Assessing Emissions from Pharmaceutical Manufacturing Based on Temporal High-Resolution Mass Spectrometry Data

Linking chemical surface water monitoring and pesticide regulation in selected European countries

The progress in chemical analytics and understanding of pesticide dynamics in surface waters allows establishing robust data on compounds with frequent exceedances of quality standards. The current chemical, temporal, and spatial coverage of the pesticide monitoring campaigns differs strongly between European countries. A questionnaire revealed differences in monitoring strategies in seven selected European countries; Nordic countries prioritize temporal coverage, while others focus on spatial coverage. Chemical coverage has increased, especially for non-polar classes like synthetic pyrethroids. Sweden combines monitoring data with agricultural practices for derived quantities, while the Netherlands emphasizes spatial coverage to trace contamination sources. None of the EU member states currently has established a process for linking chemical surface water monitoring data with regulatory risk assessment, while Switzerland has recently established a legally defined feedback loop. Due to their design and objectives, most strategies do not capture concentration peaks, especially 2-week composite samples, but also grab samples. Nevertheless, for substances that appear problematic in many data sets, the need for action is evident even without harmonization of monitoring programs. Harmonization would be beneficial, however, for cross-national assessment including risk reduction measures.

Seasonal variation in structural and functional distribution of periphyton in a macrolide antibiotics-contaminated river

Periphyton, a microbial assemblage of autotrophic and heterotrophic organisms, is vital to aquatic ecosystems. While exposure to macrolide antibiotics has been confirmed to reduce the biodiversity and damage the critical ecological functions in indoor microcosm bioassays, the distribution of periphyton along a macrolide antibiotic pollution gradient in a river has yet to be determined. Herein, we established the spatiotemporal distribution of five major macrolides, i.e., azithromycin (AZI), roxithromycin (ROX), erythromycin (ERY), clarithromycin (CLA), and anhydro erythromycin (ERY-H2O) in water and periphyton of Zao River (Xi'an, China), after which we evaluated the effects on the structures, photosynthetic activity, and carbon utilization capacity of periphyton in March, June, and September 2023. In contrast with the reference sites, the macrolides were identified in all sewage treatment plants (STPs) impacted sites with concentrations ranging from 0.05 to 2.18 μg/L in water and from not detected - 9.67 μg/g in periphyton. Regarding community structure, the occurrence of macrolides was negatively linked to FirmicutesExiguobacterium undae and Exiguobacterium sibiricum, CyanobacteriaOscillatoriales and Vischeria sp., and ChlorophytaMonostroma grevillei, Selenastrum sp. LU21 and Desmodesmus subspicatus. At the functional level, only the metabolism of phenolic acids was significantly decreased in river reach with high antibiotic levels in June, compared to the other five carbon sources that were not altered. The overall photosynthetic activity of periphytic photosystem II remained unchanged in both reference and STPs impacted groups throughout three seasons. Overall, the macrolides released from STPs were correlated with the altered periphytic structures in the river, whereas a similar trend was not detected for the community functions owing to the functional redundancy. A mesocosm experiments warrants further consideration to validate the field results.

Application of biological early warning systems in wastewater treatment plants: Introducing a promising approach to monitor changing wastewater composition

Wastewater treatment plants (WWTPs) are a major source of micropollutants to surface waters. Currently, their chemical or biological monitoring is realized by using grab or composite samples, which provides only snapshots of the current wastewater composition. Especially in WWTPs with industrial input, the wastewater composition can be highly variable and a continuous assessment would be advantageous, but very labor and cost intensive. A promising concept are automated real-time biological early warning systems (BEWS), where living organisms are constantly exposed to the water and an alarm is triggered if the organism's responses exceed a harmful threshold of acute toxicity. Currently, BEWS are established for drinking water and surface water but are seldom applied to monitor wastewater. This study demonstrates that a battery of BEWS using algae (Chlorella vulgaris in the Algae Toximeter, bbe Moldaenke), water flea (Daphnia magna in the DaphTox II, bbe Moldaenke) and gammarids (Gammarus pulex in the Sensaguard, REMONDIS Aqua) can be adapted for wastewater surveillance. For continuous low-maintenance operation, a back-washable membrane filtration system is indispensable for adequate preparation of treated wastewater. Only minor deviations in the reaction of the organisms towards treated and filtered wastewater compared to surface waters were detected. After spiking treated wastewater with two concentrations of the model compounds diuron, chlorpyrifos methyl, and sertraline, the organisms in the different BEWS showed clear responses depending on the respective compound, concentration and mode of action. Immediate effects on photosynthetic activity of algae were detected for diuron exposure, and strong behavioral changes in water flea and gammarids after exposure to chlorpyrifos methyl or sertraline were observed, which triggered automated alarms. Different types of data analysis were applied to extract more information out of the specific behavioral traits, than only provided by the vendors algorithms. To investigate, whether behavioral movement changes can be linked to impact other endpoints, the effects on feeding activity of G. pulex were evaluated and results indicated significant differences between the exposures. Overall, these findings provide an important basis indicating that BEWS have the potential to act as alarm systems for pollution events in the wastewater sector.

