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

To which extent illicit drugs are transformed during in-sewer transport, depends on a number of factors: i) substance-specific transformation rates, ii) environmental conditions, iii) point of discharge (location of drug user) and iv) sewer network properties, primarily hydraulic residence time (HRT) and the ratio of biofilm contact area to wastewater volume (A/V_eq).
Assessing associated uncertainties typically requires numerous simulations. Therefore, we propose a new two-step modeling framework: 1) Quantify hydrodynamic conditions. This computationally demanding step was performed once in SWMM to derive HRT and A/V_eq for each potential point of discharge (node) in three catchments of different size. 2) Estimate biomarker loss. In this step, Monte Carlo simulations were performed for defined scenarios. Depending on assumptions about drug user distribution and prevalence, a number of nodes was sampled. For each node an empirical first-order transformation model was applied with flow-path-corresponding HRT and A/V_eq from step 1. Biotic and abiotic transformation rates were sampled from distributions combining variability of different biofilms.
In our modeling study, median losses were >30% for amphetamine, 6-monoacetylmorphine and 6-acetylcodeine in all three catchments with high uncertainty (5%–100% loss), which would imply a systematic underestimation of consumption when neglecting in-sewer processes. Median losses for 21 other investigated biomarkers were <10% with different uncertainty ranges – “no substantial transformation” was confirmed for nine substances in a real sewer segment with a 2-h residence time. Transferability of these results must be tested for other catchments. To further reduce uncertainty, mainly additional knowledge on transformation rates, particularly in biofilm, and their distribution across a sewer network is needed to update model input objectively. Our approach allows efficient testing and, furthermore, can be expanded for many other human biomarkers. Accounting for biomarker stability during in-sewer transport will avoid biased estimates and further improve wastewater-based epidemiology.

A key uncertainty of wastewater-based epidemiology is the size of the population which contributed to a given wastewater sample. We previously developed and validated a Bayesian inference model to estimate population size based on 14 population markers which: (1) are easily measured and (2) have mass loads which correlate with population size. However, the potential uncertainty of the model prediction due to in-sewer degradation of these markers was not evaluated. In this study, we addressed this gap by testing their stability under sewer conditions and assessed whether degradation impacts the model estimates. Five markers, which formed the core of our model, were stable in the sewers while the others were not. Our evaluation showed that the presence of unstable population markers in the model did not decrease the precision of the population estimates providing that stable markers such as acesulfame remained in the model. However, to achieve the minimum uncertainty in population estimates, we propose that the core markers to be included in population models for other sites should meet two additional criteria: (3) negligible degradation in wastewater to ensure the stability of chemicals during collection; and (4) < 10% in-sewer degradation could occur during the mean residence time of the sewer network.

The economic crisis plaguing Greece was expected to impact consumption of pharmaceuticals and illicit drugs – a priori to an unknown extent. We quantified the change of use for various classes of licit and illicit drugs by monitoring Athens’ wastewater from 2010 to 2014. A high increase in the use of psychoactive drugs was detected between 2010 and 2014, especially for antipsychotics (35-fold), benzodiazepines (19-fold), and antidepressants (11-fold). This directly reflects the perceived increase of incidences associated with mental illnesses in the population, as a consequence of severe socioeconomic changes. Other therapeutic classes, like antiepileptics, hypertensives, and gastric and ulcer drugs also showed an increase in use (from 2-fold increase for antiepileptics to 13-fold for hypertensives). In contrast, the overall use of antibiotics and NSAIDs decreased. For mefenamic acid, an almost 28-fold decrease was observed. This finding is likely related to the reduction in drug expenditure applied in public health. A 2-fold increase of methamphetamine use was detected, associated with a cheap street drug called ″sisa″ (related to marginal conducts), which is a health concern. MDMA (5-fold) and methadone (7-fold) use showed also an increase, while cocaine and cannabis estimates did not show a clear trend.

