An assessment and characterization of pharmaceuticals and personal care products (PPCPs) within the Great Lakes Basin: Mussel Watch Program (2013–2018)

M. A., Edwards; K., Kimbrough; N., Fuller; E., Davenport; M., Rider; A., Freitag; S., Regan; A, Leight; K.; H., Burkart; A., Jacob; E., Johnson

doi:10.1007/s10661-023-12119-3

An assessment and characterization of pharmaceuticals and personal care products (PPCPs) within the Great Lakes Basin: Mussel Watch Program (2013–2018)

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Published: 05 March 2024

Volume 196, article number 345, (2024)
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An assessment and characterization of pharmaceuticals and personal care products (PPCPs) within the Great Lakes Basin: Mussel Watch Program (2013–2018)

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Edwards M. A.¹,
Kimbrough K.¹,
Fuller N.²,
Davenport E.¹,
Rider M.²,
Freitag A.¹,
Regan S.²,
Leight A,
K.¹,
Burkart H.²,
Jacob A.² &
…
Johnson E.¹

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Abstract

Defining the environmental occurrence and distribution of chemicals of emerging concern (CECs), including pharmaceuticals and personal care products (PPCPs) in coastal aquatic systems, is often difficult and complex. In this study, 70 compounds representing several classes of pharmaceuticals, including antibiotics, anti-inflammatories, insect repellant, antibacterial, antidepressants, chemotherapy drugs, and X-ray contrast media compounds, were found in dreissenid mussel (zebra/quagga; Dreissena spp.) tissue samples. Overall concentration and detection frequencies varied significantly among sampling locations, site land-use categories, and sites sampled proximate and downstream of point source discharge. Verapamil, triclocarban, etoposide, citalopram, diphenhydramine, sertraline, amitriptyline, and DEET (N,N-diethyl-meta-toluamide) comprised the most ubiquitous PPCPs (> 50%) detected in dreissenid mussels. Among those compounds quantified in mussel tissue, sertraline, metformin, methylprednisolone, hydrocortisone, 1,7-dimethylxanthine, theophylline, zidovudine, prednisone, clonidine, 2-hydroxy-ibuprofen, iopamidol, and melphalan were detected at concentrations up to 475 ng/g (wet weight). Antihypertensives, antibiotics, and antidepressants accounted for the majority of the compounds quantified in mussel tissue. The results showed that PPCPs quantified in dreissenid mussels are occurring as complex mixtures, with 4 to 28 compounds detected at one or more sampling locations. The magnitude and composition of PPCPs detected were highest for sites not influenced by either WWTP or CSO discharge (i.e., non-WWTPs), strongly supporting non-point sources as important drivers and pathways for PPCPs detected in this study. As these compounds are detected at inshore and offshore locations, the findings of this study indicate that their persistence and potential risks are largely unknown, thus warranting further assessment and prioritization of these emerging contaminants in the Great Lakes Basin.

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Introduction

Pharmaceuticals and personal care products (PPCPs) comprise a wide suite of prescription and over-the-counter (non-prescription medications) compounds intended for human and veterinary use, including animal production (e.g., livestock production and poultry processing), that are widely detected in aquatic and terrestrial environments (Ebele et al., 2017; Jaffrézic et al., 2017). Pharmaceutical products generally consist of biologically active organic compounds including but not limited to antibiotics, antidepressants, stimulants, X-ray contrast media drugs, anti-inflammatory, lipid regulators, β-blockers, antihypertensive compounds, and illicit/recreational drugs (Richmond et al., 2017; Yang, et al.,

Methods

Study area

The Laurentian Great Lakes constitutes the largest freshwater system in the world, containing an estimated 21% of the Earth’s surface freshwater (~ 90% of US freshwater; Fields, 2005; Sponberg, 2009). The Great Lakes Basin covers a total area of 244,000 km² (94,000 mi²) and is home to over 35 million people (Breffle et al., 2013; Danz et al., 2007). The region watersheds which drain almost 518,000 km² (200,000 mi²) support numerous economic industries, including manufacturing, agriculture, and commercial fisheries, with areas of intense urbanization and industrialization occurring along its coastal zone (Breffle et al., 2013; Wolter et al., 2006). Land-use and land cover differ between eco-regions and eco-provinces, with predominantly forested areas in the northern and southeastern sections, and agricultural activities more pronounced in the western and central sections of the Basin (Morrice et al., 2008). Increased anthropogenic and environmental stressors, including rapid urban growth and municipal and industrial wastewater discharge, have led to increased water quality impairment within the Great Lakes Basin and adjacent sub-watersheds (Danz et al., 2007; Elliot et al., 2017; Kiesling et al., 2022). Specifically, the continuous loading of organic pollutants from point and diffuse/fugitive sources has been identified as an environmental driver behind coastal water quality and ecosystem impairment within the Great Lakes (Baldwin et al., 2016; Cornwell et al., 2015; Kiesling et al., 2019).

Site designation and categorization

A total of 131 sites, representing inshore and offshore locations in the Great Lakes Basin, were sampled between 2013 and 2018 (Fig. 1). A detailed description of the Great Lakes MWP study site locations including designated reference sites is provided in Table S1 (Supplementary Information) and described elsewhere (Edwards et al., 2016; Kimbrough et al., 2018, 2021). Additional information on MWP sampling locations is also provided in Table S10. Collectively, 14 sites were sampled in 2013, 29 sites were sampled in 2014, 15 sites were sampled in 2015, 12 sites were sampled in 2016, 19 sites were sampled in 2017, and 42 sites were sampled in 2018. Overall, CEC data from dreissenid mussel tissue were generated from multiple contamination assessment studies conducted under the expanded Great Lakes MWP basin-wide contaminant monitoring objectives. These objectives included addressing the Great Lakes Restoration Initiative (GLRI) Action Plan I (2010–2014) and GLRI Action Plan II (2015–2019; Kimbrough et al., 2018). To increase the likelihood of finding PPCPs, sites were preferentially selected based on the following: (1) riverine systems and tributaries known for higher contamination based on previous MWP studies, and (2) pollution gradients influenced by urban and sub-urban centers that receive high volume of pollutants from point source discharge and urban/storm-water runoff. MWP sites established in the Great Lakes Areas of Concern (AOC; areas designated for restoration due in part to historical environmental contamination; Hartig et al., 2020) and priority urban areas, including Milwaukee, Niagara, Toledo, Cleveland, and Detroit, were targeted with the objective of providing a more robust measure of bioavailable contaminants that would be generated from municipal, industrial, and fugitive sources, including urban storm water runoff (Kimbrough et al., 2021).

Multiple techniques including monitoring studies and place-based/caged mussel deployment were used to conduct contamination assessments and contaminant source tracking at inshore riverine and nearshore sites (Kimbrough et al., 2021). Mussels sampled at designated offshore locations included all lake sites (nearshore lake and deep-water lake sites), as well as sites sampled in the Great Lakes connecting channels. Inshore sampling locations include sites sampled at harbor, river, embayment, and tributary locations. Overall, most sampling locations have 1–3 sites, except for sampling locations in the Maumee River, Detroit River, Muskegon, Milwaukee Estuary, and Niagara River.

Sampling procedures

Information on MWP sampling procedures is presented elsewhere (Kimbrough et al., 2018, 2021), as sampling methods and procedures were slightly different for various MWP basin-wide contaminant monitoring objectives. Sampling procedures conducted in this study utilized both in situ and caged dreissenid mussels for basin-wide surveillance monitoring and place-based contaminant assessment studies. When available, divers harvested in situ dreissenid mussels from established populations in open lake, near-shore lake zone, or from outer harbor stone breakwaters (Kimbrough et al., 2018). For sampling locations and place-based contaminant assessment sites where in situ mussels were unavailable, mussels were harvested by divers from nearshore harbor and stone breakwaters, placed in cages (e.g., minnow traps; approximately 300–500 mussels per cage), and deployed at selected sites for 28–55 days. For temporal studies, mussels were caged for up to 55 days.

The use of caged mussels in biomonitoring studies is well established. For example, studies have shown that caged mussels can be strategically deployed along known or suspected pollutant gradients to track and measure source contaminant exposure over time (de Solla et al., 2016; Guerlet et al., 2007; James et al., 2020; Salazar & Salazar, 1995). Additional studies have shown that caging mussels for 28–30 days (4 weeks) avoids bias relating to physiological and reproductive status that might influence organic pollutant uptake and bioaccumulation over the period of exposure (Tsangaris et al., 2010; Viarengo et al., 2007). Dreissenid mussels collected from in situ and place-based/caged deployment was rinsed with site water to remove debris, placed in labeled freezer bags, packed in ice containers, and shipped to contract laboratories within 2 days for analysis. Homogenates with more than 100 individuals were used for chemical analysis. Tissue sample collection and processing were consistent with NOAA methods and procedures for bivalve tissue assessment.

Chemical analysis

Mussel tissue samples were analyzed at SGS AXYS Analytical Services (Sidney, British Columbia, Canada). A total of 141 contaminants were analyzed in mussel tissue samples (Table S2). Tissue samples were analyzed using a series of high-performance liquid chromatography reversed phase C18 or HILIC columns, combined with tandem mass spectrometry (HPLC/MS/MS) platform extraction, including gas chromatography coupled with high-resolution mass spectrometry (GC-HRMS) extraction. Individual PPCP analytes measured by positive or negative mode electrospray ionization (+ / − ESI) liquid chromatography tandem mass spectrometry (LC/MS/MS), or electron impact (EI) or electron capture negative chemical ionization (ECNI) mode gas chromatography mass spectrometry (GC/MS), were analyzed from modified methods described in EPA Method 1694 and 1698 (Dodder et al., 2014; U.S. EPA 2007). SGS AXYS quality assurance criteria used for method MLA-075 Rev 06.01 and method MLA-075 Rev 07 included analyses of laboratory blanks, duplicate samples, labeled quantification standard recovery, and blind field sample duplicates.

Quality assurance and quality control

Standard SGS AXYS laboratory quality control measures used for mussel tissue analyses are described elsewhere (James et al., 2020). Briefly, mussel tissue analyses were performed in batches. Each batch consisted of test samples and additional QC samples, with ultrapure water used as the blank matrix. Procedural blanks were extracted and analyzed using the same procedures as the test samples in the analysis batch. Standard SGS AXYS laboratory quality control measures, which included matrix blanks and matrix spikes, were also used for mussel tissue analysis. Only blank corrected concentrations above the method detection limit were recorded as present. In addition, all PPCPs quantified in mussel tissue were prioritized and grouped into 27 classes, based on their primary therapeutic class, with concentration for each compound class summed to provide a cumulative total PPCP concentration measured at each MW site.

