Self-Organizing Maps: An AI Tool for Identifying Unexpected Source Signatures in Non-Target Screening Analysis of Urban Wastewater by HPLC-HRMS.

(1) Background: Monitoring effluent in water treatment plants has a key role in identifying potential pollutants that might be released into the environment. A non-target analysis approach can be used for identifying unknown substances and source-specific multipollutant signatures. (2) Methods: Urban and industrial wastewater effluent were analyzed by HPLC-HRMS for non-target analysis. The anomalous infiltration of industrial wastewater into urban wastewater was investigated by analyzing the mass spectra data of "unknown common" compounds using principal component analysis (PCA) and the Self-Organizing Map (SOM) AI tool. The outcomes of the models were compared. (3) Results: The outlier detection was more straightforward in the SOM model than in the PCA one. The differences among the samples could not be completely perceived in the PCA model. Moreover, since PCA involves the calculation of new variables based on the original experimental ones, it is not possible to reconstruct a chromatogram that displays the recurring patterns in the urban WTP samples. This can be achieved using the SOM outcomes. (4) Conclusions: When comparing a large number of samples, the SOM AI tool is highly efficient in terms of calculation, visualization, and identifying outliers. Interpreting PCA visualization and outlier detection becomes challenging when dealing with a large sample size.

Summary recommendations on "Analytical methods for substances in the Watch List under the Water Framework Directive".

The Watch List (WL) is a monitoring program under the European Water Framework Directive (WFD) to obtain high-quality Union-wide monitoring data on potential water pollutants for which scarce monitoring data or data of insufficient quality are available. The main purpose of the WL data collection is to determine if the substances pose a risk to the aquatic environment at EU level and subsequently to decide whether a threshold, the Environmental Quality Standards (EQS) should be set for them and, potentially to be listed as priority substance in the WFD. The first WL was established in 2015 and contained 10 individual or groups of substances while the 4th WL was launched in 2022. The results of monitoring the substances of the first WL showed that some countries had difficulties to reach an analytical Limit of Quantification (LOQ) below or equal to the Predicted No-Effect Concentrations (PNEC) or EQS. The Joint Research Centre (JRC) of the European Commission (EC) organised a series of workshops to support the EU Member States (MS) and their activities under the WFD. Sharing the knowledge among the Member States on the analytical methods is important to deliver good data quality. The outcome and the discussion engaged with the experts are described in this paper, and in addition a literature review of the most important publications on the analysis of 17-alpha-ethinylestradiol (EE2), amoxicillin, ciprofloxacin, metaflumizone, fipronil, metformin, and guanylurea from the last years is presented.