MADISON –– Scientists have been measuring global methane emissions for decades, but the boreal arctic —with a wide range of biomes including wetlands that extend across the northern parts of North America, Europe and Asia — is a key region where accurately estimating highly potent greenhouse gas emissions has been challenging.
Wetlands are great at storing carbon, but as global temperatures increase, they are warming up. That causes the carbon they store to be released into the atmosphere in the form of methane, which contributes to more global warming.
Now, researchers — including the University of Wisconsin–Madison’s Min Chen and Fa Li — have developed a new model that combines several data sources and uses physics-guided machine learning to more accurately understand methane emissions in the region. The improved model shows these wetlands are producing more methane over time.
“Wetland methane emissions are among the largest uncertainty in emissions from natural systems,” explains Chen, a professor of forest and wildlife ecology in the UW–Madison College of Agriculture and Life Sciences. “There are bacteria that live in the soils under the water of wetlands. That’s the perfect limited oxygen environment that is suitable for methane production.”
The researchers recently published their findings in the journal Nature Climate Change .
What problem are researchers trying to solve?
Why do scientists need more information on emissions from these wetlands?
How does the new model help?
What the new model is uncovering
This research was supported by a NASA Carbon Monitoring System grant (NNH20ZDA001N) and the Reducing Uncertainties in Biogeochemical Interactions through Synthesis and Computation (RUBISCO) Scientific Focus Area Project; the latter is sponsored by the Earth and Environmental Systems Modeling (EESM) Program under the Office of Biological and Environmental Research of the US Department of Energy Office of Science. This work was done in collaboration with researchers from Lawrence Berkely National Laboratory, University of Illinois Chicago, Stanford University, and the University of British Columbia.
Nature Climate Change
Data/statistical analysis
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