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Peak prioritization is one of the key steps in non-target screening of environmental samples to direct the identification efforts to relevant and important features. Occurrence of chemicals is sometimes a function of time and their presence in consecutive days (trend) reveals important aspects such as discharges from agricultural, industrial or domestic activities. This study presents a validated computational framework based on deep learning conventional neural network to classify trends of chemicals over 30 consecutive days of sampling in two sampling sites (upstream and downstream of a river). From trend analysis and factor analysis, the chemicals could be classified into periodic, spill, increasing, decreasing and false trend. The developed method was validated with list of 42 reference standards (target screening) and applied to samples. 25 compounds were selected by the deep learning and identified via non-target screening. Three classes of surfactants were identified for the first time in river water and two of them were never reported in the literature. Overall, 21 new homologous series of the newly identified surfactants were tentatively identified. The aquatic toxicity of the identified compounds was estimated by in silico tools and a few compounds along with their homologous series showed potential risk to aquatic environment.

Per- and polyfluoroalkyl substances (PFAS) are under regulatory scrutiny since some of them are persistent, bioaccumulative, and toxic. The occurrence of 4777 PFAS was investigated in the Danube River Basin (DRB; 11 countries) using target and suspect screening. Target screening involved investigation of PFAS with 56 commercially available reference standards. Suspect screening covered 4777 PFAS retrieved from the NORMAN Substance Database, including all individual PFAS lists submitted to the NORMAN Suspect List Exchange Database. Mass spectrometry fragmentation patterns and retention time index predictions of the studied PFAS were established for their screening by liquid chromatography - high resolution mass spectrometry using NORMAN Digital Sample Freezing Platform (DSFP). In total, 82 PFAS were detected in the studied 95 samples of river water, wastewater, groundwater, biota and sediments. Suspect screening detected 72 PFAS that were missed by target screening. Predicted no effect concentrations (PNECs) were derived for each PFAS via a quantitative structure-toxicity relationship (QSTR)-based approach and used for assessment of their environmental risk. Risk characterization revealed 18 PFAS of environmental concern in at least one matrix. The presence of PFAS in all studied environmental compartments across the DRB indicates a potentially large-scale migration of PFAS in Europe, which might require their further systematic regulatory monitoring.

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.

During ozonation in wastewater treatment plants, ozone reacts with emerging pollutants, which are partially removed through the secondary treatment, as long as, with their biotransformation products, triggering the formation of ozonation transformation products (TPs). Although the transformation of parent compounds (PCs) and their metabolites has been reported in the literature, the probable transformation of biotransformation products has not been investigated so far. This study evaluates the fate of citalopram (CTR) and four of its biotransformation products (DESCTR, CTRAM, CTRAC and CTROXO) during ozonation experiments. A Gaussian curve-based trend analysis was performed for the first time for the automated detection of TPs in ozone concentrations ranging from 0.06 to 12 mg/L. In total 46 ozonation TPs were detected; 7 TPs of CTR, 10 of DESCTR, 9 of CTRAM, 12 of CTRAC and 8 of CTROXO and were structurally elucidated based on their high resolution tandem mass spectra interpretation and tandem mass spectra similarity with the respective PC. Results have demonstrated that the examined compounds follow common transformation pathways in reaction with ozone and that common TPs were formed through the ozonation of different structurally-alike compounds. Moreover, the toxicity of the identified TPs was predicted with an in-house risk assessment program.

Treated wastewater irrigation (TWW) releases antibiotics and antibiotic resistance genes (ARGs) into the environment and might thus promote the dissemination of antibiotic resistance in groundwater (GW). We hypothesized that TWW irrigation increases ARG abundance in GW through two potential mechanisms: the contamination of GW with resistant bacteria and the accumulation of antibiotics in GW. To test this, the GW below a real-scale TWW-irrigated field was sampled for six months. Sampling took place before, during and after high-intensity TWW irrigation. Samples were analysed with 16S rRNA amplicon sequencing, qPCR of six ARGs and the class 1 integron-integrase gene intI1, while liquid chromatography tandem mass spectrometry was performed to detect antibiotic and pharmaceutical residues. Absolute abundance of 16S rRNA in GW decreased rather than increased during long-term irrigation. Also, the relative abundance of TWW-related bacteria did not increase in GW during long-term irrigation. In contrast, long-term TWW irrigation increased the relative abundance of sul1 and intI1 in the GW microbiome. Furthermore, GW contained elevated concentrations of sulfonamide antibiotics, especially sulfamethoxazole, to which sul1 confers resistance. Total sulfonamide concentrations in GW correlated with sul1 relative abundance. Consequently, TWW irrigation promoted sul1 and intI1 dissemination in the GW microbiome, most likely due to the accumulation of drug residues.

