Allocation of carbon emission quotas in Chinese provinces based on Super-SBM model and ZSG-DEA model

Author(s):  
Fang Chen ◽  
Tao Zhao ◽  
Hongmei Xia ◽  
Xiaoyan Cui ◽  
Zhiyuan Li
2019 ◽  
Vol 143 ◽  
pp. 291-298 ◽  
Author(s):  
Jianjun Wu ◽  
Qinghai Guo ◽  
Jiahai Yuan ◽  
Jianyi Lin ◽  
Lishan Xiao ◽  
...  

Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3081 ◽  
Author(s):  
Zeng ◽  
Lu ◽  
Liu ◽  
Zhou ◽  
Hu

With the challenge to reach targets of carbon emission reduction at the regional level, it is necessary to analyze the regional differences and influencing factors on China’s carbon emission efficiency. Based on statistics from 2005 to 2015, carbon emission efficiency and the differences in 30 provinces of China were rated by the Modified Undesirable Epsilon-based measure (EBM) Data Envelopment Analysis (DEA) Model. Additionally, we further analyzed the influencing factors of carbon emission efficiency’s differences in the Tobit model. We found that the overall carbon emission efficiency was relatively low in China. The level of carbon emission efficiency is the highest in the East region, followed by the Central and West regions. As for the influencing factors, industrial structure, external development, and science and technology level had a significant positive relationship with carbon emission efficiency, whereas government intervention and energy intensity demonstrated a negative correlation with carbon emission efficiency. The contributions of this paper include two aspects. First, we used the Modified Undesirable EBM DEA Model, which is more accurate than traditional methods. Secondly, based on the data’s unit root testing and cointegration, the paper verified the influencing factors of carbon emission efficiency by the Tobit model, which avoids the spurious regression. Based on the results, we also provide several policy implications for policymakers to improve carbon emission efficiency in different regions.


2017 ◽  
Vol 87 (3) ◽  
pp. 1453-1468 ◽  
Author(s):  
Feng Dong ◽  
Ruyin Long ◽  
Zhengfu Bian ◽  
Xihui Xu ◽  
Bolin Yu ◽  
...  

Author(s):  
Xiaohong Jiang ◽  
Jianxiao Ma ◽  
Huizhe Zhu ◽  
Xiucheng Guo ◽  
Zhaoguo Huang

Carbon emissions from the logistics industry have been rising year after year. Correct handling of the relationship between economic development and environmental protection is of great significance to the implementation of green logistics, which is an important component of China’s strategy for strong transportation. This paper focuses on the evaluation of the carbon emissions efficiency of logistics industry from a new strong transportation strategy perspective. A super-efficiency slack-based measurement (Super-SBM) model and Malmquist index are combined to evaluate the static and dynamic carbon emissions efficiency of the logistics industry. The results indicate that compared with the SBM model, the Super-SBM model can more effectively measure the carbon emissions efficiency of the logistics industry. Pilot regions for the strong transportation strategy were divided into two categories, namely regions with slow carbon emission growth rates but high efficiency, and regions with high carbon emission growth rates but low efficiency. Some policy recommendations from the strong transportation strategy perspective were proposed to improve the carbon emissions efficiency of the logistics industry, especially for the second category of pilot regions. This study is expected to provide a basis for decision-making for efficient emissions reduction measures and policies, and to encourage the pilot regions to take the lead in achieving the goal of China’s strategy for transportation.


2016 ◽  
Vol 85 (2) ◽  
pp. 1189-1208 ◽  
Author(s):  
Yu-Jie Hu ◽  
Rong Han ◽  
Bao-Jun Tang

2018 ◽  
Vol 152 ◽  
pp. 115-124 ◽  
Author(s):  
Huaping Sun ◽  
Gulzara Tariq ◽  
Hui Chen ◽  
Jin Zhu ◽  
Yue Liu ◽  
...  

2017 ◽  
Vol 24 (8) ◽  
pp. 7088-7113 ◽  
Author(s):  
Xing Zhou ◽  
Xueling Guan ◽  
Ming Zhang ◽  
Yao Zhou ◽  
Meihua Zhou

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