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Linking reduced deforestation and a global carbon market: implications for clean energy technology and policy flexibility

Published online by Cambridge University Press:  08 February 2011

VALENTINA BOSETTI
Affiliation:
Sustainable Development Unit, Fondazione Eni Enrico Mattei (FEEM) and Climate Impacts and Policy Division of the EuroMediterranean Center on Climate Change (CMCC), Fondazione Eni Enrico Mattei, Corso Magenta 63, Milan, Italy. Tel: +39 02 52036916. Fax: +39 02 52036946. Email: [email protected]
RUBEN LUBOWSKI
Affiliation:
Environmental Defense Fund (EDF), 1875 Connecticut Avenue NW, Washington, DC 20009, USA. Email: [email protected]
ALEXANDER GOLUB
Affiliation:
Environmental Defense Fund (EDF), 1875 Connecticut Avenue NW, Washington, DC 20009, USA. Email: [email protected]
ANIL MARKANDYA
Affiliation:
Basque Center for Climate Change (BC3) and University of Bath, Basque Center for Climate Change – Klima Aldaketa Ikergai, Gran Vía 35, 2, Bilbao, Spain. Email: [email protected]

Abstract

This study uses a global climate-energy-economy model to investigate potential implications of linking credits from reducing emissions from deforestation and forest degradation in developing countries to a global carbon market, focusing on reducing emissions from deforestation (RED) and effects on energy technology innovation. Integrating RED into a global carbon market lowers the estimated total costs of a policy to achieve 535 ppmv of CO2-equivalent concentrations in 2100 by up to 25 per cent. Alternatively, a global RED program could enable additional reductions of about 20 ppmv by 2100 with no added costs compared with an energy-sector-only policy. The results indicate that market linkage of RED induces modest reductions in clean energy innovation overall but slightly enhances development of particular technologies, including carbon capture and storage. We also find that RED in combination with credit banking encourages greater mitigation in the near term, enhancing flexibility to potentially tighten emission targets at lower cost in response to future information.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2011

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