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

Characterization of The Permeation Properties of Membrane Filters and Sorption Properties of Sorbents Used for Polar Organic Chemical Integrative Samplers

Polar organic chemical integrative samplers (POCIS) are promising devices for measuring the time-weighted average concentrations of hydrophilic compounds in aquatic environments. However, the mechanisms underlying compound uptake by POCIS remain unclear. We investigated the permeation kinetics of polyethersulfone and polytetrafluoroethylene membrane filters, and the sorption kinetics of Oasis HLB (Waters), Envi-Carb (Supelco), and Oasis WAX (Waters) sorbents. The log octanol-water partition coefficient (KOW) values of the 19 targeted compounds ranged from -0.55 to 6.0. The overall mass-transfer coefficients were negatively correlated with KOW, indicating that interactions between hydrophobic compounds and the membrane inhibit permeation. The sorption rate coefficient showed no correlation with KOW and depended on the type of sorbent used. These results imply that the uptake of highly hydrophilic compounds by POCIS is determined by both the membrane and the sorbent kinetics; however, membrane kinetics dominate the uptake of hydrophobic compounds. Environ Toxicol Chem 2024;43:2115-2121. © 2024 SETAC.

Chemometric modeling of pharmaceuticals for partitioning between sludge and aqueous phase during the wastewater treatment process

Computational techniques, such as quantitative structure-property relationships (QSPRs), can play a significant role in exploring the important chemical features essential for the degree of sorption or sludge/water partition coefficient (Kd) towards sewage sludge of wastewater treatment process to evaluate the environmental consequence and risk of pharmaceuticals. The current research work aims to construct a predictive QSPR model for the sorption of 148 diverse active pharmaceutical ingredients (APIs) in sewage sludge during wastewater treatment. For the development of the model, we employed easily computable 2D descriptors as independent variables. The model has been developed following the Organization for Economic Cooperation and Development's (OECD) guidelines. It has undergone internal and external validation using a variety of methodologies, as well as been tested for its applicability domain. A measure of hydrophobicity, i.e., MLOGP2, showed the most promising contribution in modeling the sorption coefficient of APIs. Among other parameters, the number of tertiary aromatic amines, the presence of electronegative atoms like N, O, and Cl, the size of a molecule, the number of aromatic hydroxyl groups, the presence of substituted aromatic nitrogen atoms and alkyl-substituted tertiary carbon atoms were also found to be influential for the regulation of solid water partition coefficient of APIs during the wastewater treatment process. The statistical validity tests performed on the developed partial least squares (PLS) model showed that it is statistically evident, robust, and predictive (R2Train = 0.750, Q2LOO = 0.683, Q2F1 = 0.655, Q2F2 (or R2Test) = 0.651). In addition, the predictivity of the constructed model was further inspected by using the "prediction reliability indicator" tool for 14 external APIs.

A Review on Per- and Polyfluoroalkyl Substances in Pregnant Women: Maternal Exposure, Placental Transfer, and Relevant Model Simulation

Per- and polyfluoroalkyl substances (PFASs) are important and ubiquitous environmental contaminants worldwide. These novel contaminants can enter human bodies via various pathways, subsequently posing risks to the ecosystem and human health. The exposure of pregnant women to PFASs might pose risks to the health of mothers and the growth and development of fetuses. However, little information is available about the placental transfer of PFASs from mothers to fetuses and the related mechanisms through model simulation. In the present study, based upon a review of previously published literature, we initially summarized the exposure pathways of PFASs in pregnant women, factors affecting the efficiency of placental transfer, and mechanisms associated with placental transfer; outlined simulation analysis approaches using molecular docking and machine learning to reveal the mechanisms of placental transfer; and finally highlighted future research emphases that need to be focused on. Consequently, it was notable that the binding of PFASs to proteins during placental transfer could be simulated by molecular docking and that the placental transfer efficiency of PFASs could also be predicted by machine learning. Therefore, future research on the maternal-fetal transfer mechanisms of PFASs with the benefit of simulation analysis approaches is warranted to provide a scientific basis for the health effects of PFASs on newborns.

Calibration of the Chemcatcher® passive sampler and derivation of generic sampling rates for a broad application in monitoring of surface waters

We determined sampling rates for 34 pesticides, five pesticide transformation products, and 34 pharmaceutical compounds with the Chemcatcher (CC) passive sampler in a laboratory-based continuous-flow system at 40 cm/s and ambient temperature. Three different sampling phases were used: styrene divinylbenzene disks (SDB-XC), styrene divinylbenzene reversed phase sulfonate disks (SDB-RPS), and hydrophilic lipophilic balance disks (HLB), in all cases covered with a diffusion-limiting polyethersulfone membrane. The measured sampling rates range from 0.007 L/d to 0.193 L/d for CC with SDB-XC (CC-XC), from 0.055 L/d to 0.796 L/d for CC with SDB-RPS (CC-RPS), and from 0.018 L/d to 0.073 L/d for CC equipped with HLB (CC-HLB). Comparison with sampling rates from literature enabled to derive generic sampling rates that can be used for compounds with unknown uptake kinetics such as transformations products and new compounds of interest. Field trial results demonstrate that the presently derived generic sampling rates are suitable for estimating time-weighted average concentrations within reasonable uncertainty limits. In this way, Chemcatcher passive sampling can be applied approximately to a broad range of solutes without the need for deriving compound-specific sampling rates, which enable compliance checks against environmental quality standards and further risk assessment.

