Automated Forecasting of Smoke Dispersion and Air Quality Using NASA Terra
and Aqua Satellite Data
Wei Min Hao, USDA Forest Service, Rocky Mountain Research Station, Fire Sciences
Laboratory; Missoula, MT, E-mail: whao@fs.fed.us
Abstract: Wildland fires are a major contributor of particulate matter and other
pollutants to the atmosphere. The new EPA Clean Air Act and the Regional Haze Rule
require quantifying accurately the emissions of PM2.5 and other pollutants from fires and
their impacts on regional haze and air quality. We are developing an automated system
that will forecast smoke dispersion and air quality in the continental U.S. The forecasting
system assimilates real-time NASA Terra and Aqua satellite data on active fire locations
and burned areas into the FARSITE fire behavior model and the NOAA WRF and
HYSPLIT forecast models. Our goal is to provide land and air quality managers with the
capability to predict smoke dispersion and PM2.5 and other pollutant concentrations
every 4-6 hours for the next 3-4 days. Managers can also use the information to quantify
the contributions of smoke from wildland fires to regional haze and air quality. In
addition, during large-scale fires, Geographic Area Coordination (GAC) centers will have
up-to-date information available to assess the effects of smoke on visibility, air quality,
and public health; to assist aviation forecasts; and to decide on public evacuations. Our
automated forecasting system complements and strengthens other smoke modeling
projects being conducted at various land management agencies.