Autonomous online measurement of β-D-glucuronidase activity in surface water: is it suitable for rapid E. coli monitoring?

Investigating the suitability of online flow cytometry for monitoring full-scale drinking water ozone system disinfection effectiveness

While online monitoring of physicochemical parameters has widely been incorporated into drinking water treatment systems, online microbial monitoring has lagged behind, resulting in the use of surrogate parameters (disinfectant residual, applied dose, concentration × time, CT) to assess disinfection system performance. Online flow cytometry (online FCM) allows for automated quantification of total and intact microbial cells. This study sought to investigate the feasibility of online FCM for full-scale drinking water ozone disinfection system performance monitoring. A water treatment plant with high lime solids turbidity in the ozone contactor influent was selected to evaluate the online FCM in challenging conditions. Total and intact cell counts were monitored for 40 days and compared to surrogate parameters (ozone residual, ozone dose, and CT) and grab sample assay results for cellular adenosine triphosphate (cATP), heterotrophic plate counts (HPC), impedance flow cytometry, and 16S rRNA gene sequencing. Online FCM provided insight into the dynamics of the full-scale ozone system, including offering early warning of increased contactor effluent cell concentrations, which was not observed using surrogate measures. Positive correlations were observed between online FCM intact cell counts and cATP levels (Kendall's tau=0.40), HPC (Kendall's tau=0.20), and impedance flow cytometry results (Kendall's tau=0.30). Though a strong correlation between log intact cell removal and CT was not observed, 16S rRNA gene sequencing results showed that passage through the ozone contactor significantly changed the microbial community (p < 0.05). Potential causes of the low overall cell inactivation in the contactor and the significant changes in the microbial community after ozonation include regrowth in the later chambers of the contactor and varied ozone resistance of drinking water microorganisms. This study demonstrates the suitability of direct, online microbial analysis for monitoring full-scale disinfection systems.

β-D-glucuronidase activity triggered monitoring of fecal contamination using microbial and chemical source tracking markers at drinking water intakes

Intense rainfall and snowmelt events may affect the safety of drinking water, as large quantities of fecal material can be discharged from storm or sewage overflows or washed from the catchment into drinking water sources. This study used β-d-glucuronidase activity (GLUC) with microbial source tracking (MST) markers: human, bovine, porcine mitochondrial DNA markers (mtDNA) and human-associated Bacteroidales HF183 and chemical source tracking (CST) markers including caffeine, carbamazepine, theophylline and acetaminophen, pathogens (Giardia, Cryptosporidium, adenovirus, rotavirus and enterovirus), water quality indicators (Escherichia coli, turbidity) and hydrometeorological data (flowrate, precipitation) to assess the vulnerability of 3 drinking water intakes (DWIs) and identify sources of fecal contamination. Water samples were collected under baseline, snow and rain events conditions in urban and agricultural catchments (Québec, Canada). Dynamics of E. coli, HF183 and WWMPs were similar during contamination events, and concentrations generally varied over 1 order of magnitude during each event. Elevated human-associated marker levels during events demonstrated that urban DWIs were impacted by recent contamination from an upstream municipal water resource recovery facility (WRRF). In the agricultural catchment, mixed fecal pollution was observed with the occurrences and increases of enteric viruses, human bovine and porcine mtDNA during peak contaminating events. Bovine mtDNA qPCR concentrations were indicative of runoff of cattle-derived fecal pollutants to the DWI from diffuse sources following rain events. This study demonstrated that the suitability of a given MST or CST indicator depend on river and catchment characteristics. The sampling strategy using continuous online GLUC activity coupled with MST and CST markers analysis was a more reliable source indicator than turbidity to identify peak events at drinking water intakes.

