ORIGINAL RESEARCH
Study on Measurement and Driving Factors of Carbon Emission Intensity From Energy Consumption in China
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College of economics and management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
CORRESPONDING AUTHOR
Tao Sun   

College of economics and management, Nanjing University of Aeronautics and Astronautics, 29 general Avenue, 211106, Nanjing, China
Submission date: 2022-01-13
Final revision date: 2022-02-21
Acceptance date: 2022-02-28
Online publication date: 2022-05-17
 
 
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ABSTRACT
In order to explore effective ways to reduce carbon emission intensity from energy consumption in China, on the basis of literature review and current situation analysis, the method of combining the energy chemical structure and combustion carbon emission principle was adopted, making a scientific measurement of carbon emission and its intensity from energy consumption in this paper. Firstly, the change law of China's carbon emission intensity from energy consumption was analyzed according to the measurement results. Secondly, through the systematic analysis of Kaya method, with full consideration to the actual situation of carbon emission from energy consumption in China, Kaya model was revised by choosing the following factors as independent variables: per capita CO2 emission (PC), per capita energy consumption (PE), energy consumption intensity of environmental pollution treatment investment (QI), the proportion of environmental pollution treatment investment to GDP (IG), etc. On this basis, the empirical test model was constructed for the driving factors of carbon emission intensity from energy consumption in China, and the empirical equilibrium equation and the error correction equation were determined through stability test, lag order test and co-integration test. The results show that all factors have a positive effect on carbon emission intensity from energy consumption, with influence elasticity of 0.8913, 0.9854, 1.0078 and 1.0169. Among all driving factors, IG has the greatest influence degree, followed by QI, the reciprocal of PE (PE-1) and the PC. Our research results are of great significance to help the government formulate effective carbon emission intensity control policies and promote the realization of the "double carbon" goal.
eISSN:2083-5906
ISSN:1230-1485