LAPSE:2023.13625
Published Article

LAPSE:2023.13625
Simulation of China’s Carbon Emission based on Influencing Factors
March 1, 2023
Abstract
China is one of the world’s largest energy consumers and carbon emitters, and the situation of carbon emission reduction is serious. This paper forecasts the future trend of China’s carbon emissions by constructing a system dynamics model of China’s carbon emissions. The results show that China cannot fulfill its commitment to peak its carbon emissions in 2030 as scheduled. Secondly, the Logarithmic Mean Divisia Index model (LMDI) was used to analyze the influencing factors of China’s carbon emissions. The contribution rates of the five factors to China’s carbon emissions are as follows: economic development (226.30%), technological innovation (−105.92%), industrial structure (−26.55%), population scale (11.44%) and energy structure (−5.28%). Finally, this paper formulates five carbon emission reduction paths according to the size and direction of various factors that affect China’s carbon emissions. The paths of carbon emission reduction were simulated by using the system dynamics model of China’s carbon emissions. It is found that technological innovation is the key pathway for China to realize its commitment to carbon emission reduction. Slowing economic growth will delay the arrival time of peak carbon emissions and increase the intensity of carbon emissions. Optimizing the industrial structure, reducing the population scale and adjusting the energy structure can reduce the peak and carbon emissions in China, but the effect is small.
China is one of the world’s largest energy consumers and carbon emitters, and the situation of carbon emission reduction is serious. This paper forecasts the future trend of China’s carbon emissions by constructing a system dynamics model of China’s carbon emissions. The results show that China cannot fulfill its commitment to peak its carbon emissions in 2030 as scheduled. Secondly, the Logarithmic Mean Divisia Index model (LMDI) was used to analyze the influencing factors of China’s carbon emissions. The contribution rates of the five factors to China’s carbon emissions are as follows: economic development (226.30%), technological innovation (−105.92%), industrial structure (−26.55%), population scale (11.44%) and energy structure (−5.28%). Finally, this paper formulates five carbon emission reduction paths according to the size and direction of various factors that affect China’s carbon emissions. The paths of carbon emission reduction were simulated by using the system dynamics model of China’s carbon emissions. It is found that technological innovation is the key pathway for China to realize its commitment to carbon emission reduction. Slowing economic growth will delay the arrival time of peak carbon emissions and increase the intensity of carbon emissions. Optimizing the industrial structure, reducing the population scale and adjusting the energy structure can reduce the peak and carbon emissions in China, but the effect is small.
Record ID
Keywords
China’s carbon emissions, factor analysis, peak carbon emissions, system simulation
Subject
Suggested Citation
Kong H, Shi L, Da D, Li Z, Tang D, Xing W. Simulation of China’s Carbon Emission based on Influencing Factors. (2023). LAPSE:2023.13625
Author Affiliations
Kong H: School of Economics and Management, Nanjing University of Science & Technology, Nanjing 210094, China [ORCID]
Shi L: School of Business, Jiangsu Vocational College of Electronics and Information, Huai’an 223001, China [ORCID]
Da D: School of Business, Jiangsu Open University, Nanjing 210000, China
Li Z: School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China [ORCID]
Tang D: School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China [ORCID]
Xing W: Office of Financial Affairs, Hu’nan Moderen Logistics College, Changsha 410131, China
Shi L: School of Business, Jiangsu Vocational College of Electronics and Information, Huai’an 223001, China [ORCID]
Da D: School of Business, Jiangsu Open University, Nanjing 210000, China
Li Z: School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China [ORCID]
Tang D: School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China [ORCID]
Xing W: Office of Financial Affairs, Hu’nan Moderen Logistics College, Changsha 410131, China
Journal Name
Energies
Volume
15
Issue
9
First Page
3272
Year
2022
Publication Date
2022-04-29
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en15093272, Publication Type: Journal Article
Record Map
Published Article

LAPSE:2023.13625
This Record
External Link

https://doi.org/10.3390/en15093272
Publisher Version
Download
Meta
Record Statistics
Record Views
213
Version History
[v1] (Original Submission)
Mar 1, 2023
Verified by curator on
Mar 1, 2023
This Version Number
v1
Citations
Most Recent
This Version
URL Here
https://psecommunity.org/LAPSE:2023.13625
Record Owner
Auto Uploader for LAPSE
Links to Related Works