Data analysis

Land-use and point source data

The land-use and land cover (LULC) assessment conducted in this study is described elsewhere (Edwards et al., 2014, 2016; Kimbrough et al., 2021; Freitag et al., 2021). A brief overview is provided here to describe additional techniques used to develop and determine LULC estimates for each Great Lakes MWP study site. Site LULC estimates were mainly created from the USGS Multi-Resolution Land Characteristics (MRLC) (https://www.mrlc.gov/data/nlcd-2016-land-cover-conus) and 2016 National Land Cover Database (NLCD) raster layer (Homer et al., https://open.canada.ca/data/en/dataset/4e615eae-b90c-420b-adee-2ca35896caf6), based on the Anderson LULC values (Anderson et al., 1976; Choy et al., 2017; Yang et al., 2). Additional information on study sites that overlap clusters and fall within the 95% confidence interval is provided in Table S10

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Table 1 Summary of dreissenid mussel tissue PPCP concentrations (ng/g (wet weight)) detected in RF clusters (1–3). Additional information is provided in Fig. 6 and Table S3 (Supplementary Information)

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Additional analysis revealed differences in mussels sampled at inshore (river-tributary-harbor complexes) and offshore sampling locations. On average, overall PPCP concentrations varied across inshore and offshore sampling locations, with the highest mean concentrations observed in mussels from tributary sites sampled in cluster 1 (58.6 ng/g wet weight; Table 2). However, differences in inshore and offshore sampling locations PPCP concentrations were not statistically significant (Kruskal–Wallis; p > 0.05). Overall mean concentrations measured in mussels from harbor (30.1 ng/g wet weight) and offshore sites (32 ng/g wet weight) in cluster 1 were 1 to 2 orders of magnitude higher than mussels from cluster 2 and cluster 3, indicating active/fresh PPCP inputs (primary source), as well as pseudo-persistence occurring at these sampling locations. Likewise, additional comparison revealed elevated mean concentration in mussels from river sites (17.2 ng/g wet weight) in cluster 2, and mussels from river, harbor, and offshore sites sampled in cluster 3 (range: 9.84–10.3 ng/g wet weight; Table 2 and Fig. S2). Overall, measured concentration for 9 PPCPs (1,7-dimethylxanthine, 2-hydroxy-ibuprofen, theophylline, ciprofloxacin, clonidine, iopamidol, sertraline, triclocarban, and melphalan) was higher in mussels across all examined inshore and offshore sampling locations (Table S5). However, with the exception of iopamidol, the magnitude for 7 compounds (melphalan, 1,7-dimethylxanthine, 2-hydroxy-ibuprofen, ciprofloxacin, clonidine, sertraline, and triclocarban) was higher in mussels from inshore (i.e., harbor and river sites) and offshore sites in cluster 3, compared to cluster 2 and cluster 1.

Table 2 Summary of the PPCP concentrations (ng/g (wet weight)) detected in dreissenid mussel tissue sampled at inshore (harbor, river, tributaries) and offshore sampling locations between 2013 and 2018

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With the exception of cluster 2, measured concentrations for 2-hydroxy-ibuprofen (range: 32.9–269 ng/g wet weight), clonidine (range: 3.6–332 ng/g wet weight), and melphalan (range: 67.8–475 ng/g wet weight) were highest across cluster 1 and cluster 3, spanning several orders of magnitude when compared to other PPCP compounds assessed in this study (Table S5). Additional examination revealed 2-hydroxy-ibuprofen (anti-inflammatory), clonidine (antihypertensives), and melphalan (chemotherapy) elevated concentrations across cluster 1 and cluster 3 are indicative of their incomplete breakdown and release from wastewater treatment processes and medical discharges, since these pharmaceuticals are used extensively to treat cancer, hypertension (e.g., regulate blood pressure), and other related ailments (Ebele et al., 2017; Godoy et al., 2015; Yadav et al., 2021). Overall, this study confirms PPCPs detected in mussels from inshore and offshore sites are similar in complexity and occurrence to other comparative studies that have examined PPCPs throughout the Great Lakes (Baker et al., 2022; Banda et al., 2020b; Choy et al., 2017; Custer et al., 2020). Equally important, this study further provides evidence of emerging contaminant concentrations and composition strong variations that can occur between inshore and offshore (i.e., open/deep lake) sampling locations.

PPCP basin-wide and reference site assessment

Basin-wide, we detected significant differences for the majority of PPCP compounds measured in this study, although more sites were sampled in Lakes Michigan (67 sites) and Erie (29 sites), compared to other lakes (Lake Huron and Lake Ontario) and connecting channels (inclusive of all sites in the Detroit River and Niagara River), due in part to PPCP sampling objectives. For example, PPCP concentration and composition varied among lakes, connecting channels, and reference sites, with relatively higher mean concentration detected in mussels from Lake Huron (39.8 ng/g wet weight), compared to Lakes Erie (11.7 ng/g wet weight), Michigan (14.0 ng/g wet weight), Ontario (21.0 ng/g wet weight), the Niagara (5.10 ng/g wet weight), and Detroit River (5.95 ng/g wet weight) connecting channels, respectively (Table 3 and Fig. S3). Overall, PPCPs were mainly detected as complex mixtures basin-wide, with 4 (reference site; NRNF-1–7.14) to 28 (LMMB-01-INMU-6.18) compounds detected in mussels at one or more sampling location. These results indicate that PPCP chemical composition generally differed among MWP sites basin-wide, with some sites experiencing elevated contaminant exposure during the 2013–2018 study period. In addition to this study, several comparative studies have shown PPCPs are also occurring as complex mixtures in surface water (Baker et al., 2022; Baldwin et al., 2016; Blair et al., 2013; Ferguson et al., 2013; Pronschinske et al., 2022) and tissue samples (i.e., mussels, fish, and tree swallows [Tachycineta bicolor]; Banda et al., 2020; Cipoletti et al., 2019; Custer et al., 2020; Deere et al., 2020; de Solla et al., 2016; Woolnough et al., 2020) in the Great Lakes region. As shown in a previous study, the detection of these compounds as complex mixtures in the Great Lakes is of concern, due to their constituents, which were formulated to act on specific molecular targets in humans (Maloney et al., 2022).

Table 3 Summary of the PPCP concentrations (ng/g (wet weight)) detected in dreissenid mussel tissue sampled at Lake Michigan, Lake Huron, Lake Erie, Lake Ontario, Detroit, and Niagara River connecting channels (*), and designated MW reference sites between 2013 and 2018. Additional information is provided in Table S5

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A lake-lake comparison revealed antihypertensives, antidepressants, anti-histamine (diphenhydramine), insect repellant (DEET), chemotherapy (Etoposide), and antibacterial (triclocarban) were among the classes of pharmaceuticals most frequently detected in mussel’s basin-wide. PPCPs frequently detected in mussels represent a wide variety of therapeutic uses, with most previously reported in comparative surface water (Baker et al., 2022; Blair et al., 2013; Ferguson et al., 2013; Pronschinske et al., 2022) and tissue studies (Banda et al., 2020; Custer et al., 2020; Deere et al., 2020; de Solla et al., 2016; Woolnough et al., 2020) in the Great Lakes region. Overall, cumulative tissue concentrations (sum of detected PPCPs) ranged by several orders of magnitude (range: 3.6–674.9 ng/g ng/g wet weight) per site, with the highest total concentrations (> 350 ng/g wet weight) measured in mussels from sites sampled in Lake Michigan (MUS-6.26.18 and LMMB-01-INMU-6.18; Fig. S5 and Table S7). This finding is consistent with results from previous studies that reported elevated PPCP levels in fish (Banda et al., 2020) and surface water (Elliott et al., 2017; Ferguson et al., 2013; Pronschinske et al., 2022) were highest in Lake Michigan.

A broader assessment of PPCPs detected in mussels from designated offshore reference sites revealed significant variation in PPCP frequency, composition, and concentration. Of the 70 PPCPs quantified in this study, 37 (53%) compounds were detected in mussels from offshore reference sites (Fig. S4 and Table S6). Etoposide (68%), diphenhydramine (79%), citalopram (79%), DEET (89%), amitriptyline (89%), and sertraline (100%) were among the PPCPs most frequently detected in mussels from designated reference sites. Overall PPCP concentrations ranged from 0.067 to 236 ng/g (wet weight), with the highest total concentrations measured in mussels from reference sites in the Milwaukee Estuary (LMMB-5-S5-8.17) and western Lake Erie basin (Maumee Lighthouse: LEMR-3–6.15; Fig. S5 and Table S7). On average, approximately 78% (29/37) of the PPCPs measured in mussels from designated reference sites were measured at relatively low concentrations (< 5 ng/g wet weight). The detection of PPCPs at environmentally low concentrations, and also as complex mixtures in non-target lower trophic organisms including dreissenid mussels, especially in offshore zones of large water bodies such as the Great Lakes remains poorly understood (Blair et al., 2013). Thus, the toxicological effects and endpoints resulting from PPCPs long-term (i.e., chronic exposure), and low-level exposures in dreissenid mussels and other aquatic biota, may warrant additional consideration and future assessments of these emerging contaminants in the Great Lakes.

In general, several compounds including 1,7-dimethylxanthine, sertraline, metformin, clonidine, and iopamidol were measured at the highest mean concentration in mussels across all designated reference sites (> 10 ng/g wet weight; Fig. S4 and Table S6). Interestingly, clonidine, 1,7-dimethylxanthine, and iopamidol concentrations measured in mussels from offshore reference sites were similar or equal to chemical signatures observed at some inshore sites. Elevated concentrations detected at offshore reference sites, which are well beyond major pollution sources (e.g., Maumee Lighthouse-3, ~ 10 km away from nearest WWTP and storm-water outfall), are indicative of some PPCPs pseudo-persistence, recalcitrance to degradation (e.g., abiotic and biotic transformations), and active offshore contaminant transport in the Great Lakes Basin (Blair et al., 2013; Helm et al., 2012; Kimbrough et al., 2018; Patel et al., 2019). This further highlights the importance of bio-monitoring programs such as the MWP, and studies such as this in sampling emerging contaminants on a larger spatial scale, even at offshore lake complexes to better understand the magnitude and distribution of these organic contaminants in large freshwater systems.

PPCP discharge type assessment

The concentration profile for PPCPs measured in dreissenid mussels at major discharge types, including sites proximate to WWTPs only, sites proximate to both WWTP and CSO point source discharge, sites downstream and along gradients of wastewater discharge, and sites not influenced by either WWTP or CSO discharge (i.e., non-WWTPs), is presented in Fig. 7 and Table S8. Overall, PPCP concentrations varied among the major discharge types assessed in this study, with relatively higher mean concentration observed in mussels from non-WWTP sites (13.4 ng/g wet weight; Table 4). However, differences in discharge type mean concentrations were not statistically significant (Kruskal–Wallis; p > 0.05). Compared to the other major discharge types, PPCP loading and composition were also higher in mussels from non-WWTP sites (62/70; Table S8), thus demonstrating non-point/diffuse sources might also be important pollution pathways and routes of exposure for PPCPs detected within the Great Lakes Basin. Equally important, the highest total PPCP concentrations (summed by their respective compound class) were measured at non-WWTP sites (11,899.1 ng/g wet weight), compared to sites sampled proximate to WWTPs (1883.4 ng/g wet weight), sites downstream and along wastewater gradients (2149.1 ng/g wet weight), and sites sampled proximate to WWTPs/CSOs (2547.0 ng/g wet weight), respectively.

