Organic Micropollutants in New York Lakes: A Statewide Citizen Science Occurrence Study

Response and roles of algal organic matter under copper stress: Spectral and mass spectrometry analysis

Eutrophication leads to various environmental issues, including pollution caused by the production of algal organic matter (AOM). Algae typically respond to environmental changes (e.g., light, temperature, copper [Cu(II)] concentration and pH) by regulating the production and release of different substances, thereby causing unpredictable effects on water quality. We explored the characteristics of AOM and the response mechanisms of algae under Cu(II) stress in the study, using fluorescence spectrum and high-resolution mass spectrometry (HRMS) analysis. The growth of Microcystis aeruginosa was inhibited under Cu(II) stress which was irreversible at Cu(II) concentration ≥ 2 μmol/L. Tryptophan- and humic-like fluorophores were important constituents of extracellular organic matter (EOM), and their contents increased with the addition of Cu(II), indicating that Cu(II) stimulates the production of tryptophan- and humic-like compounds. In addition, fulvic acid-like compounds in EOM were the main components binding to Cu(II) and were overproduced by algae under Cu(II) stress. It was found by HRMS at the molecular level that the formula numbers of EOM generally increased over inhibition time. Under 1 μmol/L Cu(II) stress, nitrogenous compounds (CHON formulae) were the primary AOM, accounting for 37.3-52.0 %. In addition, algae release a large amount of condensed aromatic structures to balance Cu(II) stress. This study provides a molecular-level analysis to explain the variation trends and response mechanisms of algae under various Cu(II) concentrations. The research methods are helpful for utilizing multiple advanced analysis methods to study algae growth and AOM release.

Identifying Organic Chemicals with Acetylcholinesterase Inhibition in Nationwide Estuarine Waters by Machine Learning-Assisted Mass Spectrometric Screening

Neurotoxicity is frequently observed in the global aquatic environment, threatening aquatic ecosystems and human health. However, a very limited proportion of neurotoxic effects (∼1%) has been explained by known chemicals of concern. Here, we integrated machine learning, nontargeted analysis, and in vitro biotesting to identify neurotoxic drivers of acetylcholinesterase (AChE) inhibition in estuarine waters along the coast of China. Machine learning was used to predict AChE inhibitors in a large chemical space. The prediction output was profiled into a suspect screening list to guide high-resolution mass spectrometry (HRMS) screening of AChE inhibitors in estuarine water samples. Ultimately, 60 chemicals with diverse known and presently unknown structures were identified, explaining 82.1% of the observed AChE inhibition. Polyunsaturated fatty acids were unexpectedly found to be neurotoxic drivers, accounting for 80.5% of the overall effect. This proof-of-concept study demonstrates that machine learning-based toxicological prediction can achieve a virtual fractionation role to pinpoint HRMS features with the bioactivity potential. Our approach is expected to enable rapid and comprehensive screening of organic pollutants associated with various in vitro end points for large-scale monitoring of water quality.

Characteristics of organic matter driven by Eichhornia crassipes during co-contamination with per(poly)fluoroalkyl substances (PFASs) and microplastics (MPs)