A Review of In Situ Methods-Solid Phase Adsorption Toxin Tracking (SPATT) and Polar Organic Chemical Integrative Sampler (POCIS) for the Collection and Concentration of Marine Biotoxins and Pharmaceuticals in Environmental Waters

Solid Phase Adsorption Toxin Tracking (SPATT) and Polar Organic Chemical Integrative Sampler (POCIS) are in situ methods that have been applied to pre-concentrate a range of marine toxins, pesticides and pharmaceutical compounds that occur at low levels in marine and environmental waters. Recent research has identified the widespread distribution of biotoxins and pharmaceuticals in environmental waters (marine, brackish and freshwater) highlighting the need for the development of effective techniques to generate accurate quantitative water system profiles. In this manuscript, we reviewed in situ methods known as Solid Phase Adsorption Toxin Tracking (SPATT) and Polar Organic Chemical Integrative Sampler (POCIS) for the collection and concentration of marine biotoxins, freshwater cyanotoxins and pharmaceuticals in environmental waters since the 1980s to present. Twelve different adsorption substrates in SPATT and 18 different sorbents in POCIS were reviewed for their ability to absorb a range of lipophilic and hydrophilic marine biotoxins, pharmaceuticals, pesticides, antibiotics and microcystins in marine water, freshwater and wastewater. This review suggests the gaps in reported studies, outlines future research possibilities and guides researchers who wish to work on water contaminates using Solid Phase Adsorption Toxin Tracking (SPATT) and Polar Organic Chemical Integrative Sampler (POCIS) technologies.

Comparison of POCIS and grab sampling techniques for monitoring PPCPs in vernal pools in central Pennsylvania

Active ingredients in pharmaceuticals and personal care products (PPCPs) can persist through wastewater treatment plants and be released into the environment where they can inadvertently pose risks to non-target organisms. Emerging contaminants (ECs), including PPCPs, are commonly detected in wastewater effluent. With the increasing beneficial re-use of treated wastewater globally, there is a need to understand how spray-irrigation activities affect the occurrence and persistence of ECs in the environment to which they are introduced. Here, we explore the impacts of wastewater spray-irrigation on nearby ephemeral wetlands (e.g., vernal pools) through the use of grab and Polar Organic Chemical Integrative Sampling (POCIS) techniques. This study sought to determine whether integrative sampling techniques are better suited than traditional grab sampling techniques in assessing the presence and concentrations of ECs in vernal pools by evaluating 34 ECs in six vernal pools in central Pennsylvania. Three pools were impacted by wastewater spray-irrigation activities and three were in a nearby forested area. Results of this study found that POCIS detected a wide range of 25 ECs (log K_ow between -2.6 and 9.37) more or, in some cases, equally frequently, relative to grab samples. Additionally, grab samples were found to best capture short-lived elevated inputs of ECs (from irrigation events) while POCIS were found to best capture ECs that were present in vernal pools over a longer period of time (weeks to months). For ECs detected more frequently in grab samples, concentrations were higher compared to time weighted average aqueous concentrations estimated from POCIS. This study advances understanding of the potential impact of wastewater beneficial reuse on vernal pools and informs how best to monitor the presence of ECs in vernal pools using integrative and grab sampling techniques.

Use of a large dataset to develop new models for estimating the sorption of active pharmaceutical ingredients in soils and sediments

Information on the sorption of active pharmaceutical ingredients (APIs) in soils and sediments is needed for assessing the environmental risks of these substances yet these data are unavailable for many APIs in use. Predictive models for estimating sorption could provide a solution. The performance of existing models is, however, often poor and most models do not account for the effects of soil/sediment properties which are known to significantly affect API sorption. Therefore, here, we use a high-quality dataset on the sorption behavior of 54 APIs in 13 soils and sediments to develop new models for estimating sorption coefficients for APIs in soils and sediments using three machine learning approaches (artificial neural network, random forest and support vector machine) and linear regression. A random forest-based model, with chemical and solid descriptors as the input, was the best performing model. Evaluation of this model using an independent sorption dataset from the literature showed that the model was able to predict sorption coefficients of 90% of the test set to within a factor of 10 of the experimental values. This new model could be invaluable in assessing the sorption behavior of molecules that have yet to be tested and in landscape-level risk assessments.