Wet-weather discharges contribute to anthropogenic micropollutant loads entering the aquatic environment. Thousands of wet-weather discharges exist in Swiss sewer systems, and we do not have the capacity to monitor them all. We consequently propose a model-based approach designed to identify critical discharge points in order to support effective monitoring.
We applied a dynamic substance flow model to four substances representing different entry routes: indoor (Triclosan, Mecoprop, Copper) as well as rainfall-mobilized (Glyphosate, Mecoprop, Copper) inputs. The accumulation on different urban land-use surfaces in dry weather and subsequent substance-specific wash-off is taken into account. For evaluation, we use a conservative screening approach to detect critical discharge points. This approach considers only local dilution generated onsite from natural, unpolluted areas, i.e. excluding upstream dilution.
Despite our conservative assumptions, we find that the environmental quality standards for Glyphosate and Mecoprop are not exceeded during any 10-min time interval over a representative one-year simulation period for all 2500 Swiss municipalities. In contrast, the environmental quality standard is exceeded during at least 20% of the discharge time at 83% of all modelled discharge points for Copper and at 71% for Triclosan. For Copper, this corresponds to a total median duration of approximately 19 days per year. For Triclosan, discharged only via combined sewer overflows, this means a median duration of approximately 10 days per year. In general, stormwater outlets contribute more to the calculated effect than combined sewer overflows for rainfall-mobilized substances. We further evaluate the Urban Index (A_{urban,impervious}/A_natural) as a proxy for critical discharge points: catchments where Triclosan and Copper exceed the corresponding environmental quality standard often have an Urban Index >0.03.
A dynamic substance flow analysis allows us to identify the most critical discharge points to be prioritized for more detailed analyses and monitoring. This forms a basis for the efficient mitigation of pollution.

Wastewater-based epidemiology (WBE) applies advanced analytical methods to quantify drug residues in wastewater with the aim to estimate illicit drug use at the population level. Transformation processes during transport in sewers (chemical and biological reactors) and storage of wastewater samples before analysis are expected to change concentrations of different drugs to varying degrees. Ignoring transformation for drugs with low to medium stability will lead to an unknown degree of systematic under- or overestimation of drug use, which should be avoided. This review aims to summarize the current knowledge related to the stability of commonly investigated drugs and, furthermore, suggest a more effective approach to future experiments. From over 100 WBE studies, around 50 mentioned the importance of stability and 24 included tests in wastewater. Most focused on in-sample stability (i.e., sample preparation, preservation and storage) and some extrapolated to in-sewer stability (i.e., during transport in real sewers). While consistent results were reported for rather stable compounds (e.g., MDMA and methamphetamine), a varying range of stability under different or similar conditions was observed for other compounds (e.g., cocaine, amphetamine and morphine). Wastewater composition can vary considerably over time, and different conditions prevail in different sewer systems. In summary, this indicates that more systematic studies are needed to: i) cover the range of possible conditions in sewers and ii) compare results more objectively. To facilitate the latter, we propose a set of parameters that should be reported for in-sewer stability experiments. Finally, a best practice of sample collection, preservation, and preparation before analysis is suggested in order to minimize transformation during these steps.

Wastewater-based epidemiology is increasingly being used as a tool to monitor drug use trends. To minimize costs, studies have typically monitored a small number of days. However, cycles of drug use may display weekly and seasonal trends that affect the accuracy of monthly or annual drug use estimates based on a limited number of samples. This study aimed to rationalize sampling methods for minimizing the number of samples required while maximizing information about temporal trends. A range of sampling strategies were examined: (i) targeted days (e.g., weekends), (ii) completely random or stratified random sampling, and (iii) a number of sampling strategies informed by known weekly cycles in drug use data. Using a time-series approach, analysis was performed for four drugs (MDMA, methamphetamine, cocaine, methadone) collected through a continuous sampling program over 14 months. Results showed, for drugs with weekly cycles (MDMA, methamphetamine and cocaine in this sample), sampling strategies which made use of those weekly cycles required fewer samples to obtain similar information as sampling 5 days per week and had better accuracy than stratified random sampling techniques.

Background: Wastewater analysis is an innovative approach that allows monitoring illicit drug use at the community level. This study focused on investigating geographical differences in drug consumption by comparing epidemiological, crime and wastewater data.
Methods: Wastewater samples were collected in 19 cities across Germany and Switzerland during one week, covering a population of approximately 8.1 million people. Self-report data and consumption offences for the investigated areas were used for comparison and to investigate differences between the indicators.
Results: Good agreement between data sources was observed for cannabis and amphetamine-type stimulants, whereas substantial discrepancies were observed for cocaine. In Germany, an important distinction could be made between Berlin, Dortmund and Munich, where cocaine and particularly amphetamine were more prevalent, and Dresden, where methamphetamine consumption was clearly predominant. Cocaine consumption was relatively homogenous in the larger urban areas of Switzerland, although prevalence and offences data suggested a more heterogeneous picture. Conversely, marked regional differences in amphetamine and methamphetamine consumption could be highlighted.
Conclusions: Combining the available data allowed for a better understanding of the geographical differences regarding prevalence, typology and amounts of substances consumed. For cannabis and amphetamine-type stimulants, the complementarity of survey, police and wastewater data could be highlighted, although notable differences could be identified when considering more stigmatised drugs (i.e. cocaine and heroin). Understanding illicit drug consumption at the national scale remains a difficult task, yet this research illustrates the added value of combining complementary data sources to obtain a more comprehensive and accurate picture of the situation.

