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Wastewater-based epidemiology (WBE) is a new methodology for estimating the drug load in a population. Simple summary statistics and specification tests have typically been used to analyze WBE data, comparing differences between weekday and weekend loads. Such standard statistical methods may, however, overlook important nuanced information in the data. In this study, we apply functional data analysis (FDA) to WBE data and compare the results to those obtained from more traditional summary measures. We analysed temporal WBE data from 42 European cities, using sewage samples collected daily for one week in March 2013. For each city, the main temporal features of two selected drugs were extracted using functional principal component (FPC) analysis, along with simpler measures such as the area under the curve (AUC). The individual cities' scores on each of the temporal FPCs were then used as outcome variables in multiple linear regression analysis with various city and country characteristics as predictors. The results were compared to those of functional analysis of variance (FANOVA). The three first FPCs explained more than 99% of the temporal variation. The first component (FPC1) represented the level of the drug load, while the second and third temporal components represented the level and the timing of a weekend peak. AUC was highly correlated with FPC1, but other temporal characteristic were not captured by the simple summary measures. FANOVA was less flexible than the FPCA-based regression, and even showed concordance results. Geographical location was the main predictor for the general level of the drug load. FDA of WBE data extracts more detailed information about drug load patterns during the week which are not identified by more traditional statistical methods. Results also suggest that regression based on FPC results is a valuable addition to FANOVA for estimating associations between temporal patterns and covariate information.

Marine debris is a global environmental issue. Smoked cigarette filters are the predominant coastal litter item; 4.5 trillion are littered annually, presenting a source of bioplastic microfibres (cellulose acetate) and harmful toxicants to marine environments. Despite the human health risks associated with smoking, little is known of the hazards cigarette filters present to marine life. Here we studied the impacts of smoked cigarette filter toxicants and microfibres on the polychaete worm Hediste diversicolor (ragworm), a widespread inhabitant of coastal sediments. Ragworms exposed to smoked cigarette filter toxicants in seawater at concentrations 60 fold lower than those reported for urban run-off exhibited significantly longer burrowing times, >30% weight loss and >2-fold increase in DNA damage compared to ragworms maintained in control conditions. In contrast, ragworms exposed to smoked cigarette filter microfibres in marine sediment showed no significant effects. Bioconcentration factors for nicotine were 500 fold higher from seawater than from sediment. Our results illustrate the vulnerability of organisms in the water column to smoking debris and associated toxicants and highlight the risks posed by smoked cigarette filter debris to aquatic life.

Monitoring water quality is critical for mitigating risks to human health and the environment. It is also essential for ensuring high quality water-based and water-dependent products and services. The monitoring and detection of chemical contamination are often based around a small set of parameters or substances. Conventional monitoring often involves the collection of water samples in the field and subsequent analyses in the laboratory. Such strategies are expensive, time consuming, and focused on a narrow set of potential risks. They also induce a significant time delay between a contamination event and a possible reactive measure. Here, we developed a real-time monitoring system based on Artificial Intelligence (AI) for field deployable sensors. We used data obtained from full-scan UV-spec and fluorescence sensors for validation in this study. This multi-sensor system consists of (a) anomaly detection that uses multivariate statistical methods to detect any anomalous state in an aqueous environment and (b) anomaly identification, using Machine Learning (ML) to classify the anomaly into one of the a priori known categories. For a proof of concept, we tested this methodology on a supply of municipal drinking water and a few representative organic chemical contaminants applied in a laboratory-controlled environment. The outcomes confirm the ability for the multi-sensor system to detect and identify changes in water quality due to incidences of chemical contamination. The method may be applied to numerous other areas where water quality should be measured online and in real time, such as in surface-water, urban runoff, or food and industrial process water.

