Clara Betancourt has completed her dissertation within the IntelliAQ project and successfully defended her thesis at the University of Bonn. Her thesis “Mapping and Interpolation of Tropospheric Ozone Data with Machine Learning Methods” develops spatio-temporal mapping and interpolation methods using machine learning techniques with the example application of ozone data. It trains the machine learning models on a large number of ozone measurements available in the Tropospheric Ozone Assessment Report (TOAR) database.
The synthesis of this work is that an interplay of physically sound data selection, uncertainty quantification, and explainability in machine learning can produce trustworthy environmental data products. Another finding is that the accuracy of the data products in a specific region is mainly dependent on good coverage with ozone measurements in that region. Therefore, this work contributes not only to the gapless quantification of ozone concentrations but also to trustworthy machine learning in the environmental sciences.