A full-scale operational digital twin for a water resource recovery facility-A case study of Eindhoven Water Resource Recovery Facility.

Digital transformation for the water sector has gained momentum in recent years, and many water resource recovery facilities modelers have already started transitioning from developing traditional models to digital twin (DT) applications. DTs simulate the operation of treatment plants in near real time and provide a powerful tool to the operators and process engineers for real-time scenario analysis and calamity mitigation, online process optimization, predictive maintenance, model-based control, and so forth. So far, only a few mature examples of full-scale DT implementations can be found in the literature, which only address some of the key requirements of a DT. This paper presents the development of a full-scale operational DT for the Eindhoven water resource recovery facility in The Netherlands, which includes a fully automated data-pipeline combined with a detailed mechanistic full-plant process model and a user interface co-created with the plant's operators. The automated data preprocessing pipeline provides continuous access to validated data, an influent generator provides dynamic predictions of influent composition data and allows forecasting 48 h into the future, and an advanced compartmental model of the aeration and anoxic bioreactors ensures high predictive power. The DT runs near real-time simulations every 2 h. Visualization and interaction with the DT is facilitated by the cloud-based TwinPlant technology, which was developed in close interaction with the plant's operators. A set of predefined handles are made available, allowing users to simulate hypothetical scenarios such as process and equipment failures and changes in controller settings. The combination of the advanced data pipeline and process model development used in the Eindhoven DT and the active involvement of the operators/process engineers/managers in the development process makes the twin a valuable asset for decision making with long-term reliability. PRACTITIONER POINTS: A full-scale digital twin (DT) has been developed for the Eindhoven WRRF. The Eindhoven DT includes an automated continuous data preprocessing and reconciliation pipeline. A full-plant mechanistic compartmental process model of the plant has been developed based on hydrodynamic studies. The interactive user interface of the Eindhoven DT allows operators to perform what-if scenarios on various operational settings and process inputs. Plant operators were actively involved in the DT development process to make a reliable and relevant tool with the expected added value.

Assessing the Biodegradability of Tire Tread Particles and Influencing Factors.

Abrasion of tire tread, caused by friction between vehicle tires and road surfaces, causes release of tire wear particles (TWPs) into various environmental compartments. These TWPs contribute to chemical, microplastic, and particulate matter pollution. Their fate remains largely unknown, especially regarding the extent and form in which they persist in the environment. The present study investigated (1) the biodegradability of tread particles (TPs) in the form of ground tire tread, (2) how accelerated ultraviolet (UV) weathering affects their biodegradability, and (3) which TP constituents are likely contributors to TP biodegradability based on their individual biodegradability. A series of closed-bottle tests, with aerobic aqueous medium inoculated with activated sludge, were carried out for pristine TPs, UV-weathered TPs, and selected TP constituents; natural rubber (NR), isoprene rubber (IR), butadiene rubber (BR), and treated distillate aromatic extracts (TDAE). Biodegradation was monitored by manometric respirometry, quantifying biological oxygen consumption over 28 days. Pristine TP biodegradability was found to be 4.5%; UV-weathered TPs showed higher biodegradability of 6.7% and 8.0% with similar and increased inoculum concentrations, respectively. The observed TP biodegradation was mainly attributed to biodegradation of NR and TDAE, with individual biodegradability of 35.4% and 8.0%, respectively; IR and BR showed negligible biodegradability. These findings indicate that biodegradability of individual constituents is decreased by a factor of 2 to 5 when compounded into TPs. Through scanning electron microscopy analysis, biodegradation was found to cause surface erosion. Processes of TP biodegradation are expected to change throughout their lifetime as new constituents are incorporated from the road and others degrade and/or leach out. Tire emissions likely persist as particles with an increased fraction of synthetic rubbers and carbon black. Environ Toxicol Chem 2024;43:31-41. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Modelling and prediction of the effect of operational parameters on the fate of contaminants of emerging concern in WWTPs.

