Search

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.Analysis of daily raw wastewater composite samples collected over 1 week per year from 2011 to 2017.Catchment areas of 143 wastewater treatment plants in 120 cities in 37 countries.Parent substances (amphetamine, methamphetamine and MDMA) and the metabolites of cocaine (benzoylecgonine) and of ΔBenzoylecgonine 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.The analysis of wastewater to quantify drug loads provides near real-time drug use estimates that globally correspond to prevalence and seizure data.

Species specific nitrogen-to-phosphorus molar ratio (NPR) has been suggested for green microalgae. Algae can store nitrogen and phosphorus, suggesting that the optimum feed concentration dynamically changes as function of the nutrient storage. We assessed the effect of varying influent NPR on microalgal cultivation in terms of microbial community stability, effluent quality and biokinetics. Mixed green microalgae (Chlorella sorokiniana and Scenedesmus sp.) and a monoculture of Chlorella sp. were cultivated in continuous laboratory-scale reactors treating used water. An innovative image analysis tool, developed in this study, was used to track microbial community changes. Diatoms proliferated as influent NPR decreased, and were outcompeted once cultivation conditions were restored to the optimal NPR range. Low NPR operation resulted in decrease in phosphorus removal, biomass concentration and effluent nitrogen concentration. ASM-A kinetic model simulation results agreed well with operational data in the absence of diatoms. The failure to predict operational data in the presence of diatoms suggest differences in microbial activity that can significantly influence nutrient recovery in photobioreactors (PBR). No contamination occurred during Chlorella sp. monoculture cultivation with varying NPRs. Low NPR operation resulted in decrease in biomass concentration, effluent nitrogen concentration and nitrogen quota. The ASM-A model was calibrated for the monoculture and the simulations could predict the experimental data in continuous operation using a single parameter subset, suggesting stable biokinetics under the different NPR conditions. Results show that controlling the influent NPR is effective to maintain the algal community composition in PBR, thereby ensuring effective nutrients uptake.

Solids-flux theory (SFT) and state-point analysis (SPA) are used for the design, operation and control of secondary settling tanks (SSTs). The objectives of this study were to assess uncertainties, propagating from flow and solids loading boundary conditions as well as compression settling behaviour to the calculation of the limiting flux (JL) and the limiting solids concentration (XL). The interpreted computational fluid dynamics (iCFD) simulation model was used to predict one-dimensional local concentrations and limiting solids fluxes as a function of loading and design boundary conditions. A two-level fractional factorial design of experiments was used to infer the relative significance of factors unaccounted for in conventional SPA. To move away from using semi-arbitrary safety factors, a systematic approach was proposed to calculate the maximum SST capacity by employing a factor of 23% and a regression meta-model to correct values of JL and XL, respectively – critical for abating hydraulic effects under wet-weather flow conditions.

Wastewater-based epidemiology (WBE) was applied for the first time in seven cities across Europe with the aim of estimating quinolones consumption via the analysis of human urinary metabolites in wastewater. This report is also the first pan-European study focussed on the enantiomeric profiling of chiral quinolones in wastewater. By considering loads of (fluoro)quinolones in wastewater within the context of human stereoselective metabolism, we identified cities in Southern Europe characterised by both high usage and direct disposal of unused ofloxacin. In Northern European cities, S-(-)-ofloxacin loads were predominant with respect to R-(+)-ofloxacin. Much more potent, enantiomerically pure S-(-)-ofloxacin was detected in wastewaters from Southern European cities, reflecting consumption of the enantiomerically pure antibiotic. Nalidixic acid, norfloxacin and lomefloxacin were detected in wastewater even though they were not prescribed according to official prescription data. S,S-(-)-moxifloxacin and S,S-(-)-moxifloxacin-N-sulphate were detected in wastewater due to metabolism of moxifloxacin. For the first time, average population-normalised ulifloxacin loads of 22.3 and 1.5 mg day−1 1000 people−1 were reported for Milan and Castellón as a result of prulifloxacin metabolism. Enrichment of flumequine with first-eluting enantiomer in all the samples indicated animal metabolism rather than its direct disposal. Fluoroquinolone loads were compared with qnrS gene encoding quinolone resistance to correlate usage of fluoroquinolone and prevalence of resistance. The highest daily loads of the qnrS gene in Milan corresponded with the highest total quinolone load in Milan proving the hypothesis that higher usage of quinolones is linked with higher prevalence of quinolone resistance genes. Utrecht, with the lowest quinolones usage (low daily loads) had also one of the lowest daily loads of the qnrS gene. However, a similar trend was not observed in Oslo nor Bristol where higher qnrS gene loads were observed despite low quinolone usage.

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., This study was supported by the following countries, institutions and projects Australia: Thyne Reid foundation; Canada: Natural Sciences and Engineering Research Council of Canada (NSERC); Iceland: The Icelandic Research Fund (Grant number 163049–051); Slovenia: Slovene Research Agency (funding Project L1–9191); Spain: MINECO/AEI projects (CTM2014–56628‐C3–2‐R, CTQ2015–65603‐P, CTM2016–81935‐REDT, CTM2017–84763‐C3–2‐R), Galician Council of Culture, Education and Universities (ED481D 2017/003); UK: Environmental Sustainability Knowledge Transfer Network, Engineering and Physical Sciences Research Council and Thermo Fisher Scientific (CASE industrial scholarship for K. Munro, Ref.: EP/J502029/1). European Monitoring Centre for Drugs and Drug Addiction (EMCDDA); EU International Training Network SEWPROF (Marie Curie‐FP7‐PEOPLE, grant number 317205); COST Action ES1307 supported by COST (European Cooperation in Science and Technology); WATCH (Wastewater Analysis of Traces of illicit drug‐related Chemicals for law enforcement and public Health DG migration and Home affairs ‐ HOME/2015/ISFP/PR/DRUG/0062). Sampling support and provision of catchment information Austria: Klemens Geiger and Michael Schlapp; Belgium: Jonathan Phariseau, Bart Coene, Luc Van Os, Peter Nys, Dieter Lemaire, Jean‐François Mougel, Patrick Vantroyen and Karel Claes; Croatia: Marin Ganjto; Czech Republic: Jiri Stara and Robert Hrich Brněnské; France: Véronique Bremont; Italy: Roberto Mazzini and Francesca Pizza (Milan), Francesco Avolio (Bologna), Fabrizio Moratto and Sergio Ghezzi (Gorizia), Rosanna Brienza and Simona Panariello (Potenza), Pier Paolo Abis and Antonia Attanasio (Bari), Antonella Cicala (Palermo); Norway: Pia Ryrfors; Portugal: João Goulão, José Martins, Pedro Alvaro and Fátima Paixão; Slovakia: Silvia Antalová and Jozef Tichy; Spain: Begoña Martínez López, Cristian Mesa, Santiago Querol Rodriguez, Fernando Llavador, Enrique Albors and Gloria Fayos; the Netherlands: Alex Veltman, Peter Theijssen, Peter van Dijk, Stefan Wijers, Mark Stevens, Ferry de Wilde. Analytical support Australia: Maulik Ghetia; Cyprus: Popi Karaolia; Greece: Nikoilaos Raikos; Spain: Ana Maria Botero‐Coy, Clara Boix, Alberto Celma, Jorge Pitarch, Inés Racamonde and Eddie Fonseca; Italy: Emma Gracia‐Lor, Nikolaos I. Rousis and Noelia Salgueiro‐Gonzalez. Data repository and data screening Eawag: Harald von Waldow; EMCDDA: Renate Hochwieser, Liesbeth Vandam, João Matias and Federica Mathis.