Co-contamination with MPs and PFASs has been recorded, particularly in surface-water environments. Floating macrophyte microcosms are an important part of the surface water ecosystem, and dissolved organic matter (DOM) driven by floating macrophytes (FMDDOM) is critical for maintaining material circulation. However, knowledge gaps remain regarding the impact of MPs and PFASs co-pollution on FMDDOM. An greenhouse simulation experiment was conducted in this study to investigate the effects of four PFASs, perfluorooctanoic acid (PFOA), perfluoro-octane-sulfonic acid (PFOS), perfluoro-2-methyl-3-oxahexanoic acid (Gen X), and potassium 9-chlorohexadecafluoro-3-oxanonane-1-sulfonate (F-53B), on FMDDOM sourced from Eichhornia crassipes (E. crassipes), a typical floating macrophyte, in the presence and absence of polystyrene (PS) MPs. Four PFASs increased FMDDOM release from E. crassipes, leading to a 32.52-77.49 % increase in dissolved organic carbon (DOC) levels. PS MPs further increased this, with results ranging from -21.28 % to 26.49 %. Based on the parallel factor analysis (PARAFAC), FMDDOM was classified into three types of fluorescent components: tryptophan-like, humic-like, and tyrosine-like compounds. Contaminants of MPs and PFASs modified the relative abundance of these three components. Protein secondary structure analysis showed that fluorocarbon bonds tended to accumulate on the α-helix of proteins in FMDDOM. The relative abundance of fluorescent and chromophorous FMDDOMs varied from 0.648 ± 0.044 to 0.964 ± 0.173, indicating that the photochemical structures of the FMDDOM were modified. FMDDOM exhibits decreased humification and increased aromaticity when contaminated with MPs and PFASs, which may be detrimental to the geochemical cycling of carbon. This study offers a theoretical basis for assessing the combined ecological risks of MPs and PFASs in floating macrophyte ecosystems.

Occurrence of contaminants of emerging concern in surface and waste water from the Yangtze River chemical contiguous zone, China: Distribution, sources and ecological risk assessment

Limited knowledge exists regarding the occurrence, potential sources, and risks of contaminants of emerging concern (CECs) in surface and waste water from chemical contiguous zones. A total of 136 CECs were detected at 32 sampling sites along the Yangtze River, with concentrations ranging from 0.55 to 4.21 × 104 ng/L. Hydrocortisonacetate, cortisone, prednisone, enalapril and medroxyprogesterone were detected across all sampling sites. Hierarchical cluster analysis based on 47 core CECs yielded similar results compared with principal components analysis and identified two major clusters: wastewater sites and surface water sites. Distinct patterns of CECs were observed in wastewater from three industrial parks owing to variations in the industrial facilities and products within each park. Nineteen CECs were initially classified as presenting a high or medium risk to aquatic organisms. Further quantitative probabilistic risk assessment revealed that caffeine, trenbolone and norethindrone posed a threat to the most vulnerable aquatic species while high-risk sites mainly occurred downstream of the chemical industrial park. The joint ecological risk of high-risk CECs was evaluated using potentially affected fractions, which ranged from 0.44 % to 47.9 % with concentration addition and 0.33 % to 45.1 % with response addition. This suggests the need to consider the joint ecological risk of the detected compounds in future studies.

Insight into spatial variations of DOM fractions and its interactions with microbial communities of shallow groundwater in a mesoscale lowland river watershed

Dissolved organic matter (DOM) plays a crucial role in driving biogeochemical processes and determining water quality in shallow groundwater systems, where DOM could be susceptible to dynamic influences of surface water influx. This study employed fluorescence excitation-emission matrix (EEM) spectroscopy combined with principal component coefficients, parallel factor analysis (PARAFAC), co-occurrence network analysis and structural equation modeling (SEM) to examine changes of DOM fractions from surface water to shallow groundwater in a mesoscale lowland river basin. Combining stable isotope and hydrochemical parameters, except for surface water (SW), two groups of groundwater samples were defined, namely, deeply influenced by surface water (IGW) and groundwater nearly non-influenced by surface water (UGW), which were 50.34 % and 19.39 % recharged by surface water, respectively. According to principal component coefficients, reassembled EEM data of these categories highlighted variations of the tyrosine-like peak in DOM. EEMs coupled with PARAFAC extracted five components (C1-C5), i.e. C1, protein-like substances, C2 and C4, humic-like substances, and C3 and C5, microbial-related substances. The abundance of the protein-like was SW > IGW > UGW, while the order of the humic-like was opposite. The bacterial communities exhibited an obvious cluster across three regions, which hinted their sensitivity to variations in environmental conditions. Based on co-occurrence, SW represented the highest connectivity between bacterial OTUs and DOM fractions, followed by IGW and UGW. SEM revealed that microbial activities increased bioavailability of the humic-like in the SW and IGW, whereas microbial compositions promoted the evolution of humic-like substances in the UGW. Generally, these results could be conducive to discern dissimilarity in DOM fractions across surface water and shallow groundwater, and further trace their interactions in the river watershed.

