Wildland fire emissions are routinely estimated in the US Environmental Protection Agency's National Emissions Inventory, specifically for fine particulate matter (PM2.5) and precursors to ozone (O3); however, there is a large amount of uncertainty in this sector. We employ a brute-force zero-out sensitivity method to estimate the impact of wildland fire emissions on air quality across the contiguous US using the Community Multiscale Air Quality (CMAQ) modelling system. These simulations are designed to assess the importance of wildland fire emissions on CMAQ model performance and are not intended for regulatory assessments. CMAQ ver. 5.0.1 estimated that fires contributed 11% to the mean PM2.5 and less than 1% to the mean O3 concentrations during 2008-2012. Adding fires to CMAQ increases the number of 'grid-cell days' with PM2.5 above 35 μg m-3 by a factor of 4 and the number of grid-cell days with maximum daily 8-h average O3 above 70 ppb by 14%. Although CMAQ simulations of specific fires have improved with the latest model version (e.g. for the 2008 California wildfire episode, the correlation r = 0.82 with CMAQ ver. 5.0.1 v. r = 0.68 for CMAQ ver. 4.7.1), the model still exhibits a low bias at higher observed concentrations and a high bias at lower observed concentrations. Given the large impact of wildland fire emissions on simulated concentrations of elevated PM2.5 and O3, improvements are recommended on how these emissions are characterised and distributed vertically in the model.
Keywords: Community Multiscale Air Quality; National Emissions inventory; air pollution; air quality modelling; wildland fire emissions.