Evaluating the in-sewer stability of three potential population biomarkers for application in wastewater-based epidemiology

A feasibility study on cortisol and cortisone as biomarkers for psychological stress in wastewater-based epidemiology

Psychological stress has a significant impact on individuals' quality of life and health. Traditionally, psychological stress assessment relies on self-reported tools such as the Perceived Stress Scale (PSS), which are inherently subjective. This study aims to evaluate the feasibility of using wastewater-based epidemiology (WBE) to assess cortisol and cortisone as biomarkers for psychological stress. We conducted sampling and monitoring of cortisol and cortisone concentrations at both a small-scale campus setting (five weeks) and a large-scale municipal wastewater treatment plant (12 months), calculating the mass loads of these hormones. At the campus level, while the mass load of cortisone was higher during exam weeks compared to regular class weeks, and higher in females than in males, no significant differences were observed in the mass load of cortisol. The mass load results of cortisone were consistent with the findings of the PSS-14 questionnaire. These results suggest that cortisone is a more suitable biomarker for psychological stress assessment. In the large-scale municipal wastewater samples, seasonal variations were observed, with higher levels of cortisol and cortisone in winter compared to summer, likely due to the COVID-19 outbreak in winter and the presence of external pharmaceutical sources. The results indicate that cortisone is more suitable for small-scale stress assessments, as larger-scale evaluations may be more significantly influenced by wastewater transport or sampling methodologies.

Improved entropy-CRITIC population model based on temporal and spatial variability: Construction and application in wastewater epidemiology

Numerous factors contribute to the uncertainty inherent in conducting wastewater-based epidemiology (WBE), with shifting populations exerting a significant influence. However, traditional single- and multi-parameter population models suffer from certain limitations. This study employs an evaluation model framework to construct a model (EC model) based on data characteristics. Weight coefficients derived from 16 cities across seven regions of China are aggregated into a national model. In contrast to alternative models, the EC model exhibits a robust correlation (r2 = 0.98) with census population data, suggesting a potentially more precise depiction of population dynamics. The low variability (RSD = 9.73 %) indicates effective constraint of anomalous parameter fluctuations, yielding minimal Bias (-1.12 %) and SRMSE (14.75 %), thus ensuring reliable population estimation. The model is applied to estimate the consumption of lifestyle-related compounds and the prevalence of hypertension in China. Northern regions demonstrate higher consumption levels, alongside a significant disparity in hypertension prevalence (26.96 %) compared to the south (16.01 %). Hypertension exhibits positive correlations with lifestyle-related compounds such as alcohol and nicotine (r = 0.52, r = 0.55). Sensitivity analysis reveals that the EC model introduces an uncertainty of 24.48 % in population estimates. Through the incorporation of representative datasets and novel algorithms, this model has the potential to enhance the reliability of outcomes in WBE strategy implementation.

Identification of protein biomarkers in wastewater linked to the incidence of COVID-19

Wastewater-based epidemiological (WBE) surveillance is a viable disease surveillance technique capable of monitoring the spread of infectious disease agents in sewershed communities. In addition to detecting viral genomes in wastewater, WBE surveillance can identify other endogenous biomarkers that are significantly elevated and excreted in the saliva, urine, and/or stool of infected individuals. Human protein biomarkers allow the realization of real-time WBE surveillance using highly sensitive biosensors. In this study, we analyzed endogenous protein biomarkers present in wastewater influent through liquid chromatography-tandem mass spectrophotometry and scaffold data-independent acquisition to identify candidate target protein biomarkers for WBE surveillance of SARS-CoV-2. We found that out of the 1382 proteins observed in the wastewater samples, 44 were human proteins associated with infectious diseases. These included immune response substances such as immunoglobulins, cytokine-chemokines, and complements, as well as proteins belonging to antimicrobial and antiviral groups. A significant correlation was observed between the intensity of human infectious disease-related protein biomarkers in wastewater and COVID-19 case numbers. Real-time WBE surveillance using biosensors targeting immune response proteins, such as antibodies or immunoglobulins, in wastewater holds promise for expediting the implementation of relevant policies for the effective prevention of infectious diseases in the near future.

Estimating rates of change to interpret quantitative wastewater surveillance of disease trends

BACKGROUND

Wastewater monitoring data can be used to estimate disease trends to inform public health responses. One commonly estimated metric is the rate of change in pathogen quantity, which typically correlates with clinical surveillance in retrospective analyses. However, the accuracy of rate of change estimation approaches has not previously been evaluated.

OBJECTIVES

We assessed the performance of approaches for estimating rates of change in wastewater pathogen loads by generating synthetic wastewater time series data for which rates of change were known. Each approach was also evaluated on real-world data.

METHODS

Smooth trends and their first derivatives were jointly sampled from Gaussian processes (GP) and independent errors were added to generate synthetic viral load measurements; the range hyperparameter and error variance were varied to produce nine simulation scenarios representing different potential disease patterns. The directions and magnitudes of the rate of change estimates from four estimation approaches (two established and two developed in this work) were compared to the GP first derivative to evaluate classification and quantitative accuracy. Each approach was also implemented for public SARS-CoV-2 wastewater monitoring data collected January 2021-May 2023 at 25 sites in North Carolina, USA.

RESULTS

All four approaches inconsistently identified the correct direction of the trend given by the sign of the GP first derivative. Across all nine simulated disease patterns, between a quarter and a half of all estimates indicated the wrong trend direction, regardless of estimation approach. The proportion of trends classified as plateaus (statistically indistinguishable from zero) for the North Carolina SARS-CoV-2 data varied considerably by estimation method but not by site.

DISCUSSION

Our results suggest that wastewater measurements alone might not provide sufficient data to reliably track disease trends in real-time. Instead, wastewater viral loads could be combined with additional public health surveillance data to improve predictions of other outcomes.