Progress in methods for the detection of viable Escherichia coli

Escherichia coli (E. coli) is a prevalent enteric bacterium and a necessary organism to monitor for food safety and environmental purposes. Developing efficient and specific methods is critical for detecting and monitoring viable E. coli due to its high prevalence. Conventional culture methods are often laborious and time-consuming, and they offer limited capability in detecting potentially harmful viable but non-culturable E. coli in the tested sample, which highlights the need for improved approaches. Hence, there is a growing demand for accurate and sensitive methods to determine the presence of viable E. coli. This paper scrutinizes various methods for detecting viable E. coli, including culture-based methods, molecular methods that target DNAs and RNAs, bacteriophage-based methods, biosensors, and other emerging technologies. The review serves as a guide for researchers seeking additional methodological options and aiding in the development of rapid and precise assays. Moving forward, it is anticipated that methods for detecting E. coli will become more stable and robust, ultimately contributing significantly to the improvement of food safety and public health.

Assessment of multiple fecal contamination sources in surface waters using environmental mitochondrial DNA metabarcoding

Waterborne diseases are transmitted to humans through the fecal contamination of water, where homeothermic species are the main reservoir. Fecal indicator bacteria (FIB) are often used to determine the occurrence of fecal contamination. However, FIB cannot provide the source of fecal contamination. Furthermore, as fecal inputs and contamination could originate from multiple sources (e.g., human, livestock, wildlife), multiple source tracking markers are required to identify fecal sources. From a previous study, we developed a mitochondrial DNA (mtDNA) metabarcoding approach to assess the presence of multiple homeotherms in four surface waters. Here, we have broadened our approach by sampling 86 surface water samples from the L'Assomption River and Ville-Marie watersheds (Province of Quebec, Canada). Fecal coliform levels were higher than the expected sanitary recommendations for recreational water (> 200 CFU/100 mL) in 73 % samples. The occurrence of mtDNA from human, livestock, domestic animals, wild mammals and wild birds was found in 40-88 % of the samples. Multivariate analyses showed significant covariations between homeothermic taxa and fecal coliforms, enterococci, β-D-glucuronidase, conductivity, the human-specific Bacteroidales Hf183 genetic marker, and the human population, in the watersheds of L'Assomption River (p = 0.001) and Ville-Marie (p = 0.015) (Province of Quebec, Canada). Through the application of Bayes Theorem, it was determined that fecal coliforms co-occurred with the detection of bovine, beaver, robin and chicken mtDNA in 100 % of cases in the L'Assomption River watershed, and human mtDNA co-occurred with fecal coliforms in 93 % and 76 % of cases in L'Assomption River watershed and Ville-Marie sub-catchment, respectively. This study suggests that fecal contamination could be the result of multiple species, among which some wild animals may contribute to fecal inputs in surface waters, resulting in potential risk to human health. This reinforces the necessity of using the mtDNA metabarcoding method to monitor multi-animal species.

A simple and rapid method for detecting fecal pollution in urban rivers by measuring the intrinsic β-D-glucuronidase activity of Escherichia coli

As urban rivers are domestic, industrial, and agricultural water resources, fecal pollution poses human health and environmental risks. In this study, we developed a simple and rapid method to detect fecal pollution in urban rivers. Water samples were mixed with liquid medium, including a fluorescent substrate and fluorescence intensity (F.I.) was measured using a microplate reader to determine Escherichia coli (E. coli) β-D-glucuronidase (GUS) activity instead of E. coli concentration. GUS activities measurements in pure E. coli cultures revealed that E. coli incubated with a GUS substrate accumulated GUS enzymes in their cells, whereas those incubated without a GUS substrate did not. The increase in GUS activity corresponded to the proliferation of E. coli and the GUS activity increased linearly even during the lag growth phase of E. coli, indicating the presence of intrinsic GUS (iGUS) in E. coli cells before incubation. iGUS activity persisted at 81 % in the chlorinated samples, even though the E. coli concentration was reduced by a factor of 106. The iGUS activity persisted for approximately three days. Therefore, we assumed that E. coli present in fecal contaminants, in which GUS substrates are present, could be distinguished from those surviving in the natural environment for three days or longer by measuring iGUS activity. River water samples were collected upstream and downstream of the discharge outlets of municipal wastewater treatment plants and a combined sewer outlet. The iGUS activities were <0.24 mMFU/mL for the upstream samples and >0.21 mMFU/mL for the downstream samples. Interestingly, E. coli concentrations were not necessarily associated with fecal pollution. This indicates that by setting a threshold for iGUS activity, our method can be used as a simple and rapid method for detecting fecal pollution in urban rivers. Because the limit of detection for our method is 20 CFU/mL, our method is applicable to detecting high fecal pollution in a small river.

