New framework for standardized notation in wastewater treatment modelling

A Review of Computational Modeling in Wastewater Treatment Processes

Wastewater treatment companies are facing several challenges related to the optimization of energy efficiency, meeting more restricted water quality standards, and resource recovery potential. Over the past decades, computational models have gained recognition as effective tools for addressing some of these challenges, contributing to the economic and operational efficiencies of wastewater treatment plants (WWTPs). To predict the performance of WWTPs, numerous deterministic, stochastic, and time series-based models have been developed. Mechanistic models, incorporating physical and empirical knowledge, are dominant as predictive models. However, these models represent a simplification of reality, resulting in model structure uncertainty and a constant need for calibration. With the increasing amount of available data, data-driven models are becoming more attractive. The implementation of predictive models can revolutionize the way companies manage WWTPs by permitting the development of digital twins for process simulation in (near) real-time. In data-driven models, the structure is not explicitly specified but is instead determined by searching for relationships in the available data. Thus, the main objective of the present review is to discuss the implementation of machine learning models for the prediction of WWTP effluent characteristics and wastewater inflows as well as anomaly detection studies and energy consumption optimization in WWTPs. Furthermore, an overview considering the merging of both mechanistic and machine learning models resulting in hybrid models is presented as a promising approach. A critical assessment of the main gaps and future directions on the implementation of mathematical modeling in wastewater treatment processes is also presented, focusing on topics such as the explainability of data-driven models and the use of Transfer Learning processes.

Assessment and modeling of effluent quality, economic benefits, and greenhouse gas reduction for receiving brewery wastewater on A2O by GPS-X

Recently, breweries have been allowed to discharge brewery wastewater (BWW) to the sewage pipe network to alleviate the shortage of carbon sources of municipal wastewater treatment plants (MWTPs) under the premise of signing a contract with MWTPs in some countries. This study aims to provide a model-based method for MWTPs to evaluate the threshold, the effluent risk, the economic benefits, and the potential greenhouse gas (GHG) emissions reduction of receiving BWW. In this research, a simulation model of an anaerobic-anoxic-oxic process (A²O) receiving BWW was established based on the data of a real MWTP and brewery using GPS-X. The sensitivity factors of 189 parameters were analyzed, and several sensitive parameters were calibrated stably and dynamically. By analyzing the errors and standardized residuals, the calibrated model was proved to be high-quality and reliable. In the next phase, the impact of receiving BWW on the A²O was evaluated in terms of effluent quality, economic benefits, and GHG emissions reduction. The results showed that receiving a certain amount of BWW can effectively reduce the carbon source cost and GHG emissions for the MWTP compared with adding methanol. Though the chemical oxygen demand (COD), biochemical oxygen demand in five days (BOD₅), and total nitrogen (TN) in the effluent increased in various degrees, the effluent quality still met the discharge standard implemented by the MWTP. The study can also facilitate the modeling work for many researchers and promote more kinds of food production wastewater to be treated equally.

Modeling the anaerobic treatment of sulfate-rich urban wastewater: Application to AnMBR technology

Although anaerobic membrane bioreactors (AnMBR) are a core technology in the transition of urban wastewater (UWW) treatment towards a circular economy, the transition is being held back by a number of bottlenecks. The dissolved methane released from the effluent, the need to remove nutrients (ideally by recovery), or the energy lost by the competition between methanogenic and sulfate-reducing bacteria (SRB) for the biodegradable COD have been identified as the main issues to be addressed before AnMBR becomes widespread. Mathematical modeling of this technology can be used to obtain further insights into these bottlenecks plus other valuable information for design, simulation and control purposes. This paper therefore proposes an AnMBR anaerobic digestion model to simulate the crucial SRB-related process since these bacteria degrade more than 40% of the organic matter. The proposed model, which is included in the BNRM2 collection model, has a reduced but all-inclusive structure, including hydrolysis, acidogenesis, acetogenesis, methanogenesis and other SRB-related processes. It was calibrated and validated using data from an AnMBR pilot plant treating sulfate-rich UWW, including parameter values obtained in off-line experiments and optimization methods. Despite the complex operating dynamics and influent composition, it was able to reproduce the process performance. In fact, it was able to simulate the AD of sulfate-rich UWW considering only two groups of SRB: heterotrophic SRB growing on both VFA (propionate) and acetate, and autotrophic SRB growing on hydrogen. Besides the above-mentioned constraints, the model reproduced the dynamics of the mixed liquor solids concentration, which helped to integrate biochemical and filtration models. It also reproduced the alkalinity and pH dynamics in the mixed liquor required for assessing the effect of chemical precipitation on membrane scaling.

