A sensitive and robust method for automated on-line monitoring of enzymatic activities in water and water resources

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.

The β-galactosidase assay in perspective: Critical thoughts for biosensor development

Recently, the β-galactosidase assay has become a key component in the development of assays and biosensors for the detection of enterobacteria and E. coli in water quality monitoring. The assay has often performed below its maximum potential, mainly due to a poor choice of conditions. In this study we establish a set of optimal conditions and provide a rough estimate of how departure from optimal values reduces the output of the assay potentially decreasing its sensitivity. We have established that maximum response for detecting low cell concentrations requires an induction of the samples using IPTG at a concentration of 0.2 mM during 180 min. Permeabilization of the samples is mandatory as lack of it results in an almost 60% reduction in assay output. The choice of enzyme substrate is critical as different substrates yield products with different extinction coefficients or fluorescence yields. The concentration of substrate used must be high enough (around 3 to 4 times K_m) to ensure that the activity measured is not substrate limited. Finally, as the color/fluorescence of the reaction products is highly dependent on pH, care must be taken to ensure that pH at the time of reading is high enough to provide maximum signal.

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.

Using surrogate data to assess risks associated with microbial peak events in source water at drinking water treatment plants

A monitoring strategy was implemented at two drinking water treatment plants in Quebec, Canada, to evaluate microbial reduction performances of full-scale treatment processes under different source water conditions. β-D-glucuronidase activity in source water was automatically monitored in near-real-time to establish baseline and event conditions at each location. High-volume water samples (50-1,500 L) were collected at the inflow and the outflow of coagulation/flocculation, filtration, and UV disinfection processes and were analysed for two naturally occurring surrogate organisms: Escherichia coli and Clostridium perfringens. Source water Cryptosporidium data and full-scale C. perfringens reduction data were entered into a quantitative microbial risk assessment (QMRA) model to estimate daily infection risks associated with exposures to Cryptosporidium via consumption of treated drinking water. Daily mean E. coli and Cryptosporidium concentrations in source water under event conditions were in the top 5% (agricultural site) or in the top 15% (urban site) of what occurs through the year at these drinking water treatment plants. Reduction performances of up to 6.0-log for E. coli and 5.6-log for C. perfringens were measured by concentrating high-volume water samples throughout the treatment train. For both drinking water treatment plants, removal performances by coagulation/flocculation/sedimentation processes were at the high end of the range of those reported in the literature for bacteria and bacterial spores. Reductions of E. coli and C. perfringens by floc blanket clarification, ballasted clarification and rapid sand filtration did not deteriorate during two snowmelt/rainfall events. QMRA results suggested that daily infection risks were similar during two rainfall/snowmelt events than during baseline conditions. Additional studies investigating full-scale reductions would be desirable to improve the evaluation of differences in treatment performances under various source water conditions.

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.

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.

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.

Emerging pathogens and deliberate attacks on European water supplies: a scenario planning workshop

Microbiological contamination of drinking water supplies is an ever-present concern for water utility managers. Most such threats are routine, well-recognised and described. Therefore, they can usually be prevented using standard protection measures. Incidents involving emerging pathogens and malicious attacks are inherently less predictable. In a multi-stage process over one day, participants with backgrounds in microbiology, medicine, infrastructure, data analysis, environmental or public health and facility management developed qualitative scenarios on potential threats posed by either an emergent pathogen in or a microbiological attack on drinking water supplies in a European country. Participants were guided via structured activities to identify key factors that would impact the magnitude and severity of such an emergency. Plausible variant states for each key factor were determined, and participants constructed sequences of events to create scenario outlines. Five scenarios in outline form are reported which incorporate genuine possible future events as well as pathogens of international concern. Common features that would exacerbate all scenarios were under-investment in public services, inadequate water quality testing, and monitoring and lack of resources to keep water supplies safe. Participant evaluation of their scenario planning experience was broadly very positive and the scenario planning process was received as credible and relevant.

