A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Decomposition Analysis of Energy-Related CO2 Emissions and Decoupling Status in China’s Logistics Industry
The logistics industry is one of the major fossil energy consumers and CO2 emitters in China, which plays an important role in achieving sustainable development as well as China’s emission reduction targets. To identify the key influencing factors regarding the logistics of CO2 reductions and ensure that the development of China’s logistics industry becomes less dependent on CO2 emissions, this paper built an extended log-mean Divisia index model (LMDI) to decompose the logistics of CO2 changes between 1985 and 2015. Then, we introduced a decoupling model that combined the decomposition results to analyze the decoupling state and identify the main factors that influenced the decoupling relationship. The results show the following. (1) The urbanization effect was the decisive factor in CO2 emissions increases, followed by structural adjustment effects, while technological progress effects played a major role in inhibiting CO2 emissions. Particularly, the energy structure showed great potential for CO2 emissions reduction in China. (2) Highways appeared to have dominant promoting roles in increasing CO2 emissions regarding transportation structure effects; highways and aviation proved to have the largest impact on CO2 emission reduction. (3) There has been an increase in the number of expansive negative decoupling states between 2005 and 2015, which implies that the development of the logistics industry has become more dependent on CO2 emissions. Finally, this paper puts forward some policy implications for CO2 emission reductions in China’s logistics industry.
Decomposition Analysis of Energy-Related CO2 Emissions and Decoupling Status in China’s Logistics Industry
The logistics industry is one of the major fossil energy consumers and CO2 emitters in China, which plays an important role in achieving sustainable development as well as China’s emission reduction targets. To identify the key influencing factors regarding the logistics of CO2 reductions and ensure that the development of China’s logistics industry becomes less dependent on CO2 emissions, this paper built an extended log-mean Divisia index model (LMDI) to decompose the logistics of CO2 changes between 1985 and 2015. Then, we introduced a decoupling model that combined the decomposition results to analyze the decoupling state and identify the main factors that influenced the decoupling relationship. The results show the following. (1) The urbanization effect was the decisive factor in CO2 emissions increases, followed by structural adjustment effects, while technological progress effects played a major role in inhibiting CO2 emissions. Particularly, the energy structure showed great potential for CO2 emissions reduction in China. (2) Highways appeared to have dominant promoting roles in increasing CO2 emissions regarding transportation structure effects; highways and aviation proved to have the largest impact on CO2 emission reduction. (3) There has been an increase in the number of expansive negative decoupling states between 2005 and 2015, which implies that the development of the logistics industry has become more dependent on CO2 emissions. Finally, this paper puts forward some policy implications for CO2 emission reductions in China’s logistics industry.
Decomposition Analysis of Energy-Related CO2 Emissions and Decoupling Status in China’s Logistics Industry
Shiqing Zhang (author) / Jianwei Wang (author) / Wenlong Zheng (author)
2018
Article (Journal)
Electronic Resource
Unknown
Metadata by DOAJ is licensed under CC BY-SA 1.0
Using LMDI to Analyze the Decoupling of Carbon Dioxide Emissions from China’s Heavy Industry
| DOAJ | 2017
Decomposition Analysis and Trend Prediction of CO2 Emissions in China’s Transportation Industry
| DOAJ | 2020
Impact of the Digital Economy on the Carbon Emissions of China’s Logistics Industry
| DOAJ | 2022