Spatiotemporal Dynamic Correlation Characteristics and Driving Factors of Major Air Pollutant Emissions in China

Abstract

Air pollution is closely associated with human health and the economy. Therefore, it is important to understand variations in the spatiotemporal and sectoral emission distributions of major air pollutants and their drivers. The policies (APAPPC) promulgated by China in 2013 have also achieved remarkable results. Rate of change, trend analysis, and a geographically and temporally weighted regression model were used to study the effects of socioeconomic factors on NOx, SO2, and dust emissions in China during 2011–2017. During the study period, annual average emissions of NOx, SO2, and dust decreased by 11.45, 13.42, and 4.82 Mt (−47.64, −60.53, and −39.05%), respectively. Pollutant emissions were concentrated in North China, with Shandong and Hebei provinces exhibiting the highest NOx and SO2 and dust emissions, respectively. Pollutant emissions from the power and industrial sectors were mainly distributed in East (27.08 and 28.00%, respectively) and North China (23.57 and 20.04%, respectively), whereas emissions from the residential sector were mainly concentrated in North (22.48%) and Southwest China (20.07%). Pollutant emissions were positively correlated with electricity generation, urban population density, urban green spaces, private car ownership, the secondary industry as a share of regional GDP, and steel production and negatively correlated with disposable income and gross construction output. Per capita disposable income was the dominant driving factor.

Keywords

• air pollution
• atmospheric pollutants
• pollutant emissions
• China
• spatiotemporal dynamic correlation