Driving forces of China's CO2 emissions from energy consumption based on Kaya-LMDI methods

Jie Yang; Wei Cai; Minda Ma; Li Li; Conghu Liu; Xin Ma; Lingling Li; Xingzheng Chen

doi:10.1016/j.scitotenv.2019.134569

Driving forces of China's CO₂ emissions from energy consumption based on Kaya-LMDI methods

Sci Total Environ. 2020 Apr 1:711:134569. doi: 10.1016/j.scitotenv.2019.134569. Epub 2019 Nov 21.

Authors

Jie Yang¹, Wei Cai², Minda Ma³, Li Li¹, Conghu Liu⁴, Xin Ma⁵, Lingling Li¹, Xingzheng Chen¹

Affiliations

¹ College of Engineering and Technology, Southwest University, Chongqing 400715, China.
² College of Engineering and Technology, Southwest University, Chongqing 400715, China; Faculty of Business, The Hong Kong Polytechnic University, Hung Hum, Kowloon, Hong Kong. Electronic address: weicai@swu.edu.cn.
³ School of Construction Management and Real Estate, Chongqing University, Chongqing 400045, China.
⁴ Sino-US Global Logistics Institute, Shanghai Jiao Tong University, Shanghai, 200030, China.
⁵ School of Science, Southwest University of Science and Technology, Mianyang 621000, China.

PMID: 32000310
DOI: 10.1016/j.scitotenv.2019.134569

Abstract

Anthropogenic carbon emission gives rise to a situation where global warming is becoming serious. China is paying for reducing carbon emissions. The concept of carbon curse suggests that countries rich in fossil fuels tend to be closely linked to high carbon emissions, but this is not absolute, which reminds policymakers that the policies implemented are positivelycorrelateswith carbon emission reduction. This study is also aimed at this, hoping to provide some proposals about reducing CO₂ emissions to policy-makers by decomposing and analyzing the important factors. To achieve this target, this paper employs the extended the Kaya identity, combines the LMDI method to analyze the impact factors of carbon emissions in China from 1996 to 2016 and discusses the effects and causes of each factor according to the actual situation. It is found that the economic activity is the greatest driving force to promote carbon emissions, while on the contrary, energy intensity is the biggest suppressor. Optimizing industrial structure, improving the structure of energy and export-import trade and intensifying the development of clean energy can effectively restrain the growth of carbon emissions. In addition, the relative innovation point in this study is to analyze carbon emissions with the combination of electricity trading and discusses that increasing imported electricity is also a strategy to reduce carbon emissions.

Keywords: CO(2) emissions; China; Driving forces; Energy consumption; Kaya-LMDI method.