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Monitoring water quality is critical for mitigating risks to human health and the environment. It is also essential for ensuring high quality water-based and water-dependent products and services. The monitoring and detection of chemical contamination are often based around a small set of parameters or substances. Conventional monitoring often involves the collection of water samples in the field and subsequent analyses in the laboratory. Such strategies are expensive, time consuming, and focused on a narrow set of potential risks. They also induce a significant time delay between a contamination event and a possible reactive measure. Here, we developed a real-time monitoring system based on Artificial Intelligence (AI) for field deployable sensors. We used data obtained from full-scan UV-spec and fluorescence sensors for validation in this study. This multi-sensor system consists of (a) anomaly detection that uses multivariate statistical methods to detect any anomalous state in an aqueous environment and (b) anomaly identification, using Machine Learning (ML) to classify the anomaly into one of the a priori known categories. For a proof of concept, we tested this methodology on a supply of municipal drinking water and a few representative organic chemical contaminants applied in a laboratory-controlled environment. The outcomes confirm the ability for the multi-sensor system to detect and identify changes in water quality due to incidences of chemical contamination. The method may be applied to numerous other areas where water quality should be measured online and in real time, such as in surface-water, urban runoff, or food and industrial process water.

Environmental monitoring data for tire road wear particles are vastly limited compared to those for other microplastics, primarily due to analytical challenges with quantification. Recently, two ISO technical specifications have been released using pyrolysis GC-MS for quantification. However, these methods have major assumptions, including that the content of natural and synthetic rubber in tire tread is constant across formulations and that the pyrolysis products chosen are selective. This study analyzed a wide range of commercially available tires from Australia and Norway, using pyrolysis GC-MS to test these assumptions. The percent mass of synthetic rubber in tires (n = 39) was highly variable, ranging from

The European and U.S. chemical agencies have listed approximately 800k chemicals about which knowledge of potential risks to human health and the environment is lacking. Filling these data gaps experimentally is impossible, so in silico approaches and prediction are essential. Many existing models are however limited by assumptions (e.g., linearity and continuity) and small training sets. In this study, we present a supervised direct classification model that connects molecular descriptors to toxicity. Categories can be driven by either data (using k-means clustering) or defined by regulation. This was tested via 907 experimentally defined 96 h LC50 values for acute fish toxicity. Our classification model explained ≈90% of the variance in our data for the training set and ≈80% for the test set. This strategy gave a 5-fold decrease in the frequency of incorrect categorization compared to a quantitative structure–activity relationship (QSAR) regression model. Our model was subsequently employed to predict the toxicity categories of ≈32k chemicals. A comparison between the model-based applicability domain (AD) and the training set AD was performed, suggesting that the training set-based AD is a more adequate way to avoid extrapolation when using such models. The better performance of our direct classification model compared to that of QSAR methods makes this approach a viable tool for assessing the hazards and risks of chemicals.

Non-target analysis (NTA) employing high-resolution mass spectrometry is a commonly applied approach for the detection of novel chemicals of emerging concern in complex environmental samples. NTA typically results in large and information-rich datasets that require computer aided (ideally automated) strategies for their processing and interpretation. Such strategies do however raise the challenge of reproducibility between and within different processing workflows. An effective strategy to mitigate such problems is the implementation of inter-laboratory studies (ILS) with the aim to evaluate different workflows and agree on harmonized/standardized quality control procedures. Here we present the data generated during such an ILS. This study was organized through the Norman Network and included 21 participants from 11 countries. A set of samples based on the passive sampling of drinking water pre and post treatment was shipped to all the participating laboratories for analysis, using one pre-defined method and one locally (i.e. in-house) developed method. The data generated represents a valuable resource (i.e. benchmark) for future developments of algorithms and workflows for NTA experiments., Measurement(s)chemical • drinking waterTechnology Type(s)high resolution mass spectrometry • non-target analysis • InterlaboratoryFactor Type(s)methodSample Characteristic - Environmentlaboratory environment Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.15028665

The COVID-19 outbreak has forced countries to introduce severe restrictive measures to contain its spread. In particular, physical distancing and restriction of movement have had important consequences on human behaviour and potentially also on illicit drug use and supply. These changes can be associated with additional risks for users, in particular due to reduced access to prevention and harm reduction activities. Furthermore, there have been limitations in the amount of data about drug use which can be collected due to restrictions. To goal of this study was to obtain information about potential changes in illicit drug use impacted by COVID-19 restrictions. Wastewater samples were collected in seven cities in the Netherlands, Belgium, Spain and Italy at the beginning of lockdowns (March-May 2020). Using previously established and validated methods, levels of amphetamine (AMP), methamphetamine (METH), MDMA, benzoylecgonine (BE, the main metabolite of cocaine) and 11-nor-9-carboxy-Δ9-tetrahydrocannabinol (THC-COOH, main metabolite of tetrahydrocannabinol (THC)) were measured and compared with findings from previous years. Important differences in levels of consumed drugs were observed across the considered countries. Whilst for some substances and locations, marked decreases in consumption could be observed (e.g., 50% decrease in MDMA levels compared to previous years). In some cases, similar or even higher levels compared to previous years could be found. Changes in weekly patterns were also observed, however these were not clearly defined for all locations and/or substances. Findings confirm that the current situation is highly heterogeneous and that it remains very difficult to explain and/or predict the effect that the present pandemic has on illicit drug use and availability. However, given the current difficulty in obtaining data due to restrictions, wastewater analysis can provide relevant information about the situation at the local level, which would be hard to obtain otherwise.

Wastewater-based epidemiology is an additional indicator of drug use that is gaining reliability to complement the current established panel of indicators. The aims of this study were to: (i) assess spatial and temporal trends of population-normalized mass loads of benzoylecgonine, amphetamine, methamphetamine and 3,4-methylenedioxymethamphetamine (MDMA) in raw wastewater over 7 years (2011-17); (ii) address overall drug use by estimating the average number of combined doses consumed per day in each city; and (iii) compare these with existing prevalence and seizure data.Analysis of daily raw wastewater composite samples collected over 1 week per year from 2011 to 2017.Catchment areas of 143 wastewater treatment plants in 120 cities in 37 countries.Parent substances (amphetamine, methamphetamine and MDMA) and the metabolites of cocaine (benzoylecgonine) and of ΔBenzoylecgonine was the stimulant metabolite detected at higher loads in southern and western Europe, and amphetamine, MDMA and methamphetamine in East and North-Central Europe. In other continents, methamphetamine showed the highest levels in the United States and Australia and benzoylecgonine in South America. During the reporting period, benzoylecgonine loads increased in general across Europe, amphetamine and methamphetamine levels fluctuated and MDMA underwent an intermittent upsurge.The analysis of wastewater to quantify drug loads provides near real-time drug use estimates that globally correspond to prevalence and seizure data.

Modeling and prediction of a city’s (Oslo, Norway) daily dynamic population using mobile device-based population activity data and three low cost markers is presented for the first time. Such data is useful for wastewater-based epidemiology (WBE), which is an approach used to estimate the population level use of licit and illicit drugs, new psychoactive substances, human exposure to a wide range of pollutants, such as pesticides or phthalates, as well as the release of endogenous substances such as oxidative stress and allergen biomarkers. Comparing WBE results between cities often requires normalization to population size, and inaccuracy in the measured population can introduce high levels of uncertainty. In this study mobile phone data from 8-weeks in 2016 was used to train three linear models based on drinking water production, electricity consumption and online measurements of ammonium in wastewater. The ammonium model showed the best correlation with R2 = 0.88 while drinking water production and electricity consumption showed more discrepancies. The three models were then re-evaluated against 5-week of mobile phone data from 2017 showing mean absolute errors

According to estimates put forward in multiple studies, tire and road wear particles are one of the largest sources to microplastic contamination in the environment. There are large uncertainties associated with local emissions and transport of tire and road wear particles into environmental compartments, highlighting an urgent need to provide more data on inventories and fluxes of these particles. To our knowledge, the present paper is the first published data on mass concentrations and snow mass load of tire and polymer-modified road wear particles in snow. Roadside snow and meltwater from three different types of roads (peri-urban, urban highway and urban) were analysed by Pyrolysis Gas Chromatography Mass Spectrometry. Tire particle mass concentrations in snow (76.0–14,500 mg/L meltwater), and snow mass loads (222–109,000 mg/m2) varied widely. The concentration ranges of polymer-modified particles were 14.8–9550 mg/L and 50.0–28,800 mg/m2 in snow and meltwater, respectively. Comparing the levels of tire and PMB particles to the total mass of particles, showed that tire and PMB-particles combined only contribute to 5.7% (meltwater) and 5.2% (mass load) of the total mass concentration of particles. The large variation between sites in the study was investigated using redundancy analysis of the possible explanatory variables. Contradictory to previous road studies, speed limit was found to be one of the most important variables explaining the variation in mass concentrations, and not Annual Average Daily Traffic. All identified variables explained 69% and 66%, for meltwater and mass load concentrations, respectively. The results show that roadside snow contain total suspended solids in concentrations far exceeding release limits of tunnel and road runoff, as well as tire particles in concentrations comparable to levels previously reported to cause toxicity effects in organisms. These findings strongly indicate that roadside snow should be treated before release into the environment.