Wastewater treatment plants (WWTPs) provide a barrier against the discharge of contaminants of emerging concern (CECs) into the environment. The removal of CECs is highly WWTP-specific and the underlying mechanisms are still poorly understood, hampering the optimization of biological treatment steps for their removal. To fill this knowledge gap, we assessed the influence of four operational parameters of activated sludge biological treatment, namely total suspended solids, temperature, pH and redox conditions, on the sorption and biodegradation of four CECs under controlled laboratory conditions. Design of Experiments was used to better address the factors influencing CECs removal and interactions among operational parameters. The derived statistical models showed results in concordance with previous studies and indicated how sorption and biodegradation of the investigated CECs depend on most tested parameters and few of their interactions. The predictions of the developed models have been compared with literature values, indicating how the tested parameters are responsible for most of the variability of sorption, while they could not reliably generalize biodegradation rates. The developed models were also implemented as an extension of a mechanistic biological treatment model, successfully describing the dynamic behaviour of a large-scale WWTP, which was observed during a three-day continuous monitoring campaign. Compared to a traditional modelling approach, the one including the developed models showed on average almost a three-fold uncertainty reduction, favouring its use to aid WWTP managers and regulators for improved assessment of CEC fate and removal. Finally, the models highlighted that, while higher temperatures and solids concentrations generically favoured CECs removal, removal efficiency vary significantly due to operational parameters and no globally optimum conditions for CECs removal exist. The use of these models opens the door to the combined dynamic management of both traditional contaminants and CECs in WWTPs.

Modelling the fate of micropollutants in integrated urban wastewater systems: Extending the applicability to pharmaceuticals.

Pharmaceutical active compounds (PhACs) are a category of micropollutants frequently detected across integrated urban wastewater systems. Existing modelling tools supporting the evaluation of micropollutant fate in such complex systems, such as the IUWS_MP model library (which acronym IUWS stands for Integrated Urban Wastewater System), do not consider fate processes and fractions that are typical for PhACs. This limitation was overcome by extending the existing IUWS_MP model library with new fractions (conjugated metabolites, sequestrated fraction) and processes (consumption-excretion, deconjugation). The performance of the extended library was evaluated for five PhACs (carbamazepine, ibuprofen, diclofenac, paracetamol, furosemide) in two different integrated urban wastewater systems where measurements were available. Despite data uncertainty and the simplicity of the modelling approach, chosen to minimize data requirements, model prediction uncertainty overlapped with the measurements ranges across both systems, stressing the robustness of the proposed modelling approach. Possible applications of the extended IUWS_MP model library are presented, illustrating how this tool can support urban water managers in reducing environmental impacts from PhACs discharges.

Monitoring and modelling of influent patterns, phase distribution and removal of 20 elements in two primary wastewater treatment plants in Norway.

Many small- or medium-sized communities in Northern Europe employ only primary wastewater treatment plants (WWTPs) and effluent discharges can be a relevant source of pollution. The current study combines monitoring and modelling approaches to investigate concentrations, influent patterns, size distribution and removal of 20 elements for the two primary WWTPs (Ladehammeren, LARA; Høvringen, HØRA) serving Trondheim, the third largest city in Norway. Element concentrations were determined in raw influent wastewater, effluents and biosolids, and diurnal inflow patterns were assessed. The elemental distribution in particulate, colloidal and dissolved fractions of untreated wastewater was characterized using filtration separation and electron microscopy. An influent generator model and multivariate statistical analyses were used to determine release patterns and to predict the (co-)occurrence of selected elements. Raw influent wastewater concentrations for most elements were similar in the two WWTPs, with only Ca, Mn, Fe, Co and Ba being significantly higher (p < 0.05) in HØRA (which receives more household and hospital discharges). Removal efficiencies varied between elements, but in most cases reflected their association with particulates. Nanosized particles of several elements were detected, with Cu/Zn being most common. Measured concentrations of most elements followed typical diurnal wastewater discharge patterns and enrichment factors calculated for biosolids confirmed the importance of anthropogenic sources for P, Cu, Zn, Cd, As, Cr, Ni, Pb, V, Co and Fe. Elemental concentrations generally correlated well with total suspended solid (TSS) concentrations at HØRA, while this was less pronounced in LARA (possibly due to higher industrial contributions). In one of its first applications for WWTP influent pattern examination, principal component analysis was found to be instrumental for source identification of target elements, showing significant differences between LARA and HØRA influents. The combined experimental, statistical and modelling approaches used herein allowed for improved understanding of element sources, patterns of discharge and fate in primary WWTPs.

