The main goal of the urban air pollution use case is to develop and provide tools for citizens and decision makers, which predict urban air quality with high resolution, high accuracy and in real time. Based on our results, we develop a control system of urban traffic, subject to air quality and traffic constraints. These all will serve to reach the ultimate goal to make the air cleaner in cities and reduce pollution caused illnesses.
By now, in operational mode air quality prediction mostly uses very simplified models (e.g. Gauss plum models) due to the high computational complexity of accurate Computational Fluid Dynamics methods. HiDALGO will use the results of an ongoing project, namely the 3DAirQualityPrediction application as an initial version for the prediction, which overcomes the aforementioned difficulties. To achieve high accuracy in real time, the recently developed mathematical modelling, simulation and optimization technology, the method of reduced order modelling (ROM) will be applied for the dispersion calculations. In addition to this model-based prediction, huge data sets will allow us to develop prediction methods purely from the data by HPDA approaches.