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FIGURE D.19 Simulated total fuel use (a) and GHG emissions (b) for the US LDV fleet in 2050.

The most prominent conclusion is that due to expected improvements, this report finds that advanced technologies are expected to have significant market penetration. In the short term (to 2015), HEVs and PHEVs offer significant fuel displacement with an acceptable additional cost; however, BEVs are likely to remain expensive and range-limited, hindering their initial market penetration. In the medium term (to 2030), hybridized hydrogen-fueled ICE-powered vehicles would offer significant fuel improvements and could potentially act as a bridging technology to establish the infrastructure required for fuel cell vehicles. In the long term (to 2045), fuel cell vehicles demonstrate the highest fuel displacement potential at a competitive cost.

D.16 THE EFFECT OF UNCERTAINTY ON U.S. TRANSPORT-RELATED GHG EMISSIONS AND FUEL CONSUMPTION OUT TO 2050 (BASTANI ET AL., 2012)

Bastani, Heywood, and Hope employed a deterministic model to shed light on the likely future of LDVs in 2050. The scenarios given by the model are based around the statistical uncertainty of key parameters driving future deployment, such as vehicle technology performance, fuel performance and GHG emissions, alternative fuel availability, and demand and market deployment of new technologies and fuels. Tens of thousands of “futures” are considered via Monte Carlo simulation using parameter values obtained via a thorough review of the literature.

Figure D.19 shows simulated fuel use and GHG emissions for the simulated scenarios. While these values are meant to represent likely scenarios for future LDV pathways, which is inconsistent with the committee’s task, they do show both the high potential for significant reductions in oil use and GHG emissions from efficiency improvements as well the high degree of uncertainty in any such modeling endeavor.

Figure D.20 outlines the most significant parameters affecting the future GHG emissions of the light duty fleet, according to the statistically modeled scenarios. The most significant contribution is the uncertainty in future vehicle sales, as should be obvious since the number of vehicles is directly proportional to the GHG emissions of the fleet. This is followed by the percentage of cellulosic ethanol in future gasoline, which has a strong impact on the well-to-wheel emissions of the fleet. There is a comparable strong dependence on the emphasis on reducing fuel consumption (ERFC). The ERFC represents the relative importance of fuel consumption as engines are improved—for example, in the 1990s the ERFC was near zero, while engine improvements were devoted primarily to increasing horsepower. Because the future fleet is dominated by spark-ignited ICE vehicles, the relative fuel



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