Using LMDI approach to analyze changes in carbon dioxide emissions of China’s logistics industry

Ying Dai, Jing Zhu, Han Song

Abstract


Purpose: China is confronting with tremendous pressure in carbon emission reduction. While logistics industry seriously relies on fossil fuel, and emits greenhouse gas, especially carbon dioxide. The aim of this article is to estimate the carbon dioxide emission in China’s logistics sector, and analyze the causes for the change of carbon dioxide emission, and identify the critical factors which mainly drive the change in carbon dioxide emissions of China’s logistics industry.

Design/methodology/approach: The logarithmic mean Divisia index (LMDI) method has often been used to analyze decomposition of energy consumption and carbon emission due to its theoretical foundation, adaptability, ease of use and result interpretation. So we use the LMDI method to analyze the changes in carbon dioxide emission in China’s logistics industry in this paper.

Findings: By analyzing carbon dioxide emission of China’s logistics, the results show that the carbon dioxide emission of logistics in China has increased by 21.5 times, from 45.1 million tons to 1014.1 million tons in the research period. The highway transport is the main contributor to carbon dioxide emission in logistics industry. The energy intensity and carbon dioxide emission factors were contributing to the reduction of carbon dioxide emission in China’s logistics industry in overall study period.

Originality/value: Although there are a lot of literature analyzed carbon dioxide emission in many industry sectors, for example manufacturing, iron and steel , pulp and paper, cement, glass industry, and so on. However, few scholars researched on carbon dioxide emission in logistics industry. This the first study is in the context of carbon dioxide emission of China’s logistics industry.


Keywords


logistics industry in China, carbon dioxide emission, LMDI

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DOI: http://dx.doi.org/10.3926/jiem.1443


Licencia de Creative Commons 

This work is licensed under a Creative Commons Attribution 4.0 International License

Journal of Industrial Engineering and Management, 2008-2019

Online ISSN: 2013-0953; Print ISSN: 2013-8423; Online DL: B-28744-2008

Publisher: OmniaScience