Characterizing the Impact of Cyanobacterial Blooms on the Photoreactivity of Surface Waters from New York Lakes: A Combined Statewide Survey and Laboratory Investigation

Cyanobacterial blooms introduce autochthonous dissolved organic matter (DOM) into aquatic environments, but their impact on surface water photoreactivity has not been investigated through collaborative field sampling with comparative laboratory assessments. In this work, we quantified the apparent quantum yields (Φapp,RI) of reactive intermediates (RIs), including excited triplet states of dissolved organic matter (3DOM*), singlet oxygen (1O2), and hydroxyl radicals (•OH), for whole water samples collected by citizen volunteers from more than 100 New York lakes. Multiple comparisons tests and orthogonal partial least-squares analysis identified the level of cyanobacterial chlorophyll a as a key factor in explaining the enhanced photoreactivity of whole water samples sourced from bloom-impacted lakes. Laboratory recultivation of bloom samples in bloom-free lake water demonstrated that apparent increases in Φapp,RI during cyanobacterial growth were likely driven by the production of photoreactive moieties through the heterotrophic transformation of freshly produced labile bloom exudates. Cyanobacterial proliferation also altered the energy distribution of 3DOM* and contributed to the accelerated transformation of protriptyline, a model organic micropollutant susceptible to photosensitized reactions, under simulated sunlight conditions. Overall, our study provides insights into the relationship between the photoreactivity of surface waters and the limnological characteristics and trophic state of lakes and highlights the relevance of cyanobacterial abundance in predicting the photoreactivity of bloom-impacted surface waters.

Ultrasonic treatment of dye chemicals in wastewater: A review

The existence of pollutants, such as toxic organic dye chemicals, in water and wastewater raises concerns as they are inadequately eliminated through conventional water and wastewater treatment methods, including physicochemical and biological processes. Ultrasonic treatment has emerged as an advanced treatment process that has been widely applied to the decomposition of recalcitrant organic contaminants. Ultrasonic treatment has several advantages, including easy operation, sustainability, non-secondary pollutant production, and saving energy. This review examines the elimination of dye chemicals and categorizes them into cationic and anionic dyes based on the existing literature. The objectives include (i) analyzing the primary factors (water quality and ultrasonic conditions) that influence the sonodegradation of dye chemicals and their byproducts during ultrasonication, (ii) assessing the impact of the different sonocatalysts and combined systems (with ozone and ultraviolet) on sonodegradation, and (iii) exploring the characteristics-based removal mechanisms of dyes. In addition, this review proposes areas for future research on ultrasonic treatment of dye chemicals in water and wastewater.

Pharmaceuticals and Personal Care Products in the Aquatic Environment: How Can Regions at Risk be Identified in the Future?

Pharmaceuticals and personal care products (PPCPs) are an indispensable component of a healthy society. However, they are well-established environmental contaminants, and many can elicit biological disruption in exposed organisms. It is now a decade since the landmark review covering the top 20 questions on PPCPs in the environment (Boxall et al., 2012). In the present study we discuss key research priorities for the next 10 years with a focus on how regions where PPCPs pose the greatest risk to environmental and human health, either now or in the future, can be identified. Specifically, we discuss why this problem is of importance and review our current understanding of PPCPs in the aquatic environment. Foci include PPCP occurrence and what drives their environmental emission as well as our ability to both quantify and model their distribution. We highlight critical areas for future research including the involvement of citizen science for environmental monitoring and using modeling techniques to bridge the gap between research capacity and needs. Because prioritization of regions in need of environmental monitoring is needed to assess future/current risks, we also propose four criteria with which this may be achieved. By applying these criteria to available monitoring data, we narrow the focus on where monitoring efforts for PPCPs are most urgent. Specifically, we highlight 19 cities across Africa, Central America, the Caribbean, and Asia as priorities for future environmental monitoring and risk characterization and define four priority research questions for the next 10 years. Environ Toxicol Chem 2024;43:575-588. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Laboratory measurements underestimate persistence of the aquatic herbicide fluridone in lakes

