We are proud to announce that Lukas Hubert Leufen has completed his dissertation within the IntelliAQ project and successfully defended his thesis at the University of Bonn. His thesis “Time Filter Assisted Deep Learning to Predict Air pollution” builds on a time series filtering approach to split up long-term and short-term variations and uses several deep learning networks to accurately predict ground-level ozone air pollution. The neural networks have been trained on large amounts of data from air quality monitoring stations distributed across Central Europe, climatological statistics on air pollutants and meteorological data from numerical weather models. The deep learning models have been integrated into a well-defined workflow for training and validation called MLAir, which ensures the reproducibility of the findings. Results substantiate that the combination of sophisticated DL architectures and time series filtering enables accurate ozone predictions, which are superior to state-of-the-art numerical modelling results.