Table 4 Summary of dreissenid mussel PPCP concentration (ng/g (wet weight)) measured at major discharge types including sites sampled proximate to point source discharge (i.e., WWTPs and CSOs), sites downstream and along gradients of wastewater discharge, and sites without wastewater influence (non-WWTPs). Additional information is provided in Table S8

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While PPCPs relative concentration and composition are expected to be higher at sites in proximity to point sources (Apeti et al., 2018), comparative studies have shown fugitive release from leaking septic systems, landfills/landfill leachate, urban runoff, agricultural runoff following the land-applied of manure and/or biosolids, runoff from CAFO facilities, and overland flow of contaminants can contribute to elevated PPCP composition and concentration detected at non-WWTP zones (Adams et al., 2014; Baldwin et al., 2016; Elliott et al., 2017; Fairbairn et al., 2016; Ferrey et al., 2015; Pronschinske et al., 2022). In a follow-up study, Deere et al. (2021) demonstrated that a large percentage of high priority pharmaceuticals was detected at remote regions (e.g., non-WWTP zones) due to factors such as atmospheric wet deposition and the persistence of these organic pollutants. On average, the highest PPCP loading and concentration were measured in mussels from non-WTTP sites in Lake Michigan (MUS-6.26.18 and LMMB-01-INMU-6.18). As shown in prior studies conducted by Blair et al. (2013) and Li et al. (2017), elevated PPCP composition and concentration detected in Milwaukee Estuary, Lake Michigan, are not uncommon, as urban runoff and river discharge from the Menomonee River, Kinnickinnic River, and Milwaukee River confluence is viewed as potential sources of elevated PPCP composition and concentration.

Overall, a total of 29 PPCPs were found recurring in mussels across all site discharge types, which further highlight the ubiquity and persistence of these contaminants across all sampling types and locations in the Great Lakes Basin. In addition, 9 PPCPs (atenolol, benztropine, cyclophosphamide, flumequine, penicillin G, prednisolone, promethazine, thiabendazole, and zidovudine) were only detected in mussels from non-WWTP sites, which were not detected at any other discharge type assessed in this study (Table S8). In general, 5 PPCPs (1,7-dimethylxanthine, 2-hydroxy-ibuprofen, iopamidol, clonidine, and melphalan) were consistently measured at relatively high mean concentrations (> 30 ng/g wet weight; Fig. 7) in mussels across all site discharge types. Similar to studies conducted by de Solla et al. (2016) and Deere et al. (2020), this study detected iopamidol (range: 77.7–254 ng/g [wet weight]), melphalan (range: 172–217 ng/g [wet weight]), and 2-hydroxy-ibuprofen (range: 47.9–269 ng/g [wet weight]) concentrations relatively higher at sites sampled in proximity to WWTP/CSO point discharge.

Based on a prior study of 1448 municipal WWTPs found within the US and Canadian portion of the Great Lakes Basin coastal zone that discharge treated effluent to the Great Lakes Basin International Joint Commission (2009), most of the secondary and conventionally designed WWTPs are capable of achieving reductions for some emerging contaminants. Thus, the above finding suggests the type of wastewater treatment system, incomplete elimination during conventional wastewater treatment processes, low in-stream dilution, and hydrodynamic flushing and residence time are important drivers for various pharmaceuticals including 2-hydroxy-ibuprofen, melphalan, and iopamidol detected at mussel sampling locations (Baker et al., 2022; Castellano‐Hinojosa et al., 2023; Deere et al., 2021; de Solla et al., 2016; Ribbers et al., 2019). Additional correlation analysis revealed strong positive association between several classes of pharmaceuticals and point source parameters (i.e., WWTPs, WWTP effluent flow, and CSOs). Specifically, strong correlations were observed between 11 classes of pharmaceuticals (antacids, anti-histamines, antihypertensives, chemotherapy, diuretics, insect repellant, metabolites and transformation products (TPs), opioids, stimulants, X-ray contrast media, and antibacterial) and site point source/wastewater parameters (Spearman’s rho (ρ) = 0.5007–0.9341; Table S12).

Similar to results presented in Fairbairn et al. (2016) and Deere et al. (2020), four mixed-use pharmaceuticals (hydrocortisone, prednisone, sulfadimethoxine, and tylosin) were only detected in mussels from WWTP/CSO sites in this study (Table S8). The presence of macrolide and sulfonamide antibiotic residue, such as tylosin and sulfadimethoxine, in freshwater environments is more related to agricultural/non-urban activities, which includes extensive use in cattle, swine, and beef confined animal feeding operations (CAFO; De Liguoro et al., 2007; Fairbairn et al., 2016; Kaczala and Blum, 2016). However, tylosin (brand name, Tylan) and sulfadimethoxine (brand name, Albon) detection in mussels from WWTP/CSO discharge sites in the lower Maumee (LEMR-1–6.16) and the Detroit riverine system (River Rouge-2–6.16) is indicative of their mixed-use in both non-urban and urban/residential settings (Grześkowiak et al., 2015; Papich., 2020).

Interestingly, among the classes of pharmaceuticals examined in this study, antifungal, anti-histamine, beta-blockers, diuretics, metabolites, and opioids displayed similar chemical profile across all major discharge types (Fig. S6 and Table S9), which is likely indicative of the environmental fate and attenuation dynamics (e.g., abiotic transformation, photodegradation, and biodegradation processes) occurring across these discharge types. Similar to our findings at wastewater impacted sites (Custer et al., 2020; de Solla et al., 2016; Elliott et al., 2018), sites downstream and along wastewater gradients (Cipoletti et al., 2020; Jorgenson et al., 2018; Thomas et al., 2017), and non-WWTP sites (Deere et al., 2020), the detection of these contaminants across major discharge types in this study highlights the acute and sublethal risk posed by these classes of emerging contaminants on non-targeted organisms in the Great Lakes Basin.

Comparable to studies conducted in the Great Lakes (Baker et al., 2022; de Solla et al., 2016; Muir et al., 2017; Woolnough et al., 2020), across North America (Bradley et al., 2017; James et al., 2020), and Europe (Álvarez-Muñoz et al., 2015), this study detected similar patterns in PPCP concentrations for antibacterial (i.e., triclocarban wastewater indicator compound), stimulant (i.e., 1,7-dimethylxanthine, amphetamine, and cocaine), and chemotherapy pharmaceuticals at sites in proximity to WWTP and CSO discharges (Fig. S6 and Table S9). Thus, input from WWTP and CSO discharge is considered an important anthropogenic driver for these organic pollutants elevated concentration measured in mussels across these major discharge types. In addition, Spearman’s correlation results further revealed antibacterial, as well as anti-histamine, beta-blockers, diuretics, and PPCP transformation products (TP), were strongly correlated to site population estimates (Spearman’s rho (ρ) = 0.707–0.799; Table S12), suggesting local usage, pharmaceutical consumption patterns (e.g., seasonal usage patterns; Boogaerts et al., 2021), and wastewater treatment loading capacity are drivers for to the widespread detection of these contaminants (Khasawneh and Palaniandy., 2021). Although PPCP chemical interactions across major discharge types were not addressed in the current study, the sublethal effects for most contaminants detected in mussels across the major discharge types in this study are unknown. As such, follow-up investigations should be conducted to address potential environmental exposure and effects on non-targeted and lower trophic aquatic organisms.

PPCP relationship to land-use gradients

Detailed information on mussel sampling locations land-use/land cover estimates are presented in Table S10. Additional information on PPCP magnitude and environmental occurrence at predominant developed and open-water sites are presented in Table S11. The overall pattern in PPCP distribution remained heterogeneous among land-use categories assessed in this study (Fig. S7 and Table S10). In addition, developed and open-water were among the dominant site land-use categories, as well as land-use groups depicting the highest correlation among the classes of pharmaceuticals examined in this study (Table S12). Planted/cultivated (agricultural) land cover category was dominant (> 32%) at one study site (NRYT-INMU-CH-10.18; Fig. 2 and Table S10). This site was not included in the final assessment of PPCPs detected at mussel study sites, since there were not enough planted/cultivated sites available for comparison and subsequent discussion in this study.

The magnitude for PPCPs examined at predominant developed (range: 0.147–332 ng/g wet weight) and open-water sites (range: 0.098–475 ng/g wet weight) sites varied, with several mixed-use and human-specific pharmaceuticals including azithromycin, etoposide, diphenhydramine, clonidine, verapamil, triclocarban, DEET, fluoxetine, citalopram, sertraline, and amitriptyline, among the compounds most frequently detected (> 50%) in mussels across developed and open-water sampling locations. However, PPCPs were detected at higher frequency in mussels from developed sites, compared to open-water sites. Relatively higher mean concentrations were observed in mussels from open-water sites (14.2 ng/g wet weight), compared to developed sites (9.72 ng/g wet weight; Fig. S8 and Table 5). However, differences in developed and open-water sites mean concentration were not statistically significant (Kruskal–Wallis; p > 0.05). Eight pharmaceuticals (triclocarban, theophylline, 1,7-dimethylxanthine, sertraline, iopamidol, 2-hydroxy-ibuprofen, clonidine, and melphalan) were among the compounds measured at relatively higher concentrations (> 40 ng/g wet weight; Fig. 8; Table S11) in mussels across developed and open-water sites. Interestingly, the magnitude for several compounds (clonidine, azithromycin, verapamil, etoposide, citalopram, triclocarban, sertraline, diphenhydramine, amitriptyline, and DEET) frequently detected (> 50%) in mussels from developed and open-water sites were similar or higher, compared to results and findings for mussels, fish, and bird tissue in other reported studies (Cipoletti et al., 2020; Custer et al., 2020; Deere et al., 2020; James et al., 2020; Meador et al., 2017; Muir et al., 2017).

Table 5 Summary of the PPCP concentrations (ng/g (wet weight)) detected in dreissenid mussel tissue sampled at predominant developed and open-water sites between 2013 and 2018. Additional information is provided in Table S9

Full size table

The highest total PPCP concentrations (> 400 ng/g wet weight) were detected in mussels from open-water and developed sites in Lakes Ontario and Michigan (Fig. S5 and Table S7). Large urban clusters and higher residential/population density is likely related to the high variability and elevated PPCP concentrations detected in mussels from developed sites sampled in this study (Ferguson et al., 2013). As discussed in a previous study (Bai et al., 2018), developed/urban land cover types such as golf courses, dog parks, and recreation parks are likely major sources and environmental pathways for pharmaceuticals, due to increased surface runoff which introduces contaminants to urban surface waters, resulting in higher PPCP concentrations. Likewise, increased urban population density/residents often result in higher pharmaceutical consumption and usage, thus resulting in increased surface runoff and overland flow of contaminants to surface water (Wu et al., 2009). Similar to MacLeod and Wong (2010), this study detected positive relationship between higher PPCP concentrations and site population estimates (Table S7). Moreover, strong positive correlations were observed between several classes of pharmaceutical concentrations (chemotherapy, anticoagulant, x-ray contrast media, stimulants, insect repellant, beta-blockers diuretics, metabolites, anti-histamine, opioids, antacids, antihypertensives, and antibacterial) and developed and open-water land-use categories (Spearman’s rho (ρ) = 0.6386–0.913; Table S12), suggesting surrounding developed/urban and open-water land-use gradients are likely sinks and hotspots for these contaminants (Baldwin et al., 2016; Deere et al., 2021; Fairbairn et al., 2016).

