AAAR 35th Annual Conference October 17 - October 21, 2016 Oregon Convention Center Portland, Oregon, USA
Abstract View
Modeling the Impact of Biomass-Burning Aerosol on Urban Areas
CHANTELLE LONSDALE, Chris Brodowski, Matthew Alvarado, John Henderson, Jeffrey R. Pierce, John Lin, AER
Abstract Number: 81 Working Group: Aerosol Chemistry
Abstract Fresh biomass-burning aerosol evolve quickly, both physically and chemically, in the atmosphere due to coagulation, primary organic aerosol evaporation, and secondary organic aerosol formation. These aerosols are a complex mixture of organic species, black carbon, and inorganic salts. The size, number, and chemical composition of these particles depend on the type of vegetation that is burning, combustion efficiency, fire size and ambient conditions. Understanding and simulating this complex evolution is critical to understanding the impact of biomass-burning plumes on air quality and climate.
We present results from a new Lagrangian aerosol modeling tool, STILT-ASP, which is comprised of the Stochastic Time Inverted Lagrangian Transport (STILT) model with an integrated Aerosol Simulation Program (ASP). This tool allows for the identification of air parcels that were influenced by fire emissions during their transport to the model receptor (i.e. an urban monitoring site). The model then determines the contribution of primary emission (of PM2.5) and secondary chemical formation (both O3 and PM2.5) from the fires to the pollutants in the parcel, and then sums these fire contributions across all parcels to determine the influence of the fire at the receptor. We present the results of two biomass-burning impact studies; 1) a fire in Bastrop, Texas in September 2011 influencing the Austin-Round Rock metropolitan area and 2) Pacific Northwest and Lower Mississippi River fires on the Houston metropolitan area in August 2011. We also discuss the preliminary integration of the System for Atmospheric Modeling (SAM) with ASP to model the evolution of plume scale biomass-burning aerosol number and size in order for this evolution to be better represented in aerosol microphysics and climate models.