High throughput and sensitive quantitation of tobacco-specific alkaloids and nitrosamines in wastewater

Tobacco-specific alkaloids and nitrosamines are important biomarkers for the estimation of tobacco use and human exposure to tobacco-specific nitrosamines that can be monitored by wastewater analysis. Thus far their analysis has used solid phase extraction, which is costly and time-consuming. In this study, we developed a direct injection liquid chromatography-tandem mass spectrometry method for the quantification of two tobacco-specific alkaloids and five nitrosamines in wastewater. The method achieved excellent linearity (R2 > 0.99) for all analytes, with calibration ranging from 0.10 to 800 ng/L. Method limits of detection and quantification were 0.17 ng/L (N-nitrosonornicotine, NNN) and 1.0 ng/L (N-nitrosoanatabine (NAT) and NNN), with acceptable accuracy (100 % ± 20 %) and precision (± 15 %). Analyte loss during filtration was < 15 %, and the relative matrix effect was < 10 %. The method was applied to 43 pooled wastewater samples collected from three wastewater treatment plants in Australia between 2017 and 2021. Anabasine and anatabine were detected in all samples at concentrations of 5.0 - 33 ng/L and 12 - 41 ng/L, respectively. Three of the five tobacco-specific nitrosamines (NAT, NNN, and (4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol) (NNAL)) were detected, in < 50 % of the wastewater samples, with concentrations nearly ten times lower than the tobacco alkaloids (< 1.0 - 6.2 ng/L). In-sewer stability of the nitrosamines was also assessed in this study, with four (NAT, NNAL, NNN, and N-nitrosoanabasine (NAB)) being stable (i.e. < 20 % transformation over 12 h in both control reactor (CR) and rising main reactor (RM) and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) being moderately stable (< 40 % loss over 12 h in RM). This direct injection method provides a high-throughput approach in simultaneous investigation of tobacco use and assessment of public exposure to tobacco-specific nitrosamines.

Current state and future perspectives on de facto population markers for normalization in wastewater-based epidemiology: A systematic literature review

Wastewater-based epidemiology (WBE) and wastewater surveillance have become a valuable complementary data source to collect information on community-wide exposure through the measurement of human biomarkers in influent wastewater (IWW). In WBE, normalization of data with the de facto population that corresponds to a wastewater sample is crucial for a correct interpretation of spatio-temporal trends in exposure and consumption patterns. However, knowledge gaps remain in identifying and validating suitable de facto population biomarkers (PBs) for refinement of WBE back-estimations. WBE studies that apply de facto PBs (including hydrochemical parameters, utility consumption data sources, endo- and exogenous chemicals, biological biomarkers and signalling records) for relative trend analysis and absolute population size estimation were systematically reviewed from three databases (PubMed, Web of Science, SCOPUS) according to the PRISMA guidelines. We included in this review 81 publications that accounted for daily variations in population sizes by applying de facto population normalization. To date, a wide range of PBs have been proposed for de facto population normalization, complicating the comparability of normalized measurements across WBE studies. Additionally, the validation of potential PBs is complicated by the absence of an ideal external validator, magnifying the overall uncertainty for population normalization in WBE. Therefore, this review proposes a conceptual tier-based cross-validation approach for identifying and validating de facto PBs to guide their integration for i) relative trend analysis, and ii) absolute population size estimation. Furthermore, this review also provides a detailed evaluation of the uncertainty observed when comparing different de jure and de facto population estimation approaches. This study shows that their percentual differences can range up to ±200 %, with some exceptions showing even larger variations. This review underscores the need for collaboration among WBE researchers to further streamline the application of de facto population normalization and to evaluate the robustness of different PBs in different socio-demographic communities.

Wastewater-based surveillance as a tool for public health action: SARS-CoV-2 and beyond

Wastewater-based surveillance (WBS) has undergone dramatic advancement in the context of the coronavirus disease 2019 (COVID-19) pandemic. The power and potential of this platform technology were rapidly realized when it became evident that not only did WBS-measured SARS-CoV-2 RNA correlate strongly with COVID-19 clinical disease within monitored populations but also, in fact, it functioned as a leading indicator. Teams from across the globe rapidly innovated novel approaches by which wastewater could be collected from diverse sewersheds ranging from wastewater treatment plants (enabling community-level surveillance) to more granular locations including individual neighborhoods and high-risk buildings such as long-term care facilities (LTCF). Efficient processes enabled SARS-CoV-2 RNA extraction and concentration from the highly dilute wastewater matrix. Molecular and genomic tools to identify, quantify, and characterize SARS-CoV-2 and its various variants were adapted from clinical programs and applied to these mixed environmental systems. Novel data-sharing tools allowed this information to be mobilized and made immediately available to public health and government decision-makers and even the public, enabling evidence-informed decision-making based on local disease dynamics. WBS has since been recognized as a tool of transformative potential, providing near-real-time cost-effective, objective, comprehensive, and inclusive data on the changing prevalence of measured analytes across space and time in populations. However, as a consequence of rapid innovation from hundreds of teams simultaneously, tremendous heterogeneity currently exists in the SARS-CoV-2 WBS literature. This manuscript provides a state-of-the-art review of WBS as established with SARS-CoV-2 and details the current work underway expanding its scope to other infectious disease targets.

Pharmaceutical and Recreational Drug Usage Patterns during and Post COVID-19 Determined by Wastewater-Based Epidemiology

Wastewater-based epidemiology (WBE) was applied to evaluate the consumption trends of pharmaceuticals (i.e., antibiotics, non-steroidal anti-inflammatory drugs, antiepileptics, antihypertensives, and others), as well as recreational drugs (caffeine, alcohol, and nicotine), in Latvia from December 2020 to July 2023. The time period covers both the COVID-19 pandemic and the post-pandemic periods; therefore, the impact of the implemented restrictions and the consequences of the illness in terms of the usage of pharmaceuticals thereon were investigated. Additionally, the seasonality and impact of the seasonal flu and other acute upper respiratory infections were studied. The results revealed that the pandemic impacted the consumption of alcohol, nicotine, and caffeine, as well as several pharmaceuticals, such as antihypertensives, antidepressants, psychiatric drugs, and the painkiller ibuprofen. The findings suggest that the imposed restrictions during the pandemic may have had a negative effect on the population's health and mental well-being. Distinct seasonal trends were discovered in the consumption patterns of caffeine and alcohol, where lower use was observed during the summer. The seasonal consumption trends of pharmaceuticals were discovered in the case of antibiotics, the antiasthmatic drug salbutamol, and the decongestant xylometazoline, where higher consumption occurred during colder seasons.

