Fires in the tropics are driven by climate and land-use change. In the Amazon, fires are linked to post-deforestation biomass burning, agricultural and pasture management fires, and forest fires. Earth system models predict an increase in the intensity of dry seasons in this region in the 21st century. Therefore, carbon emissions from drought-induced forest fires can counteract pledged reductions of deforestation in the following decades, yet they are not included in national carbon emission estimates. Further, air pollution caused by fires has been linked to seasonal upturns in respiratory diseases affecting the population in Brazil's fire-prone areas. Against the backdrop of the COVID-19 pandemic, air pollution can potentially increase the risks of hospitalisations and mortality.
Improved assessments of fire impacts, emissions and their impact on air quality are therefore of high importance. Spatially specific estimations of fire emissions are made possible through a range of satellite products that are now available. We develop a remote sensing based approach that makes use of observations of burned area, land-cover change data and new high resolution biomass maps (ESA-CCI). By generating annual reference biomass maps for forests that are continuously updated with deforestation, fire-induced mortality and regrowth and combining these with existing estimates of grassland and crop residue fuel consumption, we derive new estimates of dry matter burned.
Based on this methodology we present initial estimates of dry matter burned and trace gas emissions for the entire Amazon basin and the Brazilian Cerrado at monthly intervals and compare our estimates to those of the global fire emissions database (GFED4). This allows us to identify areas of uncertainty in current emission estimates and present alternative workflows for generating improved regional products. These products will further be used to improve greenhouse gas budgets and to study effects on human health, ecosystem services and biodiversity.
Amazon, Fires, Degradation, Carbon Emissions, Remote Sensing, Forest, Savanna