Long-term health impact of PM2.5 under whole-year COVID-19 lockdown in China
2021
Hao, Xin | Li, Jiandong | Wang, Huijun | Liao, Hong | Yin, Zhicong | Hu, Jianlin | Wei, Ying | Dang, Ruijun
The health impact of changes in particulate matter with an aerodynamic diameter <2.5 μm (PM₂.₅) pollution associated with the COVID-19 lockdown has aroused great interest, but the estimation of the long-term health effects is difficult because of the lack of an annual mean air pollutant concentration under a whole-year lockdown scenario. We employed a time series decomposition method to predict the monthly PM₂.₅ concentrations in urban cities under permanent lockdown in 2020. The premature mortality attributable to long-term exposure to ambient PM₂.₅ was quantified by the risk factor model from the latest epidemiological studies. Under a whole-year lockdown scenario, annual mean PM₂.₅ concentrations in cites ranged from 5.4 to 68.0 μg m⁻³, and the national mean concentration was reduced by 32.2% compared to the 2015–2019 mean. The Global Exposure Mortality Model estimated that 837.3 (95% CI: 699.8–968.4) thousand people in Chinese cities would die prematurely from illnesses attributable to long-term exposure to ambient PM₂.₅. Compared to 2015–2019 mean levels, 140.2 (95% CI: 122.2–156.0) thousand premature deaths (14.4% of the annual mean deaths from 2015 to 2019) attributable to long-term exposure to PM₂.₅ were avoided. Because PM₂.₅ concentrations were still high under the whole-year lockdown scenario, the health benefit is limited, indicating that continuous emission-cutting efforts are required to reduce the health risks of air pollution. Since a similar scenario may be achieved through promotion of electric vehicles and the innovation of industrial technology in the future, the estimated long-term health impact under the whole year lockdown scenario can establish an emission–air quality–health impact linkage and provide guidance for future emission control strategies from a health protection perspective.
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