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.

Normalized dynamic behavior of combined sewer overflow discharges for source water characterization and management.

As one of the major sources of surface water quality impairments, Combined Sewer Overflows (CSOs) are of concern when receiving waters are used for drinking water supplies. Given the large number and variability in CSO discharges and loads, there is a need for a general methodology for estimating discharges for environmental planning and source water protection. Detailed data on CSO flowrates, contaminant concentrations including Total Suspended Solids (TSS), Escherichia coli (E. coli), caffeine (CAF) and acetaminophen (ACE) were used to develop a simple loading model that was then verified using discharge and concentration data from other CSO and stormwater events in the literature. The variability of the parameters within each event was analyzed by normalizing flowrate, concentration and event duration to their respective peak values. The normalized flowrate data indicate that the second decile of the discharge periods was associated with peak flowrates. The dynamic behavior of CSO flowrates can be characterized by a linearly increasing trend and then a logarithmically decreasing trend in terms of normalized values. The samples captured during the first decile of the events were illustrated to be a better representation of peak concentrations of all four contaminants. By analyzing the discharge period in three sections (i.e. 1st decile, 2nd decile and remainder), a semi-probabilistic CSO loading model is proposed for the entire discharge period taking into account the variability of the phenomena. Findings can help water managers and utilities to characterize their source waters for better planning and to more efficiently design sampling campaigns for capturing peak concentrations at drinking water treatment plants.

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.

Temporal variability of parasites, bacterial indicators, and wastewater micropollutants in a water resource recovery facility under various weather conditions.

Wastewater discharges lead to the deterioration of receiving waters through treated effluents and by-passes, combined and sanitary sewer overflows, and cross-connections to storm sewers. The influence of weather conditions on fecal indicator bacteria, pathogens and wastewater micropollutants on raw and treated sewage concentrations has not been extensively characterized. However, such data are needed to understand the effects of by-pass discharges and incomplete treatment on receiving waters. A water resource recovery facility was monitored for pathogenic parasites (Cryptosporidium oocysts, Giardia cysts), fecal indicator bacteria (Escherichia coli, Clostridium perfringens), and wastewater micropollutants (caffeine, carbamazepine, 2-hydroxycarbamazepine, acesulfame, sucralose, and aspartame) during 6 events under different weather conditions (snowmelt and trace to 32 mm 2-day cumulative precipitation). Greater intra- and inter-event variability was observed for Giardia, E. coli and C. perfringens than for studied WWMPs. Even with the addition of inflow and infiltration, daily variations dominated concentration trends. Thus, afternoon and early evening were identified as critical times with regards to high concentrations and flows for potential by-pass discharges. Peak concentrations of Giardia were observed during the June wet weather event (1010 cysts/L), with the highest flowrates relative to the mean monthly flowrate. Overall, Giardia, E. coli and C. perfringens concentrations were positively correlated with flowrate (R > 0.32, p < 0.05). In raw sewage samples collected under high precipitation conditions, caffeine, carbamazepine and its metabolite 2-OH-carbamazepine were significantly correlated (p < 0.05) with Giardia, E. coli, and C. perfringens demonstrating that they are useful markers for untreated sewage discharges. Data from the study are needed for estimating peak concentrations discharged from wastewater sources in relation to precipitation or snowmelt events.