Achromobacter denitrificans PR1 has previously shown potential to degrade the antibiotic sulfamethoxazole, whereby sulfamethoxazole biotransformation was stimulated in the presence of biogenic substrates. This study examined the biotransformation kinetics of sulfamethoxazole and its two main conjugates, N4-acetyl-SMX and SMX-N1-Glucuronide, by activated sludge and activated sludge bioaugmented with A. denitrificans PR1. SMX biotransformation under both anoxic and aerobic conditions was tested, with and without the addition of acetate as growth substrate, to understand the range of applicable conditions for bioaugmentation purposes. Biological process models, such as the pseudo-first order kinetic and cometabolic models, were also applied and, following the estimation of kinetic parameters, could well describe data measured in bioaugmented and non-bioaugmented AS batch experiments under various test conditions. Experimental and modelling results suggest that (i) retransformation of the two conjugates to SMX in AS occurred under both aerobic and anoxic conditions, and (ii) biotransformation kinetics of SMX can vary significantly depending on redox conditions, e.g., SMX was biotransformed by AS only under aerobic conditions. Notably, SMX biotransformation was significantly enhanced when PR1 was bioaugmented in AS. Addition of acetate as biogenic substrate is not necessary, as PR1 was capable of enhancing the SMX biotransformation by using the carbon sources present in wastewater. Overall, bioaugmentation by means of A. denitrificans PR1 could be a viable strategy for enhancing SMX removal in AS wastewater treatment plants (WWTPs).

The subdivision of biofilm reactor in two or more stages (i.e., reactor staging) represents an option for process optimisation of biological treatment. In our previous work, we showed that the gradient of influent organic substrate availability (induced by the staging) can influence the microbial activity (i.e., denitrification and pharmaceutical biotransformation kinetics) of a denitrifying three-stage Moving Bed Biofilm Reactor (MBBR) system. However, it is unclear whether staging and thus the long-term exposure to varying organic carbon type and loading influences the microbial community structure and diversity. In this study, we investigated biofilm structure and diversity in the three-stage MBBR system (S) compared to a single-stage configuration (U) and their relationship with microbial functions. Results from 16S rRNA amplicon libraries revealed a significantly higher microbial richness in the staged MBBR (at 99% sequence similarity) compared to single-stage MBBR. A more even and diverse microbial community was selected in the last stage of S (S3), likely due to exposure to carbon limitation during continuous-flow operation. A core of OTUs was shared in both systems, consisting of Burkholderiales, Xanthomonadales, Flavobacteriales and Sphingobacteriales, while MBBR staging selected for specific taxa (i.e., Candidate division WS6 and Deinococcales). Results from quantitative PCR (qPCR) showed that S3 exhibited the lowest abundance of 16S rRNA but the highest abundance of atypical nosZ, suggesting a selection of microbes with more diverse N-metabolism (i.e., incomplete denitrifiers) in the stage exposed to the lowest carbon availability. A positive correlation (p < 0.05) was observed between removal rate constants of several pharmaceuticals with abundance of relevant denitrifying genes, but not with biodiversity. Despite the previously suggested positive relationship between microbial diversity and functionality in macrobial and microbial ecosystems, this was not observed in the current study, indicating a need to further investigate structure-function relationships for denitrifying systems.

In-sewer transformation of drug biomarkers (excreted parent drugs and metabolites) can be influenced by the presence of biomass in suspended form as well as attached to sewer walls (biofilms). Biofilms are likely the most abundant and biologically active biomass fraction in sewers. In this study, 16 drug biomarkers were selected, including the parent forms and the major human metabolites of mephedrone, methadone, cocaine, heroin, codeine, and tetrahydrocannabinol (THC). Transformation and sorption of these substances were assessed in targeted batch experiments using laboratory-scale biofilm reactors operated under aerobic and anaerobic conditions. A one-dimensional model was developed to simulate diffusive transport, abiotic and biotic transformation, and partitioning of drug biomarkers. Model calibration to experimental results allowed estimating biotransformation rate constants in sewer biofilms, which were compared to those obtained for suspended biomass. Our results suggest that sewer biofilms can enhance the biotransformation kinetics of most selected compounds. Through scenario simulations, we demonstrated that the estimation of biotransformation rate constants in biofilm can be significantly biased if the boundary layer thickness is not accurately estimated. This study complements our previous investigation on the transformation and sorption of drug biomarkers in the presence of only suspended biomass in untreated sewage. A better understanding of the role of sewer biofilms—also relative to the in-sewer suspended solids—and improved prediction of associated fate processes can result in more accurate estimation of daily drug consumption in urban areas in wastewater-based epidemiological assessments.

Human biomonitoring, i.e. the determination of chemicals and/or their metabolites in human specimens, is the most common and potent tool for assessing human exposure to pesticides, but it suffers from limitations such as high costs and biases in sampling. Wastewater-based epidemiology (WBE) is an innovative approach based on the chemical analysis of specific human metabolic excretion products (biomarkers) in wastewater, and provides objective and real-time information on xenobiotics directly or indirectly ingested by a population. This study applied the WBE approach for the first time to evaluate human exposure to pesticides in eight cities across Europe. 24 h-composite wastewater samples were collected from the main wastewater treatment plants and analyzed for urinary metabolites of three classes of pesticides, namely triazines, organophosphates and pyrethroids, by liquid chromatography-tandem mass spectrometry. The mass loads (mg/day/1000 inhabitants) were highest for organophosphates and lowest for triazines. Different patterns were observed among the cities and for the various classes of pesticides. Population weighted loads of specific biomarkers indicated higher exposure in Castellon, Milan, Copenhagen and Bristol for pyrethroids, and in Castellon, Bristol and Zurich for organophosphates. The lowest mass loads (mg/day/1000 inhabitants) were found in Utrecht and Oslo. These results were in agreement with several national statistics related to pesticides exposure such as pesticides sales. The daily intake of pyrethroids was estimated in each city and it was found to exceed the acceptable daily intake (ADI) only in one city (Castellon, Spain). This was the first large-scale application of WBE to monitor population exposure to pesticides. The results indicated that WBE can give new information about the "average exposure" of the population to pesticides, and is a useful complementary biomonitoring tool to study population-wide exposure to pesticides. (C) 2017 Elsevier Ltd. All rights reserved.

Autotrophic ammonium oxidation in membrane-aerated biofilm reactors (MABRs) can make treatment of ammonium-rich wastewaters more energy-efficient, especially within the context of short-cut ammonium removal. The challenge is to exclusively enrich ammonium-oxidizing bacteria (AOB). To achieve nitritation, strategies to suppress nitrite-oxidizing bacteria (NOB) are needed, which are ideally grounded on an understanding of underlying mechanisms. In this study, a nitrifying MABR was operated under intermittent aeration. During eight months of operation, AOB dominated, while NOB were suppressed. On the basis of dissolved oxygen (DO), ammonium, nitrite, and nitrate profiles within the biofilm and in the bulk, a 1-dimensional nitrifying biofilm model was developed and calibrated. The model was utilized to explore the potential mechanisms of NOB suppression associated with intermittent aeration, considering DO limitation, direct pH effects on enzymatic activities, and indirect pH effects on activity via substrate speciation. The model predicted strong periodic shifts in the spatial gradients of DO, pH, free ammonia, and free nitrous acid, associated with aerated and nonaerated phases. NOB suppression during intermittent aeration was mostly explained by periodic inhibition caused by free ammonia due to periodic transient pH upshifts. Dissolved oxygen limitation did not govern NOB suppression. Different intermittent aeration strategies were then evaluated for nitritation success in intermittently aerated MABRs: both aeration intermittency and duration were effective control parameters.

