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USGS2018

Temporal and spatial variation in pharmaceutical concentrations in an urban river system

Many studies have quantified pharmaceuticals in the environment, few however, have incorporated detailed temporal and spatial variability due to associated costs in terms of time and materials. Here, we target 33 physico-chemically diverse pharmaceuticals in a spatiotemporal exposure study into the occurrence of pharmaceuticals in the wastewater system and the Rivers Ouse and Foss (two diverse river systems) in the city of York, UK. Removal rates in two of the WWTPs sampled (a conventional activated sludge (CAS) and trickling filter plant) ranged from not eliminated (carbamazepine) to >99% (paracetamol). Data comparisons indicate that pharmaceutical exposures in river systems are highly variable regionally, in part due to variability in prescribing practices, hydrology, wastewater management, and urbanisation and that select annual median pharmaceutical concentrations observed in this study were higher than those previously observed in the European Union and Asia thus far. Significant spatial variability was found between all sites in both river systems, while seasonal variability was significant for 86% and 50% of compounds in the River Foss and Ouse, respectively. Seasonal variations in flow, in-stream attenuation, usage and septic effluent releases are suspected drivers behind some of the observed temporal exposure variability. When the data were used to evaluate a simple environmental exposure model for pharmaceuticals, mean ratios of predicted environmental concentrations (PECs), obtained using the model, to measured environmental concentrations (MECs) were 0.51 and 0.04 for the River Foss and River Ouse, respectively. Such PEC/MEC ratios indicate that the model underestimates actual concentrations in both river systems, but to a much greater extent in the larger River Ouse.

River Foss, River Ouse↗

USGS2018

Minimum energy requirements for desalination of brackish groundwater in the United States with comparison to international datasets

This paper uses chemical and physical data from a large 2017 U.S. Geological Survey groundwater dataset with wells in the U.S. and three smaller international groundwater datasets with wells primarily in Australia and Spain to carry out a comprehensive investigation of brackish groundwater composition in relation to minimum desalination energy costs. First, we compute the site-specific least work required for groundwater desalination. Least work of separation represents a baseline for specific energy consumption of desalination systems. We develop simplified equations based on the U.S. data for least work as a function of water recovery ratio and a proxy variable for composition, either total dissolved solids, specific conductance, molality or ionic strength. We show that the U.S. correlations for total dissolved solids and molality may be applied to the international datasets. We find that total molality can be used to calculate the least work of dilute solutions with very high accuracy. Then, we examine the effects of groundwater solute composition on minimum energy requirements , showing that separation requirements increase from calcium to sodium for cations and from sulfate to bicarbonate to chloride for anions , for any given TDS concentration. We study the geographic distribution of least work, total dissolved solids, and major ions concentration across the U.S. We determine areas with both low least work and high water stress in order to highlight regions holding potential for desalination to decrease the disparity between high water demand and low water supply. Finally, we discuss the implications of the USGS results on water resource planning, by comparing least work to the specific energy consumption of brackish water reverse osmosis plants and showing the scaling propensity of major electrolytes and silica in the U.S. groundwater samples.

Water Research↗

USGS2019

Standardized data quality acceptance criteria for a rapid Escherichia coli qPCR method (Draft Method C) for water quality monitoring at recreational beaches

There is growing interest in the application of rapid quantitative polymerase chain reaction (qPCR) and other PCR-based methods for recreational water quality monitoring and management programs. This interest has strengthened given the publication of U.S. Environmental Protection Agency (EPA)-validated qPCR methods for enterococci fecal indicator bacteria (FIB) and has extended to similar methods for Escherichia coli ( E. coli ) FIB. Implementation of qPCR-based methods in monitoring programs can be facilitated by confidence in the quality of the data produced by these methods. Data quality can be determined through the establishment of a series of specifications that should reflect good laboratory practice. Ideally, these specifications will also account for the typical variability of data coming from multiple users of the method. This study developed proposed standardized data quality acceptance criteria that were established for important calibration model parameters and/or controls from a new qPCR method for E. coli (EPA Draft Method C) based upon data that was generated by 21 laboratories. Each laboratory followed a standardized protocol utilizing the same prescribed reagents and reference and control materials. After removal of outliers, statistical modeling based on a hierarchical Bayesian method was used to establish metrics for assay standard curve slope, intercept and lower limit of quantification that included between-laboratory, replicate testing within laboratory, and random error variability. A nested analysis of variance (ANOVA) was used to establish metrics for calibrator/positive control, negative control, and replicate sample analysis data. These data acceptance criteria should help those who may evaluate the technical quality of future findings from the method, as well as those who might use the method in the future. Furthermore, these benchmarks and the approaches described for determining them may be helpful to method users seeking to establish comparable laboratory-specific criteria if changes in the reference and/or control materials must be made.