Naphthenic acids (NAs) constitute one of the toxic components of the produced water (PW) from offshore oil platforms discharged into the marine environment. We employed liquid chromatography (LC) coupled to high-resolution mass spectrometry with electrospray ionization (ESI) in negative mode for the comprehensive chemical characterization and quantification of NAs in PW samples from six different Norwegian offshore oil platforms. In total, we detected 55 unique NA isomer groups, out of the 181 screened homologous groups, across all tested samples. The frequency of detected NAs in the samples varied between 14 and 44 isomer groups. Principal component analysis (PCA) indicated a clear distinction of the PW from the tested platforms based on the distribution of NAs in these samples. The averaged total concentration of NAs varied between 6 and 56 mg L-1, among the tested platforms, whereas the concentrations of the individual NA isomer groups ranged between 0.2 and 44 mg L-1. Based on both the distribution and the concentration of NAs in the samples, the C8H14O2 isomer group appeared to be a reasonable indicator of the presence and the total concentration of NAs in the samples with a Pearson correlation coefficient of 0.89.

Pesticides offer many benefits for humanity and agriculture, but at the same time pose a potential risk to human health because of their widespread use and high biological activity. Human biomonitoring (HBM) studies are the main tool to investigate human exposure to pesticides and other chemicals, but face limitations such as sampling biases, long time to complete and high costs. Wastewater-based epidemiology (WBE) is an alternative approach that is centered on the chemical analysis of biomarkers of (pesticide) exposure in urban wastewater. The present study used WBE to assess human exposure to selected classes of pesticides, triazines, pyrethroids and organophosphates, in Norway. Untreated wastewater samples were collected from four cities, covering approximately 20% of the Norwegian population. The highest population weighted mass loads (mg/day/1000 inhabitants) were for alkyl phosphates and the lowest for triazines. Some differences were observed for the two metabolites, 2-isopropyl-6-methyl-4-pyrimidinol (IMPY) and 3-(2,2-dichlorovinyl)-2,2-dimethyl-(1-cyclopropane) carboxylic acid (DCCA), which were higher in the rural city of Hamar. WBE figures were comparable with HBM findings for the specific metabolite of chlorpyrifos and chlorpyrifos methyl (3,5,6-trichloro-2-pyridinol; TCPY) but were different for the alkyl phosphates. Pyrethroid intake was calculated and was lower than the acceptable daily intake in all the cities, indicating low risk for human health. This is the most extensive WBE study performed to date to assess national human exposure to pesticides. This study demonstrated that WBE has the potential to be a useful complementary biomonitoring tool for assessing population-wide exposure to pesticides, overcoming some of the limitations of HBM.

Background and aims Wastewater‐based epidemiology is an additional indicator of drug use that is gaining reliability to complement the current established panel of indicators. The aims of this study were to: (i) assess spatial and temporal trends of population‐normalized mass loads of benzoylecgonine, amphetamine, methamphetamine and 3,4‐methylenedioxymethamphetamine (MDMA) in raw wastewater over 7 years (2011–17); (ii) address overall drug use by estimating the average number of combined doses consumed per day in each city; and (iii) compare these with existing prevalence and seizure data. Design Analysis of daily raw wastewater composite samples collected over 1 week per year from 2011 to 2017. Setting and Participants Catchment areas of 143 wastewater treatment plants in 120 cities in 37 countries. Measurements Parent substances (amphetamine, methamphetamine and MDMA) and the metabolites of cocaine (benzoylecgonine) and of Δ9‐tetrahydrocannabinol (11‐nor‐9‐carboxy‐Δ9‐tetrahydrocannabinol) were measured in wastewater using liquid chromatography–tandem mass spectrometry. Daily mass loads (mg/day) were normalized to catchment population (mg/1000 people/day) and converted to the number of combined doses consumed per day. Spatial differences were assessed world‐wide, and temporal trends were discerned at European level by comparing 2011–13 drug loads versus 2014–17 loads. Findings Benzoylecgonine was the stimulant metabolite detected at higher loads in southern and western Europe, and amphetamine, MDMA and methamphetamine in East and North–Central Europe. In other continents, methamphetamine showed the highest levels in the United States and Australia and benzoylecgonine in South America. During the reporting period, benzoylecgonine loads increased in general across Europe, amphetamine and methamphetamine levels fluctuated and MDMA underwent an intermittent upsurge. Conclusions The analysis of wastewater to quantify drug loads provides near real‐time drug use estimates that globally correspond to prevalence and seizure data., This study was supported by the following countries, institutions and projects Australia: Thyne Reid foundation; Canada: Natural Sciences and Engineering Research Council of Canada (NSERC); Iceland: The Icelandic Research Fund (Grant number 163049–051); Slovenia: Slovene Research Agency (funding Project L1–9191); Spain: MINECO/AEI projects (CTM2014–56628‐C3–2‐R, CTQ2015–65603‐P, CTM2016–81935‐REDT, CTM2017–84763‐C3–2‐R), Galician Council of Culture, Education and Universities (ED481D 2017/003); UK: Environmental Sustainability Knowledge Transfer Network, Engineering and Physical Sciences Research Council and Thermo Fisher Scientific (CASE industrial scholarship for K. Munro, Ref.: EP/J502029/1). European Monitoring Centre for Drugs and Drug Addiction (EMCDDA); EU International Training Network SEWPROF (Marie Curie‐FP7‐PEOPLE, grant number 317205); COST Action ES1307 supported by COST (European Cooperation in Science and Technology); WATCH (Wastewater Analysis of Traces of illicit drug‐related Chemicals for law enforcement and public Health DG migration and Home affairs ‐ HOME/2015/ISFP/PR/DRUG/0062). Sampling support and provision of catchment information Austria: Klemens Geiger and Michael Schlapp; Belgium: Jonathan Phariseau, Bart Coene, Luc Van Os, Peter Nys, Dieter Lemaire, Jean‐François Mougel, Patrick Vantroyen and Karel Claes; Croatia: Marin Ganjto; Czech Republic: Jiri Stara and Robert Hrich Brněnské; France: Véronique Bremont; Italy: Roberto Mazzini and Francesca Pizza (Milan), Francesco Avolio (Bologna), Fabrizio Moratto and Sergio Ghezzi (Gorizia), Rosanna Brienza and Simona Panariello (Potenza), Pier Paolo Abis and Antonia Attanasio (Bari), Antonella Cicala (Palermo); Norway: Pia Ryrfors; Portugal: João Goulão, José Martins, Pedro Alvaro and Fátima Paixão; Slovakia: Silvia Antalová and Jozef Tichy; Spain: Begoña Martínez López, Cristian Mesa, Santiago Querol Rodriguez, Fernando Llavador, Enrique Albors and Gloria Fayos; the Netherlands: Alex Veltman, Peter Theijssen, Peter van Dijk, Stefan Wijers, Mark Stevens, Ferry de Wilde. Analytical support Australia: Maulik Ghetia; Cyprus: Popi Karaolia; Greece: Nikoilaos Raikos; Spain: Ana Maria Botero‐Coy, Clara Boix, Alberto Celma, Jorge Pitarch, Inés Racamonde and Eddie Fonseca; Italy: Emma Gracia‐Lor, Nikolaos I. Rousis and Noelia Salgueiro‐Gonzalez. Data repository and data screening Eawag: Harald von Waldow; EMCDDA: Renate Hochwieser, Liesbeth Vandam, João Matias and Federica Mathis.

