Quantifying Global Wetland Methane Emissions With In Situ Methane Flux Data and Machine Learning Approaches.

ABSTRACT: Wetland methane (CH₄) emissions have a significant impact on the global climate system. However, the current estimation of wetland CH₄ emissions at the global scale still has large uncertainties. Here we developed six distinct bottom-up machine learning (ML) models using in situ CH₄ fluxes from both chamber measurements and the Fluxnet-CH₄ network. To reduce uncertainties, we adopted a multi-model ensemble (MME) approach to estimate CH₄ emissions. Precipitation, air temperature, soil properties, wetland types, and climate types are considered in developing the models. The MME is then extrapolated to the global scale to estimate CH₄ emissions from 1979 to 2099. We found that the annual wetland CH₄ emissions are 146

SUBMITTER: Chen S 

PROVIDER: S-EPMC11607141 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature