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Renewable Energy Green Innovation, Fossil Energy Consumption, and Air Pollution—Spatial Empirical Analysis Based on China

by Neng Shen 1,2, Yifan Wang 1, Hui Peng 3 and Zhiping Hou 4,*
1
College of Public Administration, Huazhong University of Science and Technology, Wuhan 430074, China
2
School of Economics and Management, Fuzhou University, Fuzhou 350108, China
3
School of Management, Huazhong University of Science and Technology, Wuhan 430074, China
4
Business College, Guilin University of Technology, Guilin 532100, China
*
Author to whom correspondence should be addressed.
Sustainability 2020, 12(16), 6397; https://doi.org/10.3390/su12166397
Received: 4 July 2020 / Revised: 1 August 2020 / Accepted: 4 August 2020 / Published: 8 August 2020
(This article belongs to the Section Energy Sustainability)
Excessive consumption of traditional fossil energy has led to more serious global air pollution. This article incorporates renewable energy green innovation (REGI), fossil energy consumption (FEC), and air pollution into a unified analysis framework. Using China’s provincial panel data, a spatial measurement model was used to investigate the spatial effects of renewable energy green innovation and fossil energy consumption on air pollution in China from 2011 to 2017. The global Moran index shows that over time, the spatial correlation of air pollution has gradually weakened, while the global correlation of renewable energy green innovation and fossil energy consumption is increasing year by year. ArcGIS visualization and partial Moran index show that air pollution, renewable energy green innovation, and fossil energy consumption are extremely uneven in geographic space. The spatial distribution of air pollution, renewable energy green innovations, and fossil energy consumption are all characterized by high in the east and low in the west and they all show a strong spatial aggregation. Applying the spatial adjacency matrix to the spatial Durbin model gave the results that China’s air pollution has a significant spatial spillover effect. Replacing fossil fuels with clean renewable energy will reduce air pollutant emissions. The Environment Kuznets Curve (EKC) hypothesis has not been supported and verified in China. The partial differential method test found that the spatial spillover benefits can be decomposed into direct effects and indirect effects. The direct and indirect effects of renewable energy green innovation on air pollution are both significantly negative, indicating that green innovation of renewable energy not only inhibits local air pollution, but also inhibits air pollution in nearby areas. The consumption of fossil energy will significantly increase the local air pollution, while the impact of sulfur dioxide (SO2) and soot (DS) pollution in nearby areas is not obvious. It is recommended to increase investment in renewable energy green innovation, reduce the proportion of traditional fossil energy consumption, and pay attention to the spatial connection and overflow of renewable energy green innovation and air pollution. View Full-Text
Keywords: renewable energy; energy consumption; air pollution; spatial Durbin model; spatial analysis renewable energy; energy consumption; air pollution; spatial Durbin model; spatial analysis
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Shen, N.; Wang, Y.; Peng, H.; Hou, Z. Renewable Energy Green Innovation, Fossil Energy Consumption, and Air Pollution—Spatial Empirical Analysis Based on China. Sustainability 2020, 12, 6397.

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