Allocation of carbon emission responsibility among Chinese cities guided by economic welfare gains: Case study based on multi-regional input-output analysis

Kun Zhang, Yiyi Cao, Zhouyi Liu, Qi Zhou*, Shen Qu, Yi Ming Wei

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

Ensuring equitable allocation of carbon emission responsibilities at the city level is crucial for effectively mitigating climate change. However, traditional allocation methods like production-based accounting (PBA) and consumption-based accounting (CBA) encounter double-counting problems at this scale. This study for the first time addressed the ignored externality of carbon emissions among bilateral trading partners at city scale, achieving equitable carbon emission responsibility reallocations using the economic welfare gain-based (EWG) method. Examining 313 cities in China using a multi-regional input-output model, the highest carbon emission responsibilities are identified in Baotou at 400.7 Mt., followed by Yunnan (189.9 Mt) and Dalian (166.7 Mt). In this case, the EWG method reallocates producer and consumer responsibilities in bilateral trades. Among the 313 cities, emission responsibilities from 198 are situated between PBA and CBA, avoiding one-sided assignment of emissions based solely on either principle. A comparative analysis of allocation methods in China further indicates a predominance of production responsibility, mirroring a similar trend between EWG and PBA; a significant portion of producer responsibilities are identified within EWG. The results of this work may offer a fairer and economically sound basis for allocating emission responsibilities among cities, thereby facilitating more effective emission reduction strategies.

Original languageEnglish
Article number124252
JournalApplied Energy
Volume376
DOIs
Publication statusPublished - 15 Dec 2024

Keywords

  • Bilateral trade
  • Economic welfare
  • Emissions accounting
  • Environmental externality
  • Multiregional input-output modeling

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