A dynamic analysis of air pollution emissions in China: Evidence from nonparametric additive regression models |
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| Affiliation: | 1. School of Statistics, Jiangxi University of Finance and Economics, Nanchang, Jiangxi 330013, PR China;2. Research Center of Applied Statistics, Jiangxi University of Finance and Economics, Nanchang, Jiangxi 330013, PR China;3. Collaborative Innovation Center for Energy Economics and Energy Policy, China Institute for Studies in Energy Policy, Xiamen University, Xiamen, Fujian 361005, PR China;1. School of Environment, Tsinghua University, Beijing, 100084, China;2. Ministry of the Environment, Japan, Tokyo, 1008975, Japan;3. School of Environment, Beijing Normal University, Beijing, 100875, China;4. State Key Laboratory of Water Environment Simulation, Beijing Normal University, Beijing, 100875, China;5. School of Environment and Natural Resources, Renmin University of China, Beijing, 100872, China;1. Department of Economics and Management, North China Electric Power University, Baoding, Hebei 071003, China;2. Beijing Key Laboratory of New Energy and Low-Carbon Development, Changping, Beijing 102206, China;1. School of Geographic Sciences & Institute of Eco-Chongming, East China Normal University, Shanghai 200241, China;2. School of Geography, Beijing Normal University, Beijing 100875, China;3. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resource Research, Chinese Academy of Sciences, Beijing 100101, China;4. Department of Tourism and Geography, Tongren University, Tongren, Guizhou Province 554300, China;5. School of Environmental Science and Engineering, Suzhou University of Science and Technology, Suzhou, Jiangsu Province 215009, China;6. School of Economics and Management, Nanchang University, Nanchang 330031, China;1. Business School, Jiangsu Normal University, Xuzhou 221116, China;2. Management School, China University of Mining and Technology, Xuzhou 221116, China;3. College of Economics and Management, Nanjing Forestry University, Najing 210037, China |
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| 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. |
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| Keywords: | STIRPAT model Nonparametric additive regression models |
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