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Estimating greenhouse gas emissions from peat combustion in wildfires on Indonesian peatlands, and their uncertainty

Rodriguez Vasquez M.J., Benoist A., Roda J.M., Fortin M.. 2021. Global Biogeochemical Cycles, 35 (2) : 17 p..

DOI: 10.18167/DVN1/C3OWEP

DOI: 10.1029/2019GB006218

Peatlands play an important role as carbon pools, storing a third of the world's soil carbon. However, peatlands in Southeast Asia have suffered from depletion due to economic pressure and the demand for natural resources, often caused by land use changes and fires. Usually, land preparation requires drainage and fires, resulting in major greenhouse gas (GHG) emissions into the atmosphere. In this work, we propose a general equation to estimate GHG emissions from fires on peatlands. The contribution of each parameter to the variance of the estimated GHG emissions was also evaluated. We used Monte Carlo simulation, meta-analyses, and an analytical expression of variance. GHG emissions of a single fire episode were estimated at 842 Mg ha-1 CO2 eq. with a standard deviation of 466 Mg ha-1 CO2 eq. The parameter contributing most to variance was the depth of burn, at 94.2%, followed by bulk density, at 5.5%, and emission factors, at 0.3%. Our estimated GHG emissions were close to the amount estimated from the default values provided by the IPCC, strengthening confidence in the IPCC methodology. When the depth of burn was assessed by remote sensing, the parameter that most contributed to variance became the fire-damaged area, followed by the depth of burn. The contribution of each parameter to variance, as estimated in this study, made it possible to prioritize the effort in uncertainty reduction. Combining Monte Carlo simulation and an analytical expression of variance could be a promising way of obtaining more reliable confidence intervals.

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