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Pressure has been increasing to raise the corporate average fuel economy (CAFE) standard. Some researchers assert many benefits from increasing CAFE, from less dependence on imported petroleum to lower urban ozone. We find that fuel savings from increasing CAFE are subject to diminishing returns, with little or no effect on urban air pollution, and a less than proportional reduction in greenhouse gas emissions. Higher CAFE reduces safety, unless offsetting steps are taken. Should the public demand moderately higher fuel efficiency, the government should raise the CAFE standard and gasoline prices. Given current technology, substantial increases in CAFE have potential costs, and do not appear to offer significant benefits as contended.

Abstract Electric drive vehicle technologies are being considered as possible solutions to mitigate environmental problems and fossil fuels dependence. Several studies have used life cycle analysis technique, to assess energy use and CO 2 emissions, addressing fuels Well-to-Wheel life cycle or vehicle's materials Cradle-to-Grave. However, none has considered the required infrastructures for fuel supply. This study presents a methodology to evaluate energy use and CO 2 emissions from construction, maintenance and decommissioning of support infrastructures for electricity and fossil fuel supply of vehicles applied to Portugal case study. Using Global Warming Potential and Cumulative Energy Demand, three light-duty vehicle technologies were considered: Gasoline, Diesel and Electric. For fossil fuels, the extraction well, platform, refinery and refuelling stations were considered. For the Electric Vehicle, the Portuguese 2010 electric mix, grid and the foreseen charging point's network were studied. Obtained values were 0.6–1.5 gCO 2eq /km and 0.03–0.07 MJ eq /km for gasoline, 0.6–1.6 gCO 2eq /km and 0.02–0.06 MJ eq /km for diesel, 3.7–8.5 gCO 2eq /km and 0.06–0.17 MJ eq /km for EV. Monte Carlo technique was used for uncertainty analysis. We concluded that EV supply infrastructures are more carbon and energetic intensive. Contribution in overall vehicle LCA does not exceed 8%.

Abstract We present a computationally-efficient optimization model that finds the least-cost generation unit expansion, commitment, and dispatch plan to serve hourly electricity demand and ancillary service requirements. We apply the model to a case study based on data from the electricity market in Texas (ERCOT) to analyze the market and investment impacts of several incentive mechanisms that support variable renewable energy (VRE) investments and carbon emission reductions. In contrast to many previous studies, the model determines least-cost VRE investments under different cost and incentive assumptions rather than analyzing scenarios where VRE expansion is pre-determined. We find that electricity prices can vary significantly under different incentive mechanisms, even when comparable generation portfolios result. Therefore, the preferred incentive mechanism depends on stakeholder objectives as well as the prevailing electricity market framework. Our results indicate that a carbon tax is more system cost-efficient for reducing emissions, while production and investment tax credits are more system cost-efficient for increasing VRE investments. Similarly, incentive mechanisms that reduce electricity prices may increase the need for separate revenue sufficiency mechanisms (e.g. a capacity market) more than a policy that increases electricity prices. Moreover, the impacts on consumer payments are not always aligned with changes in system costs. Overall, the analysis illustrates the importance of considering electricity market impacts in assessing the economic efficiency of VRE and carbon incentive mechanisms.

Abstract This paper compares policies and programs in several European countries, Japan and the USA that could enhance the energy efficiency of office technology. Different programs are examined, including federal government programs. In some cases target values for power usage of office equipment have already been set through these federal government programs. Large customer procurement programs, industry involvement, with emphasis on voluntary labeling programs, and research projects are also examined. Procedures that provide energy consumption measurements of various types of equipment are important for providing information to emerging procurement programs. Two sets of proposed test procedures for testing energy consumption of copiers, fax machines and printers are examined and compared. The results provide information for emerging programs and provide a strong basis for a variety of further research and areas for cooperation.

Abstract China is currently the world's largest emitter of carbon dioxide (CO2). Vigorously developing new energy sources has become an important way to reduce CO2 emissions. Therefore, more and more scholars have studied effective ways to promote the development of new energy industry. However, most of the existing research use single-equation linear models or static models to study the driving forces of the new energy industry. This not only ignores the large number of dynamic relationships between economic variables, but also produces endogeneity problems. In order to overcome the shortcomings of existing research, this paper uses vector autoregressive model to study the new energy industry. The results show that energy consumption structure has a positive effect on the new energy industry in the short run, but the effect is limited in the long run. The impact of the agriculture industry is gradually narrowing over time due to the gradual reduction of crop acreage. However, the influence of economic growth is positive both in the short and long run. This is due to the gradual optimization of industrial structure. Technological progress produces a similar impact, owing to continued investment in research and development funding as well as research and development personnel.

Current optimizing climate-economy models use CO2 uptake functions that greatly underestimate both peak atmospheric CO2 concentrations and the time horizon of elevated CO2. As a result these models underestimate potential global warming damages. Here, a more realistic, but practical, carbon cycle parameterization is developed that can be incorporated within an optimizing climate-economy model framework. This method is utilized in conjunction with the DICE model (Nordhaus, 1994) to estimate optimal reductions in CO2 emissions. The results are shown to be extremely sensitive to the pore rate of time preference, rho. For rho=3% (Nordhaus' preferred value), our model predicts an optimal CO2 emission reduction of 13% by the year 2045, as compared to 11% in the original DICE model. But, for rho=0% the optimal emissions reduction rises to 79% in the year 2045 and to 97% by the year 2200. We argue that energy policy should be guided by the rho=0% results for both economic and ethical reasons. A steady-state analysis performed using the DICE model supports the argument that large fractional reductions in CO2 emissions should be undertaken.

Abstract Microgrids can provide an avenue for increasing the amount of distributed generation (DG) and delivery of electricity, where control is more dispersed and quality of service is locally tailored to end-use requirements, with applications from military bases to campuses to commercial office buildings. Many studies have been done to date on microgrid technology and operations, but fewer studies exist on demonstration programs and commercial microgrid development. As China prepares to launch the largest microgrid demonstration program in the world, we review progress made by demonstration programs across Europe, Asia, and the Americas as well as microgrid benefits and barriers. Through case studies, we highlight the difference in experience for microgrids developed under the auspices of a government-sponsored demonstration program versus those that were commercially developed. Lastly, we provide recommendations oriented towards creating a successful microgrid demonstration program.

Abstract Optimal timing of the introduction of the FBR is very sensitive to factors such as the availability of low-cost uranium, future energy demands and the possibility of the introduction of yet more advanced technology. To a lesser extent it is also sensitive to the relative capital costs of fast breeder and thermal nuclear plants. The relationship between R & D costs and the programme timing is also crucial in deciding optimisation.