ß-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 ß-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.

Monitoring of cyanobacterial breakthrough and accumulation by in situ phycocyanin probe system within full-scale treatment plants.

Worldwide, there has been an increase in the presence of potentially toxic cyanobacterial blooms in drinking water sources and within drinking water treatment plants (DWTPs). The objective of this study is to validate the use of in situ probes for the detection and management of cyanobacterial breakthrough in high and low-risk DWTPs. In situ phycocyanin YSI EXO2 probes were devised for remote control and data logging to monitor the cyanobacteria in raw, clarified, filtered, and treated water in three full-scale DWTPs. An additional probe was installed inside the sludge holding tank to measure the water quality of the surface of the sludge storage tank in a high-risk DWTP. Simultaneous grab samplings were carried out for taxonomic cell counts and toxin analysis. A total of 23, 9, and 4 field visits were conducted at the three DWTPs. Phycocyanin readings showed a 93-fold fluctuation within 24 h in the raw water of the high cyanobacterial risk plant, with higher phycocyanin levels during the afternoon period. These data provide new information on the limitations of weekly or daily grab sampling. Also, different moving averages for the phycocyanin probe readings can be used to improve the interpretation of phycocyanin signal trends. The in situ probe successfully detected high cyanobacterial biovolumes entering the clarification process in the high-risk plant. Grab sampling results revealed high cyanobacterial biovolumes in the sludge for both high and low-risk plants.

Impact of Stagnation on the Diversity of Cyanobacteria in Drinking Water Treatment Plant Sludge.

Health-related concerns about cyanobacteria-laden sludge of drinking water treatment plants (DWTPs) have been raised in the past few years. Microscopic taxonomy, shotgun metagenomic sequencing, and microcystin (MC) measurement were applied to study the fate of cyanobacteria and cyanotoxins after controlled sludge storage (stagnation) in the dark in a full-scale drinking water treatment plant within 7 to 38 days. For four out of eight dates, cyanobacterial cell growth was observed by total taxonomic cell counts during sludge stagnation. The highest observed cell growth was 96% after 16 days of stagnation. Cell growth was dominated by potential MC producers such as Microcystis, Aphanocapsa, Chroococcus, and Dolichospermum. Shotgun metagenomic sequencing unveiled that stagnation stress shifts the cyanobacterial communities from the stress-sensitive Nostocales (e.g., Dolichospermum) order towards less compromised orders and potential MC producers such as Chroococcales (e.g., Microcystis) and Synechococcales (e.g., Synechococcus). The relative increase of cyanotoxin producers presents a health challenge when the supernatant of the stored sludge is recycled to the head of the DWTP or discharged into the source. These findings emphasize the importance of a strategy to manage cyanobacteria-laden sludge and suggest practical approaches should be adopted to control health/environmental impacts of cyanobacteria and cyanotoxins in sludge.

Shotgun Metagenomic Sequencing to Assess Cyanobacterial Community Composition following Coagulation of Cyanobacterial Blooms.

The excessive proliferation of cyanobacteria in surface waters is a widespread problem worldwide, leading to the contamination of drinking water sources. Short- and long-term solutions for managing cyanobacterial blooms are needed for drinking water supplies. The goal of this research was to investigate the cyanobacteria community composition using shotgun metagenomics in a short term, in situ mesocosm experiment of two lakes following their coagulation with ferric sulfate (Fe2(SO4)3) as an option for source water treatment. Among the nutrient paramenters, dissolved nitrogen was related to Microcystis in both Missisquoi Bay and Petit Lac St. François, while the presence of Synechococcus was related to total nitrogen, dissolved nitrogen, dissolved organic carbon, and dissolved phosphorus. Results from the shotgun metagenomic sequencing showed that Dolichospermum and Microcystis were the dominant genera in all of the mesocosms in the beginning of the sampling period in Missisquoi Bay and Petit Lac St. François, respectively. Potentially toxigenic genera such as Microcystis were correlated with intracellular microcystin concentrations. A principal component analysis showed that there was a change of the cyanobacterial composition at the genus level in the mesocosms after two days, which varied across the studied sites and sampling time. The cyanobacterial community richness and diversity did not change significantly after its coagulation by Fe2(SO4)3 in all of the mesocosms at either site. The use of Fe2(SO4)3 for an onsite source water treatment should consider its impact on cyanobacterial community structure and the reduction of toxin concentrations.

Evidence-Based Framework to Manage Cyanobacteria and Cyanotoxins in Water and Sludge from Drinking Water Treatment Plants.