In-sewer stability of 31 human health biomarkers and suitability for wastewater-based epidemiology

Monitoring urinary markers of dietary, disease, and stress by wastewater-based epidemiology (WBE) is a promising tool to better understand population health and wellbeing. However, common urinary biomarkers are subject to degradation in sewer systems and their fates have to be assessed before they can be used in WBE. This study investigated the stability of 31 urinary biomarkers (12 food biomarkers, 8 vitamins, 9 oxidative stress biomarkers, and 1 histamine biomarker) in a laboratory sewer sediment reactor and evaluated their suitability for WBE, considering their detectability in real wastewater and in-sewer stability. These biomarkers showed various transformation patterns, among which 16 compounds had half-lives <2 h while other 15 compounds presented moderate to high stability (2 to >500 h). Thirteen biomarkers showed potential for WBE because of their consistently measurable concentrations in untreated wastewater and sufficient in-sewer stability. Eighteen biomarkers were unsuitable due to their rapid in-sewer degradation and/or undetectable concentration levels in untreated wastewater using previous methods. Transformation rates of these biomarkers showed generally weak relationships with molecular properties but relatively higher correlations with biological activities in sewers. Overall, this study determined in-sewer stability of 31 health-related biomarkers through laboratory experiments, providing new findings to WBE for population health assessment.

Determination of 25 quaternary ammonium compounds in sludge by liquid chromatography-mass spectrometry

With the pandemic of COVID-19, the application of quaternary ammonium compounds (QACs), which can be used in SARS-CoV-2 disinfection products, has increased substantially. QACs cumulated in sewer system are ultimately deposited and enriched in sludge. QACs in the environment can adversely affect human health and the environment. In this study, a liquid chromatography-mass spectrometry method was established for the simultaneous determination of 25 QACs in sludge samples. Ultrasonic extraction and filtration of the samples was performed using a 50 mM hydrochloric acid-methanol solution. The samples were separated by liquid chromatography and detected in multiple reaction monitoring mode. The matrix effects of the sludge on the 25 QACs ranged from - 25.5% to 7.2%. All substances showed good linearity in the range of 0.5-100 ng/mL, with all determination coefficients (R2) greater than 0.999. The method detection limits (MDLs) were 9.0 ng/g for alkyltrimethylammonium chloride (ATMAC), 3.0 ng/g for benzylalkyldimethylammonium chloride (BAC), and 3.0 ng/g for dialkyldimethylammonium chloride (DADMAC). The spiked recovery rates were in the range of 74-107%, while the relative standard deviations were in the range of 0.8-20.6%. Considering its sensitivity, accuracy, and easy operation, the proposed method in this study was used to determine 22 sludge samples collected from a comprehensive wastewater treatment plant. The results showed that the concentrations of ΣATMACs, ΣBACs, and ΣDADMACs were 19.684, 3.199, and 8.344 μg/g, respectively. The main components included ATMAC-C16, ATMAC-C18, ATMAC-C20, ATMAC-C22, BAC-C12, and DADMAC-C18:C18, with concentrations exceeding 1.0 μg/g. The concentration relationships of different components in the congeners showed that some components were of similar origin.

Understanding common population markers for SARS-CoV-2 RNA normalization in wastewater - A review

Wastewater monitoring and epidemiology have seen renewed interest during the recent COVID-19 pandemic. As a result, there is an increasing need to normalize wastewater-derived viral loads in local populations. Chemical tracers, both exogenous and endogenous compounds, have proven to be more stable and reliable for normalization than biological indicators. However, differing instrumentation and extraction methods can make it difficult to compare results. This review examines current extraction and quantification methods for ten common population indicators: creatinine, coprostanol, nicotine, cotinine, sucralose, acesulfame, androstenedione 5-hydroindoleacetic acid (5-HIAA), caffeine, and 1,7-dimethyluric acid. Some wastewater parameters such as ammonia, total nitrogen, total phosphorus, and daily flowrate were also evaluated. The analytical methods included direct injection, dilute and shoot, liquid/liquid, and solid phase extraction (SPE). Creatine, acesulfame, nicotine, 5-HIAA and androstenedione have been analysed by direct injection into LC-MS; however, most authors prefer to include SPE steps to avoid matrix effects. Both LC-MS and GC-MS have been successfully used to quantify coprostanol in wastewater, and the other selected indicators have been quantified successfully with LC-MS. Acidification to stabilize the sample before freezing to maintain the integrity of samples has been reported to be beneficial. However, there are arguments both for and against working at acidic pHs. Wastewater parameters mentioned earlier are quick and easy to quantify, but the data does not always represent the human population effectively. A preference for population indicators originating solely from humans is apparent. This review summarises methods employed for chemical indicators in wastewater, provides a basis for choosing an appropriate extraction and analysis method, and highlights the utility of accurate chemical tracer data for wastewater-based epidemiology.

Application of the metal ions as potential population biomarkers for wastewater-based epidemiology: estimating tobacco consumption in Southern China

Wastewater-based epidemiology (WBE) is an objective approach for the estimation of population-level exposure to a wide range of substances, in which the use of a population biomarker (PB) could significantly reduce back-calculation errors. Although some endogenous or exogenous compounds such as cotinine and other hormones have been developed as PBs, more PBs still need to be identified and evaluated. This study aimed to propose a novel method to estimate population parameters from the mass load of metal ion biomarkers in wastewater, and estimate the consumption of tobacco in 24 cities in Southern China using the developed method. Daily wastewater samples were collected from 234 wastewater treatment plants (WWTPs) in 24 cities in Southern China. Atomic absorption spectroscopy (AAS) was applied to determine the concentrations of common health-related metal ions in wastewater, including sodium (Na), potassium (K), magnesium (Mg), calcium (Ca), iron (Fe), and zinc (Zn), and compared them with the daily mass load of cotinine corresponding to catchment populations. The concentrations of cotinine in wastewater samples were measured using liquid chromatography-tandem mass spectrometry. There were clear and strong correlations between the target metal ion equivalent population and census data. The correlation coefficients (R) were R_K = 0.78, R_Na = 0.66, R_Ca = 0.81, R_Mg = 0.77, and R_Fe = 0.69, at p < 0.01 and R² > 0.6. Subsequently, the combination of WBE and metal ion PBs was used to estimate tobacco consumption. Daily consumption of nicotine was estimated to be approximately 1.76 ± 1.19 mg/d/capita, equivalent to an average of 13.0 ± 8.75 cigarettes/d being consumed by smokers. The data on tobacco consumption in this study were consistent with those in traditional surveys in Southern China. The metal ion potassium is an appropriate PB for reflecting the real-time population and could be used to evaluate the tobacco consumption in WBE study.

