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

Rodriguez Vasquez María José, Benoist Anthony, Roda Jean-Marc, Fortin Mathieu. 2021. Estimating greenhouse gas emissions from peat combustion in wildfires on Indonesian peatlands, and their uncertainty. Global Biogeochemical Cycles, 35 (2):e2019GB00621, 17 p.

Url - jeu de données - Dataverse Cirad : https://doi.org/10.18167/DVN1/C3OWEP

Quartile : Q1, Sujet : ENVIRONMENTAL SCIENCES / Quartile : Q1, Sujet : GEOSCIENCES, MULTIDISCIPLINARY / Quartile : Q1, Sujet : METEOROLOGY & ATMOSPHERIC SCIENCES

Résumé : 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.

Mots-clés Agrovoc : émissions de gaz à effet de serre, gaz à effet de serre, tourbière, incendie spontané, incendie de forêt, modèle de simulation, méthode de Monte Carlo, séquestration du carbone, évaluation de l'impact sur l'environnement

Mots-clés géographiques Agrovoc : Indonésie

Mots-clés libres : Peatland, Wildfire, GHG emissions, Climate Change, Peat soil, Greenhouse Gas, Fires, Depth of burn

Classification Agris : P02 - Pollution
P30 - Sciences et aménagement du sol
U10 - Informatique, mathématiques et statistiques

Champ stratégique Cirad : CTS 4 (2019-) - Santé des plantes, des animaux et des écosystèmes

Auteurs et affiliations

• Rodriguez Vasquez María José, CIRAD-PERSYST-UPR BioWooEB (FRA) - auteur correspondant
• Benoist Anthony, CIRAD-PERSYST-UPR BioWooEB (FRA) ORCID: 0000-0001-6635-4192
• Roda Jean-Marc, CIRAD-ES-UPR Forêts et sociétés (MYS) ORCID: 0000-0002-3967-5297
• Fortin Mathieu, AgroParisTech (FRA)

Source : Cirad-Agritrop (https://agritrop.cirad.fr/597566/)

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