Population size is crucial when estimating population-normalized drug consumption (PNDC) from wastewater-based drug epidemiology (WBDE). Three conceptually different population estimates can be used: de jure (common census, residence), de facto (all persons within a sewer catchment), and chemical loads (contributors to the sampled wastewater). De facto and chemical loads will be the same where all households contribute to a central sewer system without wastewater loss. This study explored the feasibility of determining a de facto population and its effect on estimating PNDC in an urban community over an extended period. Drugs and other chemicals were analyzed in 311 daily composite wastewater samples. The daily estimated de facto population (using chemical loads) was on average 32% higher than the de jure population. Consequently, using the latter would systemically overestimate PNDC by 22%. However, the relative day-to-day pattern of drug consumption was similar regardless of the type of normalization as daily illicit drug loads appeared to vary substantially more than the population. Using chemical loads population, we objectively quantified the total methodological uncertainty of PNDC and reduced it by a factor of 2. Our study illustrated the potential benefits of using chemical loads population for obtaining more robust PNDC data in WBDE.

Contamination of freshwater with micropollutants (MPs) is a growing concern worldwide. Even at very low concentrations, MPs can have adverse effects on aquatic ecosystems and possibly also on human health. Switzerland is one of the first countries to start implementing a national policy to reduce MPs in the effluents of municipal sewage treatment plants (STPs). This paper estimates the benefits of upgrading STPs based on public’s stated preferences. To assess public demand for the reduction of the environmental and health risks of MPs, we conducted a choice experiment in a national online survey. The results indicate that the average willingness to pay per household is CHF 100 (US$ 73) annually for reducing the potential environmental risk of MPs to a low level. These benefits, aggregated over households in the catchment of the STPs to be upgraded, generate a total annual economic value of CHF 155 million (US$ 113 million). This compares with estimated annual costs for upgrading 123 STPs of CHF 133 million (US$ 97 million) or CHF 86 (US$ 63) per household connected to these STPs. Hence, a cost-benefit analysis justifies the investment decision from an economic point of view and supports the implementation of the national policy in the ongoing political discussion.

An important uncertainty when estimating per capita consumption of, for example, illicit drugs by means of wastewater analysis (sometimes referred to as "sewage epidemiology") relates to the size and variability of the de facto population in the catchment of interest. In the absence of a day-specific direct population count any indirect surrogate model to estimate population size lacks a standard to assess associated uncertainties. Therefore, the objective of this study was to collect wastewater samples at a unique opportunity, that is, on a census day, as a basis for a model to estimate the number of people contributing to a given wastewater sample. Mass loads for a wide range of pharmaceuticals and personal care products were quantified in influents of ten sewage treatment plants (STP) serving populations ranging from approximately 3500 to 500 000 people. Separate linear models for population size were estimated with the mass loads of the different chemical as the explanatory variable: 14 chemicals showed good, linear relationships, with highest correlations for acesulfame and gabapentin. De facto population was then estimated through Bayesian inference, by updating the population size provided by STP staff (prior knowledge) with measured chemical mass loads. Cross validation showed that large populations can be estimated fairly accurately with a few chemical mass loads quantified from 24-h composite samples. In contrast, the prior knowledge for small population sizes cannot be improved substantially despite the information of multiple chemical mass loads. In the future, observations other than chemical mass loads may improve this deficit, since Bayesian inference allows including any kind of information relating to population size.