Secondary settling tanks (SSTs) are the most hydraulically sensitive unit operations in activated sludge water resource recovery facilities (WRRF). Mathematical models for predicting activated sludge solids settling velocity include parameters that show irreducible epistemic uncertainty. Therefore, reliable and periodic calibration of the settling velocity model is key for predicting activated sludge process capacity, thus averting possible failures under wet-weather flow- and filamentous bulking conditions. The two main knowledge gaps addressed here are: (1) Do constitutive functions for hindered and compression settling exist, for which all velocity parameters can be uniquely estimated? (2) What is the optimum sensor data requirement of developing reliable settling velocity functions? Innovative settling column sensor and full-scale data were used to identify and validate amended Vesilind function for hindered settling and a new exponential function for compression settling velocity using one-dimensional and computational fluid dynamics simulations. Results indicate practical model identifiability under well-settling and filamentous bulking conditions.

Gas–liquid mass transfer in wastewater treatment processes has received considerable attention over the last decades from both academia and industry. Indeed, improvements in modelling gas–liquid mass transfer can bring huge benefits in terms of reaction rates, plant energy expenditure, acid–base equilibria and greenhouse gas emissions. Despite these efforts, there is still no universally valid correlation between the design and operating parameters of a wastewater treatment plant and the gas–liquid mass transfer coefficients. That is why the current practice for oxygen mass transfer modelling is to apply overly simplified models, which come with multiple assumptions that are not valid for most applications. To deal with these complexities, correction factors were introduced over time. The most uncertain of them is the α-factor. To build fundamental gas–liquid mass transfer knowledge more advanced modelling paradigms have been applied more recently. Yet these come with a high level of complexity making them impractical for rapid process design and optimisation in an industrial setting. However, the knowledge gained from these more advanced models can help in improving the way the α-factor and thus gas–liquid mass transfer coefficient should be applied. That is why the presented work aims at clarifying the current state-of-the-art in gas–liquid mass transfer modelling of oxygen and other gases, but also to direct academic research efforts towards the needs of the industrial practitioners.

Microalgal and cyanobacterial resource recovery systems could significantly advance nutrient recovery from wastewater by achieving effluent nitrogen (N) and phosphorus (P) levels below the current limit of technology. The successful implementation of phytoplankton, however, requires the formulation of process models that balance fidelity and simplicity to accurately simulate dynamic performance in response to environmental conditions. This work synthesizes the range of model structures that have been leveraged for algae and cyanobacteria modeling and core model features that are required to enable reliable process modeling in the context of water resource recovery facilities. Results from an extensive literature review of over 300 published phytoplankton models are presented, with particular attention to similarities with and differences from existing strategies to model chemotrophic wastewater treatment processes (e.g., via the Activated Sludge Models, ASMs). Building on published process models, the core requirements of a model structure for algal and cyanobacterial processes are presented, including detailed recommendations for the prediction of growth (under phototrophic, heterotrophic, and mixotrophic conditions), nutrient uptake, carbon uptake and storage, and respiration., Graphical abstract Image 1, Highlights • A critical review of 324 peer-reviewed phytoplankton models was conducted. • Modeling approaches for pseudo-mechanistic processes are synthesized. • Key factors (e.g., C, P, temperature) were only included in ∼25% of models. • Core model structure for wastewater treatment is proposed to advance model utility. • Future efforts should build on existing IWA models for transparency and usability.

The use of process models to simulate the fate of micropollutants in wastewater treatment plants is constantly growing. However, due to the high workload and cost of measuring campaigns, many simulation studies lack sufficiently long time series representing realistic wastewater influent dynamics. In this paper, the feasibility of the Benchmark Simulation Model No. 2 (BSM2) influent generator is tested to create realistic dynamic influent (micro)pollutant disturbance scenarios. The presented set of models is adjusted to describe the occurrence of three pharmaceutical compounds and one of each of its metabolites with samples taken every 2–4 h: the anti-inflammatory drug ibuprofen (IBU), the antibiotic sulfamethoxazole (SMX) and the psychoactive carbamazepine (CMZ). Information about type of excretion and total consumption rates forms the basis for creating the data-defined profiles used to generate the dynamic time series. In addition, the traditional influent characteristics such as flow rate, ammonium, particulate chemical oxygen demand and temperature are also modelled using the same framework with high frequency data. The calibration is performed semi-automatically with two different methods depending on data availability. The ‘traditional’ variables are calibrated with the Bootstrap method while the pharmaceutical loads are estimated with a least squares approach. The simulation results demonstrate that the BSM2 influent generator can describe the dynamics of both traditional variables and pharmaceuticals. Lastly, the study is complemented with: 1) the generation of longer time series for IBU following the same catchment principles; 2) the study of the impact of in-sewer SMX biotransformation when estimating the average daily load; and, 3) a critical discussion of the results, and the future opportunities of the presented approach balancing model structure/calibration procedure complexity versus predictive capabilities The authors acknowledge the People Program (Marie Curie Actions) of the European Union's Seventh Framework Program FP7/2007-2013 under REA agreement 289193 (SANITAS), REA agreement 329349 (PROTEUS) and the European Union (Marie Curie Career Integration Grant PCIG9-GA-2011-293535). Dr Flores-Alsina gratefully acknowledges the financial support of the collaborative international consortium WATERJPI2015 WATINTECH of the Water Challenges for a Changing World Joint Programming Initiative (Water JPI) 2015 call. Additionally, the Spanish Ministry of Science and Innovation (Ramon y Cajal, RYC-2013-14595), Ministry of Economy and Competitiveness (CTM2012-38314-C02-01 (WATERFATE)) and the Economy and Knowledge Department of the Catalan Government through the Consolidated Research Group (2014 SGR 291) - Catalan Institute for Water Research are acknowledged

Nitrous oxide (N2 O), a by-product of biological nitrogen removal during wastewater treatment, is produced by ammonia-oxidizing bacteria (AOB) and heterotrophic denitrifying bacteria (HB). Mathematical models are used to predict N2 O emissions, often including AOB as the main N2 O producer. Several model structures have been proposed without consensus calibration procedures. Here, we present a new experimental design that was used to calibrate AOB-driven N2 O dynamics of a mixed culture. Even though AOB activity was favoured with respect to HB, oxygen uptake rates indicated HB activity. Hence, rigorous experimental design for calibration of autotrophic N2 O production from mixed cultures is essential. The proposed N2 O production pathways were examined using five alternative process models confronted with experimental data inferred. Individually, the autotrophic and heterotrophic denitrification pathway could describe the observed data. In the best-fit model, which combined two denitrification pathways, the heterotrophic was stronger than the autotrophic contribution to N2 O production. Importantly, the individual contribution of autotrophic and heterotrophic to the total N2 O pool could not be unambiguously elucidated solely based on bulk N2 O measurements. Data on NO would increase the practical identifiability of N2 O production pathways. Biotechnol. Bioeng. 2017;114: 132-140. © 2016 Wiley Periodicals, Inc.

