Investigating spatial variability of CO2 emissions in heavy industry: Evidence from a geographically weighted regression model

Bin Xu and Boqiang Lin ()

Energy Policy, 2021, vol. 149, issue C

Abstract: 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.

Keywords: CO2 emissions; The heavy industry; Geographically weighted regression model (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (19)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:enepol:v:149:y:2021:i:c:s0301421520307229

DOI: 10.1016/j.enpol.2020.112011

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