Calibration and field application of the Atlantic HLB Disk containing Chemcatcher® passive sampler - Quantitative monitoring of herbicides, other pesticides, and transformation products in German streams

The Chemcatcher® (CC) passive sampler containing an Atlantic HLB-L Disk (AD) was calibrated in a laboratory-based flow-through tank over 21 days under stirring for 38 polar organic pesticides with log K_ow ranging from -1.7 to 3.8. The resultant sampling rates R_s range from 0.025 to 0.068 L/d. In 2018, field trials were conducted in the German rivers Mulde and Havel, as well as in 7 agricultural streams in Lower Saxony and Saxony-Anhalt. For 36 detected pesticides, the overall low concentrations were 0.2 to 49.4 ng/L. The determined pesticide profiles reflect agricultural use and were dominated by triazine herbicides including transformation products, by neonicotinoid insecticides, and by the herbicide mecoprop. Additional single hot spots were provided by the herbicides metamitron, isoproturon, and MCPA (showing the overall largest value of 49.4 ng/L). Notably, the detected waterborne pesticides include banned herbicides and associated transformation products in concentration ratios suggesting also recent input. This concerns in particular atrazine and its transformation products 2-OH-atrazine, deethylatrazine and deisopropylatrazine. An extended target screening of AD-CC extracts from the river Havel revealed the additional presence of other organic micropollutants including biocides, surfactants and industrial chemicals, and demonstrated the AD-CC applicability up to log K_ow of 4.5.

Evaluation of Illicit Drug Consumption by Wastewater Analysis Using Polar Organic Chemical Integrative Sampler as a Monitoring Tool

Illicit drug abuse is a worldwide social and health problem, and monitoring illicit drug use is of paramount importance in the context of public policies. It is already known that relevant epidemiologic information can be obtained from the analysis of urban residual waters. This approach, named wastewater-based epidemiology (WBE), is based on the measurement of specific markers, resulting from human biotransformation of the target drugs, as indicators of the consumption of the compounds by the population served by the wastewater treatment installation under investigation. Drug consumption estimation based on WBE requires sewage sampling strategies that express the concentrations along the whole time period of time. To this end, the most common approach is the use of automatic composite samplers. However, this active sampling procedure is costly, especially for long-term studies and in limited-resources settings. An alternative, cost-effective, sampling strategy is the use of passive samplers, like the polar organic chemical integrative sampler (POCIS). POCIS sampling has already been applied to the estimation of exposure to pharmaceuticals, pesticides, and some drugs of abuse, and some studies evaluated the comparative performances of POCIS and automatic composite samplers. In this context, this manuscript aims to review the most important biomarkers of drugs of abuse consumption in wastewater, the fundamentals of POCIS sampling in WBE, the previous application of POCIS for WBE of drugs of abuse, and to discuss the advantages and disadvantages of POCIS sampling, in comparison with other strategies used in WBE. POCIS sampling is an effective strategy to obtain a representative overview of biomarker concentrations in sewage over time, with a small number of analyzed samples, increased detection limits, with lower costs than active sampling. Just a few studies applied POCIS sampling for WBE of drugs of abuse, but the available data support the use of POCIS as a valuable tool for the long-term monitoring of the consumption of certain drugs within a defined population, particularly in limited-resources settings.

A year-long passive sampling of phenolic endocrine disrupting chemicals in the East River, South China

The occurrence of endocrine disrupting chemicals (EDCs) in the aquatic environment is a global concern. In this study, we employed two different passive samplers Diffusive Gradients in Thin-films (DGT) and Chemcatcher for in situ measurement of 8 phenolic EDCs in the East River of the Pearl River system over one-year. These data were assessed alongside results from traditional grab sampling. Six chemicals (4tOP, 4NP, BPA, E1, EE2 and DES) were regularly detected in the water samples, of which the three phenols (i.e. 4tOP, 4NP and BPA) were in all samples and at high concentrations (0.4-1040 ng/L for 4tOP, 2.6-58500 ng/L for NP and 11.4-123300 ng/L for BPA). Fewer target chemicals were detected in both passive samplers, with only 4tOP, 4NP and BPA found in most samplers; E1 and DES were occasionally measurable above detection limits. The higher (by about a factor of 2-3) measurements provided by DGT compared to Chemcatcher could be attributed to the effect of the diffusive boundary layer on Chemcatcher uptake or the strong adsorption of target chemicals on the Chemcatcher PES filter. The temporal trends of EDC monthly loadings indicated that they were from different sources and that WWTPs were not effective in EDC removal and/or there was still some untreated wastewater discharged into the rivers.

Sampling Rate of Polar Organic Chemical Integrative Sampler (POCIS): Influence Factors and Calibration Methods

As a passive sampling device, the polar organic chemical integrative sampler (POCIS) has the characteristics of simple operation, safety, and reliability for assessing the occurrence and risk of persistent and emerging trace organic pollutants. The POCIS, allowing for the determination of time-weighted average (TWA) concentration of polar organic chemicals, exhibits good application prospects in aquatic environments. Before deploying the device in water, the sampling rate (Rs), which is a key parameter for characterizing pollutant enrichment, should be determined and calibrated accurately. However, the Rs values strongly depend on experimental hydrodynamic conditions. This paper provides an overview of the current situation of the POCIS for environmental monitoring of organic pollutants in an aquatic system. The principle and theory of the POCIS are outlined. In particular, the effect factors such as the ambient conditions, pollutant properties, and device features on the Rs are analyzed in detail from aspects of impact dependence and mechanisms. The calibration methods of the Rs under laboratory and in situ conditions are summarized. This review offers supplementary information on comprehensive understanding of mechanism and application of the POCIS. Nevertheless, the Rs were impacted by a combined effect of solute–sorbent–membrane–solution, and the influence extent of each variable was still unclear. On this basis, the ongoing challenges are proposed for the future application of the POCIS in the actual environment, for instance, the need for this device to be improved in terms of quantitative methods for more accurate measurement of the Rs.