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

Microbiological water quality is traditionally assessed using culture-based enumeration of faecal indicator bacteria such as Escherichia coli. Despite their relative ease of use, these methods require a minimal 18-24 h-incubation step before the results are obtained. This study aimed to assess the suitability of an autonomous online fluorescence-based technology measuring β-glucuronidase (GLUC) activity for rapid near-real time monitoring of E. coli in water. The analytical precision was determined and compared to an automated microbial detection system, two culture-based assays and quantitative real-time PCR (qPCR). Using replicate measurements of grab samples containing E. coli concentrations between 50 and 2330 CFU.100 mL^-1, the autonomous GLUC activity measurement technology displayed an average coefficient of variation (CV) of less than 5% that was 4-8-fold lower than other methods tested. Comparable precision was observed during online in situ monitoring of GLUC activity at a drinking water intake using three independent instruments. GLUC activity measurements were not affected by sewage or sediments at concentrations likely to be encountered during long-term monitoring. Furthermore, significant (p < 0.05) correlations were obtained between GLUC activity and the other assays including defined substrate technology (r = 0.77), membrane filtration (r = 0.73), qPCR (r = 0.55) and the automated microbial detection system (r = 0.50). This study is the first to thoroughly compare the analytical performance of rapid automated detection technologies to established culture and molecular-based methods. Results show that further research is required to correlate GLUC activity to the presence of viable E. coli as measured in terms of CFU.100 mL^-1. This would allow the use of autonomous online GLUC activity measurements for rapid E. coli monitoring in water supplies used for drinking water production and recreation.

Spatial patterns of enzymatic activity in large water bodies: Ship-borne measurements of beta-D-glucuronidase activity as a rapid indicator of microbial water quality

This study used automated enzymatic activity measurements conducted from a mobile research vessel to detect the spatial variability of beta‑d‑glucuronidase (GLUC) activity in large freshwater bodies. The ship-borne observations provided the first high-resolution spatial data of GLUC activity in large water bodies as rapid indication of fecal pollution and were used to identify associations with hydrological conditions and land use. The utility of this novel approach for water quality screening was evaluated by surveys of the Columbia River, the Mississippi River and the Yahara Lakes, covering up to a 500 km river course and 50 km² lake area. The ship-borne measurements of GLUC activity correlated with standard E. coli analyses (R² = 0.71) and revealed the effects of (1) precipitation events and urban run-off on GLUC activity in surface waters, (2) localized point inlets of potential fecal pollution and (3) increasing GLUC signals along gradients of urbanization. We propose that this ship-borne water quality screening to be integrated into future water inventory programs as an initial or complementary tool (besides established fecal indicator parameters), due to its ability to provide near real-time spatial information on potential fecal contamination of large surface water resources and therefore being helpful to greatly reduce potential human health risks.

Opening the black box of spring water microbiology from alpine karst aquifers to support proactive drinking water resource management

Over the past 15 years, pioneering interdisciplinary research has been performed on the microbiology of hydrogeologically well-defined alpine karst springs located in the Northern Calcareous Alps (NCA) of Austria. This article gives an overview on these activities and links them to other relevant research. Results from the NCA springs and comparable sites revealed that spring water harbors abundant natural microbial communities even in aquifers with high water residence times and the absence of immediate surface influence. Apparently, hydrogeology has a strong impact on the concentration and size of the observed microbes, and total cell counts (TCC) were suggested as a useful means for spring type classification. Measurement of microbial activities at the NCA springs revealed extremely low microbial growth rates in the base flow component of the studied spring waters and indicated the importance of biofilm-associated microbial activities in sediments and on rock surfaces. Based on genetic analysis, the autochthonous microbial endokarst community (AMEC) versus transient microbial endokarst community (TMEC) concept was proposed for the NCA springs, and further details within this overview article are given to prompt its future evaluation. In this regard, it is well known that during high-discharge situations, surface-associated microbes and nutrients such as from soil habitats or human settlements-potentially containing fecal-associated pathogens as the most critical water-quality hazard-may be rapidly flushed into vulnerable karst aquifers. In this context, a framework for the comprehensive analysis of microbial pollution has been proposed for the NCA springs to support the sustainable management of drinking water safety in accordance with recent World Health Organization guidelines. Near-real-time online water quality monitoring, microbial source tracking (MST) and MST-guided quantitative microbial-risk assessment (QMRA) are examples of the proposed analytical tools. In this context, this overview article also provides a short introduction to recently emerging methodologies in microbiological diagnostics to support reading for the practitioner. Finally, the article highlights future research and development needs. This article is categorized under: 1Engineering Water > Water, Health, and Sanitation2Science of Water > Water Extremes3Water and Life > Nature of Freshwater Ecosystems.

