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To find a possible trade-off between effluent quality, sludge production, energy consumption and GHG emissions, this study monitored the carbon and nutrient removal and greenhouse gas (GHG) emissions in a membrane bioreactor (MBR) pilot plant with intermittent aeration (IA). The pilot plant was operated by alternating aerobic and anoxic conditions inside the biological reactor. Up to 98.2 % of carbon and 76.4 % of nitrogen were respectively remove through this MBR pilot plant with IA. The carbon footprint was equal to 2.4 kgCO 2eq m−3. Indirect emissions contributed the most to the carbon footprint (55.3 %), mainly due to energy consumption, despite the alterations in aeration during the pilot plant operation. The result of this study provides theoretical guidance for building the wastewater treatment plant in a sustainable way. [Display omitted] • MBR pilot plant aimed at carbon and nitrogen removal was monitored. • The pilot plant was operated under intermittent aeration conditions. • Excellent pollutants removal and low greenhouse gas production were obtained. • Sewage sludge production was in line with other MBR plants. • Carbon footprint was mainly debited to the energy consumption. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • A comprehensive protocol for polyhydroxyalkanoates extraction is presented. • Purification post-treatment was performed. • The highest recovery yield (73%) was obtained when using NH 4 -Laurate. • The molecular weights of both biopolymers were low. Abstract A new protocol for polyhydroxyalkanoates (PHA) extraction from mixed microbial cultures (MMCs) is proposed. PHA-accumulating capacity of the MMC was selected in a sequencing batch reactor (SBR) fed with a synthetic effluent emulating a fermented oil mill wastewater (OMW). The highest recovery yield and purity (74 ± 8% and 100 ± 5%, respectively) was obtained when using NH 4 -Laurate for which operating conditions of the extraction process such as temperature, concentration and contact time were optimized. Best conditions for PHA extraction from MMC turned to be: i) a pre-treatment with NaClO at 85 °C with 1 h of contact time, followed by ii) a treatment with lauric acid in a ratio acid lauric to biomass of 2:1 and 3 h of contact time. [ABSTRACT FROM AUTHOR]

Abstract A new model for accounting carbon and energy footprint of wastewater treatment plants (WWTPs) is proposed. The model quantifies direct and indirect greenhouse gas (GHG) emissions related to biological and physical processes of a WWTP. The model takes into account several innovative aspects with respect to already available literature models: i. kinetic/mass-balances; ii. nitrification as a two-step process; iii. nitrous oxide (N 2 O) formation during nitrification and denitrification both in dissolved and off-gas forms. A full-scale application has been performed by adopting the case study of a real WWTP. A scenario analysis was performed to quantify the influence of: composition of inflow wastewater (scenario 1), operating conditions (scenario 2), and oxygen transfer efficiency (scenario 3). Results have underlined the key role of the ratio between influent biodegradable carbon and nitrogen concentration on influencing direct and indirect GHG emissions. Direct GHG emissions increase from 0.49 to 0.63 kgCO 2 eq m−3 with the decrease of the influent ratio of the readily biodegradable carbon and organic and ammonia nitrogen. The increase of the influent organic and ammonia nitrogen favours the daily production of active ammonia oxidization biomass. The simultaneous variation of the investigated factors has amplified direct and indirect GHG emissions to a maximum value of 0.94 and 0.24 kgCO 2eq m−3, respectively. Graphical abstract Image 10216 Highlights • A new plant-wide model including greenhouse gases is presented. • Mechanisms of nitrification and denitrification are simulated in a comprehensive way. • The new model is applied to a real case study. • Several scenarios are detected to envisage model features. • The model is a promising tool for design and manage wastewater treatment plant. [ABSTRACT FROM AUTHOR]

Abstract Stricter effluent limits, water shortage conditions, land availability requires today even more the needs of advanced wastewater treatments. Attractive solutions come from membrane bioreactors (MBR), Integrated Fixed Film Activated Sludge (IFAS) or combinations (i.e., IFAS-MBRs). One crucial aspect for the applicability of this overall new technology, compared to the conventional activated sludge systems, is the lack of knowledge for design and manage (e.g., kinetic constants, optimal operative conditions etc.). In view of the above frame, the aim of the present study was to assess the kinetic and stoichiometric parameters of bacterial species in MBRs by means of respirometric techniques. Plant configurations, operational conditions and wastewater features (domestic/industrial) were analysed. Four different MBR plants were investigated: i) sequencing batch MBR subjected to a gradual salinity increase; ii) pre-denitrification MBR treating saline wastewater contaminated by hydrocarbons; iii) University of Cape Town (UCT) MBR treating domestic wastewater subjected to a carbon-to-nitrogen (C/N) ratio variation; iiii) UCT- IFAS -MBR treating domestic wastewater. Results show a significant influence on biomass respiratory activity from both plant configurations and operational conditions. The salinity increase severely affected the activity of autotrophic species, while heterotrophic community was mainly influenced by the C/N variation. Moreover, it was observed a specialization in the IFAS-MBR configuration, with the suspended biomass more affine to organic matter, whilst biofilm in the nitrification process. The respirometric analysis confirmed to be an effective tool for the evaluation of the biomass kinetic and stoichiometric parameters. The results of this study can be useful for the application of mathematical models in the design phase and for the monitoring of biomass viability during plant operations. Graphical abstract Image 1 Highlights • The study aim was to provide new insights on biokinetic behaviour of MBRs. • Respirometry was used to assess the kinetic and stoichiometric coefficients. • Heterotrophs highly suffered low C/N ratio with increased membrane fouling. • Salinity highly affected the autotrophic activity increasing the pore blocking. • It was observed a specialization of suspended and attached biomass in the IFAS-MBR. [ABSTRACT FROM AUTHOR]

