Considerations for assessing stability of wastewater-based epidemiology biomarkers using biofilm-free and sewer reactor tests.

Wastewater-based epidemiology is an increasingly popular method for analysing drugs or metabolites excreted by populations. The in-sewer transformation of biomarkers is important but often receives little consideration in published studies. Many studies publish stability under biofilm-free conditions only, which do not represent actual sewer conditions. This study aims to fill a gap in the field by comparing the wastewater stability of 33 licit drug and pharmaceutical biomarkers in biofilm-free (BFF) conditions to stability in sewer biofilm reactors. All but one biomarker was stable under BFF conditions, whereas most transformed in sewer biofilm reactors. Sewer reactor results tended to overestimate the degradation in pilot and actual sewers, whereas BFF stability had no clear relationship to stability in pilot and actual sewers. Our results provide additional basis for more informed interpretation of biofilm-free and sewer reactor stability results for past and future WBE studies.

Wastewater-Based Epidemiology of Stimulant Drugs: Functional Data Analysis Compared to Traditional Statistical Methods.

BACKGROUND: 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. METHODS: 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). RESULTS: 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. CONCLUSION: 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.

Characterization of the effluent from a nanosilver producing washing machine.

The increasing number of nanomaterial based consumer products raises concerns about their possible impact on the environment. This study provides an assessment of the effluent from a commercially available silver nanowashing machine. The washing machine released silver in its effluent at an average concentration of 11µgL(-1), as determined by inductive coupled mass spectrometry (ICP-MS). The presence of silver nanoparticles (AgNPs) was confirmed by single particle ICP-MS as well as ion selective electrode measurements and filtration techniques. Size measurements showed particles to be in the defined nanosize range, with an average size of 10nm measured with transmission electron microscopy (TEM) and 60-100nm determined with nanoparticle tracking analysis (NTA). The effluent was shown to have negative effects on a natural bacterial community as its abundance was clearly reduced when exposed to the nanowash water. If washing machines capable of producing AgNPs become a common feature of households in the future, wastewater will contain significant loadings of AgNPs which might be released into the environment.