Optimal timing of carbon capture policies under learning-by-doing |
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Affiliation: | 1. Department of Environmental Biology, Sapienza University of Rome, Italy;2. Department of Botany and Zoology, Masaryk University, Brno, Czech Republic;3. Geography Department, Humboldt-Universität zu Berlin, Germany;4. Integrative Research Institute on Transformations of Human-Environment Systems (IRI THESys), Humboldt-Universität zu Berlin, Germany;5. LSCE-IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif-sur-Yvette, France;6. Department of Ecological Sciences, VU University, 1081 HV Amsterdam, the Netherlands |
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Abstract: | Using a standard Hotelling model of resource exploitation, we determine the optimal energy consumption paths from three options: dirty coal, which is non-renewable and carbon-emitting; clean coal, which is also non-renewable but carbon-free thanks to carbon capture and storage (CCS); and solar energy, which is renewable and carbon-free. We assume that the atmospheric carbon stock cannot exceed an exogenously given ceiling. Taking into account learning-by-doing in CCS technology, we show the following results: (i) clean coal exploitation cannot begin before the outset of the carbon constrained phase and must stop strictly before the end of this phase; (ii) the energy price path can evolve non-monotonically over time; and (iii) when the solar cost is low enough, an unusual energy consumption sequence along with solar energy is interrupted for some time and replacement by clean coal may exist. |
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Keywords: | Climate change Energy substitution Carbon capture and storage Learning-by-doing |
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