Spatiotemporal Distribution of CO2 Emissions from the Logistics Industry in the China Segment of the Silk Road Economic Belt and Its Influencing Factors

Aixia Xu (), Zhixian Liang and Guanxiong Huang
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Aixia Xu: Software Engineering Institute of Guangzhou
Zhixian Liang: Software Engineering Institute of Guangzhou
Guanxiong Huang: Software Engineering Institute of Guangzhou

A chapter in Proceedings of the 2024 6th Management Science Informatization and Economic Innovation Development Conference (MSIEID 2024), 2025, pp 833-849 from Springer

Abstract: Abstract Based on the calculation of high carbon energy CO2 emissions in the logistics industry of six provinces in the Chinese section of the Silk Road Economic Belt from 2013 to 2022, this article uses Logarithmic Mean Divisia Index and Multi-Region model to analyze the influencing factors of the differences in high carbon energy CO2 emissions in the logistics industry from both temporal and spatial dimensions. The results show that over the past decade, the high carbon energy CO2 emissions from the logistics industry in the six provinces of the Silk Road Economic Belt in China have mainly gone through three stages: high-speed growth period (2013–2014), stable growth period (2015–2019), and fluctuating decline period (2020–2022). The peak was reached in 2019, and logistics output was the main factor driving CO2 emissions. Energy structure, energy intensity, and employment scale were inhibitory factors, but their contribution was not significant. The average level of CO2 emissions in the logistics industry of the six provinces is ranked as follows: Sichuan > Yunnan > Guangxi > Shaanxi > Gansu > Qinghai. The scale of employment and logistics intensity in Sichuan have a positive effect, while only the scale of employment in Yunnan maintains a negative effect. Guangxi’s energy structure and logistics output are driving factors, Shaanxi’s logistics industry scale is the only factor driving CO2 emissions, and Gansu and Qinghai’s logistics industry CO2 emissions are driven by energy structure.

Keywords: Silk Road Economic Belt; CO2 emissions in the logistics industry; LMDI decomposition model; Multi-Region model (search for similar items in EconPapers)
Date: 2025
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DOI: 10.2991/978-94-6463-676-5_80

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