Enhanced CH4 emissions from global wildfires likely due to undetected small fires

Monitoring methane (CH 4 ) emissions from terrestrial ecosystems is essential for assessing the relative contributions of natural and anthropogenic factors leading to climate change and shaping global climate goals. Fires are a significant source of atmospheric CH 4 , with the increasing frequency o...

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Veröffentlicht in:Nature communications 2025-01, Vol.16 (1), p.804-9, Article 804
Hauptverfasser: Zhao, Junri, Ciais, Philippe, Chevallier, Frederic, Canadell, Josep G., van der Velde, Ivar R., Chuvieco, Emilio, Chen, Yang, Zhang, Qiang, He, Kebin, Zheng, Bo
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Sprache:eng
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Zusammenfassung:Monitoring methane (CH 4 ) emissions from terrestrial ecosystems is essential for assessing the relative contributions of natural and anthropogenic factors leading to climate change and shaping global climate goals. Fires are a significant source of atmospheric CH 4 , with the increasing frequency of megafires amplifying their impact. Global fire emissions exhibit large spatiotemporal variations, making the magnitude and dynamics difficult to characterize accurately. In this study, we reconstruct global fire CH 4 emissions by integrating satellite carbon monoxide (CO)-based atmospheric inversion with well-constrained fire CH 4 to CO emission ratio maps. Here we show that global fire CH 4 emissions averaged 24.0 (17.7–30.4) Tg yr −1 from 2003 to 2020, approximately 27% higher (equivalent to 5.1 Tg yr −1 ) than average estimates from four widely used fire emission models. This discrepancy likely stems from undetected small fires and underrepresented emission intensities in coarse-resolution data. Our study highlights the value of atmospheric inversion based on fire tracers like CO to track fire-carbon-climate feedback. This study reconstructs global fire methane emissions from 2003 to 2020, revealing 27% higher estimates than previous models, which is likely due to undetected small fires and underestimated emission intensity from the coarse-resolution model data.
ISSN:2041-1723
2041-1723
DOI:10.1038/s41467-025-56218-w