An integrated membrane bioreactor (MBR) model was previously proposed and tested. The model provides a comprehensive and detailed description of the nitrogen biological removal processes with respect to up-to-date literature. This paper presents a sensitivity and uncertainty analysis aimed at identifying the key factors affecting the variability of the model predictions. The Standardized Regression Coefficients (SRC) method was adopted for the sensitivity analysis. The uncertainty analysis was employed by running Monte Carlo simulations by varying only the value of the key factors affecting the model outputs. The sensitivity analysis combined with the uncertainty analysis applied here enabled to gain useful insights about the robustness of the model. By means of the SRC method 45 model factors (of 122) were selected as important. The results obtained here allowed to investigate the advantage of a detailed description of the nitrogen transformation bioprocesses (nitrification/denitrification) in terms of model accuracy and uncertainty bandwidth. The model allows to simulate the intermediate product during nitrification/denitrification, thus providing the possibility to control the nitrogen compounds that favour the formation of nitrous oxide. [ABSTRACT FROM AUTHOR]

This study aimed at evaluating the nitrous oxide (N2O) emissions from membrane bioreactors (MBRs) for wastewater treatment. The study investigated the N2O emissions considering multiple influential factors over a two-year period: (i) different MBR based process configurations; (ii) wastewater composition (municipal or industrial); (iii) operational conditions (i.e. sludge retention time, carbon-to-nitrogen ratio, C/N, hydraulic retention time); (iv) membrane modules. Among the overall analysed configurations, the highest N2O emission occurred from the aerated reactors. The treatment of industrial wastewater, contaminated with salt and hydrocarbons, provided the highest N2O emission factor (EF): 16% of the influent nitrogen for the denitrification/nitrification-MBR plant. The lowest N2O emission (EF = 0.5% of the influent nitrogen) was obtained in the biological phosphorus removal-moving bed-MBR plant likely due to an improvement in biological performances exerted by the co-presence of both suspended and attached biomass. The influent C/N ratio has been identified as a key factor affecting the N2O production. Indeed, a decrease of the C/N ratio (from 10 to 2) promoted the increase of N2O emissions in both gaseous and dissolved phases, mainly related to a decreased efficiency of the denitrification processes. [ABSTRACT FROM AUTHOR]

In this study a University of Cape Town (UCT) Integrated Fixed Film Activated Sludge (IFAS) Membrane BioReactor (MBR) wastewater treatment plant was monitored in terms of nitrous oxide (N 2 O) emissions. The short term effect on the N 2 O emission due to the influent carbon-to-nitrogen (C/N) ratio variation (C/N ratios of 2, 5 and 10 gCOD/gN) was evaluated. Since in a previous study, the effect of the C/N ratio was studied in the same system without biofilm (UCT-MBR configuration) the main aim here was to investigate the role of biofilms on N 2 O emissions. Under all the investigated C/N ratios, the N 2 O fluxes and the average emission factors were lower than that of previous studies with no biofilm presence. The total average N 2 O emission was 0.5% of the influent nitrogen with biofilm (IFAS system) and 3.5% without biofilm. This result emphasizes the potential role of the biofilms in attenuating the N 2 O emissions especially in the case of stress conditions (i.e., low C/N influent ratios). An increase of N 2 O flux from the anoxic reactor (till 28 mgN 2 O m −2 h −1 ) occurred at the lowest influent C/N tested (2 gCOD/gN - phase III). At C/N equal to 2 gCOD/gN the anoxic reactor was the main source of N 2 O, contributing 45% of all produced N 2 O. This result was attributed to an incomplete denitrification caused by a lack of organic carbon and a slight increase of dissolved oxygen concentration. [ABSTRACT FROM AUTHOR]

A comprehensive integrated membrane bioreactor (MBR) model for wastewater treatment is here proposed. The model quantifies the main biological and physical processes. The model describes the biological removal of organic matter, nitrogen and phosphorus including greenhouse gases (carbon dioxide, CO 2 and nitrous oxide, N 2 O). The model takes into account the following main innovative aspects jointly: i. Two-step nitrification process; ii. N 2 O formation due to ammonia-oxidizing bacteria as a product of the hydroxylamine oxidation (NH 2 OH) and of the nitrite (NO 2 − ) reduction; iii. Soluble microbial product (SMP) formation/degradation due to microbial growth and endogenous respiration; iv. Interlink between SMP and membrane fouling. The model was calibrated by employing a detailed calibration protocol and data from a University Cape Town (UCT) – MBR pilot plant. The key processes contributing to the N 2 O formation were properly described (total efficiency related to the calibrated model equal to 0.55). Results suggested that the incomplete hydroxylamine oxidation and the heterotrophic denitrification were the predominant processes influencing the N 2 O production. The model was able to describe the membrane fouling as demonstrated by the high efficiency (0.92) for the resistance state variable. This result confirms the importance in the modelling approach of considering both biological and physical processes jointly. [ABSTRACT FROM AUTHOR]