In this work a step forward in investigating the use of prescription drugs, namely erectile dysfunction products, at European level was taken by applying the wastewater-based epidemiology approach. 24-h composite samples of untreated wastewater were collected at the entrance of eight wastewater treatment plants serving the catchment within the cities of Bristol, Brussels, Castellón, Copenhagen, Milan, Oslo, Utrecht and Zurich. A validated analytical procedure with direct injection of filtered aliquots by liquid chromatography-tandem mass spectrometry was applied. The target list included the three active pharmaceutical ingredients (sildenafil, tadalafil and vardenafil) together with (bio)transformation products and other analogues. Only sildenafil and its two human urinary metabolites desmethyl- and desethylsildenafil were detected in the samples with concentrations reaching 60 ng L−1. The concentrations were transformed into normalized measured loads and the estimated actual consumption of sildenafil was back-calculated from these loads. In addition, national prescription data from five countries was gathered in the form of the number of prescribed daily doses and transformed into predicted loads for comparison. This comparison resulted in the evidence of a different spatial trend across Europe. In Utrecht and Brussels, prescription data could only partly explain the total amount found in wastewater; whereas in Bristol, the comparison was in agreement; and in Milan and Oslo a lower amount was found in wastewater than expected from the prescription data. This study illustrates the potential of wastewater-based epidemiology to investigate the use of counterfeit medication and rogue online pharmacy sales. Keywords: Erectile dysfunction, Prescription drugs, LC-MS/MS, Consumption, Counterfeit, Wastewater-based epidemiology

Temperature is one of the key factors, influencing the transformation kinetics of organic chemicals. In the context of wastewater-based epidemiology, however, temperature differences among sewer catchments and within the same catchment (due to, e.g., seasonal variations) have been neglected to date as a factor influencing the estimation of illicit drug consumption. In this study, we assessed the influence of temperature on the transformation of biomarkers in wastewater and its ensuing implications on the back-calculation of chemical consumption rate in urban catchments using the example of selected illicit drugs. Literature data, obtained in laboratory-scale experiments, on the stability of drug biomarkers in untreated wastewater at trace levels was systematically reviewed, and transformation rates obtained at different temperatures were collected. Arrhenius-based equations were fitted to empirical data and identified to describe the transformation of selected cocaine and morphine biomarkers at applicability temperature range (from 2–9 °C to 30–31 °C), with estimated exponential Arrhenius coefficients between 1.04 and 1.18. These empirically-derived relationships were used to assess the influence of temperature on the transformation of drug biomarkers during in-sewer transport and its effect on the back-calculation of drug consumption rate in hypothetical urban catchment scenario simulations. Up to 4-fold increase in removal efficiency was estimated when wastewater temperature increased from 15 °C to 25 °C. Findings from this study can help reducing the uncertainty intrinsic to wastewater-based epidemiology studies, and will be beneficial in comparing chemical consumption estimates from different catchments worldwide.

Excreted trace organic chemicals, e.g., pharmaceuticals and biocides, typically undergo incomplete elimination in municipal wastewater treatment plants (WWTPs) and are released to surface water via treated effluents and to agricultural soils through sludge amendment and/or irrigation with freshwater or reclaimed wastewater. Recent research has shown the tendency for these substances to accumulate in food crops. In this study, we developed and applied a simulation tool to predict the fate of three ionizable trace chemicals (triclosan—TCS, furosemide—FUR, ciprofloxacin—CIP) from human consumption/excretion up to the accumulation in soil and plant, following field amendment with sewage sludge or irrigation with river water (assuming dilution of WWTP effluent). The simulation tool combines the SimpleTreat model modified for fate prediction of ionizable chemicals in a generic WWTP and a recently developed dynamic soil-plant uptake model. The simulation tool was tested using country-specific (e.g., consumption/emission rates, precipitation and temperature) input data. A Monte Carlo-based approach was adopted to account for the uncertainty associated to physico-chemical and biokinetic model parameters. Results obtained in this study suggest significant accumulation of TCS and CIP in sewage sludge (1.4–2.8 mg kgDW−1) as compared to FUR (0.02–0.11 mg kgDW−1). For the latter substance, more than half of the influent load (60.1%–72.5%) was estimated to be discharged via WWTP effluent. Specific emission rates (g ha−1 a−1) of FUR to soil via either sludge application or irrigation were up to 300 times lower than for TCS and CIP. Nevertheless, high translocation potential to wheat was predicted for FUR, reaching concentrations up to 4.3 μg kgDW−1 in grain. Irrigation was found to enhance the relative translocation of FUR to plant (45.3%–48.9% of emission to soil), as compared to sludge application (21.9%–27.6%). A comparison with peer-reviewed literature showed that model predictions were close to experimental data for elimination in WWTP, concentrations in sewage and sludge and bioconcentration factors (BCFs) in plant tissues, which showed however a large variability. The simulation tool presented here can thus be useful for priority setting and for the estimation of human exposure to trace chemicals via intake of food crops.

The present study aims at using statistically designed computational fluid dynamics (CFD) simulations as numerical experiments for the identification of one-dimensional (1-D) advection-dispersion models - computationally light tools, used e.g., as sub-models in systems analysis. The objective is to develop a new 1-D framework, referred to as interpreted CFD (iCFD) models, in which statistical meta-models are used to calculate the pseudo-dispersion coefficient (D) as a function of design and flow boundary conditions. The method - presented in a straightforward and transparent way - is illustrated using the example of a circular secondary settling tank (SST). First, the significant design and flow factors are screened out by applying the statistical method of two-level fractional factorial design of experiments. Second, based on the number of significant factors identified through the factor screening study and system understanding, 50 different sets of design and flow conditions are selected using Latin Hypercube Sampling (LHS). The boundary condition sets are imposed on a 2-D axi-symmetrical CFD simulation model of the SST. In the framework, to degenerate the 2-D model structure, CFD model outputs are approximated by the 1-D model through the calibration of three different model structures for D. Correlation equations for the D parameter then are identified as a function of the selected design and flow boundary conditions (meta-models), and their accuracy is evaluated against D values estimated in each numerical experiment. The evaluation and validation of the iCFD model structure is carried out using scenario simulation results obtained with parameters sampled from the corners of the LHS experimental region. For the studied SST, additional iCFD model development was carried out in terms of (i) assessing different density current sub-models; (ii) implementation of a combined flocculation, hindered, transient and compression settling velocity function; and (iii) assessment of modelling the onset of transient and compression settling. Furthermore, the optimal level of model discretization both in 2-D and 1-D was undertaken. Results suggest that the iCFD model developed for the SST through the proposed methodology is able to predict solid distribution with high accuracy - taking a reasonable computational effort - when compared to multi-dimensional numerical experiments, under a wide range of flow and design conditions. iCFD tools could play a crucial role in reliably predicting systems' performance under normal and shock events.

The objective of this work is to identify relevant settling velocity and rheology model parameters and to assess the underlying filamentous microbial community characteristics that can influence the solids mixing and transport in secondary settling tanks. Parameter values for hindered, transient and compression settling velocity functions were estimated by carrying out biweekly batch settling tests using a novel column setup through a four-month long measurement campaign. To estimate viscosity model parameters, rheological experiments were carried out on the same sludge sample using a rotational viscometer. Quantitative fluorescence in-situ hybridisation (qFISH) analysis, targeting Microthrix parvicella and phylum Chloroflexi, was used. This study finds that M. parvicella - predominantly residing inside the microbial flocs in our samples - can significantly influence secondary settling through altering the hindered settling velocity and yield stress parameter. Strikingly, this is not the case for Chloroflexi, occurring in more than double the abundance of M. parvicella, and forming filaments primarily protruding from the flocs. The transient and compression settling parameters show a comparably high variability, and no significant association with filamentous abundance. A two-dimensional, axi-symmetrical computational fluid dynamics (CFD) model was used to assess calibration scenarios to model filamentous bulking. Our results suggest that model predictions can significantly benefit from explicitly accounting for filamentous bulking by calibrating the hindered settling velocity function. Furthermore, accounting for the transient and compression settling velocity in the computational domain is crucial to improve model accuracy when modelling filamentous bulking. However, the case-specific calibration of transient and compression settling parameters as well as yield stress is not necessary, and an average parameter set - obtained under bulking and good settling conditions - can be used.

