Thursday, 11 January 2018: 3:30 PM
Room 12A (ACC) (Austin, Texas)
Wildfires are large, natural sources of aerosols during the fire season (July through October) in the western U.S. due to the topography and meteorology of the region. More importantly, human exposure to wildfire smoke can be dangerous for sensitive populations, such as children, elderly, and those with respiratory ailments. Hence, modeling and forecasting the emissions and transport of air pollutants from wildfires is beneficial for public health prevention efforts. Wildfire emissions and smoke transport are challenging to represent in models due to uncertainties in transport physics parameters and spatial heterogeneity of fuel composition, which leading to uncertainties in fire emissions classification. Here, we incorporated wildfire emissions from the Fire Inventory of NCAR (FINN) into the CMAQ modeling framework, with the goal of improving modeled estimates of the chemical composition of the wildfire emissions and the transport of the related primary and secondary pollutants. FINN emissions have a higher spatial and temporal correlation with observed fire activity, due to the use of MODIS active fire products in the inventory development. We present an evaluation of CMAQ simulations over the continental U.S., for which FINN emissions replace the wildfire emissions in the National Emissions Inventory. Simulated concentrations of bulk fine particulate matter (PM2.5), PM2.5 components (e.g., organic carbon, elemental carbon, and trace metals), and ozone are evaluated by comparing the estimates with observations from regulatory monitoring networks. Regional estimates of PM2.5, PM2.5 components, and ozone provide surrogate metrics for human exposure to wildfire smoke around and down-wind of active fires.
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