Analysis of Influencing Factors and Prediction of the Peak Value of Industrial Carbon Emission in the Sichuan-Chongqing Region

Abstract

The greenhouse effect has a negative impact on social and economic development. Analyzing the factors influencing industrial carbon emissions and accurately predicting the peak of industrial carbon emissions to achieve carbon peak and carbon neutrality is therefore vital. The annual data from 2000 to 2022 were used to study the influencing factors of carbon emission and the path of carbon emission reduction. In this study, the gray correlation method and stepwise regression method were used to explore the effective factors that met the significance test and the STIRPAT expansion model was constructed to analyze the characteristics and influencing factors of industrial carbon emissions in the Sichuan-Chongqing region. Finally, the changing trend of regional industrial carbon emissions is predicted by scenario analysis and four development scenarios are set up, which show that (1) from 2000 to 2022, the change in total industrial carbon emissions in Sichuan Province and Chongqing Municipality presents an inverted U-shaped trend, reaching a phased peak in 2013 and 2014, respectively, then declining and then rising again after 2018. (2) Industrial scale foreign trade dependence and population are the effective factors of industrial carbon emission in Sichuan, and all have positive effects. Energy structure and per capita income are the effective factors in Chongqing, showing negative and positive effects, respectively. (3) Analysis of four scenarios shows that the time range of the industrial carbon peak in the Sichuan-Chongqing region is 2030–2035 and that its peak height ranges from 81.98 million tons to 87.64 million tons. Among them, the green development scenario is the most consistent path to achieve the carbon peak as soon as possible; in this case, industrial carbon emissions will peak in 2030, in line with the national target time, and the lowest peak level of 81.98 million tons. The suggestions in this paper are continuously optimizing the energy structure, adjusting the industrial scale, and accelerating scientific and technological progress to achieve sustainable development.