Fluridone is an aquatic herbicide commonly used to treat invasive freshwater plant species such as Eurasian watermilfoil, hydrilla, and curly-leaf pondweed. However, required exposures times are very long and often exceed 100 days. Thus, understanding the mechanisms that determine the fate of fluridone in lakes is critical for supporting effective herbicide treatments and minimizing impacts to non-target species. We use a combination of laboratory and field studies to quantify fluridone photodegradation, as well as sorption and microbial degradation in water and sediment microcosms. Laboratory irradiation studies demonstrate that fluridone is susceptible to direct photodegradation with negligible indirect photodegradation, with predicted half-lives in sunlight ranging from 2.3 days (1 cm path length) to 118 days (integrated over 1 meter). Biodegradation is attributable to microbes in sediment with an observed half-life of 57 days. Lastly, fluridone sorbs to sediments (Koc = 340 ± 28 L kg-1); sorption accounts for 16% of fluridone loss in the microcosm experiments. While the laboratory results indicate that all three loss pathways can influence fluridone fate, these controlled studies oversimplify herbicide behavior due to their inability to replicate field conditions. Fluridone concentration measurements in a lake following commercial application demonstrate a half-life of >150 days, indicating that the herbicide is very persistent in water. This study illustrates why caution should be used when relying on laboratory studies to predict the fate of pesticides and other polar organic compounds in the environment.

Enhancing the transformation of carbon and nitrogen organics to humus in composting: Biotic and abiotic synergy mediated by mineral material

To investigate the conversion of carbon and nitrogen organic matter to humus mediated by mineral material additives through biotic and abiotic pathways, three chicken manure composting experiments were conducted using calcium superphosphate (CS) and fly ash (FA). Results showed that CS and FA promoted carbon and nitrogen organic degradation and improved compost maturity. The ratio of humic acid-like to fulvic acid-like substances for FA (30) was significantly higher than for control (18) and CS (13). Excitation-emission-matrix spectra and parallel factor analysis identified a higher transformation of protein-like components into humic-like components in FA. Network analysis showed that CS improved compost maturity by promoting the rapid conversion of humus precursors to humus, while FA increased the richness and diversity of the microbial community, such as Chloroflexi, the unique phylum in FA. Overall, CS and FA facilitated the humification process through abiotic and biotic pathways, and FA had better humification performance.

Anthropogenic original DOM is a critical factor affecting LNA bacterial community assembly

We investigated the geographical and environmental distance-decay relationships for both of the two bacteria in the Haihe River, Tianjin, China. HNA bacteria exhibited a stronger geographical variation-dependent pattern while LNA bacteria exhibited a stronger environmental variation-dependent pattern. Variance partition analysis (VPA), Mantel test, and partial mantel test validated the discrepant impacts of geographical distance and environmental factors on their two communities. The heterogeneous selection dominated community assembly of LNA bacteria demonstrates their greater sensitivity to environmental conditions. As the deterministic environmental factor, anthropogenic original dissolved organic matter (DOM) functions exclusively on LNA bacteria, and it is the critical factor leading to the discrepant biogeographical patterns of LNA and HNA bacteria. LNA bacteria interact with HNA bacteria and mediate the DOM driving total bacteria assembly. The LNA keystone taxa, Pseudomonas, Rheinheimera, Candidatus Aquiluna, and hgcl clade are capable to compete with HNA bacteria for anthropogenic original DOM, and are potential indicators of anthropogenic pollution. Our research reveals the non-negligible effect of the LNA bacteria in regulating the ecological response of total bacteria.

