Influences of upstream wildfire emissions on CO, CO2, and PM 2.5 concentrations in Salt Lake City, Utah, using a Lagrangian model (WRF-STILT)

Influences of upstream wildfire emissions on CO, CO_2, and PM 2.5 concentrations in Salt Lake City, Utah, using a Lagrangian model (WRF-STILT)

D. V. Mallia^1*, J. C. Lin¹, S. Urbanski², J. Ehleringer³, T. Nehrkorn⁴

1 Department of Atmospheric Sciences, University of Utah, Salt Lake City, UT, USA

2 Fire Science Laboratory, Missoula, MT, USA

3 Department of Biology, University of Utah, Salt Lake City, UT, USA

4 Atmospheric and Environmental Research Inc, Lexington, MA, USA

*Corresponding E-mail: Derek.Mallia@utah.edu

16^th Conference on Mountain Meteorology, 18-22 August 2014, San Diego, CA

Abstract

Biomass burning is responsible for emitting large quantities of CO₂, CO, and PM_2.5 into earth's atmosphere. Effects of biomass burning not only affect the area local to the fire, but may also impact regions downwind of the fire. Emissions from wildfires can have significant impacts on the air quality at downwind locations. Specifically, the exposure to high concentrations of PM_2.5 can have adverse effects on human health and economic growth. The 2012 western U.S. wildfire season had significant wildfire activity which emitted ~6000 Gg of CO and ~80 Tg of CO₂ into Earth's atmosphere. Salt Lake City provided a good location to study the impacts of upstream wildfires due to its dense observation networks for CO₂, CO, and PM_2.5 along with its downwind location relative to active wildfires.

Here we use a state of the art Lagrangian transport model known as WRF-STILT to determine the impacts of upstream wildfire emissions on a downstream city (Salt Lake City). Using an ensemble of backward trajectories we were able to determine the surface influence of upstream locations by multiplying the footprint obtained from STILT with wildfire emissions obtained from a new, high-resolution biomass burning emissions inventory from the Missoula Fire Science Laboratory—the Wildfire Emissions Inventory. These simulations rely on accurate source emission inventories and WRF simulations that can accurately resolve synoptic and mesoscale wind fields in complex terrain. Various physical parameterization schemes and grid-nudging techniques were tested in order to determine the optimal model settings used within the WRF-STILT model centered over the Salt Lake Valley. Remote sensing and speciated PM_2.5 data were used to indicate periods of wildfire activity and to verify the WRF-STILT model results. Initial results show that the WRF-STILT model was able to simulate many periods of increased wildfire activity observed in the measurements. While this research highlights the transient impacts that wildfires can have on the air quality on regions downstream of wildfires, it also shows that the anthropogenic emissions are still the dominant source for CO₂, CO, and PM_2.5 in the Salt Lake Valley during the U.S. wildfire season.