D. V. Mallia*1, A. Kochanski1, and J. C. Lin1, and S. Ubranski2
1 Department of Atmospheric Sciences, University of Utah, Salt Lake City, UT, USA
2 Fire Science Laboratory, Missoula, MT, USA
*Corresponding E-mail: Derek.Mallia@utah.edu
Biomass burning is known to be responsible for emitting large quantities of CO, PM2.5, and other species relevant for air quality into the atmosphere. Effects of biomass burning not only affect the area local to the fire, but may also impact the air quality of regions downwind from the fire. The 2012 western U.S. wildfire season was characterized by significant wildfire activity across much of the Intermountain West and California. Previous studies have shown that enhancement in CO, PM2.5, and ozone (O3) concentrations can occur at sites that are downstream relative to wildfires. However, these studies have been inadequate for determining these influences as they have been unable to quantify the direct contributions from these fires. Here we will use a source apportionment modeling method that will separate the impacts of non-wildfire emissions from wildfire-emitted CO, PM2.5 and secondary species that aid in the formation of O3 and PM2.5. This modeling framework will make use of the Stochastic Time-Inverted Lagrangian Transport (STILT) model, which will be driven by wind fields generated from the WRF-ARW. Using a receptor-orientated framework, information from the STILT trajectories coupled with the latest wildfire emission inventories can be used to determine the direct influences of upstream wildfire emissions on air quality along the Wasatch Front. Initial work focused on Salt Lake City has indicated that wildfires are a signiticant contributor towards elevated PM2.5 concentrations during the summer months. In order to simulate O3, we will make use of a chemistry-version of STILT (STILT-Chem), that incorporates CB4 chemical mechanism in a form of non-linear chemical reactions, which will modify concentrations of different chemically-active species as they are transported along the parcel trajectories. The Lagrangian modeling framework represented by WRF- STILT could make for a valuable tool for understanding events in violation of National Ambient Air Quality Standards and potentially demonstrating exceptional events for O3 and PM2.5.