Raw and treated leachate samples were collected from different landfills in Greece and analyzed for several groups of emerging contaminants using high resolution mass spectrometric workflows to investigate the possible threat from their discharge to the aquatic environment. Fifty-eight compounds were detected; 2−OH-benzothiazole was found at 84 % of the samples and perfluorooctanoic acid at 68 %. Bisphenol A, valsartan and 2−OH-benzothiazole had the highest average concentrations in raw leachates, after biological treatment and after reverse osmosis, respectively. In untreated leachates, Risk Quotients > 1 were calculated for 35 and 18 compounds when maximum and average concentrations were used, indicating an ecological threat for the aquatic environment. Leachates’ biological treatment partially removed COD and NH4+-N, as well as 52.3 % of total emerging contaminants. The application of reverse osmosis resulted in a 98 % removal of major pollutants, 99 % removal of total emerging contaminants and a significant decrease of ecotoxicity to Lemna minor. Beside the decrease of the detected micropollutants during treatment, RQs > 1 were still calculated for 13 and 3 compounds after biological treatment and reverse osmosis, respectively. Among these, special attention should be given to 2−OH-benzothiazole and bisphenol A that had RQ values much higher than 1 for all tested organisms.

This study presents the development and validation of a comprehensive quantitative target methodology for the analysis of 2316 emerging pollutants in water based on Ultra-Performance Liquid Chromatography Quadrupole-Time-Of-Flight Mass Spectrometry (UPLC-Q-ToF-HRMS/MS). Target compounds include pesticides, pharmaceuticals, drugs of abuse, industrial chemicals, doping compounds, surfactants and transformation products, among others. The method was validated for 195 analytes, chosen to be representative of the chemical space of the target list, enabling the assessment of the performance of the method. The method involves a generic sample preparation based on mixed mode solid phase extraction, a UPLC-QTOF-MS/MS screening method using Data Independent Acquisition (DIA) mode, which provides MS and MS/MS spectra simultaneously and an elaborate strong post-acquisition evaluation of the data. The processing method was optimized to provide a successful identification rate >95 % and to minimize the number of false positive results (< 5 %). Decision limit (CCα) and detection capability (CCβ) were also introduced in the validation scheme to provide more realistic metrics on the performance of a HRMS-based wide-scope screening method. A new system of identification points (IPs) based on the one described in the Commission Decision 2002/657/EC was applied to communicate the confidence level in the identification of the analytes. This system considers retention time, mass accuracy, isotopic fit and fragmentation; taking full advantage of the capacities of the HRMS instruments. Finally, 398 contaminants were detected and quantified in real wastewater This project was implemented under the Operational Program “Education and Lifelong Learning” and funded by the European Union (European Social Fund) and Greek National Resources – ARISTEIA 624 (TREMEPOL project). Pablo Gago-Ferrero acknowledges the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement Smart-Workflow No 747698

The fate of four antimicrobials (cefadroxil, CFD; metronidazole, METRO; trimethoprim, TRI; sulfamethoxazole, SMX) was studied in Lemna minor systems and the role of different mechanisms on their removal was evaluated. All micropollutants were significantly removed in batch experiments with active Lemna minor; the highest removal was observed for CFD (100% in 14 d), followed by METRO (96%), SMX (73%) and TRI (59%) during 24 d of the experiment. Calculation of kinetic constants for hydrolysis, photodegradation, sorption to biomass and plant uptake revealed significant differences depending on the compound and the studied mechanism. For METRO, TRI and SMX the kinetic constants of plant uptake were by far higher comparing to those of the other mechanisms. The transformation products of antimicrobials were identified using UHPLC-QToF-MS. Two were the main degradation pathways for TRI; hydroxylation takes place during both phyto- and photodegradation, while demethylation occurs only in absence of Lemna minor. The operation of a continuous-flow duckweed system showed METRO and TRI removal equal to 71 ± 11% and 61 ± 8%, respectively. The application of mass balance and the use of published biodegradation constants showed that plant uptake and biodegradation were the major mechanisms governing METRO removal; the most important mechanism for TRI was plant uptake.

Hydrophilic interaction liquid chromatography (HILIC) and reversed phase LC (RPLC) coupled to high resolution mass spectrometry (HRMS) are widely used for the identification of suspects and unknown compounds in the environment. For the identification of unknowns, apart from mass accuracy and isotopic fitting, retention time (tR) and MS/MS spectra evaluation is required. In this context, a novel comprehensive workflow was developed to study the tR behavior of large groups of emerging contaminants using Quantitative Structure-Retention Relationships (QSRR). 682 compounds were analyzed by HILIC-HRMS in positive Electrospray Ionization mode (ESI). Moreover, an extensive dataset was built for RPLC-HRMS including 1830 and 308 compounds for positive and negative ESI, respectively. Support Vector Machines (SVM) was used to model the tR data. The applicability domains of the models were studied by Monte Carlo Sampling (MCS) methods. The MCS method was also used to calculate the acceptable error windows for the predicted tR from various LC conditions. This paper provides validated models for predicting tR in HILIC/RPLC-HRMS platforms to facilitate identification of new emerging contaminants by suspect and non-target HRMS screening, and were applied for the identification of transformation products (TPs) of emerging contaminants and biocides in wastewater and sludge.