Water Research↗

USGS2019

Evaluation of multiple laboratory performance and variability in analysis of recreational freshwaters by a rapid Escherichia coli qPCR method (Draft Method C)

There is interest in the application of rapid quantitative polymerase chain reaction (qPCR) methods for recreational freshwater quality monitoring of the fecal indicator bacteria Escherichia coli ( E. coli ). In this study we determined the performance of 21 laboratories in meeting proposed, standardized data quality acceptance (QA) criteria and the variability of target gene copy estimates from these laboratories in analyses of 18 shared surface water samples by a draft qPCR method developed by the U.S. Environmental Protection Agency (EPA) for E. coli . The participating laboratories ranged from academic and government laboratories with more extensive qPCR experience to “new” water quality and public health laboratories with relatively little previous experience in most cases. Failures to meet QA criteria for the method were observed in 24% of the total 376 test sample analyses. Of these failures, 39% came from two of the “new” laboratories. Likely factors contributing to QA failures included deviations in recommended procedures for the storage and preparation of reference and control materials. A master standard curve calibration model was also found to give lower overall variability in log 10 target gene copy estimates than the delta-delta Ct (ΔΔCt) calibration model used in previous EPA qPCR methods. However, differences between the mean estimates from the two models were not significant and variability between laboratories was the greatest contributor to overall method variability in either case. Study findings demonstrate the technical feasibility of multiple laboratories implementing this or other qPCR water quality monitoring methods with similar data quality acceptance criteria but suggest that additional practice and/or assistance may be valuable, even for some more generally experienced qPCR laboratories. Special attention should be placed on providing and following explicit guidance on the preparation, storage and handling of reference and control materials.

Water Research↗

USGS2020

Assessing the water quality impacts of two Category-5 hurricanes on St. Thomas, Virgin Islands

Managing waterborne and water-related diseases is one of the most critical factors in the aftermath of hurricane-induced natural disasters. The goal of the study was to identify water-quality impairments in order to set the priorities for post-hurricane relief and to guide future decisions on disaster preparation and relief administration. Field investigations were carried out on St. Thomas, U.S. Virgin Islands as soon as the disaster area became accessible after the back-to-back hurricane strikes by Irma and Maria in 2017. Water samples were collected from individual household rain cisterns, the coastal ocean, and street-surface runoffs for microbial concentration. The microbial community structure and the occurrence of potential human pathogens were investigated in samples using next generation sequencing. Loop mediated isothermal amplification was employed to detect fecal indicator bacteria, Enterococcus faecalis . The results showed both fecal indicator bacteria and Legionella genetic markers were prevalent but were low in concentration in the water samples. Among the 22 cistern samples, 86% were positive for Legionella and 82% for Escherichia-Shigella . Enterococcus faecalis was detected in over 68% of the rain cisterns and in 60% of the coastal waters (n = 20). Microbial community composition in coastal water samples was significantly different from cistern water and runoff water. Although identification at bacterial genus level is not direct evidence of human pathogens, our results suggest cistern water quality needs more organized attention for protection of human health, and that preparation and prevention measures should be taken before natural disasters strike.

Water Research↗

USGS2020

Interaction of bacterial communities and indicators of water quality in shoreline sand, sediment, and water of Lake Michigan

Shoreline sand harbors high concentrations of fecal indicator bacteria (FIB) that may be resuspended into the water column through washing and resuspension. Studies have explored coastal processes that influence this sand-water flux for FIB, but little is known about how microbial markers of contamination or the bacterial community interact in the sand-water interface. In this study, we take a three-tiered approach to explore the relationship between bacteria in sand, sediment, and overlying water at three shoreline sites and two associated rivers along an extended freshwater shoreline. Samples were collected over two years and analyzed for FIB, two microbial source tracking (MST) markers ( Catellicoccus marimammalium, Gull2; Bacteroides HF183), and targeted metagenomic 16S rRNA gene analysis. FIB was much higher in sand than in water at all three sites. Gull2 marker was abundant in shoreline sand and water while HF183 marker was mostly present in rivers. Overall bacterial communities were dissimilar between sand/sediment and water, indicating little interaction. Sediment composition was generally unfavorable to bacterial resuspension. Results show that FIB and MST markers were effective estimates of short-term conditions at these locations, and bacterial communities in sand and sediment reflected longer-term conditions. Findings are useful for locating contamination sources and targeting restoration by evaluating scope of shoreline degradation.

