efficient vehicles or vehicles with fuel-saving technologies.
Emissions Benefits and Costs: The effectiveness of incentives to change consumer behavior and reduce GHG emissions is unknown given that certain kinds of clean vehicles have only recently entered the market. Because consumers receive the incentive regardless of whether it influenced their decision to purchase a cleaner vehicle, the unit cost of reducing GHG is likely to be very high. Although much uncertainty makes it difficult to accurately quantify these costs, one high estimate was $3,700/MTCO2.
Implementation Concerns: Incentives could be prohibitively expensive for smaller states or regions.
The most effective fuel-saving technologies to reach mass market thus far are hybrid-electric vehicles (HEV) and clean diesel technology. While plug-in hybrid-electric vehicles (PHEV) and battery electric vehicles (BEV) may reach mass-market penetration by the end of the next decade, they currently represent a very small fraction of new vehicle sales. While these technologies have the potential to reduce fuel consumption, they are also typically more expensive due to the incremental cost of the technology over their conventional gasoline counterparts. Even at large production volumes, this incremental cost can be large and varies (depending on both technology and vehicle size) from about $2000 for a clean diesel engine in a passenger car to about $5100 for a hybrid drivetrain in a pickup truck or large SUV (Keefe et al., 2008). These technology costs are passed along to consumers who must weigh the additional cost against the potential fuel savings, and this deters many consumers from purchasing more advanced and efficient vehicles.
Governments, at both the state and federal level, have attempted to spur demand for these technologies by creating incentives to help reduce the initial cost to consumers. The Energy Policy Act of 1992 established incentives for individuals and businesses to purchase clean-technology and alternatively fueled vehicles. In 2002, hybrid electric vehicles became eligible for these clean-fuel vehicle credits (Yacobucci, 2005). These were updated in 2005, when the Energy Policy Act of 2005 replaced an existing $2,000 tax deduction for all qualifying hybrid vehicles with a system of tax credits that applied to both hybrid and clean diesel vehicles, was sensitive to differences in fuel efficiency, and that terminated once a model achieved modest market penetration (Lazzari, 2006)., Many states offer some tax incentive in addition to the federal tax credit. For example, Colorado offers tax credits of up to $6,000 (depending on the model), but this is currently the upper bound of credits provided by state programs.
Tax credit subsidies must be made by the same institutions and mechanisms that create and manage tax policies: the federal legislature at the federal level (e.g., as part of the 2005 Energy Bill) and state legislatures at the state level. As stakeholders, transportation agencies and MPOs would likely be able to review and comment on legislative proposals to create tax incentive programs but would not directly administer them.
These tax incentives target new car and light-truck buyers, specifically those buyers less inclined to pay a price premium for unfamiliar technology or who may not value fuel economy highly. However, the tax credits target all new car buyers, benefiting many early adopters and environmentally concerned buyers who would have bought these vehicles anyway.
While tax incentives seek to influence individuals' purchasing behaviors, their per-person effects are unknown and essentially impossible to quantify, given the myriad of factors that affect an individual's purchasing decisions, as well as differences in priority among these factors.
Nevertheless, one can estimate the efficiency gains from these vehicles when they are purchased. Although effect size varies by vehicle class, on average a clean diesel engine (running on ultra low sulfur diesel fuel) has 25-30% better fuel economy and an HEV has 30-40% better fuel economy than their conventional gasoline counterparts (Keefe et al., 2008). Hybrid vehicles may provide still greater savings for urban drivers due to regenerative braking and greater use of the electric capacity at low speeds. EPA fuel economy estimates assume 55% of all driving is "city" driving, though this may be higher for drivers in dense urban areas. The greenhouse gas reductions from an individual vehicle depend on assumptions about both the VMT and on the fuel economy of the new vehicle that it replaces. For example, using the EPA assumptions that new vehicles travel 15,000 miles per year, and assuming a conventional gasoline fuel efficiency of 30 mpg as a baseline, a hybrid version would save approximately 1.2 MTCO2 in that year compared to the otherwise-equal conventional model. Analogously, calculating the overall impact of these policies requires making assumptions about the number of purchases that are affected by the incentive, the fuel economies of purchased vehicles, the fuel economies of vehicles that would have been purchased if the incentive were not in place, and the miles driven in each case.
It has only recently been possible to attempt evaluations of the tax incentive policies for clean technology vehicles, due to the limited availability of most qualifying vehicles. Such evaluations also need to separate the effects of the tax incentives from the effects of other factors (e.g., gasoline prices and social trends) on consumers' vehicle choices. Notably, because the current tax incentives were enacted during a period of exceptionally high gasoline price spikes, much of the observed increase in penetration was likely due to consumers' reaction to increased fuel prices rather than the tax incentives. For example, Gallagher and Muehlegger (2008) attributed only 6% of the increase in hybrid sales from 2000-2006 to tax incentives, compared to 27% and 33% of sales resulting from rising fuel prices and changing social preferences, respectively. Beresteanu and Li (2008) found that federal tax incentives were responsible for less than 4% of hybrid sales in 2005, but accounted for nearly 25% of new Prius sales in 2006. Diamond (2009) has supported Gallagher and Muehlegger (2008), suggesting that state financial incentives had little impact on the increase in hybrid vehicle sales over that time period. Diamond (2009) also found that tax incentives that affected the vehicle price at the point of purchase had a greater impact than did credits or rebates, which took longer to realize.
According to the Department of Energy's Alternative Fuels and Advanced Vehicles Data Center, domestic new hybrid vehicle sales increased from 210,000 units in 2005 to 274,000 units in 2010, peaking at over 350,000 units in 2007. Vehicle offerings also expanded from 8 to 29 models in that 6-year time period. However, from 2000 to 2006 only 660,000 hybrids were sold. Gallagher and Muehlegger (2008) have implied that the tax incentives were responsible for the sale of less than 40,000 new hybrids during that time. Beresteanu and Li (2008) implied that approximately 25,000 units of the Toyota Prius were sold in 2006 as a result of the tax credits. The credits for the Prius have since expired, but it still leads all other hybrid models in sales.
