Spatial and temporal variation of particulate matter and gaseous pollutants in China during 2014-2016

China is experiencing severe air pollution due to rapid economic development and accelerated urbanization. High-resolution temporal and spatial air pollution data are imperative to understand the physical and chemical processes affecting air quality of China. The data of PM2.5, PM10, SO2, CO, NO2, and O-3 in 187 Chinese cities during January 2014 and November 2016 were collected to uncover the spatial and temporal variation of the pollutants in China. The annual mean concentrations of PM2.5 exceeded the Grade I standard of Chinese Ambient Air Quality (CAAQS) for all of the cities except several cities in Hainan, and more than 100 cities exceeded the CAAQS Grade II standard. The concentrations of PM2.5, PM10, SO2, CO, and NO2 decreased from 2014 to 2016, whereas the O-3 level increased dramatically during this period. The concentrations of PM2.5, PM10, SO2, CO and NO2 exhibited the highest levels in winter and the lowest in summer, and evidently decreased from 2014 to 2016, whereas the O-3 concentration peaked in spring and summer, and dramatically increased from 2014 to 2016. The non-attainment ratios were highest in winters, while high pollution days were also frequently observed in the Southeast region in autumn and in the Northwest region in spring. Pearson correlation analysis indicated that all of the pollutants exhibited significant correlation one another. PM10 was a major pollutant affecting the air quality of China in all of the seasons. Both SO2 and NO2 exerted significantly adverse effects on the air quality in spring and autumn, but CO played an important role on the air quality in winter. O-3 was found to be the dominant species among the pollutants affecting the air quality in summer, suggesting that photochemical O-3 formation should be paid more attention to improve the air quality in summer. The results of geographical weight regression (GWR) showed that more significant correlations among the pollutants and the highest air quality index (AQI) appeared in the south of China. The impacts of PM10 and NO2 on the air quality increased from the east to the west of China, while SO2 and O-3 exhibited the opposite variation. The data presented herein supplied an important support for the future source apportionment and intra- and inter-regional transport modeling of pollutants. (C) 2017 Elsevier Ltd. All rights reserved.