Estimación de emisiones atmosféricas de CO2, NO2, CO, NH3 y Black Carbon vía bottom up, generados por quema de biomasa en el norte de América del Sur

Translated title of the contribution: Bottom-up estimates of atmospheric emissions of CO2, NO2, CO, NH3, and Black Carbon, generated by biomass burning in the north of South America

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Abstract

Biomass burning is an important source of greenhouse gases (GHG) and air pollutants (AP) in developing countries. In this research, a bottom-up method was implemented for the estimation of emissions, emphasizing the validation process of aerial biomass products (AGB), which it has not been sufficiently approached from the point of view of the quantification of emissions. The most recent results on the validation of burned area (AQ) products and the analysis of uncertainty were also incorporated into the process of estimating the emissions of gases that directly or indirectly promote the greenhouse effect, such as CO2, NO2, CO, NH3, and Black Carbon (BC). In total, 87.60 Mha were burned in the region between 2001 and 2016, represented in a 57% by pasture lands a 23% by savannas, an 8% by savanna woodlands, an 8% by mixed soils with crops and natural vegetation, a 3% by evergreen broadleaf forests, and a 1 % in the region´s remaining types of land cover. With 35480 reference polygons, a model based on the uncertainty of AQ was generated, which served to find the calibration factor of the FireCCI5.0 in all the studied species. The total emissions (minimum and maximum) and the average of the same in the study period were the following: 1760 Tg CO2 (765.07-2552.88; average 110 Tg), 68.12 Tg of CO (27.11-98.87; average 4.26 Tg), 3.05 Tg of NO2 (1.27-4.40; average 0.19 Tg), 0.76 Tg of NH3 (0.33-1.12; average 0.05 Tg), and 0.44 Tg of Black Carbon (0.015-0.64; average 0.03 Tg).

Translated title of the contributionBottom-up estimates of atmospheric emissions of CO2, NO2, CO, NH3, and Black Carbon, generated by biomass burning in the north of South America
Original languageSpanish
Pages (from-to)23-47
Number of pages25
JournalRevista de Teledeteccion
Volume2022
Issue number59
DOIs
StatePublished - 2022

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