Wastewater analysis has been demonstrated to be a complementary approach for assessing the overall patterns of drug use by a population while the full potential of wastewater-based epidemiology has yet to be explored. F -isoprostanes are a prototype wastewater biomarker to study the cumulative oxidative stress at a community level. In this work, 8-iso-prostaglandin F (8-iso-PGF ) was analysed in raw 24 h-composite wastewater samples collected from 4 Norwegian and 7 other European cities in 2014 and 2015. Using the same samples, biomarkers of alcohol (ethyl sulfate) and tobacco (trans-3'-hydroxycotinine) use were also analysed to investigate any possible correlation between 8-iso-PGF and the consumption of the two drugs. The estimated per capita daily loads of 8-iso-PGF in the 11 cities ranged between 2.5 and 9.9 mg/day/1000 inhabitants with a population-weighted mean of 4.8 mg/day/1000 inhabitants. There were no temporal trends observed in the levels of 8-iso-PGF , however, spatial differences were found at the inter-city level correlating to the degree of urbanisation. The 8-iso-PGF mass load was found to be strongly associated with that of trans-3'-hydroxycotinine while it showed no correlation with ethyl sulfate. The present study shows the potential for 8-iso-PGF as a wastewater biomarker for the assessment of community public health.

•Before the year 2000, there was almost no methamphetamine on the Norwegian market.•There was a steady increase in use of methamphetamine till 2010.•This is confirmed in 5 different sets of data from police, prisons, customs and wastewater. There is a concern about methamphetamine use in Europe. Methamphetamine fatalities have recently occurred in Southern European countries. The aim of this study is to examine Norwegian methamphetamine trends in recent years, comparing different data sources. Data about amphetamines were collected from five different sources; blood samples from drivers suspected of driving under the influence of drugs and apprehended by the police (during the years 2000–2012), urine samples from inmates in Norwegian prisons (during 2000–2012), post-mortem blood samples from medico-legal autopsies (2000–2012), drug seizures (1994–2012) and wastewater samples from a metropolitan/suburban population (2010–2012). The number of cases where methamphetamine was detected has increased during the period studied for the driving under the influence cases, the samples from inmates and from forensic autopsies. The increase seems to be linear up to 2009–2010, with a subsequent stabilisation or even a decline in the market share of methamphetamine for the next few years. The number of methamphetamine seizures has risen from less than 1% in 2000 to approximately 66% in 2009, and a steady share around 60% have been seen between 2010 and 2012. Wastewater samples showed that the share of methamphetamine peaked in 2010–11, before falling. It is difficult to obtain reliable data on illicit drugs. Data from different populations might give indications of changes and trends, but are always prone to different biases. By comparing results from different data sources, a better knowledge of the illicit drug market might be obtained. All our data sources confirmed that methamphetamine became a more prevalent drug during the first decade of the new millennium in Norway, but since approximately 2009 the share of methamphetamine stabilised.

Objectives A range of approaches are now available to estimate the level of drug use in the community so it is desirable to critically compare results from the differing techniques. This paper presents a comparison of the results from three methods for estimating the level of cocaine use in the general population. Design The comparison applies to; a set of regional-scale sample survey questionnaires, a representative sample survey on drug use among drivers and an analysis of the quantity of cocaine-related metabolites in sewage. Setting 14 438 participants provided data for the set of regional-scale sample survey questionnaires; 2341 drivers provided oral-fluid samples and untreated sewage from 570 000 people was analysed for biomarkers of cocaine use. All data were collected in Oslo, Norway. Results 0.70 (0.36–1.03) % of drivers tested positive for cocaine use which suggest a prevalence that is higher than the 0.22 (0.13–0.30) % (per day) figure derived from regional-scale survey questionnaires, but the degree to which cocaine consumption in the driver population follows the general population is an unanswered question. Despite the comparatively low-prevalence figure the survey questionnaires did provide estimates of the volume of consumption that are comparable with the amount of cocaine-related metabolites in sewage. Per-user consumption estimates are however highlighted as a significant source of uncertainty as little or no data on the quantities consumed by individuals are available, and much of the existing data are contradictory. Conclusions The comparison carried out in the present study can provide an excellent means of checking the quality and accuracy of the three measurement techniques because they each approach the problem from a different viewpoint. Together the three complimentary techniques provide a well-balanced assessment of the drug-use situation in a given community and identify areas where more research is needed.

