One of the challenges associated with determining health risks associated with wildfire emissions is that the low spatial resolution of surface monitors means that surface measurements may not be representative of a population's exposure, due to steep concentration gradients. To obtain better estimates of ambient exposure levels for health studies, a chemical transport model (CTM) can be used to simulate the evolution of a wildfire plume as it travels over populated regions downwind. Improving the performance of a CTM would allow the development of a new forecasting framework that could better equip decision makers to estimate and potentially mitigate future health impacts.
We use the Weather Research and Forecasting model with online chemistry (WRF-Chem) to simulate wildfire plume evolution. By varying the model resolution, meteorology reanalysis initial conditions, and biomass burning inventories, we are able to explore the sensitivity of model simulations to these various parameters. Satellite observations are used first to evaluate model skill, and then to constrain the model results. These data are then used to estimate population-level exposure, with the aim of better characterizing the effects that wildfire emissions have on human health.
 Westerling, A.L.; Hidalgo, H. G.; Cayan, D.R.; Swetnam, T.W.; “Warming and Earlier Spring Increase Western U.S. Forest Wildfire Activity”, Science 313, 18 August 2006.
 Flannigan, M. D.; Logan, K. A.; Amiro, B. D.; Skinner, W. R.; Stocks, B.J.; “Future Area Burned in Canada”, Climate Change 72, September 2005.