Micropollutant concentration fluctuations in combined sewer overflows require short sampling intervals

Combined sewer overflows (CSOs) are an important pathway of organic micropollutants from urban areas to open water bodies. Understanding the temporal dynamics of these micropollutants during overflow events is crucial for applying appropriate sampling methods and implementing effective management strategies. Yet, little is known about the dynamics of micropollutants in CSOs, because most studies report concentrations from single grab samples or event mean concentrations (EMCs). With unique high temporal resolution measurements (3 min), we show the real dynamics of polar organic micropollutants in CSOs of one small (2,700 people: P) and one large (159,000 P) urban catchment, for two micropollutant categories: (i) 33 micropollutants in municipal wastewater and (ii) 13 micropollutants from urban surface runoff. The concentration dynamics depend on the substance source and the catchment size. Indoor substances such as pharmaceuticals show high temporal dynamics with changes of 1 to 2 orders of magnitude within 9 min in the CSO of the small catchment. In contrast, outdoor substances at the small catchment and all substances at the large catchment display considerably lower variation. We tested various time-proportional sampling strategies to assess the range of error when estimating EMCs. We recommend an interval of 3 min to capture the dynamics of indoor substances in CSOs from small catchments. The results highlight that both future monitoring campaigns and the planning and management of urban wet-weather treatment systems will benefit from high temporal sampling resolutions, not only to understand dynamics but also to minimize errors of estimated EMCs.

Effects of point and nonpoint source pollution on urban rivers: From the perspective of pollutant composition and toxicity

Wastewater discharge is considered to be one of the anthropogenic factors affecting the water quality of urban rivers. The source and composition of wastewater are complex and diverse, and it is difficult to evaluate its effect on water quality and ecological health of receiving waters. Environmental DNA method can determine all species living in waters by examining DNA sequences, reflecting the impact of water quality changes on aquatic systems. In this study, water samples from two urban rivers were collected in dry and wet seasons, and the composition of pollutants was investigated by nontarget screening. Based on the pollutant composition, compound toxicity prediction and concentration addition model were used to predict the toxicity changes of pollutants in the urban rivers. More than 1500 suspect organic pollutants were nontarget screened, and silafluofen was found to be a major toxicity contributor. Environmental DNA analysis was combined with water quality measure and pollutant toxicity prediction to reveal the effects of pollutants from different sources on aquatic ecosystems. Fish diversity was negatively correlated with the mixed toxicity of organic pollutants, suggesting potential ecological risk in these two urban rivers. Our study developed a water quality assessment method based on pollutant composition and toxicity, and the potential risk of nonpoint source pollutants on aquatic ecosystems should not be neglected.

Knowledge support for environmental information on pharmaceuticals: experiences among Swedish Drug and Therapeutics Committees

BACKGROUND

Two publicly available Swedish knowledge support systems, "Pharmaceuticals and Environment" on Janusinfo.se and Fass.se, provide environmental information on pharmaceuticals. Janusinfo is provided by the public healthcare system in Stockholm and Fass is provided by the pharmaceutical industry. The objectives of this study were to investigate the experiences among Swedish Drug and Therapeutics Committees (DTCs) with using the databases, retrieve development proposals for these, and investigate the DTCs' challenges with working with pharmaceuticals in the environment.

METHODS

A cross-sectional survey with 21 questions, both closed and open-ended, was distributed electronically in March 2022 to Sweden's 21 DTCs. Descriptive statistics and inductive categorization were used for the analysis.