Calibration and validation of an activated sludge model for membrane bioreactor wastewater treatment plants

A mathematical model to simulate the biological processes occurring in a membrane bioreactor (MBR) is presented. The model accounts for different MBR technical features by introducing specific permeability parameters for the applied membrane system. The model considers for the heterotrophic storage process and the formation of soluble microbial products. The introduction of an inhibition coefficient influencing the anoxic kinetics enables the model to simulate the particular operating conditions of the plant, such as a high or low dissolved oxygen concentration in the denitrification tank. The model was applied at the MBR wastewater treatment plant of Vila Nova do Ceira (Portugal) which uses a classic pre-denitrification cycle. Data for calibration and validation were sampled at the same wastewater treatment plant. Calibration was achieved by varying the kinetic parameters of the model to match the simulation results to the experimental data. The values of the kinetic parameters were similar to those found in the literature. The validation was performed by two different methodologies to analyse the model response to diverse operating conditions, and to evaluate the resilience of the MBR. Calibration and validation results were evaluated with mean average error, root mean square error and fractional mean bias as performance indexes. In most cases, these indexes confirmed the high accuracy of the model. Overall, the results of the calibration and validation steps enriched the proposed model by providing an effective biological description of the processes characterizing the MBR. Thus, the model is a reliable tool for the management and designing of MBR.

Modelling energy efficiency and generation potential in the South African wastewater services sector

About 55% of energy used in the South African water cycle is for wastewater treatment, with the bulk of this energy associated with aeration in biological processes. However, up to 15% of wastewater energy demand can be offset by energy generation from sludge (power and/or combined heat and power), while best practices adoption can deliver energy efficiency gains of between 5% and 25% in the water cycle. Advanced process modelling and simulation has been applied in this study as a tool to evaluate optimal process and aeration control strategies. This study further applied advanced modelling to investigate and predict the potential energy consumption and consumption cost pattern by the South African wastewater sector resulting from implementation of optimal process and aeration energy use reduction strategies in support of sustainable municipal wastewater management. Aeration energy consumption and cost savings of 9-45% were demonstrated to be achievable through implementation of energy conservation measures without compromising final effluent regulatory compliance. The study further provided significant potential future energy savings as high as 50% and 78% through implementation of simple and complex aeration energy conservation measures respectively. Generally, the model-predicted energy savings suggest that adoption of energy efficiency should be coupled with electricity generation from sludge in order to achieve maximum energy consumption and cost savings within the South African wastewater services sector.

Position paper - progress towards standards in integrated (aerobic) MBR modelling

Membrane bioreactor (MBR) models are useful tools for both design and management. The system complexity is high due to the involved number of processes which can be clustered in biological and physical ones. Literature studies are present and need to be harmonized in order to gain insights from the different studies and allow system optimization by applying a control. This position paper aims at defining the current state of the art of the main integrated MBR models reported in the literature. On the basis of a modelling review, a standardized terminology is proposed to facilitate the further development and comparison of integrated membrane fouling models for aerobic MBRs.

Improving operational management of wastewater systems. A case study

Wastewater treatment facilities collecting wastewater from longstanding sewer networks of five municipalities in the Ave River basin (located in NW Portugal) are especially vulnerable to water inflows since they have considerable extensions of sewers installed in stream and riverbeds. TRATAVE, the company responsible for operating the system, designed and implemented a monitoring network to measure discharges along the entire drainage network and treatment facilities in order to reduce those water inflows. Several flow measurement devices were installed at strategic locations within the sewer network and integrated with a SCADA system responsible for its operation. A decision support system (DSS) is being implemented using the Delft-FEWS platform, integrating monitoring data and models. Based on monitored data and model results, an estimation of infiltration volumes during wet periods is presented. Moreover, the capabilities of the DSS are illustrated in: (i) location of manholes losses along sewer networks during wet periods; (ii) identification and location of unknown connections to the sewer network using wastewater balances; and (iii) design of a PID controller for a pumping station using on-line tank water level measurement. Acquired knowledge resulting from the DSS greatly improved the utility performance both in terms of economic revenue and environmental protection.

