The Solar Geoengineering (SG) is an interim solution to combat global warming, which involves scattering back a tiny fraction of the incoming sunlight. Hence, SG and its potential impacts are important to study for the identification of changing weather patterns over regions of climate vulnerable South Asia. This study explores the projected spatio-temporal patterns of two meteorological parameters, temperature, and precipitation, under SG numerical experiment (stratospheric aerosol injection), relative to projected climate change. Furthermore, future projections of same meteorological parameters without SG under a representative concentration pathway (RCP 4.5) will also be studied for comparative analysis. Offsetting climate parameters are associated with multiple risk factors. Thus, Both SG and non-SG scenarios will be studied for the future time period. The results indicate that the temperature reduces by -0.62 °C under the SG G4 scenario and spatial distribution patterns of temperature also depicts an overall cooling effects during the G4 implementation (2020-2029) and continuation (2030-2069) phase. Moreover, on a regional scale, a cold bias (less severe) is projected as compared to projected climate under RCP 4.5. Our findings show that, precipitation is also projected to be decreased by -0.02 mmday-1. Dry bias pattern is projected during implementation phase only. The G4 based SG continuation and termination (2070-2090) phases depict no drastic change in precipitation over South Asia.

Malaria is a disease that has a significant influence on public health and affects individuals all over the Global South. Global warming affects the disease’s distribution, and the Solar Geoengineering (SG) is an interim solution to combat global warming, which involves scattering back a tiny fraction of the incoming sunlight. This study explores the projected spatio-temporal patterns of malaria distribution using Entomological Inoculation Rate (EIR) and Length of Transmission Season (LTS) as quantitative indicators of malaria transmission under G6sulfur scenario of SG in seven of the most climate vulnerable countries of South Asia (Afghanistan, Bangladesh, Bhutan, India, Iran, Nepal, and Pakistan). Furthermore, for comparative analysis, future projections of EIR and LTS are studied without SG under a Shared Socioeconomic Pathway scenario (SSP585). The result of a dynamical malaria model indicates that, under the SG G6sulfur scenario, the spatial distribution patterns of EIR depict an overall decrease in malaria distribution during the period of 2020–2090, as compared to SSP585 scenario, over South Asia. Moreover, LTS of disease will gradually be shortened during the same time scale as in G6sulfur scenario. Regionally, spatial distribution of malaria over Bangladesh, India and Pakistan is projected to experience a significant decline. While Afghanistan, Iran, and Nepal show less drastic but still a notable decrease in EIR.