globalchange  > 气候变化与战略
DOI: 10.1016/j.enpol.2020.112011
论文题名:
Investigating spatial variability of CO2 emissions in heavy industry: Evidence from a geographically weighted regression model
作者: Xu B.; Lin B.
刊名: Energy Policy
ISSN: 03014215
出版年: 2021
卷: 149
语种: 英语
中文关键词: CO2 emissions ; Geographically weighted regression model ; The heavy industry
英文关键词: Coal industry ; Economics ; Energy efficiency ; Energy utilization ; Environmental regulations ; Industrial emissions ; Investments ; Pollution control ; Regression analysis ; Urban transportation ; Emerging economies ; Energy consumption structure ; Fixed asset investments ; Geographically weighted regression models ; Heavy industries ; Industrial pollution ; Spatial variability ; Transportation infrastructures ; Carbon dioxide ; carbon dioxide ; carbon emission ; economic growth ; economic impact ; emission inventory ; energy efficiency ; energy use ; environmental economics ; environmental policy ; industrial emission ; industrial investment ; manufacturing ; pollution control ; regression analysis ; research and development ; spatial variation ; transportation infrastructure ; China
英文摘要: China is now the world's largest carbon dioxide (CO2) emitter, and the government is under tremendous pressure to reduce CO2 emissions. The heavy industry sector is the largest contributor to the growth of CO2 emissions. Investigating the driving factors of this industry's CO2 emissions has important practical value. This paper applies the geographically weighted regression model to survey this industry's CO2 emissions. Empirical results show that urbanization exerts a heterogeneous impact on CO2 emissions across provinces and regions. This is mainly due to the differences in urban real estate and transportation infrastructure investments. Economic growth drives CO2 emissions, and this effect varies significantly by region and province on account of the differences in fixed-asset investment. It is more reasonable for local governments to develop emerging economies based on their specific conditions. Energy efficiency has the highest impact on CO2 emissions in the eastern region, because of the differences in R&D personnel investment and the number of patents granted. The energy consumption structure has the largest impact on CO2 emissions in the eastern region since it consumes more coal. Environmental regulations have a greater impact on CO2 emissions in the western region due to the differences in investment for industrial pollution control. © 2020 Elsevier Ltd
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/168089
Appears in Collections:气候变化与战略

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作者单位: School of Statistics, Jiangxi University of Finance and Economics, Nanchang, Jiangxi 330013, China; School of Management, China Institute for Studies in Energy Policy, Collaborative Innovation Center for Energy Economics and Energy Policy, Xiamen UniversityFujian 361005, China

Recommended Citation:
Xu B.,Lin B.. Investigating spatial variability of CO2 emissions in heavy industry: Evidence from a geographically weighted regression model[J]. Energy Policy,2021-01-01,149
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