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A counterfactual simulation exercise of CO 2 emissions abatement through fuel-switching in the UK (2008-2012)

Author

Listed:
  • Julien Chevallier
  • Erik Delarue
  • Emeric Lujan
  • William D'haeseleer;

Abstract

This paper uses the E-simulate model of electricity generation to estimate how much the stacking order of different technologies changes when a carbon price is introduced. Different coal and gas price scenarios are explored, and some sensitivity analysis is made of the relative market share of coal and gas under various carbon price levels. The objective of the paper is to estimate how much CO2 reduction could happen in the UK through fuel switching (coal to natural gas) for different carbon price levels during Phase II (2008-2012) of the EU ETS. This country is indeed reported to have the greatest potential within the EU thanks to its suitable fuel mix (39% of coal and 36% of gas in 2007). Our results feature that 27 Mton of CO2/year can be abated at carbon prices around e25/ton (essentially through fuel-switching during the summer), 36 Mton of CO2/year can be abated at carbon prices around e40/ton (in that case, the carbon price triggers fuel-switching during the whole year), and that a maximum of 40 Mton of CO2/year can be achieved at high carbon prices (e125/ton). We also provide various scenarios depending on the relative levels of fuel prices.

Suggested Citation

  • Julien Chevallier & Erik Delarue & Emeric Lujan & William D'haeseleer;, 2012. "A counterfactual simulation exercise of CO 2 emissions abatement through fuel-switching in the UK (2008-2012)," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 35(5), pages 311-331.
    • Handle: RePEc:ids:ijgeni:v:35:y:2012:i:5:p:311-331
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    Cited by:

    1. Abrell, Jan & Kosch, Mirjam & Rausch, Sebastian, 2022. "How effective is carbon pricing?—A machine learning approach to policy evaluation," Journal of Environmental Economics and Management, Elsevier, vol. 112(C).
    2. Jan Abrell & Mirjam Kosch & Sebastian Rausch, 2019. "How Effective Was the UK Carbon Tax? — A Machine Learning Approach to Policy Evaluation," CER-ETH Economics working paper series 19/317, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.

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