Open Access
Decomposition analysis: Carbon emissions in China’s transportation sector
Author(s) -
Xiao Yan,
Zhongyun Zhang,
Zhehuan Wei,
Xiao Huang,
Peng Peng
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/467/1/012168
Subject(s) - greenhouse gas , china , transport engineering , unit (ring theory) , emission intensity , driving factors , energy intensity , carbon fibers , environmental economics , business , index (typography) , environmental science , public transport , global warming , climate change , natural resource economics , efficient energy use , engineering , economics , geography , computer science , ecology , mathematics , excitation , mathematics education , electrical engineering , archaeology , algorithm , composite number , world wide web , biology
In order to deal with global warming and control carbon emissions, it is of great importance to identify the factors and their impact on the growth of carbon emission in the transportation sector. In this paper, the situation of carbon emissions in China’s transportation sector during 1996-2013 has been discussed and the decomposition analysis has been carried out by using the generalized Fisher index (GFI) method. It is found that: (i) Economic growth, energy intensity, population size and transportation intensity have positive effect on the growth of carbon emissions. (ii) Output value of per unit traffic turnover and energy structure have negative effects, among them, the former is the primary factor and the latter has an unobvious inhibition effect. We put forward suggestions to develop low-carbon transportation in China including to encourage people to adopt new energy vehicles in the passenger transport area, to utilize new energy vehicles in road freight and new energy ships in water freight, to encourage public and shared transportation, and promote the infrastructure construction of national multimodal transport.