Microalgae and cyanobacteria modeling in water resource recovery facilities: A critical review

Microalgal and cyanobacterial resource recovery systems could significantly advance nutrient recovery from wastewater by achieving effluent nitrogen (N) and phosphorus (P) levels below the current limit of technology. The successful implementation of phytoplankton, however, requires the formulation of process models that balance fidelity and simplicity to accurately simulate dynamic performance in response to environmental conditions. This work synthesizes the range of model structures that have been leveraged for algae and cyanobacteria modeling and core model features that are required to enable reliable process modeling in the context of water resource recovery facilities. Results from an extensive literature review of over 300 published phytoplankton models are presented, with particular attention to similarities with and differences from existing strategies to model chemotrophic wastewater treatment processes (e.g., via the Activated Sludge Models, ASMs). Building on published process models, the core requirements of a model structure for algal and cyanobacterial processes are presented, including detailed recommendations for the prediction of growth (under phototrophic, heterotrophic, and mixotrophic conditions), nutrient uptake, carbon uptake and storage, and respiration.

Towards model predictive control: online predictions of ammonium and nitrate removal by using a stochastic ASM

Online model predictive control (MPC) of water resource recovery facilities (WRRFs) requires simple and fast models to improve the operation of energy-demanding processes, such as aeration for nitrogen removal. Selected elements of the activated sludge model number 1 modelling framework for ammonium and nitrate removal were included in discretely observed stochastic differential equations in which online data are assimilated to update the model states. This allows us to produce model-based predictions including uncertainty in real time while it also reduces the number of parameters compared to many detailed models. It introduces only a small residual error when used to predict ammonium and nitrate concentrations in a small recirculating WRRF facility. The error when predicting 2 min ahead corresponds to the uncertainty from the sensors. When predicting 24 hours ahead the mean relative residual error increases to ∼10% and ∼20% for ammonium and nitrate concentrations respectively. Consequently this is considered a first step towards stochastic MPC of the aeration process. Ultimately this can reduce electricity demand and cost for water resource recovery, allowing the prioritization of aeration during periods of cheaper electricity.

Starch degradation and intermediate dynamics in flocculated and dispersed microcosms

A large fraction of the organic substrate in municipal wastewater is particulate. Prior to uptake, particles have to be degraded through potentially a range of intermediates. However, research on intermediate dynamics during particle hydrolysis is limited. In this paper, batch experiments on flocculated and dispersed biomass microcosms using starch as particulate substrate are reported. Overall hydrolysis rate was not significantly different between the two systems. Particle colonization, and increased particle porosity in combination with particle breakup, led to increased substrate availability over time. Particle breakup was more important for flocculated biomass, while increased particle porosity and particle colonization played a larger role for dispersed biomass. During particle degradation intermediates were formed; however, all intermediate polymer sizes were not formed to the same extent. This can be explained by non-random enzymatic degradation, where some products are preferred over others. Intermediates' dynamics also depend on the biomass structure, and in a floc-based system, diffusion limitations allow glucose to accumulate in the system.

