Actionable wastewater surveillance: application to a university residence hall during the transition between Delta and Omicron resurgences of COVID-19.

Wastewater surveillance has gained traction during the COVID-19 pandemic as an effective and non-biased means to track community infection. While most surveillance relies on samples collected at municipal wastewater treatment plants, surveillance is more actionable when samples are collected "upstream" where mitigation of transmission is tractable. This report describes the results of wastewater surveillance for SARS-CoV-2 at residence halls on a university campus aimed at preventing outbreak escalation by mitigating community spread. Another goal was to estimate fecal shedding rates of SARS-CoV-2 in a non-clinical setting. Passive sampling devices were deployed in sewer laterals originating from residence halls at a frequency of twice weekly during fall 2021 as the Delta variant of concern continued to circulate across North America. A positive detection as part of routine sampling in late November 2021 triggered daily monitoring and further isolated the signal to a single wing of one residence hall. Detection of SARS-CoV-2 within the wastewater over a period of 3 consecutive days led to a coordinated rapid antigen testing campaign targeting the residence hall occupants and the identification and isolation of infected individuals. With knowledge of the number of individuals testing positive for COVID-19, fecal shedding rates were estimated to range from 3.70 log10 gc ‧ g feces-1 to 5.94 log10 gc ‧ g feces-1. These results reinforce the efficacy of wastewater surveillance as an early indicator of infection in congregate living settings. Detections can trigger public health measures ranging from enhanced communications to targeted coordinated testing and quarantine.

Variation in the diversity of bacterial communities and potential sources of fecal contamination of beaches in the Huron to Erie corridor.

Understanding the diversity of bacteria and E.coli levels at beaches is important for managing health risks. This study compared temporal changes of the bacterial communities of Belle Isle Beach (Detroit, MI) and Sand Point Beach (Windsor, ONT), both located near the Lake St. Clair origin of the Detroit River. Water samples collected 4 days/week for 12 weeks in summer, were subjected to 16S rRNA analysis of amplicon sequencing and E. coli enumeration. Bacterial communities changed over time, as determined by cluster dendrogram analysis, exhibiting different communities in July and August than in June and different communities at the two beaches. After June, alpha diversity decreased and relative abundance of Enterobacter (Gammaproteobacteria) increased at Sand Point; whereas, Belle Isle maintained its alpha diversity and dominance by Betaproteobacteria and Actinobacteria. Contamination at both beaches is dominated by birds (23% to 50% of samples), while only ∼10% had evidence of human-associated bacteria. High E. coli at both beaches was often associated with precipitation. Nearshore sampling counts were higher than waist-deep sampling counts. Despite the dynamic changes in bacterial communities between the two beaches, this analysis based on 16S rRNA amplicon sequencing is able to provide information about bacterial types associated with high E. coli levels and to use bacterial sequences to more precisely determine sources and health relevance of contaminants.

Averting an Outbreak of SARS-CoV-2 in a University Residence Hall through Wastewater Surveillance.

A wastewater surveillance program targeting a university residence hall was implemented during the spring semester 2021 as a proactive measure to avoid an outbreak of COVID-19 on campus. Over a period of 7 weeks from early February through late March 2021, wastewater originating from the residence hall was collected as grab samples 3 times per week. During this time, there was no detection of SARS-CoV-2 by reverse transcriptase quantitative PCR (RT-qPCR) in the residence hall wastewater stream. Aiming to obtain a sample more representative of the residence hall community, a decision was made to use passive samplers beginning in late March onwards. Adopting a Moore swab approach, SARS-CoV-2 was detected in wastewater samples just 2 days after passive samplers were deployed. These samples also tested positive for the B.1.1.7 (Alpha) variant of concern (VOC) using RT-qPCR. The positive result triggered a public health case-finding response, including a mobile testing unit deployed to the residence hall the following day, with testing of nearly 200 students and staff, which identified two laboratory-confirmed cases of Alpha variant COVID-19. These individuals were relocated to a separate quarantine facility, averting an outbreak on campus. Aggregating wastewater and clinical data, the campus wastewater surveillance program has yielded the first estimates of fecal shedding rates of the Alpha VOC of SARS-CoV-2 in individuals from a nonclinical setting. IMPORTANCE Among early adopters of wastewater monitoring for SARS-CoV-2 have been colleges and universities throughout North America, many of whom are using this approach to monitor congregate living facilities for early evidence of COVID-19 infection as an integral component of campus screening programs. Yet, while there have been numerous examples where wastewater monitoring on a university campus has detected evidence for infection among community members, there are few examples where this monitoring triggered a public health response that may have averted an actual outbreak. This report details a wastewater-testing program targeting a residence hall on a university campus during spring 2021, when there was mounting concern globally over the emergence of SARS-CoV-2 variants of concern, reported to be more transmissible than the wild-type Wuhan strain. In this communication, we present a clear example of how wastewater monitoring resulted in actionable responses by university administration and public health, which averted an outbreak of COVID-19 on a university campus.