In this study, the removal of niflumic acid (NA) and the identification of its transformation products (TPs) during ozonation was investigated. The influence of initial ozone concentration and pH value on NA's removal was tested, while suspect and non-target screening approaches were followed for the identification of ozonation TPs. The structure elucidation was based on accurate mass and isotopic pattern criteria and interpretation of the acquired MS/MS spectra. Moreover, an in-house retention time prediction model was used as a supporting tool for their identification. Results indicated the highly reactivity of NA with the molecular ozone, since the reaction was extremely fast and was completed within the first minute of the reaction. A total of thirteen TPs of NA were identified, and their proposed structures show that the oxidation occurred in the heterocyclic ring of the molecule, while the aniline-like part remained intact by ozone attack due to the presence of the three fluoride atoms, which act as electron withdrawing groups. Ozonation experiments were conducted also using the most abundant TP of NA as parent compound. Three second generation TPs of NA were detected and possible structures were proposed.

The concentrations of nine emerging contaminants, including pharmaceutically active compounds (PhACs) (ibuprofen, IBF; naproxen, NPX; diclofenac, DCF; ketoprofen, KFN) and endocrine disrupting chemicals (triclosan, TCS; bisphenol, BPA; nonylphenol, NP; nonylphenol monoethoxylate, NP1EO; nonylphenol diethoxylate, NP2EO), were determined in wastewater and sludge samples of two wastewater treatment plants (WWTPs) in Greece. Average concentrations in raw and treated wastewater ranged from 0.39 (KFN) to 12.52 μg L(-1) (NP) and fromLOD (IBF) to 0.80 μg L(-1) (DCF), respectively. A significant part of nonylphenols (NPs) and TCS in influent wastewater was bound to the particulate phase, while PhACs and BPA were mainly detected in the aqueous phase. Removal of target compounds during wastewater treatment ranged between 39% (DCF) and 100% (IBF). Except of DCF and BPA, similar removal efficiencies were observed in both WWTPs and no effect of WWTP's size and operational conditions was noticed. Use of mass balances showed that accumulation on sludge was a significant removal mechanism for NPs and TCS, while biodegradation/biotransformation was the major mechanism for the other compounds. Sampling of raw and digested sludge demonstrated that IBF and NPX are significantly removed (80%) during anaerobic digestion, whereas removal of EDCs was lower, ranging up to 55% for NP1EO.

After consumption, pharmaceuticals are excreted as parent compounds and/or metabolites in urine and faeces. Some are not completely removed during wastewater treatments, forcing sewage treatment plants (STPs) to apply alternative technologies to guarantee quality of treated water. To monitor the removal efficiency of STPs, not only unchanged compounds and metabolites have to be taken into account, but also formation of possible transformation products (TPs). In this work, QTOF MS has been used for screening metabolites/TPs of pharmaceuticals in effluent wastewater from Athens. A customised database was built with the exact masses of metabolites reported in literature for the parent drugs found in an initial screening. Additionally, TPs identified in previous degradation experiments performed at our laboratory were included. Up to 34 metabolites/TPs were detected for omeprazole, venlafaxine, clindamycin, clarithromycin, clopidogrel or dipyrone, among others. Seven corresponded to TPs whose reference standards were available at our lab, seven were TPs previously identified in laboratory degradation experiments, eight were TPs tentatively identified by QTOF MS without reference standards, and twelve TPs were discovered after using the common fragmentation pathway approach. Tentative identification of TPs was supported by prediction of their chromatographic retention time based on the use of advanced chemometric QSRR models. The authors acknowledge the financial support from Plan Nacional de I+D+i, Ministerio de Economía y Competitividad (Project ref CTQ2012-36189), and from Generalitat Valenciana (Group of Excellence Prometeo 2009/054; Collaborative Research on Environment and Food Safety, ISIC/2012/016). This research has also been co-financed by the European Union and Greek national funds through the Operational Program “Education and Lifelong Learning” of the National Strategic Reference Framework (NSRF)—ARISTEIA 624 (TREMEPOL project). Richard Bade acknowledges the European Union for his Early Stage Researcher (ESR) contract as part of the EU-International Training Network SEWPROF (Marie Curie—PEOPLE Grant #317205).

