Conibear, L orcid.org/0000-0003-2801-8862, Reddington, CL orcid.org/0000-0002-5990-4966, Silver, BJ orcid.org/0000-0003-0395-0637 et al. (3 more authors) (2022) Emission Sector Impacts on Air Quality and Public Health in China From 2010 to 2020. GeoHealth, 6 (6). e2021GH000567. ISSN 2471-1403
Abstract
Anthropogenic emissions and ambient fine particulate matter (PM2.5) concentrations have declined in recent years across China. However, PM2.5 exposure remains high, ozone (O3) exposure is increasing, and the public health impacts are substantial. We used emulators to explore how emission changes (averaged per sector over all species) have contributed to changes in air quality and public health in China over 2010–2020. We show that PM2.5 exposure peaked in 2012 at 52.8 μg m−3, with contributions of 31% from industry and 22% from residential emissions. In 2020, PM2.5 exposure declined by 36% to 33.5 μg m−3, where the contributions from industry and residential sources reduced to 15% and 17%, respectively. The PM2.5 disease burden decreased by only 9% over 2012 where the contributions from industry and residential sources reduced to 15% and 17%, respectively 2020, partly due to an aging population with greater susceptibility to air pollution. Most of the reduction in PM2.5 exposure and associated public health benefits occurred due to reductions in industrial (58%) and residential (29%) emissions. Reducing national PM2.5 exposure below the World Health Organization Interim Target 2 (25 μg m−3) would require a further 80% reduction in residential and industrial emissions, highlighting the challenges that remain to improve air quality in China.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 The Authors. GeoHealth published by Wiley Periodicals LLC on behalf of American Geophysical Union. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | emulators; air quality; China; machine learning; health impact assessment; emissions |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Inst for Climate & Atmos Science (ICAS) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 27 May 2022 10:12 |
Last Modified: | 25 Jun 2023 22:59 |
Status: | Published |
Publisher: | American Geophysical Union |
Identification Number: | 10.1029/2021GH000567 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:187347 |