Evaluating multiple predictive models for beach management at a freshwater beach in the Great Lakes region.

Recreational water quality is currently monitored at Sandpoint Beach on Lake St. Clair using culture-based enumeration of Escherichia coli. Using water quality and weather data collected over 4 yr, several multiple linear regression (MLR)-based models were developed for near real-time prediction of E. coli concentration and were tested using independent data from the fifth year. Model performance was assessed by the determination of metrics such as RMSE, accuracy, specificity, sensitivity, and area under the receiver operating characteristic curve (AUROC). Each of the developed MLR models described herein resulted in increased correct responses for both exceedance and non-exceedance of the applicable standard as compared to predictions based on E. coli measurements (persistence models, using the previous day's E. coli concentration), which is the method currently being used. The AUROC values for persistence models are between 0.5 and 0.6, as compared to >0.7 for all the MLR models described herein. Among the MLR models, model performance improved when qualitative sky weather condition, which is commonly reported but was not previously used in similar models, was included. To select the best model, a principal coordinate analysis was used to combine multiple model performance metrics and provide a more sensitive tool for model comparison. Although models developed using 2, 3, and 4 yr of monitoring data provided reasonable performance, the model developed using the most recent 2-yr data was marginally better. Thus, data from the most recent 2 yr are likely sufficient as a training dataset for updating the MLR model for Sandpoint Beach in the future.

Elucidating sulfate radical-mediated disinfection profiles and mechanisms of Escherichia coli and Enterococcus faecalis in municipal wastewater.

Practical applications of disinfection technologies for engineered waters require an in‒depth understanding of disinfection profiles and mechanisms of pathogenic bacteria in a complex matrix. This study investigated the inactivation of E. coli and E. faecalis by SO4•-, an emerging advanced disinfectant, in ultrapure water (UPW) and wastewater effluent (WE). Based on the bacterial inactivation kinetics in UPW in a zerovalent iron/peroxydisulfate system, the second order rate constants (k) for SO4•- reacting with E. coli and E. faecalis were measured to be (1.39 ± 0.1) × 109 M-1 s-1 and (6.71 ± 0.1) × 109 M-1 s-1, respectively. The morphological images of both bacteria by the scanning electron microscope indicated that SO4•- initiates oxidative reactions on the wall/membranes, causing their irreversible damage, ultimately affecting membrane permeability and physiological functions. To profile the inactivation kinetics of two strains of bacteria in WE matrix, a mechanistic process‒based model with the obtained k values was developed. Sensitivity and uncertainty analyses indicated that the key parameters for the model predictions were the concentrations of halide ions (i.e., Br- and Cl-) in WE and their k values reacting with SO4•- accounting for >80% of uncertainty or variance expected in predicted bacterial inactivation. This model allows precise estimation of required disinfectant dose even in complex water matrices, shedding lights on the extension of application of SO4•-‒based technology in wastewater treatments.

Inhibition of anaerobic biological sulfate reduction process by copper precipitates.

