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Reduction targets and abatement costs of developing countries resulting from global and developed countries’ reduction targets by 2050

Mitigation and Adaptation Strategies for Global Change volume 18, pages 491–512 (2013)Cite this article

Abstract

The European Union (EU) has advocated an emission reduction target for developed countries of 80% to 95% below the 1990 level by 2050, and a global reduction target of 50%. Developing countries have resisted the inclusion of these targets in both the UN Framework Convention on Climate Change Copenhagen Accord and Cancún Agreements. This paper analyses what these targets would imply for emission targets, abatement costs and energy consumption of developing countries, taking into account the conditional emission reduction pledges for 2020. An 80% reduction target for developed countries would imply more stringent per capita emission targets for developing countries than developed countries by 2050. Moreover, abatement costs of developing countries would be higher than those of developed countries. An 85% to 90% reduction target for developed countries would result in similar per capita emission targets and abatement costs for developed and developing countries by 2050. Total reduction targets for developing countries would range from 30% to 40% below 2005 levels by 2050 and from 30% to 35% above 2005 levels by 2030. The 2030 target for China would be 40% to 45% above 2005 levels, compared to a target for the EU of 45% to 50% below 1990 and for the United States of America (USA) 30% to 35% below 1990. Emission target trajectories for Brazil, South Africa and China would peak before 2025 and for India by around 2025. From the analysis, we may conclude that from the viewpoint of developing countries either developed countries increase their target above 85%, and/or make substantial side-payments.

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Notes

  1. 1.

    Defined as the Annex I Parties of the Kyoto Protocol, consisting of the 1997 list of the developed countries and the emerging market economies of Central and Eastern Europe.

  2. 2.

    CO2 equivalent emissions in this paper refer to the global warming potential-weighted sum of six Kyoto greenhouse gas emissions.

  3. 3.

    The model framework applied in this study accounts for the full life cycle of biofuels, including secondary emissions from fertilizer use among others, as described in van Vuuren et al. (2010b).

  4. 4.

    It should be noted that the analysis presented throughout this paper (including the allocation calculations) focuses on countries’ emissions at production level, which is most common in literature. Emissions on consumption rather than production basis may lead to substantially different results. For example, Chinese emissions have been growing rapidly, partly due to increased exports (Pan et al. 2008), which accounted for about 30% of total 2006 CO2 emissions.

  5. 5.

    Note that an even more stringent target than 60% is technically not feasible in our model framework.

  6. 6.

    The common-but-differentiated convergence approach is a continuation of the Kyoto approach, and variants have also been studied widely, for example, in the Garnaut Climate Change Review (Garnaut 2008).

  7. 7.

    This is also recognised by the IPCC AR4 (Gupta et al. 2007), i.e. “For many countries, the overall target set is critical; it dictates the emissions reduction requirements more specifically than does the approach chosen to meet that target.”. The IPCC also reports that this does not hold for extreme allocation approaches in which for instance the developed undertakes most of the reductions, like the approach of equal cumulative per capita emissions over time (e.g. Ding et al. 2009; He et al. 2009).

  8. 8.

    These are developing countries with a relatively high income per capita and include Mexico, South Africa, Kazakhstan, South Korea, China and all South American countries.

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Acknowledgements

The project was financed by the Dutch Ministry of Infrastructure and the Environment. The contribution of AH has been supported by the RESPONSES project, co-funded by the European Commission within the 7th Framework Programme.

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  1. PBL Netherlands Environmental Assessment Agency, P.O. Box 303, 3720 AH, Bilthoven, The Netherlands

    Michel G. J. den Elzen, Angelica Mendoza Beltran, Andries F. Hof, Bas van Ruijven & Jasper van Vliet

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  1. Michel G. J. den Elzen
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  2. Angelica Mendoza Beltran
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Corresponding author

Correspondence to Michel G. J. den Elzen.

Appendix A: Model description of IMAGE and TIMER

Appendix A: Model description of IMAGE and TIMER

A.1 The IMAGE land use model

Greenhouse gas emissions related to land-use changes are calculated by the IMAGE model. The IMAGE model is an integrated assessment model with 26 regions as well, consisting of a set of linked and integrated models, which, together, describe important elements in the long-term dynamics of global environmental change, such as air pollution, climate change, and land-use change (Bouwman et al. 2006). The model includes detailed descriptions of the energy system and food consumption and production, using TIMER and agricultural trade and production models. The land-cover submodels simulate the change in land-use and land cover, at 0.5 × 0.5° (driven by demand for food, timber and bioenergy, and changes in climate). The demand for agricultural products is based on scenarios from agro-economic models. A crop module computes the spatially explicit yields for the different crop groups and for grasses, as well as the areas used for their production, as determined by climate and soil quality. Where expansion of agricultural areas is required, a rule-based ‘suitability map’ determines which grid cells are selected. Land-use related emissions occur from both land use and land-use change.

A.2 The TIMER energy model

The TIMER energy model is an energy-system model that is part of the IMAGE integrated assessment framework. TIMER describes the long-term dynamics of the production and consumption of about 10 primary energy carriers for 5 end-use sectors (industry, transport, residential, services and other) in 26 world regions (van Vuuren et al. 2010b). The model’s behaviour is mainly determined by substitution processes of various technologies based on long-term prices and fuel preferences. These two factors drive multinomial logit models that describe investments in new energy production and consumption capacity. The demand for new capacity is limited by the assumption that capital is only replaced at the end of the economic lifetime. The long-term prices that drive the model are determined by resource depletion and technological development. Resource depletion is important for fossil fuels (for which depletion and costs depend on annual production rates). Bio-energy is available as a substitute of fossil fuels for both liquid fuel and thermal generation. Technological development is determined by learning curves or through exogenous assumptions. Emissions from the energy system are calculated by multiplying energy consumption and production flows with emission factors. A carbon tax can be used to induce a dynamic response such as increased use of low or zero-carbon technologies, energy efficiency improvement and end-of-pipe emission reduction technologies.

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den Elzen, M.G.J., Beltran, A.M., Hof, A.F. et al. Reduction targets and abatement costs of developing countries resulting from global and developed countries’ reduction targets by 2050. Mitig Adapt Strateg Glob Change 18, 491–512 (2013). https://doi.org/10.1007/s11027-012-9371-9

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Keywords

  • Cancún agreements
  • Climate change
  • Copenhagen accord
  • Developing countries
  • Greenhouse gas emissions
  • Long term targets
  • Mitigation