Roads are estimated to be the largest source of microplastic particles in the environment, through release of particles from tires, road markings and polymer-modified bitumen. These are all released through the wear and tear of tires and the road surface. During the winter in cold climates, the road surface may freeze and cause icing on the roads. To improve traffic safety during winter, road salt is used for de-icing. Knowledge of microplastic (MP) contamination in road salt has, until now, been lacking. This is contrary to the increasing number of studies of microplastics in food-grade salt. The objective of this study was to investigate if road salt could be an additional source of microplastics to the environment. Fourier-Transform Infrared spectroscopy (FT-IR) and Pyrolysis gas chromatography mass spectrometry (GC–MS) were employed to identify and quantify the polymer content in four types of road salts, three sea salts and one rock salt. The particle number of MP in sea salts (range 4–240 MP/kg, mean ± s.d. = 35 ± 60 MP/kg) and rock salt (range 4–192 MP/kg, 424 ± 61 MP/kg, respectively) were similar, whereas, MP mass concentrations were higher in sea salts (range 0.1–7650 μg/kg, 442 ± 1466 μg/kg) than in rock salts (1–1100 μg/kg, 322 ± 481 μg/kg). Black rubber-like particles constituted 96% of the total concentration of microplastics and 86% of all particles in terms of number of particles/kg. Black rubber-like particles appeared to be attributable to wear of conveyer belts used in the salt production. Road salt contribution to MP on state and county roads in Norway was estimated to 0.15 t/year (0.003% of total road MP release), 0.07 t/year in Sweden (0.008%) and 0.03 t/year in Denmark (0.0004–0.0008%) Thus, microplastics in road salt are a negligible source of microplastics from roads compared to other sources.

Embargo until 22 Nov 2019 This article presents a novel approach for the analysis of 13 drugs in wastewater for use in wastewater-based epidemiology (WBE) studies. Sample preparation remains one of the principal bottlenecks in modern high-throughput analysis by ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). The proposed methodology is based on the micro-extraction of small volumes (1 ml) of wastewater using a HLB 96-well microplate and both large volume injection (LVI) and post-loop mixing injection (PLM). With this configuration, the limits of quantification (LOQ) were below the reported environmental concentrations of the target compounds in wastewater. Furthermore, both the complexity of collecting, transporting and storing the wastewater sample, sample preparation time, cost and amount of solvent used are all diminished, enhancing the suitability of this methodology for future WBE studies. A new workflow is also proposed in order to create a virtual specimen library bank for WBE by using high-resolution mass spectrometry (HRMS). The method was validated and the limits of quantification were between 0.2 and 6.3 ng L−1. The relative standard deviations (RSD) for a standard mixture at 200 ng L−1 (n = 6) was between 3.4 and 14.4% while the recoveries for the 13 drug target residues (DTR) were between 92 and 110%. The developed and validated method was finally successfully applied to 10 wastewater samples collected from Oslo, Norway.

Wastewater-based epidemiology is an established approach for quantifying community drug use and has recently been applied to estimate population exposure to contaminants such as pesticides and phthalate plasticizers. A major source of uncertainty in the population weighted biomarker loads generated is related to estimating the number of people present in a sewer catchment at the time of sample collection. Here, the population quantified from mobile device-based population activity patterns was used to provide dynamic population normalized loads of illicit drugs and pharmaceuticals during a known period of high net fluctuation in the catchment population. Mobile device-based population activity patterns have for the first time quantified the high degree of intraday, week, and month variability within a specific sewer catchment. Dynamic population normalization showed that per capita pharmaceutical use remained unchanged during the period when static normalization would have indicated an average reduction of up to 31%. Per capita illicit drug use increased significantly during the monitoring period, an observation that was only possible to measure using dynamic population normalization. The study quantitatively confirms previous assessments that population estimates can account for uncertainties of up to 55% in static normalized data. Mobile device-based population activity patterns allow for dynamic normalization that yields much improved temporal and spatial trend analysis.

For the first time, ultra-high performance supercritical fluid chromatography (UHPSFC) coupled to tandem mass spectrometry has been used to determine cannabinoid and synthetic cannabinoid residues in wastewater. Combined with a downscaled version of the classic liquid-liquid extraction, the proposed method allows for the quantification of Δ9-tetrahydrocannabinol, three of its major metabolites (the monohydroxylated, the dehydroxylated, and the carboxylated species) and four synthetic cannabinoid metabolites (from the JWH-series) at low ng L−1 levels. Limits of quantification are in the 1–59 ng L−1 range, with recovery between 62 and 122% in ultrapure water and between 59 and 138% in wastewater. The applicability of the developed methodology was confirmed by the analysis of real wastewater, where cannabis metabolites could be positively quantified in all the samples analyzed. It is, therefore, a fast and simple alternative to common solid-phase extraction-liquid chromatography-mass spectrometry procedures for the determination of these low polar substances in water. Copyright © 2017 John Wiley & Sons, Ltd.

Aims To compare long-term trends in wastewater data with other indicators of stimulant use in three locations and to test the reliability of estimates based on one week of sampling.DesignComparison of trends in quantities (‘loads’) of stimulants or their metabolites in wastewater with trends in other indicators of stimulant use (e.g. treatment, police, population survey data).Setting and Participants Populations in Oslo (Norway), South-East Queensland (Australia) and Eindhoven (The Netherlands).Measurements Wastewater data were modelled for MDMA (3,4-Methylenedioxy methamphetamine), benzoylecgonine (a metabolite of cocaine), amphetamine and methamphetamine in Oslo; benzoylecgonine in Eindhoven; and methamphetamine in South-East Queensland. Choice of stimulants modelled in each region was primarily determined by availability of useable data.Findings In Oslo, wastewater data, driving under the influence of drugs statistics and seizure data all suggested increasing MDMA use between 2009 and 2017. In South-East Queensland, there was an estimated 31.1% (95%CI 29.4-32.9%) annualincrease in daily loads of methamphetamine in wastewater between 2009 and 2016, compared with a 14.1% (95%CI 10.9-17.3%) annual increase in seizures. Some of the increase in wastewater can be explained by increased purity. In Eindhoven, there was no evidence of a change in cocaine consumption from wastewater, but a reduction was observed in numbers in treatment for cocaine use from 2012 to 2017. In approximately half the cases examined in Oslo, credible intervals around estimates of annual average loads from a regression model versus estimates based on a single week of sampling did not overlap.ConclusionsLong-term trends in loads of stimulants in wastewater appear to be broadly consistent with trends in other indicators of stimulant use in three locations. Wastewater data should be interpreted alongside epidemiological indicators and purity data. One week of wastewater sampling may not be sufficient for valid inference about drug consumption.

The aquatic bioconcentration of a chemical is typically determined using conventional fish tests. To foster the approach of alternatives to animal testing, a combination of computational models and in vitro substrate depletion bioassays (e.g., primary hepatocytes) can be used. One recently developed in vitro assay is the three-dimensional (3D) hepatic spheroid model from rainbow trout (Oncorhynchus mykiss). The aim of the present study was to evaluate the metabolic competence of the 3D spheroids from rainbow trout when exposed to pyrene, using 2 different sampling procedures (SP1 and SP2). The results were compared with previously published intrinsic clearance (CL) results from S9 fractions and primary hepatocyte assays. Extraction of pyrene using SP1 suggested that the spheroids had depleted 33% of the pyrene within 4 h of exposure, reducing to 91% after 30 h. However, when applying SP2 a substantial amount (36%) of the pyrene was bound to the exposure vial within 2 h, decreasing after 6 h of exposure. Formation of hydroxypyrene-glucuronide (OH-PYR-Glu) was obtained throughout the study, displaying the metabolic competence of the 3D spheroids. The 2 sampling procedures yielded different CLin vitro , where pyrene depletion using SP2 was very similar to published studies using primary hepatocytes. The 3D spheroids demonstrated reproducibile, log-linear biotransformation of pyrene and displayed formation of OH-PYR-Glu, indicating their metabolic competence for 30 h or more. Environ Toxicol Chem 2019;38:1738-1747. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Comprehensive chemical characterization of naphthenic acids (NAs) in oilfield produced water is a challenging task due to sample complexity. The recovery of NAs from produced water, and the corresponding distribution of detectable NAs are strongly influenced by sample extraction methodologies. In this study, we evaluated the effect of the extraction method on chemical space (i.e. the total number of chemicals present in a sample), relative recovery, and the distribution of NAs in a produced water sample. Three generic and pre-established extraction methods (i.e. liquid-liquid extraction (Lq), and solid phase extraction using HLB cartridges (HLB), and the combination of ENV+ and C8 (ENV) cartridges) were employed for our evaluation. The ENV method produced the largest number of detected NAs (134 out of 181) whereas the HLB and Lq methods produced 108 and 91 positive detections, respectively, in the tested produced water sample. For the relative recoveries, the ENV performed better than the other two methods. The uni-variate and multi-variate statistical analysis of our results indicated that the ENV and Lq methods explained most of the variance observed in our data. When looking at the distribution of NAs in our sample the ENV method appeared to provide a more complete picture of the chemical diversity of NAs in that sample. Finally, the results are further discussed.