One must make assumptions about the new vehicles that these hybrids would have replaced in order to estimate CO2. One reasonable solution is to assume that the new vehicle sales replaced by the hybrid sales would have had the average fuel economy of the new vehicles sold that year. For simplicity, let us assume that the 40,000 new hybrids were purchased uniformly in each year between 2000 and 2006. The average fuel economy of new vehicles in this period was 29.4 miles per gallon, and the average miles driven for new vehicles is 15,000 ). If hybrids have an average fuel economy of 50 mpg, then the incentive would have saved approximately 8.5 million gallons of gasoline and reduced approximately 75,000 metric tons of CO2.
Given the small percentage of hybrid sales growth that is likely attributable to tax incentive programs, the costs per metric ton reduction are likely to be very high. Estimates of this value are sensitive to assumptions (as well as cost accounting-many consumers took advantage of both federal and state tax incentives). Using the conventional gasoline model for comparison and EPA estimates of travel behavior, Diamond (2009) has estimated costs as high as $3,700/MTCO2 reduction in some cases. The tax incentive typically varies by vehicle, so there is likely to be a wide range of cost effectiveness varying by both vehicle and state of purchase.
The studies that have considered the effectiveness of tax incentive programs on clean vehicle technology penetration have concluded that fuel price is a key uncertainty, as are simultaneous incentives (either tax incentives at both the state and federal level or non-monetary incentives like HOV access) and evolving social preferences. To the extent that incentives encourage owners to retire older cars sooner than they would have otherwise, the life-cycle emissions from faster turnover may reduce GHG emissions. However, these effects are not well understood or included in most studies.
Data about domestic clean vehicle technology sales is available from Department of Energy's Alternative Fuels and Advanced Vehicles Data Center. Federal tax incentive programs are regularly updated at www.fueleconomy.gov.
The federal tax incentive program phases out based on sales volume (and over time) for popular vehicles so as to avoid unnecessary subsidies for vehicles that would be purchased anyway. However, states structure their programs differently and may bear large costs, either directly or as opportunity costs, on forfeited sales tax revenue.
There are no specific agency implementation concerns associated with tax incentives.
These types of incentives have existed at the federal level for about a decade, and other federal programs have supported public-private partnerships to advance similar technologies. Given the additional incentives at the state level, social acceptability appears to be high.
None that are known to us at this time.
There is a federal tax credit program for clean vehicle technology, as well as several state-level tax incentive programs typically targeting HEVs.
There is a need for a causal analysis of the influence of incentives on demand for clean vehicles. State DOTs and MPOs can sponsor research and help to design research and data collection to this end.
Beresteanu, Arie and Shanjun Li (2008). Gasoline Prices, Government Support, and the Demand for Hybrid Vehicles in the U.S., Duke University.
Bureau of Transportation Statistics (2009). National Transportation Statistics 2009. US Department of Transportation.
Department of Energy Alternative Fuels and Advanced Vehicles Data Center URL: http://www.afdc.energy.gov. Accessed October 13, 2010.
Diamond, David (2009). 'The Impact of Government Incentives for Hybrid-Electric Vehicles: Evidence From the US States', Energy Policy, 37, pp. 972-983.
Gallagher, Kelly Sims and Erich Muelegger (2008). 'Giving Green to Get Green: Incentives and Consumer Adoption of Hybrid Vehicle Technology', KSG Faculty Research Working Paper Series, RWP08-009.
Keefe, Ryan, James P. Griffin and John D. Graham (2008). 'The Benefits and Costs of New Fuels and Engines for Light-Duty Vehicles in the United States', Risk Analysis, 28, No. 5, 1141-1154.
Lazzari, Salvatore (2006). Tax Credits for Hybrid Vehicles, CRS Report for Congress, RS22558.
Small, Kenneth and Kurt Van Dender (2007). 'Fuel Efficiency and Motor Vehicle Travel: The Declining Rebound Effect', Energy Journal, vol. 28, no.1, pp. 25-51.
Yacobucci, B.D., 2005. Tax incentives for alternative fuel and advanced technology vehicles, CRS Report for Congress, RS22351.
Policy: Retrofits to heavy-duty vehicles can improve their fuel economy and thereby reduce emissions. Effective retrofits include changes to the tires to reduce roll resistance and changes to the body to reduce drag. States can pass regulations requiring the use of retrofits, or subsidize retrofits to voluntarily encourage their use.
Emissions Benefits and Costs: Retrofits can produce a 20%-60% improvement in fuel economy for individual vehicles, but aggregate effect depends on the percentage of existing vehicles incorporating retrofits. Costs to the public and to agencies are minimal since operators undertake retrofits. There are likely to be net social gains because the initial expense of retrofits can be recovered in fuel savings.
Implementation Concerns: Retrofits require up-front costs from operators, which they may resist, particularly in lean times, despite evidence that suggests that payback periods can be short.
Heavy trucks are the preferred mode for short-to-medium distance freight transportation and for time-sensitive goods, and they are therefore a significant component of domestic freight movement. Heavy trucks have consumed nearly 33 billion gallons of gasoline, diesel, and other fuels annually in the U.S. in recent years, and virtually all of this fuel is derived from petroleum. This comprises approximately 18% of energy consumption in the transportation sector (Bureau of Transportation Statistics, 2009) and comes at the cost of associated greenhouse gas emissions, as well as more conventional pollutants.
Given the significant share of heavy-truck oil consumption, regulatory agencies (most notably the California Air Resources Board) are beginning to consider ways to improve the fuel efficiency of heavy trucks. One method to increase fuel efficiency is to target new truck sales with fuel economy standards. While this is likely to improve fuel efficiency over a two-decade time period, such a policy would not improve the average efficiency in the near term because of the slow rate of vehicle turnover.
A second policy option is to mandate retrofits to all heavy trucks to improve fuel economy. The diesel engines and powertrains in heavy trucks are not promising candidates for a retrofit strategy because of technical difficulties and the high costs of modifying existing engines and powertrains. However, there are a variety of tire and vehicle body retrofits that can improve roll resistance and aerodynamics and present feasible and cost-effective opportunities for achieving greater fuel economy.