Model-based analysis of the uptake of perfluoroalkyl acids (PFAAs) from soil into plants.

Perfluoroalkyl acids (PFAAs) bioaccumulate in crops, with uptake being particularly high for short-chain PFAAs that are constantly transported with transpiration water to aerial plant parts. Due to their amphiphilic surfactant nature and ionized state at environmental pH, predicting the partitioning behavior of PFAAs is difficult and subject to considerable uncertainty, making experimental data highly desirable. Here, we applied a plant uptake model that combines advective flux with measured partition coefficients to reproduce the set of empirically derived plant uptake and soil-partitioning data for nine PFAAs in red chicory, in order to improve the mechanistic understanding and provide new insights into the complex uptake processes. We introduced a new parameter for retarded uptake (R) to explain the slow transfer of PFAA across biomembranes of the root epidermis, which has led to low transpiration stream concentration factors (TSCFs) presented in literature so far. We estimated R values for PFAAs using experimental data derived for red chicory and used the modified plant uptake model to simulate uptake of PFAA into other crops. Results show that this semi-empirical model predicted PFAAs transport to shoots and fruits with good accuracy based on experimental root to soil concentration factors (RCFdw) and soil to water partition coefficients (Kd) as well as estimated R values and plant-specific data for growth and transpiration. It can be concluded that the combination of rather low Kd with high RCFdw and the absence of any relevant loss are the reason for the observed excellent plant uptake of PFAAs.

Risk assessment of contaminants of emerging concern in the context of wastewater reuse for irrigation: An integrated modelling approach.

Direct reuse of reclaimed wastewater (RWW) in agriculture has recently received increasing attention as a possible solution to water scarcity. The presence of contaminants of emerging concern (CECs) in RWW can be critical, as these chemicals can be uptaken in irrigated crops and eventually ingested during food consumption. In the present study, an integrated model was developed to predict the fate of CECs in water reuse systems where RWW is used for edible crops irrigation. The model was applied to a case study where RWW (originating from a municipal wastewater treatment plant) is discharged into a water channel, with subsequent irrigation of silage maize, rice, wheat and ryegrass. Environmental and human health risks were assessed for 13 CECs, selected based on their chemical and hazard characteristics. Predicted CEC concentrations in the channel showed good agreement with available measurements, indicating potential ecotoxicity of some CECs (estrogens and biocides) due to their limited attenuation. Plant uptake predictions were in good agreement with existing literature data, indicating higher uptake in leaves and roots than fruits. Notably, high uncertainties were shown for weakly acidic CECs, possibly due to degradation in soil and pH variations inside plants. The human health risk due to the ingestion of wheat and rice was assessed using the threshold of toxicological concern and the hazard quotient. Both approaches predicted negligible risk for most CECs, while sulfamethoxazole and 17α-ethinylestradiol exhibited the highest risk for consumers. Alternative scenarios were evaluated to identify possible risk minimization strategies (e.g., adoption of a more efficient irrigation system).

Modelling micropollutant fate in sewer systems - A new systematic approach to support conceptual model construction based on in-sewer hydraulic retention time.

