Non-Targeted High-Resolution Mass Spectrometric Characterisation of Highly Mobile and Highly Persistent Chemicals

Very persistent and very mobile (vPvM) chemicals are emerging environmental and human health concerns due to their resistance to degradation and high mobility in aquatic systems. At the same time, limited experimental data and analytical challenges in high-resolution mass spectrometry (HRMS) complicate their identification and prioritisation. This PhD project develops machine learning–based approaches to support large-scale screening of chemical mobility and biodegradability. By combining structure-based models with tools derived from HRMS/MS fragmentation data, the project aims to prioritise both known chemicals and unidentified features detected in complex environmental samples. Together, this work contributes to improved identification and assessment of potentially hazardous chemicals in the aquatic environment.

Please note, this is a Student Progress Review presentation by Tobias Hulleman