Experimental Estimation of 44 Pharmaceutical Polar Organic Chemical Integrative Sampler Sampling Rates in an Artificial River under Various Flow Conditions

The present study pertains to a polar organic chemical integrative sampler (POCIS) laboratory calibration to estimate the sampling rates for 44 pharmaceuticals featuring a wide range of polarity (-0.6 < octanol/water partition coefficient [log K_OW ] < 5.4). The calibration was performed at 16.0 ± 1.5 °C for 4 water flow velocities (0, 2-3, 6-7, and 20 cm/s) in both a tank (for calibration at 0 cm/s) and a laboratory-scale artificial river filled with 200 and 500 L of tap water spiked with 0.3 µg/L of each compound, respectively. Twelve new sampling rates and 26 sampling rates already available in the literature were determined, whereas the sampling rates for 6 pharmaceuticals could not be determined due to nonlinearity or poor accumulation in POCIS. An increase in the sampling rate value with flow velocity was observed, which is consistent with a decrease in the effective thickness of the water boundary layer at the POCIS membrane surface. Environ Toxicol Chem 2020;39:1186-1195. © 2020 SETAC.

Development of quantitative structure-property relationship model for predicting the field sampling rate (Rs) of Chemcatcher passive sampler

Passive sampling technology has been considered as a promising tool to measure the concentration of environmental contaminants. With this technology, sampling rate (R_s) is an important parameter. However, as experimental methods employed to obtain the R_s value of a given compound were time-consuming, laborious, and expensive. A cost-effective method for deriving R_s is urgent. In addition, considering the great dependence of R_s value on water matrix properties, the laboratory measured R_s may not be a good alternative for field R_s. Thus, obtaining the field R_s is very necessary. In this study, a multiparameter quantitative structure-property relationship (QSPR) model was constructed for predicting the field R_s of 91 polar to semi-polar organic compounds. The determination coefficient (R²_Train), leave-one-out cross-validated coefficient (Q²_LOO), bootstrap coefficient (Q²_BOOT), and root mean square error (RMSE_Train) of the training set were 0.772, 0.706, 0.769, and 0.230, respectively, while the external validation coefficient (Q²_EXT) and RMSE_EXT of the validation set were 0.641 and 0.253, respectively. According to the acceptable criteria (Q² > 0.600, R² > 0.700), the model had good robustness, goodness-of-fit, and predictive performances. Therefore, we could use the model to fill the data gap for substances within the applicability domain on their missing R_s value.

Quantitative use of passive sampling data to derive a complete seasonal sequence of flood event loads: a case study for maize herbicides in Luxembourg

Pesticides are the class of compounds with the most dynamic behaviour in their surface water occurrence: their episodic release to surface waters is closely related to the date of application and the following weather conditions and poses substantial challenges to monitoring in order to yield accurate mass transfer figures. Moreover, pesticide use, dose and time of application are largely unknown catchment wide and pose an essential problem as to the realism and reliability of pesticide fate modelling as well as accurate farmer counselling. Spatially and temporally highly resolved monitoring establishing pesticide sources was logistically unthinkable until the advent of passive samplers which combine ease of deployment and continuous sampling. However, because research on passive sampler performance has been mainly driven by analytical precision issues, doubts were high as to whether passive samplers could yield accurate time weighted averages in the field, all the more so that the number of field validations is to this day very limited. Here we present a study that used a combination of spatially distributed passive- and autosamplers to capture the runoff dynamics of pesticides used for maize crops in a 82 km2 catchment in Luxembourg. We demonstrate that passive samplers are capable of accurately monitoring episodic emissions of pesticides through a longitudinal profile in a catchment, thus allowing the identification of pesticide source areas. Thanks to the time-proportional nature of the passive sampling it was furthermore possible to calculate event mean concentrations and loads which were behaving temporally according to the physico-chemical properties of the compounds and to the timing and extent of mobilising discharge.

Theory and modelling approaches to passive sampling

Designs and applications of passive samplers for various environmental compartments have been broadened significantly since their introduction. Understanding the theory behind passive sampling is essential for proper development of sampling methods and for accurate interpretation of the results. Theoretical underpinnings of passive sampling have been explored using different approaches. The aim of this review is to describe passive sampling theory and modelling approaches presented in the literature in a manner that allows researchers to obtain comprehensive understanding of them and to recognize the assumptions behind each approach together with their applicability to a given passive sampling technique. A common approach originates from Whitman's two-film theory and produces an exponential model that describes the entire passive sampling process. This approach, however, is based on several assumptions including linear exchange kinetics between the sampled medium and the passive sampler. Two-phase air passive samplers with a well-defined barrier are commonly modeled based on the zero-sink assumption, which assumes efficient trapping of analytes in the receiving phase. This assumption may become invalid under various scenarios; consequently, other approaches to modelling have been introduced including simulation of the sampling process by approximate temporal-steady states in hypothetical segments in the adsorption phase. Another approach uses dynamic models to determine accumulation of analytes in passive samplers. Dynamic models are capable of describing mass accumulation in the passive sampler, its transient response, and its response to fluctuations in environmental concentrations. Finally, empirically calibrated models, attempting to simplify the process of passive sampling rate determination, are also presented. In general, dynamic models are used to establish a profound understanding of the sampling process and analyse the applicability of the simpler models and their assumptions, while the simplified models are desirable and practical for most users. Nonetheless, due to the advancement in the computational tools, application of the dynamic models could be made simple and user-friendly.