Current research considers wastewater as a source of energy, nutrients and water and not just a source of pollution. So far, mainly energy intensive physical and chemical unit processes have been developed to recover some of these resources, and less energy and resource demanding alternatives are needed. Here, we present a modified enhanced biological phosphorus removal and recovery system (referred to as EBP2R) that can produce optimal culture media for downstream micro-algal growth in terms of N and P content. Phosphorus is recovered as a P-stream by diversion of some of the effluent from the upstream anaerobic reactor. By operating the process at comparably low solids retention times (SRT), the nitrogen content of wastewater is retained as free and saline ammonia, the preferred form of nitrogen for most micro-algae. Scenario simulations were carried out to assess the capacity of the EBP2R system to produce nutrient rich organic-carbon depleted algal cultivation media of target composition. Via SRT control, the quality of the constructed cultivation media can be optimized to support a wide range of green micro-algal growth requirements. Up to 75% of the influent phosphorus can be recovered, by diverting 30% of the influent flow as a P-stream at an SRT of 5 days. Through global sensitivity analysis we find that the effluent N-to-P ratio and the P recovered are mainly dependent on the influent quality rather than on biokinetics or stoichiometry. Further research is needed to demonstrate that the system performance predicted through the model-based design can be achieved in reality.

Due to their widespread application in consumer products, elemental titanium (e.g., titanium dioxide, TiO2) and silver (Ag), also in nanoparticulate form, are increasingly released from households and industrial facilities to urban wastewater treatment plants (WWTPs). A seven-day sampling campaign was conducted in two full-scale WWTPs in Trondheim (Norway) employing only primary treatment. We assessed the occurrence and elimination of Ti and Ag, and conducted size-based fractionation using sequential filtration of influent samples to separate particulate, colloidal and dissolved fractions. Eight-hour composite influent samples were collected to assess diurnal variations in total Ti and Ag influx. Measured influent Ti concentrations (up to 290 µg L-1) were significantly higher than Ag (0.7 µm). Removal efficiencies ≥70% were observed for both elements, requiring for one WWTP to account for the high Ti content (~2 g L-1) in the flocculant. Nano- and micron-sized Ti particles were observed with scanning transmission electron microscopy (STEM) in influent, effluent and biosolids, while Ag nanoparticles were detected in biosolids only. Diurnal profiles of influent Ti were correlated to flow and pollutant concentration patterns (especially total suspended solids), with peaks during the morning and/or evening and minima at night, indicating household discharges as predominant source. Irregular profiles were exhibited by influent Ag, with periodic concentration spikes suggesting short-term discharges from one or few point sources (e.g., industry). Influent Ti and Ag dynamics were reproduced using a disturbance scenario generator model, and we estimated per capita loads of Ti (42–45 mg cap-1 d-1) and Ag (0.11 mg cap-1 d-1) from households as well as additional Ag load (14–22 g d-1) from point discharge. This is the first study to experimentally and mathematically describe short-term release dynamics and dry-weather sources of emissions of Ti and Ag in municipal WWTPs and receiving environments. Occurrence, characterisation and fate of (nano)particulate Ti and Ag in two Norwegian wastewater treatment plants

Caffeine metabolites in wastewater were investigated as potential biomarkers for assessing caffeine intake in a population. The main human urinary metabolites of caffeine were measured in the urban wastewater of ten European cities and the metabolic profiles in wastewater were compared with the human urinary excretion profile. A good match was found for 1,7-dimethyluric acid, an exclusive caffeine metabolite, suggesting that might be a suitable biomarker in wastewater for assessing population-level caffeine consumption. A correction factor was developed considering the percentage of excretion of this metabolite in humans, according to published pharmacokinetic studies. Daily caffeine intake estimated from wastewater analysis was compared with the average daily intake calculated from the average amount of coffee consumed by country per capita. Good agreement was found in some cities but further information is needed to standardize this approach. Wastewater analysis proved useful to providing additional local information on caffeine use. (C) 2017 Elsevier B.V. All rights reserved.

The NDHA model comprehensively describes nitrous oxide (N

The NDHA model comprehensively describes nitrous oxide (N2O) producing pathways by both autotrophic ammonium oxidizing and heterotrophic bacteria. The model was calibrated via a set of targeted extant respirometric assays using enriched nitrifying biomass from a lab-scale reactor. Biomass response to ammonium, hydroxylamine, nitrite and N2O additions under aerobic and anaerobic conditions were tracked with continuous measurement of dissolved oxygen (DO) and N2O. The sequential addition of substrate pulses allowed the isolation of oxygen-consuming processes. The parameters to be estimated were determined by the information content of the datasets using identifiability analysis. Dynamic DO profiles were used to calibrate five parameters corresponding to endogenous, nitrite oxidation and ammonium oxidation processes. The subsequent N2O calibration was not significantly affected by the uncertainty propagated from the DO calibration because of the high accuracy of the estimates. Five parameters describing the individual contribution of three biological N2O pathways were estimated accurately (variance/mean < 10% for all estimated parameters). The NDHA model response was evaluated with statistical metrics (F-test, autocorrelation function). The 95% confidence intervals of DO and N2O predictions based on the uncertainty obtained during calibration are studied for the first time. The measured data fall within the 95% confidence interval of the predictions, indicating a good model description. Overall, accurate parameter estimation and identifiability analysis of ammonium removal significantly decreases the uncertainty propagated to N2O production, which is expected to benefit N2O model discrimination studies and reliable full scale applications.

Solid-liquid partitioning is one of the main fate processes determining the removal of micropollutants in wastewater. Little is known on the sorption of micropollutants in biofilms, where molecular diffusion may significantly influence partitioning kinetics. In this study, the diffusion and the sorption of 23 micropollutants were investigated in novel moving bed biofilm reactor (MBBR) carriers with controlled biofilm thickness (50, 200 and 500 μm) using targeted batch experiments (initial concentration = 1 μg L−1, for X-ray contrast media 15 μg L−1) and mathematical modelling. We assessed the influence of biofilm thickness and density on the dimensionless effective diffusivity coefficient f (equal to the biofilm-to-aqueous diffusivity ratio) and the distribution coefficient Kd,eq (L g−1). Sorption was significant only for eight positively charged micropollutants (atenolol, metoprolol, propranolol, citalopram, venlafaxine, erythromycin, clarithromycin and roxithromycin), revealing the importance of electrostatic interactions with solids. Sorption equilibria were likely not reached within the duration of batch experiments (4 h), particularly for the thickest biofilm, requiring the calculation of the distribution coefficient Kd,eq based on the approximation of the asymptotic equilibrium concentration (t > 4 h). Kd,eq values increased with increasing biofilm thickness for all sorptive micropollutants (except atenolol), possibly due to higher porosity and accessible surface area in the thickest biofilm. Positive correlations between Kd,eq and micropollutant properties (polarity and molecular size descriptors) were identified but not for all biofilm thicknesses, thus confirming the challenge of improving predictive sorption models for positively charged compounds. A diffusion-sorption model was developed and calibrated against experimental data, and estimated f values also increased with increasing biofilm thickness. This indicates that diffusion in thin biofilms may be strongly limited (f ≪ 0.1) by the high biomass density (reduced porosity).

