Effect of Meteorological Variability on Fine Particulate Matter Simulations Over the Contiguous United States

This study quantifies the impact of meteorological variability on the Community Multiscale Air Quality (CMAQ) model-simulated particulate matter of aerodynamic diameter 2.5 μm or smaller (particulate matter 2.5 [PM_2.5]) over the contiguous United States (CONUS). The meteorological variability is represented using the Short-Range Ensemble Forecast (SREF) produced operationally by the National Oceanic and Atmospheric Administration. A hierarchical cluster analysis technique is applied to down-select a subset of the SREF members that objectively accounts for the overall meteorological forecast variability of SREF. Three SREF members are selected to drive off-line CMAQ simulations during January, April, July, and October 2016. Changes in emissions, vertical diffusion, and aerosol processes due to meteorological variability dominate changes in aerosol mass concentrations over 55-73% of the domain except in July when dry deposition dominates emissions and aerosol processes. Weather Research and Forecasting-Advanced Research WRF (WRF-ARW) simulations reproduced the variability of surface temperature very well but overestimated the 10-m wind speed, precipitation, and at some sites the planetary boundary layer height. Averaged over CONUS, CMAQ simulations driven by all three meteorological configurations capture the observed daytime low and nighttime high PM_2.5 mass concentrations but underestimated the observed concentrations likely due to faster advection and higher wet deposition in the model. PM_2.5 levels across the three simulations agreed well during daytime but showed larger variability during nighttime due to dominance of aerosol, clouds, and advection processes in nighttime. The meteorology-induced variability in PM_2.5 is estimated to be 0.08–24 μg/m³ over the CONUS with larger variability over the eastern United States.