Evaluating the impact of clean energy consumption and factor allocation on China's air pollution: A spatial econometric approach. (15th March 2020)
- Record Type:
- Journal Article
- Title:
- Evaluating the impact of clean energy consumption and factor allocation on China's air pollution: A spatial econometric approach. (15th March 2020)
- Main Title:
- Evaluating the impact of clean energy consumption and factor allocation on China's air pollution: A spatial econometric approach
- Authors:
- Li, Li
Hong, Xuefei
Wang, Jun - Abstract:
- Abstract: China's air pollution has become a widespread concern in the academic world, but there are few studies based on spatial measurement methods to quantify the impact of clean energy consumption and factor allocation on a variety of pollutants. Based on an exploratory spatial data analysis, a spatial Durbin model and extended Cobb-Douglas production function (C-D production function) are used to study the direct, indirect and total effects of clean energy consumption and element allocation on China's air pollution emissions. The exploratory spatial data analysis results showed that the three emissions had significant agglomeration effects, and the spatial aggregation patterns of the emissions were similar to the patterns of fossil energy consumption spatial aggregation. The spatial Durbin model estimation results showed that the clean energy consumption proportion and factor allocation of energy and labour inhibited air pollution emissions. The spatial spillover effect was greater than the direct effect. The fossil energy structure and factor allocation of energy and capital stock were positively related to air pollution emissions. These findings help to formulate regional industrial policies and energy policies and contribute to the governance of air pollution and the sustainable development of economic, environmental and energy resources. Highlights: The clean energy and factor allocation impact on air pollutants are revealed. Evaluate the direct and economic impactsAbstract: China's air pollution has become a widespread concern in the academic world, but there are few studies based on spatial measurement methods to quantify the impact of clean energy consumption and factor allocation on a variety of pollutants. Based on an exploratory spatial data analysis, a spatial Durbin model and extended Cobb-Douglas production function (C-D production function) are used to study the direct, indirect and total effects of clean energy consumption and element allocation on China's air pollution emissions. The exploratory spatial data analysis results showed that the three emissions had significant agglomeration effects, and the spatial aggregation patterns of the emissions were similar to the patterns of fossil energy consumption spatial aggregation. The spatial Durbin model estimation results showed that the clean energy consumption proportion and factor allocation of energy and labour inhibited air pollution emissions. The spatial spillover effect was greater than the direct effect. The fossil energy structure and factor allocation of energy and capital stock were positively related to air pollution emissions. These findings help to formulate regional industrial policies and energy policies and contribute to the governance of air pollution and the sustainable development of economic, environmental and energy resources. Highlights: The clean energy and factor allocation impact on air pollutants are revealed. Evaluate the direct and economic impacts on pollution emission intensity. Clean energy consumption could reduce the emissions of pollutants. Factor allocation of energy and capital stock are positively related to emissions. … (more)
- Is Part Of:
- Energy. Volume 195(2020)
- Journal:
- Energy
- Issue:
- Volume 195(2020)
- Issue Display:
- Volume 195, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 195
- Issue:
- 2020
- Issue Sort Value:
- 2020-0195-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-03-15
- Subjects:
- Air emissions -- Clean energy consumption -- Factor allocation -- Spatial correlation -- Spatial durbin panel models -- Cobb-douglas production function
Power resources -- Periodicals
Power (Mechanics) -- Periodicals
Energy consumption -- Periodicals
333.7905 - Journal URLs:
- http://www.elsevier.com/journals ↗
- DOI:
- 10.1016/j.energy.2019.116842 ↗
- Languages:
- English
- ISSNs:
- 0360-5442
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3747.445000
British Library DSC - BLDSS-3PM
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