Sensors for Coastal and Ocean Monitoring

In situ water monitoring sensors are critical to gain an understanding of ocean biochemistry and ecosystem health. They enable the collection of high-frequency data and capture ecosystem spatial and temporal changes, which in turn facilitate long-term global predictions. They are used as decision support tools in emergency situations and for risk mitigation, pollution source tracking, and regulatory monitoring. Advanced sensing platforms exist to support various monitoring needs together with state-of-the-art power and communication capabilities. To be fit-for-purpose, sensors must withstand the challenging marine environment and provide data at an acceptable cost. Significant technological advancements have catalyzed the development of new and improved sensors for coastal and oceanographic applications. Sensors are becoming smaller, smarter, more cost-effective, and increasingly specialized and diversified. This article, therefore, provides a review of the state-of-the art oceanographic and coastal sensors. Progress in sensor development is discussed in terms of performance and the key strategies used for achieving robustness, marine rating, cost reduction, and antifouling protection.

Recent advances of sensing strategies for the detection of β-glucuronidase activity

β-Glucuronidase (β-GLU), a kind of hydrolase, is widely distributed in mammalian tissues, body fluids, and microbiota. Abnormal changes of β-GLU activity are often correlated with the occurrence of diseases and deterioration of water quality. Therefore, detection of β-GLU activity is of great significance in biomedicine and environmental health such as cancer diagnosis and water monitoring. However, the conventional β-GLU activity assay suffers from the limitations of low sensitivity, poor accuracy, and complex procedure. With the development of analytical chemistry, many advances have been made in the detection of β-GLU activity in recent years. The sensors for β-GLU activity detection which have the advantages of rapid and reliable detection have been attracting increased attentions. In this paper, the principles, performances, and limitations of these β-GLU sensors, including colorimetric sensing, fluorescent sensing, electrochemical sensing for the determination of β-GLU activity, have been summarized and discussed. Moreover, the challenges and research trends of β-GLU activity assay are proposed.

Impact of Hydrometeorological Events for the Selection of Parametric Models for Protozoan Pathogens in Drinking-Water Sources

Temporal variations in concentrations of pathogenic microorganisms in surface waters are well known to be influenced by hydrometeorological events. Reasonable methods for accounting for microbial peaks in the quantification of drinking water treatment requirements need to be addressed. Here, we applied a novel method for data collection and model validation to explicitly account for weather events (rainfall, snowmelt) when concentrations of pathogens are estimated in source water. Online in situ β-d-glucuronidase activity measurements were used to trigger sequential grab sampling of source water to quantify Cryptosporidium and Giardia concentrations during rainfall and snowmelt events at an urban and an agricultural drinking water treatment plant in Quebec, Canada. We then evaluate if mixed Poisson distributions fitted to monthly sampling data ( n = 30 samples) could accurately predict daily mean concentrations during these events. We found that using the gamma distribution underestimated high Cryptosporidium and Giardia concentrations measured with routine or event-based monitoring. However, the log-normal distribution accurately predicted these high concentrations. The selection of a log-normal distribution in preference to a gamma distribution increased the annual mean concentration by less than 0.1-log but increased the upper bound of the 95% credibility interval on the annual mean by about 0.5-log. Therefore, considering parametric uncertainty in an exposure assessment is essential to account for microbial peaks in risk assessment.

