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Testing supply-side climate policies for the global steam coal market—can they curb coal consumption?

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Abstract

The achieved international consensus on the 1.5–2 °C target entails that most of current fossil fuel reserves must remain unburned. A major contribution has to come from coal as both the most abundant and the most emission-intensive fuel. Currently, a majority of climate policies aiming at reducing coal consumption are directed towards the demand side. In the absence of a global carbon-pricing regime, these policies are prone to carbon leakage and other adverse effects. Supply-side climate policies present an alternative and increasingly discussed approach to reduce the consumption of fossil fuels. In this article, I employ a numerical model of the international steam coal market to examine two supply-side policies that are currently discussed in academic literature and by policy-makers, alike: (1) a production subsidy reform introduced in major coal-producing countries and (2) a globally implemented moratorium on new coal mines. The model simulates global patterns of coal supply, demand, and international trade, with endogenous investment in coal production and transportation capacities. I find that mere production subsidy removal, while associated with a small positive total welfare effect, leads to a minor reduction of global emissions. By contrast, a mine moratorium induces a much more pronounced reduction in global coal consumption by effectively limiting coal availability and strongly increasing prices. Depending on the specification of reserves, the moratorium can induce a coal consumption path consistent with the 1.5–2 °C target.

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Notes

  1. From here on referred to as 2 °C (goal).

  2. The difference in the two numbers accounts for possible future use of Carbon Capture, Transport and Storage (CCS), a technology which has thus far not lived up to high hopes (Oei and Mendelevitch 2016).

  3. With one major exception, the INDCs submitted by India are not fully incorporated. The original target for solar PV installed until 2022 is reduced to 40 GW (IEA/OECD 2015a, 498), which increases consumption of fossil fuels to cover increasing energy demand, and thus induced an overestimation of coal demand.

  4. Namely, the scenario misses current developments like the peak in coal consumption (NBSC 2015) and a moratorium on new coal power plants and mines in China (see The State Council of the People’s Republic of China (2016) and Boren (2016)), and the banning of coal from the energy mix in a number of European countries like the UK (cf. Rudd 2015).

  5. Though COP23 shows increasing momentum to phase out coal in some economies (cf. global alliance to phase out coal, Powering Past Coal (2017)), concrete policies are needed to bring a global coal phase out about (Piggot et al. 2017).

  6. As argued in Bertram et al. (2015), a policy mix can inter alia help to increase the feasibility of policy measures, as it serves to cushion distributional effects and limit efficiency losses.

  7. See WTO (1994, Article 1) for a formal definition of subsidies as well as Beaton et al. (2013) for a discussion of alternative definitions.

  8. The quality and level of detail of information available for different countries vary significantly. See Appendix 1 for a country-by-country description of the approach to calculate subsidies and employed sources.

  9. Due to the spatial disaggregation of subsidies, the model can also simulate regional substitution between different coal basins, which are affected asymmetrically.

  10. Ideally, one would differentiate between subsidies that affect per-unit marginal production costs versus those lowering investment costs. Due to a lack of data and for reasons of consistency and tractability, all costs are only attributed to the marginal cost items.

  11. For comparison, the EU ETS covered 2084 MtCO2 in 2013 and the amount of certificates is currently targeted to be reduced to 1430 MtCO2 by 2030 (EC 2016). This corresponds to an average reduction of 327 MtCO2 annually, a fourfold of the reduction that I estimate as the effect of subsidy removal.

  12. All monetary values are discounted to 2020, the year when the policy is assumed to be introduced using a discount rate of 10%. There is no anticipation of the policy in the preceding years, as the variables are fixed to “no policy” values for 2010 and 2015.

  13. Until the recent inauguration of President Trump in 2016, the USA, under the Obama Administration, was also pursuing a clear Climate Action Plan (The White House 2013) and enacted a mine moratorium on federal land (Warrick and Eilperin 2016). However, using executive orders, Trump has repealed most of Obama’s climate policies, including the mine moratorium (The White House 2017a). Moreover, he decided to opt-out from the Paris agreement (The White House 2017b) and, against all trends, has committed himself to revitalize the US coal sector.

  14. Their scenario assumes that currently issued licenses where production did not start are revoked and no new licenses are issued; moreover, they account for inter- and infra-fuel substitution.

  15. A detailed description of methodologies for assessing reserves, data origins, and calculation methods can be found in Appendix B. In contrast to BGR (2015) which reports aggregated reserves from various reserve categories and level of confidence, the dataset compiled in Appendix B focusses on reserves in operating mines, with a high degree of confidence. I solely rely on publically available and verifiable sources, and where available, data is collected on the individual mine level. Unfortunately, some of the major producing countries do not report their coal reserves on the required level of detail (see Appendix B for individual assumptions and data limitations).

  16. See Holz et al. (2016) for the implementation of the WEO 450 ppm scenario in COALMOD-World.

  17. See Appendix B for more details and background on this scenario.

  18. For more details on the results of the individual scenarios, please see Appendix B.

  19. China and India were the two single largest importers of steam coal in 2013 (IEA/OECD 2015b) and increase their share of the international steam coal market in the low reserve scenario, as shown in Fig. 1a. For a detailed description of current global coal market trends and more detailed information on India and China, see Oei and Mendelevitch (2018).

  20. Depending on the discount rate and timing of the emissions, EPA reports “social cost of carbon” between US$11/tCO2 and US$95/tCO2 (EPA 2015).

  21. E.g., Forsythe (2016) argues that the current halt of coal-fired power plant construction and coal mines approval in China is rather due to economic reasons than to environmental concerns.

  22. A first attempt in this direction is presented by Kriegler et al. (2016), where the effect of fossil fuel availability on achieving climate targets is examined in a model comparison of three integrated assessment models.

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Acknowledgements

I would like to thank Christian von Hirschhausen, Franziska Holz, Jasper Meya, Pao-Yu Oei, and Fabian Stöckl, as well as the participants of the DIW Brown Bag Seminar and the International Conference on Fossil Fuel Supply and Climate Policy, Oxford, 2016, for helpful discussions and feedback. Moreover, I would like to thank three anonymous referees for their valuable critique and suggestions.

Tim Scherwath provided excellent research assistance. All remaining errors are with the author.

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  1. Humboldt-Universität zu Berlin, Resource Economics Group, Unter den Linden 6, 10099, Berlin, Germany

    Roman Mendelevitch

  2. German Institute for Economic Research (DIW Berlin), Mohrenstrasse 58, 10117, Berlin, Germany

    Roman Mendelevitch

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Correspondence to Roman Mendelevitch.

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This article is part of a Special Issue on ‘Fossil Fuel Supply and Climate Policy’ edited by Harro van Asselt and Michael Lazarus.

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Mendelevitch, R. Testing supply-side climate policies for the global steam coal market—can they curb coal consumption?. Climatic Change 150, 57–72 (2018). https://doi.org/10.1007/s10584-018-2169-3

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