![Machine learning to monitor stored CO2 saves cost and time, researchers report active smokestacks seen from accross an open field with sunset in background](/sites/geosc/files/styles/large/public/field/image/emissionszhuarticle.jpg?itok=UTgmFeoy)
Incorporating field data for the first time, researchers at Penn State demonstrated machine learning can be a powerful and cost-effective tool for monitoring sequestered carbon dioxide (CO2), overcoming a hurdle for the burgeoning technology aimed at combating climate change.
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