Estimating Vegetative Fuel Loadings and Fuel Moisture Using Satellite Data for Modeling Biomass Burning Emissions

Biomass burning is the second largest source of aerosols, which affects air quality and the Earth's radiation budget. Because the emissions of aerosols is strongly influenced by factors such as biomass density, combustion efficiency, and burned area, current burning emission estimates are rather imprecise and vary markedly with different methodologies. The aim of this study is to model biomass burning emissions using satellite-derived vegetative fuel loadings, fuel moisture, and burned areas in the USA. For this purpose, we first developed an approach for mapping vegetative fuel loadings using Moderate-Resolution Imaging Spectroradiometer (MODIS) data at a spatial resolution of 1 km. MODIS data used in this study are land cover types, vegetation continuous fields, and a time series of leaf-area index (LAI). The LAI data were used to produce live leaf fuel loadings varying with vegetation types and vegetation fractions. For forest regions, the maximum leaf fuel loading within a year was applied to calculate branch fuel loadings and total tree fuel loadings using tree allometric models. Since fuel combustion efficiency and emission factors are functions of fuel moisture, we then determined weekly fuel moisture categories from AVHRR-based vegetation condition index (VCI). The VCI was calculated by normalizing the NDVI (normalized difference vegetation index) to the difference of the extreme NDVI fluctuations (maximum and minimum) from 1982-2004. This dataset is reliable since it is calibrated using post-launch algorithms and temporally smoothed. Further, we derived sub-pixel fire size from GOES WF-ABBA fire product. This fire product is available at 30 minutes interval. We used all these inputs to estimate aerosols (PM2.5, particulate mass for particles with diameter < 2.5 μ-m) for each individual fire in 2002 across the USA. We will present the algorithm details and the analysis of the derived emissions.