The analysis of illicit drugs in urban wastewater is the basis of wastewater-based epidemiology (WBE), and has received much scientific attention because the concentrations measured can be used as a new non-intrusive tool to provide evidence-based and real-time estimates of community-wide drug consumption. Moreover, WBE allows monitoring patterns and spatial and temporal trends of drug use. Although information and expertise from other disciplines is required to refine and effectively apply WBE, analytical chemistry is the fundamental driver in this field. The use of advanced analytical techniques, commonly based on combined chromatography-mass spectrometry, is mandatory because the very low analyte concentration and the complexity of samples (raw wastewater) make quantification and identification/confirmation of illicit drug biomarkers (IDBs) troublesome. We review the most-recent literature available (mostly from the last 5 years) on the determination of IDBs in wastewater with particular emphasis on the different analytical strategies applied. The predominance of liquid chromatography coupled to tandem mass spectrometry to quantify target IDBs and the essence to produce reliable and comparable results is illustrated. Accordingly, the importance to perform inter-laboratory exercises and the need to analyze appropriate quality controls in each sample sequence is highlighted. Other crucial steps in WBE, such as sample collection and sample pre-treatment, are briefly and carefully discussed. The article further focuses on the potential of high-resolution mass spectrometry. Different approaches for target and non-target analysis are discussed, and the interest to perform experiments under laboratory-controlled conditions, as a complementary tool to investigate related compounds (e.g., minor metabolites and/or transformation products in wastewater) is treated. The article ends up with the trends and future perspectives in this field from the authors' point of view. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 37:258-280, 2018.

The administration of anticancer drugs during chemotherapy treatments has increased considerably in recent years, and based on the growing incidence of cancer worldwide there is a foreseen increase in their use over the coming years. Many anticancer drugs are not removed by conventional wastewater treatment plants (WWTPs) and can therefore reach the aquatic environment and potentially threaten aquatic life. The objective of this work was to apply a suspect screening methodology to detect chemotherapy and radiotherapy drugs and their related compounds such metabolites and/or biomarkers in wastewater. The use of logical pre-determined criteria to refine the suspect list down to a relatively small number of relevant compounds greatly improved the efficiency of the analysis. Mass accuracy, isotopic patterns and predicted retention time were used to tentatively identify the suspects. Successful identification of cancer-related suspects included two antineoplastic hormones, two X-ray contrast agents and a pyrrolizidine alkaloid related to an herbal medicine. This is the first time that a suspect screening paradigm has been successfully applied to the identification of pharmaceuticals and biomarkers related to chemotherapy in wastewater.

The consumption of psychoactive substances is considered a growing probleminmany communities. Moreover, new psychoactive substances (NPS) designed as (legal) substitutes to traditional illicit drugs are relatively easily available to the public through e-commerce and retail shops, but there is little knowledge regarding the extent and actual use of these substances. This study aims to gain new and complementary information on NPS and traditional illicit drug use at sixmusic festivals across Europe by investigatingwastewater and pooled urine. Samples were collected, between 2015 and 2018, at six music festivals across Europe with approximately 465.000 attendees. Wastewater samples were also collected during a period not coinciding with festivals. A wide-scope screening for 197 NPS, six illicit drugs and known metabolites was applied using different chromatographymass spectrometric strategies. Several illicit drugs and in total 21 different NPS, mainly synthetic cathinones, phenethylamines and tryptamines, were identified in the samples. Ketamine and the traditional illicit drugs, such as amphetamine-type stimulants, cannabis and cocaine were most abundant and/or frequently detected in the samples collected, suggesting a higher use compared to NPS. The analyses of urine and wastewater is quick and a high number of attendeesmay be monitored anonymously by analysing only a fewsampleswhich allows identifying the local profiles of use of different drugswithin awide panel of psychoactive substances. This approach contributes to the development of an efficient surveillance system which can provide timely insight in the trends of NPS and illicit drugs use. (C) 2020 Elsevier B.V. All rights reserved.

Guaranteeing clean drinking water to the global population is becoming more challenging, because of the cases of water scarcity across the globe, growing population, and increased chemical footprint of this population. Existing targeted strategies for hazard monitoring in drinking water are not adequate to handle such diverse and multidimensional stressors. In the current study, we have developed, validated, and tested a machine learning algorithm based on the data produced via non-targeted liquid chromatography coupled with high resolution mass spectrometry (LC-HRMS) for the identification of potential chemical hazards in drinking water. The machine learning algorithm consisted of a composite statistical model including an unsupervised component (i.e. principal component analysis PCA) and a supervised one (i.e. partial least square discrimination analysis PLS-DA). This model was trained using a training set of 20 drinking water samples previously tested via conventional suspect screening. The developed model was validated using a validation set of 20 drinking water samples of which 4 were spiked with 15 labeled standards at four different concentration levels. The model successfully detected all of the added analytes in the four spiked samples without producing any cases of false detection. The same validation set was processed via conventional trend analysis in order to cross validate the composite model. The results of cross validation showed that even though the conventional trend analysis approach produced a false positive detection rate of ≤5% the composite model outperformed that approach by producing zero cases of false detection. Additionally, the validated model went through an additional test with 42 extra drinking water samples from the same source for an unbiased examination of the model. Finally, the potentials and limitations of this approach were further discussed.

Publisher's version (útgefin grein), Wastewater-based epidemiology is an efficient way to assess illicit drug use, complementing currently used methods retrieved from different data sources. The aim of this study is to compare stimulant drug use in five Nordic capital cities that include for the first time wastewater samples from Torshavn in the Faroe Islands. Currently there are no published reports that compare stimulant drug use in these Nordic capitals. All wastewater samples were analyzed using solid phase extraction and ultra-high performance liquid chromatography coupled to tandem mass spectrometry. The results were compared with data published by the European Monitoring Centre for Drugs and Drug Addiction based on illicit drugs in wastewater from over 50 European cities. Confirming previous reports, the results showed high amphetamine loads compared with other European countries. Very little apparent abuse of stimulant drugs was detected in Torshavn. Methamphetamine loads were the highest from Helsinki of the Nordic countries, indicating substantial fluctuations in the availability of the drug compared with previous studies. Methamphetamine loads from Oslo confirmed that the use continues to be high. Estimated cocaine use was found to be in the lower range compared with other cities in the southern and western part of Europe. Ecstasy and cocaine showed clear variations between weekdays and weekends, indicating recreational use. This study further demonstrates geographical trends in the stimulant drug market in five Nordic capitals, which enables a better comparison with other areas of the continent., We wish to acknowledgesupport by COST (EuropeanCooperation inScience and Technology) [Grant number ES1307], as well as the Icelan-dic Research Fund [Grant number 163049-051] and the University ofIceland Research Fund [Grant number HI17060092].

A key challenge in the environmental and exposure sciences is to establish experimental evidence of the role of chemical exposure in human and environmental systems. High resolution and accurate tandem mass spectrometry (HRMS) is increasingly being used for the analysis of environmental samples. One lauded benefit of HRMS is the possibility to retrospectively process data for (previously omitted) compounds that has led to the archiving of HRMS data. Archived HRMS data affords the possibility of exploiting historical data to rapidly and effectively establish the temporal and spatial occurrence of newly identified contaminants through retrospective suspect screening. We propose to establish a global emerging contaminant early warning network to rapidly assess the spatial and temporal distribution of contaminants of emerging concern in environmental samples through performing retrospective analysis on HRMS data. The effectiveness of such a network is demonstrated through a pilot study, where eight reference laboratories with available archived HRMS data retrospectively screened data acquired from aqueous environmental samples collected in 14 countries on 3 different continents. The widespread spatial occurrence of several surfactants (e.g., polyethylene glycols ( PEGs ) and C12AEO-PEGs ), transformation products of selected drugs (e.g., gabapentin-lactam, metoprolol-acid, carbamazepine-10-hydroxy, omeprazole-4-hydroxy-sulfide, and 2-benzothiazole-sulfonic-acid), and industrial chemicals (3-nitrobenzenesulfonate and bisphenol-S) was revealed. Obtaining identifications of increased reliability through retrospective suspect screening is challenging, and recommendations for dealing with issues such as broad chromatographic peaks, data acquisition, and sensitivity are provided.

