Published March 2007 | Version v1
Journal article

Climate modelling with endogenous technical change: Stochastic learning and optimal greenhouse gas abatement in the PAGE2002 model

  • 1. Judge Business School, University of Cambridge, Trumpington Street, Cambridge CB2 1AG (United Kingdom)

Description

This paper looks at the impact of ETC on the costs and benefits of different abatement strategies using a modified version of the PAGE2002 model. It was found that for most standard abatement paths there would be an initial 'learning investment' required that would substantially reduce the unit costs of CO2 abatement as compared to a business as usual scenario. Furthermore, optimising an abatement program where ETC has been included leads to an increase in cost uncertainty during the period of widespread CO2 abatements due to our lack of knowledge of the learning investments involved. Finally, the inclusion of ETC leads to a slightly deferred optimised abatement path followed by a rapid abatement program. Together, the results draw attention to the possibilities of 'uncovering uncertainty' through proactive abatements. 'Learning about learning' could become an important consideration for any plan to optimise future abatements

Additional details

Identifiers

DOI
10.1016/j.enpol.2006.05.015;
PII
S0301-4215(06)00254-0;

Publishing Information

Journal Title
Energy Policy
Journal Volume
35
Journal Issue
3
Journal Page Range
p. 1795-1807
ISSN
0301-4215
CODEN
ENPYAC

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
38031533
Subject category
S54: ENVIRONMENTAL SCIENCES; S29: ENERGY PLANNING, POLICY AND ECONOMY;
Descriptors DEI
CARBON DIOXIDE; CLIMATIC CHANGE; COST; GREENHOUSE GASES; INVESTMENT; LEARNING
Descriptors DEC
CARBON COMPOUNDS; CARBON OXIDES; CHALCOGENIDES; OXIDES; OXYGEN COMPOUNDS

Optional Information

Copyright
Copyright (c) 2006 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.