Lake Michigan↗

USGS2020

Viral, bacterial, and protozoan pathogens and fecal markers in wells supplying groundwater to public water systems in Minnesota, USA

Drinking water supply wells can be contaminated by a broad range of waterborne pathogens. However, groundwater assessments frequently measure microbial indicators or a single pathogen type, which provides a limited characterization of potential health risk. This study assessed contamination of wells by testing for viral, bacterial, and protozoan pathogens and fecal markers. Wells supplying groundwater to community and noncommunity public water systems in Minnesota, USA (n = 145) were sampled every other month over one or two years and tested using 23 qPCR assays. Eighteen genetic targets were detected at least once, and microbiological contamination was widespread (96% of 145 wells, 58% of 964 samples). The sewage-associated microbial indicators HF183 and pepper mild mottle virus were detected frequently. Human or zoonotic pathogens were detected in 70% of wells and 21% of samples by qPCR, with Salmonella and Cryptosporidium detected more often than viruses. Samples positive by qPCR for adenovirus (HAdV), enterovirus, or Salmonella were analyzed by culture and for genotype or serotype. qPCR-positive Giardia and Cryptosporidium samples were analyzed by immunofluorescent assay (IFA), and IFA and qPCR concentrations were correlated. Comparisons of indicator and pathogen occurrence at the time of sampling showed that total coliforms, HF183, and Bacteroidales -like HumM2 had high specificity and negative predictive values but generally low sensitivity and positive predictive values. Pathogen-HF183 ratios in sewage have been used to estimate health risks from HF183 concentrations in surface water, but in our groundwater samples Cryptosporidium oocyst:HF183 and HAdV:HF183 ratios were approximately 10,000 times higher than ratios reported for sewage. qPCR measurements provided a robust characterization of microbiological water quality, but interpretation of qPCR data in a regulatory context is challenging because few studies link qPCR measurements to health risk.

Minnesota↗

USGS2020

The role of phosphorus and nitrogen on chlorophyll a: Evidence from hundreds of lakes

The effect of nutrients on phytoplankton biomass in lakes continues to be a subject of debate by aquatic scientists. However, determining whether or not chlorophyll a (CHL) is limited by phosphorus (P) and/or nitrogen (N) is rarely considered using a probabilistic method in studies of hundreds of lakes across broad spatial extents. Several studies have applied a unified CHL-nutrient relationship to determine nutrient limitation, but pose a risk of ecological fallacy because they neglect spatial heterogeneity in ecological contexts. To examine whether or not CHL is limited by P, N, or both nutrients in hundreds of lakes and across diverse ecological settings, a probabilistic machine learning method, Bayesian Network, was applied. Spatial heterogeneity in ecological context was accommodated by the probabilistic nature of the results. We analyzed data from 1382 lakes in 17 US states to evaluate the cause-effect relationships between CHL and nutrients. Observations of CHL, total phosphorus (TP), and total nitrogen (TN) were discretized into three trophic states (oligo-mesotrophic, eutrophic, and hypereutrophic) to train the model. We found that although both nutrients were related to CHL trophic state, TP was more related to CHL than TN, especially under oligo-mesotrophic and eutrophic CHL conditions. However, when the CHL trophic state was hypereutrophic, both TP and TN were important. These results provide additional evidence that P-limitation is more likely under oligo-mesotrophic or eutrophic CHL conditions and that co-limitation of P and N occurs under hypereutrophic CHL conditions. We also found a decreasing pattern of the TN/TP ratio with increasing CHL concentrations, which might be a key driver for the role change of nutrients. Previous work performed at smaller scales support our findings, indicating potential for extension of our findings to other regions. Our findings enhance the understanding of nutrient limitation at macroscales and revealed that the current debate on the limiting nutrient might be caused by failure to consider CHL trophic state. Our findings also provide prior information for the site-specific eutrophication management of unsampled or data-limited lakes.

