Improved Understanding of Dissolved Organic Matter Processing in Freshwater Using Complementary Experimental and Machine Learning Approaches
Peter Herzsprung, Valerie Carolin Wentzky, Norbert Kamjunke, Wolf von Tümpling, Christin Wilske, Kurt Friese, Bertram Boehrer, Thorsten Reemtsma, Karsten Rinke, Oliver J. Lechtenfeld
Abstract
and often shared molecular features (elemental ratios and mass) with photoreactive compounds. In particular, many photoproducts and some microbial products were identified as potential precursors of disinfection byproducts. Molecular DOM features were used to further predict molecular reactivity for the remaining compounds in the data set based on a random forest model. Our method offers an expandable classification approach to integrate the reactivity of DOM from specific environments and link it to molecular properties and chemistry.
Topics & Concepts
Dissolved organic carbonReactivity (psychology)ChemistryEnvironmental chemistryFourier transform ion cyclotron resonanceAquatic ecosystemOrganic matterMass spectrometryChlorophyll aBiological systemOrganic chemistryChromatographyBiochemistryAlternative medicineBiologyMedicinePathologyWater Treatment and DisinfectionWater Quality Monitoring and AnalysisMarine and coastal ecosystems