Can AI Help Improve Water Quality? Towards the Prediction of Degradation of Micropollutants in Wastewater


  • Hiroko Satoh University of Zurich, Research Organization of Information and Systems (ROIS)
  • Jasmin Hafner Department of Environmental Chemsitry, Eawag
  • Jürg Hutter Department of Chemistry, University of Zurich
  • Kathrin Fenner Department of Chemistry, University of Zurich; Department of Environmental Chemistry, Eawag, Überlandstrasse 133, CH-8600 Dübendorf



Cheminformatics, Degradation of micropollutants in wastewater, Quantitative structure-biodegradation relationships (QSBR), Quantum chemistry (QC)


Micropollutants have become a serious environmental problem by threatening ecosystems and the quality of drinking water. This account investigates if advanced AI can be used to find solutions for this problem. We review background, the challenges involved, and the current state-of-the-art of quantitative structure-biodegradation relationships (QSBR). We report on recent progress combining experiment, quantum chemistry (QC) and chemoinformatics, and provide a perspective on potential future uses of AI technology to help improve water quality.




How to Cite

H. Satoh, J. Hafner, J. Hutter, K. Fenner, Chimia 2023, 77, 48, DOI: 10.2533/chimia.2023.48.