Compared to other studies (Cipoletti et al., 2019; Custer et al., 2020), similar spatial patterns and chemical signatures were observed for some classes of pharmaceuticals examined at developed and open-water sites (Fig. S9 and Table S11). For example, antihistamine, antifungal, beta-blockers, diuretics, stimulants, metabolites/transformation products (TPs), and antidepressants were detected at similar or higher mean concentrations in mussels examined across developed and open-water sites, highlighting the complexity of PPCP source and anthropogenic pressures within the Great Lakes. Of interest, chemotherapeutic pharmaceuticals were detected at significantly higher mean concentrations in mussels at open-water sites, compared to developed sites. However, no statistically significant difference (Kruskal–Wallis p > 0.05) was observed between open-water and developed sites for melphalan concentrations. The highest concentrations of melphalan were found at developed and open-water sites in Lake Michigan/Black River (LMBR-0–5.18) and Lake Ontario/Cape Vincent (LOCV-INMU-10.18), respectively. Chemotherapeutic pharmaceuticals including melphalan body burden in tissue samples (i.e., fish and Bay mussels [Mytilus trossulus]) are documented for developed and open-water sites in the Great Lakes (Banda et al., 2020; Deere et al., 2020) and the Puget Sound (WA, USA; James et al., 2020). However, reported levels in the above studies are well below chemotherapeutic pharmaceuticals bivalve body burden values measured in this study (475 ng/g wet weight).

Similar patterns were observed for antihypertensive (range: 0.061–332 ng/g wet weight), and X-ray contrast media compounds (range: 49.2–261 ng/g wet weight), with mussels sampled at developed sites representing the highest concentrations detected in this study (Table S11). Compared to other developed sites examined in this study, X-ray contrast media concentrations were not statistically different across developed sampling locations (Kruskal–Wallis p > 0.05). However, higher concentrations were detected in mussels from sites sampled in the Maumee (Toledo WWTP/LEMR-1–6.15) and Ottawa (LEOT-2–6.15) riverine systems. Overall, X-ray contrast media magnitude detected in this study agrees with results reported in other studies conducted in the western Lake Erie basin (Cipoletti et al., 2020; Custer et al., 2020), northeastern Minnesota (Deere et al., 2020), and the Grand River watershed in southern Ontario (de Solla et al., 2016). Similarly, clonidine concentrations were not statistically different across developed sampling locations (Kruskal–Wallis p > 0.05). However, the highest average concentrations were observed in mussels from developed sites in Lake Huron, Thunder Bay (TBRD-INMU-CH-6.18), and Lake Michigan, Milwaukee Bay (LMMB-01-INMU-6.18). While most PPCP compounds quantified in this study were detected at relatively low concentrations (< 10 ng/g wet weight) in mussels from open-water (61%, 43/70) and developed sites (56%, 39/70), their detection as complex mixtures in this study might warrant additional assessment and prioritization, since information regarding their toxicity, fate, potential bioaccumulation, and endpoint is lacking and at times not fully understood. However, the potential adverse bio-effects and risks posed to aquatic organisms, directly associated with individual PPCPs quantified in dreissenid mussels, are beyond the scope of this study and are addressed in further detail in Fuller et al., (2023; in press).

Conclusion

In this study, a broad suite of PPCPs were assessed and characterized to better understand the environmental occurrence, magnitude, and spatial distribution of these emerging contaminants in relation to site land-use categories and proximity to point source dischargers within the Great Lakes Basin inshore (harbors, rivers, embayment, tributaries) and offshore locations. Our results revealed PPCPs were detected at all Great Lakes sites, mainly as complex mixtures, with 4 to 28 compounds detected at one or more mussel sampling locations. This emphasizes the need for continued monitoring, assessment and prioritization of these emerging contaminants, since information regarding their toxicity, fate, potential bioaccumulation, and endpoint is lacking, and at times not fully understood. Overall, several compounds comprising vasodilators, anti-inflammatory, antidepressants, X-ray contrast media, stimulants, antihypertensives, and chemotherapy classes of pharmaceuticals were consistently detected across sampling events, land-use and site discharge types. Results from the unsupervised RF classification identified patterns that were meaningful in assessing sites with the highest PPCP composition and exposures, as well as land-use categories with predominant mixtures. Significant differences between dominant site land-use categories, site discharge types, and PPCP contaminants measured in this study were detected. Overall, PPCP frequency was higher at sites sampled in proximity to WWTPs, confirming the ubiquity of these contaminants in wastewater treatment processes. Additionally, the findings in this study further revealed PPCP composition and loading was highest at non-WWTP sites, compared to other discharge types, thus confirming the importance of non-point sources as important pathways of PPCPs detected within the Great Lakes Basin. Equally significant, strong correlations were observed between several classes of pharmaceuticals and site dominant land-use categories, site population estimates, point source, and wastewater parameters. The findings of this study will help in identifying and contextualizing the relationship between detected contaminants, various point source and land-use gradients, and their likely “sinks” and “hot spots” along the Great Lakes Basin coastal zone and adjacent watersheds. These efforts will further aid in prioritizing MWP sampling locations and contaminants to be monitored, thus making the most efficient use of resources and funds, while identifying best management practices (BMPs) that can support measures in reducing and abating the continued occurrence of PPCPs in stressed aquatic environments.

Data availability

All associated data presented in this manuscript is available within the Supplementary Data file.

