Technical characteristics of a solar geoengineering deployment and implications for governance
Open accessAbstract
Consideration of solar geoengineering as a potential response to climate change will demand complex decisions. These include not only the choice of whether to deploy solar engineering, but decisions regarding how to deploy, and ongoing decision-making throughout deployment. Research on the governance of solar geoengineering to date has primarily engaged only with the question of whether to deploy. We examine the science of solar geoengineering in order to clarify the technical dimensions of decisions about deployment – both strategic and operational – and how these might influence governance considerations, while consciously refraining from making specific recommendations. The focus here is on a hypothetical deployment rather than governance of the research itself. We first consider the complexity surrounding the design of a deployment scheme, in particular the complicated and difficult decision of what its objective(s) would be, given that different choices for how to deploy will lead to different climate outcomes. Next, we discuss the on-going decisions across multiple timescales, from the sub-annual to the multi-decadal. For example, feedback approaches might effectively manage some uncertainties, but would require frequent adjustments to the solar geoengineering deployment in response to observations. Other decisions would be tied to the inherently slow process of detection and attribution of climate effects in the presence of natural variability. Both of these present challenges to decision-making. These considerations point toward particular governance requirements, including an important role for technical experts – with all the challenges that entails.Key policy insights Decisions about solar geoengineering deployment will be informed not only by political choices, but also by climate science and engineering.Design decisions will pertain to the spatial and temporal goals of a climate intervention and strategies for achieving those goals.Some uncertainty can be managed through feedback, but this would require frequent operational decisions.Some strategic decisions will depend on the detection and attribution of climatic effects from solar geoengineering, which may take decades.Governance for solar geoengineering deployment will likely need to incorporate technical expertise for making short-term adjustments to the deployment and conducting attribution analysis, while also slowing down decisions made in response to attribution analysis to avoid hasty choices.
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The SAI adjustment in a volcanic future is not simply one of scale down; SAI injection may need to increase in the opposite hemisphere to the volcanic eruption to ensure a more uniform global temperature.
“However, the SAI adjustment in a volcanic future is not simply one of scale down. SAI injection may need to increase in the opposite hemisphere to the volcanic eruption to ensure a more uniform global temperature (MacMartin et al., 2019)”
From A Fate Worse Than Warming? Stratospheric Aerosol Injection and Global Catastrophic Risk (2021) · cites this paper as MacMartin et al., 2019
Section 4.1 says that after a volcanic eruption it may be wise to decrease SAI injection overall while increasing injection in the opposite hemisphere. It gives the purpose of that opposite-hemisphere increase as counterbalancing effects on tropical precipitation, not ensuring a more uniform global temperature. (LLM, conf=0.86)
Experimental — accuracy not yet measuredSAI should be rapidly scaled down in a matter of weeks in response to a large volcanic eruption.
“SAI should be rapidly scaled down in a matter of weeks (MacMartin et al., 2019).”
From A Fate Worse Than Warming? Stratospheric Aerosol Injection and Global Catastrophic Risk (2021) · cites this paper as MacMartin et al., 2019
SAI deployment dependent on software or advanced algorithmic systems would be vulnerable to cyberattack.
“SAI deployment dependent on any software or advanced algorithmic system (Rolnick et al., 2019; Schroeder de Witt and Hornigold, 2019), which is likely given the high technological and informational demands of deployment (MacMartin et al., 2019), would be vulnerable to cyberattack.”
From A Fate Worse Than Warming? Stratospheric Aerosol Injection and Global Catastrophic Risk (2021) · cites this paper as MacMartin et al., 2019
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- Authors
- MacMartin, D. G., Irvine, P. J., Kravitz, B., & Horton, J. B.
- Affiliations
- Cornell University (US)
- Harvard University (US)
- Pacific Northwest National Laboratory (US)
- Corresponding author
- MacMartin, Douglas G.
- Venue
- Climate Policy
- Publisher
- Informa UK Limited
- Published
- 2019-09-23
- Volume
- 19
- Issue
- 10
- Pages
- 1325-1339
- ISSN
- 1469-3062 (ISSN-L)
- 1752-7457
- OpenAlex
- W2976896012
- Cited by
- 28
- References
- 68
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 5 · 2023: 3 · 2022: 6 · 2021: 4 · 2020: 2 · 2019: 1
- FWCI
- 1.67
- Type
- journal article
- Language
- en
- Open access
- green
- discovery.ucl.ac.uk
- Locations
- Climate Policy (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Physical Sciences › Environmental Science › Global and Planetary Change › Climate Change and Geoengineering
- Physical Sciences › Environmental Science › Global and Planetary Change › Atmospheric aerosols and clouds
- Physical Sciences › Environmental Science › Global and Planetary Change › Sustainability and Climate Change Governance
- Keywords
- solar geoengineering, feedback control, detection and attribution, natural variation, uncertainty management, operational decision-making, climate change mitigation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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