Very persistent and very mobile (vPvM) substances pose a threat to the environment and human health. These chemicals may persist in aquatic systems, where they can move very easily and quickly due to their affinity for water rather than adsorbents such as soil. Currently, the partition coefficient between organic carbon and water Koc is used to classify chemicals as very mobile, mobile or non-mobile. However, the lack of experimental log Koc data for most chemicals presents a major limitation. For persistence, the half-life of a chemical is used to quantify the degradation rate of a chemical in a specific environmental system under given conditions, usually simulated in controlled conditions. There is also a severe lack of experimental data to determine these half-lives. With thousands of new chemicals entering the market---and therefore our exposome---every year, there is a growing need for advanced cheminformatics tools to prioritise such chemicals of concern without the need to spend enormous resources on experiments for all chemicals.
Conference Abstracts
Hulleman, T., Turkina, V., O’Brien, J.W., Chojnacka, A., Thomas, K.V. & Samanipour, S. Critical assessment of the chemical space covered by LC-HRMS non-targeted analysis, International Mass Spectrometry Conference 2024, Melbourne, Australia, 17-23 August 2024.
Hulleman, T., Samanipour, S., Haddad, P.R., Rauert, C., Okoffo, E.D., Thomas, K.V. & O’Brien, J.W. Machine learning for predicting environmental mobility based on retention behaviour, 20th Annual Workshop On Emerging High-Resolution Mass Spectrometry (HRMS) And LC-MS/MS Applications In Environmental Analysis And Food Safety, Spain, 7-8 October 2024.
Prizes/Awards
- 2024 Second Place for Best Poster at the 20th Annual Workshop On Emerging High-Resolution Mass Spectrometry (HRMS) And LC-MS/MS Applications In Environmental Analysis And Food Safety
