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Contesting the climate

Security implications of geoengineering

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Abstract

Scientists predict higher global temperatures over this century. While this may benefit some countries, most will face varying degrees of damage. This has motivated research on solar geoengineering, a technology that allows countries to unilaterally and temporarily lower global temperatures. To better understand the security implications of this technology, we develop a simple theory that incorporates solar geoengineering, countergeoengineering to reverse its effects, and the use of military force to prevent others from modifying temperatures. We find that when countries’ temperature preferences diverge, applications of geoengineering and countergeoengineering can be highly wasteful due to deployment in opposite directions. Under certain conditions, countries may prefer military interventions over peaceful ones. Cooperation that avoids costs or waste of resources can emerge in repeated settings, but difficulties in monitoring or attributing interventions make such arrangements less attractive.

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Notes

  1. Solar geoengineering actually encompasses a class of technologies, including stratospheric aerosol scattering, seeking to break links between GHG concentrations and temperatures (Harvard Solar Geoengineering Research Program 2020). In keeping with related social science research, we refer to stratospheric aerosol scattering using the metonym “solar geoengineering” in the remainder of the paper.

  2. We do not discuss normative issues about the deployment of solar geoengineering or countergeoengineering or about the use of conflict to restrict deployment. See Parker (2014) for ongoing ethical debates on the topic.

  3. In the remainder of the paper, we will use deployment as a general term for geoengineering or countergeoengineering applications.

  4. What differentiates geoengineering is that superior military or economic power is not required for deployment. Unilateral application by one of the many actors can have global or regional implications. As we discuss later in the paper, monitoring deployment is also likely to pose additional challenges.

  5. See Vaughan and Lenton (2011) for a review of different proposed methods of deployment.

  6. See Online Supplementary Materials for further description of the properties and their implications.

  7. Further discussion about the relationship between the technology’s properties and challenges in governing it can be found in Online Supplementary Materials. For a more extensive review, see Reynolds (2019).

  8. The “Inquisitive Effect” encourages high deployment levels to distinguish the effects of solar geoengineering from stochastic noise, while “Flexibility Effect” encourages low deployment that can be scaled up if solar geoengineering is effective and produces few side effects.

  9. In decreasing the marginal cost of emissions, solar geoengineering also decreases the credibility of future carbon taxes, prompting firms to under-invest in clean energy technology.

  10. Urpelainen (2012) builds on Millard-Ball (2012)—which considers non-strategic countries making a binary decision about whether to engage in a mitigation treaty—to a pair of strategic countries choosing how much to geoengineer and mitigate.

  11. Both Moreno-Cruz (2010) and Weitzman (2015) refer to countergeoengineering in passing, but neither considers how countergeoengineering would alter countries’ strategic decision-making with respect to solar geoengineering.

  12. These parameters make the model amenable to incorporating differences in actors’ marginal costs and benefits and marginal rates of substitution.

  13. For presentational purposes, we assume that implementation of geoengineering and countergeoengineering are symmetrical, both in terms of deployment costs and overall side effects. Allowing for differential costs and effects (through ki and si) for each technology would not change the substantive conclusions as long as the remaining functional form assumptions are maintained.

  14. The proofs of the propositions are given in the Online Supplementary Materials.

  15. For instance, when \(\tau _A = \tau _B =\bar {\tau } > 0\), and \(k_A = k_B = \bar {k}\), both countries deploy \(g_i = \frac {\bar {\tau }}{k+2}\), resulting in a net temperature that is less than \(\bar {\tau }\).

  16. The choice of conflict to obtain unilateral control over deployment could be interpreted more broadly to include targeted strikes on deployment facilities, the imposition of sanctions on equipment needed to geoengineer, and information campaigns to mobilize domestic opposition to the deployment.

  17. Modeling conflict in this manner as a costly lottery is standard in the international relations literature on bargaining and war. In line with this work, expected outcomes are a function of countries’ balance of power and resolve, which are reflected in their probability of winning and costs of conflict. For examples, see Fearon (1995) and Bas and Coe (2012).

  18. We model conflict only as it pertains to the issue of controlling the climate, so its winner only obtains unilateral control over deployment, nothing else. While we assume that the winner permanently prevents interventions by the opponent, our results extend to temporary controls. Finally, for simplicity of exposition, we do not model crisis bargaining, which can be captured by various cooperative equilibria we analyze in the next section.

  19. One may also argue that states would always seek to resolve Pareto-inferior deployments using peaceful alternatives to conflict, such as imposing economic sanctions or maintaining armament levels for deterrence. While such alternatives may seem less costly than conflict over comparable time-frames, research in international relations suggests that their costs may accumulate when they need to be adopted for long periods of time to maintain peace. See Coe (2019) for an analysis comparing the costs of containment and war prior to the Iraq War in 2003.

  20. According to MacMartin et al. (2019), currently available technology limits the temperature effects of feasible deployment, making them indistinguishable from natural temperature fluctuations in the short run. Temperature changes attributable to deployment may thus require a window of multiple years before they are confidently detected. In our model, this would correspond to a situation with high levels of noise in temperatures, meaning that the variance of \(T \sim F(t | g_A, g_B)\) is high.

  21. In this section, we only consider equilibria in which states condition their behavior on temperatures from the previous period when there is no direct evidence of deployment. That being said, more complicated equilibria in which states make longer term observations of temperature trends over time to dynamically assess past defections from cooperation can also exist.

  22. Such conditional strategies based on simple cutpoints can trivially be a part of an equilibrium as the punishment itself is an equilibrium of the game.

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Acknowledgments

We thank the Weatherhead Initiative on Climate Engineering and the Solar Geoengineering Research Program of Harvard University for support. We also thank Elena McLean, Torben Mideksa, Dustin Tingley, and Gernot Wagner and the participants in Harvard University’s Political Economy workshop for comments on earlier versions of this paper.

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Authors and Affiliations

  1. Associate Professor of Political Science, New York University Abu Dhabi, PO Box 129188, Abu Dhabi, UAE

    Muhammet A. Bas

  2. Dept. of Government, Harvard University, Cambridge, MA, USA

    Aseem Mahajan

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  1. Muhammet A. Bas
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  2. Aseem Mahajan
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Both authors contributed equally to the writing of this manuscript and associated analysis. Authors’ names are listed in alphabetical order.

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Correspondence to Aseem Mahajan.

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Bas, M.A., Mahajan, A. Contesting the climate. Climatic Change 162, 1985–2002 (2020). https://doi.org/10.1007/s10584-020-02758-7

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