Reactions of neonicotinoids with peroxydisulfate: The generation of neonicotinoid anion radicals and activation pathway to form sulfate radicals

To activate persulfate to generate reactive species such as sulfate radical (SO₄^•-) for micropollutants abatement, external energy or chemicals are often needed. In this study, a novel SO₄^•- formation pathway was reported during the oxidation of neonicotinoids by peroxydisulfate (S₂O₈^2-, PDS) without any other chemical additions. Thiamethoxam (TMX) was used as a representative neonicotinoid and SO₄^•- was the dominant specie contributing to its degradation during PDS oxidation at neutral pH. TMX anion radical (TMX^•-) was found to activate PDS to generate SO₄^•- with the second-order reaction rate constant determined to be (1.44 ± 0.47)× 10⁶ M^-1s^-1 at pH 7.0 by using laser flash photolysis. TMX^•- was generated from the TMX reactions with superoxide radical (O₂^•-), which was formed from the hydrolysis of PDS. This indirect PDS activation pathway via anion radicals was also applicable to other neonicotinoids. The formation rates of SO₄^•- were found to negatively linearly correlated with E_gap (LUMO-HOMO). The DFT calculations indicated the energy barrier of anion radicals to activate PDS was greatly reduced compared to the parent neonicotinoids. The pathway of anion radicals' activation of PDS to form SO₄^•- improved the understanding of PDS oxidation chemistry and provided some guidance to enhance oxidation efficiency in field applications.

Characterization of micropollutants in urban stormwater using high-resolution monitoring and machine learning

Urban rainfall events can lead to the runoff of pollutants, including industrial, pesticide, and pharmaceutical chemicals. Transporting micropollutants (MPs) into water systems can harm both human health and aquatic species. Therefore, it is necessary to investigate the dynamics of MPs during rainfall events. However, few studies have examined MPs during rainfall events due to the high analytical expenses and extensive spatiotemporal variability. Few studies have investigated the occurrence patterns of MPs and factors that influence their transport, such as rainfall duration, antecedent dry periods, and variations in streamflow. Moreover, while there have been many analyses of nutrients, suspended solids, and heavy metals during the first flush effect (FFE), studies on the transport of MPs during FFE are insufficient. This study aimed to identify the dynamics of MPs and FFE in an urban catchment, using high-resolution monitoring and machine learning methods. Hierarchical clustering analysis and partial least squares regression (PLSR) were implemented to estimate the similarity between each MP and identify the factors influencing their transport during rainfall events. Eleven dominant MPs comprised 75% of the total MP concentration and had a 100% detection frequency. During rainfall events, pesticides and pharmaceutical MPs showed a higher FFE than industrial MPs. Moreover, the initial 30% of the runoff volume contained 78.0% of pesticide and 50.1% of pharmaceutical substances for events W1 (July 5 to July 6, 2021) and W6 (August 31 to September 1, 2021), respectively. The PLSR model suggested that stormflow (m³/s) and the duration of antecedent dry hours (h) significantly influenced MP dynamics, yielding the variable importance on projection scores greater than 1.0. Hence, our findings indicate that MPs in urban waters should be managed by considering FFE.

Malodorous volatile organic compounds (MVOCs) formation after dewatering of wastewater sludge: Correlation with the extracellular polymeric substances (EPS) and microbial communities

