Benedek G. Plósz

Impacts of Competitive Inhibition, Parent Compound Formation and Partitioning Behavior on the Removal of Antibiotics in Municipal Wastewater Treatment

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

Diurnal variations in the occurrence and the fate of hormones and antibiotics in activated sludge wastewater treatment in Oslo, Norway

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.

Factors influencing deterioration of denitrification by oxygen entering an anoxic reactor through the surface.

The purpose of the paper is to examine the factors that influence the deterioration of denitrification in open anoxic reactors. For this investigation an ASM 1-based simulation model was developed and successfully applied to fit data from batch experiments carried out in lab-scale reactor vessels (uncovered and covered) using both clarified domestic wastewater and synthetic wastewater. Applying the verified model, simulation studies were performed to investigate the effects of available denitrifiable substrate, biomass concentration, oxygen transfer rate, and temperature on deterioration of denitrification in open anoxic reactors. It has been shown that oxygen entering an anoxic reactor through the surface may not just affect denitrification metabolically, but also kinetically, due to increased dissolved oxygen (DO) concentration exerting an inhibitory effect on the denitrification rate. When the exogenous substrate concentration in the reactor vessel is high enough for a high consumption rate, the DO concentration is kept low. The higher the biomass concentration, and thereby the consumption rate of endogenous substrate, the lower the DO concentration during the low-rate denitrification phase. At low substrate removal rates, decreasing temperature will cause the DO concentration in anoxic vessels to increase. The results suggest that assuring removal of available exogenous carbon source at high rate by staging of open anoxic bioreactors may significantly improve denitrification efficiency.

An activated sludge modeling framework for xenobiotic trace chemicals (ASM-X): Assessment of diclofenac and carbamazepine†

Conventional models for predicting the fate of xenobiotic organic trace chemicals, identified, and calibrated using data obtained in batch experiments spiked with reference substances, can be limited in predicting xenobiotic removal in wastewater treatment plants (WWTPs). At stake is the level of model complexity required to adequately describe a general theory of xenobiotic removal in WWTPs. In this article, we assess the factors that influence the removal of diclofenac and carbamazepine in activated sludge, and evaluate the complexity required for the model to effectively predict their removal. The results are generalized to previously published cases. Batch experimental results, obtained under anoxic and aerobic conditions, were used to identify extensions to, and to estimate parameter values of the activated sludge modeling framework for Xenobiotic trace chemicals (ASM‐X). Measurement and simulation results obtained in the batch experiments, spiked with the diclofenac and carbamazepine content of preclarified municipal wastewater shows comparably high biotransformation rates in the presence of growth substrates. Forward dynamic simulations were performed using full‐scale data obtained from Bekkelaget WWTP (Oslo, Norway) to evaluate the model and to estimate the level of re‐transformable xenobiotics present in the influent. The results obtained in this study demonstrate that xenobiotic loading conditions can significantly influence the removal capacity of WWTPs. We show that the trace chemical retransformation in upstream sewer pipes can introduce considerable error in assessing the removal efficiency of a WWTP, based only on parent compound concentration measurements. The combination of our data with those from the literature shows that solids retention time (SRT) can enhance the biotransformation of diclofenac, which was not the case for carbamazepine. Model approximation of the xenobiotic concentration, detected in the solid phase, suggest that between approximately 1% and 16% of the total solid carbamazepine and diclofenac concentrations, respectively, is due to sorption—the remainder being non‐bioavailable and sequestered. We demonstrate the effectiveness of the models predictive power over conventional tools in a statistical analysis, performed at four levels of structural complexity. To assess WWTP retrofitting needs to remove xenobiotic trace chemicals, we suggest using mechanistic models, e.g., ASM‐X, in regional risk assessments. For preliminary evaluations, we present operating charts that can be used to estimate average xenobiotic removal rates in WWTPs as a function of SRT and the xenobiotics mass loads normalised to design treatment capacity. Biotechnol. Bioeng. 2012; 109: 2757–2769.

Biotransformation kinetics and sorption of cocaine and its metabolites and the factors influencing their estimation in wastewater

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.

Microplate-based method for high-throughput screening of microalgae growth potential

Microalgae cultivation conditions in microplates will differ from large-scale photobioreactors in crucial parameters such as light profile, mixing and gas transfer. Hence volumetric productivity (P(v)) measurements made in microplates cannot be directly scaled up. Here we demonstrate that it is possible to use microplates to measure characteristic exponential growth rates and determine the specific growth rate light intensity dependency (μ-I curve), which is useful as the key input for several models that predict P(v). Nannochloropsis salina and Chlorella sorokiniana specific growth rates were measured by repeated batch culture in microplates supplied with continuous light at different intensities. Exponential growth unlimited by gas transfer or self-shading was observable for a period of several days using fluorescence, which is an order of magnitude more sensitive than optical density. The microplate datasets were comparable to similar datasets obtained in photobioreactors and were used an input for the Huesemann model to accurately predict P(v).

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.

Comparison of pharmaceutical, illicit drug, alcohol, nicotine and caffeine levels in wastewater with sale, seizure and consumption data for 8 European cities

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

Factors influencing sorption of ciprofloxacin onto activated sludge: Experimental assessment and modelling implications

Many of the pharmaceuticals and personal care products occurring in municipal sewage are ionizing substances, and their partitioning behaviour is affected by ionic interactions with solid matrices. In activated sludge systems, such interactions have currently not been adequately understood and described, particularly for zwitterionic chemicals. Here we present an assessment of the effects of pH and iron salt dosing on the sorption of ciprofloxacin onto activated sludge using laboratory experiments and full-scale fate modelling. Experimental results were described with Freundlich isotherms and showed that non-linear sorption occurred under all the conditions tested. The greatest sorption potential was measured at pH=7.4, at which ciprofloxacin is speciated mostly as zwitterion. Iron salt dosing increased sorption under aerobic and, to a lesser extent, anoxic conditions, whereas no effect was registered under anaerobic conditions. The activated sludge model for xenobiotics (ASM-X) was extended with Freundlich-based sorption kinetics and used to predict the fate of ciprofloxacin in a wastewater treatment plant (WWTP). Scenario simulations, using experimental Freundlich parameters, were used to identify whether the assessed factors caused a significant increase of aqueous ciprofloxacin concentration in full-scale bioreactors. Simulation results suggest that a pH increase, rather than a reduction in iron salt dosing, could be responsible for a systematic deterioration of sorption of ciprofloxacin in the WWTP.

A new settling velocity model to describe secondary sedimentation

Secondary settling tanks (SSTs) are the most hydraulically sensitive unit operations in biological wastewater treatment plants. The maximum permissible inflow to the plant depends on the efficiency of SSTs in separating and thickening the activated sludge. The flow conditions and solids distribution in SSTs can be predicted using computational fluid dynamics (CFD) tools. Despite extensive studies on the compression settling behaviour of activated sludge and the development of advanced settling velocity models for use in SST simulations, these models are not often used, due to the challenges associated with their calibration. In this study, we developed a new settling velocity model, including hindered, transient and compression settling, and showed that it can be calibrated to data from a simple, novel settling column experimental set-up using the Bayesian optimization method DREAM(ZS). In addition, correlations between the Herschel-Bulkley rheological model parameters and sludge concentration were identified with data from batch rheological experiments. A 2-D axisymmetric CFD model of a circular SST containing the new settling velocity and rheological model was validated with full-scale measurements. Finally, it was shown that the representation of compression settling in the CFD model can significantly influence the prediction of sludge distribution in the SSTs under dry- and wet-weather flow conditions.