Geophysical Uncertainties in Air Pollution Exposure and Benefits of Emissions Reductions for Global Health

Exposure to fine particulate matter (PM2.5) air pollution is associated with large-scale health consequences, but the ranges in estimates of global air pollution exposure and PM2.5-related global premature mortality remain understudied. Using four model/observation-based PM2.5 data sets and six Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models, we compare ranges in current PM2.5-related mortality estimates based on model/observation combinations to the range of projected emissions reductions and the resulting impacts on global health from CMIP6 models. Although estimates of current mortality are sensitive to the PM2.5 data set (6.54–9.23 million/year using the central estimate from the Global Exposure Mortality Model), the projected near-term benefits of emissions reductions for reduced mortality are much more certain. Specifically, until the middle of the century, uncertainty ranges in projected avoided deaths are less than the magnitude of ranges in present-day mortality estimates, even when projected future changing socio-demographic factors are considered. Under a low-emissions scenario, avoided cumulative early deaths could reach 275 million (range: 243–351 million) by 2100, assuming no future socio-demographic changes. Avoided cumulative deaths could reach 124 million (range: 74–246 million) if changing future socio-demographic factors are considered. As the global population ages and becomes more sensitive to breathing polluted air, there will be an increasing need for policies that both reduce air pollution and improve public health.

Duke Scholars

Author Luke Parsons  

Author Drew Todd Shindell Earth and Climate Sciences