State DOTs and environmental regulatory agencies can provide financial incentives for aerodynamic retrofits and/or advanced low-resistance tires, or implement regulations that mandate use of retrofits. The EPA SmartWay program offers guidance, financial assistance, and other resources to increase freight efficiency.
Owners of heavy-duty truck fleets (and smaller independent companies and contractors) would be affected by retrofit incentives and/or mandates.
Retrofit policies can encourage or require operators to either make specific modifications to existing heavy vehicles or choose retrofits. Historically, the largest concern about heavy-truck traffic has been the emissions of fine particulates and oxides of nitrogen, which have been tied to adverse health outcomes in urban areas and among sensitive populations (Dierkers et al., 2007). Thus, much of the research on retrofits focuses on conventional pollutants. More recently, studies have sought to understand how retrofits can reduce GHG emissions as well. There is a tendency in these studies to focus on the design of retrofits and their fuel and cost savings, rather than on the policy instruments to encourage their use-the assumption in most cases is that regulations will mandate their adoption.
Although different types of trucks can utilize and benefit differently from various types of retrofits, this section presents data for tractor trailers, since they represent the vast majority of heavy truck fuel consumption. While fewer options exist for 'straight trucks,' the efficiency effects are comparable. Effectiveness varies with assumptions about length of average trip (short, medium, long) and the number of trailers to which flaring technology (used to streamline the profile of trailers to reduce aerodynamic drag) is applied. The description below assumes a single trailer (to each cab) and the cost/effectiveness estimates below will reflect this assumption, as well as assumptions about the average trip length.
The Argonne National Lab study (Vyas, 2002) has estimated the following:
|Retrofit Action||Fuel Economy Gain (%)||Cost ($) |
|Cab top deflector||2.0||900|
|Trailer edge curvature||1.3||600|
|Low Rolling Resistance tires||3.0||1,300|
|Engine friction reduction||2.0||600|
|Peak cylinder pressure||4.0||1,200|
|Vehicle mass (e.g., aluminum wheels)||5.0||2,400|
Langer (2004) considered the cost-effectiveness of these strategies in a variety of scenarios with different fuel prices, discount rates for fuel savings, and payback periods. Langer (2004) found that currently available technologies provided net savings under all of these scenarios. Higher fuel prices will increase expected cost savings. Findings suggest that combinations of currently available technology retrofits lead to fuel economy improvements between 18% and 29% at a net savings of $2,500 to $15,000. Looking out to technologies available in 2015 or later, fuel economy improvements could be as high as 58%, and offer savings up to $24,000. The results for more aggressive and costly retrofits like hybridization are mixed and the findings are dependent on the assumptions about fuel prices and payback periods (where lower fuel prices and shorter payback periods increase the net cost of the retrofit).
Schubert and Komer (2008) considered several retrofit packages ranging from a minimal package to an aggressive package. The minimal package consists of low rolling resistance tires and aerodynamic modifications to the cab. The aggressive package adds to that aluminum wheels (for weight reduction) and aerodynamic fairings to the trailer. Both packages use cost estimates for each modification that are comparable to the Argonne National Labs study above. Schubert and Komer (2008) considered scenarios of multiple fuel price, average trip length, and payback periods as well, and they find positive net savings in all but one case-and these savings are typically of several thousand discounted dollars.
Aggregate GHG effects depend on the penetration rates of new technology and the total area over which GHG savings are calculated. A state regulation that forces all vehicles in the state to adapt would lead to fuel savings everywhere the trucks operate, not just in the state that adopts this strategy. By 2020, after the California retrofit technology regulations are fully phased in, Schubert and Komer (2008) estimate that approximately 11-17 million MTCO2e will be saved annually. Cumulative GHG savings over twenty years are considerably higher, between 80-140 million MTCO2e. Wider implementation of heavy-truck fuel economy or retrofit mandates could increase the effectiveness significantly, as heavy-trucks in more states would be forced to make retrofits.
If one assumes that regulatory agencies or state/national governments bear no cost for implementing the regulations, then one may wish to consider the costs to fleet operators. Under most scenarios, the cost per metric ton of CO2 savings is negative-i.e., results in a net savings-and under some scenarios, largely negative for operators, given the economic benefits of saving fuel.
Access to capital remains an important factor in the penetration rates of these new technologies. Similarly, the cost of diesel fuel affects the net savings and necessary payback period.
The Transportation Data Energy Book contains annual estimates of heavy-truck VMT and fuel consumption by state. The EPA SmartWay website offers an extensive list of tools and data to help reduce emissions from heavy-duty trucks.
Agency costs depend entirely on monitoring costs (unknown) and the decision to provide financial incentives for retrofits.
State DOTs and MPOs may have little authority to mandate changes to vehicles sold or registered outside of their jurisdictions.
Trucking companies are likely to oppose measures that increase operating costs in lean times-even if payback periods are relatively short. Without regulations, rapid penetration of these technologies in existing trucks seems unlikely, though they may become more common in new vehicles.
None that are known to us at this time.
California's heavy-truck fuel economy regulations are began phasing in starting in 2010, and ramp up until 2020 (CARB, 2009). Currently, no other state has comparable measures. From 2008-2010, the EPA's SmartWay program included approximately $50M to finance and help incentivize fuel-saving and emissions-reducing technologies.
It may be beneficial and relatively straightforward to model the implementation of statewide regulations to improve truck efficiency or mandate certain retrofits. However, California (and eventually other states) will need to clarify the penalties associated with non-compliance in order to fully understand the effectiveness of a retrofit policy.
California Air Resources Board (2009), AB32 Approved Scoping Plan: Appendices.
Dierkers, Greg, Mark Houdashelt, Erin Silsbe, Shayna Stott, Steve Winkelman and Mac Wubben (2007). CCAP Transportation Emissions Guidebook Part Two: Vehicle Technology and Fuels, Center for Clean Air Policy.
Langer, Terese (2004). Energy Savings Through Increased Fuel Economy for Heavy-Duty Trucks, American Council for an Energy Efficient Economy.
