Application of a novel prioritisation strategy using non-target screening for evaluation of temporal trends (1969–2017) of contaminants of emerging concern (CECs) in archived lynx muscle tissue samples

Most environmental monitoring studies of contaminants of emerging concern (CECs) focus on aquatic species and target specific classes of CECs. Even with wide-scope target screening methods, relevant CECs may be missed. In this study, non-target screening (NTS) was used for tentative identification of potential CECs in muscle tissue of the terrestrial top predator Eurasian lynx (Lynx lynx). Temporal trend analysis was applied as a prioritisation tool for archived samples, using univariate statistical tests (Mann-Kendall and Spearman rank). Pooled lynx muscle tissue collected from 1969 to 2017 was analysed with an eight-point time series using a previously validated screening workflow. Following peak detection, peak alignment, and blank subtraction, 12,941 features were considered for statistical analysis. Prioritisation by time-trend analysis detected 104 and 61 features with statistically significant increasing and decreasing trends, respectively. Following probable molecular formula assignment and elucidation with MetFrag, two compounds with increasing trends, and one with a decreasing trend, were tentatively identified. These results show that, despite low expected concentration levels and high matrix effects in terrestrial species, it is possible to prioritise CECs in archived lynx samples using NTS and univariate statistical approaches. © 2022 The Author

Untargeted time-pattern analysis of LC-HRMS data to detect spills and compounds with high fluctuation in influent wastewater

Peak prioritization plays a key role in non-target analysis of complex samples in order to focus the elucidation efforts on potentially relevant substances. The present work shows the development of a computational workflow capable of detecting compounds that exhibit large variation in intensity over time. The developed approach is based on three open-source R packages (xcms, CAMERA and TIMECOURSE) and includes the use of the statistical test Multivariate Empirical Bayes Approach to rank the compounds based on the Hotelling T2 coefficient, which is an indicator of large concentration variations of unknown components. The approach was applied to replicate series of 24 h composite flow-proportional influent wastewater samples collected during 8 consecutive days. 60 events involving unknown substances with high fluctuation over time were successfully prioritized. 14 of those compounds were tentatively identified using HRMS/MS libraries, chemical databases, in-silico fragmentation tools, and retention time prediction models. Four compounds were confirmed with standards from which two never reported before in wastewater. © 2018 Elsevier B.V

Two stage algorithm vs commonly used approaches for the suspect screening of complex environmental samples analyzed via liquid chromatography high resolution time of flight mass spectroscopy: A test study

LC–HR–QTOF–MS recently has become a commonly used approach for the analysis of complex samples. However, identification of small organic molecules in complex samples with the highest level of confidence is a challenging task. Here we report on the implementation of a two stage algorithm for LC–HR–QTOF–MS datasets. We compared the performances of the two stage algorithm, implemented via NIVA_MZ_Analyzer™, with two commonly used approaches (i.e. feature detection and XIC peak picking, implemented via UNIFI by Waters and TASQ by Bruker, respectively) for the suspect analysis of four influent wastewater samples. We first evaluated the cross platform compatibility of LC–HR–QTOF–MS datasets generated via instruments from two different manufacturers (i.e. Waters and Bruker). Our data showed that with an appropriate spectral weighting function the spectra recorded by the two tested instruments are comparable for our analytes. As a consequence, we were able to perform full spectral comparison between the data generated via the two studied instruments. Four extracts of wastewater influent were analyzed for 89 analytes, thus 356 detection cases. The analytes were divided into 158 detection cases of artificial suspect analytes (i.e. verified by target analysis) and 198 true suspects. The two stage algorithm resulted in a zero rate of false positive detection, based on the artificial suspect analytes while producing a rate of false negative detection of 0.12. For the conventional approaches, the rates of false positive detection varied between 0.06 for UNIFI and 0.15 for TASQ. The rates of false negative detection for these methods ranged between 0.07 for TASQ and 0.09 for UNIFI. The effect of background signal complexity on the two stage algorithm was evaluated through the generation of a synthetic signal. We further discuss the boundaries of applicability of the two stage algorithm. The importance of background knowledge and experience in evaluating the reliability of results during the suspect screening was evaluated. © 2017 Elsevier B.V

Occurrence and spatial distribution of 158 pharmaceuticals, drugs of abuse and related metabolites in offshore seawater

The occurrence and spatial distribution of 158 pharmaceuticals and drugs of abuse were studied in seawater of the EasternMediterranean Sea (Saronikos Gulf and Elefsis Bay in central Aegean Sea). This area is affected by various anthropogenic pressures as it receives the treated wastewater of the greatest Athens area and off-shore input fluxes. This study constitutes the largest one in terms of number of analytes in this environmental compartment. It provides the first evidence on the occurrence of several pharmaceuticals in marine environment including amoxicillin, lidocaine, citalopram or tramadol, among others. 22 sampleswere collected at three different depths in 9 sampling stations in order to assess the presence and the spatial distribution of the target compounds. A multi-residue method based on solid phase extraction and liquid chromatography coupled to tandem mass spectrometry was developed for the determination of the 158 target substances and validated for seawater sample analysis. 38 out of the 158 target compounds were detected, 15 of them with frequencies of detection equal to or higher than 50%. The highest detected values corresponded to amoxicillin, caffeine and salicylic acid, with concentrations in the range of b5.0-127.8 ng L-1; 5.2-78.2 ng L-1 and b0.4-53.3 ng L-1, respectively. Inputs fromthewastewater treatment plant(WWTP) of Athens revealed to be the main source of pollution in the Inner Saronikos Gulf, whereas, other anthropogenic pressures such as contamination fromshipping activity, industrial effluents, dredging and/or inputs fromland proved to be also relevant. The concentrations of some compounds varied significantly with depth suggesting that currents play an important role in the dilution of the target compounds. © 2015 Elsevier B.V