Growth inhibition of freshwater microalga Pseudokirchneriella subcapitata caused by a waste water treatment plant (WWTP) effluent extract was investigated using an effect directed analysis (EDA) approach. The objective was to identify compounds responsible for the toxicity by combining state-of-the-art sampling, bioanalytical, fractionation and non-target screening techniques. Three fractionation steps of the whole extract were performed and bioactive fractions were analysed with GC (xGC)-MS and LC-HRMS. In total, 383 compounds were tentatively identified, and their toxicity was characterized using US EPA Ecotox database, open scientific literature or modelled by ECOSAR. Among the top-ranking drivers of toxicity were pesticides and their transformation products, pharmaceuticals (barbiturate derivatives and macrolide antibiotics e.g. azithromycin), industrial compounds or caffeine and its metabolites. Several of the top-ranking pesticides are no longer registered for use in plant protection products or biocides in the Czech Republic (e.g. prometryn, atrazine, acetochlor, resmethrin) and some are approved only for use in biocides (e.g. terbutryn, carbendazim, phenothrin), which indicates that their non-agricultural input into aquatic environment via WWTPs should be carefully considered. The study demonstrated a functional strategy of combining biotesting, fractionation and non-target screening techniques in the EDA study focused on the identification of algal growth inhibitors in WWTP effluent.

The comprehensive extraction recovery assessment of organic analytes from complex samples such as oil field produced water (PW) is a challenging task. A targeted approach is usually used for recovery and determination of compounds in these types of analysis. Here we suggest a more comprehensive and less biased approach for the extraction recovery assessment of complex samples. This method combines conventional targeted analysis with a non-targeted approach to evaluate the extraction recovery of complex mixtures. Three generic extraction methods: liquid-liquid extraction (Lq), and solid phase extraction using HLB cartridges (HLB), and the combination of ENV+ and C8 (ENV) cartridges, were selected for evaluation. PW was divided into three parts: non-spiked, spiked level 1, and spiked level 2 for analysis. The spiked samples were used for targeted evaluation of extraction recoveries of 65 added target analytes comprising alkanes, phenols, and polycyclic aromatic hydrocarbons, producing absolute recoveries. The non-spiked samples were used for the non-targeted approach, which used a combination of the F-ratio method and apex detection algorithm. Targeted analysis showed that the use of ENV cartridges and the Lq method performed better than use of HLB cartridges, producing absolute recoveries of 53.1 ± 15.2 for ENV and 46.8 ± 13.2 for Lq versus 19.7 ± 6.7 for HLB. These two methods appeared to produce statistically similar results for recoveries of analytes, whereas they were both different from the produced recoveries via the HLB method. The non-targeted approach captured unique features that were specific to each extraction method. This approach generated 26 unique features (mass spectral ions), which were significantly different between samples and were relevant in differentiating each extract from each method. Using a combination of these targeted and non-targeted methods we evaluated the extraction recoveries of the three extraction methods for analysis of PW.

Nontarget analysis is considered one of the most comprehensive tools for the identification of unknown compounds in a complex sample analyzed via liquid chromatography coupled to high-resolution mass spectrometry (LC–HRMS). Due to the complexity of the data generated via LC–HRMS, the data-dependent acquisition mode, which produces the MS2 spectra of a limited number of the precursor ions, has been one of the most common approaches used during nontarget screening. However, data-independent acquisition mode produces highly complex spectra that require proper deconvolution and library search algorithms. We have developed a deconvolution algorithm and a universal library search algorithm (ULSA) for the analysis of complex spectra generated via data-independent acquisition. These algorithms were validated and tested using both semisynthetic and real environmental data. A total of 6000 randomly selected spectra from MassBank were introduced across the total ion chromatograms of 15 sludge extracts at three levels of background complexity for the validation of the algorithms via semisynthetic data. The deconvolution algorithm successfully extracted more than 60% of the added ions in the analytical signal for 95% of processed spectra (i.e., 3 complexity levels multiplied by 6000 spectra). The ULSA ranked the correct spectra among the top three for more than 95% of cases. We further tested the algorithms with 5 wastewater effluent extracts for 59 artificial unknown analytes (i.e., their presence or absence was confirmed via target analysis). These algorithms did not produce any cases of false identifications while correctly identifying ∼70% of the total inquiries. The implications, capabilities, and the limitations of both algorithms are further discussed.

Thirty-seven laboratories from 25 countries present the development of an inter-laboratory testing scheme for the analysis of seven illicit drug residues in standard solutions, tap- and wastewater. Almost 10 000 concentration values were evaluated: triplicates of up to five samples and 26 laboratories per year. The setup was substantially improved with experiences gained across the six repetitions (e.g. matrix type, sample conditions, spiking levels). From this, (pre-)analytical issues (e.g. pH adjustment, filtration) were revealed for specific analytes which resulted in formulation of best-practice protocols for inter-laboratory setup and analytical procedures. The results illustrate the effectiveness of the inter-laboratory setup to assess laboratory performance in the framework of wastewater-based epidemiology. The exercise proved that measurements of laboratories were of high quality (>80% satisfactory results for six out of seven analytes) and that analytical follow-up is important to assist laboratories in improving robustness of wastewater-based epidemiology results., This article is based upon work from COST Action ES1307 supported by COST (European Cooperation in Science and Technology). We wish to acknowledge EMCDDA and Yeonsuk Ryu for support in the organization of the scheme and assistance in the preparation of the test samples, respectively. The following funding sources are acknowledged: the Research Foundation – Flanders (FWO) (Grant number: 1285216N), the Spanish Ministry of Economy, Industry and Competitiveness, the Generalitat Valenciana, Xunta de Galicia, Stavros Niarchos Foundation, Office for Combating Narcotic Drug Abuse of the Government of the Republic of Croatia, EU FP7 project SOLUTIONS (603437), the Government of Catalonia, the Natural Sciences and Engineering Research Council of Canada (NSERC), Ministry of Education, Youth and Sports of the Czech Republic (projects CENAKVA and CENAKVA II), EU Marie Skłodowska-Curie Fellowship (APOLLO 749845) and the Swiss National Science Foundation (SNSF, P2LAP2_164892). The following persons are acknowledged for help in sample analysis: Marijan Ahel, Evroula Hapeshi, Popi Karaolia, Esther López-García, Nicola Mastroianni, Cristina Postigo, Inés Racamonde, Rosario Rodil, Isaac Rodríguez, Tania Rodríguez-Álvarez, Ivan Senta, and Senka Terzic.

A reliable oxidative stress biomarker, 8-iso-prostaglandin F2α (8-iso-PGF2α), was for the first time quantitatively analysed in wastewater using an analytical method consisting of liquid chromatography-high resolution mass spectrometry coupled to immunoaffinity clean-up (IAC-LC-HRMS). Factors influencing the method's robustness were investigated, including analyte stability in sewage and enzymatic deconjugation with β-glucuronidase. The IAC-LC-HRMS method was linear over the range of 0.1-100ng/mL with correlation coefficient (R(2)) of 0.999. The quantification limits were sufficiently low to detect 8-iso-PGF2α in sewage (method quantification limit of 0.3ng/L) and precision, expressed as relative standard deviation was less than 7% and the accuracy expressed as relative recovery was in the 103-113% range. As a result, the application of the method to 24-h composite wastewater samples from Oslo showed 8-iso-PGF2α concentrations of 18.9-23.3ng/L for 8 days in March 2015. This study demonstrates a standard method to analyse 8-iso-PGF2α in sewage that will contribute to the further investigation of the potential use of 8-iso-PGF2α as a sewage biomarker for assessing the status of community health.

