Application of an Air Quality Forecasting system to Predict Air Pollution Associated with Wildfires

Wildfires raise not only fear of property damage but also health concerns due to air pollution associated with emissions from the fires. During a wildfire, people in the nearby and downwind regions may suffer the effects from inhalation of forest fire smoke that contain numerous gases and particular matters (PMs). Specification of real-time emissions from active fires to implement the ability to forecast their impacts on ambient air quality is challenging.

The current NOAA-EPA Air Quality Forecast (AQF) system is based on the coupling of North American Mesoscale (NAM) meteorological model (currently, WRF-NMM) and the Community Multiscale Air Quality (CMAQ) atmospheric chemistry transport model, wherein CMAQ is driven by the meteorological data from the NAM. To test the ability of air quality forecast system in predicting impacts of wildfires on O3 and PM air quality, an algorithm that uses the USDA BlueSky information for HYSPLIT smoke plume with some essential modifications is introduced in the NAM-CMAQ AQF system. Simulation with and without this algorithm were performed to study the contribution of wildfires emissions to predictions of ozone and particulate matter based on other catalogued pollution sources in EPA's emission inventories. The impact of this approach for improving surface-level air quality predictions is assessed through comparisons of model results with measurements from the AIRNOW network. The inter comparison with HYSPLIT product will also be conducted.