Schubert, Raymond and Matt Kromer (2008). Heavy-Duty Truck Retrofit Technology: Assessment and Regulatory Approach, Union of Concerned Scientists.
Vyas, A., C. Saricks, and F. Stodolsky (2002). The Potential Effect of Future Energy-Efficiency and Emissions-Improving Technologies on Fuel Consumption of Heavy Trucks, Center for Transportation Research, Argonne National Laboratory.
Policy: Small changes in driving behavior, collectively called 'eco-driving,' can improve fuel economy and reduce greenhouse gas emissions. Transportation agencies can encourage and enable eco-driving practices. Such changes include gentler braking and acceleration, slower driving, and avoiding idling. Three related approaches are education campaigns about eco-driving, eco-driving training programs that give drivers in-vehicle training, and dynamic eco-driving, which uses in-vehicle or road-based sensors to provide drivers with feedback about their behaviors and emissions.
Emissions Benefits and Costs: Because research on eco-driving impacts is still limited, it is difficult to draw definitive conclusions about emissions benefits and costs. Further, the effects of eco-driving depend upon the behaviors that are considered. Modest eco-driving can improve fuel economy by about 5%, although benefits can approach 30% in some circumstances. However, the effects of campaigns are largely unknown because few have been studied rigorously despite some evidence that it is one of the most cost effective ways to reduce GHG (one estimate suggests costs as low as $14/MTCO2). Training programs can encourage drivers to adopt practices initially that produce a 5-15% improvement in fuel economy, but these gains tend to decline over time as drivers revert to earlier driving habits. The effects of dynamic eco-driving are as yet unknown as these programs have not been widely implemented. The cost effectiveness of training programs and dynamic eco-driving programs is also not known.
Implementation Concerns: There are no significant barriers to implementing eco-driving campaigns, training programs, and technology programs given that eco-driving is voluntary and campaigns can be low-cost. However, persuading people to eco-drive and therefore to achieve the outcomes of these programs may be more difficult.
Small changes in driving behavior, collectively called 'eco-driving,' can improve fuel economy and reduce greenhouse gas emissions. Eco-driving on the road includes gentler braking and acceleration, slower driving, avoiding idling, driving in the highest gear, and using automated toll passes.
There are three related approaches to encouraging eco-driving that can be used individually or in concert:
The relative effectiveness of these techniques is discussed in the 'GHG Effects' subsection below.
State and local transportation or other agencies and public-interest organizations may conduct eco-driving education and training campaigns independently or as part of traditional driver education programs. They may also provide incentives to install dynamic eco-driving sensors on vehicles. Private driver training programs have begun to include eco-driving in their course offerings, and industries that rely on heavy-duty vehicles in particular have sought to use eco-driving training to improve driving performance and reduce costs.
Eco-driving campaigns and programs can potentially target all drivers.
There is some quantitative research on training programs and dynamic eco-driving, mostly from Europe and involving heavy-duty vehicles, and there is general consensus about the directional effects when individuals adopt eco-driving. However, there is little quantitative research on eco-driving campaigns, in part because it is very difficult to measure such programs' effects.
According to the U.S. Department of Energy, eco-driving techniques such as driving sensibly, observing speed limits and removing excess weight, have the potential to improve a personal vehicle's fuel economy by between 5% and 33%. Other sources, which may consider a different set of eco-driving techniques, report a 10% improvement (Barkenbus, in press).
Research on eco-driving training programs (where drivers learn and practice techniques on a driving course) and on eco-driving information technologies (in-vehicle or on-road) collectively suggest an improvement ranging from 5%-20%, with many studies reporting approximately 10%.
A review of the short- and long-term effects of eco-driver training programs in several countries suggests that, immediately after training, fuel economy from better driving styles can improve by 5-15%. In the midterm (approximately three years), fuel economy is approximately 5% better if no additional training is provided, and 10% if further training is provided (Workshop on EcoDriving, n.d.). This is generally consistent with results of the US Department of Transportation's eco-driving efforts of the 1970s (Greene, 1986). However, it is important to note that fuel prices are much higher in many parts of the world, notably Europe, than in the US. Thus, there may be less incentive in the U.S. to adopt eco-driving practices, and the findings from foreign studies may not be indicative of potential results in the U.S.
Research on the effects of dynamic eco-driving devices and technology is still emerging and conclusions are less certain. Driving simulator experiments and vehicle trials of an in-vehicle real-time eco-driving device suggested 16% and 11% reductions in fuel consumption, respectively, in comparison to driving without such a device (van der Voort, Dougherty, and van Maarseveena, 2001). Simulations of an on-road eco-driving system that encourages drivers to drive at more efficient speed suggested 25% reduction in CO2 emissions for the entire traffic stream in highly congested traffic, if 20% of drivers adopt the suggested speed (Barth and Boriboonsomsin, 2009). There are few real-world implementations of these devices. Pilot projects in Denver, CO and in the UK suggest 10% reduction in fuel consumption (Enviance, 2009; Greenroad, 2009). One pilot study in Southern California of an on-board eco-driving device that provided instantaneous fuel economy feedback showed that the city average fuel economy improved by 6% while highway economy improved by 1%. The study further found that participants are willing to adopt eco-driving practices, particularly at higher gas prices.
To compute effects on greenhouse gas emissions, let us assume as the data suggests that these strategies improve a driver's driving habits such that a 10% improvement in fuel economy is achieved. Then, using data on average fuel economy and the number of vehicle miles traveled per vehicle (as a proxy for the number of vehicle miles traveled per driver), one can approximate the CO2 emissions reduced as a result of eco-driving:
The effects of eco-driving education campaigns are much less certain because of difficulties in measuring changes in driving behavior and in attributing them to the effects of the campaign. Nevertheless, a long-running and aggressive national eco-driving campaign the Netherlands, with a total population of approximately 16.4 million people, 10 million licensed drivers, and 87 million VMT (Institute for Road Safety Research, n.d.), has saved approximately 0.3 MMT of CO2 annually. These reductions are increasing as more people are exposed to the program (Evaluation Dutch national ecodriving programme Het Nieuwe Rijden 2007, n.d.).
