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

Pengjun Zhao, Liangen Zeng, Peilin Li, Haiyan Lu, Haoyu Hu, Chengming Li, Mengyuan Zheng, Haitao Li, Zhao Yu, Yuting Qi, More Authors

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Article number121934
Number of pages17
JournalEnergy
Volume238
DOIs
Publication statusPublished - 2022

Keywords

  • Influencing factors
  • Spatial Durbin model
  • The EBM DEA model With undesirable outputs
  • Transportation sector carbon dioxide emissions efficiency

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