Exposure to fine particulate matter (PM2.5) air pollution is associated with large-scale health consequences, but the uncertainties in estimates of PM2.5-related global premature mortality remain understudied. Using four observation-based PM2.5 datasets and six Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models, we compare uncertainties in current PM2.5-related mortality estimates to the impacts of emissions reductions on global health. Although estimates of current mortality are sensitive to the PM2.5 dataset (6.54 to 8.27 million/year using the Global Exposure Mortality Model), the projected near-term and long-term benefits of emissions reductions for reduced mortality are much more certain. Specifically, uncertainties in projected avoided deaths are consistently less than half the magnitude of uncertainties in recent mortality estimates. Under a low-emissions scenario, avoided cumulative deaths would exceed a quarter-billion by 2100.