References

Ackerson, N. O. B., Liberatore, H. K., Plewa, M. J., Richardson, S. D., Ternes, T. A., & Duirk, S. E. (2020). Disinfection byproducts and halogen-specific total organic halogen speciation in chlorinated source waters – The impact of iopamidol and bromide. Journal of Environmental Sciences, 89, 90–101. https://doi.org/10.1016/j.jes.2019.10.007
Article CAS Google Scholar
Adams, J., Speakman, T., Zolman, E., Mitchum, G., Wirth, E., Bossart, G. D., & Fair, P. A. (2014). The relationship between land use and emerging and legacy contaminants in an Apex predator, the bottlenose dolphin (Tursiops truncatus), from two adjacent estuarine watersheds. Environmental Research, 135, 346–353. https://doi.org/10.1016/j.envres.2014.08.037
Article CAS Google Scholar
Álvarez-Muñoz, D., Rodríguez-Mozaz, S., Maulvault, A. L., Tediosi, A., Fernández-Tejedor, M., Van Den Heuvel, F., Kotterman, M., Marques, A., & Barceló, D. (2015). Occurrence of pharmaceuticals and endocrine disrupting compounds in macroalgaes, bivalves, and fish from coastal areas in Europe. Environmental Research, 143, 56–64. https://doi.org/10.1016/j.envres.2015.09.018
Article CAS Google Scholar
Anderson, J. R., Hardy, E. E., Roach, J. T., & Witmer, R. E. (1976). A land use and land cover classification system for use with remote sensor data. In US Geological Survey Professional Paper, 964, 28. https://pubs.usgs.gov/pp/0964/report.pdf
Apeti, D. A., Wirth, E., Leight, A., Mason, A. L., & Pisarski, E. (2018). An assessment of contaminants of emerging concern in Chesapeake Bay, MD and Charleston Harbor, SC. https://doi.org/10.25923/p4nc-7m71
Bahl, A., Hellack, B., Balas, M., Dinischiotu, A., Wiemann, M., Brinkmann, J., Luch, A., Renard, B. Y., & Haase, A. (2019). Recursive feature elimination in random forest classification supports nanomaterial grou**. NanoImpact, 15, 100179. https://doi.org/10.1016/j.impact.2019.100179
Article Google Scholar
Bai, X., Lutz, A., Carroll, R., Keteles, K., Dahlin, K., Murphy, M., & Nguyen, D. (2018). Occurrence, distribution, and seasonality of emerging contaminants in urban watersheds. Chemosphere, 200, 133–142. https://doi.org/10.1016/j.chemosphere.2018.02.106
Article CAS Google Scholar
Baker, B. B., Haimbaugh, A. S., Sperone, F. G., Johnson, D. M., & Baker, T. R. (2022). Persistent contaminants of emerging concern in a Great Lakes urban-dominant watershed. Journal of Great Lakes Research, 48(1), 171–182. https://doi.org/10.1016/j.jglr.2021.12.001
Article CAS Google Scholar
Baldwin, A. K., Corsi, S. R., De Cicco, L. A., Lenaker, P. L., Lutz, M. A., Sullivan, D. J., & Richards, K. D. (2016). Organic contaminants in Great Lakes tributaries: Prevalence and potential aquatic toxicity. Science of the Total Environment, 554–555, 42–52. https://doi.org/10.1016/j.scitotenv.2016.02.137
Article CAS Google Scholar
Banda, J. A., Gefell, D., An, V., Bellamy, A., Biesinger, Z., Boase, J., Chiotti, J., Gorsky, D., Robinson, T., Schlueter, S., Withers, J., & Hummel, S. L. (2020). Characterization of pharmaceuticals, personal care products, and polybrominated diphenyl ethers in lake sturgeon serum and gametes. Environmental Pollution, 266, 115051. https://doi.org/10.1016/j.envpol.2020.115051
Article CAS Google Scholar
Blair, B. D., Crago, J. P., Hedman, C. J., & Klaper, R. D. (2013). Pharmaceuticals and personal care products found in the Great Lakes above concentrations of environmental concern. Chemosphere, 93(9), 2116–2123. https://doi.org/10.1016/j.chemosphere.2013.07.057
Article CAS Google Scholar
Boogaerts, T., Ahmed, F., Choi, P., Tscharke, B., O’Brien, J., De Loof, H., Gao, J., Thai, P., Thomas, K., Mueller, J. F., Hall, W., Covaci, A., & Van Nuijs, A. L. (2021). Current and future perspectives for wastewater-based epidemiology as a monitoring tool for pharmaceutical use. Science of the Total Environment, 789, 148047. https://doi.org/10.1016/j.scitotenv.2021.148047
Article CAS Google Scholar
Bradley, P. M., Journey, C. A., Romanok, K. M., Barber, L. B., Buxton, H. T., Foreman, W. T., Furlong, E. T., Glassmeyer, S. T., Hladik, M. L., Iwanowicz, L. R., Jones, D. K., Kolpin, D. W., Kuivila, K. M., Loftin, K. A., Mills, M. A., Meyer, M. T., Orlando, J. L., Reilly, T. J., Smalling, K. L., & Villeneuve, D. L. (2017). Expanded target- chemical analysis reveals extensive mixed-organic-contaminant exposure in U.S. streams). Environmental Science & Technology, 51(9), 4792–4802. https://doi.org/10.1021/acs.est.7b00012
Breffle, W. S., Muralidharan, D., Donovan, R. P., Liu, F., Mukherjee, A., & **, Y. (2013). Socioeconomic evaluation of the impact of natural resource stressors on human-use services in the Great Lakes environment: A Lake Michigan case study. Resources Policy, 38(2), 152–161. https://doi.org/10.1016/j.resourpol.2012.10.004
Article Google Scholar
Bris, H. L., & Pouliquen, H. (2004). Experimental study on the bioaccumulation of oxytetracycline and oxolinic acid by the blue mussel (Mytilus edulis). An evaluation of its ability to bio-monitor antibiotics in the marine environment. Marine Pollution Bulletin, 48(5–6), 434–440. https://doi.org/10.1016/j.marpolbul.2003.08.018
Article CAS Google Scholar
Brody, D. J., & Gu, Q. (2020). Antidepressant use among adults: United States, 2015-2018. NCHS Data Brief, 377, 1–8. http://europepmc.org/article/MED/33054926
Bruner, K. A., Fisher, S. W., & Landrum, P. F. (1994). The role of the zebra mussel, Dreissena polymorpha, in contaminant cycling: II. Zebra mussel contaminant accumulation from algae and suspended particles, and transfer to the benthic invertebrate, Gammarus fasciatus. Journal of Great Lakes Research, 20(4), 735–750. https://doi.org/10.1016/s0380-1330(94)71191-6
Article CAS Google Scholar
Buschini, A., Carboni, P., Martino, A., Poli, P., & Rossi, C. (2003). Effects of temperature on baseline and genotoxicant-induced DNA damage in haemocytes of Dreissena polymorpha. Mutation Research/Genetic Toxicology and Environmental Mutagenesis, 537(1), 81–92. https://doi.org/10.1016/s1383-5718(03)00050-0
Article CAS Google Scholar
Cantwell, M. G., Katz, D. R., Sullivan, J. C., Shapley, D., Lipscomb, J., Epstein, J., Juhl, A. R., Knudson, C., & O’Mullan, G. D. (2018). Spatial patterns of pharmaceuticals and wastewater tracers in the Hudson River Estuary. Water Research, 137, 335–343. https://doi.org/10.1016/j.watres.2017.12.044
Article CAS Google Scholar
Carvalho, J., Garrido-Maestu, A., Azinheiro, S., Fuciños, P., Barros-Velázquez, J., De Miguel, R. J., Gros, V., & Prado, M. (2021). Faster monitoring of the invasive alien species (IAS) Dreissena polymorpha in river basins through isothermal amplification. Scientific Reports, 11(1). https://doi.org/10.1038/s41598-021-89574-w
Castellano-Hinojosa, A., Gallardo-Altamirano, M. J., González-López, J., & González-Martínez, A. (2023). Anticancer drugs in wastewater and natural environments: A review on their occurrence, environmental persistence, treatment, and ecological risks. Journal of Hazardous Materials, 447, 130818. https://doi.org/10.1016/j.jhazmat.2023.130818
Article CAS Google Scholar
Celeiro, M., Llompart, M., & Dagnac, T. (2022). Green analytical methodologies to determine personal care products in solid environmental matrices: Soils, sediments, sludge and biota ˗ A review. Advances in Sample Preparation, 2, 100013. https://doi.org/10.1016/j.sampre.2022.100013
Article Google Scholar
Challis, J. K., Cuscito, L. D., Joudan, S., Luong, K. H., Knapp, C. W., Hanson, M. L., & Wong, C. S. (2018). Inputs, source apportionment, and transboundary transport of pesticides and other polar organic contaminants along the lower Red River, Manitoba, Canada. Science of the Total Environment, 635, 803–816. https://doi.org/10.1016/j.scitotenv.2018.04.128
Article CAS Google Scholar
Choy, S. J., Annis, M. L., Banda, J. A., Bowman, S. R., Brigham, M. E., Elliott, S. M., Gefell, D. J., Janowski, M. D., Jorgenson, Z. G., Lee, K. E., Moore, J. N., & Tucker, W. A. (2017). Contaminants of emerging concern in the Great Lakes Basin: A report on sediment, water, and fish tissue chemistry collected in 2010–2012 (No. BTP-R3017–2013). US Fish & Wildlife Service. https://digitalmedia.fws.gov/digital/collection/document/id/2192/
Cipoletti, N., Jorgenson, Z. G., Banda, J. A., Hummel, S. L., Kohno, S., & Schoenfuss, H. L. (2019). Land use contributions to adverse biological effects in a complex agricultural and urban watershed: A case study of the Maumee River. Environmental Toxicology and Chemistry, 38(5), 1035–1051. https://doi.org/10.1002/etc.4409
Article CAS Google Scholar
Cipoletti, N., Jorgenson, Z. G., Banda, J. A., Kohno, S., Hummel, S. L., & Schoenfuss, H. L. (2020). Biological consequences of agricultural and urban land-use along the Maumee River, a major tributary to the Laurentian Great Lakes watershed. Journal of Great Lakes Research, 46(4), 1001–1014. https://doi.org/10.1016/j.jglr.2020.04.013
Article CAS Google Scholar
Contardo-Jara, V., Lorenz, C., Pflugmacher, S., Nützmann, G., Kloas, W., & Wiegand, C. (2011). Exposure to human pharmaceuticals carbamazepine, ibuprofen and bezafibrate causes molecular effects in Dreissena polymorpha. Aquatic Toxicology, 105(3–4), 428–437. https://doi.org/10.1016/j.aquatox.2011.07.017
Article CAS Google Scholar
Cornwell, E. R., Goyette, J. O., Sorichetti, R. J., Allan, D. J., Kashian, D. R., Sibley, P. K., Taylor, W. D., & Trick, C. G. (2015). Biological and chemical contaminants as drivers of change in the Great Lakes–St. Lawrence River Basin. Journal of Great Lakes Research, 41, 119–130. https://doi.org/10.1016/j.jglr.2014.11.003
Article CAS Google Scholar
Custer, C. M., Custer, T. W., Dummer, P. M., Schultz, S., Tseng, C. Y., Karouna-Renier, N., & Matson, C. W. (2020). Legacy and contaminants of emerging concern in tree swallows along an agricultural to industrial gradient: Maumee River. Ohio. Environmental Toxicology and Chemistry, 39(10), 1936–1952. https://doi.org/10.1002/etc.4792
Article CAS Google Scholar
Danz, N. P., Niemi, G. J., Regal, R. R., Hollenhorst, T., Johnson, L. B., Hanowski, J. M., Axler, R. P., Ciborowski, J. J. H., Hrabik, T., Brady, V. J., Kelly, J. R., Morrice, J. A., Brazner, J. C., Howe, R. W., Johnston, C. A., & Host, G. E. (2007). Integrated measures of anthropogenic stress in the U.S. Great Lakes Basin. Environmental Management, 39(5), 631–647. https://doi.org/10.1007/s00267-005-0293-0
Article Google Scholar
De Liguoro, M., Poltronieri, C., Capolongo, F., & Montesissa, C. (2007). Use of sulfadimethoxine in intensive calf farming: Evaluation of transfer to stable manure and soil. Chemosphere, 68(4), 671–676. https://doi.org/10.1016/j.chemosphere.2007.02.009
Article CAS Google Scholar
de Solla, S., Gilroy, A., Klinck, J., King, L., McInnis, R., Struger, J., Backus, S., & Gillis, P. (2016). Bioaccumulation of pharmaceuticals and personal care products in the unionid mussel Lasmigona costata in a river receiving wastewater effluent. Chemosphere, 146, 486–496. https://doi.org/10.1016/j.chemosphere.2015.12.022
Article CAS Google Scholar
Deere, J. R., Moore, S., Ferrey, M., Jankowski, M. D., Primus, A., Convertino, M., Servadio, J. L., Phelps, N. B., Hamilton, M. C., Chenaux-Ibrahim, Y., Travis, D. A., & Wolf, T. M. (2020). Occurrence of contaminants of emerging concern in aquatic ecosystems utilized by Minnesota tribal communities. Science of the Total Environment, 724, 138057. https://doi.org/10.1016/j.scitotenv.2020.138057
Article CAS Google Scholar
Deere, J. R., Streets, S., Jankowski, M. D., Ferrey, M., Chenaux-Ibrahim, Y., Convertino, M., Isaac, E., Phelps, N. B., Primus, A., Servadio, J. L., Singer, R. S., Travis, D. A., Moore, S., & Wolf, T. M. (2021). A chemical prioritization process: Applications to contaminants of emerging concern in freshwater ecosystems (phase I). Science of the Total Environment, 772, 146030. https://doi.org/10.1016/j.scitotenv.2021.146030
Article CAS Google Scholar
Dehm, J., Singh, S., Ferreira, M., Piovano, S., & Fick, J. (2021). Screening of pharmaceuticals in coastal waters of the southern coast of Viti Levu in Fiji South Pacific. Chemosphere, 276, 130161. https://doi.org/10.1016/j.chemosphere.2021.130161
Article CAS Google Scholar
Dodder, N. G., Maruya, K. A., Ferguson, P. L., Grace, R., Klosterhaus, S., La Guardia, M. J., Lauenstein, G. G., & Ramirez, J. (2014). Occurrence of contaminants of emerging concern in mussels (Mytilus spp.) along the California coast and the influence of land use, storm water discharge, and treated wastewater effluent. Marine Pollution Bulletin, 81(2), 340–346. https://doi.org/10.1016/j.marpolbul.2013.06.041
Ebele, A. J., Abou-Elwafa Abdallah, M., & Harrad, S. (2017). Pharmaceuticals and personal care products (PPCPs) in the freshwater aquatic environment. Emerging Contaminants, 3(1), 1–16. https://doi.org/10.1016/j.emcon.2016.12.004
Article Google Scholar
ECHO, (2022). Enforcement and compliance history online exporter version 2.0. United States environmental protection agency. Online. https://echo.epa.gov/. Accessed 22 Sep 2022.
Edwards, M., Jacob, A., Kimbrough, K., Davenport, E., & Johnson, W. (2014). Assessment of trace elements and legacy contaminant concentrations in California Mussels (Mytilus spp.): Relationship to land use and outfalls. Marine Pollution Bulletin, 81(2), 325–333. https://doi.org/10.1016/j.marpolbul.2014.02.030
Article CAS Google Scholar
Edwards, M. A., Jacob, A., Kimbrough, K., Johnson, W., & Davenport, E. D. (2016). Great lakes mussel watch sites land-use characterization and assessment. In NOAA Technical memorandum NOS NCCOS (Vol. 208, p. 138). https://repository.library.noaa.gov/view/noaa/12942
Elliott, S. M., Brigham, M. E., Lee, K. E., Banda, J. A., Choy, S. J., Gefell, D. J., Minarik, T. A., Moore, J. N., & Jorgenson, Z. G. (2017). Contaminants of emerging concern in tributaries to the Laurentian Great Lakes: I Patterns of Occurrence. Plos One, 12(9), e0182868. https://doi.org/10.1371/journal.pone.0182868
Article CAS Google Scholar
