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DOI	10.1016/j.enpol.2020.112011
	Investigating spatial variability of CO2 emissions in heavy industry: Evidence from a geographically weighted regression model
	Xu B.; Lin B.
发表日期	2021
ISSN	03014215
卷号	149
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
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
语种	英语
来源期刊	Energy Policy
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/205412
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
推荐引用方式 GB/T 7714	Xu B.,Lin B.. Investigating spatial variability of CO2 emissions in heavy industry: Evidence from a geographically weighted regression model[J],2021,149.
APA	Xu B.,&Lin B..(2021).Investigating spatial variability of CO2 emissions in heavy industry: Evidence from a geographically weighted regression model.Energy Policy,149.
MLA	Xu B.,et al."Investigating spatial variability of CO2 emissions in heavy industry: Evidence from a geographically weighted regression model".Energy Policy 149(2021).