Stability of human stress hormones and stress hormone metabolites in wastewater under oxic and anoxic conditions

Levels in wastewater of human stress biomarkers, such as cortisone (E), cortisol (F), tetrahydrocortisone (THE), and tetrahydrocortisol (THF) may serve as indicators of population wellbeing and overall health. This study examined the stability of these biosignature compounds in wastewater to inform on their applicability for use in wastewater-based epidemiology (WBE). Wastewater from two undisclosed U.S. municipalities were fortified with the above four biomarkers of stress to a concentration of 10 ppb, and their decay was studied at three temperatures (15, 25, and 35 °C) over 24 h in oxic and anoxic conditions. Samples were analyzed using liquid chromatography tandem mass spectrometry (LC-MS/MS) in conjunction with the isotope dilution method for absolute quantitation. Results demonstrated short-term persistence (24 h) of biomarkers at low temperatures (15 °C), and accelerating kinetics of decay that were positively correlated with temperature increases. Among the four biomarkers evaluated, the tetrahydro derivatives were the most long-lived sewage-borne stress biomarkers and these are recommended as prime analytical targets for use in WBE when tracking population stress. Statistical analyses using a non-parametric Wilcoxon test further revealed no significant differences (p > 0.05) between oxic and anoxic decay rates for all stress biomarkers in wastewater from all study locations, regardless of the prevailing temperature regime. This negative finding is worthy of reporting because it suggests the feasibility of straightforward modeling of stress hormone decay, irrespective of whether the sewerage system monitored contains fully filled, pressurized pipes or partially filled gravity flow pipes, whose filling level, and with it its redox conditions, are known to fluctuate over time with water use and storm events.

Expanding the Pathogen Panel in Wastewater Epidemiology to Influenza and Norovirus

Since the start of the 2019 pandemic, wastewater-based epidemiology (WBE) has proven to be a valuable tool for monitoring the prevalence of SARS-CoV-2. With methods and infrastructure being settled, it is time to expand the potential of this tool to a wider range of pathogens. We used over 500 archived RNA extracts from a WBE program for SARS-CoV-2 surveillance to monitor wastewater from 11 treatment plants for the presence of influenza and norovirus twice a week during the winter season of 2021/2022. Extracts were analyzed via digital PCR for influenza A, influenza B, norovirus GI, and norovirus GII. Resulting viral loads were normalized on the basis of NH4-N. Our results show a good applicability of ammonia-normalization to compare different wastewater treatment plants. Extracts originally prepared for SARS-CoV-2 surveillance contained sufficient genomic material to monitor influenza A, norovirus GI, and GII. Viral loads of influenza A and norovirus GII in wastewater correlated with numbers from infected inpatients. Further, SARS-CoV-2 related non-pharmaceutical interventions affected subsequent changes in viral loads of both pathogens. In conclusion, the expansion of existing WBE surveillance programs to include additional pathogens besides SARS-CoV-2 offers a valuable and cost-efficient possibility to gain public health information.

Does normalization of SARS-CoV-2 concentrations by Pepper Mild Mottle Virus improve correlations and lead time between wastewater surveillance and clinical data in Alberta (Canada): comparing twelve SARS-CoV-2 normalization approaches

Wastewater-based surveillance (WBS) data normalization is an analyte measurement correction that addresses variations resulting from dilution of fecal discharge by non-sanitary sewage, stormwater or groundwater infiltration. No consensus exists on what WBS normalization parameters result in the strongest correlations and lead time between SARS-CoV-2 WBS data and COVID-19 cases. This study compared flow, population size and biomarker normalization impacts on the correlations and lead times for ten communities in twelve sewersheds in Alberta (Canada) between September 2020 and October 2021 (n = 1024) to determine if normalization by Pepper Mild Mottle Virus (PMMoV) provides any advantages compared to other normalization parameters (e.g., flow, reported and dynamic population sizes, BOD, TSS, NH3, TP). PMMoV concentrations (GC/mL) corresponded with plant influent flows and were highest in the urban centres. SARS-CoV-2 target genes E, N1 and N2 were all negatively associated with wastewater influent pH, while PMMoV was positively associated with temperature. Pooled data analysis showed that normalization increased ρ-values by almost 0.1 and was highest for ammonia, TKN and TP followed by PMMoV. Normalization by other parameters weakened associations. None of the differences were statistically significant. Site-specific correlations showed that normalization of SARS-CoV-2 data by PMMoV only improved correlations significantly in two of the twelve systems; neither were large sewersheds or combined sewer systems. In five systems, normalization by traditional wastewater strength parameters and dynamic population estimates improved correlations. Lead time ranged between 1 and 4 days in both pooled and site-specific comparisons. We recommend that WBS researchers and health departments: a) Investigate WWTP influent properties (e.g., pH) in the WBS planning phase and use at least two parallel approaches for normalization only if shown to provide value; b) Explore normalization by wastewater strength parameters and dynamic population size estimates further; and c) Evaluate purchasing an influent flow meter in small communities to support long-term WBS efforts and WWTP management.

Biomarker selection strategies based on compound stability in wastewater-based epidemiology

The specific compositions of human excreta in sewage can be used as biomarkers to indicate the disease prevalence, health status, and lifestyle of the population living in the investigated catchment. It is important for guiding and evaluating public health policies as well as promoting human health development. Among several parameters of wastewater-based epidemiology (WBE), the decay of biomarkers during transportation in sewer and storage plays a crucial role in the back-calculation of population consumption. In this paper, we summarized the stability data of common biomarkers in storage at different temperatures and in-sewer transportation. Among them, cardiovascular drugs and antidiabetic drugs are very stable which can be used as biomarkers; most of the illicit drugs are stable except for cocaine, heroin, and tetrahydrocannabinol which could be substituted by their metabolites as biomarkers. There are some losses for part of antibiotics and antidepressants even in frozen storage. Rapid detection of contagious viruses is a new challenge for infectious disease control. With the deeper and broader study of biomarkers, it is expected that the reliable application of the WBE will be a useful addition to epidemiological studies.

The role of the sewer system in estimating urban emissions of chemicals of emerging concern

The use of chemicals by society has resulted in calls for more effective control of their emissions. Many of these chemicals are poorly characterized because of lacking data on their use, environmental fate and toxicity, as well as lacking detection techniques. These compounds are sometimes referred to as contaminants of emerging concern (CECs). Urban areas are an important source of CECs, where these are typically first collected in sewer systems and then discharged into the environment after being treated in a wastewater treatment plant. A combination of emission estimation techniques and environmental fate models can support the early identification and management of CEC-related environmental problems. However, scientific insight in the processes driving the fate of CECs in sewer systems is limited and scattered. Biotransformation, sorption and ion-trapping can decrease CEC loads, whereas enzymatic deconjugation of conjugated metabolites can increase CEC loads as metabolites are back-transformed into their parent respective compounds. These fate processes need to be considered when estimating CEC emissions. This literature review collates the fragmented knowledge and data on in-sewer fate of CECs to develop practical guidelines for water managers on how to deal with in-sewer fate of CECs and highlights future research needs. It was assessed to what extent empirical data is in-line with text-book knowledge and integrated sewer modelling approaches. Experimental half-lives (n = 277) of 96 organic CECs were collected from literature. The findings of this literature review can be used to support environmental modelling efforts and to optimize monitoring campaigns, including field studies in the context of wastewater-based epidemiology.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11157-022-09638-9.

