Satellite-Based Estimation of Biomass Burning Emissions for Modeling Smoke Impacts: Where We Are and What We Need

November 4, 2020 3:00pm to 4:00pm
Zoom Seminar


Speaker: Charles Ichoku

Institution: Howard University, NCAS-M


Wildfires and other types of biomass burning (BB) are a seasonal phenomenon in different vegetated land ecosystems around the world. These fires are estimated to consume 2–5 petagrams of biomass carbon globally every year, generate heat energy, and emit smoke plumes that comprise different species of aerosols and trace gases. These emissions can have adverse effects on human health, air quality, and environmental processes. However, BB emissions need to be properly constrained in global and regional models, in order to improve our understanding of their overall impacts. In this study, we compared six BB emission datasets for 2008 globally as well as in 14 sub-regions. The datasets are: (1) GFED3.1 (Global Fire Emissions Database version 3.1); (2) GFED4s (Global Fire Emissions Database version 4 with small fires); (3) FINN1.5 (Fire INventory from NCAR version 1.5); (4) GFAS1.2 (Global Fire Assimilation System version 1.2); (5) FEER1.0 (Fire Energetics and Emissions Research version 1.0), and (6) QFED2.4 (Quick Fire Emissions Dataset version 2.4). Although BB emissions of aerosols from these datasets showed similar spatial distributions, their global total emission amounts differed by a factor of 3-4, ranging from 13.76 to 51.93 Tg for organic carbon and from 1.65 to 5.54 Tg for black carbon. These differences translate to similar degrees of disagreement when the emissions are used in the forecasting of surface PM2.5 concentrations. We found that the differences between these six BB emission datasets are attributable to the approaches and input data used to derive BB emissions, such as whether aerosol optical depth (AOD) from satellite observations is used as a constraint, whether the approaches to parameterize the fire activities are based on burned area, active fire count, or fire radiative power (FRP), and which set of emission factors was used in deriving them. In this presentation, we will examine various existing methods of deriving BB emissions from satellite observations, discuss the results of the comparison of these BB emission datasets, and explore potential ways of improving results in future efforts.


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