Research Article
Research and Prediction of Carbon Emission Influencing Factors in 30 Provinces of China--Analysis Based on Extended STIRPAT Model
@INPROCEEDINGS{10.4108/eai.2-6-2023.2334659, author={Chaoran Yang and Ruiqi Li and Shadan Sun and Jiacheng Yang and Yucheng Zhang}, title={Research and Prediction of Carbon Emission Influencing Factors in 30 Provinces of China--Analysis Based on Extended STIRPAT Model}, proceedings={Proceedings of the 2nd International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2023, June 2--4, 2023, Nanchang, China}, publisher={EAI}, proceedings_a={ICIDC}, year={2023}, month={8}, keywords={carbon emissions; stirpat model; dual fixed effects model; regression of ridge}, doi={10.4108/eai.2-6-2023.2334659} }- Chaoran Yang
Ruiqi Li
Shadan Sun
Jiacheng Yang
Yucheng Zhang
Year: 2023
Research and Prediction of Carbon Emission Influencing Factors in 30 Provinces of China--Analysis Based on Extended STIRPAT Model
ICIDC
EAI
DOI: 10.4108/eai.2-6-2023.2334659
Abstract
Global warming and the climate problems it causes have become a common challenge faced by human beings all over the world, especially true for China, which has achieved great development results in recent years and thus brought serious environmental problems. China urgently needs to achieve low-carbon development and reach a peak in carbon emissions in 2030. Owing to China's East-West unbalanced model of development and the background of regional industrial transfer, the carbon emissions of provinces with different development levels are greatly different, and the carbon peak time of each province based on social and economic indicators and carbon emissions is also different.Based on this, this paper divides the 30 provinces in China into the group that carbon dioxide emissions peak ahead of 2030 and the group that carbon dioxide emissions peak in 2030 and select the total population, per capita GDP, amount of foreign direct investment, urbanization rate, energy intensity, and secondary industry structure to explore the difference in the impact of different variables on the total carbon emissions of different groups. Then, predicting whether China can successfully reach carbon emissions peak in 2030 under three different scenarios based on the STIRPAT model.
