Self-organized global control of carbon emissions

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

Date Published: 2010-09-01

DOI: 10.1016/j.physa.2010.04.011

Sponsors: Research Grants Council of Hong Kong

Platforms: No platforms listed

Model Documentation: Other Narrative Flow charts

Model Code URLs: Model code not found

Abstract

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. (C) 2010 Elsevier B.V. All rights reserved.

Tags

Agent-based model Competition Self-organized