Malodorous volatile organic compounds (MVOCs) are often the key odorants in determining sludge odor character and odor impact. However, the emission characterization and generation mechanisms of MVOCs from various dewatered sludge have not been sufficiently understood partly due to the diverse and complex composition and low concentration of odorants. In this study, waste activated sludge (WAS) was collected to examine the variation of MVOC emission from sludge after different dewatering treatment in lab-scale trials. The MVOCs were measured using the electronic nose (eNose), headspace gas chromatography-coupled ion mobility spectrometry (HS-GC-IMS), and headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS). The results showed that centrifugation treatment promoted the generation of various odorous volatiles. The identified key odorants included dimethyl sulfide (DMS), dimethyl disulfide (DMDS), dimethyl trisulfide (DMTS), geosmin, and p-cresol according to their odor activity values (OAVs). The effects of the enhanced dewatering on volatile production were greater than thickening, however, the key odorants of dewatered sludge using gravity thickening varied more greatly than sludges from centrifuge thickening. The distribution of extracellular polymeric substances (EPS) and variation of microbial community showed correlations with the production of key odorants. Tryptophan-like substances in the inner layer of EPS (LB-EPS and TB-EPS) were better correlated with the key odorants. The bound EPS released by centrifugation may play the role of precursor for odorous microbial volatiles. According to the predicted functions of differential microbial genera, Desulfobulbus (Desulfobacterota), Gordonia (Actinobacteriota), and Hyphomicrobium (Proteobacteria) were associated with the production of DMS, DMDS, and DMTS, while Gordonia and Hyphomicrobium were related to p-cresol production.

Combining Passive Sampling with Suspect and Nontarget Screening to Characterize Organic Micropollutants in Streams Draining Mixed-Use Watersheds

Organic micropollutants (OMPs) represent an anthropogenic stressor on stream ecosystems. In this work, we combined passive sampling with suspect and nontarget screening enabled by liquid chromatography-high-resolution mass spectrometry to characterize complex mixtures of OMPs in streams draining mixed-use watersheds. Suspect screening identified 122 unique OMPs for target quantification in polar organic chemical integrative samplers (POCIS) and grab samples collected from 20 stream sites in upstate New York over two sampling seasons. Hierarchical clustering established the co-occurrence profiles of OMPs in connection with watershed attributes indicative of anthropogenic influences. Nontarget screening leveraging the time-integrative nature of POCIS and the cross-site variability in watershed attributes prioritized and confirmed 11 additional compounds that were ubiquitously present in monitored streams. Field sampling rates for 37 OMPs that simultaneously occurred in POCIS and grab samples spanned the range of 0.02 to 0.22 L/d with a median value of 0.07 L/d. Comparative analyses of the daily average loads, cumulative exposure-activity ratios, and multi-substance potentially affected fractions supported the feasibility of complementing grab sampling with POCIS for OMP load estimation and screening-level risk assessments. Overall, this work demonstrated a multi-watershed sampling and screening approach that can be adapted to assess OMP contamination in streams across landscapes.

Applying EEM-PARAFAC combined with moving-window 2DCOS and structural equation modeling to characterize binding properties of Cu (II) with DOM from different sources in an urbanized river

Dissolved organic matter (DOM) in aquatic environment distinctly affects the behavior and fate of heavy metals via complexation, while the interfacial mechanisms and processes are still lacking in detail. Here, Cu (II) binding characteristics of DOM originated from hilly (NDOM), rural (RDOM) and urban (UDOM) regions in an urbanized river was explored by fluorescence excitation-emission matrix spectroscopy (EEM) combined with principal component coefficients, parallel factor analyses (PARAFAC), moving-window two-dimensional correlation spectroscopy (MW2DCOS) and structural equation modeling (SEM). Eight components were extracted from the titrants through EEM-PARAFAC, i.e., phenol-like substance (C1), tyrosine-like substance (C2), visible tryptophan-like substance (C3), ultraviolet tryptophan-like substance (C4), recent biological production (C5), wastewater-derived organic matter (C6), microbial humic-like substance (C7) and fulvic-like substance (C8). Interestingly, NDOM only contained C1, C3, C5 and C8, while nearly all components were found in RDOM (except for C2) and UDOM (except for C4). The f value of C1 (1.239) in NDOM was much higher than those in RDOM (0.134) and UDOM (0.115), so was of C8. It indicated that phenol-like and fulvic-like derived from autochthonous sources exhibited great binding ratios in the complexation with Cu (II). Moreover, C3 and C5 from UDOM exhibited higher f values (0.591 and 1.983) than those from NDOM and RDOM, suggesting that Cu (II) has a great binding capacity on protein-like from domestic and industrial wastewater. The MW2DCOS revealed that phenol-like and protein-like in NDOM and RDOM were essential for the binding of 160 μmol L^-1 Cu (II), whereas fulvic-like in NDOM and UDOM could react significantly with 10 μmol L^-1 Cu (II). Based on SEM, Cu (II) concentration had a negative direct effect on the fluorescence intensity of C7 or C8, whereas it showed an indirect positive effect on C7 or C8 through influencing C5, so was C6. It suggested that Cu (II) showed an indirect positive effect on the C8. This study might present a further comprehend of the environmental behaviors of Cu (II) in rivers.