In theory, eco-driving campaigns (e.g., formal public education and outreach on the nature and benefits of eco-driving) and programs may be among the more cost-effective ways to address GHG emissions (Barkenbus, n.d.), although costs will vary widely from program to program. In The Netherlands, the Dutch education program reported a program cost of $14 per metric ton of CO2 (Wilbers, Wismans, and Jansen, 2004). The costs associated with training-only or dynamic eco-driving systems are not currently known.
There are uncertainties in the long-term effects of eco-driving training and also the extent to which campaigns can reach the public and alter behavior. There is also uncertainty and variation in the cost of campaigns.
Costs to transportation agencies from undertaking eco-driving programs depend on the extent of campaign activities they undertake. Sources of cost include signage and postings, employee salaries, advertising costs, and training systems and technologies.
There are no specific agency implementation concerns associated with eco-driving education and training programs. However, agencies' eco-driving programs may be more effective if they are implemented in cooperation with automobile associations, whose members number in the millions.
The social acceptability of such programs is likely to be high given that they are voluntary. Expenditures by individuals, government, and industry for eco-driving education and training will likely be negligible at a national level. As eco-driving technology is as yet largely undeveloped, the costs to individuals, government and industry for such technology is unknown but conceivably would be implemented as part of larger transportation infrastructure projects and ongoing vehicle technology advancements.
Eco-Driving campaigns are more common in the EU than in the US. EU programs exist in The Netherlands, Sweden, Portugal, and the UK. In the U.S., the Eco-Driving USA campaign is national and endorsed by many state governors, but it is not clear that any state or region has undertaken its own campaign. Some higher-end vehicles also already provide instantaneous fuel economy feedback.
In the longer term, eco-driving education and training programs should be undertaken and/or studied in the US to provide more information on the effects of such programs. There may also be value in conducting long-term studies of the impact of in-vehicle eco-driving systems.
Barkenbus, J.N. (in press). Eco-driving: An overlooked climate change initiative. Energy Policy. Available online 28 October 2009 at http://www.sciencedirect.com/science/article/pii/S0301421509007484.
Barth, M., and Boriboonsomsin, K. (2009). Energy and emissions impacts of a freeway-based dynamic eco-driving system, Transportation Research Part D, pp. 400-410.
EcoDrivingUSA (n.d.). The Ecodriver's manual: A guide to increasing your mileage and reducing your carbon footprint [brochure]. Available online at http://puff.lbl.gov/transportation/transportation/pdf/ecodriving-manual.pdf.
Enviance. (2009, January 27). Denver's driving change program reduces vehicular CO2 emissions [press release]. Available online at http://www.enviance.com/about-enviance/PressReleaseView.aspx?id=53.
Evaluation Dutch national ecodriving programme Het Nieuwe Rijden 2007 (n.d.). [Brochure]. Available at http://fiabrussels.com/download/projects/ecodriven/factsheet_evaluation_hnr_2007_en2.pdf.
Greene, D.L. (1986). Driver energy conservation awareness training: review and recommendations for a national program. Report from the Oak Ridge National Laboratory (No. ORNL/TM-9897).
Greenroad. (2009). Datashred's fleet goes green. Available online at: http://greenroad.com/site2011/success/datashreds-fleet-goes-green/
Van der voort, M., Dougherty, M.S., and Van Maarseveee, M. (2001). A prototype fuel-efficiency support tool, Transportation Research Part C, 279-296.
Workshop on Eco-Driving: Findings and Messages for Policymakers (n.d.). [Report from workshop, Paris, November 22-23, 2007]. Available online at: http://www.internationaltransportforum.org/Proceedings/ecodriving/EcoConclus.pdf.
Policy: Truck-stop electrification (TSE) and auxiliary power unit (APU) technologies provide long-haul truckers with heating, cooling, and other amenities at truck stops without requiring vehicle idling, thereby reducing GHG emissions. Agencies can encourage the adoption of TSE and APUs through funding and partnerships with private companies.
Emissions Benefits and Costs: Using TSEs or APUs instead of idling reduces GHG emissions by 60% or more. The aggregate effects depend on the number of hours of idling that are actually offset. Without considering revenue generated from providing power services, the cost is $20-$60/MTCO2 for TSE systems, depending on usage rates and system lifespan. The cost of APUs, on the other hand, can be fully recovered by operators in 2-3 years from lower fuel and maintenance costs.
Implementation Concerns: TSE offers business opportunities to truck stop operators and TSE and APUs both reduce costs for fleet operators. Nevertheless, acquiring financing for APUs and other technologies may pose a barrier for fleet operators. The cost to public agencies depends on the level of support they choose to offer.
Federal safety regulations require that truckers must rest ten hours for every eleven hours of consecutive driving (Federal Motor Carrier Safety Administration, n.d.). In complying with these regulations, long-haul truck drivers idle their engines 5-8 hours a day to power air conditioning, heat, and other on-board appliances, and to keep engines and fuels warm in cold weather. Trucks typically consume 0.8 gallons of diesel fuel per hour of idling, using between 900 and 1,400 gallons of fuel each year per truck. This extensive idling results in significant GHG emissions.
Truck stop electrification (TSE) technologies reduce extended idling at truck stops by providing electricity-powered heating, cooling, and other amenities. On-board TSE solutions require some vehicle modification and use batteries on the truck to power appliances, and they offer outlets at truck stops to recharge these batteries. Off-board TSE solutions (which require no vehicle modifications) provide complete heating and air conditioning infrastructure via an overhead unit and a hose connection. In addition to basic heating and cooling, off-board systems can offer Internet access, movies, and satellite programming (California Energy Commission, 2006). These options generate revenue for truck stop operators and simultaneously are less costly to truck operators than idling because of lower electricity costs (relative to diesel fuel costs for the same energy) and lower maintenance costs that would be incurred because of the negative effects of idling on the engine.
Other anti-idling technologies include auxiliary power units (APUs), which typically provide heat and electricity through small, externally mounted, diesel-powered internal combustion engines, and cooling through electric air conditioners or the vehicle's air conditioning system. APUs are proven, commercially available technologies and are efficient because the engine is appropriately sized to meet heating and electricity needs (Argonne National Laboratory, 2000).
