LAPSE:2023.20346
Published Article
LAPSE:2023.20346
Carbon Emission Scenario Prediction and Peak Path Selection in China
Xiaodie Liu, Xiangqian Wang, Xiangrui Meng
March 17, 2023
Abstract
Due to the emission of carbon dioxide and other greenhouse gases, the global climate is warming. As the world’s biggest emitter of carbon emissions, China faces a more severe challenge in reducing carbon emissions than developed countries. A reasonable prediction of the carbon peak in China will help the government to formulate effective emission reduction paths. This paper analyzes the changes in carbon emissions in China from 2004 to 2020, uses the STIRPAT model and scenario analysis method to predict carbon emissions from 2021 to 2030, and then calculates the carbon efficiency during carbon peaking to select the most effective carbon peak path for China. The results show that China’s carbon emissions increased year by year from 2004 to 2020. Under the baseline scenario, China is unlikely to reach its carbon peak before 2030. Under the regulatory scenarios, China can reach its carbon peak before 2030. The peak values from high to low are seen with the rapid development-weak carbon control scenario, rapid development-intensified carbon control scenario, slow development-weak carbon control scenario and slow development-intensified carbon control scenario, respectively. Correspondingly, China will peak its carbon emissions in 2029, 2028, 2028 and 2028, respectively, according to these scenarios. The carbon efficiency under the rapid development-weak carbon control scenario is the highest, which means that accelerating the growth rate of population, GDP and urbanization while moderately carrying out the transformation of industrial structure and energy structure is an effective way to achieve the goal of “carbon peak by 2030”.
Keywords
carbon efficiency, carbon emission, carbon peak path, scenario analysis, STIRPAT model
Suggested Citation
Liu X, Wang X, Meng X. Carbon Emission Scenario Prediction and Peak Path Selection in China. (2023). LAPSE:2023.20346
Author Affiliations
Liu X: School of Economic and Management, Anhui University of Science and Technology, Huainan 232001, China
Wang X: School of Economic and Management, Anhui University of Science and Technology, Huainan 232001, China
Meng X: School of Economic and Management, Anhui University of Science and Technology, Huainan 232001, China
Journal Name
Energies
Volume
16
Issue
5
First Page
2276
Year
2023
Publication Date
2023-02-27
ISSN
1996-1073
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Original Submission
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PII: en16052276, Publication Type: Journal Article
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LAPSE:2023.20346
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https://doi.org/10.3390/en16052276
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