RESULTS

A total of 132 respondents from 18 regions filled out the survey. The average regional response rate was 42%. The DTCs used the knowledge supports to consider environmental aspects of pharmaceuticals in their formularies and in education. Respondents were more familiar with Janusinfo compared to Fass but appreciated the availability of both. The DTCs especially valued the concrete proposals for certain active pharmaceutical ingredients on Janusinfo. Respondents requested that all medicinal products have environmental information on Fass. Challenges included lack of data, lack of transparency from the pharmaceutical industry and difficulties considering the environmental aspect of pharmaceuticals in their healthcare practice. Respondents wanted more knowledge, clear messages, and legislation to support their work to reduce the negative environmental impact of pharmaceuticals.

CONCLUSIONS

This study demonstrates that knowledge supports for environmental information on pharmaceuticals are valuable for the DTCs in Sweden, but the respondents experienced challenges in their work in this field. The study can provide insights to those in other countries interested in considering environmental aspects in their formulary decision-making.

From market to environment - consumption-normalised pharmaceutical emissions in the Rhine catchment

Direct and indirect threats by organic micropollutants can only be reliably assessed and prevented if the exposure to these chemicals is known, which in turn requires a confident estimate of their emitted amounts into the environment. APIs (Active Pharmaceutical Ingredients) enter surface waters mostly through the sewer system and wastewater treatment plants (WWTPs). However, their effluent fluxes are highly variable and influenced by several different factors that challenge robust emission estimates. Here, we defined a dimensionless, theoretically consumption-independent 'escape factor' (k_esc) for estimating the amount of APIs (expected to be) present in WWTP effluents. The factor is determined as the proportion of marketed and actually emitted amounts of APIs. A large collection of German and Swiss monitoring datasets were analyzed to calculate stochastic k_esc values for 31 APIs, reflecting both the magnitude and uncertainty of consumption-normalised emissions. Escape factors provide an easy-to-use tool for the estimation of average API emissions and expected variability from numerous WWTPs given that consumption data are provided, thereby supporting simulation modeling of the fate of APIs in stream networks or exposure assessments.

Water pollution threats in important bird and biodiversity areas from Spain

Chemical pollution is still an underestimated threat to surface waters from natural areas. This study has analysed the presence and distribution of 59 organic micropollutants (OMPs) including pharmaceuticals, lifestyle compounds, pesticides, organophosphate esters (OPEs), benzophenone and perfluoroalkyl substances (PFASs) in 411 water samples from 140 Important Bird and Biodiversity Areas (IBAs) from Spain, to evaluate the impact of these pollutants in sites of environmental relevance. Lifestyle compounds, pharmaceuticals and OPEs were the most ubiquitous chemical families, while pesticides and PFASs showed a detection frequency below 25% of the samples. The mean concentrations detected ranged from 0.1 to 301 ng/L. According to spatial data, agricultural surface has been identified as the most important source of all OMPs in natural areas. Lifestyle compounds and PFASs have been related to the presence of artificial surface and wastewater treatment plants (WWTPs) discharges, which were also an important source of pharmaceuticals to surface waters. Fifteen out of 59 OMPs have been found at levels posing a high risk for the aquatic IBAs ecosystems, being the insecticide chlorpyrifos, the antidepressant venlafaxine and perfluorooctanesulfonic acid (PFOS) the most concerning compounds. This is the first study to quantify water pollution in IBAs and evidence that OMPs are an emerging threat to freshwater ecosystems that are essential for biodiversity conservation.

Residential proximity to industrial pollution and mammographic density

BACKGROUND

Mammographic density (MD), expressed as percentage of fibroglandular breast tissue, is an important risk factor for breast cancer. Our objective is to investigate the relationship between MD and residential proximity to pollutant industries in premenopausal Spanish women.

METHODS

A cross-sectional study was carried out in a sample of 1225 women extracted from the DDM-Madrid study. Multiple linear regression models were used to assess the association of MD percentage (and their 95% confidence intervals (95%CIs)) and proximity (between 1 km and 3 km) to industries included in the European Pollutant Release and Transfer Register.

