AI offers accurate measurement of air pollution

The advance by a team at Cornell University means that city planners and government health officials can obtain a more precise accounting about the well-being of urban dwellers and the air they breathe. The research is detailed in Transportation Research Part D.

“Infrastructure determines our living environment, our exposure,” said senior author Oliver Gao, the Howard Simpson Professor of Civil and Environmental Engineering in the College of Engineering at Cornell University. “Air pollution impact due to transportation – put out as exhaust from the cars and trucks that drive on our streets – is very complicated. Our infrastructure, transportation and energy policies are going to impact air pollution and hence public health.”

According to Cornell, previous methods to gauge air pollution were cumbersome and reliant on extraordinary amounts of data points. “Older models to calculate particulate matter were computationally and mechanically consuming and complex,” said Gao, a faculty fellow at the Cornell Atkinson Center for Sustainability. “But if you develop an easily accessible data model, with the help of artificial intelligence filling in some of the blanks, you can have an accurate model at a local scale.”