Water Research↗

USGS2021

Nutrient limitation of phytoplankton in Chesapeake Bay: Development of an empirical approach for water-quality management

Understanding the temporal and spatial roles of nutrient limitation on phytoplankton growth is necessary for developing successful management strategies. Chesapeake Bay has well-documented seasonal and spatial variations in nutrient limitation, but it remains unknown whether these patterns of nutrient limitation have changed in response to nutrient management efforts. We analyzed historical data from nutrient bioassay experiments (1992–2002) and data from long-term, fixed-site water-quality monitoring program (1990–2017) to develop empirical approaches for predicting nutrient limitation in the surface waters of the mainstem Bay. Results from classification and regression trees (CART) matched the seasonal and spatial patterns of bioassay-based nutrient limitation in the 1992–2002 period much better than two simpler, non-statistical approaches. An ensemble approach of three selected CART models satisfactorily reproduced the bioassay-based results (classification rate = 99%). This empirical approach can be used to characterize nutrient limitation from long-term water-quality monitoring data on much broader geographic and temporal scales than would be feasible using bioassays, providing a new tool for informing water-quality management. Results from our application of the approach to 21 tidal monitoring stations for the period of 2007–2017 showed modest changes in nutrient limitation patterns, with expanded areas of nitrogen-limitation and contracted areas of nutrient saturation (i.e., not limited by nitrogen or phosphorus). These changes imply that long-term reductions in nitrogen load have led to expanded areas with nutrient-limited phytoplankton growth in the Bay, reflecting long-term water-quality improvements in the context of nutrient enrichment. However, nutrient limitation patterns remain unchanged in the majority of the mainstem, suggesting that nutrient loads should be further reduced to achieve a less nutrient-saturated ecosystem.

Maryland, Virginia↗

USGS2020

Evaluating the impacts of foreshore sand and birds on microbiological contamination at a freshwater beach

Beaches along the Great Lakes shorelines are important recreational and economic resources. However, contamination at the beaches can threaten their usage during the swimming season, potentially resulting in beach closures and/or advisories. Thus, understanding the dynamics that control nearshore water quality is integral to effective beach management. There have been significant improvements in this effort, including incorporating modeling (empirical, mechanistic) in recent years. Mechanistic modeling frameworks can contribute to this understanding of dynamics by determining sources and interactions that substantially impact fecal indicator bacteria concentrations, an index routinely used in water quality monitoring programs. To simulate E. coli concentrations at Jeorse Park beaches in southwest Lake Michigan, a coupled hydrodynamic and wave–current interaction model was developed that progressively added contaminant sources from river inputs, avian presence, bacteria–sediment interactions, and bacteria–sand–sediment interactions. Results indicated that riverine inputs affected E. coli concentrations at Jeorse Park beaches only marginally, while avian, shoreline sand, and sediment sources were much more substantial drivers of E. coli contamination at the beach. By including avian and riverine inputs, as well as bacteria–sand–sediment interactions at the beach, models can reasonably capture the variability in observed E. coli concentrations in nearshore water and bed sediments at Jeorse Park beaches. Consequently, it will be crucial to consider avian contamination sources and water-sand-sediment interactions in effective management of the beach for public health and as a recreational resource and to extend these findings to similar beaches affected by shoreline embayment.

Illlinois↗

USGS2021

Partitioning and transformation of organic and inorganic phosphorus among dissolved, colloidal and particulate phases in a hypereutrophic freshwater estuary

Phosphorus (P) loadings to the Great Lakes have been regulated for decades, but re-eutrophication and seasonal hypoxia have recently been increasingly reported. It is of paramount importance to better understand the fate, transformation, and biogeochemical cycling processes of different P species across the river-lake interface. We report here results on chemical speciation of P in the seasonally hypoxic Fox River-Green Bay system and variations in sources and partitioning of P species along the aquatic continuum. During midsummer when productivity is generally high, phosphate and dissolved organic P (DOP) were the major species in river water while particulate-organic-P predominated in open bay waters, showing a dynamic change in the chemical speciation of P along the river-bay transect with active transformations between inorganic and organic P and between colloidal and particulate phases. Colloidal organic P (COP, >1 kDa) comprised 33‒65% of the bulk DOP, while colloidal inorganic P was generally insignificant and undetectable especially in open bay water. Sources of COP changed from mainly allochthonous in the Fox River, having mostly smaller sized colloids (1–3 kDa) and a lower organic carbon to phosphorus (C/P) ratio, to predominantly autochthonous in open bay waters with larger sized colloids (>10 kDa) and a higher organic C/P ratio. The observed high apparent distribution coefficients ( K d ) of P between dissolved and particulate phases and high-abundant autochthonous colloidal and particulate organic P in the hypereutrophic environment suggest that, in addition to phosphate, colloidal/particulate organic P may play a critical role in the biogeochemical cycling of P and the development of seasonal hypoxia.

