The increasing severity of impacts from anthropogenic climate change, including extreme weather and large-scale wildfires, has spurred interest in various approaches to climate intervention or geoengineering. Besides efforts at carbon dioxide removal (CDR) and achieving net-zero emissions through enhanced carbon uptake, sequestration, and transitioning to renewable energy, there is rising interest in stabilizing global surface temperatures. Stratospheric aerosol injection (SAI), involving sulfur dioxide (SO₂) injection into the lower stratosphere, is considered the most feasible option to significantly impact surface temperature. In our research, we quantify the benefits and risks of SAI by applying it under two CMIP6-endorsed future scenarios (SSP5-8.5 and SSP5-3.4-Overshoot) in DOE’s Energy Exascale Earth System Model version 3 (E3SMv3). To enable credible SAI simulations, E3SMv3 has been updated to include a comprehensive chemistry package—Troposphere, Stratosphere, Mesosphere, and Lower Thermosphere (TSMLT) chemistry—and a modified four-mode version of the modal aerosol model (MAM4) for prognostic stratospheric sulfate aerosols. Furthermore, to capture the full dynamics of the stratosphere, the top of the model is increased from 60 km (0.1 hPa) to 80 km (0.01 hPa). To estimate the appropriate injection amount of SO₂ required to meet the temperature target (a 1.5°C increase relative to 1850-1900), we implement the feedback algorithm from Kravitz et al. (2017) in E3SMv3, adhering to the same protocol. SAI simulations by fully coupled E3SMv3 under the SSP5-8.5 and SSP5-3.4-Overshoot scenarios indicate that the target global mean surface temperature is well maintained until 2100. It is found that the annual SO₂ injection amount required by 2100 in E3SMv3 is approximately 50% greater than that reported by Kravitz et al. (2017) using CESM2. Certain climatological differences due to SAI, such as lower stratospheric warming, are consistent with findings from several previous studies. Further analysis is currently underway to present the overall impact of SAI on the global climate, as well as the response of the land ecosystem to SAI. This work will help reduce significant uncertainties among Earth system models participating in the Geoengineering Model Intercomparison Project.