Wastewater analysis has been demonstrated to be a complementary approach for assessing the overall patterns of drug use by a population while the full potential of wastewater-based epidemiology has yet to be explored. F 2 -isoprostanes are a prototype wastewater biomarker to study the cumulative oxidative stress at a community level. In this work, 8-iso-prostaglandin F 2α (8-iso-PGF 2α ) was analysed in raw 24 h-composite wastewater samples collected from 4 Norwegian and 7 other European cities in 2014 and 2015. Using the same samples, biomarkers of alcohol (ethyl sulfate) and tobacco (trans-3′-hydroxycotinine) use were also analysed to investigate any possible correlation between 8-iso-PGF 2α and the consumption of the two drugs. The estimated per capita daily loads of 8-iso-PGF 2α in the 11 cities ranged between 2.5 and 9.9 mg/day/1000 inhabitants with a population-weighted mean of 4.8 mg/day/1000 inhabitants. There were no temporal trends observed in the levels of 8-iso-PGF 2α , however, spatial differences were found at the inter-city level correlating to the degree of urbanisation. The 8-iso-PGF 2α mass load was found to be strongly associated with that of trans-3′-hydroxycotinine while it showed no correlation with ethyl sulfate. The present study shows the potential for 8-iso-PGF 2α as a wastewater biomarker for the assessment of community public health.

If asked whether you had consumed illicit drugs recently, would you admit it? If yes, could you precisely recall types of drug, times and amounts used? If you were the person commissioned with the task of quantifying drug use, what approach would you use given the social stigma attached with such behavior? We measure drug residues in sewage, which represents urine of entire populations, to provide an objective estimate of total drug use in a region. In transdisciplinary projects, sewage-based results provide valuable information at unrivaled spatiotemporal resolution complementing traditional data.

Wastewater-based epidemiology (WBE) is a new methodology for estimating the drug load in a population. Simple summary statistics and specification tests have typically been used to analyze WBE data, comparing differences between weekday and weekend loads. Such standard statistical methods may, however, overlook important nuanced information in the data. In this study, we apply functional data analysis (FDA) to WBE data and compare the results to those obtained from more traditional summary measures. We analysed temporal WBE data from 42 European cities, using sewage samples collected daily for one week in March 2013. For each city, the main temporal features of two selected drugs were extracted using functional principal component (FPC) analysis, along with simpler measures such as the area under the curve (AUC). The individual cities' scores on each of the temporal FPCs were then used as outcome variables in multiple linear regression analysis with various city and country characteristics as predictors. The results were compared to those of functional analysis of variance (FANOVA). The three first FPCs explained more than 99% of the temporal variation. The first component (FPC1) represented the level of the drug load, while the second and third temporal components represented the level and the timing of a weekend peak. AUC was highly correlated with FPC1, but other temporal characteristic were not captured by the simple summary measures. FANOVA was less flexible than the FPCA-based regression, and even showed concordance results. Geographical location was the main predictor for the general level of the drug load. FDA of WBE data extracts more detailed information about drug load patterns during the week which are not identified by more traditional statistical methods. Results also suggest that regression based on FPC results is a valuable addition to FANOVA for estimating associations between temporal patterns and covariate information.

Wastewater-based epidemiology (WBE) is a new methodology for estimating the drug load in a population. Simple summary statistics and specification tests have typically been used to analyze WBE data, comparing differences between weekday and weekend loads. Such standard statistical methods may, however, overlook important nuanced information in the data. In this study, we apply functional data analysis (FDA) to WBE data and compare the results to those obtained from more traditional summary measures. We analysed temporal WBE data from 42 European cities, using sewage samples collected daily for one week in March 2013. For each city, the main temporal features of two selected drugs were extracted using functional principal component (FPC) analysis, along with simpler measures such as the area under the curve (AUC). The individual cities' scores on each of the temporal FPCs were then used as outcome variables in multiple linear regression analysis with various city and country characteristics as predictors. The results were compared to those of functional analysis of variance (FANOVA). The three first FPCs explained more than 99% of the temporal variation. The first component (FPC1) represented the level of the drug load, while the second and third temporal components represented the level and the timing of a weekend peak. AUC was highly correlated with FPC1, but other temporal characteristic were not captured by the simple summary measures. FANOVA was less flexible than the FPCA-based regression, and even showed concordance results. Geographical location was the main predictor for the general level of the drug load. FDA of WBE data extracts more detailed information about drug load patterns during the week which are not identified by more traditional statistical methods. Results also suggest that regression based on FPC results is a valuable addition to FANOVA for estimating associations between temporal patterns and covariate information.