Towards a consensus-based biokinetic model for green microalgae - The ASM-A

Cultivation of microalgae in open ponds and closed photobioreactors (PBRs) using wastewater resources offers an opportunity for biochemical nutrient recovery. Effective reactor system design and process control of PBRs requires process models. Several models with different complexities have been developed to predict microalgal growth. However, none of these models can effectively describe all the relevant processes when microalgal growth is coupled with nutrient removal and recovery from wastewaters. Here, we present a mathematical model developed to simulate green microalgal growth (ASM-A) using the systematic approach of the activated sludge modelling (ASM) framework. The process model - identified based on a literature review and using new experimental data - accounts for factors influencing photoautotrophic and heterotrophic microalgal growth, nutrient uptake and storage (i.e. Droop model) and decay of microalgae. Model parameters were estimated using laboratory-scale batch and sequenced batch experiments using the novel Latin Hypercube Sampling based Simplex (LHSS) method. The model was evaluated using independent data obtained in a 24-L PBR operated in sequenced batch mode. Identifiability of the model was assessed. The model can effectively describe microalgal biomass growth, ammonia and phosphate concentrations as well as the phosphorus storage using a set of average parameter values estimated with the experimental data. A statistical analysis of simulation and measured data suggests that culture history and substrate availability can introduce significant variability on parameter values for predicting the reaction rates for bulk nitrate and the intracellularly stored nitrogen state-variables, thereby requiring scenario specific model calibration. ASM-A was identified using standard cultivation medium and it can provide a platform for extensions accounting for factors influencing algal growth and nutrient storage using wastewater resources.

Fabrication of polysiloxane-modified polyurethane sponge as low-cost organics/water separation and selective absorption material

Through sol-gel and dip-coating processes, commercial polyurethane sponge modified by polysiloxane was fabricated under low temperature (60 °C) and atmosphere. The contact angle of the obtained polysiloxane/polyurethane sponge is 145 ± 5°. Hence, the polysiloxane/polyurethane sponge could float on water and selectively absorb organics from the surface of the water, indicating simultaneous properties of hydrophobicity and oleophilicity. The absorbent maximum value is 50-150 times of its own weight. The polysiloxane/polyurethane sponge exhibited excellent recyclability, which could be reused by squeezing the sponge due to its high mechanical stability and flexibility. Thermogravimetry-differential thermal analysis test indicated that the polysiloxane/polyurethane sponge exhibited good thermal stability and the stable contact angle of samples tested under increasing temperature indicated its good weather resistance. Due to the commercial property of polyurethane sponge and easy-handling of polysiloxane, the polysiloxane/polyurethane sponge can be easily scaled up to recover a large-area oil spill in water and further work based on the designed equipment has been under consideration.

A dynamic physicochemical model for chemical phosphorus removal

A dynamic physico-chemical model for chemical phosphorus removal in wastewater is presented as a tool to optimize chemical dosing simultaneously while ensuring compliant effluent phosphorus concentration. This new model predicts the kinetic and stoichiometric variable processes of precipitation of hydrous ferric oxides (HFO), phosphates adsorption and co-precipitation. It is combined with chemical equilibrium and physical precipitation reactions in order to model observed bulk dynamics in terms of pH. The model is calibrated and validated based on previous studies and experimental data from Smith et al. (2008) and Szabo et al. (2008) as a first step for full-plant implementation. The simulation results show that the structure of the model describes adequately the mechanisms of adsorption and co-precipitation of phosphate species onto HFO and that the model is robust under various experimental conditions.

Chronic impact of tetracycline on nitrification kinetics and the activity of enriched nitrifying microbial culture

This study evaluated the chronic impact of tetracycline on biomass with enriched nitrifying community sustained in a lab-scale activated sludge system. For this purpose, a fill and draw reactor fed with 100 mg COD/L of peptone mixture and 50 mg N/L of ammonia was sustained at a sludge age of 15 days. At steady-state, the reactor operation was continued with a daily tetracycline dosing of 50 mg/L for more than 40 days, with periodic monitoring of the microbial composition, the nitrifying bacteria abundance, as well as the amoA and 16S rRNA gene activity, using molecular techniques. Changes in the kinetics of nitrification were quantified by modelling concentration profiles of major nitrogen fractions and oxygen uptake rate profiles derived from parallel batch experiments. Activated sludge modeling results indicated inhibitory impact of tetracycline on the growth of nitrifiers with a significant increase of the half saturation coefficients in corresponding rate equations. Tetracycline also inactivated biomass components of the enriched culture at a gradually increasing rate with time of exposure, leading to total collapse of nitrification. Molecular analyses revealed significant changes in the composition of the microbial community throughout the observation period. They also showed that continuous exposure to tetracycline inflicted significant reduction in amoA mRNA and 16S rRNA levels directly affecting nitrification. The chronic impact was much more pronounced on the ammonia oxidizing bacteria (AOB) community. These observations explained the basis of numerical changes identified in the growth kinetics of nitrifiers under stress conditions.