State DOTs, MPOs, and other agencies (e.g., state environmental protection or energy agencies) can provide funding and strategic planning support to truck stop operators and truck operators to implement on-board and off-board TSE and APUs. Such projects are frequently undertaken as public-private partnerships and agencies or operators may seek funding and support from other (e.g., federal) sources. The EPA SmartWay program offers guidance, financial assistance, and other resources to freight operators for using such technologies.
TSE and APU projects are targeted at truck stop operators, long-haul truckers, and fleet operators. By providing funding to truck stop operators, these efforts seek first to enable and encourage truck stop operators to install TSE facilities. Second, assuming TSE facilities can offer amenities at lower costs to truckers than burning diesel fuel, these efforts aim to enable and encourage truckers to use TSE facilities. TSE and APU projects can also enable fleet operators to install on-board TSE or APU equipment.
Public agencies have been successful in enabling TSE projects through financial and strategic planning support. However, it is not possible to generalize and quantify the effects of funding opportunities on operators' decisions to undertake TSE projects, since these efforts tend to be public-private partnerships and the decision to implement TSE depends on a wide range of factors. These factors include the total cost of implementation, the level of funding available from public sources, the demand from truckers and fleet operators, and the anticipated revenue to operators.
Nevertheless, theoretical and practical studies do provide estimates of the reductions in emissions from using TSE or APUs instead of idling. There is some variation in these estimates at all levels (hourly, yearly, per-space, and per-site) due to different assumptions about and variations in power requirements, fuel efficiency, facility usage. The literature also includes estimates of system implementation costs and costs per metric ton of GHG reduction. Again, there are some variations depending on the type of technology used and assumptions about technology lifespan. Many TSE projects in particular are less than five years old, so actual long-term costs and benefits are unknown.
As noted, long-haul truck drivers idle their engines five to eight hours a day to power air conditioning, heat, and other on-board appliances, and to keep engines and fuels warm in cold weather. Trucks typically consume 0.8 gallons of diesel fuel per hour of idling. Given that one gallon of diesel fuel emits 22.4 lbs of CO2, then an idling truck would emit approximately 18 lbs of CO2 per hour or 90-145 lbs of CO2 per day.
In contrast, if an hour of off-board TSE use draws 7.5kW (Center for Clean Air Policy, 2007), and given an average emission of 1.33 lb of CO2 per kWh from the electricity grid (EPA, 2008), then a truck that uses a TSE spot would produce approximately 10 lbs of CO2 per hour, or approximately 60-80 lbs of CO2 per day.
Other reports use different estimates of both the fuel consumed for idling and the equivalent electricity requirements:
In sum, this amounts to approximate a 60% or more decrease in GHG emissions from idling to TSE or APU use.
The absolute effect on GHG emissions from an individual APU or TSE spot depends on the number of hours of idling that have been offset. Because APUs are installed in individual vehicles, variations in use are largely a function of travel patterns and climate. TSEs on the other hand, are designed to serve many vehicles, and their use depends additionally on their location, number, and distribution of nearby TSE facilities, and other factors. Reports from TSE proposals and projects illustrate some of the benefits observed or anticipated:
A 2000 report found that if market penetration of TSE or APUs was 100%, 7 to 8 MMTCO2 could be saved annually (Argonne National Laboratories, 2000).
On-board TSE spots cost less to implement at the truck stop but require equipment installation in trucks. The study of New York's on-board TSE (Antares Group, Inc., 2005) estimated that the costs to install one on-board TSE spot ranges from $3,000 to $6,000 and that 363 metric tons of CO2 were reduced in 13 months. Continuing with our assumption of a 10-year lifespan and assuming the same utilization rates, the cost per metric ton of CO2 ranges from $15 to $30 per metric ton. Note that for truck stop operators, this cost is likely to be offset by revenues from vehicle operators who use the TSE. This cost figure does not include the cost for on-board equipment, which ranges from $180 to over $3000, but which can be recovered by operators in a few years from fuel savings (Argonne National Laboratories, 2000).
Operators can recover the $6,000 to $7,000 cost of APUs in less than two years from fuel and engine maintenance savings (Argonne National Laboratories, 2000).
There is significant uncertainty in the actual rates of use of TSE spots and the change in use over time. Variations in fleet efficiency, climate, CO2 emissions from electricity generation, and lifetime costs of TSE further contribute to uncertainty in both the costs and level of reductions.
TSE and APU project costs stem from planning, technology implementation, outreach, and evaluation activities. The cost to agencies depends entirely on the nature and size of support they offer to operators. For example, the state of Pennsylvania contributed $900,000 for three TSE sites, while the EPA contributed $100,000 and the private partner, IdleAire, contributed $2.5M (Shulman, 2008).
TSE projects can involve partnerships between state and local transportation agencies, other state and local organizations, federal agencies, and private companies, and such complex partnerships present collaborative challenges. There are no apparent significant inter-agency or institutional concerns associated with APU use at this time.
TSE facilities are socially viable because of the business opportunities they provide to truck stop operators and TSE technology providers, and, as with APUs, because of the cost-saving opportunities they provide to truck operators.
The installation of both on-board and off-board TSE facilities requires substantial initial investment from truck stop operators and other firms. On-board TSE systems also require investments from truck operators. However, public agencies can provide support and incentives to reduce these costs, and the success of such initiatives in generating TSE projects suggests that this initial hurdle can be overcome.
Despite the benefits that TSE offers to both truck stop operators and fleet operators, the development of TSE spots has been uneven. In 2009, when this work began, there were 138 TSE locations around the U.S. As of August 2010, only 12 locations remained because the company that owned nearly all TSE locations had filed for bankruptcy. The specific causes of this are not known, though the economic downturn in recent years may have played a role (e.g., in limiting investments in new infrastructure or technology).
A searchable map of TSE sites can be found at http://www.afdc.energy.gov/afdc/locator/tse/. There has been a significant decline in the number of TSE locations, from approximately 140 at the end of 2009 to only 12 in August 2010.
