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Optimal Timing of CCS Policies with Heterogeneous Energy Consumption Sectors

Abstract

Using the Chakravorty et al. (J Econ Dyn Control 30:2875–2904, 2006) ceiling model, we characterize the optimal consumption paths of three energy resources: dirty oil, which is non-renewable and carbon emitting; clean oil, which is also non-renewable but carbon-free thanks to an abatement technology, and solar energy, which is renewable and carbon-free. The resulting energy-mix can supply the energy needs of two sectors. These sectors differ in the additional abatement cost they have to pay for consuming clean rather than dirty oil, as Sector 1 (industry) can abate its emissions at a lower cost than Sector 2 (transport). We show that it is optimal to begin by fully capturing Sector 1’s emissions before the ceiling is reached. Also, there may be optimal paths along which the capture devices of both sectors must be activated. In this case, Sector’s 1 emissions are fully abated first, before Sector 2 abates partially. Finally, we discuss the way heterogeneity of abatement costs causes sectoral energy price paths to differ.

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Notes

  1. CCS technology consists in filtering \(\text{ CO }_2\) fluxes at the source of the emissions. For this purpose, in fossil energy-fueled power plants for instance, scrubbers are installed next to the top of chimney stacks. Carbon is next sequestered in reservoirs, such as depleted oil and gas fields or deep saline aquifers. However, as mentioned by Herzog (2011), the idea of separating and capturing \(\text{ CO }_2\) from the flue gas of power plants did not originate with climate change concerns. The first commercial CCS plants were built in the late 1970s in the United States to achieve enhanced oil recovery operations, where \(\text{ CO }_2\) is injected into oil reservoirs to increase the pressure and thus the output of the reservoir.

  2. Currently, chemical air capture is probably the most credible process for capturing carbon directly from the atmosphere (Barrett 2009). This technology consists in bringing air into contact with a chemical “sorbent” (an alkaline liquid). The sorbent absorbs \(\text{ CO }_2\) in the air, and the chemical process then separates the \(\text{ CO }_2\) and recycles the sorbent. The captured \(\text{ CO }_2\) is stored in geological deposits just as is done in the case of CCS technology used in power plants. Otherwise, the most obvious way to reduce the atmospheric carbon concentration would be to exploit the process of photosynthesis by increasing forested areas or changing agricultural processes. However, this is not the type of device we want to consider in the present paper.

  3. This result is in accordance with Coulomb and Henriet (2010) who show that in a model with a single abatement technology, when technical constraints make it impossible to capture emissions from all energy consumers, and if such emissions are large enough, CCS should be used before the ceiling is reached.

  4. Since the focus of the paper is on the effect of heterogeneity of abatement costs, all the other sectoral characteristics are assumed to be the same in order to highlight the effects of this sole difference.

  5. \(s_i\) is an average cost per unit of oil and may be seen as a cost of capture and storage. The CCS cost per unit of carbon captured in sector \(i\) amounts to \(s_i/\zeta \). It is assumed to be constant. For non-linear cost functions, see Amigues et al. (2012).

  6. In order to focus on the abatement options for each sector and their respective costs, we ignore the consideration that reservoirs might have limited capacity. The question of the size of carbon sinks and of the time profile for filling them is addressed by Lafforgue et al. (2008a, b) in models with carbon cap, and by Ayong Le Kama et al. (2013) in a model with a standard damage function.

  7. Taking into account non negligible damage for \(Z<\bar{Z}\) would not change the main qualitative properties of the optimal paths as shown in Amigues et al. (2011).

  8. This characteristic is standard under the assumption of a linear natural regeneration process of the atmospheric carbon stock. For non-linear decay functions, see e.g. Toman and Withagen (2000).

  9. Since both \(c_x\) and \(c_y\) are constant, dirty oil and solar energy may only be simultaneously used during a phase at the ceiling. A generalization of this result to the case of a damage function that increases with the atmospheric carbon stock can be found in Hoel and Kverndokk (1996) and Tahvonen (1997). In particular, using a stock-dependent marginal extraction cost, but a constant marginal cost of the backstop, Tahvonen (1997) shows that there can be a multiplicity of simultaneous energy-use scenarios.

  10. See e.g. Chakravorty et al. (2011).

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Acknowledgments

We acknowledge financial support from the French Energy Council (CFE)

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Correspondence to Gilles Lafforgue.

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Amigues, JP., Lafforgue, G. & Moreaux, M. Optimal Timing of CCS Policies with Heterogeneous Energy Consumption Sectors. Environ Resource Econ 57, 345–366 (2014). https://doi.org/10.1007/s10640-013-9683-6

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  • DOI: https://doi.org/10.1007/s10640-013-9683-6

Keywords

  • Energy resources
  • Carbon stabilization cap
  • Heterogeneity
  • Carbon capture and storage
  • Air capture

JEL Classification

  • Q32
  • Q42
  • Q54
  • Q58