Non-target analysis (NTA) using liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) has become an indispensable tool in analysis over the last 20 years. The range of applications extends from environmental analysis to process and food analysis and into the field of biochemical analysis. The basis for this was a stable and robust ion source such as electrospray ionization. This opened up the possibility of identifying and quantifying polar compounds directly in the ng/L range without enrichment in the water sample. LC-HRMS also enables new strategies for water analysis. In addition to the targeted analysis of organic trace substances in the water sample (target analysis), it is now also possible to search for non-targeted substances in a water sample (NTA). [1]
The NTA makes it possible to characterize the sample more extensively with regard to organic trace substances than may be necessary for the actual question or task. Together with this unused information from the NTS data of the individual water samples from different sampling points, it is possible to generate a picture of the status of the water bodies (region, federal state, Germany, Europe). This requires the merging and networking of data from different laboratories in a common database. This database thus represents a collective tool for the large-scale recording of organic trace substance pollution and its temporal dynamics. It can also be used to determine changes caused by exceptional events, such as floods, in different water bodies.
A prerequisite for the collective use of NTS data is their comparability. Comparability here means that the detected features, characterized by retention time, mass and mass spectrum, by different analysis systems can be transformed into a congruent structure. In the K2I research project of the Federal Ministry of Education and Research (BMBF), the possibilities of recording and merging NTS data from different sources were demonstrated. In addition, the temporal and spatial information of the features of known and unknown substances was to be used to reveal important relationships with the help of machine and deep learning. [2]
Literature:
[1] Federal Environment Agency (2021): Methodology for the application of non-target screening (NTS) using LC-MS/MS in water monitoring, Dessau-Roßlau. http://www.umweltbundesamt.de/publikationen. [2] BMBF project (2023) Artificial and collective intelligence for trace substance tracking K2I, https://www.k2i-tracker.de/