Automated Targeted Sampling of Waterborne Pathogens and Microbial Source Tracking Markers Using Near-Real Time Monitoring of Microbiological Water Quality

Waterborne pathogens are heterogeneously distributed across various spatiotemporal scales in water resources, and representative sampling is therefore crucial for accurate risk assessment. Since regulatory monitoring of microbiological water quality is usually conducted at fixed time intervals, it can miss short-term fecal contamination episodes and underestimate underlying microbial risks. In the present paper, we developed a new automated sampling methodology based on near real-time measurement of a biochemical indicator of fecal pollution. Online monitoring of β-D-glucuronidase (GLUC) activity was used to trigger an automated sampler during fecal contamination events in a drinking water supply and at an urban beach. Significant increases in protozoan parasites, microbial source tracking markers and E. coli were measured during short-term (<24 h) fecal pollution episodes, emphasizing the intermittent nature of their occurrence in water. Synchronous triggering of the automated sampler with online GLUC activity measurements further revealed a tight association between the biochemical indicator and culturable E. coli. The proposed event sampling methodology is versatile and in addition to the two triggering modes validated here, others can be designed based on specific needs and local settings. In support to regulatory monitoring schemes, it should ultimately help gathering crucial data on waterborne pathogens more efficiently during episodic fecal pollution events.

Demonstrating the reduction of enteric viruses by drinking water treatment during snowmelt episodes in urban areas

This study investigates short-term fluctuations in virus concentrations in source water and their removal by full-scale drinking water treatment processes under different source water conditions. Transient peaks in raw water faecal contamination were identified using in situ online β-d-glucuronidase activity monitoring at two urban drinking water treatment plants. During these peaks, sequential grab samples were collected at the source and throughout the treatment train to evaluate concentrations of rotavirus, adenovirus, norovirus, enterovirus, JC virus, reovirus, astrovirus and sapovirus by reverse transcription and real-time quantitative PCR. Virus infectivity was assessed through viral culture by measurement of cytopathic effect and integrated cell culture qPCR. Virus concentrations increased by approximately 0.5-log during two snowmelt/rainfall episodes and approximately 1.0-log following a planned wastewater discharge upstream of the drinking water intake and during a β-d-glucuronidase activity peak in dry weather conditions. Increases in the removal of adenovirus and rotavirus by coagulation/flocculation processes were observed during peak virus concentrations in source water, suggesting that these processes do not operate under steady-state conditions but dynamic conditions in response to source water conditions. Rotavirus and enterovirus detected in raw and treated water samples were predominantly negative in viral culture. At one site, infectious adenoviruses were detected in raw water and water treated by a combination of ballasted clarification, ozonation, GAC filtration, and UV disinfection operated at a dose of 40 mJ cm^-2. The proposed sampling strategy can inform the understanding of the dynamics associated with virus concentrations at drinking water treatment plants susceptible to de facto wastewater reuse.

Coupling Genomics and Hydraulic Information to Predict the Nitrogen Dynamics in a Channel Confluence

The simulation of nitrogen dynamics in urban channel confluences is essential for the evaluation and improvement of water quality. The omics-based modeling approaches that have been rapidly developed have been increasingly applied to characterize metabolisms of the microbial community and transformation of the associated materials. However, the transport of microorganisms and chemicals within and among different phases, which could be the rate-limiting step for the nitrogen dynamics, are always neglected or oversimplified in omics-based models. Therefore, this study proposes a novel simulation system coupling genomic and hydraulic information to simulate transport and transformation processes and provide predictions of nitrogen dynamics in a confluence. The proposed model was able to capture multiphase mass transport, microbial population dynamics, and nitrogen transformation and accurately predict gene abundances and nitrogen concentrations in both water and sediment; the mean relative errors were all lower than 40%. The model emphasized the importance of transport processes, which contributed more than 90% to gene abundances and chemical concentrations. Moreover, the simulation of reaction rates exhibited the specific nitrogen transformation processes in the confluence. The sulfide oxidation and the nitrate reduction and anaerobic ammonium oxidation, with the participation of the genes nap and hzo, respectively, were promoted as the main processes of nitrate and nitrite reduction.