RESULTS

Although no association was found between MD and distance to all industries as a whole, several industrial sectors showed significant association for some distances: "surface treatment of metals and plastic" (β = 4.98, 95%CI = (0.85; 9.12) at ≤1.5 km, and β = 3.00, 95%CI = (0.26; 5.73) at ≤2.5 km), "organic chemical industry" (β = 6.73, 95%CI = (0.50; 12.97) at ≤1.5 km), "pharmaceutical products" (β = 4.14, 95%CI = (0.58; 7.70) at ≤2 km; β = 3.55, 95%CI = (0.49; 6.60) at ≤2.5 km; and β = 3.11, 95%CI = (0.20; 6.01) at ≤3 km), and "urban waste-water treatment plants" (β = 8.06, 95%CI = (0.82; 15.30) at ≤1 km; β = 5.28; 95%CI = (0.49; 10.06) at ≤1.5 km; β = 4.30, 95%CI = (0.03; 8.57) at ≤2 km; β = 5.26, 95%CI = (1.83; 8.68) at ≤2.5 km; and β = 3.19, 95%CI = (0.46; 5.92) at ≤3 km). Moreover, significant increased MD was observed in women close to industries releasing specific pollutants: ammonia (β = 4.55, 95%CI = (0.26; 8.83) at ≤1.5 km; and β = 3.81, 95%CI = (0.49; 7.14) at ≤2 km), dichloromethane (β = 3.86, 95%CI = (0.00; 7.71) at ≤2 km), ethylbenzene (β = 8.96, 95%CI = (0.57; 17.35) at ≤3 km), and phenols (β = 2.60, 95%CI = (0.21; 5.00) at ≤2.5 km).

CONCLUSIONS

Our results suggest no statistically significant relationship between MD and proximity to industries as a whole, although we detected associations with various industrial sectors and some specific pollutants, which suggests that MD could have a mediating role in breast carcinogenesis.

Approaches for assessing performance of high-resolution mass spectrometry-based non-targeted analysis methods

Non-targeted analysis (NTA) using high-resolution mass spectrometry has enabled the detection and identification of unknown and unexpected compounds of interest in a wide range of sample matrices. Despite these benefits of NTA methods, standardized procedures do not yet exist for assessing performance, limiting stakeholders’ abilities to suitably interpret and utilize NTA results. Herein, we first summarize existing performance assessment metrics for targeted analyses to provide context and clarify terminology that may be shared between targeted and NTA methods (e.g., terms such as accuracy, precision, sensitivity, and selectivity). We then discuss promising approaches for assessing NTA method performance, listing strengths and key caveats for each approach, and highlighting areas in need of further development. To structure the discussion, we define three types of NTA study objectives: sample classification, chemical identification, and chemical quantitation. Qualitative study performance (i.e., focusing on sample classification and/or chemical identification) can be assessed using the traditional confusion matrix, with some challenges and limitations. Quantitative study performance can be assessed using estimation procedures developed for targeted methods with consideration for additional sources of uncontrolled experimental error. This article is intended to stimulate discussion and further efforts to develop and improve procedures for assessing NTA method performance. Ultimately, improved performance assessments will enable accurate communication and effective utilization of NTA results by stakeholders.

Large-scale assessment of organic contaminant emissions from chemical and pharmaceutical manufacturing into Swiss surface waters

This study presents a nation-wide assessment of the influence of chemical and pharmaceutical manufacturing (CPM) wastewaters on synthetic organic contaminant (SOC) emissions to Swiss surface waters. Geographic Information System (GIS) based analysis of the presence of CPM in wastewater treatment plant (WWTP) catchments revealed wide distribution of this industrial sector across Switzerland, suggesting that one-third of the 718 Swiss WWTPs may be influenced by CPM wastewaters. To reflect the diversity of this type of wastewaters, we investigated the effluents of 11 WWTPs of diverse sizes and technologies, which treated 0-100% wastewater from a variety of CPM activities. In an extensive sampling campaign, we collected temporally high resolved (i.e., daily) samples for 2-3 months to capture the dynamics of CPM discharges. The > 850 samples were then measured with liquid chromatography high-resolution mass spectrometry (LC-HRMS). Non-target characterization of the LC-HRMS time series datasets revealed that CPM wastewaters left a highly variable and site-specific signature in the effluents of the WWTPs. Particularly, compared to WWTPs with purely domestic input, a larger variety of substances (up to 15 times more compounds) with higher maximum concentrations (1-2 orders of magnitude) and more uncommon substances were found in CPM-influenced effluents. Moreover, in the latter, highly fluctuating discharges often contributed to a substantial fraction of the overall emissions. The largely varying characteristics of CPM discharges between different facilities were primarily related to the type of activities at the industries (i.e., production versus processing of chemicals) as well as to the pre-treatment and storage of CPM wastewaters. Eventually, for one WWTP, LC-HRMS time series were correlated with ecotoxicity time series obtained from bioassays and major toxic components could be identified. Overall, in view of their potential relevance to water quality, a strong focus on SOC discharges from CPM is essential, including the design of situation-specific monitoring, as well as risk assessment and mitigation strategies that consider the variability of industrial emissions.

