Air quality resolution for health impact assessment: influence of regional characteristics

This research article examines how the spatial resolution of air quality models influences estimates of the health benefits associated with reductions in air pollution. Using the Community Multiscale Air Quality (CAMx) model and the U.S. EPA’s BenMAP health benefits assessment tool, the authors compare health impact estimates generated at 36 km, 12 km, and 4 km resolutions across nine regions in the eastern United States. The study evaluates changes in ozone (O₃) and fine particulate matter (PM₂.₅) concentrations resulting from an emissions reduction scenario to determine whether higher-resolution modelling produces more accurate estimates of avoided health impacts.

The findings show that model resolution has a significant influence on estimated health benefits for ozone, particularly in urban areas where coarse-resolution models can substantially overestimate benefits. In contrast, PM₂.₅ health impact estimates are relatively insensitive to model resolution and remain within the uncertainty range associated with epidemiological concentration–response functions. The paper provides important methodological guidance for researchers and policymakers conducting health impact assessments, helping them balance computational costs with the need for accurate air quality modelling in support of evidence-based air quality management.