Abstract
Deep emission cuts rely on the use of low carbon technologies like renewable energy or carbon capture and storage. There is considerable uncertainty about their future costs. We carry out a sensitivity analysis based on Gauss Quadrature for cost parameters describing these technologies in order to evaluate the effect of the uncertainty on total and marginal mitigation costs as well as composition changes in the energy system. Globally, effects in total cost often average out, but different regions are affected quite differently from the underlying uncertainty in costs for key abatement technologies. Regions can be either affected because they are well suited to deploy a technology for geophysical reasons or because of repercussions through international energy markets. The absolute impact of uncertainty on consumption increases over the time horizon and with the ambition of emission reductions. Uncertainty in abatement costs relative to expected abatement costs are however larger under a moderate ambition climate policy scenario because in this case the marginal abatement occurs in the electricity sector where the cost uncertainty is implemented. Under more ambitious climate policy in line with the two degree target, the electricity sector is always decarbonized by 2050, hence uncertainty has less effect on the electricity mix. The findings illustrate the need for regional results as global averages can hide distributional consequences on technological uncertainty.
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Notes
Using economic models to estimate costs from mitigation actions became more widespread with analyses of the Kyoto protocol (Weyant et al. 1999). In recent years, new model generations have improved especially their representation of the energy sector.
One reason for the importance for CCS compared with renewables is the possibility to use CCS to abate process emissions from industry not resulting from burning of fossil fuels (Akashi et al. 2014). Furthermore, in combination with biomass, CCS can lead to net negative emissions which are important in many long-term emission scenarios (Koelbl et al. 2014).
The LES separates consumption into basic consumption and utility generating consumption. Consumption changes here only refer to the latter.
Cost uncertainties for wind and solar also affect fossil fuel prices, although to a much lower extend because global emissions are held constant in all scenarios, thus shutting off any large quantity reaction for fossil fuels.
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Acknowledgments
I would like to thank Sonja Peterson for helpful discussions and Michael Rose for research assistance. The manuscript has benefited from comments provided by participants of several project workshops, the 17th Annual Conference on Global Economic Analysis in Dakar, Senegal and the 2014 NCAR IAM Annual Meeting in Boulder, CO. Funding by the German Federal Ministry of Education and Research (reference 01LA1127C) is acknowledged.
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Appendices
Appendix 1
Appendix 2
Appendix 3
Cost of electricity generation from coal and gas with CCS relative to generation without CCS. Standard deviations of cost markup are represented by error bars
Appendix 4
Electricity generation in terawatt hours in expectations accounting for uncertainty in CCS, wind, and solar in 2050 in different regions and different climate policy scenarios
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Weitzel, M. The role of uncertainty in future costs of key CO2 abatement technologies: a sensitivity analysis with a global computable general equilibrium model. Mitig Adapt Strateg Glob Change 22, 153–173 (2017). https://doi.org/10.1007/s11027-015-9671-y
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DOI: https://doi.org/10.1007/s11027-015-9671-y