Freshwater bodies and, consequently, drinking water treatment plants (DWTPs) sources are increasingly facing toxic cyanobacterial blooms. Even though conventional treatment processes including coagulation, flocculation, sedimentation, and filtration can control cyanobacteria and cell-bound cyanotoxins, these processes may encounter challenges such as inefficient removal of dissolved metabolites and cyanobacterial cell breakthrough. Furthermore, conventional treatment processes may lead to the accumulation of cyanobacteria cells and cyanotoxins in sludge. Pre-oxidation can enhance coagulation efficiency as it provides the first barrier against cyanobacteria and cyanotoxins and it decreases cell accumulation in DWTP sludge. This critical review aims to: (i) evaluate the state of the science of cyanobacteria and cyanotoxin management throughout DWTPs, as well as their associated sludge, and (ii) develop a decision framework to manage cyanobacteria and cyanotoxins in DWTPs and sludge. The review identified that lab-cultured-based pre-oxidation studies may not represent the real bloom pre-oxidation efficacy. Moreover, the application of a common exposure unit CT (residual concentration × contact time) provides a proper understanding of cyanobacteria pre-oxidation efficiency. Recently, reported challenges on cyanobacterial survival and growth in sludge alongside the cell lysis and cyanotoxin release raised health and technical concerns with regards to sludge storage and sludge supernatant recycling to the head of DWTPs. According to the review, oxidation has not been identified as a feasible option to handle cyanobacterial-laden sludge due to low cell and cyanotoxin removal efficacy. Based on the reviewed literature, a decision framework is proposed to manage cyanobacteria and cyanotoxins and their associated sludge in DWTPs.

Locating illicit discharges in storm sewers in urban areas using multi-parameter source tracking: Field validation of a toolbox composite index to prioritize high risk areas.

In urban areas served by separate sewerage systems, illicit connections to the storm drain system from residences or commercial establishments are frequent whether these misconnections were made accidentally or deliberately. As a result, untreated and contaminated wastewater enters into storm sewers leading to pollution of receiving waters and non-compliance with water quality standards. Typical procedures for detecting illicit connections to the storm sewer system are time consuming and expensive, especially in a highly urbanised area. In this study, we investigated the use of human wastewater micropollutants WWMPs (caffeine, theophylline, and carbamazepine) and advanced DNA molecular markers (human specific Bacteroides HF183 and mitochondrial DNA) as anthropogenic tracers in order to assist identifying potential cross connections. Water samples from storm outfalls and storm sewer pipes in three urban subcatchments were collected in dry weather from 2013 to 2018. All samples contained various concentrations of these markers especially HF183, caffeine and theophylline, suggesting that the storm pipe system studied is widely contaminated by sanitary sewers. None of the traditional indicators or markers tested is sufficient alone to determine the origin of fecal pollution. In a highly urbanised area, the combination of at least three specific human markers was needed in order to locate the residential section with likely misconnections. The human specific Bacteroides HF183, and theophylline appeared to be the most effective markers (along with E. coli) of crossconnections, whereas carbamazepine can provide an indication of contamination through sanitary sewer exfiltration. A composite sewer cross-connection index was developed, and eight misconnected houses were identified and corrected. The index approach enables the reduction of false positives that could lead to expensive interventions to identify cross-connected households. The results show the multiparameter source tracking toolbox as an effective method to identify sewer cross connections for sustainable storm water management.

The Effects of Ferric Sulfate (Fe2(SO4)3) on the Removal of Cyanobacteria and Cyanotoxins: A Mesocosm Experiment.

Cyanobacterial blooms are a global concern. Chemical coagulants are used in water treatment to remove contaminants from the water column and could potentially be used in lakes and reservoirs. The aims of this study was to: 1) assess the efficiency of ferric sulfate (Fe2(SO4)3) coagulant in removing harmful cyanobacterial cells from lake water with cyanobacterial blooms on a short time scale, 2) determine whether some species of cyanobacteria can be selectively removed, and 3) determine the differential impact of coagulants on intra- and extra-cellular toxins. Our main results are: (i) more than 96% and 51% of total cyanobacterial cells were removed in mesocosms with applied doses of 35 mgFe/L and 20 mgFe/L, respectively. Significant differences in removing total cyanobacterial cells and several dominant cyanobacteria species were observed between the two applied doses; (ii) twelve microcystins, anatotoxin-a (ANA-a), cylindrospermopsin (CYN), anabaenopeptin A (APA) and anabaenopeptin B (APB) were identified. Ferric sulfate effectively removed the total intracellular microcystins (greater than 97% for both applied doses). Significant removal of extracellular toxins was not observed after coagulation with both doses. Indeed, the occasional increase in extracellular toxin concentration may be related to cells lysis during the coagulation process. No significant differential impact of dosages on intra- and extra-cellular toxin removal was observed which could be relevant to source water applications where optimal dosing is difficult to achieve.

