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Sectoral marginal abatement cost curves: implications for mitigation pledges and air pollution co-benefits for Annex I countries

Sustainability Science volume 7, pages 169–184 (2012)Cite this article

Abstract

Using the GAINS (Greenhouse Gas–Air Pollution Interactions and Synergies) model, we derived Annex I marginal abatement cost curves for the years 2020 and 2030 for three World Energy Outlook baseline scenarios (2007–2009) of the International Energy Agency. These cost curves are presented by country, by greenhouse gas and by sector. They are available for further inter-country comparisons in the GAINS Mitigation Efforts Calculator—a free online tool. We illustrate the influence of the baseline scenario on the shape of mitigation cost curves, and identify key low cost options as well as no-regret priority investment areas for the years 2010–2030. Finally, we show the co-effect of GHG mitigation on the emissions of local air pollutants and argue that these co-benefits offer strong local incentives for mitigation.

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Notes

  1. The version of the GAINS model we are using covers 36 Annex I countries, which accounted for 96 % of 1990 emissions of the whole of Annex I. In the following we use the label Annex I* for these countries and treat the 27 EU member states as a single party (EU27), though the results are based on country-level modelling.

  2. http://www.unece.org/env/lrtap/.

  3. http://europa.eu/legislation_summaries/environment/air_pollution/l28159_en.htm.

  4. http://gains.iiasa.ac.at.

  5. http://www.capri-model.org/dokuwiki/doku.php.

  6. The fluorinated gases are represented in GAINS by a single gas ‘FGAS’, which is characterized by a global warming potential that is a weighted average of the relevant species in a particular sector and country. Mitigation options reflect the speciation implicitly.

  7. All Annex I countries are represented in GAINS as separate regions. For sub-national analyses in India and China we have developed state/province-level versions of the model in collaboration with national experts, cf. Purohit et al. (2010) and Amann et al. (2008b).

  8. GAINS distinguishes up to 10 distinct climate zones per country.

  9. It is known that individuals and commercial enterprises use higher rates than that of a social planner.

  10. This is true only for technologies with life-times beyond the year 2020.

  11. Contrast this with the 0 and 3 % reduction relative to 1990 by 2020 in the WEO 2007 and WEO 2008 baseline for EU27, respectively.

  12. Hydropower, wind, solar, geothermal. Note that we follow the convention to assign Nuclear power a conversion efficiency of 33%, but 100 % for most renewables, the latter fact explaining partially the increase in primary consumption in 2030 relative to 2005 in the WEO 2009 baseline scenario.

  13. We emphasise again that here we are estimating the economic potential at a given marginal cost. There may be barriers (see below) that prevent agents from choosing options that are economically efficient from a social perspective. In practice, this means that emission reductions to be expected from imposing a carbon price in the form of a tax cannot be read off from the curves in Fig. 5—unless all barriers can be overcome.

  14. For the sake of computational speed we keep the number of points on the curve below 50 and generate curves with 5 €/tCO2eq. steps between 0 and 50 €/tCO2eq. and larger steps above.

  15. We have already indicated above that our cost concept excludes transaction costs, but adequately reflects the social planner’s perspective. In contrast, Stern (2009, p. 50) assumes an average implementation cost of 25 €/tCO2eq. On the basis of this assumption his total cost estimate of 0.8 % of GDP for a 20 GtCO2eq reduction by 2030 amounts to the same as the sum over the implementation costs. Thus, Stern’s calculation suggests that mitigation technology pays for itself, while the real challenge is to reduce transaction costs and to manage institutional change.

  16. The backwards bend of the curve for the Japanese power sector above 100 €/tCO2eq emerges as an accounting effect, when industrial boilers are replaced by combined-heat and power plants. This reduces emissions in industry but increases emissions in the power sector.

  17. Latest figures indicate that this is already taking place now and should be considered to be part of the baseline.

  18. Accessible at http://gains.iiasa.ac.at/MEC/. Registration is required but is free, as is access to all GAINS input data.

  19. An assigned amount unit (AAU) is a tradable 'Kyoto unit' or 'carbon credit' representing an allowance to emit greenhouse gases comprising 1 tonne of CO2eq calculated using their global warming potential.

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Authors and Affiliations

  1. International Institute for Applied Systems Analysis (IIASA), Schlossplatz 1, 2361, Laxenburg, Austria

    Fabian Wagner, Markus Amann, Jens Borken-Kleefeld, Janusz Cofala, Lena Höglund-Isaksson, Pallav Purohit, Peter Rafaj, Wolfgang Schöpp & Wilfried Winiwarter

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  1. Fabian Wagner
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  2. Markus Amann
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  3. Jens Borken-Kleefeld
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  4. Janusz Cofala
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  5. Lena Höglund-Isaksson
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  6. Pallav Purohit
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  7. Peter Rafaj
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  8. Wolfgang Schöpp
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  9. Wilfried Winiwarter
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Correspondence to Fabian Wagner.

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Handled by Tatsuya Hanaoka, National Institute of Environmental Studies, Japan.

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Wagner, F., Amann, M., Borken-Kleefeld, J. et al. Sectoral marginal abatement cost curves: implications for mitigation pledges and air pollution co-benefits for Annex I countries. Sustain Sci 7, 169–184 (2012). https://doi.org/10.1007/s11625-012-0167-3

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Keywords

  • Greenhouse gas mitigation
  • Marginal abatement costs
  • UNFCCC
  • Annex I pledges
  • Co-benefits
  • GAINS model