Utilizing an ecosystem model and satellite data to estimate daily PM2.5 emissions from recent wildland–urban interface fires in California

Background Wildfires in California have become larger and spread more rapidly over the past decade, burning forests and the wildland–urban interface (WUI). Aims Because these fires are a major source of air pollutants, there is a pressing need to develop accurate ground-based modeling systems of hazardous emissions. Methods The Carnegie–Ames–Stanford Approach (CASA) model, based on satellite observations of monthly vegetation cover, was used to estimate daily emissions of fine particulate matter (PM2.5), CO and CO2 from four destructive wildfires in California. CASA included refined emission factors for vegetation biomass, building structures and vehicle burning, resulting in a daily CASA-WUI modeling approach that produced ‘bottom–up’ emissions estimates at 30-m spatial resolution. Key results We compared daily species burning totals of PM2.5 and CO from CASA-WUI modeling with region- to global-scale wildfire emission models. The PM2.5 daily emission rates from developed urban areas were typically five times higher than from wildland areas owing to lower fuel densities in the wildlands. Conclusions Locations and neighborhoods with the highest estimated PM2.5 emissions had the highest fraction of Low Intensity Developed urban structure density. Implications This suggests the air quality was far worse in developed urban areas during the high smoke emission dates of the Thomas, Tubbs and Carr Fires than in remote wooded areas.