Emission inventory processing of biomass burning from a global dataset for air quality modeling

Abstract

Wildfires generate large amounts of atmospheric pollutants yearly. The development of an emission inventory for this activity is a challenge today, mainly to perform the air quality modeling. There are accessible available databases with historical information about this source. The main goal of this study was to process the results of biomass burning emissions for the year 2014 from the Global Fire Assimilation System (GFAS). The pollutants studied were black carbon, organic carbon, and fine and coarse particulate matter. The inputs were pre-formatted to enter into the simulation software of the emission inventory. In this case, the Sparse Matrix Operator Kernel Emissions (SMOKE) was used, and the values obtained in various cities were analyzed. As a result, the spatial distribution of the forest fire emissions in the Southern Hemisphere was achieved, with the polar stereographic projection. The highest emissions were located in the African continent, followed by the northern region of Australia. Future air quality modeling at a local level could apply the results and the methodology of this study. The biomass burning emissions could add a better performance of the results and more knowledge on the effect of this source.