A multi-marker assessment of sewage contamination in streams using human-associated indicator bacteria, human-specific viruses, and pharmaceuticals.

Human sewage contaminates waterways, delivering excess nutrients, pathogens, chemicals, and other toxic contaminants. Contaminants and various sewage indicators are measured to monitor and assess water quality, but these analytes vary in their representation of sewage contamination and the inferences about water quality they support. We measured the occurrence and concentration of multiple microbiological (n = 21) and chemical (n = 106) markers at two urban stream locations in Milwaukee, Wisconsin, USA over two years. Five-day composite water samples (n = 98) were collected biweekly, and sewage influent samples (n = 25) were collected monthly at a Milwaukee, WI water reclamation facility. We found the vast majority of markers were not sensitive enough to detect sewage contamination. To compare analytes for monitoring applications, five consistently detected human sewage indicators were used to evaluate temporal patterns of sewage contamination, including microbiological (pepper mild mottle virus, human Bacteroides, human Lachnospiraceae) and chemical (acetaminophen, metformin) markers. The proportion of human sewage in each stream was estimated using the mean influent concentration from the water reclamation facility and the mean concentration of all stream samples for each sewage indicator marker. Estimates of instream sewage pollution varied by marker, differing by up to two orders of magnitude, but four of the five sewage markers characterized Underwood Creek (mean proportions of human sewage ranged 0.0025 % - 0.075 %) as less polluted than Menomonee River (proportions ranged 0.013 % - 0.14 %) by an order of magnitude more. Chemical markers correlated with each other and yielded higher estimates of sewage pollution than microbial markers, which exhibited greater temporal variability. Transport, attenuation, and degradation processes can influence chemical and microbial markers differently and cause variation in human sewage estimates. Given the range of potential human and ecological health effects of human sewage contamination, robust characterization of sewage contamination that uses multiple lines of evidence supports monitoring and research applications.

Modeled predictions of human-associated and fecal-indicator bacteria concentrations and loadings in the Menomonee River, Wisconsin using in-situ optical sensors.

Human sewage contamination of waterways is a major issue in the United States and throughout the world. Models were developed for estimation of two human-associated fecal-indicator and three general fecal-indicator bacteria (HIB and FIB) using in situ optical field-sensor data for estimating concentrations and loads of HIB and FIB and the extent of sewage contamination in the Menomonee River in Milwaukee, Wisconsin. Three commercially available optical sensor platforms were installed into an unfiltered custom-designed flow-through system along with a refrigerated automatic sampler at the Menomonee River sampling location. Ten-minute optical sensor measurements were made from November 2017 to December 2018 along with the collection of 153 flow-weighted discrete water samples (samples) for HIB, FIB, dissolved organic carbon (DOC), and optical properties of water. Of those 153 samples, 119 samples were from event-runoff periods, and 34 were collected during low-flow periods. Of the 119 event-runoff samples, 43 samples were from event-runoff combined sewer overflow (CSO) influenced periods (event-CSO periods). Models included optical sensor measurements as explanatory variables with a seasonal variable as an interaction term. In some cases, separate models for event-CSO periods and non CSO-periods generally improved model performance, as compared to using all the data combined for estimates of FIB and HIB. Therefore, the CSO and non-CSO models were used in final estimations for CSO and non-CSO time periods, respectively. Estimated continuous concentrations for all bacteria markers varied over six orders of magnitude during the study period. The greatest concentrations, loads, and proportion of sewage contamination occurred during event-runoff and event-CSO periods. Comparison to water quality standards and microbial risk assessment benchmarks indicated that estimated bacteria levels exceeded recreational water quality criteria between 34 and 96% of the entire monitoring period, highlighting the benefits of high-frequency monitoring compared to traditional grab sample collection. The application of optical sensors for estimation of HIB and FIB markers provided a thorough assessment of bacterial presence and human health risk in the Menomonee River.

Phytoplankton community interactions and cyanotoxin mixtures in three recurring surface blooms within one lake.

