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Life Cycle Greenhouse Gas Analysis of Multiple Vehicle Fuel Pathways in China

Authors: Tianduo Peng; Sheng Zhou; Zhiyi Yuan; Xunmin Ou;

Life Cycle Greenhouse Gas Analysis of Multiple Vehicle Fuel Pathways in China

Abstract

The Tsinghua University Life Cycle Analysis Model (TLCAM) is applied to calculate the life cycle fossil energy consumption and greenhouse gas (GHG) emissions for more than 20 vehicle fuel pathways in China. In addition to conventional gasoline and diesel, these include coal- and gas-based vehicle fuels, and electric vehicle (EV) pathways. The results indicate the following. (1) China’s current dependence on coal and relative low-efficiency processes limits the potential for most alternative fuel pathways to decrease energy consumption and emissions; (2) Future low-carbon electricity pathways offer more obvious advantages, with coal-based pathways needing to adopt carbon dioxide capture and storage technology to compete; (3) A well-to-wheels analysis of the fossil energy consumption of vehicles fueled by compressed natural gas and liquefied natural gas (LNG) showed that they are comparable to conventional gasoline vehicles. However, importing rather than domestically producing LNG for vehicle use can decrease domestic GHG emissions by 35% and 31% compared with those of conventional gasoline and diesel vehicles, respectively; (4) The manufacturing and recovery of battery and vehicle in the EV analysis has significant impact on the overall ability of EVs to decrease fossil energy consumption and GHG emissions from ICEVs.

Related Organizations
Keywords

carbon footprint, Environmental effects of industries and plants, TJ807-830, life cycle analysis, vehicle fuel, TD194-195, Renewable energy sources, Environmental sciences, greenhouse gas, energy consumption, life cycle analysis; carbon footprint; vehicle fuel; energy consumption; greenhouse gas, GE1-350

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
43
Top 10%
Top 10%
Top 10%
gold