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Analysis of Regional Differences in Energy-Related PM 2.5 Emissions in China: Influencing Factors and Mitigation Countermeasures

Hui Wang (), Guangxing Ji () and Jisheng Xia ()
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Hui Wang: School of Resource, Environment and Earth Sciences, Yunnan University, Kunming, Yunnan 650091, China
Guangxing Ji: Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China
Jisheng Xia: School of Resource, Environment and Earth Sciences, Yunnan University, Kunming, Yunnan 650091, China

Sustainability, 2019, vol. 11, issue 5, 1-14

Abstract: China’s rapid economic development has resulted in a series of serious environmental pollution problems, such as atmospheric particulate pollution. However, the socioeconomic factors affecting energy-related PM 2.5 emissions are indistinct. Therefore, this study first explored the change in PM 2.5 emissions over time in China from 1995 to 2012. Then the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model was adopted for quantitatively revealing the mechanisms of various factors on energy-related PM 2.5 emissions. Finally, the Environmental Kuznets Curve (EKC) hypothesis was adopted to examine whether an EKC relationship between affluence and energy-related PM 2.5 emissions is present from a multiscale perspective. The results showed that energy-related PM 2.5 emissions in most regions showed an increasing trend over the study period. The influences of the increase in population, energy intensity, and energy use mix on energy-related PM 2.5 emissions were positive and heterogeneous, and population scale was the major driving force of energy-related PM 2.5 emissions. The effects of the increase in the urbanization level and the proportion of tertiary industry increased value to GDP on energy-related PM 2.5 emissions varied from area to area. An inverse U-shape EKC relationship for energy-related PM 2.5 emissions was not verified except for eastern China. The conclusions are valuable for reducing PM 2.5 emissions without affecting China’s economic development.

Keywords: energy-related PM 2.5 emissions; STIRPAT model; influence factors; Environmental Kuznets Curve (search for similar items in EconPapers)
JEL-codes: Q Q0 Q2 Q3 Q5 Q56 O13 (search for similar items in EconPapers)
Date: 2019
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