Assessing population-level stress through glucocorticoid hormone monitoring in wastewater

Stress is oftentimes overlooked in societies, despite its life-threatening impact. Here, we assessed the feasibility of measuring endogenous stress hormones to estimate population-level stress by wastewater-based epidemiology (WBE). Two primary glucocorticoids, cortisol and cortisone, were monitored in wastewater by liquid chromatography tandem mass spectrometry (LC-MS/MS), to assess changes in these physiological markers of stress in a student population (n = 26,000 ± 7100) on a university campus in the southwestern U.S. Daily composite samples were collected for seven consecutive days each month during the Fall (Autumn) 2017 and Spring 2018 academic semesters (n = 134). Reproducible weekly patterns were seen in stress hormone excretion, with the highest levels occurring on Mondays (124 ± 44 μg d^-1 per person) and Tuesdays (127 ± 54 μg d^-1 per person) and the lowest on Sundays (87 ± 32 μg d^-1 per person). Stress levels on weekdays (defined by class schedules Monday-Thursday) were significantly higher than on weekends (p < 0.05). During both Fall and Spring semesters, per person stress levels of these hormones were significantly higher (p < 0.05) during the first two months of each semester, 162 ± 28 μg d^-1 per person (August), 104 ± 29 μg d^-1 per person (September), 180 ± 14 μg d^-1 per person (January), and 114 ± 54 μg d^-1 per person (February) than in the remaining measured weeks in the semester, including finals week captured in both semesters. Overall Spring semester stress levels (113 ± 45 μg d^-1 per person) were significantly higher than the Fall (94 ± 42 μg d^-1 per person), p < 0.01. This study is the first to demonstrate the utility of endogenous biomarkers, specifically glucocorticoid hormones, to monitor population health status (in this instance community stress) in near real-time by wastewater assessments.

Biomarkers selection for population normalization in SARS-CoV-2 wastewater-based epidemiology

Wastewater-based epidemiology (WBE) has been one of the most cost-effective approaches to track the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) levels in the communities since the coronavirus disease 2019 (COVID-19) outbreak in 2020. Normalizing SARS-CoV-2 concentrations by the population biomarkers in wastewater is critical for interpreting the viral loads, comparing the epidemiological trends among the sewersheds, and identifying the vulnerable communities. In this study, five population biomarkers, pepper mild mottle virus (PMMoV), creatinine (CRE), 5-hydroxyindoleacetic acid (5-HIAA), caffeine (CAF) and its metabolite paraxanthine (PARA) were investigated and validated for their utility in normalizing the SARS-CoV-2 loads through two normalizing approaches using the data from 64 wastewater treatment plants (WWTPs) in Missouri. Their utility in assessing the real-time population contributing to the wastewater was also evaluated. The best performing candidate was further tested for its capacity for improving correlation between normalized SARS-CoV-2 loads and the clinical cases reported in the City of Columbia, Missouri, a university town with a constantly fluctuating population. Our results showed that, except CRE, the direct and indirect normalization approaches using biomarkers allow accounting for the changes in wastewater dilution and differences in relative human waste input over time regardless flow volume and population of the given WWTP. Among selected biomarkers, PARA is the most reliable population biomarker in determining the SARS-CoV-2 load per capita due to its high accuracy, low variability, and high temporal consistency to reflect the change in population dynamics and dilution in wastewater. It also demonstrated its excellent utility for real-time assessment of the population contributing to the wastewater. In addition, the viral loads normalized by the PARA-estimated population significantly improved the correlation (rho=0.5878, p < 0.05) between SARS-CoV-2 load per capita and case numbers per capita. This chemical biomarker complements the current normalization scheme recommended by CDC and helps us understand the size, distribution, and dynamics of local populations for forecasting the prevalence of SARS-CoV2 within each sewershed.

Qualitative fingerprinting of psychoactive pharmaceuticals, illicit drugs, and related human metabolites in wastewater: A year-long study from Riga, Latvia

The COVID-19 pandemic has become an unprecedented public health emergency causing immense societal and socio-economic consequences. Multiple studies have outlined that interventions to curb the spread of the virus are likely to have an effect on substance use patterns. In this study, we explored the presence of psychoactive pharmaceuticals, illicit drugs and related human metabolites in 24-h composite wastewater samples that were collected weekly in 2021 from the central WWTP of Riga, Latvia. The analysis was performed via suspect screening approach using three separate high-resolution mass spectrometry (HRMS) workflows, which relied on reversed-phase liquid chromatography (RPLC), hydrophilic interaction liquid chromatography (HILIC) and direct infusion HRMS. In total, 39 out of 149 substances were detected throughout the sampling period. These include pharmaceuticals (mainly antiepileptics, antidepressants and antipsychotics), illicit drugs (e.g., MDMA, MDEA, cocaine, etc.) and new psychoactive substances (alpha-PVP). The results were evaluated in relation to COVID-19 incidence rate and the severity of containment and closure policies. For some compounds we observed temporal changes that may be potentially linked to the state of the pandemic. For instance, higher detection rates were observed for several illicit drugs during periods, when restrictions on public events were relaxed. Meanwhile, some psychoactive pharmaceuticals and drugs used to treat upper respiratory tract infections displayed increased prevalence in weeks when the national COVID-19 incidence rates were higher. However, without baseline reference data from previous years, it is difficult to discern how much of the relationships seen are linked to pandemic progression and seasonal variability.

