The importance of spatial resolutions of Community Multiscale Air Quality (CMAQ) models on health impact assessment

Abstract

We used the Community Multiscale Air Quality (CMAQ) simulation model to predict daily average of fine particulate matter (PM2.5) concentrations. The primary focus of our study was to investigate the sensitivity of CMAQ prediction accuracy associated with the horizontal grid resolutions and assess its impact on human health studies. To illustrate our point we ran CMAQ model at 4 km and 12 km resolutions over New York State for the year 2011, and systematically assessed the differences between two modeled PM2.5 concentrations. Model performance was evaluated against PM2.5 measured values at monitoring stations. The results indicated that simulations at both 4 km and 12 km resolutions reproduced measured PM2.5 values with fractional error (54.41% for 4 km and 52.28% for 12 km) that are within the recommend performance criteria except for summer seasons and rural areas. Additionally, model results at 12 km compared to 4 km resolution generally performed better and had substantially lower computational burden. In our health impact assessment study, we found that estimated adverse health outcomes associated with PM2.5 exposure derived from the two CMAQ models were compatible, especially in rural areas. Based on our findings, we conclude that the CMAQ simulation at 12 km resolution with further calibration and/or downscaling is a viable option than 4 km simulation to estimate small-scale within-city variations of air pollution concentrations.