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Greenhouse gas emission from prescribed fires is influenced by vegetation types in West African Savannas. | LitMetric

AI Article Synopsis

  • This study investigates the greenhouse gas emissions from prescribed fires using a carbon mass balance approach across 80 experimental plots.
  • It finds that grass and shrub savannas produce higher carbon emissions due to intense burning, while tree savannas and woodlands show higher emission factors despite lower total emissions, due to their high biomass carbon content.
  • The research emphasizes that vegetation types and climate zone interactions significantly affect carbon emissions and highlights the need for better measurement and reporting of GHG emissions from fires.

Article Abstract

Greenhouse gas (GHG) emissions from prescribed fires are poorly investigated, resulting in a high uncertainty in GHG budgets. Using, a carbon mass balance approach and experimental prescribed fires in 80 plots, this study assessed carbon emissions and established emission factors (EFs) for carbon dioxides (CO), carbon monoxide (CO), and methane (CH) across climate zones and vegetation types. In grass and shrub savannas, fires could burn intensely due to the lower moisture content and continuous spatial distribution of biomass fuel, causing greater carbon emissions with 1.61 ± 0.13 t C ha and 1.01 ± 0.13 t C ha, respectively. Despite their low carbon emissions, tree savannas (1658.17 ± 11.13 g kg) and woodlands (1629.94 ± 12.23 g kg) have the highest EFs, which can be attribute to the high carbon content of biomass fuel in these vegetation types. Vegetation types and their interaction with climate zones have a substantial impact on carbon emissions and carbon species EFs, and should therefore be considered in assessing GHG emissions from fires. The findings from this study provide a useful basis for improving the national measurement, reporting, and verification of GHG emissions and for improving the measurement of the global balance of GHG emissions from fires.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11467211PMC
http://dx.doi.org/10.1038/s41598-024-73753-6DOI Listing

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