An immission perspective of emerging micropollutant pressure in Luxembourgish surface waters: A simple evaluation scheme for wastewater impact assessment

While wastewater treatment plants have been identified as the most prominent source of emerging micropollutants in surface waters, prediction of their ambient concentrations remains a challenge. This is due to the variability of loads entering individual treatment plants and of the elimination capacity by the latter as well as potential attenuation in the river network. Although geospatially detailed models exist, they suffer from the same data input uncertainties. Here, we investigated the concentration profiles of 20 emerging pollutants in different river stretches in Luxembourg with variable sanitary pressures. Using carbamazepine as a recalcitrant wastewater indicator, the correlation of the compounds to the latter revealed source and fate variability as well as specific emitters. Relating carbamazepine to sanitary pressure, expressed as the sum of population equivalents in a catchment divided by its surface [PE ha^-1] allowed predicting the impact of emerging pollutants on the entire river network. The limited variability of the pollutant profiles allowed for prioritization of impacted stretches depending on the different sanitary pressures at risk quotient exceedance. The main drivers of impact were triclosan, diclofenac, clarithromycine and diuron.

Mechanistic Model Describing the Uptake of Chemicals by Aquatic Integrative Samplers: Comparison to Data and Implications for Improved Sampler Configurations

Aquatic integrative passive samplers are used to determine aqueous concentrations of polar organic pollutants, yet their uptake mechanisms are poorly understood. We introduce a one-dimensional model to simulate uptake by a passive sampler, Chemcatcher. The model considers the uptake as molecular diffusion through a series consisting of the aqueous boundary layer (ABL), the membrane filter (MF), and the sorbent disk with concurrent sorption by matrix of the MF and the disk. Uptake profiles of ∼20 polar chemicals measured over a week and a month were accurately modeled. Characteristic behaviors such as lag phases, linear and curved uptake, and equilibrating behavior were explained well by the model. As the model is mechanistically based, it was able to show the combined influences of the MF/water ( K_MF/w) and disk/water ( K_disk/w) partition coefficients, diffusion coefficients, and the ABL thickness on the sampling rates. On the basis of the model results, we offer three concrete recommendations for achieving the linear uptake needed for measuring time-weighted average concentrations: (i) use a MF that does not significantly sorb chemicals (e.g., log K_MF/w < 3) to avoid lag phases, (ii) use a sorbent with strong sorption properties (e.g., log K_disk/w > 6) for effective trapping of chemicals on the disk top layer, and (iii) make the ABL and/or the MF thicker so that the diffusion toward the disk slows.

Prediction of bioconcentration factors in fish and invertebrates using machine learning

The application of machine learning has recently gained interest from ecotoxicological fields for its ability to model and predict chemical and/or biological processes, such as the prediction of bioconcentration. However, comparison of different models and the prediction of bioconcentration in invertebrates has not been previously evaluated. A comparison of 24 linear and machine learning models is presented herein for the prediction of bioconcentration in fish and important factors that influenced accumulation identified. R² and root mean square error (RMSE) for the test data (n = 110 cases) ranged from 0.23-0.73 and 0.34-1.20, respectively. Model performance was critically assessed with neural networks and tree-based learners showing the best performance. An optimised 4-layer multi-layer perceptron (14 descriptors) was selected for further testing. The model was applied for cross-species prediction of bioconcentration in a freshwater invertebrate, Gammarus pulex. The model for G. pulex showed good performance with R² of 0.99 and 0.93 for the verification and test data, respectively. Important molecular descriptors determined to influence bioconcentration were molecular mass (MW), octanol-water distribution coefficient (logD), topological polar surface area (TPSA) and number of nitrogen atoms (nN) among others. Modelling of hazard criteria such as PBT, showed potential to replace the need for animal testing. However, the use of machine learning models in the regulatory context has been minimal to date and is critically discussed herein. The movement away from experimental estimations of accumulation to in silico modelling would enable rapid prioritisation of contaminants that may pose a risk to environmental health and the food chain.

Comparison of different monitoring methods for the measurement of metaldehyde in surface waters

Metaldehyde is recognised as an emerging contaminant. It is a powerful molluscicide and is the active compound in many types of slug pellets used for the protection of crops. The application of pellets to land generally takes place between August and December when slugs thrive. Due to its high use and physico-chemical properties, metaldehyde can be present in the aquatic environment at concentrations above the EU Drinking Water Directive limit of 100 ng L^-1 for a single pesticide. Such high concentrations are problematic when these waters are used in the production of drinking water. Being able to effectively monitor this pollutant of concern is important. We compared four different monitoring techniques (spot and automated bottle sampling, on-line gas chromatography/mass spectrometry (GC/MS) and passive sampling) to estimate the concentration of metaldehyde. Trials were undertaken in the Mimmshall Brook catchment (Hertfordshire, UK) and in a feed in a drinking water treatment plant for differing periods between 17th October and 31st December 2017. This period coincided with the agricultural application of metaldehyde. Overall, there was a good agreement between the concentrations measured by the four techniques, each providing complementary information. The highest resolution data was obtained using the on-line GC/MS. During the study, there was a large exceedance (500 ng L^-1) of metaldehyde that entered the treatment plant; but this was not related to rainfall in the area. Each monitoring method had its own advantages and disadvantages for monitoring investigations, particularly in terms of cost and turn-a-round time of data.