Changes in Escherichia coli to enteric protozoa ratios in rivers: Implications for risk-based assessment of drinking water treatment requirements.

Minimum treatment requirements are set in response to established or anticipated levels of enteric pathogens in the source water of drinking water treatment plants (DWTPs). For surface water, contamination can be determined directly by monitoring reference pathogens or indirectly by measuring fecal indicators such as Escherichia coli (E. coli). In the latter case, a quantitative interpretation of E. coli for estimating reference pathogen concentrations could be used to define treatment requirements. This study presents the statistical analysis of paired E. coli and reference protozoa (Cryptosporidium, Giardia) data collected monthly for two years in source water from 27 DWTPs supplied by rivers in Canada. E. coli/Cryptosporidium and E. coli/Giardia ratios in source water were modeled as the ratio of two correlated lognormal variables. To evaluate the potential of E. coli for defining protozoa treatment requirements, risk-based critical mean protozoa concentrations in source water were determined with a reverse quantitative microbial risk assessment (QMRA) model. Model assumptions were selected to be consistent with the World Health Organization (WHO) Guidelines for drinking-water quality. The sensitivity of mean E. coli concentration trigger levels to identify these critical concentrations in source water was then evaluated. Results showed no proportionalities between the log of mean E. coli concentrations and the log of mean protozoa concentrations. E. coli/protozoa ratios at DWTPs supplied by small rivers in agricultural and forested areas were typically 1.0 to 2.0-log lower than at DWTPs supplied by large rivers in urban areas. The seasonal variations analysis revealed that these differences were related to low mean E. coli concentrations during winter in small rivers. To achieve the WHO target of 10-6 disability-adjusted life year (DALY) per person per year, a minimum reduction of 4.0-log of Cryptosporidium would be required for 20 DWTPs, and a minimum reduction of 4.0-log of Giardia would be needed for all DWTPs. A mean E. coli trigger level of 50 CFU 100 mL-1 would be a sensitive threshold to identify critical mean concentrations for Cryptosporidium but not for Giardia. Treatment requirements higher than 3.0-log would be needed at DWTPs with mean E. coli concentrations as low as 30 CFU 100 mL-1 for Cryptosporidium and 3 CFU 100 mL-1 for Giardia. Therefore, an E. coli trigger level would have limited value for defining health-based treatment requirements for protozoa at DWTPs supplied by small rivers in rural areas.

Comparison of approaches to quantify SARS-CoV-2 in wastewater using RT-qPCR: Results and implications from a collaborative inter-laboratory study in Canada.

Detection of SARS-CoV-2 RNA in wastewater is a promising tool for informing public health decisions during the COVID-19 pandemic. However, approaches for its analysis by use of reverse transcription quantitative polymerase chain reaction (RT-qPCR) are still far from standardized globally. To characterize inter- and intra-laboratory variability among results when using various methods deployed across Canada, aliquots from a real wastewater sample were spiked with surrogates of SARS-CoV-2 (gamma-radiation inactivated SARS-CoV-2 and human coronavirus strain 229E [HCoV-229E]) at low and high levels then provided "blind" to eight laboratories. Concentration estimates reported by individual laboratories were consistently within a 1.0-log10 range for aliquots of the same spiked condition. All laboratories distinguished between low- and high-spikes for both surrogates. As expected, greater variability was observed in the results amongst laboratories than within individual laboratories, but SARS-CoV-2 RNA concentration estimates for each spiked condition remained mostly within 1.0-log10 ranges. The no-spike wastewater aliquots provided yielded non-detects or trace levels (<20 gene copies/mL) of SARS-CoV-2 RNA. Detections appear linked to methods that included or focused on the solids fraction of the wastewater matrix and might represent in-situ SARS-CoV-2 to the wastewater sample. HCoV-229E RNA was not detected in the no-spike aliquots. Overall, all methods yielded comparable results at the conditions tested. Partitioning behavior of SARS-CoV-2 and spiked surrogates in wastewater should be considered to evaluate method effectiveness. A consistent method and laboratory to explore wastewater SARS-CoV-2 temporal trends for a given system, with appropriate quality control protocols and documented in adequate detail should succeed.