Elliott, S. M., Brigham, M. E., Kiesling, R. L., Schoenfuss, H. L., & Jorgenson, Z. G. (2018). Environmentally relevant chemical mixtures of concern in waters of United States tributaries to the Great Lakes. Integrated Environmental Assessment and Management, 14(4), 509–518. https://doi.org/10.1002/ieam.4041
Article CAS Google Scholar
Fabbri, D., Calza, P., Dalmasso, D., Chiarelli, P., Santoro, V., & Medana, C. (2016). Iodinated X-ray contrast agents: Photoinduced transformation and monitoring in surface water. Science of the Total Environment, 572, 340–351. https://doi.org/10.1016/j.scitotenv.2016.08.003
Article CAS Google Scholar
Fairbairn, D. J., Karpuzcu, M. E., Arnold, W. A., Barber, B. L., Kaufenberg, E. F., Koskinen, W. C., Novak, P. J., Rice, P. J., & Swackhamer, D. L. (2016). Sources and transport of contaminants of emerging concern: A two-year study of occurrence and spatiotemporal variation in a mixed land use watershed. Science of the Total Environment, 551–552, 605–613. https://doi.org/10.1016/j.scitotenv.2016.02.056
Article CAS Google Scholar
Felis, E., Kalka, J., Sochacki, A., Kowalska, K., Bajkacz, S., Harnisz, M., & Korzeniewska, E. (2020). Antimicrobial pharmaceuticals in the aquatic environment - Occurrence and environmental implications. European Journal of Pharmacology, 866, 172813. https://doi.org/10.1016/j.ejphar.2019.172813
Article CAS Google Scholar
Ferguson, P. J., Bernot, M. J., Doll, J. C., & Lauer, T. E. (2013). Detection of pharmaceuticals and personal care products (PPCPs) in near-shore habitats of southern Lake Michigan. Science of the Total Environment, 458–460, 187–196. https://doi.org/10.1016/j.scitotenv.2013.04.024
Article CAS Google Scholar
Ferrey, M. L., Heiskary, S., Grace, R., Hamilton, M. C., & Lueck, A. (2015). Pharmaceuticals and other anthropogenic tracers in surface water: A randomized survey of 50 Minnesota lakes. Environmental Toxicology and Chemistry, 34(11), 2475–2488. https://doi.org/10.1002/etc.3125
Article CAS Google Scholar
Fields, S. (2005). Great Lakes resource at risk. Environmental Health Perspectives, 113(3). https://doi.org/10.1289/ehp.113-a164
Ford, S. E., & Paillard, C. (2007). Repeated sampling of individual bivalve mollusks I: Intraindividual variability and consequences for haemolymph constituents of the Manila clam Ruditapes philippinarum. Fish and Shellfish Immunology, 23(2), 280–291. https://doi.org/10.1016/j.fsi.2006.10.013
Article CAS Google Scholar
Fraley, C., Raftery, A. E., Murphy, T. B., & Scrucca, L. (2012). Mclust version 4 for R: Normal mixture modelling for model-based clustering, classification, and density estimation. In Technical report no. 597. Department of Statistics, University of Washington. https://stat.uw.edu/sites/default/files/files/reports/2012/tr597.pdf
Franquet-Griell, H., Medina, A., Sans, C., & Lacorte, S. (2017). Biological and photochemical degradation of cytostatic drugs under laboratory conditions. Journal of Hazardous Materials, 323, 319–328. https://doi.org/10.1016/j.jhazmat.2016.06.057
Article CAS Google Scholar
Freitag, A., Regan, S., Leight, A. K., Kimbrough, K., Edwards, M., Burkart, H., & Rider, M. (2021). Polycyclic aromatic hydrocarbon characterization and prediction in coastal sediments using regression modeling and machine learning. In NOAA technical memorandum NOS NCCOS (Vol. 293, p. 27). https://doi.org/10.25923/r7k5-vj14
Fuller, N., Kimbrough, K., Edwards, M. E., Maloney, E. M., Corsi, S. R., Pronschinske, M. A., DeCicco, L., Custer, C. R., Frisch, J., Baldwin, A. K. M., Hummel, S. L., Vinas, N., & Villeneuve, D. L. (in press). Retrospective stepwise prioritization of chemicals of emerging concern in bivalve molluscs in the great lakes basin. Environmental Science & Technology.
Gao, Z. C., Lin, Y. L., Xu, B., **a, Y., Hu, C. Y., Cao, T. C., Zou, X. Y., & Gao, N. Y. (2019). Evaluating iopamidol degradation performance and potential dual-wavelength synergy by UV-LED irradiation and UV-LED/chlorine treatment. Chemical Engineering Journal, 360, 806–816. https://doi.org/10.1016/j.cej.2018.12.022
Article CAS Google Scholar
Godoy, A. A., Kummrow, F., & Pamplin, P. A. Z. (2015). Occurrence, ecotoxicological effects and risk assessment of antihypertensive pharmaceutical residues in the aquatic environment - A review. Chemosphere, 138, 281–291. https://doi.org/10.1016/j.chemosphere.2015.06.024
Article CAS Google Scholar
Gómez-Oliván, L. M., Galár-Martínez, M., García-Medina, S., Valdés-Alanís, A., Islas-Flores, H., & Neri-Cruz, N. (2014). Genotoxic response and oxidative stress induced by diclofenac, ibuprofen and naproxen inDaphnia magna. Drug and Chemical Toxicology, 37(4), 391–399. https://doi.org/10.3109/01480545.2013.870191
Article CAS Google Scholar
González-Fernández, C., Albentosa, M., Campillo, J. A., Viñas, L., Romero, D., Franco, A., & Bellas, J. (2015). Effect of nutritive status on Mytilus galloprovincialis pollution biomarkers: Implications for large-scale monitoring programs. Aquatic Toxicology, 167, 90–105. https://doi.org/10.1016/j.aquatox.2015.07.007
Article CAS Google Scholar
Grześkowiak, U., Endo, A., Beasley, S., & Salminen, S. (2015). Microbiota and probiotics in canine and feline welfare. Anaerobe, 34, 14–23. https://doi.org/10.1016/j.anaerobe.2015.04.002
Article Google Scholar
Guerlet, E., Ledy, K., Meyer, A., & Giambérini, L. (2007). Towards a validation of a cellular biomarker suite in native and transplanted zebra mussels: A 2-year integrative field study of seasonal and pollution-induced variations. Aquatic Toxicology, 81(4), 377–388. https://doi.org/10.1016/j.aquatox.2006.12.016
Article CAS Google Scholar
Hartig, J. H., Krantzberg, G., & Alsip, P. J. (2020). Thirty-five years of restoring Great Lakes Areas of Concern: Gradual progress, hopeful future. Journal of Great Lakes Research, 46(3), 429–442. https://doi.org/10.1016/j.jglr.2020.04.004
Article Google Scholar
Hashemzadeh, B., Alamgholiloo, H., Noroozi Pesyan, N., Asgari, E., Sheikhmohammadi, A., Yeganeh, J., & Hashemzadeh, H. (2021). Degradation of ciprofloxacin using hematite/MOF nanocomposite as a heterogeneous Fenton-like catalyst: A comparison of composite and core−shell structures. Chemosphere, 281, 130970. https://doi.org/10.1016/j.chemosphere.2021.130970
Article CAS Google Scholar
Helm, P. A., Howell, E. T., Li, H., Metcalfe, T. L., Chomicki, K. M., & Metcalfe, C. D. (2012). Influence of nearshore dynamics on the distribution of organic wastewater-associated chemicals in Lake Ontario determined using passive samplers. Journal of Great Lakes Research, 38, 105–115. https://doi.org/10.1016/j.jglr.2012.01.005
Article CAS Google Scholar
Homer, C., Dewitz, J., **, S., **an, G., Costello, C., Danielson, P., Gass, L., Funk, M., Wickham, J., Stehman, S., Auch, R., & Riitters, K. H. (2020). Conterminous United States land cover change patterns 2001–2016 from the 2016 National Land Cover Database. ISPRS Journal of Photogrammetry and Remote Sensing, 162, 184–199. https://doi.org/10.1016/j.isprsjprs.2020.02.019
Article Google Scholar
Hull, R. N., Kleywegt, S., & Schroeder, J. (2015). Risk-based screening of selected contaminants in the Great Lakes Basin. Journal of Great Lakes Research, 41(1), 238–245. https://doi.org/10.1016/j.jglr.2014.11.013
Article CAS Google Scholar
Hwang, S. A., Hwang, S. J., Park, S. R., & Lee, S. W. (2016). Examining the relationships between watershed urban land use and stream water quality using linear and generalized additive models. Water, 8(4), 155. https://doi.org/10.3390/w8040155
Article CAS Google Scholar
Iacopetta, D., Catalano, A., Ceramella, J., Saturnino, C., Salvagno, L., Ielo, I., Drommi, D., Scali, E., Plutino, M. R., Rosace, G., & Sinicropi, M. S. (2021). The different facets of triclocarban: A review. Molecules, 26(9), 2811. https://doi.org/10.3390/molecules26092811
Article CAS Google Scholar
International Joint Commission. (2009). Work group report on Great Lakes chemicals of emerging concern, special publication 2009–01 Great Lakes water quality agreement priorities 2007–09 series. IJC. https://gis.ijc.org/wwtp2021/CEC_report.pdf
Izadi, P., Izadi, P., Salem, R., Papry, S. A., Magdouli, S., Pulicharla, R., & Brar, S. K. (2020). Non-steroidal anti-inflammatory drugs in the environment: Where were we and how far we have come? Environmental Pollution, 267, 115370. https://doi.org/10.1016/j.envpol.2020.115370
Article CAS Google Scholar
Jaffrézic, A., Jardé, E., Soulier, A., Carrera, L., Marengue, E., Cailleau, A., & Le Bot, B. (2017). Veterinary pharmaceutical contamination in mixed land use watersheds: From agricultural headwater to water monitoring watershed. Science of the Total Environment, 609, 992–1000. https://doi.org/10.1016/j.scitotenv.2017.07.206
Article CAS Google Scholar
James, C. A., Lanksbury, J., Khangaonkar, T., & West, J. (2020). Evaluating exposures of bay mussels (Mytilus trossulus) to contaminants of emerging concern through environmental sampling and hydrodynamic modeling. Science of the Total Environment, 709, 136098. https://doi.org/10.1016/j.scitotenv.2019.136098
Article CAS Google Scholar
Jorgenson, Z. G., Thomas, L. M., Elliott, S. M., Cavallin, J. E., Randolph, E. C., Choy, S. J., Alvarez, D. A., Banda, J. A., Gefell, D. J., Lee, K. E., Furlong, E. T., & Schoenfuss, H. L. (2018). Contaminants of emerging concern presence and adverse effects in fish: A case study in the Laurentian Great Lakes. Environmental Pollution, 236, 718–733. https://doi.org/10.1016/j.envpol.2018.01.070
Article CAS Google Scholar
Jureczko, M., & Kalka, J. (2020). Cytostatic pharmaceuticals as water contaminants. European Journal of Pharmacology, 866, 172816. https://doi.org/10.1016/j.ejphar.2019.172816
Article CAS Google Scholar
Kaczala, F., & Blum, S. E. (2016). The occurrence of veterinary pharmaceuticals in the environment: A review. Current Analytical Chemistry, 12(3), 169–182. https://doi.org/10.2174/1573411012666151009193108
Article CAS Google Scholar
Khasawneh, O. F. S., & Palaniandy, P. (2021). Occurrence and removal of pharmaceuticals in wastewater treatment plants. Process Safety and Environmental Protection, 150, 532–556. https://doi.org/10.1016/j.psep.2021.04.045
Article CAS Google Scholar
Kiesling, R. L., Elliott, S. M., Kammel, L. E., Choy, S. J., & Hummel, S. L. (2019). Predicting the occurrence of chemicals of emerging concern in surface water and sediment across the U.S. portion of the Great Lakes Basin. Science of the Total Environment, 651, 838–850. https://doi.org/10.1016/j.scitotenv.2018.09.201
Article CAS Google Scholar
Kiesling, R. L., Elliott, S. M., Kennedy, J. L., & Hummel, S. L. (2022). Validation of a vulnerability index of exposure to chemicals of emerging concern in surface water and sediment of Great Lakes tributaries of the United States. Science of the Total Environment, 830, 154618. https://doi.org/10.1016/j.scitotenv.2022.154618
Article CAS Google Scholar
Kimbrough, K., Johnson, W. E., Jacob, A., Edwards, M., Davenport, E., Lauenstein, G., Nalepa, T., Fulton, M., & Pait, A. (2014). Mussel watch great lakes contaminant monitoring and assessment: Phase 1. In Silver Spring, MD. NOAA technical memorandum NOS NCCOS 180, 113 pp. https://repository.library.noaa.gov/view/noaa/4834
Kimbrough, K., Johnson, W. E., Jacob, A., Edwards, M., & Davenport, E. (2018). Great Lakes mussel watch: Assessment of contaminants of emerging concern. In NOAA technical memorandum NOS NCCOS 249 (p. 66). https://doi.org/10.25923/2jp9-pn57
Kimbrough, K., Jacob, A., Regan, S., Davenport, E., Edwards, M., Leight, A. K., Freitag, A., Rider, M., & Johnson, W. E. (2021). Characterization of polycyclic aromatic hydrocarbons in the Great Lakes Basin using Dreissenid mussels. Environmental Monitoring and Assessment, 193(12). https://doi.org/10.1007/s10661-021-09401-7
Kovalakova, P., Cizmas, L., McDonald, T. J., Maršálek, B., Feng, M., & Sharma, V. K. (2020). Occurrence and toxicity of antibiotics in the aquatic environment: A review. Chemosphere, 251, 126351. https://doi.org/10.1016/j.chemosphere.2020.126351
Article CAS Google Scholar
Kumar, M., Jaiswal, S., Sodhi, K. K., Shree, P., Singh, D. K., Agrawal, P. K., & Shukla, P. (2019). Antibiotics bioremediation: Perspectives on its ecotoxicity and resistance. Environment International, 124, 448–461. https://doi.org/10.1016/j.envint.2018.12.065
Article CAS Google Scholar
Lacorte, S., Gómez-Canela, C., & Calas-Blanchard, C. (2021). Pharmaceutical residues in senior residences wastewaters: High loads, emerging risks. Molecules, 26(16), 5047. https://doi.org/10.3390/molecules26165047
Article CAS Google Scholar
Laitta, M. T. (2016). Waste water treatment plants in the Great Lakes. Retrieved December 16, 2022, from: https://usgs.maps.arcgis.com/home/item.html?id=e4a5b201232944c2a671eb96621274dd
Larson, J. H., Trebitz, A. S., Steinman, A. D., Wiley, M. J., Mazur, M. C., Pebbles, V., Braun, H. A., & Seelbach, P. W. (2013). Great Lakes rivermouth ecosystems: Scientific synthesis and management implications. Journal of Great Lakes Research, 39(3), 513–524. https://doi.org/10.1016/j.jglr.2013.06.002
Article Google Scholar
Li, S., Villeneuve, D. L., Berninger, J. P., Blackwell, B. R., Cavallin, J. E., Hughes, M. N., Jensen, K. M., Jorgenson, Z., Kahl, M. D., Schroeder, A. L., Stevens, K. E., Thomas, L. M., Weberg, M. A., & Ankley, G. T. (2017). An integrated approach for identifying priority contaminant in the Great Lakes Basin – Investigations in the Lower Green Bay/Fox River and Milwaukee Estuary areas of concern. Science of the Total Environment, 579, 825–837. https://doi.org/10.1016/j.scitotenv.2016.11.021
Article CAS Google Scholar
Liu, Q., Feng, X., Chen, N., Shen, F., Zhang, H., Wang, S., Sheng, Z., & Li, J. (2022). Occurrence and risk assessment of typical PPCPs and biodegradation pathway of ribavirin in wastewater treatment plants. Environmental Science and Ecotechnology, 11, 100184. https://doi.org/10.1016/j.ese.2022.100184
Article CAS Google Scholar
Luo, Y., Kataoka, Y., Ostinelli, E. G., Cipriani, A., & Furukawa, T. A. (2020). National Prescription Patterns of antidepressants in the treatment of adults with major depression in the US between 1996 and 2015: A population representative survey based analysis. Frontiers in Psychiatry, 11. https://doi.org/10.3389/fpsyt.2020.00035