Wisconsin↗

USGS2021

Assessing cyanobacterial frequency and abundance at surface waters near drinking water intakes across the United States

This study presents the first large-scale assessment of cyanobacterial frequency and abundance of surface water near drinking water intakes across the United States. Public water systems serve drinking water to nearly 90% of the United States population. Cyanobacteria and their toxins may degrade the quality of finished drinking water and can lead to negative health consequences. Satellite imagery can serve as a cost-effective and consistent monitoring technique for surface cyanobacterial blooms in source waters and can provide drinking water treatment operators information for managing their systems. This study uses satellite imagery from the European Space Agency's Ocean and Land Colour Instrument (OLCI) spanning June 2016 through April 2020. At 300-m spatial resolution, OLCI imagery can be used to monitor cyanobacteria in 685 drinking water sources across 285 lakes in 44 states, referred to here as resolvable drinking water sources. First, a subset of satellite data was compared to a subset of responses ( n = 84) submitted as part of the U.S. Environmental Protection Agency's fourth Unregulated Contaminant Monitoring Rule (UCMR 4). These UCMR 4 qualitative responses included visual observations of algal bloom presence and absence near drinking water intakes from March 2018 through November 2019. Overall agreement between satellite imagery and UCMR 4 qualitative responses was 94% with a Kappa coefficient of 0.70. Next, temporal frequency of cyanobacterial blooms at all resolvable drinking water sources was assessed. In 2019, bloom frequency averaged 2% and peaked at 100%, where 100% indicated a bloom was always present at the source waters when satellite imagery was available. Monthly cyanobacterial abundances were used to assess short-term trends across all resolvable drinking water sources and effect size was computed to provide insight on the number of years of data that must be obtained to increase confidence in an observed change. Generally, 2016 through 2020 was an insufficient time period for confidently observing changes at these source waters; on average, a decade of satellite imagery would be required for observed environmental trends to outweigh variability in the data. However, five source waters did demonstrate a sustained short-term trend, with one increasing in cyanobacterial abundance from June 2016 to April 2020 and four decreasing.

Water Research↗

USGS2021

Tandem field and laboratory approaches to quantify attenuation mechanisms of pharmaceutical and pharmaceutical transformation products in a wastewater effluent-dominated stream

Evolving complex mixtures of pharmaceuticals and transformation products in effluent-dominated streams pose potential impacts to aquatic species; thus, understanding the attenuation dynamics in the field and characterizing the prominent attenuation mechanisms of pharmaceuticals and their transformation products (TPs) is critical for hazard assessments. Herein, we determined the attenuation dynamics and the associated prominent mechanisms of pharmaceuticals and their corresponding TPs via a combined long-term field study and controlled laboratory experiments. For the field study, we quantified spatiotemporal exposure concentrations of five pharmaceuticals and six associated TPs in a small, temperate-region effluent-dominated stream during baseflow conditions where the wastewater plant was the main source of pharmaceuticals. We selected four sites (upstream, at, and two progressively downstream from effluent discharge) and collected water samples at 16 time points (64 samples in total, approximately twice monthly, depending on flows) for 1 year. Concurrently, we conducted photolysis, sorption, and biodegradation batch tests under controlled conditions to determine the major attenuation mechanisms. We observed 10-fold greater attenuation rates in the field compared to batch tests, demonstrating that connecting laboratory batch tests with field measurements to enhance predictive power is a critical need. Batch systems alone, often used for assessment, are useful for determining fate processes but poorly approximate in-stream attenuation kinetics. Sorption was the dominant attenuation process (t 1/2 <7.7 d) for 5 of 11 compounds in the batch tests, while the other compounds ( n = 6) persisted in the batch tests and along the 5.1 km stream reach. In-stream parent-to-product transformation was minimal. Differential attenuation contributed to the evolving pharmaceutical mixture and created changing exposure conditions with concomitant implications for aquatic and terrestrial biota. Tandem field and laboratory characterization can better inform modeling efforts for transport and risk assessments.