The data on TSE projects is distributed in individual project proposals and reports. While this section cites data from a few of these, a broader survey of projects would provide more comprehensive data and insights into the costs and benefits of TSE.
Antares Group, Inc. (2005). Fleet Demonstration of Shorepower Truck Electrified Parking On The I-87 Northway [Final report for NYSERDA].
California Energy Commission (2006, June). Truck Stop Electrification (Publication No. CEC-600-2006-001-FS). Retrieved from http://www.energy.ca.gov/2006publications/CEC-600-2006-001/CEC-600-2006-001-FS.PDF.
Center for Clean Air Policy (2007). CCAP Transportation Emissions Guidebook [online], Washington, DC. Accessed on January 6, 2010 from http://www.ccap.org/safe/guidebook/guide_complete.html.
Cook, W. (n.d.). Georgia Truck Stop Electrification (TSE) and Green Corridors [Proposal from the Georgia Environmental Protection Division for American Recovery and Reinvestment Act Funding] Retrieved from http://www.gaepd.org/Files_PDF/arra/ARRA_truck_work_plan.pdf.
Downing, K. (2005, Winter). Saving Energy, The Environment, And A Good Night's Rest-Oregon's Approach To Truck Idling. The Journal of the Environmental Council of the States, 17-19. Retrieved from http://www.ecos.org/files/1411_file_Winter_2005_ECOStates.pdf.
Environmental Protection Agency (2004, January). Guidance for Quantifying and Using Long Duration Truck Idling Emission Reductions in State Implementation Plans and Transportation Conformity (Publication No. EPA420-B-04-001). Retrieved from http://www.epa.gov/smartway/documents/publications/420b04001.pdf.
Environmental Protection Agency (2008, December). eGRID2007 Version 1.1 Year 2005 Summary Tables. Accessed on January 6, 2010 from http://www.epa.gov/cleanenergy/documents/egridzips/eGRID2007V1_1_year05_SummaryTables.pdf.
Environmental Protection Agency (n.d.). Technologies, Strategies and Policies: Idling Reduction. Accessed on March 6, 2013, from http://www.epa.gov/smartway/forpartners/technology.htm.
Federal Motor Carrier Safety Administration (n.d.). Interstate Truck Driver's Guide to Hours of Service. Accessed on January 6, 2010 from http://www.fmcsa.dot.gov/regulations/hours-service/interstate-truck-drivers-guide-hours-service.
Gaines, L. and Hartman, C. (2009). Energy Use and Emissions Comparison of Idling Reduction Options for Heavy-Duty Diesel Trucks. In Proceedings of the Annual Meeting of the Transportation Research Board, Washington, D.C., Paper No. 09-3395. Retrieved from http://www.transportation.anl.gov/pdfs/EE/582.pdf
Lim, H. (2002, October). Study of exhaust emissions from idling heavy-duty diesel trucks and commercially available idle-reducing devices. Environmental Protection Agency. (Publication No. EPA420-R-02-025). Retrieved from http://www.epa.gov/smartway/documents/publications/epaidlingtesting.pdf.
Perrot, T., Dario, J., Kim, J., and Hagan, C. (2004, September) Installation and Economics of a Shorepower Facility for Long-Haul Trucks [Report for NYSERDA]. Retrieved from http://www.nyserda.ny.gov/en/Publications/Research-and-Development/~/media/Files/Publications/Research/Transportation/shorepower.ashx (inactive 12/13)
Shulman, A. (2008). Final Report Award # XA - 83207301-0 [Final report from the Pennsylvania Department of Environmental Protection to the US Environmental Protection Agency]. Retrieved from http://www.epa.gov/smartway/documents/publications/adeq-pennsylvania-final-report.pdf.
Stodolsky, F., Gaines, L., and Vyas, A. (2000). Analysis Of Technology Options To Reduce The Fuel Consumption Of Idling Trucks (Technical Report ANL/ESD-43). Retrieved from Argonne National Laboratory Website: http://www.transportation.anl.gov/pdfs/TA/15.pdf.
U.S. Department of Energy, (2009). Energy Efficiency and Renewable Energy, Truck Stop Electrification for Heavy-Duty Trucks. http://www.afdc.energy.gov/conserve/idle_reduction_electrification.html.
Policy: Idling in traffic may be necessary for safety and system efficiency, but idling to warm the engine and idling while waiting for non-traffic reasons is generally unnecessary. Anti-idling regulations and campaigns seek to require or encourage drivers to reduce vehicle idling, thereby reducing greenhouse gas emissions.
Emissions Benefits and Costs: While the effects of idling are understood, it is not known how regulations and campaigns affect drivers' idling behaviors. Additionally, costs of anti-idling regulations are largely unknown.
Implementation Concerns: The public generally supports voluntary anti-idling campaigns, and opposition to regulations can presumably be overcome given that anti-idling regulations are widespread.
Drivers of passenger vehicles and commercial trucks (excluding long-haul freight) typically idle their vehicles in three situations: while waiting in traffic (e.g., at traffic lights), while waiting for non-traffic reasons (e.g., waiting for other passengers or while making deliveries), and to warm the engine (Carrico, 2009). While idling in traffic may be necessary for safety and system efficiency, idling to warm the engine (excluding rest-periods for long-haul trucking) and idling while waiting for non-traffic reasons is generally unnecessary. It also results in wasted fuel, increases conventional air pollutants, and emits greenhouse gases.
In an effort to curb conventional air pollutant emissions in particular, many state and local governments have implemented anti-idling laws that limit idling times to various extents depending on the class of vehicle, zoning, time of day, and environmental conditions. Transportation agencies and public interest organizations have also undertaken anti-idling campaigns, separately or in conjunction with regulations, to educate drivers about the effects of idling. Despite the traditional focus on conventional pollutants, these regulations and campaigns simultaneously reduce greenhouse gas emissions.
State and local governments are responsible for passing regulations that limit idling. The role of transportation agencies in implementing these policies is to provide appropriate signage. Law enforcement or parking/traffic enforcement agencies would enforce the regulations. Transportation agencies and public interest organizations may also undertake anti-idling education campaigns.