MacLeod, S. L., & Wong, C. S. (2010). Loadings, trends, comparisons, and fate of achiral and chiral pharmaceuticals in wastewaters from urban tertiary and rural aerated lagoon treatments. Water Research, 44(2), 533–544. https://doi.org/10.1016/j.watres.2009.09.056
Article CAS Google Scholar
Maloney, E. M., Villeneuve, D. L., Jensen, K., Blackwell, B. R., Kahl, M. D., Poole, S., Vitense, K., Feifarek, D. J., Patlewicz, G., Dean, K., Tilton, C. B., Randolph, E. C., Cavallin, J. E., LaLone, C. A., Blatz, D., Schaupp, C. M., & Ankley, G. T. (2023). Evaluation of complex mixture toxicity in the Milwaukee Estuary (WI, USA) using whole-mixture and component-based evaluation methods. Environmental Toxicology and Chemistry, 42(6), 1229–1256. https://doi.org/10.1002/etc.5571
Article CAS Google Scholar
Matsushita, T., Kobayashi, N., Hashizuka, M., Sakuma, H., Kondo, T., Matsui, Y., & Shirasaki, N. (2015). Changes in mutagenicity and acute toxicity of solutions of iodinated X-ray contrast media during chlorination. Chemosphere, 135, 101–107. https://doi.org/10.1016/j.chemosphere.2015.03.082
Article CAS Google Scholar
Meador, J. P., Yeh, A., Young, G., & Gallagher, E. P. (2016). Contaminants of emerging concern in a large temperate estuary. Environmental Pollution, 213, 254–267. https://doi.org/10.1016/j.envpol.2016.01.088
Article CAS Google Scholar
Mestre, A. S., Machuqueiro, M., Silva, M., Freire, R., Fonseca, I. M., Santos, M. S. C. S., Calhorda, M. J., & Carvalho, A. P. (2014). Influence of activated carbons porous structure on iopamidol adsorption. Carbon, 77, 607–615. https://doi.org/10.1016/j.carbon.2014.05.065
Article CAS Google Scholar
Metcalfe, C. D., Chu, S., Judt, C., Li, H., Oakes, K. D., Servos, M. R., & Andrews, D. M. (2010). Antidepressants and their metabolites in municipal wastewater, and downstream exposure in an urban watershed. Environmental Toxicology and Chemistry, 29(1), 79–89. https://doi.org/10.1002/etc.27
Article CAS Google Scholar
Morrice, J. A., Danz, N. P., Regal, R. R., Kelly, J. R., Niemi, G. J., Reavie, E. D., Hollenhorst, T., Axler, R. P., Trebitz, A. S., Cotter, A. M., & Peterson, G. S. (2007). Human influences on water quality in Great Lakes coastal wetlands. Environmental Management, 41(3), 347–357. https://doi.org/10.1007/s00267-007-9055-5
Article Google Scholar
Mosqueda-Garcia, R., Oates, J. A., Appalsamy, M., & Robertson, D. (1991). Administration of carbamazepine in the nucleus of the solitary tract inhibits the antihypertensive effect of clonidine. European Journal of Pharmacology, 197(2–3), 213–216. https://doi.org/10.1016/0014-2999(91)90524-t
Article CAS Google Scholar
Muir, D. C., Simmons, D., Wang, X., Peart, T., Villella, M., Miller, J. K., & Sherry, J. (2017). Bioaccumulation of pharmaceuticals and personal care product chemicals in fish exposed to wastewater effluent in an urban wetland. Scientific Reports, 7(1). https://doi.org/10.1038/s41598-017-15462-x
Noguera-Oviedo, K., & Aga, D. S. (2016). Lessons learned from more than two decades of research on emerging contaminants in the environment. Journal of Hazardous Materials, 316, 242–251. https://doi.org/10.1016/j.jhazmat.2016.04.058
Article CAS Google Scholar
Ohoro, C. R., Adeniji, A. O., Okoh, A. I., & Okoh, O. O. (2019). Distribution and chemical analysis of pharmaceuticals and personal care products (PPCPs) in the environmental systems: A review. International Journal of Environmental Research and Public Health, 16(17), 3026. https://doi.org/10.3390/ijerph16173026
Article CAS Google Scholar
Oliver, M., & Hinks, T. S. C. (2020). Azithromycin in viral infections. Reviews in Medical Virology, 31(2). https://doi.org/10.1002/rmv.2163
Pal, A., He, Y., Jekel, M., Reinhard, M., & Gin, K. Y. H. (2014). Emerging contaminants of public health significance as water quality indicator compounds in the urban water cycle. Environment International, 71, 46–62. https://doi.org/10.1016/j.envint.2014.05.025
Article CAS Google Scholar
Papich, M. G. (2020). Antimicrobial agent use in small animals what are the prescribing practices, use of PK-PD principles, and extralabel use in the United States? Journal of Veterinary Pharmacology and Therapeutics, 44(2), 238–249. https://doi.org/10.1111/jvp.12921
Article Google Scholar
Parolini, M. (2020). Toxicity of the non-steroidal anti-inflammatory drugs (NSAIDs) acetylsalicylic acid, paracetamol, diclofenac, ibuprofen and naproxen towards freshwater invertebrates: A review. Science of the Total Environment, 740, 140043. https://doi.org/10.1016/j.scitotenv.2020.140043
Article CAS Google Scholar
Patel, M., Kumar, R., Kishor, K., Mlsna, T., Pittman, C. U., & Mohan, D. (2019). Pharmaceuticals of emerging concern in aquatic systems: Chemistry, occurrence, effects, and removal methods. Chem Rev, 119(6), 3510–3673. https://doi.org/10.1021/acs.chemrev.8b00299
Article CAS Google Scholar
Pinter, J., Jones, B. S., & Vriens, B. (2022). Loads and elimination of trace elements in wastewater in the Great Lakes Basin. Water Research, 209, 117949. https://doi.org/10.1016/j.watres.2021.117949
Article CAS Google Scholar
Postigo, C., DeMarini, D. M., Armstrong, M. D., Liberatore, H. K., Lamann, K., Kimura, S. Y., Cuthbertson, A. A., Warren, S. H., Richardson, S. D., McDonald, T., Sey, Y. M., Ackerson, N. O. B., Duirk, S. E., & Simmons, J. E. (2018). Chlorination of source water containing iodinated x-ray contrast media: Mutagenicity and identification of new iodinated disinfection byproducts. Environmental Science & Technology, 52(22), 13047–13056. https://doi.org/10.1021/acs.est.8b04625
Pronschinske, M. A., Corsi, S. R., DeCicco, L., Furlong, E. T., Ankley, G. T., Blackwell, B. R., Villeneuve, D. L., Lenaker, P. L., & Nott, M. A. (2022). Prioritizing pharmaceutical contaminants in Great Lakes tributaries using risk-based screening techniques. Environmental Toxicology and Chemistry, 41(9), 2221–2239. https://doi.org/10.1002/etc.5403
Article CAS Google Scholar
R Core Team. (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing. http://www.R-project.org/
Ren, B., Shi, X., **, X., Wang, X. C., & **, P. (2021). Comprehensive evaluation of pharmaceuticals and personal care products (PPCPs) in urban sewers: Degradation, intermediate products and environmental risk. Chemical Engineering Journal, 404, 127024. https://doi.org/10.1016/j.cej.2020.127024
Ribbers, K., Breuer, L., & Düring, R. (2019). Detection of artificial sweeteners and iodinated X-ray contrast media in wastewater via LC-MS/MS and their potential use as anthropogenic tracers in flowing waters. Chemosphere, 218, 189–196. https://doi.org/10.1016/j.chemosphere.2018.10.193
Article CAS Google Scholar
Richmond, E. K., Grace, M., Kelly, J. J., Reisinger, A. J., Rosi-Marshall, E. J., & Walters, D. (2017). Pharmaceuticals and personal care products (PPCPs) are ecological disrupting compounds (EcoDC). Elementa, 5. https://doi.org/10.1525/elementa.252
Rizzo, L., Malato, S., Antakyali, D., Beretsou, V. G., Đolić, M. B., Gernjak, W., Heath, E., Ivancev-Tumbas, I., Karaolia, P., Lado Ribeiro, A. R., Mascolo, G., McArdell, C. S., Schaar, H., Silva, A. M. T., & Fatta-Kassinos, D. (2019). Consolidated vs newadvanced treatment methods for the removal of contaminants of emerging concern from urban wastewater. Sci. Total Environ., 655(November 2018), 986–1008. https://doi.org/10.1016/j.scitotenv.2018.11.265
Article CAS Google Scholar
Rodriguez-Galiano, V., Ghimire, B., Rogan, J., Chica-Olmo, M., & Rigol-Sanchez, J. (2012). An assessment of the effectiveness of a random forest classifier for land-cover classification. ISPRS Journal of Photogrammetry and Remote Sensing, 67, 93–104. https://doi.org/10.1016/j.isprsjprs.2011.11.002
Article Google Scholar
Salazar, M., & Salazar, S. M. (1995). In-situ bioassays using transplanted mussels: I. Estimating chemical exposure and bioeffects with bioaccumulation and growth. In ASTM international eBooks (pp. 216–226). https://doi.org/10.1520/stp12693s
Santos, L. H., Gros, M., Rodriguez-Mozaz, S., Delerue-Matos, C., Pena, A., Barceló, D., & Montenegro, M. C. B. (2013). Contribution of hospital effluents to the load of pharmaceuticals in urban wastewaters: Identification of ecologically relevant pharmaceuticals. Science of the Total Environment, 461–462, 302–316. https://doi.org/10.1016/j.scitotenv.2013.04.077
Article CAS Google Scholar
Shi, P., Zhang, Y., Li, Z., Li, P., & Xu, G. (2017). Influence of land use and land cover patterns on seasonal water quality at multi-spatial scales. CATENA, 151, 182–190. https://doi.org/10.1016/j.catena.2016.12.017
Article CAS Google Scholar
Sponberg, A. F. (2009). Great Lakes: Sailing to the forefront of national water policy? BioScience, 59(5), 372–372. https://doi.org/10.1525/bio.2009.59.5.4
Article Google Scholar
Srour, S. A., Milton, D. R., Bashir, Q., Mehta, R. S., Delgado, R., Rondon, G., Nieto, Y., Hosing, C., Popat, U., Ciurea, S. O., Patel, K., Lee, H. C., Manasanch, E. E., Thomas, S. K., Weber, D. M., Orlowski, R. Z., Champlin, R. E., & Qazilbash, M. H. (2019). Melphalan dose intensity for autologous stem cell transplantation (ASCT) in multiple myeloma. Biology of Blood and Marrow Transplantation, 25(3), S21. https://doi.org/10.1016/j.bbmt.2018.12.090
Article Google Scholar
Talib, A., & Randhir, T. O. (2017). Managing emerging contaminants in watersheds: Need for comprehensive, systems-based strategies. Sustainability of Water Quality and Ecology, 9–10, 1–8. https://doi.org/10.1016/j.swaqe.2016.05.002
Article Google Scholar
Thomas, L. M., Jorgenson, Z. G., Brigham, M. E., Choy, S. J., Moore, J. N., Banda, J. A., Gefell, D. J., Minarik, T. A., & Schoenfuss, H. L. (2017). Contaminants of emerging concern in tributaries to the Laurentian Great Lakes: II Biological Consequences of Exposure. Plos One, 12(9), e0184725. https://doi.org/10.1371/journal.pone.0184725
Article CAS Google Scholar
Thompson, W. A., & Vijayan, M. M. (2022). Antidepressants as endocrine disrupting compounds in fish. Frontiers in Endocrinology, 13. https://doi.org/10.3389/fendo.2022.895064
Tsangaris, C., Kormas, K., Strogyloudi, E., Hatzianestis, I., Neofitou, C., Andral, B., & Galgani, F. (2010). Multiple biomarkers of pollution effects in caged mussels on the Greek coastline. Comparative Biochemistry and Physiology Part C: Toxicology Pharmacology, 151(3), 369–378. https://doi.org/10.1016/j.cbpc.2009.12.009
Article CAS Google Scholar
U.S. Environmental Protection Agency, (2007). Method 1694: Pharmaceuticals and personal care products in water, soil, sediment, and biosolids by HPLC/MS/MS: USEPA, Washington, DC, EPA-821-R-08-008, 77 p. https://www.epa.gov/sites/default/files/2015-10/documents/method_1694_2007.pdf
Van Boeckel, T. P., Gandra, S., Ashok, A., Caudron, Q., Grenfell, B. T., Levin, S. A., & Laxminarayan, R. (2014). Global antibiotic consumption 2000 to 2010: An analysis of national pharmaceutical sales data. Lancet Infectious Diseases, 14(8), 742–750. https://doi.org/10.1016/s1473-3099(14)70780-7
Article Google Scholar
Viarengo, A., Lowe, D., Bolognesi, C., Fabbri, E., & Koehler, A. (2007). The use of biomarkers in biomonitoring: A 2-tier approach assessing the level of pollutant-induced stress syndrome in sentinel organisms. Comparative Biochemistry and Physiology Part C: Toxicology and Pharmacology, 146(3), 281–300. https://doi.org/10.1016/j.cbpc.2007.04.011
Article CAS Google Scholar
Wang, J., & Chu, L. (2016). Irradiation treatment of pharmaceutical and personal care products (PPCPs) in water and wastewater: An overview. Radiation Physics and Chemistry, 125, 56–64. https://doi.org/10.1016/j.radphyschem.2016.03.012
Article CAS Google Scholar
Wilkinson, J., Hooda, P. S., Barker, J., Barton, S., & Swinden, J. (2017). Occurrence, fate and transformation of emerging contaminants in water: An overarching review of the field. Environmental Pollution, 231, 954–970. https://doi.org/10.1016/j.envpol.2017.08.032
Wolter, P. T., Johnston, C. A., & Niemi, G. J. (2006). Land use land cover change in the U.S. Great Lakes Basin 1992 to 2001. Journal of Great Lakes Research, 32(3), 607–628. https://doi.org/10.3394/0380-1330(2006)32[607:LULCCI]2.0.CO;2
Article Google Scholar
Woolnough, D. A., Bellamy, A., Hummel, S. L., & Annis, M. (2020). Environmental exposure of freshwater mussels to contaminants of emerging concern: Implications for species conservation. Journal of Great Lakes Research, 46(6), 1625–1638. https://doi.org/10.1016/j.jglr.2020.10.001
Wu, C., Witter, J. D., Spongberg, A. L., & Czajkowski, K. P. (2009). Occurrence of selected pharmaceuticals in an agricultural landscape, western Lake Erie Basin. Water Research, 43(14), 3407–3416. https://doi.org/10.1016/j.watres.2009.05.014
Article CAS Google Scholar
Yadav, A., Rene, E. R., Mandal, M. K., & Dubey, K. K. (2021). Threat and sustainable technological solution for antineoplastic drugs pollution: Review on a persisting global issue. Chemosphere, 263, 128285. https://doi.org/10.1016/j.chemosphere.2020.128285
Article CAS Google Scholar
Yang, L., **, S., Danielson, P., Homer, C., Gass, L., Bender, S. M., Case, A., Costello, C., Dewitz, J., Fry, J., Funk, M., Granneman, B., Liknes, G. C., Rigge, M., & **an, G. (2018). A new generation of the United States National Land Cover Database: Requirements, research priorities, design, and implementation strategies. ISPRS Journal of Photogrammetry and Remote Sensing, 146, 108–123. https://doi.org/10.1016/j.isprsjprs.2018.09.006
Article Google Scholar
Yang, Z., Lu, T., Zhu, Y., Zhang, Q., Zhou, Z., Pan, X., & Qian, H. (2019). Aquatic ecotoxicity of an antidepressant, sertraline hydrochloride, on microbial communities. Science of the Total Environment, 654, 129–134. https://doi.org/10.1016/j.scitotenv.2018.11.164
Article CAS Google Scholar
Zakari-Jiya, A., Frazzoli, C., Obasi, C. N., Babatunde, B. B., Patrick-Iwuanyanwu, K. C., & Orisakwe, O. E. (2022). Pharmaceutical and personal care products as emerging environmental contaminants in Nigeria: A systematic review. Environmental Toxicology and Pharmacology, 94, 103914. https://doi.org/10.1016/j.etap.2022.103914

