Carbon dioxide emissions reduction in China's transport sector: A dynamic VAR (vector autoregression) approach

被引:145
作者
Xu, Bin [1 ,2 ]
Lin, Boqiang [3 ,4 ]
机构
[1] Jiangxi Univ Finance & Econ, Sch Stat, Nanchang 330013, Jiangxi, Peoples R China
[2] Jiangxi Univ Finance & Econ, Res Ctr Appl Stat, Nanchang 330013, Jiangxi, Peoples R China
[3] Xiamen Univ, China Inst Studies Energy Policy, Collaborat Innovat Ctr Energy Econ & Energy Polic, Xiamen 361005, Fujian, Peoples R China
[4] Minjiang Univ, Newhuadu Business Sch, Fuzhou 350108, Fujian, Peoples R China
关键词
Transport sector; Carbon dioxide emissions; Vector autoregression model; GREENHOUSE-GAS EMISSIONS; CO2; EMISSIONS; ENERGY-CONSUMPTION; ROAD TRANSPORT; ECONOMIC-GROWTH; STIRPAT MODEL; POLICY; POPULATION; COINTEGRATION; DECOMPOSITION;
D O I
10.1016/j.energy.2015.02.052
中图分类号
O414.1 [热力学];
学科分类号
摘要
Energy saving and carbon dioxide emission reduction in China is attracting increasing attention worldwide. At present, China is in the phase of rapid urbanization and industrialization, which is characterized by rapid growth of energy consumption. China's transport sector is highly energy-consuming and pollution-intensive. Between 1980 and 2012, the carbon dioxide emissions in China's transport sector increased approximately 9.7 times, with an average annual growth rate of 7.4%. Identifying the driving forces of the increase in carbon dioxide emissions in the transport sector is vital to developing effective environmental policies. This study uses Vector Autoregressive model to analyze the influencing factors of the changes in carbon dioxide emissions in the sector. The results show that energy efficiency plays a dominant role in reducing carbon dioxide emissions. Private vehicles have more impact on emission reduction than cargo turnover due to the surge in private car population and its low energy efficiency. Urbanization also has significant effect on carbon dioxide emissions because of large-scale population movements and the transformation of the industrial structure. These findings are important for the relevant authorities in China in developing appropriate energy policy and planning for the transport sector. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:486 / 495
页数:10
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