The single-stage biological sulfate reduction process for treatment of heavy metal laden wastewater is a promising treatment method, but the formation of metal precipitates has been suggested to be inhibitory to the activity of sulfate reducers. The present study examined the impact of copper (Cu) precipitates on anaerobic biological sulfate reduction in semi continuous stirred tank reactors (SCSTRs) at 35 ±â€¯2 °C. The results show that Cu precipitates significantly affected the sulfate reduction process. At an HRT of 50 days, steady-state sulfate reduction was approximately 55% at influent Cu concentrations of 0 (control) and 200 mg/L, which reduced to approximately 39% at influent Cu concentration of 400 mg/L. Microbial population (measured as volatile suspended solids) and rate of sulfate reduction were also affected, with reductions observed even at influent Cu of 200 mg/L. Copper precipitates also affected the microbial community diversity distribution.

Wastewater Colloidal Organic Carbon: Characterization of Filtration Fractions Using 1H NMR.

The current study separates colloidal organic carbon (COC) of municipal wastewater using membrane and ultrafiltration filters followed by characterization using 1H nuclear magnetic resonance (NMR) and UV absorbance with the goal of determination of size-specific characteristics, which may be used to correlate contaminant partitioning to natural COC. Passing fractions included 49.7, 44.8, 39.3, and 33.1 mg/L COC for filter sizes 1.5 µm, 0.45 µm, 100 kDa, and 1 kDa, respectively. The methodology used for processing COC prior to 1H NMR characterization was novel and successful in concentrating COC without modification of structures, which is the general drawback of other separation techniques such as resin extractions. This concentration technique is quite simple (i.e., not dependent on specialized instrumentation) and allows much shorter NMR experimental durations saving time and cost of analysis. Further work using NMR techniques will allow for greater understanding of COC molecular characteristics and be valuable for use in predictive modeling improvements.

Hydrophobic organic compound (HOC) partitioning behaviour to municipal wastewater colloidal organic carbon.

The sorption behaviour of hydrophobic organic compounds (HOCs) 1,2,4,5-tetrachlor-obenzene (TeCB), pentachlorobenzene (PeCB) and hexachlorobenzene (HCB) to Aldrich humic acid (AHA) and municipal wastewater treatment plant (MWTP) influent colloidal organic carbon (COC) was investigated using the gas-stripping technique. Gas stripping assumptions of gas/water equilibrium and a constant volatilization rate were validated prior to calculation of partitioning parameters. The logKCOC coefficients determined for MWTP influent COC were 3.86, 3.89 and 3.19 for TeCB, PeCB and HCB, respectively. Due to the presence of COC, the mass transfer of TeCB, PeCB and HCB with the primary effluent to the secondary biological stage was predicted to increase 8.7%, 9.6% and 1.2%, respectively, based on the measured COC concentration and logKCOC values. The calculated increases in apparent solubility for TeCB, PeCB and HCB in the primary effluent were 14.4%, 22.0% and 6.5%, respectively. This partitioning did not follow the expected trend (TeCB < PeCB < HCB) based on hydrophobicity predicted by octanol/water partitioning. The trend observed differed from the current AHA standard and correlation-based trends derived from natural COCs. More experiments with other HOCs are needed to better understand and predict the magnitude and significance of MWTP influent COCs on the fate and transport of HOCs during the MWTP process.

Investigation of hydrophobic organic carbon (HOC) partitioning to 1 kDa fractionated municipal wastewater colloids.

