Real-time testing of satellite-based wild fire detection and their associated pollution impact on surface concentration of particulate matter

Friday, 19 December 2014
Li Pan1,2, Pius Lee3, Ivanka Stajner4, Shobha Kondragunta5, Jeffrey McQueen6, Cheng-Hsuan Lu6, Mark Ruminski7, Daniel Tong8, Hyun C Kim1,2, Youhua Tang9, Jian-Ping Huang6, Ho-Chun Huang10 and Sikchya Upadhayay11, (1)Cooperative Institute for Climate and Satellites University of Maryland, College Park, MD, United States, (2)NOAA Center for Weather and Climate Prediction, Air Resources Lab, College Park, MD, United States, (3)NOAA, Boulder, CO, United States, (4)NOAA, National Weather Service, Silver Spring, MD, United States, (5)NOAA College Park, College Park, MD, United States, (6)NOAA, Center for Weather and Climate Prediction, National Weather Service, College Park, MD, United States, (7)NOAA College Park, NESDIS, College Park, MD, United States, (8)George Mason Univeristy, Center for spatial Information Science and Systems, Fairfax, VA, United States, (9)NOAA/NESDIS/STAR, Suitland, MD, United States, (10)UMD/ESSIC at NOAA/NESDIS/STAR, College Park, MD, United States, (11)Syneren Technologies, Arlington, VA, United States
Wild fire contributes to air pollution. This study uses the NOAA National Air Quality Forecasting Capability (NAQFC) developmental product to quantify such pollution attributions in terms of surface level concentration of particulate matter smaller than 2.5 μm in diameter (PM2.5) over the contiguous US (CONUS). Sensitivity study using the NAQFC to predict surface concentrations of PM2.5 with and without projected wild fires provides a baseline apportionment of pollutant attributable to wild fire. The forecast system entails wild fire related pollutant emission to be projected near real time. It uses the National Environmental Satellite, Data, and Information Service (NESDIS) Hazard Mapping System (HMS), a multiple satellite and human-analyst-assisted wild fire detection system, to locate wild fires. The U.S. Forest Service Bluesky Modeling framework is used during the emission projection to provide parameterization for fuel type, loading inventories and burn duration. Subsequent to the Bluesky process, the U.S. EPA Sparse Matrix Operator Kernel Emissions (SMOKE) model is invoked to map chemical speciation and to calculate plume rise for the chemical transport model (CTM) within the NAQFC. Fire plumes intruded into CONUS were also considered. The CTM used is the U.S. EPA Community Air Quality Multi-scale Model (CMAQ) version 4.6 with CB05 gas phase mechanism and the AERO4 tri-modal aerosol size-distribution module. Both surface-based concentration and space-based observation such as aerosol optical thickness are used to verify performance of the forecast. A standard statistical performance metric is used to rank the performance improvement achieved by accounting for wild fires over the CONUS during an extended period of real-time testing.