The aim of the present paper was to investigate the effect of solids (SRT) and hydraulic (HRT) retention time on Integrated Fixed Film Activated Sludge (IFAS) University of Cape Town (UCT) membrane Bioreactor (MBR). In particular, three different pairs of SRT and HRT values were analysed, namely, Phase I 56 d/30 h, Phase II 31 d/15 h and Phase III 7 d/13 h. The short-term effect of these three SRT/HRT conditions was assessed by analysing several system performance indicators: organic carbon and biological nutrient (nitrogen and phosphorus) removal, biomass respiratory activity, activated sludge filtration properties and membrane fouling. The results showed that the decrease of SRT/HRT had a positive influence on system performance. Specifically, the IFAS-UCT-MBR showed excellent removal of organic matter - highest value (99%) at the shortest SRT/HRT (7 d/13 h). Also, the increase in organic loading rate resulting from the decrease of SRT and HRT led to improved nitrogen removal due to higher N removal by sludge wasting requiring less N removal (as N 2 ) by denitrification. Complete nitrification of influent ammonia was achieved at all three SRT/HRT phases, guaranteed by the presence of biofilm carriers in the aerobic reactor, which ensured a higher media SRT than suspended biomass SRT. The increase of the organic loading rate and decrease in SRT led also to a higher heterotrophic activity as demonstrated by the respirometric batch tests, which is due to the increasing active biomass fraction of the volatile suspended solids as SRT decreases. The SRT/HRT decrease over the three phases resulted in an overall increase of the Extracellular Polymeric Substance concentration, which caused an increase in membrane fouling. [ABSTRACT FROM AUTHOR]

The paper presents the sensitivity and uncertainty analysis of an integrated urban drainage model which includes micropollutants. Specifically, a bespoke integrated model developed in previous studies has been modified in order to include the micropollutant assessment (namely, sulfamethoxazole – SMX). The model takes into account also the interactions between the three components of the system: sewer system (SS), wastewater treatment plant (WWTP) and receiving water body (RWB). The analysis has been applied to an experimental catchment nearby Palermo (Italy): the Nocella catchment. Overall, five scenarios, each characterized by different uncertainty combinations of sub-systems (i.e., SS, WWTP and RWB), have been considered applying, for the sensitivity analysis, the Extended-FAST method in order to select the key factors affecting the RWB quality and to design a reliable/useful experimental campaign. Results have demonstrated that sensitivity analysis is a powerful tool for increasing operator confidence in the modelling results. The approach adopted here can be used for blocking some non-identifiable factors, thus wisely modifying the structure of the model and reducing the related uncertainty. The model factors related to the SS have been found to be the most relevant factors affecting the SMX modeling in the RWB when all model factors (scenario 1) or model factors of SS (scenarios 2 and 3) are varied. If the only factors related to the WWTP are changed (scenarios 4 and 5), the SMX concentration in the RWB is mainly influenced (till to 95% influence of the total variance for S SMX,max ) by the aerobic sorption coefficient. A progressive uncertainty reduction from the upstream to downstream was found for the soluble fraction of SMX in the RWB. [ABSTRACT FROM AUTHOR]

The present study explores the interlinkages among the operational variables of a University of Cape Town (UCT) Integrated Fixed Film Activated Sludge (IFAS) membrane bioreactor (MBR) pilot plant. Specifically, dedicated experimental tests were carried out with the final aim to find-out a constitutive relationship among operational costs (OCs), effluent quality index (EQI), effluent fines (EF). Greenhouse gas (GHG) emissions were also included in the study. Results showed that the EQI increases at low flow rate likely due to the dissolved oxygen (DO) limitation in the biological processes. Direct GHGs increase with the increasing of the air flow due to the anoxic N 2 O contribution. Irreversible membrane fouling reduce from 98% to 85% at the air flow rate of 0.57 m 3 h −1 and 2.56 m 3 h −1 , respectively. However, the increase of the air flow rate leads to the increase of the N 2 O–N flux emitted from the MBR (from 40% to 80%). [ABSTRACT FROM AUTHOR]

The aim of the present work was to investigate the behavior of a membrane bioreactor (MBR) system for the treatment of oily wastewater. A bench scale MBR was fed with synthetic wastewater containing diesel fuel. Organic carbon, hydrocarbon and ammonium removal, kinetic constants, extracellular polymeric substances production, and membrane fouling rates were monitored. The MBR plant was operated for more than 200 days, and the results highlighted good carbon removal and nitrification, suggesting a sort of biomass adaptation to hydrocarbons. Membrane fouling analysis showed an increase in total resistance, likely due to hydrocarbons, which caused an irreversible fouling (pore blocking) mainly due to oil deposition. [ABSTRACT FROM AUTHOR]