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. ß-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 ß-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 ß-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.

Can Cyanobacterial Diversity in the Source Predict the Diversity in Sludge and the Risk of Toxin Release in a Drinking Water Treatment Plant?

Conventional processes (coagulation, flocculation, sedimentation, and filtration) are widely used in drinking water treatment plants and are considered a good treatment strategy to eliminate cyanobacterial cells and cell-bound cyanotoxins. The diversity of cyanobacteria was investigated using taxonomic cell counts and shotgun metagenomics over two seasons in a drinking water treatment plant before, during, and after the bloom. Changes in the community structure over time at the phylum, genus, and species levels were monitored in samples retrieved from raw water (RW), sludge in the holding tank (ST), and sludge supernatant (SST). Aphanothece clathrata brevis, Microcystis aeruginosa, Dolichospermum spiroides , and Chroococcus minimus were predominant species detected in RW by taxonomic cell counts. Shotgun metagenomics revealed that Proteobacteria was the predominant phylum in RW before and after the cyanobacterial bloom. Taxonomic cell counts and shotgun metagenomic showed that the Dolichospermum bloom occurred inside the plant. Cyanobacteria and Bacteroidetes were the major bacterial phyla during the bloom. Shotgun metagenomics also showed that Synechococcus, Microcystis , and Dolichospermum were the predominant detected cyanobacterial genera in the samples. Conventional treatment removed more than 92% of cyanobacterial cells but led to cell accumulation in the sludge up to 31 times more than in the RW influx. Coagulation/sedimentation selectively removed more than 96% of Microcystis and Dolichospermum. Cyanobacterial community in the sludge varied from raw water to sludge during sludge storage (1-13 days). This variation was due to the selective removal of coagulation/sedimentation as well as the accumulation of captured cells over the period of storage time. However, the prediction of the cyanobacterial community composition in the SST remained a challenge. Among nutrient parameters, orthophosphate availability was related to community profile in RW samples, whereas communities in ST were influenced by total nitrogen, Kjeldahl nitrogen (N- Kjeldahl), total and particulate phosphorous, and total organic carbon (TOC). No trend was observed on the impact of nutrients on SST communities. This study profiled new health-related, environmental, and technical challenges for the production of drinking water due to the complex fate of cyanobacteria in cyanobacteria-laden sludge and supernatant.

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 ß-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.

Importance of Distributional Forms for the Assessment of Protozoan Pathogens Concentrations in Drinking-Water Sources.

The identification of appropriately conservative statistical distributions is needed to predict microbial peak events in drinking water sources explicitly. In this study, Poisson and mixed Poisson distributions with different upper tail behaviors were used for modeling source water Cryptosporidium and Giardia data from 30 drinking water treatment plants. Small differences (<0.5-log) were found between the "best" estimates of the mean Cryptosporidium and Giardia concentrations with the Poisson-gamma and Poisson-log-normal models. However, the upper bound of the 95% credibility interval on the mean Cryptosporidium concentrations of the Poisson-log-normal model was considerably higher (>0.5-log) than that of the Poisson-gamma model at four sites. The improper choice of a model may, therefore, mislead the assessment of treatment requirements and health risks associated with the water supply. Discrimination between models using the marginal deviance information criterion (mDIC) was unachievable because differences in upper tail behaviors were not well characterized with available data sets ( n<30 ). Therefore, the gamma and the log-normal distributions fit the data equally well but may predict different risk estimates when they are used as an input distribution in an exposure assessment. The collection of event-based monitoring data and the modeling of larger routine monitoring data sets are recommended to identify appropriately conservative distributions to predict microbial peak events.

Diversity Assessment of Toxic Cyanobacterial Blooms during Oxidation.