Water Research↗

USGS2021

Evaluating the impact of watershed development and climate change on stream ecosystems: A Bayesian network modeling approach

A continuous-variable Bayesian network (cBN) model is used to link watershed development and climate change to stream ecosystem indicators. A graphical model, reflecting our understanding of the connections between climate change, weather condition, loss of natural land cover, stream flow characteristics , and stream ecosystem indicators is used as the basis for selecting flow metrics for predicting macroinvertebrate-based indicators. Selected flow metrics were then linked to variables representing watershed development and climate change. We fit the model to data from two river basins in southeast US and the resulting model was used to simulate future stream ecological conditions using projected future climate and development scenarios. The three climate models predicted varying ecological condition trajectories, but similar worst-case ecological conditions. The established modeling approach couples mechanistic understanding with field data to develop predictions of management-relevant variables across a heterogeneous landscape. We discussed the transferability of the modeling approach.

North Carolina, South Carolina, Virginia↗

USGS2022

Identifying factors that affect mountain lake sensitivity to atmospheric nitrogen deposition across multiple scales

Increased nitrogen (N) deposition rates over the past century have affected both North American and European mountain lake ecosystems. Ecological sensitivity of mountain lakes to N deposition varies, however, because chemical and biological responses are modulated by local watershed and lake properties. We evaluated predictors of mountain lake sensitivity to atmospheric N deposition across North American and European mountain ranges and included as response variables dissolved inorganic N (DIN = N NH 4 + + N NO 3 – ) concentrations and phytoplankton biomass. Predictors of these responses were evaluated at three different spatial scales (hemispheric, regional, subregional) using regression tree, random forest, and generalized additive model (GAM) analysis. Analyses agreed that Northern Hemisphere mountain lake DIN was related to N deposition rates and smaller scale spatial variability (e.g., regional variability between North American and European lakes, and subregional variability between mountain ranges). Analyses suggested that DIN, N deposition, and subregional variability were important for Northern Hemisphere mountain lake phytoplankton biomass. Together, these findings highlight the need for finer-scale, subregional analyses (by mountain range) of lake sensitivity to N deposition. Subregional analyses revealed differences in predictor variables of lake sensitivity. In addition to N deposition rates, lake and watershed features such as land cover, bedrock geology, maximum lake depth (Z max ), and elevation were common modulators of lake DIN. Subregional phytoplankton biomass was consistently positively related with total phosphorus (TP) in Europe, while North American locations showed variable relationships with N or P. This study reveals scale-dependent watershed and lake characteristics modulate mountain lake ecological responses to atmospheric N deposition and provides important context to inform empirically based management strategies.

Water Research↗

USGS2022

Pollutant co-attenuation via in-stream interactions between mine drainage and municipal wastewater

Municipal wastewater (MWW) and mine drainage (MD) are common co-occurring sources of freshwater pollution in mining regions. The physicochemical interactions that occur after mixing MWW and MD in a waterway may improve downstream water quality of an impaired reach by reducing downstream concentrations of nutrients and metals (i.e., “co-attenuation”). A first-order stream (Bradley Run in central Pennsylvania), with coal MD and secondarily treated MWW entering the stream in the same location, was systematically monitored to determine in-stream water-quality dynamics. Monitored constituents included pH, nutrients (i.e., phosphorus and nitrogen), and metals (e.g., iron, aluminum, manganese). Mixing of the MWW, MD, and upstream water decreased concentrations of phosphate, aluminum, and iron by 94%, 91%, and 98%, respectively, relative to conservative mixtures at the 1400-m-downstream site. The pollutant co-attenuation resulted in water quality equivalent to that upstream of the pollutant sources and improved the phosphorus-based trophic status of the stream. Geochemical models indicate the primary mechanisms for P attenuation in the studied stream were precipitation as variscite (AlPO 4 :2H 2 O) or amorphous AlPO 4 plus adsorption to hydrous ferric oxide, despite a much greater abundance of hydrous aluminum oxide. The results presented in this study suggest that in-stream mixing of MD with untreated or secondarily treated MWW may be an important, overlooked factor affecting downstream transport of common pollutants in mining regions. Decreased metals loading and increased pH resulting from natural attenuation and remediation of MD could affect the potential for retention of phosphate by stream sediment and could lead to the release of nutrients from legacy accumulations, highlighting the potential need to address high-nutrient discharges (e.g., improved MWW treatment) in concert with MD remediation.

Pennsylvania↗

USGS2022

A decade of monitoring micropollutants in urban wet-weather flows: What did we learn?