Anti-idling regulations and campaigns can potentially affect all motorists and all vehicles. Some may be targeted at specific groups or areas, such as anti-idling regulations for school buses.
Several studies have sought to quantify the extent of unnecessary idling of private and commercial vehicles. Light-duty vehicle idling emits approximately 1.4g of CO2 per second (Frey et al., 2003), or 84 grams of CO2 per minute. A 2007 survey of drivers by Carrico et al. (2009) suggested that the average passenger-car driver unnecessarily idles their vehicle for approximately 6 minutes every day, emitting 1.1 lbs of CO2. This results in approximately 16 MMT of CO2 annually in the U.S. with unnecessary engine warming and waiting.
A study by the Argonne National Laboratory (Gaines, Vyas, and Anderson, 2006) estimated that commercial vehicles emit between 40 and 170 grams of CO2 per minute and that drivers of these vehicles idle from half an hour to two hours a day, depending on the type of vehicle and commercial activity. This translates to unnecessary emissions of between of over 20 lbs of CO2 per day for certain vehicles. In sum, unnecessary commercial truck idling can consume 2.5 billion gallons of gas and emit approximately 23 MMT of CO2 annually.
Although anti-idling regulations and campaigns have been implemented in various ways in many places to counteract such idling, there is little quantifiable data on the extent to which they actually change driver behavior, either on a per-person or on an aggregate level. The effectiveness of legislation depends in part on how the legislation itself is structured (schedule of penalties, exemptions to rules, etc.), how it is made known to the public (e.g., extent of signage and education campaigns), and how it is enforced (complaints from the public, enforcement blitzes, ongoing proactive enforcement). Not only is there variability in the regulations and their implementation (and hence their effects), there is also little evidence and data available about the effects of particular regulation. The reasons for this include:
Many of these informational and data collection challenges are common to anti-idling campaigns, but some campaigns have made informal efforts to gather direct and indirect data for short periods of time. Some campaigns reported that between 50% and up to 95% of idling drivers approached by campaigners complied with requests to limit idling and/or expressed a commitment to reduce idling (Kings County Economic Development Agency, n.d.; Freedman, 2009), but it is unclear if and how that translates into regular changes in behavior. Most campaigns that observed idling behavior reported inconclusive and mixed results (e.g., because of confounding effects of different weather conditions during data collection times) (Kings County Economic Development Agency, n.d.; Transport Canada, 2004).
Private companies and organizations may also undertake anti-idling campaigns and target a particular group of drivers (bus drivers, police fleet, etc.). A survey of several anti-idling training efforts conducted by various companies for their delivery truckers decreased emissions by 60 to 160 lbs of CO2 per vehicle per week in the two weeks following training (Engine Idling - Costs You Money and Gets You Nowhere, n.d.), but it is unclear how these campaigns have affected long-term behavior.
Costs to the public largely depend on the extent of the education and campaign activities, and enforcement activities in the case of regulations. The nature of these efforts and their costs vary. Given that both the effects and costs are unknown and highly variable, it is not feasible to calculate the cost per metric ton.
There are significant uncertainties in the effect of campaigns and regulations on behavior, particularly given variation in policy structure and enforcement efforts (for regulations), and given that the effects are confounded with other influencing factors such as the cost of gas, anti-idling campaigns. There are also uncertainties and high variability associated with cost.
EPA's MOVES model can be used to estimate changes in emissions.
Costs to transportation agencies for anti-idling regulations vary and depend in part on the approach they take for education and enforcement. Costs include signage and postings associated with the regulation, training of enforcement personnel, hiring new personnel, and creating a hotline for receiving public complaints. In some cases, policymakers may not anticipate any new costs associated with enforcement (Pennsylvania Department of Environmental Protection Environmental Quality Board, 2008).
Costs for campaigns largely depend on the extent of campaign activities, but are not likely to be expensive overall. The literature from several locations showed costs ranging from $4,000 for signage (Kings County Economic Development Agency, n.d.) to $130,000 for a more extensive media campaign (Transport Canada, 2004), but this is by no means an upper bound. This $130,000 cost included staff resources of $50,000 for one year, production costs of $30,000 and $50,000 for evaluation. Various organizations may undertake these campaigns and bear the costs.
There are no specific agency concerns associated with anti-idling regulations or campaigns, though their effectiveness depends on how and how well they are enforced. For example, a recent report found that New York City police rarely ticket for idling, despite regulations (New York City law cracks down on idling cars, 2009). In Canada, most municipalities with by-laws have taken a limited approach to enforcement. Typically, communities do some public outreach and education on the issue of vehicle idling prior to passing the by-law as well as afterwards. Enforcement has mainly involved reacting to complaints from the public by speaking to offenders, providing information on the by-law and the reasons for it, and asking for voluntary compliance. Few communities issue tickets and summonses, and those that do usually limit this activity to short sporadic campaigns rather than undertaking ongoing enforcement (Clean Air Partnership, 2005).
Surveys conducted by campaigns suggest that the public supports voluntary anti-idling efforts for air quality purposes in particular, and acceptability for these campaigns is likely to be high. The literature does not discuss public support for or opposition to anti-idling regulations, but, given that just over half of all states have anti-idling regulations, one can infer that they are socially acceptable. Nevertheless, support likely varies in part on the environmental and health concerns of the public, who the regulation targets, and how.
As of 2006, approximately 30 states had some type of anti-idling regulation, either at the state level or in particular cities or counties. EPA provides a list at: http://www.epa.gov/smartway/documents/420b06004.pdf. Many regions have undertaken anti-idling campaigns at some point or another, but there is no comprehensive database or list of such efforts.
Anti-idling campaigns and regulations are rarely evaluated, so further research would be helpful in designing and executing evaluations. In the near term, additional information about anti-idling regulations may be gleaned from individual states' planning documents, particularly related to costs of education campaigns and enforcement and related to the extent to which states have monitored the effects of such rule making (at minimum, in terms of citations, and more broadly, in terms of other behavioral effects).