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Spatiotemporal patterns of particulate matter (PM) and associations between PM and mortality in Shenzhen, China

Permanent link
https://hdl.handle.net/10037/10494
DOI
https://doi.org/10.1186/s12889-016-2725-6
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Date
2016-03-02
Type
Peer reviewed
Journal article
Tidsskriftsartikkel

Author
Zhang, Fengying; Liu, Xiaojian; Zhou, Lei; Yu, Yong; Wang, Li; Lu, Jinmei; Wang, Wuyi; Krafft, Thomas
Abstract
Background: Most studies on air pollution exposure and its associations with human health in China have focused on the heavily polluted industrial areas and/or mega-cities, and studies on cities with comparatively low air pollutant concentrations are still rare. Only a few studies have attempted to analyse particulate matter (PM) for the vibrant economic centre Shenzhen in the Pearl River Delta. So far no systematic investigation of PM spatiotemporal patterns in Shenzhen has been undertaken and the understanding of pollution exposure in urban agglomerations with comparatively low pollution is still limited. Methods: We analyze daily and hourly particulate matter concentrations and all-cause mortality during 2013 in Shenzhen, China. Temporal patterns of PM (PM2.5 and PM10) with aerodynamic diameters of 2.5 (10) μm or less (or less (including particles with a diameter that equals to 2.5 (10) μm) are studied, along with the ratio of PM2.5 to PM10. Spatial distributions of PM10 and PM2.5 are addressed and associations of PM10 or PM2.5 and all-cause mortality are analyzed. Results: Annual average PM10 and PM2.5 concentrations were 61.3 and 39.6 μg/m3 in 2013. PM2.5 failed to meet the Class 2 annual limit of the National Ambient Air Quality Standard. PM2.5 was the primary air pollutant, with 8.8 % of days having heavy PM2.5 pollution. The daily PM2.5/PM10 ratios were high. Hourly PM2.5 concentrations in the tourist area were lower than downtown throughout the day. PM10 and PM2.5 concentrations were higher in western parts of Shenzhen than in eastern parts. Excess risks in the number of all-cause mortality with a 10 μg/m3 increase of PM were 0.61 % (95 % confidence interval [CI]: 0.50–0.72) for PM10, and 0.69 % (95 % CI: 0.55–0.83) for PM2.5, respectively. The greatest ERs of PM10 and PM2.5 were in 2-day cumulative measures for the all-cause mortality, 2-day lag for females and the young (0–65 years), and L02 for males and the elder (>65 years). PM2.5 had higher risks on all-cause mortality than PM10. Effects of high PM pollution on mortality were stronger in the elder and male. Conclusions: Our findings provide additional relevant information on air quality monitoring and associations of PM and human health, valuable data for further scientific research in Shenzhen and for the on-going discourse on improving environmental policies
Description
DOI: 10.1186/s12889-016-2725-6
Publisher
BioMed Central
Citation
Zhang F, Liu, Zhou L, Yu, Wang L, Lu J, Wang W, Krafft. Spatiotemporal patterns of particulate matter (PM) and associations between PM and mortality in Shenzhen, China. BMC Public Health. Zhang F, Liu, Zhou L, Yu, Wang L, Lu J, Wang W, Krafft. Spatiotemporal patterns of particulate matter (PM) and associations between PM and mortality in Shenzhen, China. BMC Public Health. (2016) 16:215
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