The paper reports the results of nitrous oxide (N 2 O) emissions from aerobic and anoxic tank of a Sequential Batch Membrane Bioreactor (SB-MBR) pilot plant. The influence of salinity variation on N 2 O emission was analyzed by gradually increasing the inlet salt concentration from 0 to 10 g NaCl L −1 . The observed results showed that the N 2 O concentration of the gaseous samples was strongly influenced by the salt concentration. This result was likely related to a worsening of the nitrification activity due to the effect of salinity on autotrophic bacteria. Dissolved oxygen concentration and salinity were found to be the key factors affecting N 2 O concentration in the gaseous samples withdrawn from the anoxic tank. Despite the fact that the N 2 O concentration in the anoxic tank was higher than in the aerobic one, it was found that the aerobic tank emitted around 25 times more N 2 O than the anoxic one. [ABSTRACT FROM AUTHOR]

In this work, a sequential batch membrane bioreactor pilot plant is investigated to analyze the effect of a gradual increase in salinity on carbon and nutrient removal, membrane fouling and biomass kinetic parameters. The salinity was increased by 2 g NaCl L −1 per week up to 10 g NaCl L −1 . The total COD removal efficiency was quite high (93%) throughout the experiment. A gradual biomass acclimation to the salinity level was observed during the experiment, highlighting the good recovery capabilities of the system. Nitrification was also influenced by the increase in salinity, with a slight decrease in nitrification efficiency (the lowest value was obtained at 10 g NaCl L −1 due to lower nitrifier activity). Irreversible cake deposition was the predominant fouling mechanism observed during the experiment. Respirometric tests exhibited a stress effect due to salinity, with a reduction in the respiration rates observed (from 8.85 mgO 2 L −1 h −1 to 4 mgO 2 L −1 h −1 ). [ABSTRACT FROM AUTHOR]

This paper presents the sensitivity and uncertainty analysis of a mathematical model for greenhouse gas emission (GHG) and energy consumption assessment in wastewater treatment plants. A sensitivity analysis was carried out (using two different methods) to determine which model factors have the greatest effect on the predicted values of the GHG production. Further, an uncertainty analysis was carried out to quantify the uncertainty of the key model outputs, such as carbon dioxide production from activated sludge treatment. The results show that influent fractionation factors, which characterize influent composition, have an important role on direct and indirect GHGs production and emission. Moreover, model factors related to the aerobic biomass growth show a relevant influence on GHGs in terms of emission from off-site power generation (mCO2eq;PG). Further, model factors related to the autotrophic biomass growth were found to strongly interact with other factors especially in modeling mCO2eq;PG. Finally, nitrous oxide (N2O) emission associated with the effluent has the highest uncertainty, suggesting the need for a mechanistic model for N2O production in biological treatment. [ABSTRACT FROM AUTHOR]

Nitrous oxide, carbon dioxide and methane are greenhouse gases (GHG) emitted from wastewater treatment that contribute to its carbon footprint. As a result of the increasing awareness of GHG emissions from wastewater treatment plants (WWTPs), new modelling, design, and operational tools have been developed to address and reduce GHG emissions at the plant-wide scale and beyond. This paper reviews the state-of-the-art and the recently developed tools used to understand and manage GHG emissions from WWTPs, and discusses open problems and research gaps. The literature review reveals that knowledge on the processes related to N 2 O formation, especially due to autotrophic biomass, is still incomplete. The literature review shows also that a plant-wide modelling approach that includes GHG is the best option for the understanding how to reduce the carbon footprint of WWTPs. Indeed, several studies have confirmed that a wide vision of the WWPTs has to be considered in order to make them more sustainable as possible. Mechanistic dynamic models were demonstrated as the most comprehensive and reliable tools for GHG assessment. Very few plant-wide GHG modelling studies have been applied to real WWTPs due to the huge difficulties related to data availability and the model complexity. For further improvement in GHG plant-wide modelling and to favour its use at large real scale, knowledge of the mechanisms involved in GHG formation and release, and data acquisition must be enhanced. [ABSTRACT FROM AUTHOR]

The paper reports the main results of an experimental campaign performed on a membrane bioreactor pilot plant designed to treat synthetic shipboard slops. The experimental campaign was divided into two phases: salinity acclimation up to 20 g NaCl L −1 (Phase I) and hydrocarbon (diesel fuel) dosing (Phase II). The observed results show that the carbon removal was not severely affected by the wastewater features. Conversely, respirometric tests showed that nitrification was strongly affected by the salinity (33% of nitrification efficiency at 20 g NaCl L −1 – Phase I) as a result of the salinity in the autotrophic biomass. Moreover, the sludge viscosity increased during Phase II due to the wastewater composition, leading to an increase in the membrane resistance, and severe degradation of the sludge dewaterability was also observed. Indeed, the capillary suction time increased by a factor of 3 times compared with that of Phase I. [ABSTRACT FROM AUTHOR]

