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The Potential Impacts of Electric Vehicles on Urban Air Quality in Shanghai City

descriptionPublicationkeyboard_double_arrow_right Article , Journal 07 Jan 2021Publisher:MDPI AGJournal:Sustainability, volume 13, page 496 (eissn: 2071-1050,

Authors: Bicheng Yin; Xiaojian Hu; Nuo Chen; Nan Wu;

doi: 10.3390/su13020496

The Potential Impacts of Electric Vehicles on Urban Air Quality in Shanghai City

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Abstract

The Shanghai government has outlined plans for the new vehicles used for the public transportation, rental, sanitation, postal, and intra-city freight to be completely powered by electricity by 2020. This paper analyzed the characteristics of vehicle emissions in Shanghai in the past five years. The potential reduction in road traffic related emissions due to the promotion and application of electric vehicle in Shanghai was evaluated. The potential reduction was quantified by vehicular emissions. The vehicular emissions inventories are calculated by the COPERT IV model under the different scenarios, of which the results indicate that promoting electric vehicles is the efficient measure to control all road traffic related emissions and improve urban air quality. The results also provided basis and support for making policies to promote and manage electric vehicles.

Related Organizations

Southeast University
China (People's Republic of)
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School of Environment, Education and Development University of Manchester
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Southeast University
China (People's Republic of)
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Keywords

Environmental effects of industries and plants, TJ807-830, TD194-195, Renewable energy sources, Environmental sciences, vehicle emissions, urban air quality, COPERT IV, GE1-350, electric vehicles

Impact byBIP!

	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).	25
	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).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%