Canary in the coliform mine: Exploring the industrial application limits of a microbial respiration alarm system

Fundamental ecological principles of ecosystem-level respiration are extensively applied in greenhouse gas and elemental cycle studies. A laboratory system termed CEMS (Carbon Dioxide Evolution Measurement System), developed to explore microbial biofilm growth and metabolic responses, was evaluated as an early-warning system for microbial disturbances in industrial settings: in (a) potable water system contamination, and (b) bioreactor inhibition. Respiration was detected as CO2 production, rather than O2 consumption, including aerobic and anaerobic metabolism. Design, thresholds, and benefits of the remote CO2 monitoring technology were described. Headspace CO2 correlated with contamination levels, as well as chemical (R2 > 0.83-0.96) and microbiological water quality indicators (R2 > 0.78-0.88). Detection thresholds were limiting factors in monitoring drinking water to national and international standards (0 CFU/100 mL fecal coliforms) in both open- (>1500 CFU/mL) and closed-loop CO2 measuring regimes (>100 CFU/100 mL). However, closed-loop detection thresholds allow for the detection of significant contamination events, and monitoring less stringent systems such as irrigation water (<100 CFU/mL). Whole-system respiration was effectively harnessed as an early-warning system in bioreactor performance monitoring. Models were used to deconvolute biological CO2 fluctuations from chemical CO2 dynamics, to optimize this real-time, sustainable, low-waste technology, facilitating timeous responses to biological disturbances in bioreactors.

Simple enumeration of Escherichia coli concentrations in river water samples by measuring β-d-glucuronidase activities in a microplate reader

Monitoring of Escherichia coli concentrations in river water (RW) is essential to identify fecal pollution of the river. The objective of this study was to assess the suitability of a novel, simple and high throughput method developed in our laboratory to enumerate E. coli concentrations in RW samples. The method is based on the use of the synthetic substrate specific for the β-d-glucuronidase (GUS) produced by E. coli. GUS activities and E. coli concentrations were monitored at eight selected sites in rivers running through Sapporo, Japan. Because the fluorescence intensities of the synthetic substrate in the RW samples increased linearly over a 4-h incubation period, we could estimate the GUS activities of the RW samples. The GUS activities were highly correlated with E. coli concentrations at >100 most probable numbers 100 mL^-1 with a correlation coefficient of 0.87. The GUS activities of the RW samples collected from all sampling sites fitted well to a single correlation equation, which indicates that it was applicable to the estimation of E. coli concentrations regardless of the sampling sites. This method is simple, rapid, reliable, inexpensive, and high throughput, and is therefore useful for monitoring E. coli in RW.

Optimizing short time-step monitoring and management strategies using environmental tracers at flood-affected bank filtration sites

Bank filtration is a popular pre-treatment method to produce drinking water as it benefits from the natural capacity of the sediments to attenuate contaminants. Under flood conditions, bank filtration systems are known to be vulnerable to contamination, partly because flow patterns may evolve at short timescales and result in a rapid evolution of the origin and travel times of surface water in the aquifer. However, high frequency monitoring for water quality is not common practice yet, and water quality management decisions for the operation of bank filtration systems are typically based on weekly to monthly assays. The aim of this study is to illustrate how monitoring strategies of environmental tracers at flood-affected sites can be optimized and to demonstrate how tracer-based evidence can help to define adequate pumping strategies. Data acquisition spanned two intense flood events at a two-lake bank filtration site. Based on bacteriological indicators, the bank filtration system was shown to be resilient to the yearly recurring flood events but more vulnerable to contamination during the intense flood events. The origin of the bank filtrate gradually evolved from a mixture between the two lakes towards a contribution of floodwater and one lake only. Automatized measurements of temperature and electrical conductivity at observation wells allowed to detect changes in the groundwater flow patterns at a daily timescale, while the regulatory monthly monitoring for indicator bacteria did not fully capture the potential short timescale variability of the water quality. The recovery to pre-flood conditions was shown to be accelerated for the wells operating at high rates (i.e., ≥1000 m³/day), partly because of floodwater storage in the vicinity of the less active wells. These results establish new perspectives to anticipate water quality changes through selected pumping schemes, which depend on and must be adapted to site-specific water quality issues.