Fresh-water sources of drinking water are experiencing toxic cyanobacterial blooms more frequently. Chemical oxidation is a common approach to treat cyanobacteria and their toxins. This study systematically investigates the bacterial/cyanobacterial community following chemical oxidation (Cl2, KMnO4, O3, H2O2) using high throughput sequencing. Raw water results from high throughput sequencing show that Proteobacteria, Actinobacteria, Cyanobacteria and Bacteroidetes were the most abundant phyla. Dolichospermum, Synechococcus, Microcystis and Nostoc were the most dominant genera. In terms of species, Dolichospermum sp.90 and Microcystis aeruginosa were the most abundant species at the beginning and end of the sampling, respectively. A comparison between the results of high throughput sequencing and taxonomic cell counts highlighted the robustness of high throughput sequencing to thoroughly reveal a wide diversity of bacterial and cyanobacterial communities. Principal component analysis of the oxidation samples results showed a progressive shift in the composition of bacterial/cyanobacterial communities following soft-chlorination with increasing common exposure units (CTs) (0-3.8 mg·min/L). Close cyanobacterial community composition (Dolichospermum dominant genus) was observed following low chlorine and mid-KMnO4 (287.7 mg·min/L) exposure. Our results showed that some toxin producing species may persist after oxidation whether they were dominant species or not. Relative persistence of Dolichospermum sp.90 was observed following soft-chlorination (0.2-0.6 mg/L) and permanganate (5 mg/L) oxidation with increasing oxidant exposure. Pre-oxidation using H2O2 (10 mg/L and one day contact time) caused a clear decrease in the relative abundance of all the taxa and some species including the toxin producing taxa. These observations suggest selectivity of H2O2 to provide an efficient barrier against toxin producing cyanobacteria entering a water treatment plant.

Near real-time notification of water quality impairments in recreational freshwaters using rapid online detection of ß-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 ß-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.

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 ß-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.

Precipitation effects on parasite, indicator bacteria, and wastewater micropollutant loads from a water resource recovery facility influent and effluent.

The variability of fecal microorganisms and wastewater micropollutants (WWMPs) loads in relation to influent flow rates was evaluated for a water resource recovery facility (WRRF) in support of a vulnerability assessment of a drinking water source. Incomplete treatment and bypass discharges often occur following intense precipitation events that represent conditions that deviate from normal operation. Parasites, fecal indicator bacteria, and WWMPs concentrations and flow rate were measured at the WRRF influent and effluent during dry and wet weather periods. Influent concentrations were measured to characterize potential bypass concentrations that occur during wet weather. Maximum influent Giardia and C. perfringens loads and maximum effluent Escherichia coli and C. perfringens loads were observed during wet weather. Influent median loads of Cryptosporidium and Giardia were 6.8 log oocysts/day and 7.9 log cysts/day per 1,000 people. Effluent median loads were 3.9 log oocysts/day and 6.3 log cysts/day per 1,000 people. High loads of microbial contaminants can occur during WRRF bypasses following wet weather and increase with increasing flow rates; thus, short-term infrequent events such as bypasses should be considered in vulnerability assessments of drinking water sources in addition to the increased effluent loads during normal operation following wet weather.

Assessing microbial risk through event-based pathogen loading and hydrodynamic modelling.

The aim of this study was to assess the variability of microbial risk associated with drinking water under various contaminant loading conditions in a drinking water source. For this purpose, a probabilistic-deterministic approach was applied to estimate the loadings of Cryptosporidium, Giardia, and Escherichia coli (E. coli) from fecal contamination sources during both dry and wet weather conditions. The relative importance of loads originating from various fecal contamination sources was also determined by a probabilistic approach. This study demonstrates that water resource recovery facilities were the dominant source of Giardia, yet rivers were more important with regards to Cryptosporidium. Estimated loadings were used as input to a three-dimensional hydrodynamic model of Lake Ontario; the fate and transport of microbial organisms were simulated at the influent of a drinking water intake. Discharge-based hydrodynamic modelling results were compared to observed concentrations. Simulated probability distributions of concentrations at the intake were used as an input to a quantitative microbial risk assessment (QMRA) model such that the variability of microbial risk in the context of drinking water could be examined. Depending on wind and currents, higher levels of fecal contamination reached the intake during wet weather loading scenarios. Probability distribution functions of Cryptosporidium, Giardia and E. coli concentrations at the intake were significantly higher during wet weather conditions when compared to dry conditions (p < 0.05). For all contaminants studied, the QMRA model showed a higher risk during wet weather (over 1 order of magnitude) compared to dry weather conditions. When considering sewage by-pass scenarios, risks remained below 2.7 × 10-7 person-1 day-1 for Giardia and E. coli O157:H7. Limited data were available for Cryptosporidium in by-pass effluents and the risk is unknown; hence it is critical to obtain reliable loading data for the riskiest scenarios, such as those associated with water resource recovery facility by-passes.

Tracking the contribution of multiple raw and treated wastewater discharges at an urban drinking water supply using near real-time monitoring of ß-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 ß-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.