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Abstract Ambient fine particulate matter (PM 2.5 ) is the world’s leading environmental health risk factor. Reducing the PM 2.5 disease burden requires specific strategies that target dominant sources across multiple spatial scales. We provide a contemporary and comprehensive evaluation of sector- and fuel-specific contributions to this disease burden across 21 regions, 204 countries, and 200 sub-national areas by integrating 24 global atmospheric chemistry-transport model sensitivity simulations, high-resolution satellite-derived PM 2.5 exposure estimates, and disease-specific concentration response relationships. Globally, 1.05 (95% Confidence Interval: 0.74–1.36) million deaths were avoidable in 2017 by eliminating fossil-fuel combustion (27.3% of the total PM 2.5 burden), with coal contributing to over half. Other dominant global sources included residential (0.74 [0.52–0.95] million deaths; 19.2%), industrial (0.45 [0.32–0.58] million deaths; 11.7%), and energy (0.39 [0.28–0.51] million deaths; 10.2%) sectors. Our results show that regions with large anthropogenic contributions generally had the highest attributable deaths, suggesting substantial health benefits from replacing traditional energy sources. 

Abstract We investigate and assess how well a global chemical transport model (GEOS‐Chem) simulates submicron aerosol mass concentrations in the remote troposphere. The simulated speciated aerosol (organic aerosol (OA), black carbon, sulfate, nitrate, and ammonium) mass concentrations are evaluated against airborne observations made during all four seasons of the NASA Atmospheric Tomography Mission (ATom) deployments over the remote Pacific and Atlantic Oceans. Such measurements over pristine environments offer fresh insights into the spatial (Northern [NH] and Southern Hemispheres [SH], Atlantic, and Pacific Oceans) and temporal (all seasons) variability in aerosol composition and lifetime, away from continental sources. The model captures the dominance of fine OA and sulfate aerosol mass concentrations in all seasons. There is a high bias across all species in the ATom‐2 (NH winter) simulations; implementing recent updates to the wet scavenging parameterization improves our simulations, eliminating the large ATom‐2 (NH winter) bias, improving the ATom‐1 (NH summer) and ATom‐3 (NH fall) simulations, but producing a model underestimate in aerosol mass concentrations for the ATom‐4 (NH spring) simulations. Following the wet scavenging updates, simulated global annual mean aerosol lifetimes vary from 1.9 to 4.0 days, depending on species. Aerosol lifetimes in each hemisphere vary by season, and are longest for carbonaceous aerosol during the southern hemispheric fire season. The updated wet scavenging parameterization brings simulated concentrations closer to observations and reduces global aerosol lifetime for all species, indicating the sensitivity of global aerosol lifetime and burden to wet removal processes.