A new mathematical model able to quantify greenhouse gas (GHG) emissions in terms of carbon dioxide (CO 2 ) and nitrous oxide (N 2 O) for a Membrane Bioreactor (MBR) is presented. The proposed mathematical model is of the Activated Sludge Model (ASM) family and takes into account simultaneously both biological and physical processes (e.g., membrane fouling). An analysis of the key factors and sources of uncertainty influencing GHG emissions is also presented. Specifically, the standardized regression coefficient, the Extended-FAST and a Monte Carlo based method are employed for assessing model factors which influence three performance indicators: effluent quality index, operational costs and GHGs. Model factors are classified as important, non-influential and interacting. The model is applied to a University Cape Town–MBR pilot plant which was object of an extensive field gathering campaign. The results reveal that model factors related to nitrogen transformation and membrane separation processes play a central role in the uncertainty of GHG estimation. Model factors that are associated with physical processes exhibit large first-order and total-order effects, which emphasises the importance of a holistic approach that jointly considers biological and physical processes. Furthermore, the membrane has a key role in GHG emissions as a result of the cake layer thickness which in turns influences the mass of substrate retained by the membrane and, thus, the biological process in the MBR. The results show that a modeller should not exclude the role of phosphorus in the contribution of accumulating organisms during the prediction of GHGs due to the high interaction of N 2 O. The results reveal that the uncertainty in the emission factors for CO 2 is higher than the uncertainty in the emission factors for N 2 O (namely, 2.2 and 0.17%, respectively). [ABSTRACT FROM AUTHOR]

Abstract: Three global sensitivity analysis (GSA) methods are applied and compared to assess the most relevant processes occurring in wastewater treatment systems. In particular, the Standardised Regression Coefficients, Morris Screening and Extended-FAST methods are applied to a complex integrated membrane bioreactor (MBR) model considering 21 model outputs and 79 model factors. The three methods are applied with numerical settings as suggested in literature. The main objective considered is to classify important factors (factors prioritisation) as well as non-influential factors (factors fixing). The performance is assessed by comparing the most reliable method (Extended-FAST), by means of proposed criteria, with the two other methods. In particular, similarity to results obtained from Extended-FAST is assessed for sensitivity indices, for the ranking of sensitivity indices, for the classification into important/non-influential factors and for the method's ability to detect interaction among factors and to provide results in a reasonable time. It was found that the computationally less expensive SRC method was applied outside its range of applicability (R 2) = (0.3–0.6) < 0.7. Still, the SRC produced a ranking of important factors similar to Extended-FAST. For some variables significant interactions among the factors were revealed by computing the total effect indices STi using Extended-FAST. This means that to obtain reliable variance decomposition and to detect and quantify interactions among the factors, the use of the Extended-FAST is recommended. Regarding the comparison between Morris screening and Extended-FAST a poor agreement was found. In particular, the Morris screening overestimated the number of both important and non-influential factors compared to Extended-FAST for the analysed case study. [Copyright &y& Elsevier]

Abstract: In the recent years, there has been an increasing interest in the development of hybrid reactors, especially in the up-grading of existing activated sludge plants that are no longer able to comply with concentration limits established by regulatory agencies. In such systems the biomass grows both as suspended flocs and as biofilm. In this way, it is possible to obtain a higher biomass concentration in the reactor, but without any significant increase of the load to the final clarifier. The paper presents the setting-up of a dynamic mathematical model aimed at quantitatively describing the biokinetic processes occurring in a hybrid moving bed biofilm reactor (HMBBR), and, more in general, in integrated fixed-film activated sludge (IFAS) processes, as well as to compare the simulation results with measured data from a HMBBR pilot plant built at the Norwegian University of Science and Technology in Trondheim (Norway). Particularly, the pilot plant consisted of three aerobic tanks in series; the first and third aerobic reactors were pure suspended biomass systems, while the second aerobic reactor was filled with the AnoxKaldnes™ K1 carriers for biofilm development. The mathematical model consists of two connected models for the simulation of both suspended biomass and biofilm. Biochemical conversions are evaluated according to the well known matrix notation used in the Activated Sludge Model No. 1 (ASM1) for both attached and suspended biomass and, in addition to biochemical conversion, the model contains the simulation of particulate detachment from the biofilm into the bulk liquid. The results showed an overall good agreement between measured and simulated data, for both biofilm and suspended biomass, with a good reproduction of dynamic processes in the hybrid moving bed pilot plant, and they are encouraging for further developments. [Copyright &y& Elsevier]

Abstract: Mathematical modelling of membrane bioreactors (MBRs) for wastewater treatment has targeted either the biological processes (treatment quality target) as well as various aspects of system management. However, the high number of interactions among the involved physical–chemical processes, hampers a straightforward mathematical modelling. This circumstance is much more emphasized for submerged MBR systems where the membrane is immersed in an aeration tank. One of the main crucial points that prevents a comprehensive understanding is the interpretation of the fouling phenomenon and its connections with the biological processes. An overall mathematical model for MBR has not been completely established yet. Indeed, existing MBR models are generally focused only on some of the involved processes (e.g. biological, physical, chemical, etc.) to analyze limited MBR aspects. However, a comprehensive integrated mathematical approach aimed at an in-depth analysis is warmly recommended in order to optimize the whole MBR system. Seeking the development of the area, the paper presents an integrated MBR model that simulates and takes into account both biological and physical processes. An innovative calibration protocol was applied to evaluate the model parameter values as well. This protocol is based on a preliminary global sensitivity analysis to reduce the number of model parameters to be calibrated to the most influential ones. The calibration protocol consists of a novel step-wise Monte Carlo based calibration of the subset of influential parameters. The key point of the step-wise procedure is that calibration is carried out for sub-groups of variables instead of solving a complex multi-objective function. The model results compare fairly well with the experimental results of a MBR pilot plant. [Copyright &y& Elsevier]