Online analysis: Deeper insights into water quality dynamics in spring water

We have studied the dynamics of water quality in three karst springs taking advantage of new technological developments that enable high-resolution measurements of bacterial load (total cell concentration: TCC) as well as online measurements of abiotic parameters. We developed a novel data analysis approach, using self-organizing maps and non-linear projection methods, to approximate the TCC dynamics using the multivariate data sets of abiotic parameter time-series, thus providing a method that could be implemented in an online water quality management system for water suppliers. The (TCC) data, obtained over several months, provided a good basis to study the microbiological dynamics in detail. Alongside the TCC measurements, online abiotic parameter time-series, including spring discharge, turbidity, spectral absorption coefficient at 254nm (SAC254) and electrical conductivity, were obtained. High-density sampling over an extended period of time, i.e. every 45min for 3months, allowed a detailed analysis of the dynamics in karst spring water quality. Substantial increases in both the TCC and the abiotic parameters followed precipitation events in the catchment area. Differences between the parameter fluctuations were only apparent when analyzed at a high temporal scale. Spring discharge was always the first to react to precipitation events in the catchment area. Lag times between the onset of precipitation and a change in discharge varied between 0.2 and 6.7h, depending on the spring and event. TCC mostly reacted second or approximately concurrent with turbidity and SAC254, whereby the fastest observed reaction in the TCC time series occurred after 2.3h. The methodological approach described here enables a better understanding of bacterial dynamics in karst springs, which can be used to estimate risks and management options to avoid contamination of the drinking water.

Evaluating Monitoring Strategies to Detect Precipitation-Induced Microbial Contamination Events in Karstic Springs Used for Drinking Water

Monitoring of microbial drinking water quality is a key component for ensuring safety and understanding risk, but conventional monitoring strategies are typically based on low sampling frequencies (e.g., quarterly or monthly). This is of concern because many drinking water sources, such as karstic springs are often subject to changes in bacterial concentrations on much shorter time scales (e.g., hours to days), for example after precipitation events. Microbial contamination events are crucial from a risk assessment perspective and should therefore be targeted by monitoring strategies to establish both the frequency of their occurrence and the magnitude of bacterial peak concentrations. In this study we used monitoring data from two specific karstic springs. We assessed the performance of conventional monitoring based on historical records and tested a number of alternative strategies based on a high-resolution data set of bacterial concentrations in spring water collected with online flow cytometry (FCM). We quantified the effect of increasing sampling frequency and found that for the specific case studied, at least bi-weekly sampling would be needed to detect precipitation events with a probability of >90%. We then proposed an optimized monitoring strategy with three targeted samples per event, triggered by precipitation measurements. This approach is more effective and efficient than simply increasing overall sampling frequency. It would enable the water utility to (1) analyze any relevant event and (2) limit median underestimation of peak concentrations to approximately 10%. We conclude with a generalized perspective on sampling optimization and argue that the assessment of short-term dynamics causing microbial peak loads initially requires increased sampling/analysis efforts, but can be optimized subsequently to account for limited resources. This offers water utilities and public health authorities systematic ways to evaluate and optimize their current monitoring strategies.

Evaluation of β-d-glucuronidase and particle-size distribution for microbiological water quality monitoring in Northern Vietnam

In many karst regions in developing countries, the populations often suffer from poor microbial water quality and are frequently exposed to bacterial pathogens. The high variability of water quality requires rapid assays, but the conventional cultivation-based analysis of fecal indicator bacteria, such as Escherichia coli (E. coli), is very time-consuming. In this respect, the measurement of the enzymatic activity of E. coli could prove to be a valuable tool for water quality monitoring. A mobile automated prototype device was used for the investigation of β-d-glucuronidase (GLUC) activity at a remote karst spring, connected to a sinking surface stream, in Northern Vietnam. To assess the relationship between GLUC activity, discharge dynamics and contamination patterns, multiple hydrological, hydrochemical, physicochemical and microbiological parameters, including discharge, turbidity, particle-size distributions, and E. coli, were measured with high temporal resolution during ten days of on-site monitoring. A complex contamination pattern due to anthropogenic and agricultural activities led to high E. coli concentrations (270 to >24,200 MPN/100ml) and a GLUC activity between 3.1 and 102.2 mMFU/100ml. A strong daily fluctuation pattern of GLUC activity and particle concentrations within small size classes (<10μm) could be observed, as demonstrated by autocorrelations. A Spearman's rank correlation analysis resulted in correlation coefficients of rs=0.56 for E. coli and GLUC activity and rs=0.54 for GLUC activity and the concentration of 2-3μm particles. On an event scale, correlations were found to be higher (rs=0.69 and 0.87, respectively). GLUC activity and E. coli displayed a general contamination pattern, but with significant differences in detail, which may be explained by interferences of e. g. viable but non-culturable cells. Although further evaluations are recommended, GLUC activity is a promising, complementary parameter for on-site and near real-time water quality monitoring.

