Self-organized global control of carbon emissions

Zhenyuan Zhao, Daniel J. Fenn, Pak Ming Hui, Neil F. Johnson

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


There is much disagreement concerning how best to control global carbon emissions. We explore quantitatively how different control schemes affect the collective emission dynamics of a population of emitting entities. We uncover a complex trade-off which arises between average emissions (affecting the global climate), peak pollution levels (affecting citizens' everyday health), industrial efficiency (affecting the nation's economy), frequency of institutional intervention (affecting governmental costs), common information (affecting trading behavior) and market volatility (affecting financial stability). Our findings predict that a self-organized free-market approach at the level of a sector, state, country or continent can provide better control than a top-down regulated scheme in terms of market volatility and monthly pollution peaks. The control of volatility also has important implications for any future derivative carbon emissions market.

Original languageEnglish (US)
Pages (from-to)3546-3551
Number of pages6
JournalPhysica A: Statistical Mechanics and its Applications
Issue number17
StatePublished - Sep 1 2010
Externally publishedYes


  • Agent-based model
  • Competition
  • Self-organized

ASJC Scopus subject areas

  • Statistics and Probability
  • Condensed Matter Physics


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