Cyanobacteria can produce numerous secondary metabolites (cyanotoxins) with various toxicities, yet data on cyanotoxins in many lakes are limited. Moreover, little research is available on complex relations among cyanobacteria that produce toxins. Therefore, we studied cyanobacteria and 19 cyanotoxins at three sites with recurring blooms in Kabetogama Lake (USA). Seven of 19 toxins were detected in various combinations. Anabaenopeptin A and B were detected in every sample. Microcystin-YR was detected more frequently than microcystin-LR, unlike other lakes in the region. Microcystin-YR concentrations, however, generally were low; two samples exceeded drinking water guidelines and no samples exceeded recreational guidelines. Anabaenopeptins correlated with six cyanobacterial taxa, most of which lack available literature on peptide production. The potential toxin producing cyanobacteria, Microcystis, was significantly correlated to microcystin-YR. Pseudanabaena sp. and Synechococcus sp. had strong negative correlations with several toxins that may indicate competition or stress between organisms. Non-metric multidimensional scaling identified three cyanobacterial pairs that may reflect symbiotic or antagonistic relations. This study highlights interactions among cyanobacteria and multiple cyanotoxins and the methods used may be useful for uncovering additional patterns in cyanobacteria communities in other systems, leading to further understanding of how those interactions lead to toxin production.

Benzotriazole concentrations in airport runoff are reduced following changes in airport deicer formulations.

A comparison of the presence of additives in airport deicers commonly used in the United States and in airport runoff was conducted with data collected before and after changes in deicer formulations. Three isomers of benzotriazoles (BTs)-4-methyl-1H-benzotriazole (4-MeBT), 5-methyl-1H-benzotriazole (5-MeBT), and 1H-benzotriazole (1H-BT)-are corrosion inhibitors added to some formulations of airport deicers and are reported to be a source of aquatic toxicity in streams receiving airport runoff. Concentrations of BT in aircraft deicers and anti-icing fluids (ADAF) were reduced over time but were not reduced in potassium acetate airfield-pavement deicer material (PDM) that was used throughout the study period. Streams receiving runoff from Milwaukee Mitchell International Airport, Milwaukee, Wisconsin, USA, were monitored from 2004 to 2019 for BTs, with concentrations of 4-MeBT varying from <0.35 to 4600 µg/L, 5-MeBT varying from <0.25 to 6600 µg/L, and 1H-BT varying from <0.25 to 150 µg/L. Median 4-MeBT concentrations at sites downstream from the airport decreased by approximately 74%, 5-MeBT by 69%, and 1H-BT by 82% following reduction in BTs in ADAF formulations, resulting in a reduction in the potential for aquatic toxicity in receiving streams. A change in residuals from regression analysis between freezing point depressants and BTs indicate that the reduction in BT concentrations in airport runoff was a result of BT reduction in ADAF formulations, but PDM may still be a substantial source of BTs in airport runoff. Because BTs are a source of aquatic toxicity in airport deicers, the reductions in BTs in the common deicers observed in this study can be used to demonstrate the potential for a reduction in the effects to aquatic organisms in airport runoff, resulting in greater likelihood of meeting aquatic toxicity requirements in airport stormwater permits, and potentially driving airports, airlines, and permit holders to advocate further reduction or elimination of BTs and other harmful contaminants in airport deicers. Integr Environ Assess Manag 2022;18:245-257. Published 2021. This article is a U.S. Government work and is in the public domain in the USA. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Cyanotoxin mixture models: Relating environmental variables and toxin co-occurrence to human exposure risk.

Toxic cyanobacterial blooms, often containing multiple toxins, are a serious public health issue. However, there are no known models that predict a cyanotoxin mixture (anatoxin-a, microcystin, saxitoxin). This paper presents two cyanotoxin mixture models (MIX) and compares them to two microcystin (MC) models from data collected in 2016-2017 from three recurring cyanobacterial bloom locations in Kabetogama Lake, Voyageurs National Park (Minnesota, USA). Models include those using near-real-time environmental variables (readily available) and those using additional comprehensive variables (based on laboratory analyses). Comprehensive models (R2 = 0.87 MC; R2 = 0.86 MIX) explained more variability than the environmental models (R2 = 0.58 MC; R2 = 0.57 MIX). Although neither MIX model was a better fit than the MC models, the MIX models produced no false negatives in the calibration dataset, indicating that all observations above regulatory guidelines were simulated by the MIX models. This is the first known use of Virtual Beach software for a cyanotoxin mixture model, and the methods used in this paper may be applicable to other lakes or beaches.

