Collection and Characterization of Wildfire Smoke Particulate using Automated SEM Techniques
Roger West, Traci Lersch, GARY CASUCCIO,
RJ Lee Group, Inc. Abstract Number: 378
Working Group: Biomass Combustion: Outdoor/Indoor Transport and Indoor Air Quality
AbstractConditions related to global warming have resulted in more frequent and intense wildfires in the western United States. Emissions generated during wildfires affect ambient air quality with smoke aerosols primarily concentrated in fine particulate matter. Studies incorporating automated scanning electron microscopy (SEM) methods have been performed to characterize emissions from wildfires and evaluate their contribution to ambient air quality. In these studies, a passive sampler developed at the University of North Carolina (UNC) was deployed to collect particles in wildfire environments. The passive samples were analyzed using automated SEM techniques to provide information on particle mass and species concentrations associated with ambient concentrations of PM10 and PM2.5. SEM imaging and elemental composition were applied to identify emissions known to be associated with wildfire emissions.