Assessment of the chemical pollution status of the Dniester River Basin by wide-scope target and suspect screening using mass spectrometric techniques

The quality of the Dniester River Basin has been seriously impacted by the chemicals released by agriculture, industry, and wastewater discharges. To assess its current chemical pollution status, a transboundary monitoring campaign was conducted in May 2019. Thirteen surface water, 13 sediment, and three biota samples were collected and analyzed using generic sample preparation methods for the determination of organic substances by liquid chromatography high-resolution mass spectrometry (LC-HRMS) and metals by inductively coupled plasma mass spectrometry (ICP-MS). Wide-scope target and suspect screening resulted in detection of Water Framework Directive (WFD) priority substances and emerging contaminants, whereas the raw data were stored in NORMAN Digital Sample Freezing Platform (DSFP) for future retrospective screening. Furthermore, risk assessment was performed to prioritize detected substances and propose a draft list of river basin–specific pollutants. All studied metals (As, Hg, Zn, Cu, Cr, Cd, Pb, Ni) were detected in the surface water and sediments. In total, 139 organic contaminants belonging to various chemical classes (pesticides, pharmaceuticals, drugs of abuse, stimulants, sweeteners, industrial chemicals, and their transformation products) were detected. The highest cumulative concentration of contaminants was observed in surface water from the Byk River, a tributary of the Dniester (Moldova). Concentrations of WFD priority substances diuron and mercury and EU Watch List neonicotinoid compounds imidacloprid and thiamethoxam exceeded their environmental quality standards (EQS), whereas concentrations of 23 emerging substances exceeded their predicted no-effect concentration (PNEC) at minimum one site. Emerging contaminants telmisartan, metolachlor, terbuthylazine, and 4-acetamidoantipyrine were prioritized as potential river basin–specific pollutants. [Figure not available: see fulltext.]. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature

NORMAN digital sample freezing platform: A European virtual platform to exchange liquid chromatography high resolution-mass spectrometry data and screen suspects in “digitally frozen” environmental samples

A platform for archiving liquid chromatography high-resolution mass spectrometry (LC-HRMS) data was developed for the retrospective suspect screening of thousands of environmental pollutants with the ambition of becoming a European and possibly global standard. It was termed Digital Sample Freezing Platform (DSFP) and incorporates all the recent developments in the HRMS screening methods within the NORMAN Network. In the workflow, raw mass spectral data are converted into mzML, then mass spectral and chromatographic information on thousands of peaks of each sample is extracted into Data Collection Templates. The ‘digitally frozen’ samples can be retrospectively screened for the presence of virtually any compound amenable to LC–MS using a combination of information on its (i) exact mass, (ii) predicted retention time window in the chromatogram, (iii) isotopic fit and (iv) qualifier fragment ions. Its potential was demonstrated on monitoring of 670 antibiotics and 777 REACH chemicals from the Joint Black Sea Surveys (JBSS). © 2019 The Author

Occurrence and potential environmental risk of surfactants and their transformation products discharged by wastewater treatment plants

Seven-day composite effluent samples from a German monitoring campaign including 33 conventional wastewater treatment plants (WWTP) were analyzed for linear alkylbenzene sulfonates (LAS) and alkyl ethoxysulfates (AES) and were screened by wide-scope suspect screening for 1564 surfactants and their transformation products (TPs) by UHPLC-ESI-QTOF-MS. Corresponding seven-day composite influent samples of selected WWTPs showed high influent concentrations as well as very high removal rates for LAS and AES. However, average total LAS and AES effluent concentrations were still 14.4 μg/L and 0.57 μg/L, respectively. The LAS-byproducts di-alkyl tetralin sulfonates (DATSs), the TPs sulfophenyl alkyl carboxylic acids (SPACs) and sulfo-tetralin alkyl carboxylic acids (STACs) reached maximum effluent concentrations of 19 μg/L, 17 μg/L and 5.3 μg/L, respectively. In many cases the sum of the concentration of all LAS-related byproducts and TPs surpassed the concentration of the precursors. High concentrations of up to 7.4 μg/L were found for 41 polyethylenoglycol homologs. Quantified surfactants and their TPs and by-products together accounted for concentrations up to 82 μg/L in WWTP effluents. To determine the risk of individual surfactants and their mixtures, single homologs were grouped by a “weighted carbon number approach” to derive normalized Predicted No-Effect Concentrations (PNEC), based on experimental ecotoxicity data from existing risk assessments, complemented by suitable Quantitative Structure-Activity Relationships (QSAR) predictions. Predicted Environmental Concentrations (PEC) were derived by dividing effluent concentrations of surfactants by local dilution factors. Risks for all analyzed surfactants were below the commonly accepted PEC/PNEC ratio of 1 for single compounds, while contributions to mixture toxicity effects from background levels of LAS and DATS cannot be excluded. Maximum LAS concentrations exceeded half of its PNEC, which may trigger country-wide screening to investigate potential environmental risks. © 2019 Elsevier B.V