Registro de acceso restringido Este recurso no está disponible en acceso abierto por política de la editorial. No obstante, se puede acceder al texto completo desde la Universitat Jaume I o si el usuario cuenta con suscripción. Registre d'accés restringit Aquest recurs no està disponible en accés obert per política de l'editorial. No obstant això, es pot accedir al text complet des de la Universitat Jaume I o si l'usuari compta amb subscripció. Restricted access item This item isn't open access because of publisher's policy. The full--text version is only available from Jaume I University or if the user has a running suscription to the publisher's contents.

No abstract

A fast and memory-efficient calculation of theoretical isotope patterns is crucial for the routine interpretation of mass spectrometric data. For high-resolution experiments, calculations must procure the exact masses and probabilities of relevant isotopologues over a wide range of polyisotopic compounds, while pruning low-probable ones. Here, a novel albeit simple treelike structure is introduced to swiftly derive sets of relevant subisotopologues for each element in a molecule, which are then combined to the isotopologues of the full molecule. In contrast to existing approaches, transitions via single replacements of the most abundant isotope per element are used in separable tree branches to derive subisotopologues from each other. Moreover, the underlying transition trees prevent redundant replacements and permit the detection of the most probable isotopologue in a first phase. A relative threshold can then be exploited in a second parallelized phase for a precise prepruning of large fractions of the remaining subisotopologues. The gain in performance from such early pruning and the lower variation in the distortion of simulated data with use of relative rather than absolute thresholds were validated in a large-scale benchmark simulation, unprecedentedly comprising several thousand molecular formulas. Both the algorithm and a wealth of related features are freely available as R-package enviPat and as a user-friendly Web interface.

Upon partial degradation of polar organic micropollutants during activated sludge treatment, transformation products (TPs) may be formed that enter the aquatic environment in the treated effluent. However, TPs are rarely considered in prospective environmental risk assessments of wastewater-relevant compound classes such as pharmaceuticals and biocides. Here, we suggest and evaluate a tiered procedure, which includes a fast initial screening step based on high resolution tandem mass spectrometry (HR-MS/MS) and a subsequent confirmatory quantitative analysis, that should facilitate consideration of TPs formed during activated sludge treatment in the exposure assessment of micropollutants. At the first tier, potential biotransformation product structures of seven pharmaceuticals (atenolol, bezafibrate, ketoprofen, metoprolol, ranitidine, valsartan, and venlafaxine) and one biocide (carbendazim) were assembled using computer-based biotransformation pathway prediction and known human metabolites. These target structures were screened for in sludge-seeded batch reactors using HR-MS/MS. The 12 TPs found to form in the batch experiments were then searched for in the effluents of two full-scale, municipal wastewater treatment plants (WWTPs) to confirm the environmental representativeness of this first tier. At the second tier, experiments with the same sludge-seeded batch reactors were carried out to acquire kinetic data for major TPs that were then used as input parameters into a cascaded steady-state completely-stirred tank reactor (CSTR) model for predicting TP effluent concentrations. Predicted effluent concentrations of four parent compounds and their three major TPs were corroborated by comparison to 3-day average influent and secondary effluent mass flows from one municipal WWTP. CSTR model-predicted secondary effluent mass flows agreed within a factor of two with measured mass flows and confidence intervals of predicted and measured mass flows overlapped in all cases. The observed agreement suggests that the combination of batch-determined transformation kinetics with a simple WWTP model may be suitable for estimating aquatic exposure to TPs formed during activated sludge treatment. Overall, we recommend the tiered procedure as a realistic and cost-effective approach to include consideration of TPs of wastewater-relevant compounds into exposure assessment in the context of prospective chemical risk assessment.

Incomplete micropollutant elimination in wastewater treatment plants (WWTPs) results in transformation products (TPs) that are released into the environment. Improvements in analytical technologies have allowed researchers to identify several TPs from specific micropollutants but an overall picture of nontarget TPs is missing. In this study, we addressed this challenge by applying multivariate statistics to data collected with liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) and subsequent tandem HRMS (MS/MS) in order to characterize peaks detected in the influent and effluent of a WWTP. Known biotransformation reactions were used to link potential parent compounds and TPs, while the structural similarity of these pairs hypothesized by MS/MS similarity was used for further prioritization. The methodology was validated with a set of spiked compounds, which included 25 parent/TP pairs for which analytical standards were available. This procedure was then applied to nontarget data, and 20 potential parent and TP pairs were selected for identification. In summary, primarily a surfactant homologue series, with associated TPs, was detected. Some obstacles still remain, including spectral interferences from coeluting compounds and identification of TPs, whose structures are less likely to be present in compound databases. The workflow was developed using openly accessible tools and, after parameter adjustment, could be applied to any data set with before and after information about various biological or chemical processes.

