Optimizing U.S. Mitigation Strategies for the Light-Duty Transportation Sector: What We Learn from a Bottom-Up Model
Few integrated analysis models examine significant U.S. transportation greenhouse gas emission reductions within an integrated energy system. Our analysis, using a bottom-up MARKet ALocation (MARKAL) model, found that stringent system-wide CO2 reduction targets will be required to achieve significan...
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Veröffentlicht in: | Environmental science & technology 2008-11, Vol.42 (22), p.8202-8210 |
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creator | Yeh, Sonia Farrell, Alex Plevin, Richard Sanstad, Alan Weyant, John |
description | Few integrated analysis models examine significant U.S. transportation greenhouse gas emission reductions within an integrated energy system. Our analysis, using a bottom-up MARKet ALocation (MARKAL) model, found that stringent system-wide CO2 reduction targets will be required to achieve significant CO2 reductions from the transportation sector. Mitigating transportation emission reductions can result in significant changes in personal vehicle technologies, increases in vehicle fuel efficiency, and decreases in overall transportation fuel use. We analyze policy-oriented mitigation strategies and suggest that mitigation policies should be informed by the transitional nature of technology adoptions and the interactions between the mitigation strategies, and the robustness of mitigation strategies to long-term reduction goals, input assumptions, and policy and social factors. More research is needed to help identify robust policies that will achieve the best outcome in the face of uncertainties. |
doi_str_mv | 10.1021/es8005805 |
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subjects | Air Pollutants Analysis Applied sciences Carbon dioxide Carbon Dioxide - chemistry Emissions Environmental policy Environmental Restoration and Remediation Exact sciences and technology Greenhouse Effect Greenhouse gases Humans Models, Theoretical Pollution Transportation Transportation industry Vehicle Emissions Vehicles Waste Management |
title | Optimizing U.S. Mitigation Strategies for the Light-Duty Transportation Sector: What We Learn from a Bottom-Up Model |
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