Urban wet-weather discharges from combined sewer overflows (CSO) and stormwater outlets (SWO) are a potential pathway for micropollutants (trace contaminants) to surface waters, posing a threat to the environment and possible water reuse applications. Despite large efforts to monitor micropollutants in the last decade, the gained information is still limited and scattered. In a metastudy we performed a data-driven analysis of measurements collected at 77 sites (683 events, 297 detected micropollutants) over the last decade to investigate which micropollutants are most relevant in terms of 1) occurrence and 2) potential risk for the aquatic environment, 3) estimate the minimum number of data to be collected in monitoring studies to reliably obtain concentration estimates, and 4) provide recommendations for future monitoring campaigns. We highlight micropollutants to be prioritized due to their high occurrence and critical concentration levels compared to environmental quality standards. These top-listed micropollutants include contaminants from all chemical classes (pesticides, heavy metals, polycyclic aromatic hydrocarbons, personal care products, pharmaceuticals, and industrial and household chemicals). Analysis of over 30,000 event mean concentrations shows a large fraction of measurements (> 50%) were below the limit of quantification, stressing the need for reliable, standard monitoring procedures. High variability was observed among events and sites, with differences between micropollutant classes. The number of events required for a reliable estimate of site mean concentrations (error bandwidth of 1 around the “true" value) depends on the individual micropollutant. The median minimum number of events is 7 for CSO (2 to 31, 80%-interquantile) and 6 for SWO (1 to 25 events, 80%-interquantile). Our analysis indicates the minimum number of sites needed to assess global pollution levels and our data collection and analysis can be used to estimate the required number of sites for an urban catchment. Our data-driven analysis demonstrates how future wet-weather monitoring programs will be more effective if the consequences of high variability inherent in urban wet-weather discharges are considered.

Water Research↗

USGS2023

Using cyanobacteria and other phytoplankton to assess trophic conditions: A qPCR-based, multi-year study in twelve large rivers across the United States

Phytoplankton is the essential primary producer in fresh surface water ecosystems. However, excessive phytoplankton growth due to eutrophication significantly threatens ecologic, economic, and public health. Therefore, phytoplankton identification and quantification are essential to understanding the productivity and health of freshwater ecosystems as well as the impacts of phytoplankton overgrowth (such as Cyanobacterial blooms) on public health. Microscopy is the gold standard for phytoplankton assessment but is time-consuming, has low throughput, and requires rich experience in phytoplankton morphology. Quantitative polymerase chain reaction (qPCR) is accurate and straightforward with high throughput. In addition, qPCR does not require expertise in phytoplankton morphology. Therefore, qPCR can be a useful alternative for molecular identification and enumeration of phytoplankton. Nonetheless, a comprehensive study is missing which evaluates and compares the feasibility of using qPCR and microscopy to assess phytoplankton in fresh water. This study 1) compared the performance of qPCR and microscopy in identifying and quantifying phytoplankton and 2) evaluated qPCR as a molecular tool to assess phytoplankton and indicate eutrophication. We assessed phytoplankton using both qPCR and microscopy in twelve large freshwater rivers across the United States from early summer to late fall in 2017, 2018, and 2019. qPCR- and microscope-based phytoplankton abundance had a significant positive linear correlation (adjusted R 2 = 0.836, p -value < 0.001). Phytoplankton abundance had limited temporal variation within each sampling season and over the three years studied. The sampling sites in the midcontinent rivers had higher phytoplankton abundance than those in the eastern and western rivers. For instance, the concentration (geometric mean) of Bacillariophyta, Cyanobacteria, Chlorophyta, and Dinoflagellates at the sampling sites in the midcontinent rivers was approximately three times that at the sampling sites in the western rivers and approximately 18 times that at the sampling sites in the eastern rivers. Welch's analysis of variance indicates that phytoplankton abundance at the sampling sites in the midcontinent rivers was significantly higher than that at the sampling sites in the eastern rivers ( p -value = 0.013) but was comparable to that at the sampling sites in the western rivers ( p -value = 0.095). The higher phytoplankton abundance at the sampling sites in the midcontinent rivers was presumably because these rivers were more eutrophic. Indeed, low phytoplankton abundance occurred in oligotrophic or low trophic sites, whereas eutrophic sites had greater phytoplankton abundance. This study demonstrates that qPCR-based phytoplankton abundance can be a useful numerical indicator of the trophic conditions and water quality in freshwater rivers.

Water Research↗