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Title: Decomposing long-run carbon abatement cost curves : robustness and uncertainty
Author: Kesicki, F. A.
ISNI:       0000 0004 2728 3805
Awarding Body: University College London (University of London)
Current Institution: University College London (University of London)
Date of Award: 2012
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Policy makers in the United Kingdom (UK), as in many countries around the world, are confronted with a situation of legally binding commitments to reduce carbon emissions. In this context it remains an open question of how to find a cost-efficient approach to climate change mitigation. Marginal abatement cost (MAC) curves have already been applied to help understand the economics of many different environmental problems and can likewise assist with illustrating the economics of climate change mitigation. Current approaches to generate MAC curves rely mostly on the individual assessment of each abatement measure, which are then ranked in order of decreasing cost-efficiency. These existing ways of generating MAC curves fail to allow both the graphical representation of the technological detail and the incorporation of system-wide behavioural, technological, and intertemporal interactions. They also fail to provide a framework for uncertainty analysis. This dissertation addresses these shortcomings by proposing a new approach to deriving MAC curves through the combination of an integrated energy system model, UK MARKAL, and index decomposition analysis. The energy system model is used to capture system-wide interactions, while decomposition analysis permits the analysis of measures responsible for emissions reduction. Sensitivity analysis and stochastic modelling are also employed to represent how sensitive the measures are to variations of the underlying drivers and assumptions, as well as how they interact. With a focus on the UK and the year 2030, as an important intermediate emissions reduction target, system-wide MAC curves are presented accompanied by a detailed analysis of the power, transport, and the residential sectors. This analysis allows important insights to be made into the economics of emissions mitigation, as well as investigating the robustness of findings. The results of the dissertation project represent a suitable orientation base for decision making in long-term climate policy.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available