In integrated urban drainage water quality models, due to the fact that integrated approaches are basically a cascade of sub-models (simulating sewer system, wastewater treatment plant and receiving water body), uncertainty produced in one sub-model propagates to the following ones depending on the model structure, the estimation of parameters and the availability and uncertainty of measurements in the different parts of the system. Uncertainty basically propagates throughout a chain of models in which simulation output from upstream models is transferred to the downstream ones as input. The overall uncertainty can differ from the simple sum of uncertainties generated in each sub-model, depending on well-known uncertainty accumulation problems. The present paper aims to study the uncertainty propagation throughout an integrated urban water-quality model. At this scope, a parsimonious bespoke integrated model has been used allowing analysis of the combinative effect between different sub-models. Particularly, the data and parameter uncertainty have been assessed and compared by means of the variance decomposition concept. The integrated model and the methodology for the uncertainty decomposition have been applied to a complex integrated catchment: the Nocella basin (Italy). The results show that uncertainty contribution due to the model structure is higher with respect to the other sources of uncertainty. [ABSTRACT FROM AUTHOR]

Over the last decade new technologies are emerging even more for wastewater treatment. Among the new technologies, a recent possible solution regards Moving Bed Biofilm Reactors (MBBRs) that represent an effective alternative to conventional processes. More specifically such systems consist in the introduction of plastic elements inside the aerobic reactor as carrier material for the growth of attached biomass. Recently, one of the mostly used alternatives is to couple the Moving Bed Biofilm Reactor (MBBR) process with the conventional activated sludge process, and the resulting process is usually called HMBBR (Hybrid MBBR). In the MBBR process the biofilm grows attached on small plastic elements that are kept in constant motion throughout the entire volume of the reactor. Indeed, in such a system, a competition between the two biomasses, suspended and attached, can arise for the availability of the substrates, leading, as a consequence, to a modification in the biokinetic parameters of the two biomasses, compared to that of a pure suspended or attached biomass process. This paper presents the first results of a study aimed at estimating the kinetic heterotrophic constants in a HMBBR pilot plant using respirometric techniques. The pilot plant was built at the Acqua dei Corsari (Palermo) wastewater treatment plant and consisted of two parallel lines realized in a pre-anoxic scheme, in one of which the carrier material was added to the aerobic reactor with a filling ratio of 30%. [ABSTRACT FROM AUTHOR]

In the past three decades, scientific research has focused on the preservation of water resources, and in particular, on the polluting impact of urban areas on natural water bodies. One approach to this research has involved the development of tools to describe the phenomena that take place on the urban catchment during both wet and dry periods. Research has demonstrated the importance of the integrated analysis of all the transformation phases that characterise the delivery and treatment of urban water pollutants from source to outfall. With this aim, numerous integrated urban drainage models have been developed to analyse the fate of pollution from urban catchments to the final receiving waters, simulating several physical and chemical processes. Such modelling approaches require calibration, and for this reason, researchers have tried to address two opposing needs: the need for reliable representation of complex systems, and the need to employ parsimonious approaches to cope with the usually insufficient, especially for urban sources, water quality data. The present paper discusses the application of a bespoke model to a complex integrated catchment: the Nocella basin (Italy). This system is characterised by two main urban areas served by two wastewater treatment plants, and has a small river as the receiving water body. The paper describes the monitoring approach that was used for model calibration, presents some interesting considerations about the monitoring needs for integrated modelling applications, and provides initial results useful for identifying the most relevant polluting sources. [ABSTRACT FROM AUTHOR]

Abstract: In the last years, the attention on integrated analysis of sewer networks, wastewater treatment plants and receiving waters has been growing. However, the common lack of data in the urban water-quality field and the incomplete knowledge regarding the interpretation of the main phenomena taking part in integrated urban water systems draw attention to the necessity of evaluating the reliability of model results. Uncertainty analysis can provide useful hints and information regarding the best model approach to be used by assessing its degrees of significance and reliability. Few studies deal with uncertainty assessment in the integrated urban-drainage field. In order to fill this gap, there has been a general trend towards transferring the knowledge and the methodologies from other fields. In this respect, the Generalised Likelihood Uncertainty Evaluation (GLUE) methodology, which is widely applied in the field of hydrology, can be a possible candidate for providing a solution to the above problem. However, the methodology relies on several user-defined hypotheses in the selection of a specific formulation of the likelihood measure. This paper presents a survey aimed at evaluating the influence of the likelihood measure formulation in the assessment of uncertainty in integrated urban-drainage modelling. To accomplish this objective, a home-made integrated urban-drainage model was applied to the Savena case study (Bologna, IT). In particular, the integrated urban-drainage model uncertainty was evaluated employing different likelihood measures. The results demonstrate that the subjective selection of the likelihood measure greatly affects the GLUE uncertainty analysis. [Copyright &y& Elsevier]

