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Conversion of wastewater treatment plants into biorefineries is a sustainable alternative for obtaining valuable compounds, thus reducing pollutants and costs and protecting the environment and human health. Under specific operating conditions, microbial fermentative products of sewage sludge are volatile fatty acids (VFA) that can be precursors of polyhydroxyalkanoate thermoplastic polyesters. The role of various operating parameters in VFA production has yet to be elucidated. This study aimed to correlate the levels of VFA yields with prokaryotic microbiota structures of sewage sludge in two sets of batch fermentations with an initial pH of 8 and 10. The sewage sludge used to inoculate the batch fermentations was collected from a Sicilian WWTP located in Marineo (Italy) as a case study. Gas chromatography analysis revealed that initial pH 10 stimulated chemical oxygen demands (sCOD) and VFA yields (2020 mg COD/L) in comparison with initial pH 8. Characterization of the sewage sludge prokaryotic community structures—analyzed by next-generation sequencing of 16S rRNA gene amplicons—demonstrated that the improved yield of VFA paralleled the increased abundance of fermenting bacteria belonging to Proteobacteria, Bacteroidetes, Chloroflexi, and Firmicutes phyla and, conversely, the reduced abundance of VFA-degrading strains, such as archaeal methanogens. [ABSTRACT FROM AUTHOR]

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]

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]

As sources of greenhouse gas (GHG) emissions, integrated urban drainage systems (IUDSs) (i.e., sewer systems, wastewater treatment plants and receiving water bodies) contribute to climate change. This paper, produced by the International Working Group on Data and Models, which works under the IWA/IAHR Joint Committee on Urban Drainage, reviews the state-of-the-art and modelling tools developed recently to understand and manage GHG emissions from IUDS. Further, open problems and research gaps are discussed and a framework for handling GHG emissions from IUDSs is presented. The literature review reveals that there is a need to strengthen already available mathematical models for IUDS to take GHG into account. [ABSTRACT FROM AUTHOR]

The influence of the main operational variables on N 2 O emissions from an Integrated Fixed Film Activated Sludge University of Cape Town membrane Bioreactor pilot plant was studied. Nine operational cycles (total duration: 340 days) were investigated by varying the value of the mixed liquor sludge retention time (SRT) (Cycles 1–3), the feeding ratio between carbon and nitrogen (C/N) (Cycles 4–6) and simultaneously the hydraulic retention time (HRT) and the SRT (Cycles 7–9). Results show a huge variability of the N 2 O concentration in liquid and off-gas samples (ranged from 10 −1 μg N 2 O-N L −1 to 10 3 μg N 2 O-N L −1 ). The maximum N 2 O concentration (1228 μg N 2 O-N L −1 ) in the off-gas samples occurred in the anoxic reactor at the lowest C/N value confirming that unbalanced C/N promotes the N 2 O emission during denitrification. The aerated reactors (aerobic and MBR) have been the major N 2 O emitters during all the three Phases. [ABSTRACT FROM AUTHOR]

The paper reports the results of an experimental campaign carried out on a University of Cape Town (UCT) integrated fixed-film activated sludge (IFAS) membrane bioreactor (MBR) pilot plant. The pilot plant was analysed in terms of chemical oxygen demand (COD) and nutrients removal, kinetic/stoichiometric parameters, membrane fouling and sludge dewaterability. Moreover, the cultivable bacterial community structure was also analysed. The pilot plant showed excellent COD removal efficiency throughout experiments, with average value higher than 98%, despite the slight variations of the influent wastewater. The achieved nitrification efficiency was close to 98% for most of the experiments, suggesting that the biofilm in the aerobic compartment might have sustained the complete nitrification of the influent ammonia, even for concentrations higher than 100 mg L −1 . The irreversible resistance due to superficial cake deposition was the mechanism that mostly affected the membrane fouling. Moreover, it was noticed an increase of the resistance due pore blocking likely due to the increase of the EPS Bound fraction that could derive by biofilm detachment. The bacterial strains isolated from aerobic tank are wastewater bacteria known for exhibiting efficient heterotrophic nitrification–aerobic denitrification and producing biofilm. [ABSTRACT FROM AUTHOR]