Embargo until 20 May 2019. A passive sampling device, the Polar Organic Chemical Integrative Sampler (POCIS), was calibrated in-situ over a 4-week period in Oslo (Norway) for 10 illicit drugs and pharmaceuticals with the goal of developing an approach for monitoring long-term wastewater drug loads. The calibrations were performed in triplicate using three different overlapping calibration sets under changing environmental conditions that allowed the uncertainty of the sampling rates to be evaluated. All 10 compounds exhibited linear uptake kinetics and provided sampling rates of between 0.023 and 0.192 L d−1. POCIS were deployed for consecutive 2-week periods during 2012 and 2013 and the calculated time-weighted average (TWA) concentrations used to define different drug use trends. The relative uncertainty related to the POCIS data was approximately 40% and, except for citalopram, 85% of all the long-term measurements of pharmaceuticals were within the confidence interval levels calculated to evaluate the effects of changing environmental conditions on the TWA estimations. POCIS was demonstrated to be sufficiently robust to provide reliable annual drug use estimates with a smaller number of samplers (n = 24) than recommended for active sampling (n = 56) within an acceptable level of sample size related uncertainty < 10%. POCIS is demonstrated to be a valuable and reliable tool for the long-term monitoring of certain drugs and pharmaceuticals within a defined population.

For the first time, ultra-high performance supercritical fluid chromatography (UHPSFC) coupled to tandem mass spectrometry has been used to determine cannabinoid and synthetic cannabinoid residues in wastewater. Combined with a downscaled version of the classic liquid-liquid extraction, the proposed method allows for the quantification of Δ9-tetrahydrocannabinol, three of its major metabolites (the monohydroxylated, the dehydroxylated, and the carboxylated species) and four synthetic cannabinoid metabolites (from the JWH-series) at low ng L

Liquid chromatography coupled to high resolution mass spectrometry (LC-HR-MS) has been one of the main analytical tools for the analysis of small polar organic pollutants in the environment. LC-HR-MS typically produces a large amount of data for a single chromatogram. The analyst is therefore required to perform prioritization prior to nontarget structural elucidation. In the present study, we have combined the F-ratio statistical variable selection and the apex detection algorithms in order to perform prioritization in data sets produced via LC-HR-MS. The approach was validated through the use of semisynthetic data, which was a combination of real environmental data and the artificially added signal of 31 alkanes in that sample. We evaluated the performance of this method as a function of four false detection probabilities, namely: 0.01, 0.02, 0.05, and 0.1%. We generated 100 different semisynthetic data sets for each F-ratio and evaluated that data set using this method. This design of experiment created a population of 30 000 true positives and 32 000 true negatives for each F-ratio, which was considered sufficiently large enough in order to fully validate this method for analysis of LC-HR-MS data. The effect of both the F-ratio and signal-to-noise ratio (S/N) on the performance of the suggested approach were evaluated through normalized statistical tests. We also compared this method to the pixel-by-pixel as well as peak list approaches. More than 92% of features present in the final feature list via the F-ratio method were also present in the conventional peak list generated by MZmine. However, this method was the only approach successful in the classification of samples, and thus prioritization, when compared to the other evaluated approaches. The application potential and limitations of the suggested method are discussed.

The quantitative analysis of human urinary metabolites as biomarkers in wastewater streams has been used to estimate the rates of illicit drug use in the wider community. The primary underlying assumption in such studies is that a sample of wastewater is equivalent to a cumulative sample of urine. Drug metabolism in humans is predominantly enzymatically mediated, but these processes are not exclusive to the human body, and are found to occur in the environment and the sewer network. Understanding what happens to drugs and their urinary metabolites in the sewer system between the point of excretion and sampling is particularly important since it is possible that in-sewer transformation may influence final biomarker concentration. The present study uses batch experiments to measure and assess the biotransformation processes of cocaine and its two major human metabolites, benzoylecgonine and ecgonine methyl ester. The activated sludge modelling framework for xenobiotic organic micro-pollutants (ASM-X) is used for model structure identification and calibration. Biotransformation was observed to follow pseudo first-order kinetics. The biodegradation kinetics of cocaine, benzoylecgonine and ecgonine methyl ester is not significantly affected by the availability of dissolved oxygen. Results obtained in this study show that omitting in-pipe biotransformation affects the accuracy of back-calculated cocaine use estimates. This varies markedly depending on the in-sewer hydraulic retention time, total biomass concentration and the relative concentration of each metabolite. However, back-calculated cocaine use estimates derived from wastewater concentrations of benzoylecgonine and ecgonine methyl ester do show very close agreement if ex-vivo biotransformation of these compounds is considered.

Second generation anticoagulant rodenticides (SGARs) are commonly used for rodent pest control in Norway resulting in the potential exposure of non-target raptor species. In this study the occurrence of flocoumafen, difethialone, difenacoum, bromadiolone and brodifacoum was determined in the livers of five species of raptors found dead in Norway between 2009 and 2011. The SGARs brodifacoum, bromadiolone, difenacoum and flocoumafen were detected in golden eagle ( Aquila chrysaetos ) and eagle owl ( Bubo bubo ) livers at a total SGAR concentration of between 11 and 255 ng/g in approximately 70% of the golden eagles and 50% of the eagle owls examined in this study. In the absence of specific golden eagle and eagle owl toxicity thresholds for SGARs, a level of > 100 ng/g was used as a potential lethal range, accepting that poisoning may occur below this level. Thirty percent (7/24) of the golden eagle and eagle owl livers contained total SGAR residue levels above this threshold. Further estimation of the potential mortality impact on the sampled raptor populations was not possible.

The analysis of sewage for the residues of commonly used illicit drugs has successfully been applied as a suitable approach for estimating community illicit drug use. The drug market is increasingly dynamic with new substances continually being marketed for recreational purposes. In this study, ultra-high pressure liquid chromatography coupled to tandem mass spectrometry (UHPLC-MS/MS) was used to simultaneously and quantitatively detect the exogenous biomarkers of new classes of recreational drugs in sewage collected from three different Norwegian cities (Oslo, Bergen, Hamar). The samples were screened for the presence of khat (d-norpseudoephedrine and cathinone), mephedrone, pseudoephedrine, 7-aminoflunitrazepam, para-methoxyamphetamine (PMA), para-methoxy-N-methylamphetamine (PMMA) and a selection of urinary metabolites of synthetic cannabinoids collectively termed ´Spice´ (5-3-1-naphthoyl-1H-indol-1-yl-pentanoic acid (JWH 018 N-pentanoic acid), 1-5-hydroxypentyl-1H-indol-3-ylnaphthalen-1-yl-methanone (JWH 018 N-5-hydroxypentyl), 4-3-1-naphthoyl-1H-indol-1-yl-butanoic acid (JWH 073 N-butanoic acid), 1-4-hydroxybutyl-1H-indol-3-ylnaphthalen-1-yl-methanone (JWH 073 N-4-hydroxybutyl), 1-5-hydroxypentyl-1H-indol-3-yl4-methylnaphthalen-1-yl-methanone (JWH 122 N-5-hydroxypentyl), 1-5-fluoro-4-hydroxypentyl-1H-indol-3-ylnaphthalen-1-ylmethanone (AM2201 N-4-hydroxypentyl), and 1-5-hydroxypentyl-1H-indol-3-yl4-methoxyphenyl-methanone (RCS-4 N-5-hydroxypentyl)). Limits of detection were 1 ng/L for amphetamine like compounds and 5 ng/L for the metabolites of synthetic cannabinoids while the limits of quantification were 3 and 15 ng/L, respectively. Three of the fourteen selected biomarkers (cathine, pseudoephedrine and the synthetic cannabinoid metabolite JWH-018 N-5-hydroxypentyl) were detected in sewage, alongside the illicit drugs (and/or metabolites) typically found in sewage (cocaine, benzoylecognine, methamphetamine, MDMA, and THC-COOH). The khat biomarker d-norpseudoephedrine was detected in Oslo sewage at a mean concentration of 93 ng/L that represents a daily load of 54 mg/day/1000 inhabitants. Pseudoephedrine was present at mean concentrations of between 27 and 67 ng/L representing normalized daily loads of between 10 (Hamar) and 24 mg/day/1000 inhabitants (Bergen). The daily normalized loads of JWH-018 N-5-hydroxypentyl were between 49 (Oslo) and 62 mg/day/1000 inhabitants (Hamar). This study demonstrates for the first time that sewage biomarker analysis can be applied to evaluate not only the use the traditional illicit drugs (cocaine, cannabis and amphetamines), but also the use of certain new synthetic drugs.

Embargo until 20 April 2019. 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 AnalyzerTM, 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 di erent 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.

