A team from associate professor Max Zhang’s lab will work with the Environmental Protection Agency (EPA) over the next year on a machine learning model designed to predict fossil fuel emissions.
A team from associate professor Max Zhang’s lab will work with the Environmental Protection Agency (EPA) over the next year on a machine learning model designed to predict fossil fuel emissions. The project was a winning entry in the EPA-sponsored EmPOWER Air Data Challenge.
Zhang directs the Energy and the Environment Research Laboratory at the Sibley School of Mechanical and Aerospace Engineering. His collaborators on the EPA project are Ye Jiang and Vignesh Rao, students in the Cornell Engineering master’s program in computer science; and doctoral student Jeff Sward.
The project, “Predicting the Environmental Performance of Power Plants Using Machine Learning,” will apply the machine learning model to air pollution monitoring data from the EPA’s Clean Air Markets Division (CAMD) to predict emissions rates from fossil fuel-burning power plants. The group will develop the model further to identify anomalies in CAMD data to enhance the quality of the data.
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