Leveraging Integrated Assessment Models to Assess Socioeconomic Impacts of Potential Stratospheric Aerosol Injection

Stratospheric aerosol injection (SAI) is a proposed climate intervention that involves injecting aerosols (or aerosol precursors) into the stratosphere to reduce global warming and associated devastating impacts. In this study, I estimate the socioeconomic effects of future SAI using model results from the Stratospheric Aerosol Geoengineering Large Ensemble (GLENS-SAI) and the Assessing Responses and Impacts of Solar Climate Intervention on the Earth System (ARISE-SAI)  as inputs to the Climate Framework for Uncertainty, Negotiation, and Distribution Integrated Assessment model (FUND). GLENS-SAI and ARISE-SAI are an ensemble of SAI simulations between 2020 and 2100 (GLENS) and 2035-2064 (ARISE-SAI-1.5) using the Community Earth System Model, wherein SAI is simulated to offset the warming produced by a high-emission scenario (RCP 8.5) and a middle of the road (SSP2-4.5). FUND's components include agriculture, forestry, heating, cooling, water resources, tropical and extratropical storms, biodiversity, cardiovascular and respiratory mortality, vector-borne diseases, diarrhea, migration, morbidity, and rising sea levels. These aggregate impacts culminate in net damages, calculated as a percentage of gross domestic product (GDP). In both emission scenarios, global damages take a more linear trend in time, with up to 1% of global GDP loss under SSP2 - 4.5, as opposed to 6% under RCP8.5 (Figure 1). Under GLENS and ARISE SAI, damages follow a beneficial pathway, resulting in up to 0.6% and 1% savings of global GDP, respectively (Figure 1). Significant aspects of net damages include cooling and heating demand, agriculture, and water resources. Whereas cooling costs rise under both warming scenarios, savings accrue from avoided heating costs. However, SAI elicits the opposite effect. Additionally, the Dynamic Integrated Climate-Economy model, a neoclassical IAM, was tailored similarly to give further insight into damages. A nonlinear regression approach was then applied to climate and economic data to validate the results from the integrated assessment models. Finally, a cost-benefit analysis was performed on the GLENS and ARISE scenarios using operational and deployment cost estimates from Wagner and Smith (2018). SAI benefits (savings) are more than sufficient to cover the costs of operation and deployment. Even in the extreme case (GLENS-SAI), cost peaks at around 0.03% of global GDP (Figure 2). This analysis will be pivotal in advising policymakers on the economic outcomes and feasibility of SAI. 

Figure 1 ( Damages as a percentage of global GDP. Left: SSP2-4.5 and ARISE-SAI. Right: RCP8.5 and GLENS-SAI)

Figure 2 (SAI costs as a percentage of Global GDP. Blue: ARISE-SAI, Yellow: GLENS-SAI)

 

References

Smith, W., & Wagner, G. (2018). Stratospheric aerosol injection tactics and costs in the first 15 years of deployment. Environmental Research Letters, 13(12), 124001.