Carbon market maturity analysis with an integrated multi-criteria decision making method: A case study of EU and China

Research output: Contribution to journalArticlepeer-review

Abstract

As a crucial tool to conserve energy utilization and reduce greenhouse gas (GHG) emissions, carbon market has drawn close attention from political circles and academia. A mature carbon market makes the market run orderly and achieve the goal of reducing emissions effectively. It is meaningful to assess the maturity of carbon market. This paper aims at identifying the comprehensive criteria for evaluating the maturity degree of carbon market and proposing a feasible method to evaluate the maturity level of the European Union Emission Trading Scheme (EU ETS) and carbon markets in China. Firstly, this paper proposes 23 specific criteria based on triple bottom line (environmental, economic, and social aspects) to assess the maturity of carbon market. Secondly, we put forward a novel multi-criteria decision approach, which integrates subjective weights and objective weights. Rough set theory is introduced into this method to deal with subjectivity and vagueness problems. Lastly, a case study is applied to assess the maturity level of the EU ETS and carbon markets in China. The results indicate that the EU ETS is currently the most mature carbon trading market. Comparing with the EU ETS, the maturity degrees of carbon markets in China are lower overall. Chinese carbon markets could be divided into three levels according to maturity: Hubei and Guangdong rank the first level; Shenzhen, Beijing and Shanghai rank the second level; Tianjin and Chongqing are at the lowest level.

Original languageEnglish
Article number118296
JournalJournal of Cleaner Production
Volume241
DOIs
StatePublished - 20 Dec 2019

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

Keywords

  • Carbon market
  • Integrated weight
  • Maturity
  • Rough set theory
  • Technique for order preference by similarity to ideal solution

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