Research on the Factors Affecting Carbon Emissions Based on Multivariate Regression Models
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Keywords

Carbon emissions
Energy structure
Industrial structure
Multivariate regression model

DOI

10.26689/ssr.v4i3.3664

Submitted : 2022-02-14
Accepted : 2022-03-01
Published : 2022-03-16

Abstract

Carbon peak and carbon neutrality are two new terms that are being mentioned more frequently, and the measurement of carbon emissions has become an important research topic. Based on relevant data, this paper studies the relationship and evolution law of the driving factors of carbon emissions from energy structure and industrial structure as well as the result factors of carbon emissions from energy consumption, and then establishes corresponding mathematical models. The driving factors, result factors, and relationship attributes that are difficult to measure in the carbon emissions from energy structure and industrial structure are analyzed to fathom the evolution law of carbon emissions and absorption. Based on the results, phased and global suggestions for carbon neutrality have been suggested, taking into account the characteristics of different industries and regions.

References

Liu J, 2018, Study on LED Lighting Load Participating Primary Frequency Modulation and Standby Optimal Configuration in Power System, Shandong University, 135. http://cdmd.cnki.com.cn/Article/CDMD-10422-1018117998.htm

Liang Q, Feng X, Du X, et al., 2020, Study on the Influencing Factors of Carbon Emission from Energy Consumption Based on LMDI: A Case Study of Tangshan. Environment and Sustainable Development, 2020(1): 150-154.

Li H, Lou W, 2016, Prediction of Carbon Dioxide Emission Intensity and Analysis of the 13th Five-Year Plan Emission Reduction Path: Based on STIRPAT Model. Research on Science and Technology Management, 2016(05): 240-247.

Jiang Q, 2005, College Math Experiment, Tsinghua University Press, Beijing.

Wang Z, 2005, Theory and Application of Control System, Beijing University of Posts and Telecommunications Press, Beijing.

Sheng Z, 2008, Probability Theory and Mathematical Statistics, Higher Education Press, Beijing.

Cheng L, 2000, Course on Models and Methods of Operational Research, Tsinghua University Press, Beijing.

Wang W, 2006, Detailed Explanation of Mathematical Modeling and Its Basic Knowledge, Wuhan University Press, Wuhan.

Zhang X, 2006, Advanced Mathematics Experiment, East China University of Technology Press, Shanghai.

Zhang T, Zhu X, 2017, Environmental Regulation, Industrial Agglomeration, and Industrial Transformation and Upgrading – From the Perspective of the Heterogeneous Factor Input Structure, Shandong University, 172. http://cdmd.cnki.com.cn/Article/CDMD-10290-1018826136.htm