Modeling and prediction of polar organic chemical integrative sampler (POCIS) sampling rates (Rs) for 73 compounds using artificial neural networks (ANNs) is presented for the first time. Two models were constructed: the first was developed ab initio using a genetic algorithm (GSD-model) to shortlist 24 descriptors covering constitutional, topological, geometrical and physicochemical properties and the second model was adapted for Rs prediction from a previous chromatographic retention model (RTD-model). Mechanistic evaluation of descriptors showed that models did not require comprehensive a priori information to predict Rs. Average predicted errors for the verification and blind test sets were 0.03 ± 0.02 L d(-1) (RTD-model) and 0.03 ± 0.03 L d(-1) (GSD-model) relative to experimentally determined Rs. Prediction variability in replicated models was the same or less than for measured Rs. Networks were externally validated using a measured Rs data set of six benzodiazepines. The RTD-model performed best in comparison to the GSD-model for these compounds (average absolute errors of 0.0145 ± 0.008 L d(-1) and 0.0437 ± 0.02 L d(-1), respectively). Improvements to generalizability of modeling approaches will be reliant on the need for standardized guidelines for Rs measurement. The use of in silico tools for Rs determination represents a more economical approach than laboratory calibrations.

Gas chromatography coupled with high resolution time of flight mass spectrometry (GC–HR-TOFMS) has gained popularity for the target and suspect analysis of complex samples. However, confident detection of target/suspect analytes in complex samples, such as produced water, remains a challenging task. Here we report on the development and validation of a two stage algorithm for the confident target and suspect analysis of produced water extracts. We performed both target and suspect analysis for 48 standards, which were a mixture of 28 aliphatic hydrocarbons and 20 alkylated phenols, in 3 produced water extracts. The two stage algorithm produces a chemical standard database of spectra, in the first stage, which is used for target and suspect analysis during the second stage. The first stage is carried out through five steps via an algorithm here referred to as unique ion extractor (UIE). During the first step the m/z values in the spectrum of a standard that do not belong to that standard are removed in order to produce a clean spectrum and then during the last step the cleaned spectrum is calibrated. The Dot-product algorithm, during the second stage, uses the cleaned and calibrated spectra of the standards for both target and suspect analysis. We performed the target analysis of 48 standards in all 3 samples via conventional methods, in order to validate the two stage algorithm. The two stage algorithm was demonstrated to be more robust, reliable, and less sensitive to the signal-to-noise ratio (S/N), when compared to the conventional method. The Dot-product algorithm showed lower potential in producing false positives compared to the conventional methods, when dealing with complex samples. We also evaluated the effect of the mass accuracy on the performances of Dot-product algorithm. Our results indicated the crucial importance of HR-MS data and the mass accuracy for confident suspect analysis in complex samples.

Quantitative measurement of drug consumption biomarkers in wastewater can provide objective information on community drug use patterns and trends. This study presents the measurement of alcohol consumption in 20 cities across 11 countries through the use of wastewater-based epidemiology (WBE), and reports the application of these data for the risk assessment of alcohol on a population scale using the margin of exposure (MOE) approach. Raw 24-h composite wastewater samples were collected over a one-week period from 20 cities following a common protocol. For each sample a specific and stable alcohol consumption biomarker, ethyl sulfate (EtS) was determined by liquid chromatography coupled to tandem mass spectrometry. The EtS concentrations were used for estimation of per capita alcohol consumption in each city, which was further compared with international reports and applied for risk assessment by MOE. The average per capita consumption in 20 cities ranged between 6.4 and 44.3L/day/1000 inhabitants. An increase in alcohol consumption during the weekend occurred in all cities, however the level of this increase was found to differ. In contrast to conventional data (sales statistics and interviews), WBE revealed geographical differences in the level and pattern of actual alcohol consumption at an inter-city level. All the sampled cities were in the "high risk" category (MOE10) and the average MOE for the whole population studied was 2.5. These results allowed direct comparisons of alcohol consumption levels, patterns and risks among the cities. This study shows that WBE can provide timely and complementary information on alcohol use and alcohol associated risks in terms of exposure at the community level.

Wastewater analysis has been demonstrated to be a complementary approach for assessing the overall patterns of drug use by a population while the full potential of wastewater-based epidemiology has yet to be explored. F2-isoprostanes are a prototype wastewater biomarker to study the cumulative oxidative stress at a community level. In this work, 8-iso-prostaglandin F2α (8-iso-PGF2α) was analysed in raw 24 h-composite wastewater samples collected from 4 Norwegian and 7 other European cities in 2014 and 2015. Using the same samples, biomarkers of alcohol (ethyl sulfate) and tobacco (trans-3′-hydroxycotinine) use were also analysed to investigate any possible correlation between 8-iso-PGF2α and the consumption of the two drugs. The estimated per capita daily loads of 8-iso-PGF2α in the 11 cities ranged between 2.5 and 9.9 mg/day/1000 inhabitants with a population-weighted mean of 4.8 mg/day/1000 inhabitants. There were no temporal trends observed in the levels of 8-iso-PGF2α, however, spatial differences were found at the inter-city level correlating to the degree of urbanisation. The 8-iso-PGF2α mass load was found to be strongly associated with that of trans-3′-hydroxycotinine while it showed no correlation with ethyl sulfate. The present study shows the potential for 8-iso-PGF2α as a wastewater biomarker for the assessment of community public health. This work is part of the EU Marie Curie Initial Training Network SEWPROF (Marie Curie-FP7-PEOPLE, grant No. 317205) and the financial support of the EU is greatly acknowledged. E.G.L. is also grateful to Generalitat Valenciana (APOSTD/2015, Programa VALi + d). The authors thank all personnel of the wastewater treatment plants for their collaboration in the collection of the wastewater samples.

Background: Monitoring the scale of pharmaceuticals, illicit and licit drugs consumption is important to assess the needs of law enforcement and public health, and provides more information about the different trends within different countries. Community drug use patterns are usually described by national surveys, sales and seizure data. Wastewater-based epidemiology (WBE) has been shown to be a reliable approach complementing such surveys. Method: This study aims to compare and correlate the consumption estimates of pharmaceuticals, illicit drugs, alcohol, nicotine and caffeine from wastewater analysis and other sources of information. Wastewater samples were collected in 2015 from 8 different European cities over a one week period, representing a population of approximately 5 million people. Published pharmaceutical sale, illicit drug seizure and alcohol, tobacco and caffeine use data were used for the comparison. Results: High agreement was found between wastewater and other data sources for pharmaceuticals and cocaine, whereas amphetamines, alcohol and caffeine showed a moderate correlation. methamphetamine and 3,4- methylenedioxymethamphetamine (MDMA) and nicotine did not correlate with other sources of data. Most of the poor correlations were explained as part of the uncertainties related with the use estimates and were improved with other complementary sources of data. Conclusions: This work confirms the promising future of WBE as a complementary approach to obtain a more accurate picture of substance use situation within different communities. Our findings suggest further improvements to reduce the uncertainties associated with both sources of information in order to make the data more comparable. Jose Antonio Baz Lomba, Stefania Salvatore, Richard Bade, Erika Castrignanò, Ana Causanilles, Juliet Kinyua, Ann-Kathrin McCall, Pedram Ramin, Nikolaos I. Rousis, and Yeonsuk Ryu acknowledge the EU Marie-Skłodowska Curie Initial Training Network SEWPROF (Marie Curie-FP7-PEOPLE, grant number 317205) for their Early Stage Researcher grant and Emma Gracia-Lor for her Experienced Researcher grant. We thank the people and agencies who assisted in the collection of the wastewater samples, in particular Pia Ryrfors and colleagues at Vestfjorden Avløpselskap (VEAS, Oslo, Norway).

The quantification of illicit drug and pharmaceutical residues in sewage has been shown to be a valuable tool that complements existing approaches in monitoring the patterns and trends of drug use. The present work delineates the development of a novel analytical tool and dynamic workflow for the analysis of a wide range of substances in sewage-based samples. The validated method can simultaneously quantify 51 target psychoactive substances and pharmaceuticals in sewage-based samples using an off-line automated solid phase extraction (SPE-DEX) method, using Oasis HLB disks, followed by ultra-high performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC-QTOF) in MS(e). Quantification and matrix effect corrections were overcome with the use of 25 isotopic labeled internal standards (ILIS). Recoveries were generally greater than 60% and the limits of quantification were in the low nanogram-per-liter range (0.4-187 ng L(-1)). The emergence of new psychoactive substances (NPS) on the drug scene poses a specific analytical challenge since their market is highly dynamic with new compounds continuously entering the market. Suspect screening using high-resolution mass spectrometry (HRMS) simultaneously allowed the unequivocal identification of NPS based on a mass accuracy criteria of 5 ppm (of the molecular ion and at least two fragments) and retention time (2.5% tolerance) using the UNIFI screening platform. Applying MS(e) data against a suspect screening database of over 1000 drugs and metabolites, this method becomes a broad and reliable tool to detect and confirm NPS occurrence. This was demonstrated through the HRMS analysis of three different sewage-based sample types; influent wastewater, passive sampler extracts and pooled urine samples resulting in the concurrent quantification of known psychoactive substances and the identification of NPS and pharmaceuticals.

