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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01dj52w7779
Title: Alternative energy vehicle deployment coupled with decarbonizing electricity generation amplifies climate, air quality and health co-benefits in China
Contributors: Peng, Liqun
Liu, Feiqi
Zhou, Mi
Li, Mingwei
Zhang, Qiang
Mauzerall, Denise L.
Keywords: co-benefits
climate
air quality
health
alternative energy vehicles
electrification
Issue Date: 17-Jun-2021
Publisher: Princeton University
Abstract: China is the world's largest carbon emitter and suffers from severe air pollution. About one million deaths in China were attributable to air pollution in 2017. Alternative energy vehicles (AEVs), e.g. electric, hydrogen fuel cell, and natural gas vehicles, can help achieve both carbon emission mitigation and air quality improvement. However, climate, air quality and health co-benefit of AEVs powered by deeply decarbonized electricity generation remain poorly quantified. Here, we conduct a quantitative integrated assessment of the air quality, health, carbon emission mitigation and economic benefits of AEV deployment as the electricity grid decarbonizes in China. We find population-weighted annual PM2.5 and summer O3 concentration can decrease as large as 5.7μgm−3 and 4.9ppb. Annual avoided premature mortalities and years of life lost resulting from improved ambient air pollution can be as large as ~329,000 persons and ~1,611,000 years. We thus show that maximizing climate, air quality and health benefits of AEV deployment in China requires rapid decarbonization of the power system.
Description: This dataset is too large to download directly from this item page. You can access and download the data via Globus at this link: https://app.globus.org/file-manager?origin_id=dc43f461-0ca7-4203-848c-33a9fc00a464&origin_path=%2F2ye8-px32%2F
URI: http://arks.princeton.edu/ark:/88435/dsp01dj52w7779
https://doi.org/10.34770/2ye8-px32
https://app.globus.org/file-manager?origin_id=dc43f461-0ca7-4203-848c-33a9fc00a464&origin_path=%2F2ye8-px32%2F
Appears in Collections:C-PREE Research Data Sets

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