Influence factors and forecast of carbon emission in China: structure adjustment for emission peak

3rd International Conference on Advances in Energy Resources and Environment Engineering

能源学;生态环境科学

Wang, B.^1,2 ; Cui, C.Q.^1,2 ; Li, Z.P.^3

School of Resources and Safety Engineering, China University of Mining and Technology (Beijing), Beijing

100083, China^1

Beijing Key Laboratory for Precise Mining of Intergrown Energy and Resources, Beijing

100083, China^2

Chinese Hydraulic Engineering Society, Beijing

100053, China^3

关键词: Carbon emissions;    Consumption levels;    Economic structure;    Energy structures;    Integrated modeling;    Multivariate linear regression model;    Multivariate regression analysis;    Structure adjustments;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/113/1/012197/pdf
DOI  :  10.1088/1755-1315/113/1/012197

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

This paper introduced Principal Component Analysis and Multivariate Linear Regression Model to verify long-term balance relationships between Carbon Emissions and the impact factors. The integrated model of improved PCA and multivariate regression analysis model is attainable to figure out the pattern of carbon emission sources. Main empirical results indicate that among all selected variables, the role of energy consumption scale was largest. GDP and Population follow and also have significant impacts on carbon emission. Industrialization rate and fossil fuel proportion, which is the indicator of reflecting the economic structure and energy structure, have a higher importance than the factor of urbanization rate and the dweller consumption level of urban areas. In this way, some suggestions are put forward for government to achieve the peak of carbon emissions.