Sewer systems convey mostly dry weather flow, coming from domestic and industrial sanitary sewage as well as infiltration flow, and stormwater due to meteoric precipitations. Traditionally, in urban drainage two types of sewer systems are adopted: separate and combined sewers. The former convey dry and wet weather flow separately into two different networks, while the latter convey dry and wet weather flow together. Which is the best solution in terms of costbenefit analysis still remains a controversial subject. The present study was aimed at comparing the pollution loads discharged to receiving bodies by Wastewater Treatment Plant (WWTP) and Combined Sewer Overflow (CSO) for different kinds of sewer systems (combined and separate). To accomplish this objective, a comparison between the two systems was carried out using results from simulations of catchments characterised by different dimensions, population densities and water supply rate. The analysis was based on a parsimonious mathematical model able to simulate the sewer system as well as the WWTP during both dry and wet weather. The rain series employed for the simulations was six years long. Several pollutants, both dissolved and particulate, were modelled. The results confirmed the uncertainties in the choice of one system versus the other, emphasising the concept that case-by-case solutions have to be undertaken. Further, the compared systems showed different responses in terms of effectiveness in reducing the discharged mass to the RWB in relation to the particular pollutant taken into account. [ABSTRACT FROM AUTHOR]

Summary: Over the last few years, the use of mathematical models has gained importance in urban drainage system management; indeed, such models enable the combined analysis of different components that constitute a drainage system; the sewer system, wastewater treatment plant and the receiving water body. The effectiveness of an integrated approach has been widely demonstrated in the past and is presented in the EU Water Framework Directive, which also introduces a new point of view regarding the water quality management of the whole system, requiring a global analysis at the river basin scale for pollutant sources. However, integrated urban drainage models introduce several uncertain factors that are due to the high complexity level of the adopted approaches as well as to the lack of data for a robust model calibration. This paper presents the uncertainty assessment of an integrated urban drainage model developed in previous studies by means of the Generalized Likelihood Uncertainty Estimation methodology. The analysis has been applied to an experimental catchment in Bologna (Italy) which covers a part of the Bologna sewer network and a reach of the Savena River. [Copyright &y& Elsevier]

The current exploitation of freshwater, as well as the significant increase in sewage sludge production from wastewater treatment plants (WWTPs), represent nowadays a critical issue for the implementation of sustainable development consistent with the circular economy concept. There is an urgent need to rethink the concept of WWTPs from the conventional approach consisting in pollutant removal plants to water resource recovery facilities (WRRFs). The aim of this paper is to provide an overview of the demonstration case studies at the Marineo and Corleone WRRFs in Sicily (IT), with the final aim showing the effectiveness of the resources recovery systems, as well as the importance of plant optimization to reduce greenhouse gas (GHG) emissions from WRRFs. This study is part of the H2020 European Project "Achieving wider uptake of water-smart solutions—Wider-Uptake", which final aim is to demonstrate the water-smart solution feasibility in the wastewater sector. The main project goal is to overcome the existing barriers that hamper the transition to circularity through the implementation of a governance analysis tool. The preliminary actions in the two demonstration cases are first presented, while, subsequently, the water-smart solutions to be implemented are thoroughly described, highlighting their roles in the transition process. The achieved preliminary results underlined the significant potential of WRRF application, a great chance to demonstrate the feasibility of innovative solutions in the wastewater sector to overcome the existing social, administrative and technical barriers. [ABSTRACT FROM AUTHOR]

The wastewater sector paradigm is shifting from wastewater treatment to resource recovery. In addition, concerns regarding sustainability during the operation have increased. In this sense, there is a need to break barriers (i.e., social, economic, technological, legal, etc.) for moving forward towards water resource recovery facilities and demonstration case studies can be very effective and insightful. This paper presents a new water resource recovery case study which is part of the Horizon 2020 EU Project "Achieving wider uptake of water-smart solutions—Wider Uptake". The final aim is to demonstrate the importance of a resource recovery system based on the circular economy concept. The recovery facilities at Palermo University (Italy) are first presented. Afterwards, the resource recovery pilot plants are described. Preliminary results have underlined the great potential of the wastewater treatment plant in terms of resources recovery and the central role of the University in fostering the transition towards circular economy. The fermentation batch test highlighted a volatile fatty acids (VFAs) accumulation suitable for polyhydroxyalkanoates (PHAs) production. The results of static adsorption and desorption tests showed that the highest amount of adsorbed NH4+ was recorded for untreated and HCl-Na treated clinoptilolite. [ABSTRACT FROM AUTHOR]

Abstract: The paper presents the setting up of a mathematical model for membrane bioreactor able to simulate physical-biological wastewater organic removal. The model is basically divided into two sub-models: the first sub-model is basically devoted for the simulation of the biological features and the second one for the physical processes. In particular regarding the biological aspects, the ASM concept has been employed. On the other hand, the physical processes have been modelled considering the deep-bed theory taking into account not only the effect of the physical membrane filtration but also the cake layer effect. This latter operates as a biological membrane leading to a further reduction of the effluent COD. The model was applied to a SMBR pilot plant characterized by hollow fibre membrane module in submerged configuration. The SMBR was fed by raw wastewater collected from the Palermo (IT) WWTP and it was in operation for a total period of 130 days. During the whole experimentation the TSS was maintained meanly constant with periodic sludge withdrawal, in order to analyse the role of cake layer on organic removal. The model results are interesting and confirm the importance of cake deposition in the filtration process. The developed model can be employed as a useful tool in optimizing operation conditions as well as design issues for SMBR systems. [Copyright &y& Elsevier]