Natural organic matter from the aquatic environment passing a 1 kDa filter has been hypothesized to not contribute appreciably to hydrophobic organic compound (HOC) partitioning; however, to our knowledge this limit has not been verified experimentally for any sorbate/sorbent system. Presently, colloidal organic carbon (COC) < 1 kDa approached 70% of the total COC (<1.5 µm) mass in primary effluent (PE) from a municipal wastewater treatment plant. Partitioning of HOCs 1,2,4,5-tetrachlorobenzene, pentachlorobenzene, and hexachlorobenzene to COC for both 1.5 µm and 1 kDa filtrates of PE was investigated using the gas-stripping technique. Contrary to the hypothesis, significant HOC-COC partitioning to the 1 kDa filtrate was observed with organic carbon-normalized partitioning coefficients (logKCOC) of 4.30, 4.36, and 3.74 for 1,2,4,5-TeCB, PeCB, and HCB, respectively. Further, partitioning to COC < 1 kDa dominated the overall partitioning of the three chlorobenzenes in the 1.5 µm filtrate, and the partitioning behavior did not follow the trend based on hydrophobicity (KOW). The results show that significant partitioning of HOC may occur to OC < 1 kDa and highlights the need for further experiments with other HOCs and COC characterization to better understand and explain the observed partitioning.

Evaluation of the gas stripping technique for calculation of Henry's law constants using the initial slope method for 1,2,4,5-tetrachlorobenzene, pentachlorobenzene, and hexachlorobenzene.

Henry's law constant (HLC) is an important factor used in environmental risk assessment and fate and transport models to describe mass transfer of chemical between water and air. HLCs and structure-property relationships were assessed for 1,2,4,5-tetrachlorobenzene (TeCB), pentachlorobenzene (PeCB), and hexachlorobenzene (HCB). HLCs were determined using the volatilization rate (kv) of sparged chemical at 25 °C. Despite the assumption that kv should be constant throughout the stripping duration, results indicated that kv decreased over time according to three separate slope regions. Results of ANCOVA indicate that kv is statistically different in the third slope region, which leads to the conclusion that use of the entire stripping data set would lead to biased HLCs. This decrease in kv may be attributed to desorption from sparger surfaces, which has not been considered widely in the literature. Statistical analysis was possible because of the robustness of the current experimental procedure which included numerous replications (15 total spargers) and extensive data points available to discern key slope changes. HLCs determined using the gas stripping technique were 57, 33, and 30 Pa m(3) mol(-1) for 1,2,4,5-TeCB, PeCB, and HCB, respectively. In comparison to literature values, current TeCB and HCB HLCs were within wide reference ranges spanning approximately an order of magnitude for each chemical. PeCB HLC of the current study was two times lower than the lowest reference data.

Continued development of a mass balance model of chemical fate in a sewage treatment plant.

Chemicals that pass through a sewage treatment plant (STP) and into receiving waters lead to exposure of human and ecological receptors. Most countries require that such chemicals and especially those that are new to commerce be assessed for their treatability in STPs using a screening-level model. The STP model has been widely used for such assessments in Canada, the US and elsewhere. It is important for both industry and regulators that such a model be simple, accurate and applicable even with the limited data available for most chemicals. The STP model has been upgraded to include the capability to handle ionizing chemicals, and a variety of treatment plant configurations commonly used in Canada and elsewhere around the world. A scheme for obtaining appropriate biodegradation half-lives for the different treatment options from available aqueous biodegradation half-lives or standard biodegradability tests is suggested. Model simulations show good agreement with pilot-scale experimental data from literature for 20 organic chemicals with widely varying physico-chemical properties.

Evaluation of the STP model: comparison of modelled and experimental results for ten polycyclic aromatic hydrocarbons (PAHs).

Screening level risk assessment models are used by many countries to assess the treatability of organic chemicals during the sewage treatment process, especially those that are new to commerce. The performance of one such model, the sewage treatment plant model, is evaluated in the current study by comparing model predictions with actual measurement data collected at various stages of a typical full-scale activated sludge type sewage treatment plant. A suite of ten polycyclic aromatic hydrocarbons (PAHs) with widely varying physico-chemical properties were monitored for the comparison. Model predicted removal efficiencies were in very good agreement with those measured for all ten PAHs. Observed chemical concentrations and their trends at various stages of the sewage treatment process were also well simulated by the model. Results also suggest that a reasonable first approximation estimate of a range for the biodegradation half-life needed for the model may be obtained by dividing reported aqueous biodegradation half-life by scaling factors of 50 and 150.