Sludge dewatering represents, nowadays, one of the greatest operational cost to wastewater treatment cycle. Physical–chemical and biological parameters are recognized to influence the sludge dewaterability. However, many authors agree in identifying the sludge origin as one of the main aspect involved in sludge dewaterability. Indeed, the sludge origin such as the processes involved in liquid–solid separation, seriously affect the sludge features. In order to elucidate the key factors influencing the dewaterability process, the present work is aimed to investigate the influence of the treatment plant lay-out on sludge dewaterability. The analyzed sludge samples were derived from four conventional activated sludge and two membrane bioreactor wastewater treatment plants. Experimental investigation was focused to highlight difference in sludge dewaterability derived from the application of European Standards adopted for sludge characterization. The achieved results confirmed the complexity of the inter-relationships between many factors affecting the sludge dewaterability. [ABSTRACT FROM PUBLISHER]

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]

The increasing attention paid to the environment has led to a reduction in the emissions from wastewater treatment plants (WWTPs). Moreover, the increasing interest in the greenhouse gas (GHG) emissions from WWTPs suggests that we reconsider the traditional tools used for designing and managing WWTPs. Indeed, nitrous oxide, carbon dioxide and methane can be emitted from wastewater treatment, significantly contributing to the greenhouse gas (GHG) footprint. The reduction of energy consumption as well as GHG emission are of particular concern for large WWTPs which treat the majority of wastewater in terms of both volume and pollution load. Nowadays, there is an increasing need to develop new tools that include additional performance indicators related to GHG emissions and energy consumption as well as traditional effluent quality parameters. Energy consumption, in fact, can be considered as an indirect source of GHGs. This paper presents the development of an ongoing research project aiming at setting-up an innovative mathematical model platform for the design and management of WWTPs. The final goal of the project by means of this platform is to minimize the environmental impact of WWTPs through their optimization in terms of energy consumptions and emissions, which can be regarded as discharged pollutants, sludge and GHGs. [ABSTRACT FROM AUTHOR]

Abstract: Global sensitivity analysis (GSA) is a valuable tool to support the use of mathematical models that characterise technical or natural systems. In the field of wastewater modelling, most of the recent applications of GSA use either regression-based methods, which require close to linear relationships between the model outputs and model factors, or screening methods, which only yield qualitative results. However, due to the characteristics of membrane bioreactors (MBR) (non-linear kinetics, complexity, etc.) there is an interest to adequately quantify the effects of non-linearity and interactions. This can be achieved with variance-based sensitivity analysis methods. In this paper, the Extended Fourier Amplitude Sensitivity Testing (Extended-FAST) method is applied to an integrated activated sludge model (ASM2d) for an MBR system including microbial product formation and physical separation processes. Twenty-one model outputs located throughout the different sections of the bioreactor and 79 model factors are considered. Significant interactions among the model factors are found. Contrary to previous GSA studies for ASM models, we find the relationship between variables and factors to be non-linear and non-additive. By analysing the pattern of the variance decomposition along the plant, the model factors having the highest variance contributions were identified. This study demonstrates the usefulness of variance-based methods in membrane bioreactor modelling where, due to the presence of membranes and different operating conditions than those typically found in conventional activated sludge systems, several highly non-linear effects are present. Further, the obtained results highlight the relevant role played by the modelling approach for MBR taking into account simultaneously biological and physical processes. [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]

The behavior of a University of Cape Town (UCT) membrane bioreactor (MBR) system was investigated for use in biological nutrient removal from real wastewater. The pilot plant was in operation for a period of 165 days, during which an extensive data gathering campaign was conducted. The pilot plant was started up by inoculating it with activated sludge from a nearby wastewater treatment plant, and it was fed by real municipal wastewater characterized by high organic nitrogen concentrations attributable to discharges from industrial wastewater and sporadic landfill leachate. Carbon and biological nutrient removal processes, a sludge production process, and a membrane fouling mechanism were analyzed and discussed. The organic nitrogen levels, which were higher than typical values for municipal wastewater, caused ammonification phenomena. This led to intense nitrification and denitrification activities. The pilot plant showed satisfactory efficiency in terms of average removal efficiencies for both carbon and nitrogen. However, lower efficiencies were recorded for phosphorus removal as an indirect effect of the intense denitrifying activity of the phosphorus-accumulating organisms in the anoxic tank. Membrane fouling was mainly of reversible nature, and low values of soluble microbial product were measured. [ABSTRACT FROM AUTHOR]