Polar organic chemical integrative samplers (POCIS) were calibrated in situ for selected illicit drugs and their metabolites at a sewage treatment works. Eleven out of 13 target compounds were detected and eight of those exhibited linear uptake kinetics with sampling rates between 0.035 and 0.150 L d(-1). Subsequently POCIS were deployed for 2 week periods over the course of a whole year, in order to examine trends in drug usage. Amphetamine and methamphetamine showed several similar peaks in concentration during the course of the year as did cocaine and two of its metabolites. Low levels of ecstasy were observed, with a prominent peak in May and a steady increase toward the end of the year. The antihistamine Cetirizine showed a clear increase in use during the summer months as expected and back calculation of the yearly dosage from POCIS accumulations yielded very similar results to that registered in the Norwegian prescription database. Estimations of cocaine usage using the parent compound averaged between 0.31 and 2.8 g d(-1) per 1000 inhabitants. POCIS is a cost-effective technique for the long-term monitoring of drug usage of a defined population and may overcome the difficulties of representative sampling associated with autosampling equipment.

Marine debris is a global environmental issue. Smoked cigarette filters are the predominant coastal litter item; 4.5 trillion are littered annually, presenting a source of bioplastic microfibres (cellulose acetate) and harmful toxicants to marine environments. Despite the human health risks associated with smoking, little is known of the hazards cigarette filters present to marine life. Here we studied the impacts of smoked cigarette filter toxicants and microfibres on the polychaete worm Hediste diversicolor (ragworm), a widespread inhabitant of coastal sediments. Ragworms exposed to smoked cigarette filter toxicants in seawater at concentrations 60 fold lower than those reported for urban run-off exhibited significantly longer burrowing times, >30% weight loss and >2-fold increase in DNA damage compared to ragworms maintained in control conditions. In contrast, ragworms exposed to smoked cigarette filter microfibres in marine sediment showed no significant effects. Bioconcentration factors for nicotine were 500 fold higher from seawater than from sediment. Our results illustrate the vulnerability of organisms in the water column to smoking debris and associated toxicants and highlight the risks posed by smoked cigarette filter debris to aquatic life.

In this article, a dataset from a collaborative non-target screening trial organised by the NORMAN Association is used to review the state-of-the-art and discuss future perspectives of non-target screening using high-resolution mass spectrometry in water analysis. A total of 18 institutes from 12 European countries analysed an extract of the same water sample collected from the River Danube with either one or both of liquid and gas chromatography coupled with mass spectrometry detection. This article focuses mainly on the use of high resolution screening techniques with target, suspect, and non-target workflows to identify substances in environmental samples. Specific examples are given to emphasise major challenges including isobaric and co-eluting substances, dependence on target and suspect lists, formula assignment, the use of retention information, and the confidence of identification. Approaches and methods applicable to unit resolution data are also discussed. Although most substances were identified using high resolution data with target and suspect-screening approaches, some participants proposed tentative non-target identifications. This comprehensive dataset revealed that non-target analytical techniques are already substantially harmonised between the participants, but the data processing remains time-consuming. Although the objective of a “fully-automated identification workflow” remains elusive in the short term, important steps in this direction have been taken, exemplified by the growing popularity of suspect screening approaches. Major recommendations to improve non-target screening include better integration and connection of desired features into software packages, the exchange of target and suspect lists, and the contribution of more spectra from standard substances into (openly accessible) databases., Analytical and Bioanalytical Chemistry, 407 (21), ISSN:1618-2650, ISSN:1618-2642

Eight organic UV filters and stabilizers were quantitatively determined in wastewater sludge and effluent, landfill leachate, sediments, and marine and freshwater biota. Crab, prawn and cod from Oslofjord, and perch, whitefish and burbot from Lake Mjøsa were selected in order to evaluate the potential for trophic accumulation. All of the cod livers analysed were contaminated with at least 1 UV filter, and a maximum concentration of almost 12 μg/g wet weight for octocrylene (OC) was measured in one individual. 80% of the cod livers contained OC, and approximately 50% of cod liver and prawn samples contained benzophenone (BP3). Lower concentrations and detection frequencies were observed in freshwater species and the data of most interest is the 4 individual whitefish that contained both BP3 and ethylhexylmethoxycinnamate (EHMC) with maximum concentrations of almost 200 ng/g wet weight. The data shows a difference in the loads of UV filters entering receiving water dependent on the extent of wastewater treatment. Primary screening alone is insufficient for the removal of selected UV filters (BP3, Padimate, EHMC, OC, UV-234, UV-327, UV-328, UV-329). Likely due in part to the hydrophobic nature of the majority of the UV filters studied, particulate loading and organic carbon content appear to be related to concentrations of UV filters in landfill leachate and an order of magnitude difference in these parameters correlates with an order of magnitude difference in the effluent concentrations of selected UV filters (Fig. 2). From the data, it is possible that under certain low flow conditions selected organic UV filters may pose a risk to surface waters but under the present conditions the risk is low, but some UV filters will potentially accumulate through the trophic food chain. Keywords: UV filters, UV stabilizers, Sunscreen, Bioaccumulation, Wastewater, Landfill leachate

Background There is a concern about methamphetamine use in Europe. Methamphetamine fatalities have recently occurred in Southern European countries. The aim of this study is to examine Norwegian methamphetamine trends in recent years, comparing different data sources. Material and methods Data about amphetamines were collected from five different sources; blood samples from drivers suspected of driving under the influence of drugs and apprehended by the police (during the years 2000–2012), urine samples from inmates in Norwegian prisons (during 2000–2012), post-mortem blood samples from medico-legal autopsies (2000–2012), drug seizures (1994–2012) and wastewater samples from a metropolitan/suburban population (2010–2012). Results The number of cases where methamphetamine was detected has increased during the period studied for the driving under the influence cases, the samples from inmates and from forensic autopsies. The increase seems to be linear up to 2009–2010, with a subsequent stabilisation or even a decline in the market share of methamphetamine for the next few years. The number of methamphetamine seizures has risen from less than 1% in 2000 to approximately 66% in 2009, and a steady share around 60% have been seen between 2010 and 2012. Wastewater samples showed that the share of methamphetamine peaked in 2010–11, before falling. Interpretation It is difficult to obtain reliable data on illicit drugs. Data from different populations might give indications of changes and trends, but are always prone to different biases. By comparing results from different data sources, a better knowledge of the illicit drug market might be obtained. All our data sources confirmed that methamphetamine became a more prevalent drug during the first decade of the new millennium in Norway, but since approximately 2009 the share of methamphetamine stabilised.

Data obtained from the analysis of wastewater from large-scale sewage treatment plants has been successfully applied to study trends in the use of classical illicit drugs such as cocaine, but the dynamic nature of the new psychoactive substances (NPS) market presents a unique set of challenges to epidemiologists. In an attempt to overcome some of the challenges, this paper presents a framework whereby a collection of tools and alternative data-sources can be used to support the design and implementation of wastewater-based studies on NPS use. Within this framework the most likely and most suitable biomarkers for a given NPS are predicted via in-silico metabolism, biotransformation and sorption models. Subsequent detection and confirmation of the biomarkers in samples of wastewater are addressed via high-resolution mass spectrometry (HRMS). The proposed framework is applied to a set of test substances including synthetic cannabinoids and cathinones. In general, the in-silico models predict that transformation via N-dealkylation and hydroxylation is likely for these compounds, and that adsorption is expected to be significant for cannabinoids in wastewater. Screening via HRMS is discussed with examples from the literature, and common-fragment searching and mass-defect filtering are successfully performed on test samples such that spectral noise is removed to leave only the information that is most likely to be related to the NPS biomarkers. HRMS screening is also applied to a set of pissoir-sourced wastewater samples and a total of 48 pharmaceuticals and drugs including 1-(2-methoxyphenyl)piperazine (oMeOPP) are identified. The framework outlined in this paper can provide an excellent means of maximizing the chances of success when identifying and detecting biomarkers of NPS in wastewater.