Research on the correlation network of carbon emissions and economic between Chinese urban agglomerations

Sijia Li, Weiming Chen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Urban agglomerations are currently at the center of China's efforts to reduce carbon emission and sustainable economic development. It is critical to investigate the carbon emissions and economic correlation between urban agglomerations in order to assist their carbon emission reduction and economic coordinated development. This paper is based on an environmentally extended multi-regional input-output model, and studies the embodied carbon emissions and economic two-dimensional correlation network between major urban agglomerations in China from 2012 to 2017. The research results indicate that the production-based carbon emissions of the production and supply of electricity and heat industry in the Yangtze River Delta urban agglomeration were higher than the consumption-based carbon emissions, with a significant gap. However, the construction and service industries were the opposite. The Hohhot-Baotou-Ordos-Yulin urban agglomeration experienced carbon emission losses and economic benefits. The Yangtze River Delta urban agglomeration achieved a win-win situation for carbon emissions and economy. The Pearl River Delta urban agglomeration benefited from carbon emissions but suffered economic losses. The Central Plains urban agglomeration faced a loss-loss situation for carbon emissions and economy. Major urban agglomerations in China should implement differentiated emission reduction measures based on their own characteristics. For example, the Hohhot-Baotou-Ordos-Yulin urban agglomeration should utilize natural resources to develop green industries and high value added industries.

Original languageEnglish
Article number102118
JournalUrban Climate
Volume57
DOIs
Publication statusPublished - Sept 2024

Keywords

  • Carbon emissions
  • Multi-regional input-output model
  • Urban agglomerations
  • Value added

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