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Mortality attributable to ambient PM<sub>2.5</sub> pollution in China's aging population

dc.contributor.authorWan, Leien
dc.contributor.authorBambrick, Hilaryen
dc.contributor.authorTong, Michaelen
dc.date.accessioned2026-06-07T18:40:36Z
dc.date.available2026-06-07T18:40:36Z
dc.date.issued2025en
dc.description.abstractBackground: As China's population is aging rapidly, understanding the shifts in PM2.5 attributable mortality within this context is crucial for informing future clean air policies. Methods: We adopted a Fusion relative risk model, combined with 100 m resolution age structure data, to better estimate China's age- and cause-specific mortality attributable to PM2.5 over 2010–2019, and projected attributable mortality in 2030 and 2060 at a 0.1° spatial resolution under three scenarios: Baseline, Carbon-peak and Carbon-neutral. We also assessed the impact of population aging using a decomposition method at the grid level. Results: PM2.5 attributable deaths declined by 9.2 % from 2010 (1.95 million, 95 % UI: 1.80–2.09) to 2019 (1.77 million, 95 % UI: 1.64–1.90), with population aging contributing an increase of 0.48 million deaths. The elderly population constituted over 70 % of total attributable mortality during 2010–2019, and this share is expected to increase to over 90 % in 2060 under three future scenarios. Under Baseline scenario, attributable deaths are expected to increase, with population aging as the major contributor. Under Carbon-peak scenario, the projected mortality declines over 2019–2030 and 2030–2060 will be partly offset by population aging. Under Carbon-neutral scenario, population aging is projected to increase attributable deaths by 0.57 million and 1.27 million over the two periods, largely offsetting the reductions achieved by the declines in PM2.5 concentrations and cause-specific baseline mortality rates. Conclusions: Population aging is the main factor that increases PM2.5 attributable mortality. Specific measures considering the vulnerability of the elderly are needed to further alleviate future health burden from air pollution.en
dc.description.sponsorshipThis study is supported by the Australian Government Research Training Program Scholarship. We would like to thank Prof Richard Burnett for providing the parameters for the Fusion relative risk model. We would also like to thank Prof Qiang Zhang and Dr. Yang Liu at Tsinghua University for providing simulated PM2.5 data under future scenarios.en
dc.description.statusPeer-revieweden
dc.format.extent11en
dc.identifier.issn0195-9255en
dc.identifier.otherWOS:001419592900001en
dc.identifier.otherORCID:/0000-0002-9694-9207/work/216711842en
dc.identifier.otherORCID:/0000-0001-5361-950X/work/216715357en
dc.identifier.scopus85214697505en
dc.identifier.urihttps://hdl.handle.net/1885/733810059
dc.language.isoenen
dc.provenanceCC BY 4.0en
dc.rights © 2025 The Authorsen
dc.sourceEnvironmental Impact Assessment Reviewen
dc.subjectCarbon-neutralen
dc.subjectCarbon-peaken
dc.subjectFusion relative risk modelen
dc.subjectPM attributable mortalityen
dc.subjectPopulation agingen
dc.titleMortality attributable to ambient PM<sub>2.5</sub> pollution in China's aging populationen
dc.typeJournal articleen
dspace.entity.typePublicationen
local.contributor.affiliationWan, Lei; The Australian National Universityen
local.contributor.affiliationBambrick, Hilary; National Centre for Epidemiology and Population Health, ANU College of Law, Governance and Policy, The Australian National Universityen
local.contributor.affiliationTong, Michael; National Centre for Epidemiology and Population Health, ANU College of Law, Governance and Policy, The Australian National Universityen
local.identifier.citationvolume112en
local.identifier.doi10.1016/j.eiar.2025.107823en
local.identifier.doi10.1016/j.eiar.2025.107823en
local.identifier.pure49f0088b-0df9-435f-bc47-824ecf2ddb26en
local.identifier.urlhttps://www.scopus.com/pages/publications/85214697505en
local.type.statusPublisheden

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