Modeling the Effect of Fuel Moisture and Meteorology on Wildfire Model Emissions

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Sunday, 2 February 2014
Hall C3 (The Georgia World Congress Center )
Megan Elizabeth Buzanowicz, Millersville University, Millersville, PA; and F. L. Herron-Thorpe and J. Vaughan

Wildfire emissions severely impact air quality in the Pacific Northwest, typically during dry summers and falls.  The AIRPACT air quality system uses the BlueSky modeling framework (BSF) to forecast the smoke effects from numerous wildfires for air quality managers.  BSF uses Satellite Mapping Automated Reanalysis Tool for Fire Incident Reconciliation (SMARTFIRE) fire information to initialize predictions of fuel loading, fuel consumption, fire emissions, and plume rise.  BSF runs across a sequence of steps and at each step there are many options for those models.  These options include the Fire Emissions Production Simulator (FEPS), the Fuel Characteristic Classification System (FCCS), and CONSUME, which is designed to import data directly from the FCCS and provide an output formatted to feed other models.  AIRPACT wildfire emissions are currently based on the default BSF “dry” inputs, but would benefit from a more dynamic prediction of fuel moisture parameters and meteorological data, such as temperature, wind, and humidity.  The goal of this project is to determine what effects different fuel moistures and meteorology have on predicted heat generated by the fire and the subsequent particulate matter 2.5 (PM2.5) emitted.  Fires located in central Idaho were selected from the 2012 wildfire season and tested with varying fuel moisture and meteorological parameters. 

We found that the meteorological conditions and moisture content affected the percent of fuels consumed during the fire simulation, thus affecting the amount of emissions released.  For a larger fire, the amount of PM2.5 emissions decreased by ~32%, while the amount of heat generated decreased by ~11%.  For a smaller fire, the amount of PM2.5 emissions decreased by ~64%, while the amount of heat generated decreased by ~30%.  In the future, this research will help to guide development of a more dynamic use of meteorological conditions and fuel moisture in AIRPACT wildfire forecasts.