Modeling micropollutant removal by nanofiltration and reverse osmosis membranes: considerations and challenges

Organic micropollutants (OMPs) in drinking water constitute a potential risk to human health; therefore, effective removal of these pollutants is required. Nanofiltration (NF) and reverse osmosis (RO) are promising membrane-based technologies to remove OMPs. In NF and RO, the rejection of OMPs depends on the properties and characteristics of the membrane, the solute, and the solution. In this review, we discuss how these properties can be included in models to study and predict the rejection of OMPs. Initially, an OMP classification is proposed to capture the relevant properties of 58 OMPs. Following the methodology described in this study, more and new OMPs can be easily included in this classification. The classification aims to increase the comprehension and mechanistic understanding of OMP removal. Based on the physicochemical principles used to classify the 58 OMPs, it is expected that other OMPs in the same groups will be similarly rejected. From this classification, we present an overview of the rejection mechanisms involved in the removal of specific OMP groups. For instance, we discuss the removal of OMPs classified as perfluoroalkyl substances (e.g., perfluorooctanoic acid, PFOA). These substances are highly relevant due to their human toxicity at extremely low concentration as well as their persistence and omnipresence in the environment. Finally, we discuss how the rejection of OMPs can be predicted by describing both the membrane-solution interface and calculating the transport of solutes inside the membrane. We illustrate the importance and impact of different rejection mechanisms and interfacial phenomena on OMP removal and propose an extended Nernst-Plank equation to calculate the transport of solutes across the membrane due to convection, diffusion, and electromigration. Finally, we show how the theory discussed in this review leads to improved predictions of OMP rejection by the membranes.

Suspect screening to support source identification and risk assessment of organic micropollutants in the aquatic environment of a Sub-Saharan African urban center

Organic micropollutants (OMPs) are contaminants of global concern and have garnered increasing attention in Africa, particularly in urban and urbanizing areas of Sub-Saharan Africa (SSA). In this work, we coupled suspect screening enabled by liquid chromatography-high-resolution mass spectrometry (LC-HRMS) with multivariate analysis to characterize OMPs in wastewater, surface water, and groundwater samples collected from Kampala, the capital and largest city of Uganda. Suspect screening prioritized and confirmed 157 OMPs in Kampala samples for target quantification. Many OMPs detected in Kampala samples occurred within concentration ranges similar to those documented in previous studies reporting OMP occurrence in SSA, but some have never or rarely been quantified in environmental water samples from SSA. Hierarchical cluster analysis established the source-related co-occurrence profiles of OMPs. Partial least squares regression and multiple linear regression analyses further pinpointed the concentration of nitrate and the content of a fluorescent organic matter component with excitation/emission maxima around 280/330 nm as predictors for the sample-specific cumulative concentrations of OMPs, suggesting the likely contribution of diffuse runoff and wastewater discharges to OMP occurrence in the aquatic environment of Kampala. Parallel calculations of exposure-activity ratios and multi-substance potentially affected fractions provided insights into the potential for biological effects associated with OMPs and highlighted the importance of expanded analytical coverage for screening-level risk assessments. Overall, our study demonstrates a versatile database-driven screening and data analysis methodology for the multipronged characterization of OMP contamination in a representative SSA urban center.

