AI-powered model improves ozone pollution forecasting

A research team led by Prof. Xie Pinhua from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences has developed a novel prediction model for surface ozone concentration in the North China Plain (NCP) and Yangtze River Delta (YRD) regions. The model leverages a sequential convolutional long short-term memory network framework (CNN-LSTM) to integrate spatiotemporal meteorological features, addressing key limitations in existing forecasting methods.