New AI deep learning model allows earlier, more accurate ozone warnings

That would improve health alerts for people at heightened risk of developing problems because of high ozone levels. Yunsoo Choi, associate professor in the Department of Earth and Atmospheric Sciences and corresponding author for a paper explaining the work, said they built an artificially intelligent model using a convolutional neural network, which is able to take information from current conditions and accurately predict ozone levels for the next day. The work was published in the journal Neural Networks. "If we know the conditions of today, we can predict the conditions of tomorrow," Choi said. Ozone is an unstable gas, formed by a chemical reaction when sunlight combines with nitrogen oxides (NOx) and volatile organic compounds, both of which are found in automobile and industrial emissions.