TrendProbe: Time profile analysis of emerging contaminants by LC-HRMS non-target screening and deep learning convolutional neural network

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

Novel prioritisation strategies for evaluation of temporal trends in archived white-tailed sea eagle muscle tissue in non-target screening

Environmental monitoring studies based on target analysis capture only a small fraction of contaminants of emerging concern (CECs) and miss pollutants potentially harmful to wildlife. Environmental specimen banks, with their archived samples, provide opportunities to identify new CECs by temporal trend analysis and non-target screening. In this study, archived white-tailed sea eagle (Haliaeetus albicilla) muscle tissue was analysed by non-targeted high-resolution mass spectrometry. Univariate statistical tests (Mann-Kendall and Spearman rank) for temporal trend analysis were applied as prioritisation methods. A workflow for non-target data was developed and validated using an artificial time series spiked at five levels with gradient concentrations of selected CECs (n = 243). Pooled eagle muscle tissues collected 1965-2017 were then investigated with an eight-point time series using the validated screening workflow. Following peak detection, peak alignment, and blank subtraction, 14 409 features were considered for statistical analysis. Prioritisation by time-trend analysis detected 207 features with increasing trends. Following unequivocal molecular formula assignment to prioritised features and further elucidation with MetFrag and EU Massbank, 13 compounds were tentatively identified, of which four were of anthropogenic origin. These results show that it is possible to prioritise new CECs in archived biological samples using univariate statistical approaches.

Molecular biomarker responses in the freshwater mussel Anodonta anatina exposed to an industrial wastewater effluent

Using a selection of molecular biomarkers, we evaluated responses in freshwater mussels (Anodonta anatina) exposed to effluent from an industrial wastewater treatment facility. The aims of this work were to (1) assess biomarkers of general toxicity under sublethal exposure to an anthropogenic mixture of chemicals, represented by an arbitrary effluent, and (2) evaluate the potential of A. anatina as a bioindicator of pollution. Adult mussels (n = in total 32; 24 males and 8 females) were exposed (96 h) in the laboratory to a fixed dilution of effluent or to a control treatment of standardized freshwater. Metal concentrations were in general higher in the effluent, by an order of magnitude or more, compared to the control. Toxic unit estimates were used as proxies of chemical stress, and Cu, Ni, and Zn were identified as potential major contributors (Cu> Ni > Zn). Six transcriptional (cat, gst, hsp70, hsp90, mt, sod) and two biochemical (AChE, GST) biomarkers were analyzed in two tissues, gills, and digestive glands. Out of the 16 responses (eight biomarkers × two tissues), 14 effect sizes were small (within ± 28 % of control) and differences non-significant (p > 0.05). Results did however show that (1) AChE activity increased by 40% in gills of exposed mussels compared to control, (2) hsp90 expression was 100% higher in exposed female gills compared to control, and (3) three marker signals (AChE in both tissues, and hsp70 in gills) differed between sexes, independent of treatment. Results highlight a need for further investigation of molecular biomarker variability and robustness in A. anatina.

Antibiotic resistance in the environment

Antibiotic resistance is a global health challenge, involving the transfer of bacteria and genes between humans, animals and the environment. Although multiple barriers restrict the flow of both bacteria and genes, pathogens recurrently acquire new resistance factors from other species, thereby reducing our ability to prevent and treat bacterial infections. Evolutionary events that lead to the emergence of new resistance factors in pathogens are rare and challenging to predict, but may be associated with vast ramifications. Transmission events of already widespread resistant strains are, on the other hand, common, quantifiable and more predictable, but the consequences of each event are limited. Quantifying the pathways and identifying the drivers of and bottlenecks for environmental evolution and transmission of antibiotic resistance are key components to understand and manage the resistance crisis as a whole. In this Review, we present our current understanding of the roles of the environment, including antibiotic pollution, in resistance evolution, in transmission and as a mere reflection of the regional antibiotic resistance situation in the clinic. We provide a perspective on current evidence, describe risk scenarios, discuss methods for surveillance and the assessment of potential drivers, and finally identify some actions to mitigate risks.