A comparison of equilibrium and kinetic passive sampling for the monitoring of aquatic organic contaminants in German rivers

The performances of an equilibrium and a kinetic passive sampler for monitoring a range of organic contaminants (Log K_OW from -0.03 to 6.26) were evaluated in the effluent of a wastewater treatment plant, the receiving river Saar as well as the river Mosel in Germany. The polar organic chemical integrative sampler (POCIS) and a new mixed polymer sampler (MPS) were selected as kinetic and equilibrium passive samplers, respectively. Concentrations were described in terms of a time-weighted average concentration (C_TWA) from the POCIS measurements and as an equilibrium concentration from the MPS (C_Equil-MPS) and POCIS membrane (C_Equil-PES) analyses. Twenty-seven compounds could be detected, including eight priority substances of the EU Water Framework Directive. Both sampler types detected a similar range of compounds in the low ng/L to μg/L range, with a high proportion of pharmaceuticals being detected at all sampling sites. To account for uncertainty in the POCIS sampling rates, a range in C_TWA was estimated by applying low and high sampling rates. For the compounds that were detected in the POCIS this range was within a factor of 3.5. Interestingly, the MPS extracts showed lower ionisation artefacts than the POCIS extracts during the LC-MS/MS analysis. Finally, total water concentrations (C_Total) were estimated from the dissolved concentrations, literature organic carbon partition coefficients (K_OC) and the total organic carbon levels measured in the rivers. For the compounds in this study, negligible differences between C_Total and the passive sampler-derived dissolved concentrations were found with a maximum difference of 15% for diclofenac. Overall, this study demonstrated that the parallel application of kinetic and equilibrium passive samplers can improve the description of water quality.

Calibration and application of the Chemcatcher® passive sampler for monitoring acidic herbicides in the River Exe, UK catchment

Acidic herbicides are used to control broad-leaved weeds. They are stable, water-soluble, and with low binding to soil are found frequently in surface waters, often at concentrations above the EU Drinking Water Directive limit of 0.10 μg L^-1. This presents a problem when such waters are abstracted for potable supplies. Understanding their sources, transport and fate in river catchments is important. We developed a new Chemcatcher^® passive sampler, comprising a 3M Empore™ anion-exchange disk overlaid with a polyethersulphone membrane, for monitoring acidic herbicides (2,4-D, dicamba, dichlorprop, fluroxypyr, MCPA, MCPB, mecoprop, tricolpyr). Sampler uptake rates (R_s = 0.044-0.113 L day^-1) were measured in the laboratory. Two field trials using the Chemcatcher^® were undertaken in the River Exe catchment, UK. Time-weighted average (TWA) concentrations of the herbicides obtained using the Chemcatcher^® were compared with concentrations measured in spot samples of water. The two techniques gave complimentary monitoring data, with the samplers being able to measure stochastic inputs of MCPA and mecoprop occurring in field trial 1. Chemcatcher^® detected a large input of MCPA not found by spot sampling during field trial 2. Devices also detected other pesticides and pharmaceuticals with acidic properties. Information obtained using the Chemcatcher^® can be used to develop improved risk assessments and catchment management plans and to assess the effectiveness of any mitigation and remediation strategies.

Comparison of the sampling rates and partitioning behaviour of polar and non-polar contaminants in the polar organic chemical integrative sampler and a monophasic mixed polymer sampler for application as an equilibrium passive sampler

In this work, Oasis HLB® beads were embedded in a silicone matrix to make a single phase passive sampler with a higher affinity for polar and ionisable compounds than silicone alone. The applicability of this mixed polymer sampler (MPS) was investigated for 34 aquatic contaminants (log K_OW -0.03 to 6.26) in batch experiments. The influence of flow was investigated by comparing uptake under static and stirred conditions. The sampler characteristics of the MPS was assessed in terms of sampling rates (R_S) and sampler-water partition coefficients (K_SW), and these were compared to those of the polar organic chemical integrative sampler (POCIS) as a reference kinetic passive sampler. The MPS was characterized as an equilibrium sampler for both polar and non-polar compounds, with faster uptake rates and a shorter time to reach equilibrium than the POCIS. Water flow rate impacted sampling rates by up to a factor of 12 when comparing static and stirred conditions. In addition, the relative accumulation of compounds in the polyethersulfone (PES) membranes versus the inner Oasis HLB sorbent was compared for the POCIS, and ranged from <1% to 83% depending on the analyte properties. This is indicative of a potentially significant lag-phase for less polar compounds within POCIS. The findings of this study can be used to quantitatively describe the partitioning and kinetic behaviour of MPS and POCIS for a range of aquatic organic contaminants for application in field sampling.