Monitoring Approaches for Faecal Indicator Bacteria in Water: Visioning a Remote Real-Time Sensor for E. coli and Enterococci

A comprehensive review was conducted to assess the current state of monitoring approaches for primary faecal indicator bacteria (FIB) E. coli and enterococci. Approaches were identified and examined in relation to their accuracy, ability to provide continuous data and instantaneous detection results, cost, environmental awareness regarding necessary reagent release or other pollution sources, in situ monitoring capability, and portability. Findings showed that several methods are precise and sophisticated but cannot be performed in real-time or remotely. This is mainly due to their laboratory testing requirements, such as lengthy sample preparations, the requirement for expensive reagents, and fluorescent tags. This study determined that portable fluorescence sensing, combined with advanced modelling methods to compensate readings for environmental interferences and false positives, can lay the foundations for a hybrid FIB sensing approach, allowing remote field deployment of a fleet of networked FIB sensors that can collect high-frequency data in near real-time. Such sensors will support proactive responses to sudden harmful faecal contamination events. A method is proposed to enable the development of the visioned FIB monitoring tool.

Near real-time notification of water quality impairments in recreational freshwaters using rapid online detection of β-D-glucuronidase activity as a surrogate for Escherichia coli monitoring

Waterborne disease outbreaks associated with recreational waters continue to be reported around the world despite existing microbiological water quality monitoring frameworks. Most regulations resort to the use of culture-based enumeration of faecal indicator bacteria such as Escherichia coli to protect bathers from gastrointestinal illness risks. However, the long sample-to-result time of standard culture-based assays (minimum 18-24 h) and infrequent regulatory sampling (weekly or less) do not enable detection of episodic water quality impairments and associated public health risks. The objective of this study was to assess the suitability of an autonomous online technology measuring β-D-glucuronidase (GLUC) activity for near real-time monitoring of microbiological water quality in recreational waters and for the resulting beach management decisions. GLUC activity and E. coli concentrations were monitored at three freshwater sites in Quebec, Canada (sites Qc1-3) and one site in New Zealand (site NZ) between 2016 and 2018. We found site-dependent linear relationships between GLUC activity and E. coli concentrations and using confusion matrices, we developed site-specific GLUC activity beach action values (BAVs) matching the regulatory E. coli BAVs. Using the regulatory E. coli BAV as the gold standard, rates of false alarms (unnecessary beach advisories using GLUC activity BAV) and failures to act (failure to trigger advisories using GLUC activity) ranged between 0 and 32% and between 3 and 10%, respectively, which is comparable to the rates reported in other studies using qPCR-defined BAVs. However, a major benefit of the autonomous enzymatic technology is the real-time reporting of threshold exceedances, while temporal trends in GLUC activity can assist in understanding the underlying dynamics of faecal pollution and potential health risks. Our study is the first to describe the applicability of online near real-time monitoring of microbiological water quality as a tool for improved beach management and public health protection.

Simple and reliable enumeration of Escherichia coli concentrations in wastewater samples by measuring β-d-glucuronidase (GUS) activities via a microplate reader

Monitoring of Escherichia coli concentrations at wastewater treatment plants (WWTPs) is important to ensure process performance and protect public health. However, conventional E. coli enumeration methods are complicated and time- and labor-consuming. Here, we report a novel simple and reliable method based on β-d-glucuronidase (GUS) activity assay to enumerate E. coli concentrations in wastewater (WW) samples. An aliquot (20 μL) of the medium with fluorogenic enzyme substrate for E. coli and 180 μL of a WW sample were added to one well of a 96-well microplate. The microplate was placed in a microplate reader at 37 °C. To this end, the fluorescence intensity of a fluorogenic enzyme substrate for E. coli was measured every 10 min over 3 h to determine GUS activity. The linear increase in the fluorescence intensity representing the GUS activities showed a positive correlation with E. coli concentrations in wastewater samples. However, the correlation equations were specific to WWTPs, which could be due to the difference in the E. coli population structures among WWTPs. We observed that the wastewater matrix is not a limitation to measure the GUS activity, and a WWTP-specific correlation equation can be used as a calibration curve to estimate the E. coli concentrations in the samples collected from that site. A comparison of the results with those of culture-dependent Colilert method proved that the current method is simple and useful for the enumeration of E. coli concentrations in wastewater samples reliably.