Conceptual sewer models are useful tools to assess the fate of micropollutants (MPs) in integrated wastewater systems. However, the definition of their model structure is highly subjective, and obtaining a realistic simulation of the in-sewer hydraulic retention time (HRT) is a major challenge without detailed hydrodynamic information or with limited measurements from the sewer network. This study presents an objective approach for defining the structure of conceptual sewer models in view of modelling MP fate in large urban catchments. The proposed approach relies on GIS-based information and a Gaussian mixture model to identify the model optimal structure, providing a multi-catchment conceptual model that accounts for HRT variability across urban catchment. This approach was tested in a catchment located in a highly urbanized Italian city and it was compared against a traditional single-catchment conceptual model (using a single average HRT) for the fate assessment of reactive MPs. Results showed that the multi-catchment model allows for a successful simulation of dry weather flow patterns and for an improved simulation of MP fate compared to the classical single-catchment model. Specifically, results suggested that a multi-catchment model should be preferred for (i) degradable MPs with half-life lower than the average HRT of the catchment and (ii) MPs undergoing formation from other compounds (e.g. human metabolites); or (iii) assessing MP loads entering the wastewater treatment plant from point sources, depending on their location in the catchment. Overall, the proposed approach is expected to ease the building of conceptual sewer models, allowing to properly account for HRT distribution and consequently improving MP fate estimation.

Microbial Turnover of Glyphosate to Biomass: Utilization as Nutrient Source and Formation of AMPA and Biogenic NER in an OECD 308 Test.

Environmental fate assessment of chemicals involves standardized simulation tests with isotope-labeled molecules to balance transformation, mineralization, and formation of nonextractable residues (NER). Methods to predict microbial turnover and biogenic NER have been developed, having limited use when metabolites accumulate, the chemicals are not the only C source, or provide for other macroelements. To improve predictive capability, we extended a recently developed method for microbial growth yield estimation to account for incomplete degradation and multiple-element assimilation and combined it with a dynamic model for fate description in soils and sediments. We evaluated the results against the unique experimental data of 13C3-15N co-labeled glyphosate turnover with AMPA formation in water-sediment systems (OECD 308). Balancing 13C- and 15N- fluxes to biomass showed a pronounced shift of glyphosate transformation from full mineralization to AMPA formation. This may be explained by various hypotheses, for example, the limited substrate turnover inherent to the batch conditions of the test system causing microbial starvation or inhibition by P release. Modeling results indicate initial N overload due to the lower C/N ratio in glyphosate compared to average cell composition leading to subsequent C demand and accumulation of AMPA.

Predicting the uptake of emerging organic contaminants in vegetables irrigated with treated wastewater - Implications for food safety assessment.

Emerging organic contaminants (EOCs) undergoing incomplete removal during wastewater treatment may be found in treated wastewater (TWW) used for irrigation of agricultural products. Following uptake into edible plant parts, EOCs may eventually enter in the food chain, with associated human exposure. In the present study, we used a newly developed steady-state plant uptake model with added phloem transport to predict the uptake of four EOCs (carbamazepine, ibuprofen, ketoprofen and naproxen) into three varieties of lettuce. Input data were derived from an experimental study with vegetables grown in greenhouse and irrigated with TWW spiked with CBZ at 0, 30, 60, 120 and 210 µg/L in each variety of lettuce. Predicted carbamazepine concentrations in leaves were on average 82% higher than in roots, with good agreement between measured and calculated data. We subsequently predicted the uptake of anti-inflammatory compounds ibuprofen, ketoprofen and naproxen, for which the chemical analysis could not provide concentrations above detection limit. These three substances are weak acids and predicted concentrations in roots were higher than in the edible leaves, mainly due to phloem transport downwards. The daily dietary intake of all four EOCs was estimated for consumption of leafy vegetables, being far below usual therapeutic doses.

Occurrence, characterisation and fate of (nano)particulate Ti and Ag in two Norwegian wastewater treatment plants.

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 (<0.15-2.1 µg L-1), being mostly associated with suspended solids (>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.