Abstract: Identifiability analysis enables the quantification of the number of model parameters that can be assessed by calibration with respect to a data set. Such a methodology is based on the appraisal of sensitivity coefficients of the model parameters by means of Monte Carlo runs. By employing the Fisher Information Matrix, the methodology enables one to gain insights with respect to the number of model parameters that can be reliably assessed. The paper presents a study where identifiability analysis is used as a tool for setting up measuring campaigns for integrated water quality modelling. Particularly, by means of the identifiability analysis, the information about the location and the number of the monitoring stations in the integrated system required for assessing a specific group of model parameters were gained. The analysis has been applied to a real, partially urbanised, catchment containing two sewer systems, two wastewater treatment plants and a river. Several scenarios of measuring campaigns have been considered; each scenario was characterised by different monitoring station locations for the gathering of quantity and quality data. The results enabled us to assess the maximum number of model parameters quantifiable for each scenario i.e. for each data set. The methodology resulted to be a powerful tool for designing measuring campaign for integrated water quality modelling. Indeed, the crucial cross sections throughout the integrated wastewater system were detected optimizing both human and economic efforts in the gathering of field data. Further, a connection between the data set and the number of model parameters effectively assessable has been established leading to much more reliable model results. [Copyright &y& Elsevier]

Abstract: In the last few years, the use of mathematical models in WasteWater Treatment Plant (WWTP) processes has become a common way to predict WWTP behaviour. However, mathematical models generally demand advanced input for their implementation that must be evaluated by an extensive data-gathering campaign, which cannot always be carried out. This fact, together with the intrinsic complexity of the model structure, leads to model results that may be very uncertain. Quantification of the uncertainty is imperative. However, despite the importance of uncertainty quantification, only few studies have been carried out in the wastewater treatment field, and those studies only included a few of the sources of model uncertainty. Seeking the development of the area, the paper presents the uncertainty assessment of a mathematical model simulating biological nitrogen and phosphorus removal. The uncertainty assessment was conducted according to the Generalised Likelihood Uncertainty Estimation (GLUE) methodology that has been scarcely applied in wastewater field. The model was based on activated-sludge models 1 (ASM) and 2 (ASM2). Different approaches can be used for uncertainty analysis. The GLUE methodology requires a large number of Monte Carlo simulations in which a random sampling of individual parameters drawn from probability distributions is used to determine a set of parameter values. Using this approach, model reliability was evaluated based on its capacity to globally limit the uncertainty. The method was applied to a large full-scale WWTP for which quantity and quality data was gathered. The analysis enabled to gain useful insights for WWTP modelling identifying the crucial aspects where higher uncertainty rely and where therefore, more efforts should be provided in terms of both data gathering and modelling practises. [Copyright &y& Elsevier]

Summary: Quantification of uncertainty is of paramount interest in integrated urban drainage water quality modelling. Indeed, the assessment of the reliability of the results of complex water quality models is crucial in understanding their significance. However, the state of knowledge regarding uncertainties in urban drainage models is poor. In the case of integrated urban drainage water quality models, due to the fact that integrated approaches are basically a cascade of sub-models (simulating the sewer system, wastewater treatment plant and receiving water body), uncertainty produced in one sub-model propagates to the following ones in a manner dependent 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 the simulation output from upstream models is transferred to the downstream ones as input. The Variance Decomposition Approach tracks uncertainty propagation commonly assuming that the correlation among error sources is negligible. In complex environmental models, the overall uncertainty can differ significantly from the simple sum of uncertainties generated in each sub-model, showing the well-known uncertainty accumulation problems due to non-linearity in the model and correlation among the sources of uncertainty. This work discusses the importance of such issues in the application of a complex integrated urban drainage model with the aim of evaluating the applicability of Variance Decomposition Approach. The integrated model and the methodology for the uncertainty decomposition were then applied to a complex integrated catchment: the Nocella basin (Italy). The results showed that the Variance Decomposition Approach can be a powerful tool for uncertainty analysis, but a possible correlation among uncertainty sources should be considered because it can greatly affect the analysis. [ABSTRACT FROM AUTHOR]