Occurrence and Distribution of Pharmaceuticals and Their Transformation Products in Luxembourgish Surface Waters

Pharmaceuticals and their transformation products (TPs) are continuously released into the aquatic environment via anthropogenic activity. To expand knowledge on the presence of pharmaceuticals and their known TPs in Luxembourgish rivers, 92 samples collected during routine monitoring events between 2019 and 2020 were investigated using nontarget analysis. Water samples were concentrated using solid-phase extraction and then analyzed using liquid chromatography coupled to a high-resolution mass spectrometer. Suspect screening was performed using several open source computational tools and resources including Shinyscreen (https://git-r3lab.uni.lu/eci/shinyscreen/), MetFrag (https://msbi.ipb-halle.de/MetFrag/), PubChemLite (https://zenodo.org/record/4432124), and MassBank (https://massbank.eu/MassBank/). A total of 94 pharmaceuticals, 88 confirmed at a level 1 confidence (86 of which could be quantified, two compounds too low to be quantified) and six identified at level 2a, were found to be present in Luxembourg rivers. Pharmaceutical TPs (12) were also found at a level 2a confidence. The pharmaceuticals were present at median concentrations up to 214 ng/L, with caffeine having a median concentration of 1424 ng/L. Antihypertensive drugs (15), psychoactive drugs (15), and antimicrobials (eight) were the most detected groups of pharmaceuticals. A spatiotemporal analysis of the data revealed areas with higher concentrations of the pharmaceuticals, as well as differences in pharmaceutical concentrations between 2019 and 2020. The results of this work will help guide activities for improving water management in the country and set baseline data for continuous monitoring and screening efforts, as well as for further open data and software developments.

Biotransformation of Chemicals at the Water–Sediment Interface─Toward a Robust Simulation Study Setup

Studying aquatic biotransformation of chemicals in laboratory experiments, i.e., OECD 308 and OECD 309 studies, is required by international regulatory frameworks to prevent the release of persistent chemicals into natural water bodies. Here, we aimed to address several previously described shortcomings of OECD 308/309 studies regarding their variable outcomes and questionable environmental relevance by broadly testing and characterizing a modified biotransformation test system in which an aerated water column covers a thin sediment layer. Compared to standard OECD 308/309 studies, the modified system showed little inter-replicate variability, improved observability of biotransformation, and consistency with first-order biotransformation kinetics for the majority of 43 test compounds, including pharmaceuticals, pesticides, and artificial sweeteners. To elucidate the factors underlying the decreased inter-replicate variability compared to OECD 309 outcomes, we used multidimensional flow cytometry data and a machine learning-based cell type assignment pipeline to study cell densities and cell type diversities in the sediment and water compartments. Our here presented data on cell type composition in both water and sediment allows, for the first time, to study the behavior of microbial test communities throughout different biotransformation simulation studies. We found that sediment-associated microbial communities were generally more stable throughout the experiments and exhibited higher cell type diversity than the water column-associated communities. Consistently, our data indicate that aquatic biotransformation of chemicals can be most robustly studied in test systems providing a sufficient amount of sediment-borne biomass. While these findings favor OECD 308-type systems over OECD 309-type systems to study biotransformation at the water-sediment interface, our results suggest that the former should be modified toward lower sediment-water ratios to improve observability and interpretability of biotransformation.

Screening priority indicator pollutants in full-scale wastewater treatment plants by non-target analysis

Wastewater treatment plants (WWTPs) are the main sources of emerging contaminants (ECs) in aquatic environment. However, the standards for limiting emerging pollutants in effluent are extremely lacking. We investigated the occurrence and removal of emerging pollutants in 16 WWTPs in China using non-target analysis. 568 substances screened out were divided into 9 kinds including 167 pharmaceuticals, 113 natural substances, 85 pesticides, 86 endogenous substances, 64 chemical raw materials, 14 personal care products, 17 food additives, 6 hormones and 16 others. And they were divided into 5 fates. Pesticides and pharmaceutical compounds seemed to be the most notable categories, the kinds detected in each sample is the largest compared with other compounds. Besides, the average removal rate of pesticides and pharmaceuticals in all WWTPs were the lowest, at 9.54% and 23.77%, respectively. Priority pollutants were screened by considering distribution of pollutants with different fates. Pollutants with the same fate especially "consistent" in different WWTPs had attracted attention. 4 potential priority pollutants including metoprolol, carbamazepine, 10, 11-dihydro-10, 11-dihydroxycarbamazepine and irbesartan were proposed. And it was found that the 4 compounds, "consistent suspects" and "consistent non-targets" had similar rankings of removal rate in 16 WWTPs, which can reflect the performance of different WWTPs.