Detection of SARS-CoV-2 RNA in wastewater and importance of population size assessment in smaller cities: An exploratory case study from two municipalities in Latvia

Wastewater-based epidemiology (WBE) has regained global importance during the COVID-19 pandemic. The mobility of people and other factors, such as precipitation and irregular inflow of industrial wastewater, are complicating the estimation of the disease prevalence through WBE, which is crucial for proper crisis management. These estimations are particularly challenging in urban areas with moderate or low numbers of inhabitants in situations where movement restrictions are not adopted (as in the case of Latvia) because residents of smaller municipalities tend to be more mobile and less strict in following the rules and measures of disease containment. Thus, population movement can influence the outcome of WBE measurements significantly and may not reflect the actual epidemiological situation in the respective area. Here, we demonstrate that by combining the data of detected SARS-CoV-2 RNA copy number, 5-hydroxyindoleacetic acid (5-HIAA) analyses in wastewater and mobile call detail records it was possible to provide an accurate assessment of the COVID-19 epidemiological situation in towns that are small (COVID-19 28-day cumulative incidence r = 0.609 and 35-day cumulative incidence r = 0.89, p < 0.05) and medium-sized towns (COVID-19 21-day cumulative incidence r = 0.997, 28-day cumulative incidence r = 0.98 and 35-day cumulative incidence r = 0.997, p < 0.05). This is the first study demonstrating WBE for monitoring COVID-19 outbreaks in Latvia. We demonstrate that the application of population size estimation measurements such as total 5-HIAA and call detail record data improve the accuracy of the WBE approach.

Comparison of high-frequency in-pipe SARS-CoV-2 wastewater-based surveillance to concurrent COVID-19 random clinical testing on a public U.S. university campus

Wastewater-based epidemiology (WBE) is utilized globally as a tool for quantifying the amount of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) within communities, yet the efficacy of community-level wastewater monitoring has yet to be directly compared to random Coronavirus Disease of 2019 (COVID-19) clinical testing; the best-supported method of virus surveillance within a single population. This study evaluated the relationship between SARS-CoV-2 RNA in raw wastewater and random COVID-19 clinical testing on a large university campus in the Southwestern United States during the Fall 2020 semester. Daily composites of wastewater (24-hour samples) were collected three times per week at two campus locations from 16 August 2020 to 1 January 2021 (n = 95) and analyzed by reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) targeting the SARS-CoV-2 E gene. Campus populations were estimated using campus resident information and anonymized, unique user Wi-Fi connections. Resultant trends of SARS-CoV-2 RNA levels in wastewater were consistent with local and nationwide pandemic trends showing peaks in infections at the start of the Fall semester in mid-August 2020 and mid-to-late December 2020. A strong positive correlation (r = 0.71 (p < 0.01); n = 15) was identified between random COVID-19 clinical testing and WBE surveillance methods, suggesting that wastewater surveillance has a predictive power similar to that of random clinical testing. Additionally, a comparative cost analysis between wastewater and clinical methods conducted here show that WBE was more cost effective, providing data at 1.7% of the total cost of clinical testing ($6042 versus $338,000, respectively). We conclude that wastewater monitoring of SARS-CoV-2 performed in tandem with random clinical testing can strengthen campus health surveillance, and its economic advantages are maximized when performed routinely as a primary surveillance method, with random clinical testing reserved for an active outbreak situation.

Opportunities and limits of wastewater-based epidemiology for tracking global health and attainment of UN sustainable development goals

Wastewater-based epidemiology (WBE) emerged as a powerful, actionable health management tool during the COVID-19 pandemic. Hypothesizing future uses, we explored its potential for real-time, tracking of progress in attaining United Nations Sustainable Development Goals (SDGs) globally as a non-expensive method using existing infrastructure. We inventoried (i) literature-documented sewerage infrastructure, (ii) demographics of populations served, and (iii) WBE markers informative of 9 SDGs. Among the 17 different sustainable development goals listed by the UN 2030 agenda, more than half of these may be monitored by using WBE monitoring at centralized treatment infrastructure as tabulated in this study. Driven mainly by COVID-19, WBE currently is practiced in at least 55 countries, reaching about 300 million people. Expansion of WBE to 109,000 + treatment plants inventoried in 129 countries would increase global coverage 9-fold to 34.7% or 2.7 billion, leaving out 5 billion people not served by centralized sewerage systems. Associations between population demographics and present-day infrastructure are explored, and geospatial regions particularly vulnerable to infectious disease outbreaks are identified. The results suggest that difference in the differential outcomes in well-being is an outcome of the sanitation infrastructure inequalities and lack of sanitation infrastructure creates doubly disadvantaged populations at risk of poor hygiene and cut off from the early-warning benefits of conventional WBE. This is the first study to explore the feasibility and potential barriers to the use of WBE for tracking the attainment of SDGs globally with at least 9 out of 17 SDGs.

Enhanced decay of coronaviruses in sewers with domestic wastewater

Recent outbreaks caused by coronaviruses and their supposed potential fecal-oral transmission highlight the need for understanding the survival of infectious coronavirus in domestic sewers. To date, the survivability and decay of coronaviruses were predominately studied using small volumes of wastewater (normally 5-30 mL) in vials (in-vial tests). However, real sewers are more complicated than bulk wastewater (wastewater matrix only), in particular the presence of sewer biofilms and different operational conditions. This study investigated the decay of infectious human coronavirus 229E (HCoV-229E) and feline infectious peritonitis virus (FIPV), two typical surrogate coronaviruses, in laboratory-scale reactors mimicking the gravity (GS, gravity-driven sewers) and rising main sewers (RM, pressurized sewers) with and without sewer biofilms. The in-sewer decay of both coronaviruses was greatly enhanced in comparison to those reported in bulk wastewater through in-vial tests. 99% of HCoV-229E and FIPV decayed within 2 h under either GS or RM conditions with biofilms, in contrast to 6-10 h without biofilms. There is limited difference in the decay of HCoV and FIPV in reactors operated as RM or GS, with the T90 and T99 difference of 7-10 min and 14-20 min, respectively. The decay of both coronaviruses in sewer biofilm reactors can be simulated by biphasic first-order kinetic models, with the first-order rate constant 2-4 times higher during the first phase than the second phase. The decay of infectious HCoV and FIPV was significantly faster in the reactors with sewer biofilms than in the reactors without biofilms, suggesting an enhanced decay of these surrogate viruses due to the presence of biofilms and related processes. The mechanism of biofilms in virus adsorption and potential inactivation remains unclear and requires future investigations. The results indicate that the survivability of infectious coronaviruses detected using bulk wastewater overestimated the infectivity risk of coronavirus during wastewater transportations in sewers or the downstream treatment.

