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Implications of simultaneously mitigating and adapting to climate change: initial experiments using GCAM

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Abstract

Most research on future climate change discusses mitigation and impacts/adaptation separately. However, mitigation will have implications for impacts and adaptation. Similarly, impacts and adaptation will affect mitigation. This paper begins to explore these two veins of research simultaneously using an integrated assessment model. We begin by discussing the types of interactions one might expect by impact sector. Then, we develop a numerical experiment in the agriculture sector to illustrate the importance of considering mitigation, impacts, and adaptation at the same time. In our experiment, we find that climate change can reduce crop yields, resulting in an expansion of cropland to feed a growing population and a reduction in bioenergy production. These two effects, in combination, result in an increase in the cost of mitigation.

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Notes

  1. There are many models that fall into the middle ground between highly-aggregated IA models and higher-resolution IA models. These models attempt to maintain a balance the goals of the two sorts of models. They can often be used to conduct cost-benefit analysis, but they also maintain some degree of detail in sectors of interest. Some examples of these models of intermediate complexity are MERGE (Clarke et al. 2007) and WITCH (Bosetti et al. 2006).

  2. These values range from 0.25 % per year to 1.4 % per year depending on the region and year.

  3. Previous work (Wise et al. 2009) has shown that the choice in productivity growth estimates has a significant impact on cropland area and land-use change emissions.

  4. We assume that the carbon sequestered while bioenergy is growing offsets the emissions associated with combusting bioenergy. As a result, we treat bioenergy as carbon neutral and thus there is no penalty for its use in the energy system.

  5. Wise et al. (2009) showed that the choice of whether or not to tax CO2 emissions from the terrestrial system has a profound impact on deforestation, bioenergy potential, and the cost of mitigation. We do not explore this phenomenon here and instead only consider a world where terrestrial CO2 emissions are not taxed. It is important to note that climate change can affect the ability of ecosystems, particularly forests, to store carbon. Capturing this effect is critical when considering climate change impacts in any scenario that heavily relies on afforestation as a mitigation measure, like a scenario that taxes terrestrial CO2.

  6. Note that all scenarios include the exogenously specified agricultural productivity growth estimates, which include some shifts in management practices. However, we do not allow additional shifts in management in response to climate change in this paper.

  7. It is important to note that only the effects of land cover change on land-use change emissions are considered in this paper. We do not consider the effects of changing carbon densities of land on carbon emissions.

  8. In this version of GCAM, we assume that demand for grains, produce, and other crops is not responsive to price. Demand for meat and dairy declines as prices rise, but the price elasticity of demand for meat is very low (−0.1 to −0.25 depending on the region) (USDA 2011). We do not allow substitution among the different sources of proteins in this study. However, such substitution would be important to consider if we were to analyze the effects of ocean acidification in addition to the climate effects considered in this paper.

  9. Note that we are not including any effects climate change may have on energy production in this analysis.

  10. Alternatively, one could assume that the carbon price applied to all emissions. In this case, emissions would decline in both the energy system and the terrestrial system. Such a policy environment, while easy to impose in a model, would be difficult to implement in the real world. For this reason, and because of the dramatic land-use changes it induces, we do not consider such a policy here. See Wise et al. (2009) for further discussion.

  11. In absolute terms, the change in fossil fuel and industrial emissions completely offsets the change in LUC emissions. However, because fossil fuel and industrial emissions constitute a larger share of total anthropogenic emissions, the percentage increase/decrease due to climate impacts is smaller for fossil fuel and industrial emissions.

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Acknowledgments

The authors are grateful for support from the Environmental Protection Agency’s Climate Change Division. Additionally, we are grateful for long-term support for the GCAM model from the Department of Energy Office of Science. The opinions expressed in this article are the authors alone.

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Authors and Affiliations

  1. Joint Global Change Research Institute/PNNL, College Park, USA

    Katherine Calvin, Marshall Wise, Leon Clarke, Jae Edmonds, Page Kyle & Allison Thomson

  2. Synapse Energy, Boston, USA

    Patrick Luckow

Authors
  1. Katherine Calvin
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  2. Marshall Wise
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  3. Leon Clarke
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  4. Jae Edmonds
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  5. Page Kyle
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  6. Patrick Luckow
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  7. Allison Thomson
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Correspondence to Katherine Calvin.

Additional information

This article is part of a Special Issue on “Improving the Assessment and Valuation of Climate Change Impacts for Policy and Regulatory Analysis” edited by Alex L. Marten, Kate C. Shouse, and Robert E. Kopp.

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Calvin, K., Wise, M., Clarke, L. et al. Implications of simultaneously mitigating and adapting to climate change: initial experiments using GCAM. Climatic Change 117, 545–560 (2013). https://doi.org/10.1007/s10584-012-0650-y

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