Solar geoengineering could redistribute malaria risk in developing countries

Abstract

Solar geoengineering is often framed as a stopgap measure to decrease the magnitude, impacts, and injustice of climate change. However, the benefits or costs of geoengineering for human health are largely unknown. We project how geoengineering could impact malaria risk by comparing current transmission suitability and populations-at-risk under moderate and high greenhouse gas emissions scenarios (Representative Concentration Pathways 4.5 and 8.5) with and without geoengineering. We show that if geoengineering deployment cools the tropics, it could help protect high elevation populations in eastern Africa from malaria encroachment, but could increase transmission in lowland sub-Saharan Africa and southern Asia. Compared to extreme warming, we find that by 2070, geoengineering would nullify a projected reduction of nearly one billion people at risk of malaria. Our results indicate that geoengineering strategies designed to offset warming are not guaranteed to unilaterally improve health outcomes, and could produce regional trade-offs among Global South countries that are often excluded from geoengineering conversations.

Fig. 1. Thermal suitability for malaria.

Suitability is measured by a scaled thermal suitability R₀(T), which ranges between zero and one as a function of mean daily temperature, averaged across a full year (every day in 2020 or 2070). Values are mapped for the present day (A, B), future scenarios without geoengineering (C, D), and future scenarios with geoengineering (E, F).

Fig. 2. Impacts of solar geoengineering on malaria transmission.

Values are given as the difference in scaled thermal suitability R₀(T) between different scenarios, where a higher positive value indicates that the geoengineering scenario creates greater thermal suitability for malaria transmission. Geoengineering scenarios are compared to future scenarios with climate change (A, B), and compared to the present day (C, D).

Fig. 3. Global population at risk from malaria.

Population at highest risk is given as the global total of stable risk (6 months or more of suitability) for both falciparum and vivax malaria. Scenarios are paired between baseline scenarios and geoengineering scenarios, where solar radiation management deployment is modeled in the G3 scenario relative to Representative Concentration Pathway (RCP) 4.5, and in the Geoengineering Large Ensemble (GLENS) scenario relative to RCP 8.5. Each value is averaged across three scenario-specific runs from a climate model ensemble. (Note that while three scenarios in the two panels follow superficially similar trajectories, the use of different Shared Socio-economic Pathways [SSPs] paired with the RCPs makes results incomparable between RCP 4.5 and RCP 8.5 based scenarios.).