Online flow cytometry reveals microbial dynamics influenced by concurrent natural and operational events in groundwater used for drinking water treatment

Detailed measurements of physical, chemical and biological dynamics in groundwater are key to understanding the important processes in place and their influence on water quality – particularly when used for drinking water. Measuring temporal bacterial dynamics at high frequency is challenging due to the limitations in automation of sampling and detection of the conventional, cultivation-based microbial methods. In this study, fully automated online flow cytometry was applied in a groundwater system for the first time in order to monitor microbial dynamics in a groundwater extraction well. Measurements of bacterial concentrations every 15 minutes during 14 days revealed both aperiodic and periodic dynamics that could not be detected previously, resulting in total cell concentration (TCC) fluctuations between 120 and 280 cells μL⁻¹. The aperiodic dynamic was linked to river water contamination following precipitation events, while the (diurnal) periodic dynamic was attributed to changes in hydrological conditions as a consequence of intermittent groundwater extraction. Based on the high number of measurements, the two patterns could be disentangled and quantified separately. This study i) increases the understanding of system performance, ii) helps to optimize monitoring strategies, and iii) opens the possibility for more sophisticated (quantitative) microbial risk assessment of drinking water treatment systems.

Real-time monitoring of beta-d-glucuronidase activity in sediment laden streams: A comparison of prototypes

Detection of enzymatic activities has been proposed as a rapid surrogate for the culture-based microbiological pollution monitoring of water resources. This paper presents the results of tests on four fully automated prototype instruments for the on-site monitoring of beta-d-glucuronidase (GLUC) activity. The tests were performed on sediment-laden stream water in the Hydrological Open Air Laboratory (HOAL) during the period of March 2014 to March 2015. The dominant source of faecal pollution in the stream was swine manure applied to the fields within the catchment. The experiments indicated that instrument pairs with the same construction design yielded highly consistent results (R(2) = 0.96 and R(2) = 0.94), whereas the results between different designs were less consistent (R(2) = 0.71). Correlations between the GLUC activity measured on-site and culture-based Escherichia coli analyses over the entire study period yielded R(2) = 0.52 and R(2) = 0.47 for the two designs, respectively. The correlations tended to be higher at the event scale. The GLUC activity was less correlated with suspended sediment concentrations than with E. coli, which is interpreted in terms of indicator applicability and the time since manure application. The study shows that this rapid assay can yield consistent results over a long period of on-site operation in technically challenging habitats. Although the use of GLUC activity as a proxy for culture-based assays could not be proven for the observed habitat, the study results suggest that this biochemical indicator has high potential for implementation in early warning systems.

The effects of combined sewer overflow events on riverine sources of drinking water

This study was set out to investigate the impacts of Combined Sewer Overflows (CSOs) on the microbiological water quality of a river used as a source of drinking water treatment plants. Escherichia coli concentrations were monitored at various stations of a river segment located in the Greater Montreal Area including two Drinking Water Intakes (DWIs) in different weather conditions (dry weather and wet weather (precipitation and snowmelt period)). Long-term monitoring data (2002-2011) at DWIs revealed good microbiological water quality with E. coli median concentrations of 20 and 30 CFU/100 mL for DWI-1 and DWI-2 respectively. However, E. coli concentration peaks reached up to 510 and 1000 CFU/100 mL for both DWIs respectively. Statistical Process Control (SPC) analysis allowed the identification of E. coli concentration peaks in almost a decade of routine monitoring data at DWIs. Almost 80% of these concentrations were linked to CSO discharges caused by precipitation exceeding 10 mm or spring snowmelt. Dry weather monitoring confirmed good microbiological water quality. Wet weather monitoring showed an increase of approximately 1.5 log of E. coli concentrations at DWIs. Cumulative impacts of CSO discharges were quantified at the river center with an increase of approximately 0.5 log of E. coli concentrations. Caffeine (CAF) was tested as a potential chemical indicator of CSO discharges in the river and CAF concentrations fell within the range of previous measurements performed for surface waters in the same area (∼20 ng/L). However, no significant differences were observed between CAF concentrations in dry and wet weather, as the dilution potential of the river was too high. CSO event based monitoring demonstrated that current bi-monthly or weekly compliance monitoring at DWIs underestimate E. coli concentrations entering DWIs and thus, should not be used to quantify the risk at DWIs. High frequency event-based monitoring is a desirable approach to establish the importance and duration of E. coli peak concentrations entering DWIs.