The popularity of new psychoactive substances (NPS) has grown in recent years, with certain NPS commonly and preferentially consumed even following the introduction of preventative legislation. With the objective to improve the knowledge on the use of NPS, a rapid and very sensitive method was developed for the determination of ten priority NPS (N-ethylcathinone, methylenedioxypyrovalerone (MDPV), methylone, butylone, methedrone, mephedrone, naphyrone, 25-C-NBOMe, 25-I-NBOMe and 25-B-NBOMe) in influent wastewater. Sample clean-up and pre-concentration was made by off-line solid phase extraction (SPE) with Oasis MCX cartridges. Isotopically labelled internal standards were used to correct for matrix effects and potential SPE losses. Following chromatographic separation on a C18 column within 6 min, the compounds were measured by tandem mass spectrometry in positive ionization mode. The method was optimised and validated for all compounds. Limits of quantification were evaluated by spiking influent wastewater samples at 1 or 5 ng/L. An investigation into the stability of these compounds in influent wastewater was also performed, showing that, following acidification at pH 2, all compounds were relatively stable for up to 7 days. The method was then applied to influent wastewater samples from eight European countries, in which mephedrone, methylone and MDPV were detected. This work reveals that although NPS use is not as extensive as for classic illicit drugs, the application of a highly sensitive analytical procedure makes their detection in wastewater possible. The developed analytical methodology forms the basis of a subsequent model-based back-calculation of abuse rate in urban areas (i.e. wastewater-based epidemiology). The authors would like to thank all the personnel of the wastewater treatment plants for their collaboration in providing the samples: Sociedad de Fomento Agrícola Castellonense (FACSA, Castellon, Spain), VEAS (Oslo, Norway), Aquiris (Brussels, Belgium), Hoogheemraadschap de Stichtse Rijnlanden (Utrecht, the Netherlands), Wessex Water (Bristol, UK), Metropolitana Milanese (Milan, Italy), Werdhölzli (Zurich, Switzerland) and BIOFOS (Copenhagen, Denmark). RB, JBL, EC, AC, JK, AKM, PR and NIR acknowledge the European Union for their Early Stage Researcher (ESR) contracts and EGL for her Experienced Researcher (ER) contract as part of the EU-International Training Network SEWPROF (Marie Curie- PEOPLE Grant #317205). LB acknowledges NPS-Euronet (HOME/2014/JDRUG/AG/DRUG/7086), co-funded by the European Union, for his post-doctoral fellowship. This publication reflects the views only of the authors, and the European Commission cannot be held responsible for any use which may be made of the information contained therein. AvN acknowledges the support of the Flanders Foundation for Research (FWO). EGL is also thankful for the financial support from Generalitat Valenciana (APOSTD/2015, Programa VALi+d). The financial support of Generalitat Valenciana and of the Spanish Ministry of Economy and Competitiveness (Project ref CTQ2015-65603) is also acknowledged by the authors of University Jaume I.

Addition of external carbon sources to post-denitrification systems is frequently used in wastewater treatment plants to enhance nitrate removal. However, little is known about the fate of micropollutants in post-denitrification systems and the influence of external carbon dosing on their removal. In this study, we assessed the effects of two different types and availability of commonly used carbon sources -methanol and ethanol- on the removal of micropollutants in biofilm systems. Two laboratory-scale moving bed biofilm reactors (MBBRs), containing AnoxKaldnes K1 carriers with acclimated biofilm from full-scale systems, were operated in continuous-flow using wastewater dosed with methanol and ethanol, respectively. Batch experiments with 22 spiked pharmaceuticals were performed to assess removal kinetics. Acetyl-sulfadiazine, atenolol, citalopram, propranolol and trimethoprim were easily biotransformed in both MBBRs (biotransformations rate constants kbio between 1.2 and 12.9 L gbiomass(-1) d(-1)), 13 compounds were moderately biotransformed (rate constants between 0.2 and 2 L gbiomass(-1) d(-1)) and 4 compounds were recalcitrant. The methanol-dosed MBBR showed higher kbio (e.g., 1.5-2.5-fold) than in the ethanol-dosed MBBR for 9 out of the 22 studied compounds, equal kbio for 10 compounds, while 3 compounds (i.e., targeted sulfonamides) were biotransformed faster in the ethanol-dosed MBBR. While biotransformation of most of the targeted compounds followed first-order kinetics, removal of venlafaxine, carbamazepine, sulfamethoxazole and sulfamethizole could be described with a cometabolic model. Analyses of the microbial composition in the biofilms using 16S rRNA amplicon sequencing revealed that the methanol-dosed MBBR contained higher microbial richness than the one dosed with ethanol, suggesting that improved biotransformation of targeted compounds could be associated with higher microbial richness. During continuous-flow operation, at conditions representative of full-scale denitrification systems (hydraulic residence time = 2 h), the removal efficiencies of micropollutants were below 35% in both MBBRs, with the exception of atenolol and trimethoprim (>80%). Overall, this study demonstrated that MBBRs used for post-denitrification could be optimized to enhance the biotransformation of a number of micropollutants by accounting for optimal carbon sources and extended residence time.

This paper demonstrates how occurrence, transport and fate of pharmaceuticals at trace levels can be assessed when modelling wastewater treatment systems using two case studies. Firstly, two approaches based on: 1) phenomenology; and, 2) Markov Chains, are developed to describe the dynamics of pharmaceuticals with or without clear administration patterns. Additional simulations also show that sewer conditions might have an important effect on the behaviour of the generated compounds and their metabolites. The results demonstrate that different operating conditions in wastewater treatment plants can have opposite effects on the studied pharmaceuticals, especially when they present co-metabolic or inhibitory behaviour in the presence of biodegradable substrate. Finally, the paper ends with: i) a critical discussion of the presented results; ii) a thorough analysis of the limitations of the proposed approach; and, iii) future pathways to improve the overall modelling of micropollutants. Display Omitted A set of models predicting occurrence, transport and fate of pharmaceuticals is shown.Patterns are modelled using phenomenological/stochastic approaches.Transport conditions have an impact on soluble/particulate compounds.Co-metabolic/inhibitory effect with other wastewater compounds is included.

Current research focuses on predicting and mitigating the impacts of high hydraulic loadings on centralized wastewater treatment plants (WWTPs) under wet-weather conditions. The maximum permissible inflow to WWTPs depends not only on the settleability of activated sludge in secondary settling tanks (SSTs) but also on the hydraulic behaviour of SSTs. The present study investigates the impacts of ideal and non-ideal flow (dry and wet weather) and settling (good settling and bulking) boundary conditions on the sensitivity of WWTP model outputs to uncertainties intrinsic to the one-dimensional (1-D) SST model structures and parameters. We identify the critical sources of uncertainty in WWTP models through global sensitivity analysis (GSA) using the Benchmark simulation model No. 1 in combination with first- and second-order 1-D SST models. The results obtained illustrate that the contribution of settling parameters to the total variance of the key WWTP process outputs significantly depends on the influent flow and settling conditions. The magnitude of the impact is found to vary, depending on which type of 1-D SST model is used. Therefore, we identify and recommend potential parameter subsets for WWTP model calibration, and propose optimal choice of 1-D SST models under different flow and settling boundary conditions. Additionally, the hydraulic parameters in the second-order SST model are found significant under dynamic wet-weather flow conditions. These results highlight the importance of developing a more mechanistic based flow-dependent hydraulic sub-model in second-order 1-D SST models in the future.

This study investigates the sensitivity of wastewater treatment plant (WWTP) model performance to the selection of one-dimensional secondary settling tanks (1-D SST) models with first-order and second-order mathematical structures. We performed a global sensitivity analysis (GSA) on the benchmark simulation model No. 2 with the input uncertainty associated to the biokinetic parameters in the activated sludge model No. 1 (ASM1), a fractionation parameter in the primary clarifier, and the settling parameters in the SST model. Based on the parameter sensitivity rankings obtained in this study, the settling parameters were found to be as influential as the biokinetic parameters on the uncertainty of WWTP model predictions, particularly for biogas production and treated water quality. However, the sensitivity measures were found to be dependent on the 1-D SST models selected. Accordingly, we suggest a different optimum parameter selection for the calibration of WWTP models when either of the 1-D SST models is used. Using first-order models, the calibration should give equal importance to the adjustment of the hindered settling and slow settling parameter values. The adjusted hindered settling parameters have, however, no physical meaning, and might additionally obtain unrealistic values. In contrast, using second-order SST models, the focus of calibration should be on providing measured values for the hindered settling parameters. This approach is in close agreement with the recommendations made in the good modelling practice protocol on activated sludge modelling. Besides, based on the GSA results, adjusting the non-measurable slow settling parameter produces significantly less variance in the model outputs using the second-order model than using the first-order model.

