Air pollution is a public health challenge that threatens people and the environment, making timely and precise air quality measurements and predictions more crucial than ever. A team of researchers at the Department of Earth Science and Engineering and the Data Science Institute at Imperial College London have developed an innovative tool to address this challenge.  Known as Dynamic Neural Assimilation (DyNA), the new model combines the strength of AI with data assimilation to provide fast and accurate forecasts of air pollution levels. Published in the journal Discover Applied Sciences, the findings highlight a link between air pollution data and … Continue reading Imperial College’s New AI Model Predicts Air Pollution Levels with Unprecedented Accuracy