Back to Search Start Over

Regional disparities and influencing factors of Average CO 2 Emissions from transportation industry in Yangtze River Economic Belt

Authors :
Shan Huang
Huiyuan Jiang
Shengrong Lu
Yao Liu
Source :
Transportation Research Part D: Transport and Environment. 57:112-123
Publication Year :
2017
Publisher :
Elsevier BV, 2017.

Abstract

Transportation industry is an important source of CO2 emissions, and has become the third largest energy consuming industry in China. Most existing researches studied regional disparities and influencing factors of Total CO2 Emissions from transportation industry, while limited researches studied the average amount specially. Based on the relevant data of Yangtze River Economic Belt from 2005 to 2014, Theil index was utilized to measure the regional disparities of Average CO2 Emissions from three aspects: CO2 emissions per capita (CEPC), CO2 emissions intensity (CEI) and CO2 emissions per converted transportation turnover (CEPT). Combining with extended Kaya identity, LMDI decomposition method was applied to analyze the influencing factors of CEPC, CEI and CEPT respectively. The empirical results indicate that regional disparities of CEPC, CEI and CEPT do exist and they are on downtrend after 2011. Regional disparity of CEPC is more significant than CEI and CEPT. Energy structure and energy intensity contribute to increasing CEPC and decreasing CEI and CEPT. Added-value per converted transportation turnover has positive effect on increasing CEPC and decreasing CEPT. Transportation intensity inhibits increasing CEPC, while economic level plays the most important positive role in increasing CEPC. The findings implicate that governments should transform the economic development mode, optimize the energy structure, improve transportation efficiency and develop differential policies according to practical situations.

Details

ISSN :
13619209
Volume :
57
Database :
OpenAIRE
Journal :
Transportation Research Part D: Transport and Environment
Accession number :
edsair.doi...........ea93163c3cbffe17003cdc6b75d8758b