Spatiotemporal variation and socioeconomic drivers of air pollution in China during 2005-2016

Abstract

Air pollution in China has become a matter of significant public concern. In this study, we investigated the spatiotemporal patterns and socioeconomic drivers of air pollution in China during 2005-2016, based on a long time series of air monitoring data together with the spatial econometrics model. The results show that air pollution in China as a whole exhibited a decreasing trend during the study period whereas concentrated and intensified in the north of China. The heavily polluted areas, based on hierarchical clustering analysis, include the regions of Beijing-Tianjin-Hebei (BTH), Shandong Peninsula and the middle reaches of the Yellow River. Temporally, air pollution in China was higher in winter and lower in summer, while the primary pollutants varied seasonally. Empirical results at the national scale showed that the influencing factors can be ranked in descending order of importance, as follows: vehicle volume, energy consumption, secondary industry as a percentage of GDP, GDP per capita, greenery coverage rate, and expenditure on science and technology. In addition, the positive impact of vehicle volume on air pollution exhibited a significant increasing trend. On a regional scale, secondary industry and energy consumption had a strong impact on air pollution in Shandong Peninsula, and automobile exhaust pollution had the greatest impact on the BTH and Yangtze River Delta (YRD) regions. The estimated coefficients of GDP per capita in the regions of BTH, YRD and South China were significantly negative because of an Environmental Kuznets Curve relationship.

Keywords: AQI; Regional correlation; Spatial econometrics model; Spatiotemporal patterns; Vehicle pollution.