Characterization of advanced wastewater treatment with ozone and activated carbon using LC-HRMS based non-target screening with automated trend assignment

Advanced treatment is increasingly being applied to improve abatement of micropollutants in wastewater effluent and reduce their load to surface waters. In this study, non-target screening of high-resolution mass spectrometry (HRMS) data, collected at three Swiss wastewater treatment plants (WWTPs), was used to evaluate different advanced wastewater treatment setups, including (1) granular activated carbon (GAC) filtration alone, (2) pre-ozonation followed by GAC filtration, and (3) pre-ozonation followed by powdered activated carbon (PAC) dosed onto a sand filter. Samples were collected at each treatment step of the WWTP and analyzed with reverse-phase liquid chromatography coupled to HRMS. Each WWTP received a portion of industrial wastewater and a prioritization method was applied to select non-target features potentially resulting from industrial activities. Approximately 37,000 non-target features were found in the influents of the WWTPs. A number of non-target features (1207) were prioritized as likely of industrial origin and 54 were identified through database spectral matching. The fates of all detected non-target features were assessed through a novel automated trend assignment method. A trend was assigned to each non-target feature based on the normalized intensity profile for each sampling date. Results showed that 73±4% of influent non-target features and the majority of industrial features (89%) were well-removed (i.e., >80% intensity reduction) during biological treatment in all three WWTPs. Advanced treatment removed, on average, an additional 11% of influent non-target features, with no significant differences observed among the different advanced treatment settings. In contrast, when considering a subset of 66 known micropollutants, advanced treatment was necessary to adequately abate these compounds and higher abatement was observed in fresh GAC (7,000-8,000 bed volumes (BVs)) compared to older GAC (18,000-48,000 BVs) (80% vs 56% of micropollutants were well-removed, respectively). Approximately half of the features detected in the WWTP effluents were features newly formed during the various treatment steps. In ozonation, between 1108-3579 features were classified as potential non-target ozonation transformation products (OTPs). No difference could be observed for their removal in GAC filters at the BVs investigated (70% of OTPs were well-removed on average). Similar amounts (67%) was observed with PAC (7.7-13.6 mg/L) dosed onto a sand filter, demonstrating that a post-treatment with activated carbon is efficient for the removal of OTPs.

Metabolomic Profiling and Toxicokinetics Modeling to Assess the Effects of the Pharmaceutical Diclofenac in the Aquatic Invertebrate Hyalella azteca

The exposure of ecologically critical invertebrate species to biologically active pharmaceuticals poses a serious risk to the aquatic ecosystem. Yet, the fate and toxic effects of pharmaceuticals on these nontarget aquatic invertebrates and the underlying mechanisms are poorly studied. Herein, we investigated the toxicokinetic (TK) processes (i.e., uptake, biotransformation, and elimination) of the pharmaceutical diclofenac and its biotransformation in the freshwater invertebrate Hyalella azteca. We further employed mass spectrometry-based metabolomics to assess the toxic effects of diclofenac on the metabolic functions of H. azteca exposed to environmentally relevant concentrations (10 and 100 μg/L). The TK results showed a quick uptake of diclofenac by H. azteca (maximum internal concentration of 1.9 μmol/kg) and rapid formation of the conjugate diclofenac taurine (maximum internal concentration of 80.6 μmol/kg), indicating over 40 times higher accumulation of diclofenac taurine than that of diclofenac in H. azteca. Depuration kinetics demonstrated that the elimination of diclofenac taurine was 64 times slower than diclofenac in H. azteca. Metabolomics results suggested that diclofenac inhibited prostaglandin synthesis and affected the carnitine shuttle pathway at environmentally relevant concentrations. These findings shed light on the significance of the TK process of diclofenac, especially the formation of diclofenac taurine, as well as the sublethal effects of diclofenac on the bulk metabolome of H. azteca. Combining the TK processes and metabolomics provides complementary insights and thus a better mechanistic understanding of the effects of diclofenac in aquatic invertebrates.