Evidence of low levels of trace organic contaminants in terminal lakes

Endorheic lakes (or terminal lakes, TLs) have no natural outlet other than evaporation and slow infiltration. Some TLs receive reclaimed wastewater which contains poorly removed trace organic contaminants (TrOCs). To determine if TLs accumulate TrOCs we conducted a preliminary assessment of the occurrence of ten TrOCs in three TLs receiving reclaimed wastewater and one TL which does not directly receive reclaimed wastewater. Five of ten TrOCs (carbamazepine, DEET, fluoxetine, primidone, and trimethoprim) were present in all four TLs' surface waters (~0.3-1109 ng/L), six (caffeine, carbamazepine, DEET, diphenhydramine, primidone, and trimethoprim) were present in sediment samples (0.1-77 ng/gDW) and in soil samples (0.1-137 ng/gDW). Concentrations of caffeine, carbamazepine, diphenhydramine, fluoxetine and meprobamate were significantly higher in TLs receiving wastewater from a secondary treatment plant compared to those TLs which received tertiary treated wastewater. Carbamazepine, fluoxetine, sulfamethoxazole, and trimethoprim were present at concentrations greater than is typical of other U.S. freshwater lakes, but other TrOC concentrations were present at lower concentrations than in other freshwater lakes. We conclude that some TrOCs may accumulate in TLs, but to a lesser extent than would be expected based on the accumulation of dissolved constituents alone, which indicates that there are other unidentified processes in TLs that contribute to TrOC losses. Other TLs across the globe may have similar levels of TrOCs due to anthropogenic influence and treated wastewater inputs.

Coupling Suspect and Nontarget Screening with Mass Balance Modeling to Characterize Organic Micropollutants in the Onondaga Lake-Three Rivers System

Characterizing the occurrence, sources, and fate of organic micropollutants (OMPs) in lake-river systems serves as an important foundation for constraining the potential impacts of OMPs on the ecosystem functions of these critical landscape features. In this work, we combined suspect and nontarget screening with mass balance modeling to investigate OMP contamination in the Onondaga Lake-Three Rivers system of New York. Suspect and nontarget screening enabled by liquid chromatography-high-resolution mass spectrometry led to the confirmation and quantification of 105 OMPs in water samples collected throughout the lake-river system, which were grouped by their concentration patterns into wastewater-derived and mixed-source clusters via hierarchical cluster analysis. Four of these OMPs (i.e., galaxolidone, diphenylphosphinic acid, N-butylbenzenesulfonamide, and triisopropanolamine) were prioritized and identified by nontarget screening based on their characteristic vertical distribution patterns during thermal stratification in Onondaga Lake. Mass balance modeling performed using the concentration and discharge data highlighted the export of OMPs from Onondaga Lake to the Three Rivers as a major contributor to the OMP budget in this lake-river system. Overall, this work demonstrated the utility of an integrated screening and modeling framework that can be adapted for OMP characterization, fate assessment, and load apportionment in similar surface water systems.

High-throughput wastewater analysis for substance use assessment in central New York during the COVID-19 pandemic

Wastewater entering sewer networks represents a unique source of pooled epidemiological information. In this study, we coupled online solid-phase extraction with liquid chromatography-high resolution mass spectrometry to achieve high-throughput analysis of health and lifestyle-related substances in untreated municipal wastewater during the coronavirus disease 2019 (COVID-19) pandemic. Twenty-six substances were identified and quantified in influent samples collected from six wastewater treatment plants during the COVID-19 pandemic in central New York. Over a 12 week sampling period, the mean summed consumption rate of six major substance groups (i.e., antidepressants, antiepileptics, antihistamines, antihypertensives, synthetic opioids, and central nervous system stimulants) correlated with disparities in household income, marital status, and age of the contributing populations as well as the detection frequency of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater and the COVID-19 test positivity in the studied sewersheds. Nontarget screening revealed the covariation of piperine, a nontarget substance, with SARS-CoV-2 RNA in wastewater collected from one of the sewersheds. Overall, this proof-of-the-concept study demonstrated the utility of high-throughput wastewater analysis for assessing the population-level substance use patterns during a public health crisis such as COVID-19.