Renewable Energy Green Innovation, Fossil Energy Consumption, and Air Pollution—Spatial Empirical Analysis Based on China
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 me...
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doaj-8f065199959845f1a6aa6bf6b932b9bf2020-11-25T03:09:30ZengMDPI AGSustainability2071-10502020-08-01126397639710.3390/su12166397Renewable Energy Green Innovation, Fossil Energy Consumption, and Air Pollution—Spatial Empirical Analysis Based on ChinaNeng Shen0Yifan Wang1Hui Peng2Zhiping Hou3College of Public Administration, Huazhong University of Science and Technology, Wuhan 430074, ChinaCollege of Public Administration, Huazhong University of Science and Technology, Wuhan 430074, ChinaSchool of Management, Huazhong University of Science and Technology, Wuhan 430074, ChinaBusiness College, Guilin University of Technology, Guilin 532100, ChinaExcessive 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 (SO<sub>2</sub>) 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.https://www.mdpi.com/2071-1050/12/16/6397renewable energyenergy consumptionair pollutionspatial Durbin modelspatial analysis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Neng Shen Yifan Wang Hui Peng Zhiping Hou |
spellingShingle |
Neng Shen Yifan Wang Hui Peng Zhiping Hou Renewable Energy Green Innovation, Fossil Energy Consumption, and Air Pollution—Spatial Empirical Analysis Based on China Sustainability renewable energy energy consumption air pollution spatial Durbin model spatial analysis |
author_facet |
Neng Shen Yifan Wang Hui Peng Zhiping Hou |
author_sort |
Neng Shen |
title |
Renewable Energy Green Innovation, Fossil Energy Consumption, and Air Pollution—Spatial Empirical Analysis Based on China |
title_short |
Renewable Energy Green Innovation, Fossil Energy Consumption, and Air Pollution—Spatial Empirical Analysis Based on China |
title_full |
Renewable Energy Green Innovation, Fossil Energy Consumption, and Air Pollution—Spatial Empirical Analysis Based on China |
title_fullStr |
Renewable Energy Green Innovation, Fossil Energy Consumption, and Air Pollution—Spatial Empirical Analysis Based on China |
title_full_unstemmed |
Renewable Energy Green Innovation, Fossil Energy Consumption, and Air Pollution—Spatial Empirical Analysis Based on China |
title_sort |
renewable energy green innovation, fossil energy consumption, and air pollution—spatial empirical analysis based on china |
publisher |
MDPI AG |
series |
Sustainability |
issn |
2071-1050 |
publishDate |
2020-08-01 |
description |
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 (SO<sub>2</sub>) 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. |
topic |
renewable energy energy consumption air pollution spatial Durbin model spatial analysis |
url |
https://www.mdpi.com/2071-1050/12/16/6397 |
work_keys_str_mv |
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