Urban water quality management often requires use of numerical models allowing the evaluation of the cause-effect relationship between the input(s) (i.e. rainfall, pollutant concentrations on catchment surface and in sewer system) and the resulting water quality response. The conventional approach to the system (i.e. sewer system, wastewater treatment plant and receiving water body), considering each component separately, does not enable optimisation of the whole system. However, recent gains in understanding and modelling make it possible to represent the system as a whole and optimise its overall performance. Indeed, integrated urban drainage modelling is of growing interest for tools to cope with Water Framework Directive requirements. Two different approaches can be employed for modelling the whole urban drainage system: detailed and simplified. Each has its advantages and disadvantages. Specifically, detailed approaches can offer a higher level of reliability in the model results, but can be very time consuming from the computational point of view. Simplified approaches are faster but may lead to greater model uncertainty due to an over-simplification. To gain insight into the above problem, two different modelling approaches have been compared with respect to their uncertainty. The first urban drainage integrated model approach uses the Saint-Venant equations and the 1D advection-dispersion equations, for the quantity and for the quality aspects, respectively. The second model approach consists of the simplified reservoir model. The analysis used a parsimonious bespoke model developed in previous studies. For the uncertainty analysis, the Generalised Likelihood Uncertainty Estimation (GLUE) procedure was used. Model reliability was evaluated on the basis of capacity of globally limiting the uncertainty. Both models have a good capability to fit the experimental data, suggesting that all adopted approaches are equivalent both for quantity and quality. The detailed model approach is more robust and presents less uncertainty in terms of uncertainty bands. On the other hand, the simplified river water quality model approach shows higher uncertainty and may be unsuitable for receiving water body quality assessment. [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]

The paper presents the comparison between the traditional activated sludge system (AS) and a hybrid moving bed biofilm reactor (HMBBR). In particular, an experimental campaign has been carried out at the WWTP in Palermo (Italy), on a pilot plant consisting of two pre-anoxic schemes. The aerated tank of the HMBBR line was filled with suspended carriers (AnoxKaldnes® K1), with a 30% filling ratio. The hydraulic load of the HMBBR line was increased up to two times the AS one. Further, in order to distinguish the additional contribution of the attached biomass for the HMBBR system, in the two lines the Mixed Liquor Suspended Solids (MLSS) was maintained as equal as possible. The monitoring period lasted three months during which several parameters were monitored. The obtained results showed a good treatment ability of the HMBBR system, referring to the organic matter removal as well as to the ammonium removal. In particular, in spite of the increase of the hydraulic load for the HMBBR line, the two systems showed a similar performance in terms of both organic and nitrogen removal. The results demonstrate the higher treatment capacity of the HMBBR addressing such system as an effective technology for the upgrading of overloaded wastewater treatment plants. [ABSTRACT FROM AUTHOR]

Over the last few years there has been a growing attention regarding the receiving water body quality state. As a matter of a fact, the Directive 91/271 of the European Union (EU) replaced the "emission standard" concept that fixes discharge limits depending on polluting emission characteristics, with the "stream standard" concept that fixes discharge limits for each polluting substance depending on self-depurative characteristics of the RWB. In this context, several WWTPs need to be upgraded in order to meet stricter effluent limits. The need of WWTP upgrading was also emphasized by the growing urbanization that have led, in most cases, to get overloaded WWTP due to an overcoming of the maximum WWTP capacity. In order to upgrade existing WWTP basically two main possibilities can be chosen: building new tanks or modify the WWTP by introducing new technologies such as the HMBBR systems. In this paper, such latter possibility was explored and as a case study an existing Italian WWTP (Acqua dei Corsari) located in Palermo (IT) was analysed. The main goal was to test the effectiveness of HMBBR systems with respect to the WWTP upgrading. The survey was carried out by means of model simulation and an HMBBR pilot plant. This latter was employed for the evaluation of the model parameters as well as kinetic coefficients for the HMBBR. The model results are encouraging towards the WWTP upgrading by means of HMBBR. As a matter of fact, the model simulation results showed that the WWTP maximum capacity can be upgraded from 480,000 up to one million PE. [ABSTRACT FROM AUTHOR]