Can routine monitoring of E. coli fully account for peak event concentrations at drinking water intakes in agricultural and urban rivers?

In several jurisdictions, the arithmetic mean of Escherichia coli concentrations in raw water serves as the metric to set minimal treatment requirements by drinking water treatment plants (DWTPs). An accurate and precise estimation of this mean is therefore critical to define adequate requirements. Distributions of E. coli concentrations in surface water can be heavily skewed and require statistical methods capable of characterizing uncertainty. We present four simple parametric models with different upper tail behaviors (gamma, log-normal, Lomax, mixture of two log-normal distributions) to explicitly account for the influence of peak events on the mean concentration. The performance of these models was tested using large E. coli data sets (200-1800 samples) from raw water regulatory monitoring at six DWTPs located in urban and agricultural catchments. Critical seasons of contamination and hydrometeorological factors leading to peak events were identified. Event-based samples were collected at an urban DWTP intake during two hydrometeorological events using online β-d-glucuronidase activity monitoring as a trigger. Results from event-based sampling were used to verify whether selected parametric distributions predicted targeted peak events. We found that the upper tail of the log-normal and the Lomax distributions better predicted large concentrations than the upper tail of the gamma distribution. Weekly sampling for two years in urban catchments and for four years in agricultural catchments generated reasonable estimates of the average raw water E. coli concentrations. The proposed methodology can be easily used to inform the development of sampling strategies and statistical indices to set site-specific treatment requirements.

Fieldwork-based determination of design priorities for point-of-use drinking water quality sensors for use in resource-limited environments

Improved capabilities in microfluidics, electrochemistry, and portable assays have resulted in the development of a wide range of point-of-use sensors intended for environmental, medical, and agricultural applications in resource-limited environments of developing countries. However, these devices are frequently developed without direct interaction with their often-remote intended user base, creating the potential for a disconnect between users' actual needs and those perceived by sensor developers. As different analytical techniques have inherent strengths and limitations, effective measurement solution development requires determination of desired sensor attributes early in the development process. In this work, we present our findings on design priorities for point-of-use microbial water sensors based on fieldwork in rural India, as well as a guide to fieldwork methodologies for determining desired sensor attributes. We utilized group design workshops for initial identification of design priorities, and then conducted choice-based conjoint analysis interviews for quantification of user preferences among these priorities. We found the highest user preference for integrated reporting of contaminant concentration and recommended actions, as well as significant preferences for mostly reusable sensor architectures, same-day results, and combined ingredients. These findings serve as a framework for future microbial sensor development and a guide for fieldwork-based understanding of user needs.

Demonstration of an optical biosensor for the detection of faecal indicator bacteria in freshwater and coastal bathing areas

ColiSense, an early warning system developed for Escherichia coli detection, is assessed using environmental samples. The system relies on the detection of β-glucuronidase (GUS), a biomarker enzyme for E. coli. In contrast with other rapid GUS-based methods, ColiSense is the only method that uses 6-chloro-4-methyl-umbelliferyl-β-D-glucuronide (6-CMUG) as a fluorogenic substrate. The system measures a direct kinetic response of extracted GUS, and the detection was carried out in the absence of particles or bacteria. It is necessary to evaluate the system with environmental samples to establish the relationship between faecal indicator bacteria E. coli and the response measured by the ColiSense. This paper presents the results of tests carried out with the ColiSense system for 2 trials, one conducted with freshwater samples collected from rivers in the Dublin area and a second conducted with seawater samples from coastal areas collected over the bathing season. A positive linear correlation was found between E. coli (MPN 100 mL^-1) and ColiSense response (R² = 0.85, N = 125, p < 0.01) for the seawater sample. A ColiSense response threshold was identified as 0-1.8 pmol min^-1 100 mL^-1, equivalent to 0-500 E. coli 100 mL^-1. Using this threshold, 96.8% of the samples were correctly classified as being above or below 500 E. coli 100 mL^-1 by the ColiSense system. Results presented demonstrate that the ColiSense system can be used as an early warning tool with potential for active management of bathing areas by providing results in 75 min from sample collection.

