China's transportation sector carbon dioxide emissions efficiency and its influencing factors based on the EBM DEA model with undesirable outputs and spatial Durbin model

被引:149
|
作者
Zhao, Pengjun [1 ,2 ]
Zeng, Liangen [1 ,3 ]
Li, Peilin [4 ,5 ]
Lu, Haiyan [6 ]
Hu, Haoyu [1 ,3 ]
Li, Chengming [7 ]
Zheng, Mengyuan [8 ]
Li, Haitao [9 ]
Yu, Zhao [10 ]
Yuan, Dandan [1 ,3 ]
Xie, Jinxin [1 ,3 ]
Huang, Qi [11 ]
Qi, Yuting [12 ]
机构
[1] Peking Univ, Coll Urban & Environm Sci, Beijing 100871, Peoples R China
[2] Peking Univ, Sch Urban Planning & Design, Shenzhen Grad Sch, Shenzhen 518055, Peoples R China
[3] Peking Univ, Minist Educ, Lab Earth Surface Proc LESP, Beijing 100871, Peoples R China
[4] Chinese Acad Macroecon Res, Beijing 100038, Peoples R China
[5] Natl Dev & Reform Commiss, Inst Spatial Planning & Reg Econ, Beijing 100038, Peoples R China
[6] Harbin Inst Technol, Sch Econ & Management, Shenzhen 518055, Peoples R China
[7] Minzu Univ China, Sch Econ, Beijing 100871, Peoples R China
[8] Peking Univ, Sch Econ, Beijing 100871, Peoples R China
[9] Tsinghua Univ, Dept Int Relat, Beijing 100084, Peoples R China
[10] Beijing Univ Technol, Fac Architecture Civil & Transportat Engn, Beijing 100124, Peoples R China
[11] Peking Univ, Sch Software & Microelect, Beijing 100871, Peoples R China
[12] Delft Univ Technol, Fac Architecture & Built Environm, NL-2628 BL Delft, Netherlands
关键词
Transportation sector carbon dioxide emissions efficiency; Influencing factors; The EBM DEA model With undesirable outputs; Spatial Durbin model; EPSILON-BASED MEASURE; SLACKS-BASED MEASURE; ENVIRONMENTAL EFFICIENCY; ENERGY EFFICIENCY; CO2; EMISSIONS; PASSENGER TRANSPORT; INFRASTRUCTURE; PERFORMANCE; IMPACT;
D O I
10.1016/j.energy.2021.121934
中图分类号
O414.1 [热力学];
学科分类号
摘要
The threat of global climate change has caused the international community to pay close attention to atmospheric levels of greenhouse gases such as carbon dioxide. Transportation sector carbon dioxide emissions efficiency (TSCDEE) is a key indicator used to prioritize sustainable development in the transportation sector. In this paper, the epsilon-based measure data envelopment analysis model with undesirable outputs is applied to estimate TSCDEE for 30 provinces in China from 2010 to 2016. We also analyze influencing factors using the spatial Durbin model. Research shows that the overall TSCDEE of the Chinese provinces studied was 0.618, indicating that most regions are still in need of improvements. The provinces with the highest TSCDEE are located in developed coastal regions of China. This study shows that factors such as transportation structure, traffic infrastructure level, and technological progress have prominent positive effects on TSCDEE, while both urbanization level and urban population density exert significantly negative effects on TSCDEE. The findings should have a far-reaching impact on the sustainable development of global transportation. (c) 2021 Elsevier Ltd. All rights reserved.
引用
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页数:17
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