The quantitative analysis of human urinary metabolites as biomarkers in wastewater streams has been used to estimate the rates of illicit drug use in the wider community. The primary underlying assumption in such studies is that a sample of wastewater is equivalent to a cumulative sample of urine. Drug metabolism in humans is predominantly enzymatically mediated, but these processes are not exclusive to the human body, and are found to occur in the environment and the sewer network. Understanding what happens to drugs and their urinary metabolites in the sewer system between the point of excretion and sampling is particularly important since it is possible that in-sewer transformation may influence final biomarker concentration. The present study uses batch experiments to measure and assess the biotransformation processes of cocaine and its two major human metabolites, benzoylecgonine and ecgonine methyl ester. The activated sludge modelling framework for xenobiotic organic micro-pollutants (ASM-X) is used for model structure identification and calibration. Biotransformation was observed to follow pseudo first-order kinetics. The biodegradation kinetics of cocaine, benzoylecgonine and ecgonine methyl ester is not significantly affected by the availability of dissolved oxygen. Results obtained in this study show that omitting in-pipe biotransformation affects the accuracy of back-calculated cocaine use estimates. This varies markedly depending on the in-sewer hydraulic retention time, total biomass concentration and the relative concentration of each metabolite. However, back-calculated cocaine use estimates derived from wastewater concentrations of benzoylecgonine and ecgonine methyl ester do show very close agreement if ex-vivo biotransformation of these compounds is considered.

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(ZS). 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.

Nitrous oxide (N

Quantitative measurement of drug consumption biomarkers in wastewater can provide objective information on community drug use patterns and trends. This study presents the measurement of alcohol consumption in 20 cities across 11 countries through the use of wastewater-based epidemiology (WBE), and reports the application of these data for the risk assessment of alcohol on a population scale using the margin of exposure (MOE) approach. Raw 24-h composite wastewater samples were collected over a one-week period from 20 cities following a common protocol. For each sample a specific and stable alcohol consumption biomarker, ethyl sulfate (EtS) was determined by liquid chromatography coupled to tandem mass spectrometry. The EtS concentrations were used for estimation of per capita alcohol consumption in each city, which was further compared with international reports and applied for risk assessment by MOE. The average per capita consumption in 20 cities ranged between 6.4 and 44.3L/day/1000 inhabitants. An increase in alcohol consumption during the weekend occurred in all cities, however the level of this increase was found to differ. In contrast to conventional data (sales statistics and interviews), WBE revealed geographical differences in the level and pattern of actual alcohol consumption at an inter-city level. All the sampled cities were in the "high risk" category (MOE10) and the average MOE for the whole population studied was 2.5. These results allowed direct comparisons of alcohol consumption levels, patterns and risks among the cities. This study shows that WBE can provide timely and complementary information on alcohol use and alcohol associated risks in terms of exposure at the community level.

Nowadays, wastewater is considered as a set of resources to be recovered rather than a mixture of pollutants that should be removed. Many resource recovery schemes have been proposed, involving the use of novel technologies whose controllability is poorly studied. In this paper we present a control structure for the novel enhanced biological phosphorus removal and recovery (EBP2R) process, which is currently under development. The aim of the EBP2R is to maximize phosphorus recovery through optimal green micro-algal cultivation, which is achieved by controlling the nitrogen to phosphorus ratio (N-to-P ratio) fed to the algae. Process control structures are developed for a sequencing batch reactor (SBR) and a continuous flow reactor system (CFS). Results, obtained using the Benchmark Simulation Model No. 1 (BSM1) dynamic input disturbance time series, suggest that the SBR can maintain a stable N-to-P ratio in the effluent (16.9 ± 0.07) and can recover about 72% of the influent phosphorus. The phosphorus recovered by the CFS is limited by the influent nitrogen (65% of the influent phosphorus load). Using the CFS configuration the effluent N-to-P ratio cannot be effectively controlled (16.45 ± 2.48). Therefore, it is concluded that the SBR is the most effective reactor configuration for the EBP2R process. Importantly, the designed control structures rely on control loops that do not require chemical dosing for nutrient management, thereby reducing the environmental footprint of the EBP2R process. The proposed control strategies can be applied to other phosphorus recovery schemes where short sludge age EBPR systems play an important role.

Third generation biofuels, e.g. biofuels production from algal biomass, have gained attention due to increased interest on global renewable energy. However, crop-based biofuels compete with food production and should be avoided. Microalgal cultivation for biofuel production offers an alternative to crops and can become economically viable when combined with the use of used water resources. Besides nutrients and water, harvesting microalgal biomass represents one of the major costs related to biofuel production and thus efficient and cheap solutions are needed. In bacterial-algal systems, there is the potential to produce energy by co-digesting the two types of biomass. We present an innovative approach to recover microalgal biomass via a two-step flocculation using bacterial biomass after the destabilisation of microalgae with conventional cationic polymer. A short solids retention time (SRT) enhanced biological phosphorus removal (EBPR) system was combined with microalgal cultivation. Two different bacterial biomass removal strategies were assessed whereby bacterial biomass was collected from the solid-liquid separation after the anaerobic phase and after the aerobic phase. Microalgal recovery was tested by jar tests where three different chemical coagulants in coagulation-flocculation tests (AlCl3, PDADMAC and Greenfloc 120) were assessed. Furthermore, jar tests were conducted to assess the microalgal biomass recovery by a two-step flocculation method, involving chemical coagulants in the first step and bacterial biomass used in the second step to enhance the flocculation. Up to 97% of the microalgal biomass was recovered using 16 mg polymer/g algae and 0.1 g algae/g bacterial biomass. Moreover, the energy recovery by the short-SRT EBPR system combined with microalgal cultivation was assessed via biomethane potential tests. Up to 560 ± 24 mL CH4/gVS methane yield was obtained by co-digesting bacterial biomass collected after the anaerobic phase and microalgal biomass. The energy recovery in terms of methane production obtained in the short-SRT EBPR system is about 40% of the influent chemical energy.

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. F2-isoprostanes are a prototype wastewater biomarker to study the cumulative oxidative stress at a community level. In this work, 8-iso-prostaglandin F2α (8-iso-PGF2α) 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-PGF2α and the consumption of the two drugs. The estimated per capita daily loads of 8-iso-PGF2α 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-PGF2α, however, spatial differences were found at the inter-city level correlating to the degree of urbanisation. The 8-iso-PGF2α 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-PGF2α as a wastewater biomarker for the assessment of community public health. This work is part of the EU Marie Curie Initial Training Network SEWPROF (Marie Curie-FP7-PEOPLE, grant No. 317205) and the financial support of the EU is greatly acknowledged. E.G.L. is also grateful to Generalitat Valenciana (APOSTD/2015, Programa VALi + d). The authors thank all personnel of the wastewater treatment plants for their collaboration in the collection of the wastewater samples.