Aqueous film-forming foams (AFFFs) are proprietary mixtures containing hydrocarbon surfactants and per-and polyfluoroalkyl substances (PFASs) that are used to extinguish hydrocarbonbased fuel fires. There is limited information on hydrocarbon surfactants in AFFFs and AFFF-contaminated groundwater even though hydrocarbon surfactants are more abundant (5−10% w/w) than PFASs (0.9− 1.5% w/w) in AFFFs. Eight commercial AFFFs manufactured between 1988 and 2012 and 10 AFFF-contaminated groundwaters collected from near source zones of fire-fighter training areas were analyzed for suspect hydrocarbon surfactants by liquid chromatography quadrupole time-of-flight mass spectrometry. A suspect list and a homologous series detection computational tool, enviMass, were combined to screen for hydrocarbon surfactants. Nine classes of hydrocarbon surfactants were detected in AFFFs including octylphenol polyethoxylates, linear alcohol ethoxylates, ethoxylated cocoamines, alkyl ether sulfates, alkyl amido dipropionates, linear alkyl benzenesulfonates, alkyl sulfates, and polyethylene glycols. Of those, six were also found in groundwater along with diethanolamines and alkyl amido betaines, which were not found in the eight archived AFFFs. This indicates that although aerobically biodegradable, hydrocarbon surfactants likely persist in groundwater due to anaerobic aquifer conditions. To the best of our knowledge, this is the first screening for hydrocarbon surfactants in AFFFs and in AFFFcontaminated groundwater.

Background A large proportion of polar anthropogenic compounds routinely released into the environment comprises homologue series, i.e., sets of chemicals differing in a repeating chemical unit. Using analytical techniques such as liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS), these compounds are readily measurable as signal sets with characteristic differences in mass and typically retention time. However, and despite such distinct characteristics, no computational approach for the direct, simultaneous and untargeted detection of all such signal sets comprising both LC and HRMS information has to date been presented.ResultsA fast two-staged approach has been developed to extract LC-HRMS signal patterns which can be indicative of homologous analytes. In a first stage, a k-d tree representation of picked LC-HRMS peaks is used to extract all feasible 3-tuples of peaks with restrictions in, e.g., mass defect differences. A second stage then recombines these 3-tuples to larger series tuples while ensuring smooth changes in their retention time characteristics. This unsupervised approach was evaluated for ten effluent samples from Swiss sewage treatment plants (STPs), in both positive and negative electrospray-ionization.ConclusionsBeside recovering all continuous series of previously identified homologues, substantial fractions of nontargeted peaks could subsequently be assigned into very diverse peak series, although assignments were often not unique. The latter ambiguities were resolved by a self-organizing map technique and revealed both distinctive series meshing and rivaling combinatorial solutions in the presence of isobaric or gapped series peaks. When comparing STPs, several ubiquitous yet partially low-frequent series mass differences emerged and may prioritize future identification efforts. The presented algorithm is freely available as part of the R package nontarget and as a user-friendly web-interface at www.envihomolog.eawag.ch.Graphical AbstractSearch for systematic series indicative of homologous compounds is based on a partitioned representation of LC-HRMS signal characteristics. This nontargeted search first extracts series triplets in a nearest-neighbour walk and then recombines them to larger ones. For illustration, the two dimensions involving mass defect characteristics are represented by one only Electronic supplementary materialThe online version of this article (doi:10.1186/s13321-017-0197-z) contains supplementary material, which is available to authorized users.

This study presents a nontarget approach to detect discharges from pharmaceutical production in municipal wastewater treatment plant (WWTP) effluents and to estimate their relevance on the total emissions. Daily composite samples were collected for 3 months at two WWTPs in Switzerland, measured using liquid chromatography high-resolution mass spectrometry, and time series were generated for all features detected. The extent of intensity variation in the time series was used to differentiate relatively constant domestic inputs from highly fluctuating industrial emissions. We show that an intensity variation threshold of 10 correctly classifies compounds of known origin and reveals clear differences between the two WWTPs. At the WWTP receiving wastewater from a pharmaceutical manufacturing site, (i) 10 times as many potential industrial emissions were detected as compared to the WWTP receiving purely domestic wastewater; (ii) for 11 pharmaceuticals peak concentrations, >10 g/L and up to 214 g/L were quantified, which are clearly above typical municipal wastewater concentrations; and (iii) a pharmaceutical not authorized in Switzerland was identified. Signatures of potential industrial emissions were even traceable at the downstream Rhine monitoring station at a >4000-fold dilution. Several of them occurred repeatedly, suggesting that they were linked to regular production, not to accidents. Our results demonstrate that small wastewater volumes from a single industry not only left a clear signature in the effluents of the respective WWTP but also influenced the water quality of one of Europe's most important river systems. Overall, these findings indicate that pharmaceutical production is a relevant emission source even in highly developed countries with a strong focus on water quality, such as Switzerland.