Skip to main navigation Skip to search Skip to main content

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
  • , Dandan Yuan
  • , Jinxin Xie
  • , Qi Huang
  • , Yuting Qi
  • *Corresponding author for this work
  • Peking University
  • Ministry of Education of the People's Republic of China
  • Chinese Academy of Macroeconomic Research
  • National Development and Reform Commission of China
  • School of Economics and Management, Harbin Institute of Technology Shenzhen
  • Minzu University of China
  • Tsinghua University
  • Beijing University of Technology
  • Delft University of Technology

Research output: Contribution to journalArticlepeer-review

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
JournalEnergy
Volume238
DOIs
StatePublished - 1 Jan 2022
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  2. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities
  3. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

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

Fingerprint

Dive into the research topics of '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'. Together they form a unique fingerprint.

Cite this