High levels of sewage contamination released from urban areas after storm events: A quantitative survey with sewage specific bacterial indicators.

BACKGROUND: Past studies have demonstrated an association between waterborne disease and heavy precipitation, and climate change is predicted to increase the frequency of these types of intense storm events in some parts of the United States. In this study, we examined the linkage between rainfall and sewage contamination of urban waterways and quantified the amount of sewage released from a major urban area under different hydrologic conditions to identify conditions that increase human risk of exposure to sewage. METHODS AND FINDINGS: Rain events and low-flow periods were intensively sampled to quantify loads of sewage based on two genetic markers for human-associated indicator bacteria (human Bacteroides and Lachnospiraceae). Samples were collected at a Lake Michigan estuary and at three river locations immediately upstream. Concentrations of indicators were analyzed using quantitative polymerase chain reaction (qPCR), and loads were calculated from streamflow data collected at each location. Human-associated indicators were found during periods of low flow, and loads increased one to two orders of magnitude during rain events from stormwater discharges contaminated with sewage. Combined sewer overflow (CSO) events increased concentrations and loads of human-associated indicators an order of magnitude greater than heavy rainfall events without CSO influence. Human-associated indicator yields (load per km2 of land per day) were related to the degree of urbanization in each watershed. Contamination in surface waters were at levels above the acceptable risk for recreational use. Further, evidence of sewage exfiltration from pipes threatens drinking water distribution systems and source water. While this study clearly demonstrates widespread sewage contamination released from urban areas, a limitation of this study is understanding human exposure and illness rates, which are dependent on multiple factors, and gaps in our knowledge of the ultimate health outcomes. CONCLUSIONS: With the prediction of more intense rain events in certain regions due to climate change, sewer overflows and contamination from failing sewer infrastructure may increase, resulting in increases in waterborne pathogen burdens in waterways. These findings quantify hazards in exposure pathways from rain events and illustrate the additional stress that climate change may have on urban water systems. This information could be used to prioritize efforts to invest in failing sewer infrastructure and create appropriate goals to address the health concerns posed by sewage contamination from urban areas.

Human-Associated Indicator Bacteria and Human-Specific Viruses in Surface Water: A Spatial Assessment with Implications on Fate and Transport.

Hydrologic, seasonal, and spatial variability of sewage contamination was studied at six locations within a watershed upstream from water reclamation facility (WRF) effluent to define relative loadings of sewage from different portions of the watershed. Fecal pollution from human sources was spatially quantified by measuring two human-associated indicator bacteria (HIB) and eight human-specific viruses (HSV) at six stream locations in the Menomonee River watershed in Milwaukee, Wisconsin from April 2009 to March 2011. A custom, automated water sampler, which included HSV filtration, was deployed at each location and provided unattended, flow-weighted, large-volume (30-913 L) sampling. In addition, wastewater influent samples were composited over discrete 7 day periods from the two Milwaukee WRFs. Of the 8 HSV, only 3 were detected, present in up to 38% of the 228 stream samples, while at least 1 HSV was detected in all WRF influent samples. HIB occurred more often with significantly higher concentrations than the HSV in stream and WRF influent samples ( p < 0.05). HSV yield calculations showed a loss from upstream to the most-downstream sub-watershed of the Menomonee River, and in contrast, a positive HIB yield from this same sub-watershed emphasizes the complexity in fate and transport properties between HSV and HIB. This study demonstrates the utility of analyzing multiple HSV and HIB to provide a weight-of-evidence approach for assessment of fecal contamination at the watershed level, provides an assessment of relative loadings for prioritizing areas within a watershed, and demonstrates how loadings of HSV and HIB can be inconsistent, inferring potential differences in fate and transport between the two indicators of human fecal presence.