Tracking the contribution of multiple raw and treated wastewater discharges at an urban drinking water supply using near real-time monitoring of β-d-glucuronidase activity

Past waterborne outbreaks have demonstrated that informed vulnerability assessment of drinking water supplies is paramount for the provision of safe drinking water. Although current monitoring frameworks are not designed to account for short-term peak concentrations of fecal microorganisms in source waters, the recent development of online microbial monitoring technologies is expected to fill this knowledge gap. In this study, online near real-time monitoring of β-d-glucuronidase (GLUC) activity was conducted for 1.5 years at an urban drinking water intake impacted by multiple point sources of fecal pollution. Parallel routine and event-based monitoring of E. coli and online measurement of physico-chemistry were performed at the intake and their dynamics compared over time. GLUC activity fluctuations ranged from seasonal to hourly time scales. All peak contamination episodes occurred between late fall and early spring following intense rainfall and/or snowmelt. In the absence of rainfall, recurrent daily fluctuations in GLUC activity and culturable E. coli were observed at the intake, a pattern otherwise ignored by regulatory monitoring. Cross-correlation analysis of time series retrieved from the drinking water intake and an upstream Water Resource Recovery Facility (WRRF) demonstrated a hydraulic connection between the two sites. Sewage by-passes from the same WRRF were the main drivers of intermittent GLUC activity and E. coli peaks at the drinking water intake following intense precipitation and/or snowmelt. Near real-time monitoring of fecal pollution through GLUC activity enabled a thorough characterization of the frequency, duration and amplitude of peak contamination periods at the urban drinking water intake while providing crucial information for the identification of the dominant upstream fecal pollution sources. To the best of our knowledge, this is the first characterization of a hydraulic connection between a WRRF and a downstream drinking water intake across hourly to seasonal timescales using high frequency microbial monitoring data. Ultimately, this should help improve source water protection through catchment mitigation actions, especially in a context of de facto wastewater reuse.

Microbial risk associated with CSOs upstream of drinking water sources in a transboundary river using hydrodynamic and water quality modeling

Urban source water protection planning requires the characterization of sources of contamination upstream of drinking water intakes. Elevated pathogen concentrations following Combined Sewer Overflows (CSOs) represent a threat to human health. Quantifying peak pathogen concentrations at the intakes of drinking water plants is a challenge due to the variability of CSO occurrences and uncertainties with regards to the fate and transport mechanisms from discharge points to source water supplies. Here, a two-dimensional deterministic hydrodynamic and water quality model is used to study the fluvial contaminant transport and the impacts of the upstream CSO discharges on the downstream concentrations of Escherichia coli in the raw water supply of two drinking water plants, located on a large river. CSO dynamic loading characteristics were considered for a variety of discharges. As a result of limited Cryptosporidium data, a probability distribution of the ratio of E. coli to Cryptosporidium based on historical data was used to estimate microbial risk from simulated CSO-induced E. coli concentrations. During optimal operational performance of the plants, the daily risk target was met (based on the mean concentration during the peak) for 80% to 90% of CSO events. For suboptimal performance of the plants, these values dropped to 40% to 55%. Mean annual microbial risk following CSO discharge events was more dependent on treatment performance rather than the number of CSO occurrences. The effect of CSO-associated short term risk on the mean annual risk is largely dependent on the treatment performance as well as representativeness of the baseline condition at the intakes, demonstrating the need for assessment of treatment efficacy. The results of this study will enable water utilities and managers with a tool to investigate the potential alternatives in reducing the microbial risk associated with CSOs.