Many scientific studies present removal efficiencies for pharmaceuticals in laboratory-, pilot-, and full-scale wastewater treatment plants, based on observations that may be impacted by theoretical and methodological approaches used. In this Critical Review, we evaluated factors influencing observed removal efficiencies of three antibiotics (sulfamethoxazole, ciprofloxacin, tetracycline) in pilot- and full-scale biological treatment systems. Factors assessed include (i) retransformation to parent pharmaceuticals from e.g., conjugated metabolites and analogues, (ii) solid retention time (SRT), (iii) fractions sorbed onto solids, and (iv) dynamics in influent and effluent loading. A recently developed methodology was used, relying on the comparison of removal efficiency predictions (obtained with the Activated Sludge Model for Xenobiotics (ASM-X)) with representative measured data from literature. By applying this methodology, we demonstrated that (a) the elimination of sulfamethoxazole may be significantly underestimated when not considering retransformation from conjugated metabolites, depending on the type (urban or hospital) and size of upstream catchments; (b) operation at extended SRT may enhance antibiotic removal, as shown for sulfamethoxazole; (c) not accounting for fractions sorbed in influent and effluent solids may cause slight underestimation of ciprofloxacin removal efficiency. Using tetracycline as example substance, we ultimately evaluated implications of effluent dynamics and retransformation on environmental exposure and risk prediction.

Background: Monitoring 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. Method: This 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. Results: High 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. Conclusions: This 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. Jose Antonio Baz Lomba, Stefania Salvatore, Richard Bade, Erika Castrignanò, Ana Causanilles, Juliet Kinyua, Ann-Kathrin McCall, Pedram Ramin, Nikolaos I. Rousis, and Yeonsuk Ryu acknowledge the EU Marie-Skłodowska Curie Initial Training Network SEWPROF (Marie Curie-FP7-PEOPLE, grant number 317205) for their Early Stage Researcher grant and Emma Gracia-Lor for her Experienced Researcher grant. We thank the people and agencies who assisted in the collection of the wastewater samples, in particular Pia Ryrfors and colleagues at Vestfjorden Avløpselskap (VEAS, Oslo, Norway).

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.

The new paradigm for used water treatment suggests the use of short solid retention times (SRT) to minimize organic substrate mineralization and to maximize resource recovery. However, little is known about the microbes and the underlying biogeochemical mechanisms driving these short-SRT systems. In this paper, we report the start-up and operation of a short-SRT enhanced biological phosphorus removal (EBPR) system operated as a sequencing batch reactor (SBR) fed with preclarified municipal wastewater, which is supplemented with propionate. The microbial community was analysed via 16S rRNA amplicon sequencing. During start-up (SRT = 8 d), the EBPR was removing up to 99% of the influent phosphate and completely oxidized the incoming ammonia. Furthermore, the sludge showed excellent settling properties. However, once the SRT was shifted to 3.5 days nitrification was inhibited and bacteria of the Thiothrix taxon proliferated in the reactor, thereby leading to filamentous bulking (sludge volume index up to SVI = 1100 mL/g). Phosphorus removal deteriorated during this period, likely due to the out-competition of polyphosphate accumulating organisms (PAO) by sulphate reducing bacteria (SRB). Subsequently, SRB activity was suppressed by reducing the anaerobic SRT from 1.2 day to 0.68 day, with a consequent rapid SVI decrease to ∼200 ml/g. The short-SRT EBPR effectively removed phosphate and nitrification was mitigated at SRT = 3 days and oxygen levels ranging from 2 to 3 mg/L.

In WWTP models, the accurate assessment of solids inventory in bioreactors equipped with solid-liquid separators, mostly described using one-dimensional (1-D) secondary settling tank (SST) models, is the most fundamental requirement of any calibration procedure. Scientific knowledge on characterising particulate organics in wastewater and on bacteria growth is well-established, whereas 1-D SST models and their impact on biomass concentration predictions are still poorly understood. A rigorous assessment of two 1-DSST models is thus presented: one based on hyperbolic (the widely used Takács-model) and one based on parabolic (the more recently presented Plósz-model) partial differential equations. The former model, using numerical approximation to yield realistic behaviour, is currently the most widely used by wastewater treatment process modellers. The latter is a convection-dispersion model that is solved in a numerically sound way. First, the explicit dispersion in the convection-dispersion model and the numerical dispersion for both SST models are calculated. Second, simulation results of effluent suspended solids concentration (XTSS,Eff), sludge recirculation stream (XTSS,RAS) and sludge blanket height (SBH) are used to demonstrate the distinct behaviour of the models. A thorough scenario analysis is carried out using SST feed flow rate, solids concentration, and overflow rate as degrees of freedom, spanning a broad loading spectrum. A comparison between the measurements and the simulation results demonstrates a considerably improved 1-D model realism using the convection-dispersion model in terms of SBH, XTSS,RAS and XTSS,Eff. Third, to assess the propagation of uncertainty derived from settler model structure to the biokinetic model, the impact of the SST model as sub-model in a plant-wide model on the general model performance is evaluated. A long-term simulation of a bulking event is conducted that spans temperature evolution throughout a summer/winter sequence. The model prediction in terms of nitrogen removal, solids inventory in the bioreactors and solids retention time as a function of the solids settling behaviour is investigated. It is found that the settler behaviour, simulated by the hyperbolic model, can introduce significant errors into the approximation of the solids retention time and thus solids inventory of the system. We demonstrate that these impacts can potentially cause deterioration of the predictive power of the biokinetic model, evidenced by an evaluation of the system's nitrogen removal efficiency. The convection-dispersion model exhibits superior behaviour, and the use ofthis type of model thus is highly recommended, especially bearing in mind future challenges, e.g., the explicit representation of uncertainty in WWTP models.

In this study, we investigate factors that can affect nitrification and denitrification in a moving bed biofilm system, treating partly stabilized landfill leachate. The optimization of biological treatment by means of controlled ozonation is additionally evaluated. Results obtained with a laboratory-scale, continuous-flow biofilm system suggest that nitrogen removal can be limited by the low influent biodegradable substrate concentrations, and that autotrophic nitrification can be adversely impacted by the high alkalinity buffer and ammonium/ammonia concentration. Our results suggest an optimum ozone dosage as high as 0.5 g/L O3 can be required to effectively decrease the effluent soluble COD concentration and pH profile in the aerobic reactors, improve the biodegradable COD production from inert compounds, and induce chemical nitrification in the system. The specific cost of ozonation evaluated is 0.36-0.73 euro/m 3 with 911 mg/L average effluent soluble COD measured in the biofilm system.

We present an assessment of the dynamics in the influent concentration of hormones (estrone, estriol) and antibiotics (trimethoprim, sulfamethoxazole, tetracycline, ciprofloxacin) in the liquid phase including the efficiency of biological municipal wastewater treatment. The concentration of estradiol, 17-alpha-ethinylestradiol, doxycycline, oxytetracycline, demeclocycline, chlortetracycline, cefuroxime, cyclophosphamide, and ifosfamide were below the limit of detection in all of the sewage samples collected within this study. Two different types of diurnal variation pattern were identified in the influent mass loads of selected antibiotics and hormones that effectively correlate with daily drug administration patterns and with the expected maximum human hormone release, respectively. The occurrence of natural hormones and antimicrobials, administered every 12 hours, shows a daily trend of decreasing contaminant mass load, having the maximum values in the morning hours. The occurrence of antibiotics, typically administered every 8 hours, indicates a daily peak value in samples collected under the highest hydraulic loading. The efficiency of biological removal of both hormones and antibiotics is shown to be limited. Compared to the values obtained in the influent samples, increased concentrations are observed in the biologically treated effluent for trimethoprim, sulfamethoxazole and ciprofloxacin, mainly as a result of deconjugation processes. Ciprofloxacin is shown as the predominant antimicrobial compound in the effluent, and it is present at quantities approximately 10 fold greater than the total mass of the other of the compounds due to poor removal efficiency and alternating solid-liquid partitioning behaviour. Our results suggest that, to increase the micro-pollutant removal and the chemical dosing efficiency in enhanced tertiary treatment, significant benefits can be derived from the optimisation of reactor design and the development of control schemes that accounts for diurnal secondary effluent micro-pollutant and hydraulic loading patterns.