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]

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]

• A literature review on DSS for wastewater treatment plants is presented. • DSSs are capable of integrating several data and a multi-criteria perspective. • The development of more user-friendly and web-based DSSs is also encouraged. • Web-based DSSs could stimulate group decision-making. The use of decision support systems (DSS) allows integrating all the issues related with sustainable development in view of providing a useful support to solve multi-scenario problems. In this work an extensive review on the DSSs applied to wastewater treatment plants (WWTPs) is presented. The main aim of the work is to provide an updated compendium on DSSs in view of supporting researchers and engineers on the selection of the most suitable method to address their management/operation/design problems. Results showed that DSSs were mostly used as a comprehensive tool that is capable of integrating several data and a multi-criteria perspective in order to provide more reliable results. Only one energy-focused DSS was found in literature, while DSSs based on quality and operational issues are very often applied to site-specific conditions. Finally, it would be important to encourage the development of more user-friendly DSSs to increase general interest and usability. [ABSTRACT FROM AUTHOR]

[Display omitted] • Monitoring a new pilot plant fermenter. • Up to 409 mg COD/L of VFA were obtained from domestic sewage sludge. • Evaluation of the effect of different headspace volumes. • VFA accounted for more than 40% of sCOD with 20% headspace volume. • Membrane fouling was monitored during the experiments. Volatile fatty acids (VFAs) produced by acidogenic digestion of sewage sludge are very interesting bio-products which can contribute to carbon neutrality of wastewater treatment plants. Studies on the production of VFAs from sewage sludge from fermenters with membrane are limited. In view of above, VFAs from a fermenter pilot plant equipped with a membrane bioreactor and fed with real sewage sludge has been monitored. The effect of headspace volume (HdV) on VFA production was studied for the first time to elucidate the optimal operation conditions. Specifically, three fermenter HdV values (namely, 20, 40 and 60% of the total volume) have been investigated. Results revealed that the HdV of 20% ensured the highest sCOD production (900 mgCOD/L) and VFA/COD ratio (45.4%). High value of HdV (namely, 40 and 60%) strongly decreased the acidogenic fermentation performance in terms of VFA production. [ABSTRACT FROM AUTHOR]

The shift from conventional wastewater treatment plants to biorefineries is one of the most environmentally and economically sustainable pathways for extracting valuable compounds from waste. Besides chemical-physical processes, microorganisms within sewage sludge utilize organic and inorganic pollutants in the wastewater as nutrients, leading to effective water purification. However, the remaining solid sludge residue, typically destined for specific landfills or incineration, could undergo microbial fermentation to produce volatile fatty acids (VFA), metabolic precursors for biopolymers. Increasing attention has been directed towards optimizing operational parameters to enhance VFA production during sewage sludge fermentation. This study examined the impact of potassium permanganate (PP) on microbial communities during the sewage sludge's acidogenic fermentation. The results highlighted the positive effect of PP treatment, which increased COD production and VFA yield up to 1263.5 mg/L and 664.2 mg COD/L, respectively. The presence of PP significantly enhances VFA yield promoting bacteria positively linked to VFA production. • Bacterial fermentation of solid sludge residue from WWTP presents an opportunity to produce volatile fatty acids (VFA). • Potassium permanganate (KMnO₄) addition enhanced the VFA share up to 55 % of sCOD. • Macellibacteroides fermentans , Pseudomonas veronii and Proteocatella sphenisci increased in sludge treated with KMnO₄. • The addition of KMnO₄ in sewage sludge fermentation is a promising strategy for enhancing VFA yield by modulating bacterial communities. [ABSTRACT FROM AUTHOR]