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Funding

Funding for research was provided by the Great Lakes Restoration Initiative and NOAA National Centers for Coastal Ocean Science.

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Authors and Affiliations

Monitoring and Assessment Branch, NOAA/NOS/NCCOS, 1305 East/West Highway, Silver Spring, MD, 20910, USA
Edwards M. A., Kimbrough K., Davenport E., Freitag A., K. & Johnson E.
CSS-Inc., Under NOAA National Centers for Coastal Ocean Science Contract No, EA133C17BA0062 & EA133C17BA0049, Fairfax, VA, USA
Fuller N., Rider M., Regan S., Burkart H. & Jacob A.

Authors

Edwards M. A.
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Kimbrough K.
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Fuller N.
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Davenport E.
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Rider M.
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Freitag A.
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Regan S.
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Leight A
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K.
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Burkart H.
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Jacob A.
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Johnson E.
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Contributions

Michael A. Edwards: conceptualization; data curation; formal analysis; investigation; visualization; methodology; writing — original draft; writing — review and editing. Kimani Kimbrough: conceptualization; data curation; formal analysis; visualization; writing — review and editing. Neil Fuller: fata curation; writing — review and editing. Erik Davenport: formal analysis; data curation; writing — review and editing. Amy Freitag: writing — review and editing. Mary Rider: writing — review and editing. Seann Regan: data curation; writing — review and editing. Andrew. K. Leight: writing — review and editing. Heidi Burkart: writing — review and editing. Anne Jacobs: writing — review and editing. Edward Johnson: data curation; funding acquisition.

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Correspondence to Edwards M. A..

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M. A., E., K., K., N., F. et al. An assessment and characterization of pharmaceuticals and personal care products (PPCPs) within the Great Lakes Basin: Mussel Watch Program (2013–2018). Environ Monit Assess 196, 345 (2024). https://doi.org/10.1007/s10661-023-12119-3

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Received: 14 August 2023
Accepted: 08 November 2023
Published: 05 March 2024
DOI: https://doi.org/10.1007/s10661-023-12119-3

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An assessment and characterization of pharmaceuticals and personal care products (PPCPs) within the Great Lakes Basin: Mussel Watch Program (2013–2018)

Abstract

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Introduction

Methods

Study area

Site designation and categorization

Sampling procedures

Chemical analysis

Quality assurance and quality control

Data analysis

Land-use and point source data

PPCP basin-wide and reference site assessment

PPCP discharge type assessment

PPCP relationship to land-use gradients

Conclusion

Data availability

References

Funding

Author information

Authors and Affiliations

Contributions

Corresponding author

Ethics declarations

Ethical approval

Consent to participate

Competing interests

Additional information

Publisher's Note

Supplementary Information

Supplementary file1 (DOCX 1543 KB)

Supplementary file2 (XLSX 145 KB)

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About this article

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