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Factor Decomposition and Regression Analysis of the Energy Related Carbon Emissions in Shandong, China: A Perspective of Industrial Structure

Weifeng Gong1,2, Baoqing Zhu3, Chuanhui Wang1,*, Zhenyue Fan1, Mengzhen Zhao1, Liang Chen4
1 School of Economics, Qufu Normal University, Rizhao, 276826, China
2 College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China
3 School of Marxism, Fudan University, Shanghai, 200433, China
4 Department of Accounting, Zhengzhou Business University, Zhengzhou, 451200, China
* Corresponding Author: Chuanhui Wang. Email:
(This article belongs to this Special Issue: Energy Systems Management and Climate Change)

Energy Engineering 2021, 118(4), 981-994. https://doi.org/10.32604/EE.2021.014554

Received 07 October 2020; Accepted 25 November 2020; Issue published 31 May 2021

Abstract

An in-depth study of the energy related carbon emissions has important practical significance for carbon emissions reduction and structural adjustment in Shandong Province and throughout China. Based on the perspective of industrial structure, the expanded KAYA equation to measure the energy related carbon emissions of the primary industries (Resources and Agriculture) and secondary industries (Manufacturing and Construction) and tertiary industries (Retail and Service) was utilized in Shandong Province from 2011 to 2017. The carbon emissions among industries in Shandong Province were empirically analyzed using the Logarithmic Mean Divisia Index decomposition approach. The results were follows: (1) Under the three industrial dimensions, the energy structure effect and the energy intensity effect have a restraining influence on the carbon emissions of the three industries. (2) The development level effect and the employment scale effect play a pulling role in carbon emissions. (3) From the perspective of the employment structure effect of the primary industry, there is a restraining effect on carbon emissions, while the employment structure effects of the secondary and tertiary industries play a pulling role in carbon emissions, and the employment structure effect of the tertiary industry has a greater pulling effect on carbon emissions than the secondary industry.

Keywords

Carbon emissions; industrial structure; expanded KAYA equation; LMDI decomposition; regression analysis

Cite This Article

Gong, W., Zhu, B., Wang, C., Fan, Z., Zhao, M. et al. (2021). Factor Decomposition and Regression Analysis of the Energy Related Carbon Emissions in Shandong, China: A Perspective of Industrial Structure. Energy Engineering, 118(4), 981–994.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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