In biofilm systems for wastewater treatment (e.g., moving bed biofilms reactors-MBBRs) biofilm thickness is typically not under direct control. Nevertheless, biofilm thickness is likely to have a profound effect on the microbial diversity and activity, as a result of diffusion limitation and thus substrate penetration in the biofilm. In this study, we investigated the impact of biofilm thickness on nitrification and on the removal of more than 20 organic micropollutants in laboratory-scale nitrifying MBBRs. We used novel carriers (Z-carriers, AnoxKaldnes) that allowed controlling biofilm thickness at 50, 200, 300, 400, and 500 μm. The impact of biofilm thickness on microbial community was assessed via 16S rRNA gene amplicon sequencing and ammonia monooxygenase (amoA) abundance quantification through quantitative PCR (qPCR). Results from batch experiments and microbial analysis showed that (i) the thickest biofilm (500 μm) presented the highest specific biotransformation rate constants (kbio, L g(-1) d(-1)) for 14 out of 22 micropollutants; (ii) biofilm thickness positively associated with biodiversity, which was suggested as the main factor for the observed enhancement of kbio; (iii) the thinnest biofilm (50 μm) exhibited the highest nitrification rate (gN d(-1) g(-1)), amoA gene abundance and kbio values for some of the most recalcitrant micropollutants (i.e., diclofenac and targeted sulfonamides). Although thin biofilms favored nitrification activity and the removal of some micropollutants, treatment systems based on thicker biofilms should be considered to enhance the elimination of a broad spectrum of micropollutants.

Sewer pipelines, although primarily designed for sewage transport, can also be considered as bioreactors. In-sewer processes may lead to significant variations of chemical loadings from source release points to the treatment plant influent. In this study, we assessed in-sewer utilization of growth substrates (primary metabolic processes) and transformation of illicit drug biomarkers (secondary metabolic processes) by suspended biomass. Sixteen drug biomarkers were targeted, including mephedrone, methadone, cocaine, heroin, codeine, and tetrahydrocannabinol (THC) and their major human metabolites. Batch experiments were performed under aerobic and anaerobic conditions using raw wastewater. Abiotic biomarker transformation and partitioning to suspended solids and reactor wall were separately investigated under both redox conditions. A process model was identified by combining and extending the Wastewater Aerobic/anaerobic Transformations in Sewers (WATS) model and Activated Sludge Model for Xenobiotics (ASM-X). Kinetic and stoichiometric model parameters were estimated using experimental data via the Bayesian optimization method DREAM. Results suggest that biomarker transformation significantly differs from aerobic to anaerobic conditions, and abiotic conversion is the dominant mechanism for many of the selected substances. Notably, an explicit description of biomass growth during batch experiments was crucial to avoid significant overestimation (up to 385%) of aerobic biotransformation rate constants. Predictions of in-sewer transformation provided here can reduce the uncertainty in the estimation of drug consumption as part of wastewater-based epidemiological studies.

We present a process model that predicts the removal of the antibiotic micropollutants, sulfamethoxazole (SMX), tetracycline (TCY), and ciprofloxacin (CIP), in an activated sludge treatment system. A novel method was developed to solve the inverse problem of inferring process rate, sorption, and correction factor parameter values from batch experimental results obtained under aerobic and anoxic conditions. Instead of spiking the batch reactors with reference substances, measurements were made using the xenobiotic organic micropollutant content of preclarified municipal sewage. Parent compound formation and removal were observed, and the model developed using the simulation software West showed limited efficiency to describe the selected micropollutants profiles, when growth substrate removal occurs. The model structure was optimized by accounting for competitive inhibition by readily biodegradable substrates on the cometabolic micropollutant biotransformation processes. Our results suggest that, under anoxic conditions, hydrophobicity-independent mechanisms can significantly impact solid-liquid partitioning that our model takes into account by using the sorption coefficient as a lumped parameter. Forward dynamic simulations were carried out to evaluate the developed model and to confirm it for SMX using data obtained in a full-scale treatment plant. Evaluation of measured and simulation results suggest that, robust model prediction can be achieved by approximating the influent load of chemicals biodegrading via a given parent compound, e.g., human conjugates, as an antibiotic mass that is proportional to the parent compound load.

Background and aims Wastewater‐based epidemiology is an additional indicator of drug use that is gaining reliability to complement the current established panel of indicators. The aims of this study were to: (i) assess spatial and temporal trends of population‐normalized mass loads of benzoylecgonine, amphetamine, methamphetamine and 3,4‐methylenedioxymethamphetamine (MDMA) in raw wastewater over 7 years (2011–17); (ii) address overall drug use by estimating the average number of combined doses consumed per day in each city; and (iii) compare these with existing prevalence and seizure data. Design Analysis of daily raw wastewater composite samples collected over 1 week per year from 2011 to 2017. Setting and Participants Catchment areas of 143 wastewater treatment plants in 120 cities in 37 countries. Measurements Parent substances (amphetamine, methamphetamine and MDMA) and the metabolites of cocaine (benzoylecgonine) and of Δ9‐tetrahydrocannabinol (11‐nor‐9‐carboxy‐Δ9‐tetrahydrocannabinol) were measured in wastewater using liquid chromatography–tandem mass spectrometry. Daily mass loads (mg/day) were normalized to catchment population (mg/1000 people/day) and converted to the number of combined doses consumed per day. Spatial differences were assessed world‐wide, and temporal trends were discerned at European level by comparing 2011–13 drug loads versus 2014–17 loads. Findings Benzoylecgonine was the stimulant metabolite detected at higher loads in southern and western Europe, and amphetamine, MDMA and methamphetamine in East and North–Central Europe. In other continents, methamphetamine showed the highest levels in the United States and Australia and benzoylecgonine in South America. During the reporting period, benzoylecgonine loads increased in general across Europe, amphetamine and methamphetamine levels fluctuated and MDMA underwent an intermittent upsurge. Conclusions The analysis of wastewater to quantify drug loads provides near real‐time drug use estimates that globally correspond to prevalence and seizure data.

BackgroundMonitoring the scale of pharmaceuticals, illicit and licit drugs consumption is important to assess the needs of law enforcement and public health, and provides more information about the different trends within different countries. Community drug use patterns are usually described by national surveys, sales and seizure data. Wastewater-based epidemiology (WBE) has been shown to be a reliable approach complementing such surveys.MethodThis study aims to compare and correlate the consumption estimates of pharmaceuticals, illicit drugs, alcohol, nicotine and caffeine from wastewater analysis and other sources of information. Wastewater samples were collected in 2015 from 8 different European cities over a one week period, representing a population of approximately 5 million people. Published pharmaceutical sale, illicit drug seizure and alcohol, tobacco and caffeine use data were used for the comparison.ResultsHigh agreement was found between wastewater and other data sources for pharmaceuticals and cocaine, whereas amphetamines, alcohol and caffeine showed a moderate correlation. methamphetamine and 3,4-methylenedioxymethamphetamine (MDMA) and nicotine did not correlate with other sources of data. Most of the poor correlations were explained as part of the uncertainties related with the use estimates and were improved with other complementary sources of data.ConclusionsThis work confirms the promising future of WBE as a complementary approach to obtain a more accurate picture of substance use situation within different communities. Our findings suggest further improvements to reduce the uncertainties associated with both sources of information in order to make the data more comparable.Electronic supplementary materialThe online version of this article (doi:10.1186/s12889-016-3686-5) contains supplementary material, which is available to authorized users.