Biomarkers Selection for Population Normalization in SARS-CoV-2 Wastewater-based Epidemiology

Wastewater-based epidemiology (WBE) has been one of the most cost-effective approaches to track the SARS-CoV-2 levels in the communities since the COVID-19 outbreak in 2020. Normalizing SARS-CoV-2 concentrations by the population biomarkers in wastewater can be critical for interpreting the viral loads, comparing the epidemiological trends among the sewersheds, and identifying the vulnerable communities. In this study, five population biomarkers, pepper mild mottle virus (pMMoV), creatinine (CRE), 5-hydroxyindoleacetic acid (5-HIAA), caffeine (CAF) and its metabolite paraxanthine (PARA) were investigated for their utility in normalizing the SARS-CoV-2 loads through developed direct and indirect approaches. Their utility in assessing the real-time population contributing to the wastewater was also evaluated. The best performed candidate was further tested for its capacity for improving correlation between normalized SARS-CoV-2 loads and the clinical cases reported in the City of Columbia, Missouri, a university town with a constantly fluctuated population. Our results showed that, except CRE, the direct and indirect normalization approaches using biomarkers allow accounting for the changes in wastewater dilution and differences in relative human waste input over time regardless flow volume and population at any given WWTP. Among selected biomarkers, PARA is the most reliable population biomarker in determining the SARS-CoV-2 load per capita due to its high accuracy, low variability, and high temporal consistency to reflect the change in population dynamics and dilution in wastewater. It also demonstrated its excellent utility for real-time assessment of the population contributing to the wastewater. In addition, the viral loads normalized by the PARA-estimated population significantly improved the correlation ( rho =0.5878, p <0.05) between SARS-CoV-2 load per capita and case numbers per capita. This chemical biomarker offers an excellent alternative to the currently CDC-recommended pMMoV genetic biomarker to help us understand the size, distribution, and dynamics of local populations for forecasting the prevalence of SARS-CoV2 within each sewershed.

HIGHLIGHT bullet points

The paraxanthine (PARA), the metabolite of the caffeine, is a more reliable population biomarker in SARS-CoV-2 wastewater-based epidemiology studies than the currently recommended pMMoV genetic marker.SARS-CoV-2 load per capita could be directly normalized using the regression functions derived from correlation between paraxanthine and population without flowrate and population data.Normalizing SARS-CoV-2 levels with the chemical marker PARA significantly improved the correlation between viral loads per capita and case numbers per capita.The chemical marker PARA demonstrated its excellent utility for real-time assessment of the population contributing to the wastewater.

Application of Wastewater-Based Epidemiology for Tracking Human Exposure to Deoxynivalenol and Enniatins

Wastewater-based epidemiology (WBE) is a promising biomonitoring approach with the potential to provide direct information on human intake and exposure to food contaminants and environmental chemicals. The aim of this study was to apply WBE while employing the normalization method for exploring human exposure to selected mycotoxins according to population biomarker 5-hydroxyindoleacetic acid (5-HIAA). This type of normalization technique has been previously used to detect various other compounds. However, to the best of our knowledge, this is the first study tracking human exposure to mycotoxins. A sensitive analytical methodology was developed to achieve reliable quantification of deoxynivalenol, enniatins, and beauvericin in wastewater (WW) samples. The applicability of the method was evaluated by testing 29 WW samples collected at WW treatment plants in Latvia. With frequency of detection greater than 86%, enniatins B, B1, A, and A1 were revealed in WW samples. The estimated total daily intake for enniatins was in the range of 1.8-27.6 µg/day per person. Free deoxynivalenol (DON) was determined in all analysed WW samples. Based on the average 5-HIAA excretion level and the determined 5-HIAA content in the samples, the intake of DON by the human population of Riga was estimated at 325 ng/kg b.w. day.

Two-dimensional liquid chromatography - mass spectrometry as an effective tool for assessing a wide range of pharmaceuticals and biomarkers in wastewater-based epidemiology studies

The biomarkers used in wastewater-based epidemiology studies have a wide range of physicochemical properties, making simultaneous analysis extremely challenging or even impossible. So far, the majority of analytical procedures employed in this field have focused on specific classes or a limited number of analytes. The heart-cutting two-dimensional liquid chromatography tandem mass spectrometry technique (2D-LC-MS/MS) has enabled the incorporation of compounds with significantly different polarities in a single analytical method. In this study, a 2D-LC-MS/MS method has been developed and optimized for the simultaneous analysis of various biomarkers in wastewater, providing relevant information about lifestyle habits (the usage of alcohol, tobacco, and caffeine), health and well-being (pharmaceuticals), and a population size biomarker (5-HIAA) that is useful for correct calculation of human population during wastewater-based epidemiology studies. A single-laboratory validation procedure showed satisfactory analytical performance, with the mean trueness for most compounds falling in the range of 80÷110 % and the mean repeatability being less than 20 %. The applicability of the method was evaluated by testing 28 wastewater samples collected at different wastewater treatment plants in Latvia. The obtained results revealed the occurrence of 44 out of 62 selected biomarkers, with the lowest quantified concentration at 1.1 ng L^-1 in the case of xylometazoline and up to 148 μg L^-1 in the case of metformin and 156 μg L^-1 for caffeine.

Application of catecholamine metabolites as endogenous population biomarkers for wastewater-based epidemiology

Wastewater-based epidemiology studies use catchment populations to normalise chemical marker mass loads in 24-h composite wastewater samples. However, one of the biggest uncertainties within the field is the accuracy of the population used. A population marker in wastewater may significantly reduce the uncertainty. This study evaluated the catecholamine metabolites - homovanillic acid (HVA) and vanillylmandelic acid (VMA) - as potential population biomarkers. Influent wastewater 24-h composite samples were collected from 38 wastewater catchments from around Australia (representing ~33% of Australia's population), extracted and analysed by liquid chromatography tandem mass spectrometry. Measured mass loads were compared to population sizes determined by mapping catchment maps against high-resolution census data. Both biomarkers correlated with coefficient of determinations (r²) of 0.908 and 0.922 for HVA and VMA, respectively. From the regression analysis, a slope (i.e. the daily per-capita excretion) of 1.241 and 1.067 mg.day^-1.person^-1 was obtained for HVA and VMA, respectively. The mass load ratio between VMA:HVA were very similar to that reported in literature for urinary analysis among all catchments. Overall, this study provided further evidence that catecholamine metabolites are suitable candidates as population biomarkers for future studies.

