Remote Sensing and Modeling of the Georgia 2007 Fires Eun-Su Yang, Sundar A. Christopher, Yuling Wu, Arastoo P. Biazar Earth System Science Center University.

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Remote Sensing and Modeling of the Georgia 2007 Fires Eun-Su Yang, Sundar A. Christopher, Yuling Wu, Arastoo P. Biazar Earth System Science Center University of Alabama in Huntsville Shobha Kondragunta NOAA/NESDIS Presentation to 2008 CMAS Conference October 7, 2008

 Overview of the GA/FL fires in May 2007  Fire emissions derived from satellite data  Air quality modeling approach  CMAQ simulations with local emissions  Simulations with local plus fire emissions  Evaluations with satellite and in-situ data  Summary Outline

Meteorological situation in May 2007 NCEP 850 hPa Geopotential Height: MM5: Surface pressure and wind Dry spring caused exten sive wildfires in Georgia and Florida.

MODIS Terra: 1615ZFLAMBE Fires in May 22, 2007 Fire detection is near real time. (upper) (left)

Emissions (kg) = (burned area)  GOES x (fuel load)  MODIS vegetation x (fraction of combustion)  AVHRR moisture x (fraction of emission)  AVHRR moisture Produces: PM2.5 *, CO, N2O, NH3, SO2, CH4, NOX *, and TNMHC *. ( * non-CBIV species) Biomass burning emissions are derived from (burned area). Biomass Burning Emissions

PM2.5 mass from one location in Birmingham, Alabama from April 1-May 31, The colors indicate various air quality categories ranging from Good to extremely unhealthy conditions. smoke plume or local emission? Contribution of local emission Background emissions could be important in urban areas.

MM5/WRF SMOKE:Emission Inventory Model CMAQ fire emissions satellite and ground-based measurements: AOT, PM2.5 AQI Forecast: Good Moderate Unhealthy for Sensitive Group Unhealthy Very Unhealthy Hazardous input validation MM5/SMOKE/CMAQ Biogenic (BEIS3) Mobile (MOBILE6) Point, Area

Modeling Approaches CMAQ run for May km grid. 40 vertical layers: more layers near surface and tropopause. Include BIOGENIC and MOBILE emissions for local emissions. EBI solver, cb4-ae4-aq mechanism. Fire emissions are uniformly distributed from surface to PBL.

CMAQ simulations with local emissions

AOT simulations with local & fire emissions There is big difference near the boundary of smoke plume.

PM2.5 simulations with local & fire emissions Local emissions are ok, but fire emissions are overestimated.

Fire emissions can be estimated near-real time satellite measurements. Meteorological fields such as winds are important to precisely locate fire plumes. The results are preliminary and, therefore, subject to change. Fire emission rate are overestimated; need check consistency in unit. Summary