Aims. Quantifying illicit drug loads through wastewater analysis (WWA) is an alternative approach to estimating population drug use. This study investigated the variability of daily drug loads in wastewater and their relationships to environmental factors over an extended period to: (i) explore the suitability of WWA in small populations and (ii) optimize the monitoring design for future studies.
Design, Setting, Participants. Daily wastewater samples (n = 1369 consecutive days) from a German village with approximately 7160 inhabitants.
Measurements. Samples were analysed for cocaine and benzoylecgonine with liquid chromatography-tandem mass spectrometry. Time-series analysis was used to explore the effects of weather and other factors on daily cocaine loads. Subsampling was used to assess monitoring design.
Findings. Cocaine loads [mean = 652 mg_COC/day, standard deviation (SD) = 498 mg_COC/day] increased over the study period, with higher values during winter and spring. Despite high day-to-day variation, loads were significantly higher during weekends [+161 mg_COC/day, 95% confidence interval (CI) = 115–207 mg_COC/day, P < 10⁻⁴] and days with frost (+114 mg_COC/day, 95% CI = 6–223 mg_COC/day, P = 0.039) or snow (+150 mg_COC/day, 95% CI = 46–253 mg_COC/day, P = 0.005). Annual means estimated from 1-week periods were subject to approximately 60% relative error. Increasing sample size and changing sampling from consecutive days to stratified random decreased this uncertainty.
Conclusions. Day-to-day variation and seasonality of drug loads from the few long-term wastewater studies available to date suggest that up to 56 stratified random samples are required to obtain reliable (expected uncertainty around 10%) annual estimates of drug loads. Successfully assessing changes in consumption patterns or relationships to external factors requires larger sample sizes than estimating annual means, which holds true for high-prevalence drugs in small communities and low-prevalence drugs in big cities.

Aims. To perform wastewater analyses to assess spatial differences and temporal changes of illicit drug use in a large European population.
Design. Analyses of raw wastewater over a 1-week period in 2012 and 2013.
Setting and Participants. Catchment areas of wastewater treatment plants (WWTPs) across Europe, as follows: 2012: 25 WWTPs in 11 countries (23 cities, total population 11.50 million); 2013: 47 WWTPs in 21 countries (42 cities, total population 24.74 million).
Measurements. Excretion products of five illicit drugs (cocaine, amphetamine, ecstasy, methamphetamine, cannabis) were quantified in wastewater samples using methods based on liquid chromatography coupled to mass spectrometry.
Findings. Spatial differences were assessed and confirmed to vary greatly across European metropolitan areas. In general, results were in agreement with traditional surveillance data, where available. While temporal changes were substantial in individual cities and years (P ranging from insignificant to <10⁻³), overall means were relatively stable. The overall mean of methamphetamine was an exception (apparent decline in 2012), as it was influenced mainly by four cities.
Conclusions. Wastewater analysis performed across Europe provides complementary evidence on illicit drug consumption and generally concurs with traditional surveillance data. Wastewater analysis can measure total illicit drug use more quickly and regularly than is the current norm for national surveys, and creates estimates where such data does not exist.

Discharge of silver nanoparticles (Ag-NP) from textiles and cosmetics, todays major application areas for metallic Ag-NP, into wastewater is inevitable. Transformation and removal processes in sewers and wastewater treatment plants (WWTP) will determine the impact of Ag-NP on aquatic and terrestrial environments, via the effluents of the WWTP and via the use of digested sludge as fertilizer. We thus conducted experiments addressing the behavior of Ag-NP in sewers and in WWTP.
We spiked Ag-NP to a 5 km long main trunk sewer and collected 40 wastewater samples after 500 m, 2400 m and 5000 m each according to the expected travel times of the Ag-NP. Excellent mass closure of the Ag derived by multiplying the measured Ag concentrations times the volumetric flow rates indicate an efficient transport of the Ag-NP without substantial losses to the sewer biofilm. Ag-NP reacted with raw wastewater in batch experiments were sulfidized to roughly 15% after 5 h reaction time as revealed by X-ray absorption spectroscopy (XAS). However, acid volatile sulfide (AVS) concentrations were substantially higher in the sewer channel (100 μM) compared to the batch experiments (3 μM; still sufficient to sulfidize spiked 2 μM Ag) possibly resulting in a higher degree of sulfidation in the sewer channel. We further investigated the removal efficiency of 10 nm and 100 nm Ag- and gold (Au)-NP coated with citrate or polyvinylpyrrolidone in activated sludge batch experiments. We obtained very high removal efficiencies (∼99%) irrespective of size and coating for Ag- and Au-NP, the latter confirming that the particle type was of minor importance with respect to the degree of NP removal. We observed a strong size dependence of the sulfidation kinetics. We conclude that Ag-NP discharged to the wastewater stream will become sulfidized to various degrees in the sewer system and are efficiently transported to the WWTP. The sulfidation of the Ag-NP will continue in the WWTP, but primarily depending on the size the Ag-NP, may not be complete. Very high removal efficiencies in the WWTP will divert most of the Ag-NP mass flow to the digester and only a small fraction of the Ag will be released to surface waters.