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Article: A novel framework for decomposing PM2.5 variation and demographic change effects on human exposure using satellite observations

TitleA novel framework for decomposing PM<inf>2.5</inf> variation and demographic change effects on human exposure using satellite observations
Authors
KeywordsUrbanization
Satellite observations
Public health
PM 2.5
Human exposure
Issue Date2020
Citation
Environmental Research, 2020, v. 182, article no. 109120 How to Cite?
Abstract© 2020 Elsevier Inc. Human exposure to PM2.5, represented by population-weighted mean PM2.5 concentration (cρ), declines under three conditions: (1) mean PM2.5 concentration declines, (2) PM2.5 concentration within urban areas goes through more of a decrease than within rural areas, or (3) city planning relocates people into cleaner areas. Decomposing these effects on human exposure is essential to guide future environmental policies. The lack of ground PM2.5 observations limits the assessment of human exposure to PM2.5 over China. This study proposed a novel diagnostic framework using satellite observations to decompose the variation in cρ resulting from change in the mean PM2.5 concentration, spatial difference in PM2.5 change, and demographic change. In this framework, we decomposed cρ into mean PM2.5 concentration (c0) and pollution-population-coincidence induced PM2.5 exposure (PPCE). We then used this framework to decompose the variation in cρ over China within three recent Five-Year Plans (FYPs) (2001–2015). The results showed that the decline in c0 reduced cρ in most provinces within the eleventh and twelfth FYPs. The spatial difference in PM2.5 change reduced the PPCE and cρ in most provinces within the tenth and twelfth FYPs, with the most substantial reduction rate of −3.64 μg m−3·yr−1 in Tianjin within the twelfth FYP. Rural-to-urban migration resulting from rapid urbanization, however, increased the PPCE and cρ (by as much as 0.22 μg m−3·yr−1) in all provinces except Taiwan within all three FYPs. The demographic change reduced cρ in Taiwan because of the migration of population into less polluted areas. To better reduce human exposure, it is recommended that control efforts further target populous residential areas and urbanization planning relocates people into less polluted areas. Our decomposition framework paves a new way to decompose the human exposure to other air pollutants in China and other regions.
Persistent Identifierhttp://hdl.handle.net/10722/287050
ISSN
2023 Impact Factor: 7.7
2023 SCImago Journal Rankings: 1.679
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLin, Changqing-
dc.contributor.authorLau, Alexis K.H.-
dc.contributor.authorLao, Xiang Qian-
dc.contributor.authorFung, Jimmy C.H.-
dc.contributor.authorLu, Xingcheng-
dc.contributor.authorLi, Zhiyuan-
dc.contributor.authorMa, Jun-
dc.contributor.authorLi, Chengcai-
dc.contributor.authorWong, Andromeda H.S.-
dc.date.accessioned2020-09-07T11:46:21Z-
dc.date.available2020-09-07T11:46:21Z-
dc.date.issued2020-
dc.identifier.citationEnvironmental Research, 2020, v. 182, article no. 109120-
dc.identifier.issn0013-9351-
dc.identifier.urihttp://hdl.handle.net/10722/287050-
dc.description.abstract© 2020 Elsevier Inc. Human exposure to PM2.5, represented by population-weighted mean PM2.5 concentration (cρ), declines under three conditions: (1) mean PM2.5 concentration declines, (2) PM2.5 concentration within urban areas goes through more of a decrease than within rural areas, or (3) city planning relocates people into cleaner areas. Decomposing these effects on human exposure is essential to guide future environmental policies. The lack of ground PM2.5 observations limits the assessment of human exposure to PM2.5 over China. This study proposed a novel diagnostic framework using satellite observations to decompose the variation in cρ resulting from change in the mean PM2.5 concentration, spatial difference in PM2.5 change, and demographic change. In this framework, we decomposed cρ into mean PM2.5 concentration (c0) and pollution-population-coincidence induced PM2.5 exposure (PPCE). We then used this framework to decompose the variation in cρ over China within three recent Five-Year Plans (FYPs) (2001–2015). The results showed that the decline in c0 reduced cρ in most provinces within the eleventh and twelfth FYPs. The spatial difference in PM2.5 change reduced the PPCE and cρ in most provinces within the tenth and twelfth FYPs, with the most substantial reduction rate of −3.64 μg m−3·yr−1 in Tianjin within the twelfth FYP. Rural-to-urban migration resulting from rapid urbanization, however, increased the PPCE and cρ (by as much as 0.22 μg m−3·yr−1) in all provinces except Taiwan within all three FYPs. The demographic change reduced cρ in Taiwan because of the migration of population into less polluted areas. To better reduce human exposure, it is recommended that control efforts further target populous residential areas and urbanization planning relocates people into less polluted areas. Our decomposition framework paves a new way to decompose the human exposure to other air pollutants in China and other regions.-
dc.languageeng-
dc.relation.ispartofEnvironmental Research-
dc.subjectUrbanization-
dc.subjectSatellite observations-
dc.subjectPublic health-
dc.subjectPM 2.5-
dc.subjectHuman exposure-
dc.titleA novel framework for decomposing PM<inf>2.5</inf> variation and demographic change effects on human exposure using satellite observations-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.envres.2020.109120-
dc.identifier.pmid31927247-
dc.identifier.scopuseid_2-s2.0-85077474226-
dc.identifier.volume182-
dc.identifier.spagearticle no. 109120-
dc.identifier.epagearticle no. 109120-
dc.identifier.eissn1096-0953-
dc.identifier.isiWOS:000516094400083-
dc.identifier.issnl0013-9351-

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