US EPA

7495916 

Journal Article 

Satellite-based short- and long-term exposure to PM2.5 and adult mortality in urban Beijing, China 

Liang, F; Xiao, Q; Gu, D; Xu, M; Tian, L; Guo, Q; Wu, Z; Pan, X; Liu, Y 

2018 

Yes 

Environmental Pollution
ISSN: 0269-7491
EISSN: 1873-6424 

242 

Pt A 

492-499 

English 

30005261 

10.1016/j.envpol.2018.06.097 

WOS:000446150300053 

Severe and persistent haze accompanied by high concentrations of fine particulate matter (PM2.5) has become a great public health concern in urban China. However, research on the health effects of PM2.5 in China has been hindered by the lack of high-quality exposure estimates. In this study, we assessed the excess mortality associated with both short- and long-term exposure to ambient PM2.5 simultaneously using satellite-derived exposure data at a high spatiotemporal resolution. Adult registries of non-accidental, respiratory and cardiovascular deaths in urban Beijing in 2013 were collected. Exposure levels were estimated from daily satellite-based PM2.5 concentrations at 1 km spatial resolution from 2004 to 2013. Mixed Poisson regression models were fitted to estimate the cause-specific mortality in association with PM2.5 exposures. With the mutual adjustment of short- and long-term exposure of PM2.5, the percent increases associated with every 10 μg/m3 increase in short-term PM2.5 exposure were 0.09% (95% CI: -0.14%, 0.33%; lag 01), 1.02% (95% CI: 0.08%, 1.97%; lag 04) and 0.09% (95% CI: -0.23%, 0.42%; lag 01) for non-accidental, respiratory and cardiovascular mortality, respectively; those attributable to every 10 μg/m3 increase in long-term PM2.5 exposure (9-year moving average) were 16.78% (95% CI: 10.58%, 23.33%), 44.14% (95% CI: 20.73%, 72.10%) and 3.72% (95% CI: -3.75%, 11.77%), respectively. Both associations of short- and long-term exposure with the cause-specific mortality decreased after they were mutually adjusted. Associations between short-term exposure to satellite-based PM2.5 and cause-specific mortality were larger than those estimated using fixed measurements. Satellite-based PM2.5 predictions help to improve the spatiotemporal resolution of exposure assessments and the mutual adjustment model provide better estimation of PM2.5 associated health effects. Effects attributable to long-term exposure of PM2.5 were larger than those of short-term exposure, which should be more concerned for public health.