Understanding and predicting the diffusivity of organic compounds in polydimethylsiloxane material for passive sampler applications using a simple quantitative structure-property relationship model

The diffusivity of 145 compounds in polydimethylsiloxane (PDMS) material was determined in the laboratory using a film stacking technique. The results were pooled with available literature data, providing a final data set of 198 compounds with diffusivity (D_PDMS ) spanning over approximately 5 log units. The principal variables controlling the diffusivity of penetrants were investigated by comparing D_PDMS within and between different homologous series. The dipole moment, molecular size, and flexibility of penetrants appear to be the most prevalent factors controlling a compound's diffusivity. A nonlinear quantitative structure-property relationship is proposed using as predicting variables the molecular volume, the number of rotatable bonds, the topological polar surface area, and the number of O and N atoms. The final relationship has a correlation coefficient of R²  = 0.81 and a mean absolute error of 0.26 m² s^-1 (log unit), approaching the average error for the experimentally determined values (0.12 m² s^-1 ). The model, based on a heuristic approach, is ready for use by analytical chemists with no specific background in theoretical chemistry (notably for passive sampler development). Environ Toxicol Chem 2018;37:1291-1300. © 2018 SETAC.

Characterizing Sorption and Permeation Properties of Membrane Filters Used for Aquatic Integrative Passive Samplers

Aquatic integrative passive sampling is a promising approach to measure the time-weighted average concentration, yet our understanding for the sampling mechanisms of polar organic contaminants should be further advanced to fully exploit the potential of the method for real-world applications. This study aimed to characterize the sorption and permeation properties of poly(ether sulfone) (PES) and poly(tetrafluoroethylene) (PTFE) membrane filters (MFs) used for passive samplers. Batch sorption experiments with 14 probe chemicals showed that the sorption by PES was generally strong, with the respective sorption coefficients greater than the octanol-water partition coefficients by 2-3 log units. In contrast, the PTFE filter exhibited no significant sorption for all tested chemicals, representing a promising candidate MF that avoids lag-times and slow responses to fluctuating concentrations. Permeation experiments in a glass cell system and successive modeling demonstrated that, if no sorption to the MF occurs, the MF permeation of a chemical can be fully described with a first-order model that considers the transfer through the aqueous boundary layers and the diffusion in water-filled MF pores. Significant sorption to the MF coincided with substantial delay of permeation, which was successfully modeled with the local sorption equilibrium assumption. These findings have implications for improved sampler configurations and successful models for the chemical uptake.

Kinetic accumulation processes and models for 43 micropollutants in "pharmaceutical" POCIS

The "pharmaceutical" polar organic integrative sampler (POCIS) is a passive sampler composed of an outer polyethersulfone (PES) membrane and an inner receiving Hydrophilic-Lipophilic Balance (HLB) phase. Target micropollutants can accumulate in the POCIS HLB phase following different uptake patterns. Two of the most common ones are a first-order kinetic uptake (Chemical Reaction Kinetic 1, CRK1 model), and a first-order kinetic uptake with an inflexion point (CRK2 model). From a previous study, we identified 30 and 13 micropollutants following CRK1 and CRK2 accumulation model in the POCIS HLB phase, respectively. We hypothesized that uptake in the outer PES membrane of POCIS may influence the uptake pathway. Thus, novel measurements of uptake in PES membrane were performed for these micropollutants to characterise kinetic accumulation in the membrane with and without the HLB phase. We determined, for the first time, the membrane-water distribution coefficient for 31 micropolluants. Moreover, the lag times for molecules to breakthrough the POCIS membrane increased with increasing hydrophobicity, defined by the octanol-water dissociation constant D_ow. However, D_ow alone was insufficient to predict whether uptake followed a CRK1 or CRK2 model in the POCIS HLB phase. Thus, we performed a factorial discriminant analysis considering several molecular physico-chemical properties, and the model of accumulation for the studied micropollutants can be predicted with >90% confidence. The most influent properties to predict the accumulation model were the log D_ow and the polar surface area of the molecule (>70% confidence with just these two properties). Molecules exhibiting a CRK1 uptake model for the POCIS HLB phase tended to have log D_ow>2.5 and polar surface area <50Ǻ².

Monitoring alkylphenols in water using the polar organic chemical integrative sampler (POCIS): Determining sampling rates via the extraction of PES membranes and Oasis beads

Polar organic chemical integrative samplers (POCIS) have previously been used to monitor alkylphenol (AP) contamination in water and produced water. However, only the sorbent receiving phase of the POCIS (Oasis beads) is traditionally analyzed, thus limiting the use of POCIS for monitoring a range of APs with varying hydrophobicity. Here a "pharmaceutical" POCIS was calibrated in the laboratory using a static renewal setup for APs (from 2-ethylphenol to 4-n-nonylphenol) with varying hydrophobicity (log K_ow between 2.47 and 5.76). The POCIS sampler was calibrated over its 28 day integrative regime and sampling rates (R_s) were determined. Uptake was shown to be a function of AP hydrophobicity where compounds with log K_ow < 4 were preferentially accumulated in Oasis beads, and compounds with log K_ow > 5 were preferentially accumulated in the PES membranes. A lag phase (over a 24 h period) before uptake in to the PES membranes occurred was evident. This work demonstrates that the analysis of both POCIS phases is vital in order to correctly determine environmentally relevant concentrations owing to the fact that for APs with log K_ow ≤ 4 uptake, to the PES membranes and the Oasis beads, involves different processes compared to APs with log K_ow ≥ 4. The extraction of both the POCIS matrices is thus recommended in order to assess the concentration of hydrophobic APs (log K_ow ≥ 4), as well as hydrophilic APs, most effectively.

