Driving factors and spatio-temporal features underlying industrial SO2 emissions in “2+26” in North China and extended cities

Abstract

As one of the largest global emitters of sulfur dioxide (SO2), China faces increasing pressure to achieve sustainable economic and social development. Using panel data of 58 prefecture-level cities in North China between 2003 and 2017, this paper considers the dynamic spatio-temporal characteristics of industrial SO2 emissions in the “2 ​+ ​26” in North China and extended cities in North China and decomposes the determinants of industrial SO2 emissions into eight effects using the Generalized Divisia Index Model (GDIM). The contributions of each effect on changes in emissions are assessed on regional, provincial, and prefectural levels, as well as according to various stages. The results indicate the following. First, industrial SO2 emissions in the “2 ​+ ​26” cities in North China and extended cities in North China exhibit spatial autocorrelation and agglomeration effects. Cities with high-high (HH) and low-low (LL) agglomeration patterns were concentrated in Shanxi and Henan provinces, respectively. Second, industrialization, energy consumption, and economic development were the main factors that increased industrial SO2 emissions, while technology, energy sulfur intensity, and economic sulfur intensity were the key factors that reduced them. Third, 13 cities, including Tangshan, were the most important regions where further emissions regulations need to be implemented. These cities were divided into three types and different corresponding measures for reducing their emissions are suggested. Based on the conclusions of this study, this paper puts forward some targeted policy recommendations for reducing industrial SO2 emissions according to different categories of cities.