Ground-level gaseous pollutants (NO 2 , SO 2 , and CO) in China: daily seamless mapping and spatiotemporal variations

[摘要] Gaseous pollutants at the ground level seriously threaten the urban airquality environment and public health. There are few estimates of gaseouspollutants that are spatially and temporally resolved and continuous acrossChina. This study takes advantage of big data and artificial-intelligencetechnologies to generate seamless daily maps of three major ambientpollutant gases, i.e., NO 2 , SO 2 , and CO, across China from 2013 to 2020 at a uniform spatial resolution of 10 km. Cross-validation between our estimates and ground observations illustrated a high data quality on a daily basis for surface NO 2 , SO 2 , and CO concentrations, with mean coefficients of determination (root-mean-square errors) of 0.84(7.99  µ g m −3 ), 0.84 (10.7  µ g m −3 ), and 0.80 (0.29 mg m −3 ),respectively. We found that the COVID-19 lockdown had sustained impacts ongaseous pollutants, where surface CO recovered to its normal level in Chinaon around the 34th day after the Lunar New Year, while surface SO 2 and NO 2 rebounded more than 2 times slower due to more CO emissions fromresidents' increased indoor cooking and atmospheric oxidation capacity.Surface NO 2 , SO 2 , and CO reached their peak annual concentrationsof 21.3  ±  8.8  µ g m −3 , 23.1  ±  13.3  µ g m −3 , and 1.01  ±  0.29 mg m −3 in 2013, then continuously declined overtime by 12 %, 55 %, and 17 %, respectively, until 2020. The declining rates were more prominent from 2013 to 2017 due to the sharper reductions in anthropogenic emissions but have slowed down in recent years. Nevertheless, people still suffer from high-frequency risk exposure to surface NO 2 ineastern China, while surface SO 2 and CO have almost reached the World Health Organization (WHO)recommended short-term air quality guidelines (AQG) level since 2018, benefiting from theimplemented stricter “ultra-low” emission standards. This reconstructeddataset of surface gaseous pollutants will benefit future (especiallyshort-term) air pollution and environmental health-related studies.

[学科分类] 医学（综合）