Monitoring Herbicide Concentrations and Loads during a Flood Event: A Comparison of Grab Sampling with Passive Sampling

The suitability of passive samplers (Chemcatcher) as an alternative to grab sampling in estimating time-weighted average (TWA) concentrations and total loads of herbicides was assessed. Grab sampling complemented deployments of passive samplers in a tropical waterway in Queensland, Australia, before, during and after a flood event. Good agreement was observed between the two sampling modes in estimating TWA concentrations that was independent of herbicide concentrations ranging over 2 orders of magnitude. In a flood-specific deployment, passive sampler TWA concentrations underestimated mean grab sampler (n = 258) derived concentrations of atrazine, diuron, ametryn, and metolachlor by an average factor of 1.29. No clear trends were evident in the ratios of load estimates from passive samplers relative to grab samples that ranged between 0.3 and 1.8 for these analytes because of the limitations of using TWA concentrations to derive flow-weighted loads. Stratification of deployments by flow however generally resulted in noticeable improvements in passive sampler load estimates. By considering the magnitude of the uncertainty (interquartile range and the root-mean-squared error) of load estimates a modeling exercise showed that passive samplers were a viable alternative to grab sampling since between 3 and 17 grab samples were needed before grab sampling results had less uncertainty.

Quantitative structure-property relationships for predicting sorption of pharmaceuticals to sewage sludge during waste water treatment processes

Understanding the sorption of pharmaceuticals to sewage sludge during waste water treatment processes is important for understanding their environmental fate and in risk assessments. The degree of sorption is defined by the sludge/water partition coefficient (Kd). Experimental Kd values (n=297) for active pharmaceutical ingredients (n=148) in primary and activated sludge were collected from literature. The compounds were classified by their charge at pH7.4 (44 uncharged, 60 positively and 28 negatively charged, and 16 zwitterions). Univariate models relating log Kd to log Kow for each charge class showed weak correlations (maximum R2=0.51 for positively charged) with no overall correlation for the combined dataset (R2=0.04). Weaker correlations were found when relating log Kd to log Dow. Three sets of molecular descriptors (Molecular Operating Environment, VolSurf and ParaSurf) encoding a range of physico-chemical properties were used to derive multivariate models using stepwise regression, partial least squares and Bayesian artificial neural networks (ANN). The best predictive performance was obtained with ANN, with R2=0.62-0.69 for these descriptors using the complete dataset. Use of more complex Vsurf and ParaSurf descriptors showed little improvement over Molecular Operating Environment descriptors. The most influential descriptors in the ANN models, identified by automatic relevance determination, highlighted the importance of hydrophobicity, charge and molecular shape effects in these sorbate-sorbent interactions. The heterogeneous nature of the different sewage sludges used to measure Kd limited the predictability of sorption from physico-chemical properties of the pharmaceuticals alone. Standardization of test materials for the measurement of Kd would improve comparability of data from different studies, in the long-term leading to better quality environmental risk assessments.

Development and Calibration of an Organic-Diffusive Gradients in Thin Films Aquatic Passive Sampler for a Diverse Suite of Polar Organic Contaminants

A unique configuration of the diffusive gradients in thin films sampler for polar organics (o-DGT) without a poly(ether sulfone) membrane was developed, calibrated, and field-evaluated. Diffusion coefficients (D) through agarose diffusive gels ranged from (1.02 to 4.74) × 10^-6 cm²/s for 34 pharmaceuticals and pesticides at 5, 13, and 23 °C. Analyte-specific diffusion-temperature plots produced linear (r² > 0.85) empirical relationships whereby D could be estimated at any environmentally relevant temperature (i.e., matched to in situ water conditions). Linear uptake for all analytes was observed in a static renewal calibration experiment over 25 days except for three macrolide antibiotics, which reached saturation at 300 ng (≈15 d). Experimental sampling rates ranged from 8.8 to 16.1 mL/d and were successfully estimated with measured and modeled D within 19% and 30% average relative error, respectively. Under slow flowing (2.4 cm/s) and static conditions, the in situ diffusive boundary layer (DBL) thickness ranged from 0.023 to 0.075 cm, resulting in a maximum contribution to mass transfer of <45%. Estimated water concentrations by o-DGT at a wastewater treatment plant agreed well with grab samples and appeared to be less influenced by the boundary layer compared to that of polar organic chemical integrative samplers (POCIS) deployed simultaneously. The o-DGT sampler is a promising monitoring tool that is largely insensitive to the DBL under typical flow conditions, facilitating the application of measured/modeled diffusion-based sampling rates. This significantly reduces the need for sampler calibration, making o-DGT more widely applicable, reliable, and cost-effective compared to current polar passive samplers.

Comparison of pharmaceutical, illicit drug, alcohol, nicotine and caffeine levels in wastewater with sale, seizure and consumption data for 8 European cities

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.