Assessing sample extraction efficiencies for the analysis of complex unresolved mixtures of organic pollutants: a comprehensive non-target approach

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

Enantiomeric profiling of chiral illicit drugs in a pan-European study

The aim of this paper is to present the first study on spatial and temporal variation in the enantiomeric profile of chiral drugs in eight European cities. Wastewater-based epidemiology (WBE) and enantioselective analysis were combined to evaluate trends in illicit drug use in the context of their consumption vs direct disposal as well as their synthetic production routes. Spatial variations in amphetamine loads were observed with higher use in Northern European cities. Enantioselective analysis showed a general enrichment of amphetamine with the R-(−)-enantiomer in wastewater indicating its abuse. High loads of racemic methamphetamine were detected in Oslo (EF = 0.49 ± 0.02). This is in contrast to other European cities where S-(+)-methamphetamine was the predominant enantiomer. This indicates different methods of methamphetamine synthesis and/or trafficking routes in Oslo, compared with the other cities tested. An enrichment of MDMA with the R-(−)-enantiomer was observed in European wastewaters indicating MDMA consumption rather than disposal of unused drug. MDA's chiral signature indicated its enrichment with the S-(+)-enantiomer, which confirms its origin from MDMA metabolism in humans. HMMA was also detected at quantifiable concentrations in wastewater and was found to be a suitable biomarker for MDMA consumption. Mephedrone was only detected in wastewater from the United Kingdom with population-normalised loads up to 47.7 mg 1000 people−1 day−1. The enrichment of mephedrone in the R-(+)-enantiomer in wastewater suggests stereoselective metabolism in humans, hence consumption, rather than direct disposal of the drug. The investigation of drug precursors, such as ephedrine, showed that their presence was reasonably ascribed to their medical use

Estimation of caffeine intake from analysis of caffeine metabolites in wastewater

Caffeine metabolites in wastewater were investigated as potential biomarkers for assessing caffeine intake in a population. The main human urinary metabolites of caffeine were measured in the urban wastewater of ten European cities and the metabolic profiles in wastewater were compared with the human urinary excretion profile. A good match was found for 1,7-dimethyluric acid, an exclusive caffeine metabolite, suggesting that might be a suitable biomarker in wastewater for assessing population-level caffeine consumption. A correction factor was developed considering the percentage of excretion of this metabolite in humans, according to published pharmacokinetic studies. Daily caffeine intake estimated from wastewater analysis was compared with the average daily intake calculated from the average amount of coffee consumed by country per capita. Good agreement was found in some cities but further information is needed to standardize this approach. Wastewater analysis proved useful to providing additional local information on caffeine use

Enantiomeric profiling of chiral illicit drugs in a pan-European study

The aim of this paper is to present the first study on spatial and temporal variation in the enantiomeric profile of chiral drugs in eight European cities. Wastewater-based epidemiology (WBE) and enantioselective analysis were combined to evaluate trends in illicit drug use in the context of their consumption vs direct disposal as well as their synthetic production routes. Spatial variations in amphetamine loads were observed with higher use in Northern European cities. Enantioselective analysis showed a general enrichment of amphetamine with the R-(−)-enantiomer in wastewater indicating its abuse. High loads of racemic methamphetamine were detected in Oslo (EF = 0.49 ± 0.02). This is in contrast to other European cities where S-(+)-methamphetamine was the predominant enantiomer. This indicates different methods of methamphetamine synthesis and/or trafficking routes in Oslo, compared with the other cities tested. An enrichment of MDMA with the R-(−)-enantiomer was observed in European wastewaters indicating MDMA consumption rather than disposal of unused drug. MDA's chiral signature indicated its enrichment with the S-(+)-enantiomer, which confirms its origin from MDMA metabolism in humans. HMMA was also detected at quantifiable concentrations in wastewater and was found to be a suitable biomarker for MDMA consumption. Mephedrone was only detected in wastewater from the United Kingdom with population-normalised loads up to 47.7 mg 1000 people day. The enrichment of mephedrone in the R-(+)-enantiomer in wastewater suggests stereoselective metabolism in humans, hence consumption, rather than direct disposal of the drug. The investigation of drug precursors, such as ephedrine, showed that their presence was reasonably ascribed to their medical use

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

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

The First Attempt at Non-Linear in Silico Prediction of Sampling Rates for Polar Organic Chemical Integrative Samplers (POCIS)

Modeling and prediction of polar organic chemical integrative sampler (POCIS) sampling rates (R) 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 R 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 R. Average predicted errors for the verification and blind test sets were 0.03 ± 0.02 L d (RTD-model) and 0.03 ± 0.03 L d (GSD-model) relative to experimentally determined R. Prediction variability in replicated models was the same or less than for measured R. Networks were externally validated using a measured R 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 and 0.0437 ± 0.02 L d, respectively). Improvements to generalizability of modeling approaches will be reliant on the need for standardized guidelines for R measurement. The use of in silico tools for R determination represents a more economical approach than laboratory calibrations

Assessing sample extraction efficiencies for the analysis of complex unresolved mixtures of organic pollutants: A comprehensive non-target approach

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

International snapshot of new psychoactive substance use: Case study of eight countries over the 2019/2020 new year period

There is considerable concern around the use of new psychoactive substances (NPS), but still little is known about how much they are really consumed. Analysis by forensics laboratories of seized drugs and post-mortem samples as well as hospital emergency rooms are the first line of identifying both ‘new’ NPS and those that are most dangerous to the community. However, NPS are not necessarily all seized by law enforcement agencies and only substances that contribute to fatalities or serious afflictions are recorded in post-mortem and emergency room samples. To gain a better insight into which NPS are most prevalent within a community, complementary data sources are required. In this work, influent wastewater was analysed from 14 sites in eight countries for a variety of NPS. All samples were collected over the 2019/2020 New Year period, a time which is characterized by celebrations and parties and therefore a time when more NPS may be consumed. Samples were extracted in the country of origin following a validated protocol and shipped to Australia for final analysis using two different mass spectrometric strategies. In total, more than 200 were monitored of which 16 substances were found, with geographical differences seen. This case study is the most comprehensive wastewater analysis study ever carried out for the identification of NPS and provides a starting point for future, ongoing monitoring of these substances