and their penetration into the market. As a result, the committee developed a range of estimates for use in this study.

For vehicle technologies, the committee used two sets of assumptions for cost and performance: (1) midrange estimates that are ambitious but reasonable goals in the committee’s assessment; and (2) optimistic estimates which are potentially attainable, but will require greater successes in R&D and vehicle design. Both sets are predicated on the assumption that strong and effective policies are implemented to continually increase requirements or incentives (at least through 2050) to ensure that technology gains are focused on reducing petroleum use and GHG emissions.

Alternate assumptions were also developed for fuels to aid in assessing uncertainties. For example, several production processes were considered for hydrogen and biofuels, and both conventional generation and low-GHG-emission scenarios were considered for electricity.

In its assessment of the current state of LDV fuel and vehicle technologies and their projections to 2050, the committee built on earlier studies by the NRC and other organizations as listed in Appendix D. In addition, the committee examined publicly available literature and gathered information through presentations at open meetings. Insofar as possible, the committee assessed the fuels and vehicle technologies on a consistent and integrated basis. Its approach accounted for important effects, including the following:

  • Potential projected performance characteristics of specific vehicles and fuel systems,
  • Costs of the technologies including economies of scale and learning,
  • Technical readiness,
  • Barriers to implementation,
  • Resource demands, and
  • Time and capital investments required to build new fuel and vehicle technology infrastructure.

The committee also considered crosscutting technologies. For vehicles, these included weight reduction and improvements in rolling and aerodynamic resistance; for fuels, carbon capture and storage (CCS). In addition, the analysis took into account sector-wide effects such as consumer preferences and potential changes in vehicle miles traveled (VMT).

The committee then analyzed the impact of the various options. Vehicle performance was projected using a model developed by the committee and its consultants that estimates the impact of reductions in energy losses. Costs were projected for expected technologies relative to a 2010 base vehicle. These analyses and the results are described in Chapter 2. Efficiencies, costs, and performance characteristics were analyzed consistently for all vehicle classes and powertrain options, with the partial exception of travel range. Fuel technologies were analyzed individually using consistent assumptions and cost data across all fuels as shown in Chapter 3.

The vehicle and fuel data were then used to forecast future LDV fleet energy use and GHG emissions using two models described in Chapter 5. VISION was used to assess technology pathways to on-road fleets in 2050 based on inputs from the vehicle and fuel analyses developed in Chapters 2 and 3. LAVE-Trans—a spreadsheet model that takes into account consumer choices (discussed in Chapter 4), which are affected by vehicle and fuel characteristics, costs, and policy incentives—was used to compare different policy-driven scenarios. These scenarios are not intended as predictions of the future but rather to evaluate the relative potential impact on future petroleum use and GHG emissions of technological success and policy options, and the resulting costs and benefits.

By their nature, all models are simplifications and approximations of the real world and will always be constrained by computational limitations, assumptions, and knowledge gaps. All the models’ estimations depend critically on assumptions about technologies, economics, and policies and should best be viewed as tools to help inform decisions rather than as machines to generate truth or make decisions. The LAVE-Trans model in particular uses the committee’s assumptions about technological progress over several decades, how people behave, what things cost and what they are worth. It predicts, in a formal relational structure, how the vehicle fleet composition would then evolve and what the impact would be on petroleum use and GHG emissions. Some of the LAVE-Trans results were surprising, but the committee examined them and the model, fixed mistakes, and revised assumptions, until it was satisfied with the robustness of the outputs that resulted from the inputs. Even so, there is considerable uncertainty about the results presented here. Input assumptions are estimates that may prove inaccurate. The model’s handling of market relationships may be simplistic. Nevertheless, as described in Chapter 5, the results are robust for a variety of inputs, and, as long as the results are used with an understanding of the models’ strengths and weaknesses, they should be valuable assets in thinking about potential policy actions.

The major results of the committee’s work are listed below; additional findings and policy options are embedded in individual chapters of the report.

MEETING THE GOALS OF REDUCING PETROLEUM USE AND GHG EMISSIONS

Finding: It will be very difficult for the nation to meet the goal of a 50 percent reduction in annual LDV petroleum use by 2030 relative to 2005, but with additional policies, it might achieve a 40 percent reduction.

Future petroleum use is likely to decline as more efficient vehicles enter the market in response to the Corporate Average Fuel Economy (CAFE) standards and GHG requirements for 2025, more than compensating for the increased number



The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement