A dynamic analysis of air pollution emissions in China: Evidence from nonparametric additive regression models. (April 2016) - Xu, Bin; Luo, Liangqing; Lin, Boqiang
Highlights: We explore the driving forces of PM2.5 emissions in China. The nonlinear impact of urbanization on PM2.5 emissions exhibits an inverted "U-shaped" pattern. Energy efficiency follows a positive "U-shaped" pattern in relation to PM2.5 emissions. The inverted "U-shaped" impact of private cars may be due to the different roles of scale, structural and technical effects at different stages. Abstract: PM2.5 emissions not only have serious adverse health effects, but also impede transportation activities, especially in air and highway transport. As a result, PM2.5 emissions have become a public policy concern in China in recent years. Currently, the vast majority of existing researches on PM2.5 are based on natural science perspective. Very few economic studies on the subject have been conducted with linear models. This paper adopts provincial panel data from 2001 to 2012, and uses the STIRPAT model and nonparametric additive regression models to examine the key driving forces of PM2.5 emissions in China. The results show that the nonlinear effect of economic growth on PM2.5 emissions is consistent with the Environmental Kuznets Curve (EKC) hypothesis. The nonlinear impact of urbanization exhibits an inverted "U-shaped" pattern due to the rapid development of urban real estate in the early stages and the strengthening of environmental protection measures in the latter stage. Coal consumption follows an inverted "U-shaped" relationship with PM2.5 emissions owing to massive coal consumption at the beginning and efforts to optimize the energy structure as well as technological progress in clean energy in the latter stages. The nonlinear inverted "U-shaped" impact of private vehicles may be due to the different roles of scale, structural and technical effects at different stages. However, energy efficiency improvement follows a positive "U-shaped" pattern in relation to PM2.5 emissions because of differences in the scale of the economy and the speed of technological progress at different times. As a result, the differential dynamic effects of the driving forces of PM2.5 emissions at different times should be taken into consideration when initiating policies to reduce PM2.5 emissions in China.