Quantification of Active Ingredient Losses from Formulating Pharmaceutical Industries and Contribution to Wastewater Treatment Plant Emissions

In this work, emissions of active pharmaceutical ingredients (APIs) from formulating pharmaceutical industries (FPIs) were investigated for the first time based on detailed production information and compared to overall API emissions in wastewater treatment plant (WWTP) effluents. At two municipal WWTPs, both receiving wastewater from several FPIs, two months' daily effluent samples were collected and measured using liquid chromatography high-resolution mass spectrometry (LC-HRMS). Thirty-three APIs formulated during the sampling period as well as >120 organic contaminants commonly present in WWTP effluents were quantified. On the basis of their time patterns and manufacturing data, industrial contributions were found for 22 of 26 APIs (85%) detected in the samples and processed by the FPIs. API emissions from FPIs led to daily concentration increases of up to 300-fold, despite pretreatment of the industrial wastewater. However, emissions from FPIs seemed to depend on the type of formulating activity, with granulation and mixing being most prone to API losses. Losses from FPIs were responsible for the highest concentrations and for up to 60% of the daily total API emissions measured. Furthermore, screening for suspects in LC-HRMS data resulted in the detection of unexpected emissions from FPIs, demonstrating the value of these data to comprehensively assess industrial API losses. Overall, this study showed that FPIs were relevant contributors of APIs emitted in the WWTP effluents, although only a minor fraction (<1%) of the total processed API quantity was lost to the wastewater, and despite the small percentage (<5%) of FPI wastewater compared to the total wastewater flow.

Evaluation of Nontarget Long-Term LC-HRMS Time Series Data Using Multivariate Statistical Approaches

The use of liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) has steadily increased in many application fields ranging from metabolomics to environmental science. HRMS data are frequently used for nontarget screening (NTS), i.e., the search for compounds that are not previously known and where no reference substances are available. However, the large quantity of data produced by NTS analytical workflows makes data interpretation and time-dependent monitoring of samples very sophisticated and necessitates exploiting chemometric data processing techniques. Consequently, in this study, a prioritization method to handle time series in nontarget data was established. As proof of concept, industrial wastewater was investigated. As routine industrial wastewater analyses monitor the occurrence of a limited number of targeted water contaminants, NTS provides the opportunity to detect also unknown trace organic compounds (TrOCs) that are not in the focus of routine target analysis. The developed prioritization method enables reducing raw data and including identification of prioritized unknown contaminants. To that end, a five-month time series for industrial wastewaters was utilized, analyzed by liquid chromatography-time-of-flight mass spectrometry (LC-qTOF-MS), and evaluated by NTS. Following peak detection, alignment, grouping, and blank subtraction, 3303 features were obtained of wastewater treatment plant (WWTP) influent samples. Subsequently, two complementary ways for exploratory time trend detection and feature prioritization are proposed. Therefore, following a prefiltering step, featurewise principal component analysis (PCA) and groupwise PCA (GPCA) of the matrix (temporal wise) were used to annotate trends of relevant wastewater contaminants. With sparse factorization of data matrices using GPCA, groups of correlated features/mass fragments or adducts were detected, recovered, and prioritized. Similarities and differences in the chemical composition of wastewater samples were observed over time to reveal hidden factors accounting for the structure of the data. The detected features were reduced to 130 relevant time trends related to TrOCs for identification. Exemplarily, as proof of concept, one nontarget pollutant was identified as N-methylpyrrolidone. The developed chemometric strategies of this study are not only suitable for industrial wastewater but also could be efficiently employed for time trend exploration in other scientific fields.

Developing Unique Nontarget High-Resolution Mass Spectrometry Signatures to Track Contaminant Sources in Urban Waters

Diffuse pollution in urban receiving waters often adversely impacts both humans and ecosystems. Identifying such pollution sources is challenging and limits the effectiveness of management actions intended to reduce risk. Here, we evaluated the use of nontarget analysis via high-resolution mass spectrometry (HRMS) to develop chemical fingerprints/signatures for source tracking. Specifically, we applied nontarget HRMS to characterize and differentiate two urban chemical sources: roadway runoff and wastewater influent. We isolated 112 and 598 nontarget compounds (both known and unidentified chemicals) that co-occurred in all roadway runoff and wastewater influent samples, respectively, and were unique relative to other sampled sources. For example, methamphetamine, often considered wastewater derived, was detected in all samples, implying that individual wastewater indicators may lack sufficient specificity in urban receiving waters impacted by multiple sources. Hierarchical cluster analysis differentiated source types, and normalized abundance profiling prioritized nontarget compounds with consistent relative abundance patterns across field sites for a given source. Hexa(methoxymethyl)melamine, 1,3-diphenylguanidine, and polyethylene glycols co-occurred in roadway runoff across geographic areas and traffic intensities, supporting continued development of a universal roadway runoff fingerprint based on ubiquitous compounds. This study provides a proof-of-concept for isolating nontarget source fingerprints to track diffuse contamination in urban receiving waters.