Reactor staging influences microbial community composition and diversity of denitrifying MBBRs- Implications on pharmaceutical removal.

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.

The impact of temperature on the transformation of illicit drug biomarkers in wastewater.

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.

A systematic model identification method for chemical transformation pathways - the case of heroin biomarkers in wastewater.

This study presents a novel statistical approach for identifying sequenced chemical transformation pathways in combination with reaction kinetics models. The proposed method relies on sound uncertainty propagation by considering parameter ranges and associated probability distribution obtained at any given transformation pathway levels as priors for parameter estimation at any subsequent transformation levels. The method was applied to calibrate a model predicting the transformation in untreated wastewater of six biomarkers, excreted following human metabolism of heroin and codeine. The method developed was compared to parameter estimation methods commonly encountered in literature (i.e., estimation of all parameters at the same time and parameter estimation with fix values for upstream parameters) by assessing the model prediction accuracy, parameter identifiability and uncertainty analysis. Results obtained suggest that the method developed has the potential to outperform conventional approaches in terms of prediction accuracy, transformation pathway identification and parameter identifiability. This method can be used in conjunction with optimal experimental designs to effectively identify model structures and parameters. This method can also offer a platform to promote a closer interaction between analytical chemists and modellers to identify models for biochemical transformation pathways, being a prominent example for the emerging field of wastewater-based epidemiology.

Transformation and Sorption of Illicit Drug Biomarkers in Sewer Biofilms.

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.

Removal of pharmaceuticals in pre-denitrifying MBBR - Influence of organic substrate availability in single- and three-stage configurations.

Due to the limited efficiency of conventional biological treatment, innovative solutions are being explored to improve the removal of trace organic chemicals in wastewater. Controlling biomass exposure to growth substrate represents an appealing option for process optimization, as substrate availability likely impacts microbial activity, hence organic trace chemical removal. This study investigated the elimination of pharmaceuticals in pre-denitrifying moving bed biofilm reactors (MBBRs), where biofilm exposure to different organic substrate loading and composition was controlled by reactor staging. A three-stage MBBR and a single-stage reference MBBR (with the same operating volume and filling ratio) were operated under continuous-flow conditions (18 months). Two sets of batch experiments (day 100 and 471) were performed to quantify and compare pharmaceutical removal and denitrification kinetics in the different MBBRs. Experimental results revealed the possible influence of retransformation (e.g., from conjugated metabolites) and enantioselectivity on the removal of selected pharmaceuticals. In the second set of experiments, specific trends in denitrification and biotransformation kinetics were observed, with highest and lowest rates/rate constants in the first (S1) and the last (S3) staged sub-reactors, respectively. These observations were confirmed by removal efficiency data obtained during continuous-flow operation, with limited removal (<10%) of recalcitrant pharmaceuticals and highest removal in S1 within the three-stage MBBR. Notably, biotransformation rate constants obtained for non-recalcitrant pharmaceuticals correlated with mean specific denitrification rates, maximum specific growth rates and observed growth yield values. Overall, these findings suggest that: (i) the long-term exposure to tiered substrate accessibility in the three-stage configuration shaped the denitrification and biotransformation capacity of biofilms, with significant reduction under substrate limitation; (ii) biotransformation of pharmaceuticals may have occurred as a result of cometabolism by heterotrophic denitrifying bacteria.

Diffusion and sorption of organic micropollutants in biofilms with varying thicknesses.

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 â‰ª 0.1) by the high biomass density (reduced porosity).

Impact of external carbon dose on the removal of micropollutants using methanol and ethanol in post-denitrifying Moving Bed Biofilm Reactors.

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.

Transformation and Sorption of Illicit Drug Biomarkers in Sewer Systems: Understanding the Role of Suspended Solids in Raw Wastewater.

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.

Biofilm Thickness Influences Biodiversity in Nitrifying MBBRs-Implications on Micropollutant Removal.

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.