Wastewater treatment plants (WWTPs) require an urgent transition from a linear to a circular economy operation/design concept with a consequent resource recovery and more sustainable waste management. Natural resources have to be preserved, and wastes have to become an opportunity for recovering resources and materials (water reuse, energy, sludge reuse). However, the transition toward a circular economy is a complex and long process due to the existence of technical, economic, social and regulatory barriers. These existing barriers are critical challenges for a modern and sustainable WWTP concept. The recovery of resources must be considered a strategic target from the earliest process-design phase. In this context, the European Union's Horizon 2020 project "Achieving wider uptake of water-smart solutions—WIDER UPTAKE" aims to overcome the existing barriers (technological, regulatory, organizational, social and economic) toward the transition from a linear to a circular economy model for WWTPs. This study is aimed at increasing the awareness of the existing barriers to a circular economy and summarizes the key contributions of the WIDER UPTAKE project in terms of water reuse, sludge reuse and nutrient recovery. [ABSTRACT FROM AUTHOR]

The membrane bioreactor (MBR), as one of the promising technologies, has been widely applied for treatments of wastewater. However, serious membrane fouling and low microbial activity have been reported as major problems hindering the development of the MBR. To overcome these drawbacks, we intend to improve the MBR process in the view of membrane surface modification and efficient granular bacteria cultivation. In the present study, immobilized photosynthetic bacteria integration with graphene oxide (GO)/polysulfone (PSF) composite membrane separation (IPMBR) was first applied for textile wastewater treatment. Due to the high activity of immobilized cells, the IPMBR system exhibited higher efficiency on the removal of color, ammonia–nitrogen, and chemical oxygen demand than the conventional MBR system. In comparison with a pure PSF membrane, GO/PSF composite membrane presented the higher hydrophilicity (water contact angles of 62.9°) and more attractive permeability (178.5 L/m2h) by reducing the adhesion of hydrophobic foulants. During the whole operation, the immobilized photobioreactor exhibited approximately seven times higher membrane permeability that that of the conventional MBR. Meanwhile, the effect of the structure and character of immobilized photosynthetic bacteria on the membrane fouling reduction was investigated in detail. The change of extracellular polymeric substance concentration, settleability and particle size of flocs was very beneficial to alleviate membrane fouling. As a result, this research will open a new avenue for developing efficient and anti-fouling MBR technology in the future. [ABSTRACT FROM AUTHOR]

• MBR operational conditions are important in terms of environmental impact. • Multi-objective analysis is required to optimize the MBR behavior. • The sludge retention time is the key parameter affecting the gas emissions. • High sludge retention time value leads to the increase of nitrous oxide emission. This paper presents a modelling study aimed at minimizing the environmental foot print of a membrane bioreactor (MBR) for wastewater treatment. Specifically, an integrated model for MBR was employed in view of the management optimization of an MBR biological nutrient removal (BNR) pilot plant in terms of operational costs and direct greenhouse gases emissions. The influence of the operational parameters (OPs) on performance indicators (PIs) was investigated by adopting the Extended-FAST sensitivity analysis method. Further, a multi-objective analysis was performed by applying the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The results show-up that the sludge retention time is the OP mostly affecting all the investigated PIs. By applying the set of optimal OPs, there was a reduction of 48% and 10% of the operational costs and direct emissions, respectively. [ABSTRACT FROM AUTHOR]

• Two-step cascade control strategies have been applied to MBR. • An integrated MBR mathematical model has been adopted. • Energy consumption reduces till to 82% controlling the aerobic airflow rate. • Operating cost reduces till 64% controlling the aerobic airflow rate. • Direct GHG emission reduces from 0.52 to 0.47 kgCO 2eq m−3 under control condition. In this study different scenarios were scrutinized to minimize the energy consumption of a membrane bioreactor system for wastewater treatment. Open-loop and closed-loop scenarios were investigated by two-step cascade control strategies based on dissolved oxygen, ammonia and nitrite concentrations. An integrated MBR model which includes also the greenhouse gas formation/emission processes was applied. A substantial energy consumption reduction was obtained for the closed-loop scenarios (32% for Scenario 1 and 82% for Scenario 2). The air flow control based on both ammonia and nitrite concentrations within the aerobic reactor (Scenario 2) provided excellent results in terms of reduction of operating cost reduction (64%), direct (10%) and indirect (81%) emissions. [ABSTRACT FROM AUTHOR]

• Polyhydroxyalkanoates production by mixed microbial cultures is reviewed. • Obstacles and possible solutions in the economic production of PHA are discussed. • Current pilot scale studies are presented. • Improvements are needed for the transition to the industrial commercialization. Polyhydroxyalkanoates (PHAs) are biopolyesters accumulated as carbon and energy storage materials under unbalanced growth conditions by various microorganisms. They are one of the most promising potential substitutes for conventional non-biodegradable plastics due to their similar physicochemical properties, but most important, its biodegradability. Production cost of PHAs is still a great barrier to extend its application at industrial scale. In order to reduce that cost, research is focusing on the use of several wastes as feedstock (such as agro-industrial and municipal organic waste and wastewater) in a platform based on mixed microbial cultures. This review provides a critical illustration of the state of the art of the most likely-to-be-scale-up PHA production processes using mixed microbial cultures platform and waste streams as feedstock, with a particular focus on both, upstream and downstream processes. Current pilot scale studies, future prospects, challenges and developments in the field are also highlighted. [ABSTRACT FROM AUTHOR]