An integrated workflow based on liquid chromatography coupled to a quadrupole-time-of-flight mass spectrometer (LC-QTOF-MS) was developed and applied to detect and identify suspect and unknown contaminants in Greek wastewater. Tentative identifications were initially based on mass accuracy, isotopic pattern, plausibility of the chromatographic retention time and MS/MS spectral interpretation (comparison with spectral libraries, in silico fragmentation). Moreover, new specific strategies for the identification of metabolites were applied to obtain extra confidence including the comparison of diurnal and/or weekly concentration trends of the metabolite and parent compounds and the complementary use of HILIC. Thirteen of 284 predicted and literature metabolites of selected pharmaceuticals and nicotine were tentatively identified in influent samples from Athens and seven were finally confirmed with reference standards. Thirty four nontarget compounds were tentatively identified, four were also confirmed. The sulfonated surfactant diglycol ether sulfate was identified along with others in the homologous series (SO4C2H4(OC2H4)xOH), which have not been previously reported in wastewater. As many surfactants were originally found as nontargets, these compounds were studied in detail through retrospective analysis.

Over the past decade, the application of liquid chromatography-high resolution mass spectroscopy (LC-HRMS) has been growing extensively due to its ability to analyze a wide range of suspected and unknown compounds in environmental samples. However, various criteria, such as mass accuracy and isotopic pattern of the precursor ion, MS/MS spectra evaluation, and retention time plausibility, should be met to reach a certain identification confidence. In this context, a comprehensive workflow based on computational tools was developed to understand the retention time behavior of a large number of compounds belonging to emerging contaminants. Two extensive data sets were built for two chromatographic systems, one for positive and one for negative electrospray ionization mode, containing information for the retention time of 528 and 298 compounds, respectively, to expand the applicability domain of the developed models. Then, the data sets were split into training and test set, employing k-nearest neighborhood clustering, to build and validate the models’ internal and external prediction ability. The best subset of molecular descriptors was selected using genetic algorithms. Multiple linear regression, artificial neural networks, and support vector machines were used to correlate the selected descriptors with the experimental retention times. Several validation techniques were used, including Golbraikh–Tropsha acceptable model criteria, Euclidean based applicability domain, modified correlation coefficient (r m 2), and concordance correlation coefficient values, to measure the accuracy and precision of the models. The best linear and nonlinear models for each data set were derived and used to predict the retention time of suspect compounds of a wide-scope survey, as the evaluation data set. For the efficient outlier detection and interpretation of the origin of the prediction error, a novel procedure and tool was developed and applied, enabling us to identify if the suspect compound was in the applicability domain or not.

Most current bioexposure assessments for UV filters focus on contaminants concentrations in fish from river and lake. To date there is not information available on the occurrence of UV filters in marine mammals. This is the first study to investigate the presence of sunscreen agents in tissue liver of Franciscana dolphin (Pontoporia blainvillei), a species under special measures for conservation. Fifty six liver tissue samples were taken from dead individuals accidentally caught or found stranded along the Brazilian coastal area (six states). The extensively used octocrylene (2-ethylhexyl-2-cyano-3,3-diphenyl-2-propenoate, OCT) was frequently found in the samples investigated (21 out of 56) at concentrations in the range 89-782 ng·g(-1) lipid weight. São Paulo was found to be the most polluted area (70% frequency of detection). Nevertheless, the highest concentration was observed in the dolphins from Rio Grande do Sul (42% frequency of detection within that area). These findings constitute the first data reported on the occurrence of UV filters in marine mammals worldwide.

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