© 2016 Elsevier B.V. This review focuses on the removal of emerging contaminants (ECs) by biological, chemical and hybrid technologies in effluents from wastewater treatment plants (WWTPs). Results showed that endocrine disruption chemicals (EDCs) were better removed by membrane bioreactor (MBR), activated sludge and aeration processes among different biological processes. Surfactants, EDCs and personal care products (PCPs) can be well removed by activated sludge process. Pesticides and pharmaceuticals showed good removal efficiencies by biological activated carbon. Microalgae treatment processes can remove almost all types of ECs to some extent. Other biological processes were found less effective in ECs removal from wastewater. Chemical oxidation processes such as ozonation/H2O2, UV photolysis/H2O2 and photo-Fenton processes can successfully remove up to 100% of pesticides, beta blockers and pharmaceuticals, while EDCs can be better removed by ozonation and UV photocatalysis. Fenton process was found less effective in the removal of any types of ECs. A hybrid system based on ozonation followed by biological activated carbon was found highly efficient in the removal of pesticides, beta blockers and pharmaceuticals. A hybrid ozonation-ultrasound system can remove up to 100% of many pharmaceuticals. Future research directions to enhance the removal of ECs have been elaborated.

The fate of four benzotriazoles [1-H-benzotriazole (1-H-BTRi), tolyltriazole (TTRi), xylyltriazole (XTRi) and 1-hydroxy-benzotriazole (1-OH-BTRi)] and three benzothiazoles [benzothiazole (BTH), 2-hydroxy-benzothiazole (2-OH-BTH) and 2-amino-benzothiazole (2-amino-BTH)], during chlorination batch experiments was investigated. In the first step, their degradation under different experimental conditions (applied molar ratio of NaOCl and the target contaminant (m.r.), reaction’s contact time, pH value of the reaction’s solution and the influence of total suspended solids (TSS) presence) was investigated and their removal kinetics parameters (kobs and t1/2) were determined. In the second step, LC-QTOFMS/MS was used for the detection and identification of transformation products (TPs) formed during chlorination, through the application of suspect and non-target screening approaches. Four and five TPs of XTRi and 2-amino-BTH, respectively, were detected and tentatively identified, while 1-H-BTRi was proven to be formed by the chlorination of 1-OH-BTRi. Moreover, since the identified TPs were also detected in spiked wastewater samples, after lab-scale chlorination experiments, toxicity assessment was carried out by ECOSAR calculations for the environmental relevance of their occurrence. The proposed chlorinated TPs were proven to be more toxic than their parent compounds.

The ecological threat associated with emerging pollutants detected in wastewater was estimated in country level. Treated wastewater was analyzed for pharmaceuticals and illicit drugs; whereas the concentrations of all emerging contaminants determined in Greek Sewage Treatment Plants were recorded through literature review. Toxicity data was collected after literature review or using ECOSAR and risk quotients (RQs) were calculated for treated wastewater and 25 Greek rivers, for 3 different aquatic organisms (fish, daphnia magna, algae). According to the results, monitoring data was available for 207 micropollutants belonging to 8 different classes. RQ>1 was calculated for 30 compounds in secondary treated wastewater. Triclosan presented RQ>1 (in algae) for all studied rivers; decamethylcyclopentasilane (in daphnia magna), caffeine (in algae) and nonylphenol (in fish) presented RQ>1 in rivers with dilution factors (DF) equal or lower to 1910, 913 and 824, respectively. The class of emerging contaminants that present the greatest threat due to single or mixture toxicity was endocrine disrupters. The mixture of microcontaminants seems to pose significant ecological risk, even in rivers with DF equal to 2388. Future national monitoring programs should include specific microcontaminants that seem to possess environment risk to surface water.

The concentrations of eighteen perfluorinated compounds (PFCs: C5–C14 carboxylates, C4, C6–C8 and C10 sulfonates and 3 sulfonamides) were determined in wastewater and sludge samples originating from two different wastewater treatment plants (WWTPs). The analytes were extracted by solid phase extraction (dissolved phase) or sonication followed by solid phase extraction (solid phase). Qualitative and quantitative analyses were performed by LC–MS/MS. According to the results, perfluoropentanoic acid (PFPeA), perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) were dominant in wastewater and sludge samples from both plants. The average concentrations in the raw and treated wastewater ranged up to 75.7 ng L−1 (perfluorotridecanoic acid, PFTrDA) and 76.0 ng L−1 (PFPeA), respectively. Concentrations of most PFCs were higher in effluents than in influents, indicating their formation during wastewater treatment processes. In sewage sludge, the average concentrations ranged up to 6.7 ng g−1 dry weight (PFOS). No significant seasonal variations in PFCs concentrations were observed, while higher concentrations of PFOA, PFOS and perfluorononanoic acid (PFNA) were determined in the WWTP receiving municipal and industrial wastewater. Significantly different distribution coefficient (Kd) values were determined for different PFCs and different type of sludge, ranging between 169 L kg−1 (PFHxS) to 12,922 L kg−1 (PFDA).