Wastewater-based epidemiology pilot study to examine drug use in the Western United States

The extent of prescription and illicit drug abuse in geographically isolated rural and micropolitan communities in the intermountain western United States (US) has not been well tracked. The goal of this pilot study was to accurately measure drug dose consumption rates (DCR) between two select populations, normalize the data and compare the DCRs to similar communities. To learn about patterns of drug abuse between the two disparate communities, we used the emergent field of wastewater-based epidemiology (WBE). A rapid, quantitative and systematic process for the determination of multiple classes of prescribed and illicit drugs was applied to influent wastewater samples. Influent samples were collected over the course of three months (April to June 2019) at two wastewater treatment plants representing a small urban and a rural community. Collection of sewage influent included 24-h composite samples and the use of polar organic chemical integrative samplers (POCIS), time-weighted samplers. Using the results from the composite sampling data, DCRs per 1000 population could be calculated from the concentration data and the use of excretion correction factors. The following 18 compounds: amphetamine, methamphetamine, MDA, MDMA, morphine, 6-acetylmorphine, methadone, EDDP, codeine, benzoylecgonine, hydrocodone, hydromorphone, oxycodone, noroxycodone, ketamine, fluoxetine, tramadol, and ritalinic acid; represent a subset of the targeted analytes that were consistently measured at detectable concentration levels, and present at both sites. Following normalization of the drug measurements to influent flow rates and per capita, the small urban community demonstrated greater collective excretion rates (CER) than the rural community, with the exceptions of amphetamine and methamphetamine.

High-throughput wastewater analysis for substance use assessment in central New York during the COVID-19 pandemic

Wastewater entering sewer networks represents a unique source of pooled epidemiological information. In this study, we coupled online solid-phase extraction with liquid chromatography-high resolution mass spectrometry to achieve high-throughput analysis of health and lifestyle-related substances in untreated municipal wastewater during the coronavirus disease 2019 (COVID-19) pandemic. Twenty-six substances were identified and quantified in influent samples collected from six wastewater treatment plants during the COVID-19 pandemic in central New York. Over a 12 week sampling period, the mean summed consumption rate of six major substance groups (i.e., antidepressants, antiepileptics, antihistamines, antihypertensives, synthetic opioids, and central nervous system stimulants) correlated with disparities in household income, marital status, and age of the contributing populations as well as the detection frequency of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater and the COVID-19 test positivity in the studied sewersheds. Nontarget screening revealed the covariation of piperine, a nontarget substance, with SARS-CoV-2 RNA in wastewater collected from one of the sewersheds. Overall, this proof-of-the-concept study demonstrated the utility of high-throughput wastewater analysis for assessing the population-level substance use patterns during a public health crisis such as COVID-19.

Simulated 2017 nationwide sampling at 13,940 major U.S. sewage treatment plants to assess seasonal population bias in wastewater-based epidemiology

Wastewater-based epidemiology (WBE) is an economical technique for monitoring and managing the health and behavior of human populations. Using 2017 nationwide data on geospatial population demographics as a test case, we simulated repeated sampling at all major U.S. wastewater treatment plants (WWTPs; n = 13,940) under constant biomarker loading conditions, to explore the potential sensitivity of WBE for generating skewed data. Simulation of repeated sewage sampling over all four seasons of 2017 yielded a number of expected, inter-dependent phenomena triggered by cooler wintertime temperatures compared to summertime results, including relatively (i) slower in-sewer biomarker decay, (ii) longer distal reach of WBE, (iii) larger effective sewershed monitoring areas, and (iv) an increase in the population represented. Additional important but not necessarily anticipated simulation outcomes included (v) distinct, non-random changes in demographic parameters of monitored subpopulations (e.g., by household income, educational attainment, military service, unemployment, and lack of health insurance), (vi) recurring observation of the latter demographic patterns across various geospatial scales and regions, and (vii) more evenly distributed results in the winter. In contrast, data obtainable by WBE in the summertime were dominated by households residing closest to the WWTP and subpopulations of relatively lesser wealth, educational achievement, healthcare access and employability. The analytical approach presented here should be readily applicable to other regions worldwide and may help to improve the design, robustness and interpretation of future WBE studies.

Modeling wastewater temperature and attenuation of sewage-borne biomarkers globally

Accurate modeling of in-sewer degradation of sewage-borne epidemiological biomarkers requires information on local wastewater temperature. We applied a deterministic, physical model to map theoretical wastewater temperature on a monthly scale worldwide and incorporated in the model estimated changes in the decay rate of 31 biomarkers of public health relevance frequently used in wastewater-based epidemiology (WBE). Over the course of a year, 75% of the world's global wastewater temperatures were estimated to fall into the temperature range of 6.9-34.4 °C. These non-fitted results obtained purely a priori were in good agreement with empirical observations (n = 400), as indicated by coefficients for Pearson (0.81; 0.76) and Spearman (0.86; 0.78) correlations for annual minima and maxima, respectively. Application of the Q₁₀ rule for biochemical reaction rates showed that, depending on wastewater temperature, half-lives of sewage-borne biomarkers will change significantly (range: 27%-7,010%) from the baseline at ambient conditions (21 ± 1 °C; 100%). Importantly, these temperature-related modulations of in-sewer biomarker decay changed the size of the area observable by WBE; in the extreme, changes in the distal reach observable by WBE were predicted to be as large as 49-fold over the course of a year at a given location. This first model of spatial and temporal variability in wastewater temperature has multiple suggested applications, including (i) utility for explaining literature-reported discrepancies in the detectability and levels of sewage-borne biomarkers, (ii) identification of optimal and sub-optimal wastewater-borne biomarkers depending on their varying half-lives over the course of the year at the sampling location of interest, and (iii) estimating the effective size of the sewershed capture zone in WBE studies.

Evaluating the stability of three oxidative stress biomarkers under sewer conditions and potential impact for use in wastewater-based epidemiology

Wastewater contains a wealth of information about the population who contribute to it including biological and chemical markers of human activity and exposures. F₂-isoprostanes have been proposed as oxidative stress biomarkers that can be measured in wastewater to provide a measure of oxidative stress at the population level. While an association between tobacco use and their level in wastewater has been demonstrated, an in-sewer stability assessment has not been conducted to support their use as oxidative stress biomarkers for wastewater-based epidemiology studies. In this study we investigated the stability of 8-iso-prostaglandin F_2α (PGF_2α), its metabolite dinor-11β-Prostaglandin F_2α (dnPGF_2α) and Prostaglandin E₂ (PGE₂) (representative of other classes of prostaglandins) in laboratory-scale sewer reactors simulating real sewers. PGF_2α, dnPGF_2α and PGE₂ were all found to be sufficiently stable under typical sewer conditions therefore satisfying the stability requirement of wastewater-based epidemiology population health biomarkers.