[Display omitted] • A tailor-made software was prepared to perform automated accumulation tests. • 60 % w/w of PHA accumulation was achieved. • The organic load highly influenced PHA productivity and final content. • PHA polymers were recovered with a yield of 78% and purity of 89%. • The food-on-demand strategy adopted may have a high scaling up potential. Despite the increasing number of studies related to the polyhydroxyalkanoate (PHA) production from sewage sludge of wastewater treatment plants, there is still a gap in the correlation between the operational conditions, such as the organic loading rate (OLR), and the intracellular polyhydroxyalkanoate (PHA) content, productivity and final recovery of the polymer. Therefore, this work aims to provide experimental data on PHA productivity and purity in view of scaling up the process to an industrial level taking into account process parameters. In view of that, three OLR were applied during the selection of PHA-accumulating bacteria in sewage sludge. Then, the biomass was harvested and subjected to batch accumulation experiments at two organic loads per dosage by employing a tailor-made software to adopt an automated feed-on-demand strategy, which allowed for 30–56 h of accumulation tests in stand-alone mode. Finally, an improved protocol for PHA extraction has been applied. Experimental results show that the maximum PHA content (60% w/w) was achieved using the highest organic load per dosage during the accumulation test with the biomass selected at the highest OLR (1.8 g COD L−1 d−1). Also, the extraction protocol efficiency was proven with four samples with different PHA content, achieving recovery yield as high as 78 ± 3 % with a purity of 89 ± 2 %, thus demonstrating that the adopted strategy might be beneficial for industrial use. [ABSTRACT FROM AUTHOR]

Activated sludge models are widely used to simulate, optimize and control performance of wastewater treatment plants (WWTP). For simulation of nutrient removal and energy consumption, kinetic parameters would need to be estimated, which requires an extensive measurement campaign. In this study, a novel methodology is proposed for modeling the performance and energy consumption of a biological nutrient removal activated sludge system under sensitivity and uncertainty. The actual data from the wastewater treatment plant in Slupsk (northern Poland) were used for the analysis. Global sensitivity analysis methods accounting for interactions between kinetic parameters were compared with the local sensitivity approach. An extensive procedure for estimation of kinetic parameters allowed to reduce the computational effort in the uncertainty analysis and improve the reliability of the computational results. Due to high costs of measurement campaigns for model calibration, a modification of the Generalized Likelihood Uncertainty method was applied considering the location of measurement points. The inclusion of nutrient measurements in the aerobic compartment in the uncertainty analysis resulted in percentages of ammonium, nitrate, ortho-phosphate measurements of 81%, 90%, 78%, respectively, in the 95% confidence interval. The additional inclusion of measurements in the anaerobic compartment resulted in an increase in the percentage of ortho-phosphate measurements in the aerobic compartment by 5% in the confidence interval. The developed procedure reduces computational and measurement efforts, while maintaining a high compatibility of the observed data and model predictions. This enables to implement activated sludge models also for the facilities with a limited availability of data. • Nutrient removal and energy consumption were modeled in a real facility. • Global sensitivity analysis was compared with local sensitivity analysis. • New effective approach to uncertainty analysis was applied. • Optimal selection of sampling points and scope of measurements was determined. [ABSTRACT FROM AUTHOR]

Abstract: Over the last two decades, Membrane Bioreactors (MBRs) emerged even more for wastewater treatment, ensuring high removal efficiencies as well as very small footprint requirements. Indeed, in this kind of process, a modification in biomass activity and viability can exist compared to that of a CAS process. In this context, respirometric analysis represents a reliable tool in order to evaluate the actual biomass kinetic parameters, to insert in mathematical models in the design phase, as well as to monitor the biomass viability, especially when these processes are operated with high SRT values. The paper presents some results of respirometric techniques applied for the characterisation of wastewater and biomass activity in a pilot UCT-MBR plant for nutrient removal, operating with high SRT. In particular, the respirometric tests were specifically aimed at investigating heterotrophic and autotrophic bacterial activity. The pilot plant was built at Palermo WWTP and consisted of three reactors: anaerobic, anoxic and aerobic, followed by an aerobic compartment containing two submerged hollow fibre membrane modules with typical recycling lines. The kinetic parameters for heterotrophic bacteria resulted lower respect to the CAS; regarding the nitrifying bacteria, the kinetic constants were in the range of CAS, suggesting a good nitrification activity. [Copyright &y& Elsevier]