Fate, partitioning, and mass loading of polybrominated diphenyl ethers (PBDEs) during the treatment processing of municipal sewage.

Sewage treatment plant (STP) effluents are likely a major source of contamination for PBDEs, especially in the receiving water bodies of local aquatic environments surrounding the location of these discharges. Congeners of the pentaBDE mixture, 2,2,',4,4'-tetrabromodiphenyl ether (BDE47), 2,2,',4,4',5-pentabromodiphenyl ether (BDE99), 2,2,',4,4',6-pentabromodiphenyl ether (BDE100), 2,2,',4,4',5,5'-hexabromodiphenyl ether (BDE153), and 2,2,',4,4',5,6'-hexabromodiphenyl ether (BDE154), are of great environmental concern in North America due to their persistence, potential for bioaccumulation, and >97% use of the global production of the mixture in the region. Detailed characterization of the distribution of eight PBDE congeners (2,4,4'-tribromoDE (BDE28) and BDE47, 99, 100, 138, 153, 154, and 183) was carried out at five sites along the treatment process at an activated sludge-type secondary treatment municipal STP facility. PentaBDE mixture congeners, sigma5PBDE (sum of BDE47, 99, 100, 153, and 154) accounted for >98% of the total (sigma 8) PBDE concentration at all sites, with over 80% of the composition being BDE47 and BDE99. Presence of dissolved organic matter affected the mobility of PBDEs during the initial stages of the treatment process. About 9% of the influent mass of sigma5PBDE to the facility is estimated to be discharged into the Little River (leading to the Detroit River) with the final effluent, resulting in an estimated mass loading of approximately 0.7 kg/year. The total mass loading of sigma5PBDE to the Detroit River is expected to be much larger as effluent from this facility accounts for <10% of the total STP discharges to the river.

Electrochemical degradation of 1,2- dichloroethane (DCA) in a synthetic groundwater medium using stainless-steel electrodes.

The electrochemical degradation of 1,2-dichloroethane (DCA) was examined in a synthetic groundwater medium. An undivided electrolytic reactor constructed with 304 L-type stainless-steel plate electrodes was employed in all experiments. The removal of total organic carbon (TOC) content during the electrolysis of DCA was experimentally examined. Stainless-steel plate electrodes were effective in degrading DCA under experimental conditions including varying initial concentrations, chloride concentrations, electrolyte conductivities and applied current densities. A half-life method demonstrated TOC removal followed zero-order kinetics under the experimental conditions examined. Chlorides concentration and applied current affected the TOC removal rates. An increase in current density increased the rate of TOC removal but caused a reduction in mineralization current efficiency. Increase in electrolyte conductivity had no effect on TOC removal rates but it decreased the energy consumption by reducing the cell voltage. Reaction temperature was shown to affect the TOC removal and was modeled by the Arrhenius equation.

A dynamic level IV multimedia environmental model: application to the fate of polychlorinated biphenyls in the United Kingdom over a 60-year period.

A dynamic or level IV multimedia model is described and illustrated by application to the fate of three polychlorinated biphenyl (PCB) congeners in the United Kingdom over a 60-year period from their introduction into commerce until the present. Models of this type are shown to be valuable for elucidating the time response of environmental systems to increasing, decreasing, or pulse inputs. The suggestion is made that in addition to the outputs of time-dependent concentrations (which can be compared with monitoring data for validation purposes), it is useful to examine masses, fugacities, and fugacity ratios between media? The relative importance of processes is best evaluated by compiling cumulative intermedia fluxes and quantities lost by reaction and advection and examining the corresponding process rate constants or their reciprocals, the characteristic times. The suggestion is made that uncertainty and sensitivity analyses are desirable, but it must be appreciated that relative sensitivities of input parameters may change during the simulation period, so a single sensitivity analysis conducted at one point in time can be misleading. The use of the model for forecasting future trends in concentration is illustrated. Given the uncertainties in emission and advective inflow rates, the simulation of PCB fate in the United Kingdom is regarded as showing time trends that are in satisfactory agreement with monitoring data.