A novel protocol for model calibration in biological wastewater treatment

Activated sludge models (ASMs) have been widely used for process design, operation and optimization in wastewater treatment plants. However, it is still a challenge to achieve an efficient calibration for reliable application by using the conventional approaches. Hereby, we propose a novel calibration protocol, i.e. Numerical Optimal Approaching Procedure (NOAP), for the systematic calibration of ASMs. The NOAP consists of three key steps in an iterative scheme flow: i) global factors sensitivity analysis for factors fixing; ii) pseudo-global parameter correlation analysis for non-identifiable factors detection; and iii) formation of a parameter subset through an estimation by using genetic algorithm. The validity and applicability are confirmed using experimental data obtained from two independent wastewater treatment systems, including a sequencing batch reactor and a continuous stirred-tank reactor. The results indicate that the NOAP can effectively determine the optimal parameter subset and successfully perform model calibration and validation for these two different systems. The proposed NOAP is expected to use for automatic calibration of ASMs and be applied potentially to other ordinary differential equations models.

Modelling and characterization of primary settlers in view of whole plant and resource recovery modelling

Characterization and modelling of primary settlers have been neglected pretty much to date. However, whole plant and resource recovery modelling requires primary settler model development, as current models lack detail in describing the dynamics and the diversity of the removal process for different particulate fractions. This paper focuses on the improved modelling and experimental characterization of primary settlers. First, a new modelling concept based on particle settling velocity distribution is proposed which is then applied for the development of an improved primary settler model as well as for its characterization under addition of chemicals (chemically enhanced primary treatment, CEPT). This model is compared to two existing simple primary settler models (Otterpohl and Freund; Lessard and Beck), showing to be better than the first one and statistically comparable to the second one, but with easier calibration thanks to the ease with which wastewater characteristics can be translated into model parameters. Second, the changes in the activated sludge model (ASM)-based chemical oxygen demand fractionation between inlet and outlet induced by primary settling is investigated, showing that typical wastewater fractions are modified by primary treatment. As they clearly impact the downstream processes, both model improvements demonstrate the need for more detailed primary settler models in view of whole plant modelling.

Impact of coexistence of flocs and biofilm on performance of combined nitritation-anammox granular sludge reactors

Nitrogen (N) removal from high-strength wastewater can be accomplished in single-stage combined nitritation-anammox reactors with suspended growth biomass composed of floccular sludge, granular sludge, or of any mix of these 2 different sludge fractions. To date, the influence of floccular biomass on granular sludge reactor performance and stability has not been investigated experimentally or numerically. To address this knowledge gap, two 1D multi-species models were developed in Aquasim to assess the importance of small levels of flocs in putatively granular sludge combined nitritation-anammox reactors for different bulk oxygen concentrations and organics loads. The models included the growth and decay of aerobic ammonium-oxidizing organism (AOO), nitrite-oxidizing organisms (NOO), heterotrophic organisms (OHO), and anammox organisms (AMO) in exclusively granular sludge reactors, and in granular sludge reactors with small levels (∼5% of total biomass) of flocs. While maximum N removal efficiencies were similar for both model structures, floc addition led to a lower optimal dissolved oxygen concentration (DO) as well as a narrower maximum N removal peak, suggesting that small levels of floccular material may decrease process robustness to bulk oxygen changes. For some DO levels, this led to drastic efficiency drops. Furthermore, floc addition also led to substantial segregation in activity and microbial population distribution, with AOO, NOO and OHO concentrated in flocs and AMO concentrated in granules. Increased organic loading (COD:N = 4:3) improved maximum N removal efficiency in both model structures, but yielded substantially different predictions for optimal DO setpoint and process robustness to variations in DO. Taken together, our results indicate that even small levels of floccular biomass in biofilm reactors can have profound implications for reactor performance and optimization and for segregation of linked microbial processes, and suggest that the common practice of neglecting small levels of floccular material in biofilm models and in practice may lead to erroneous predictions.

A model framework to describe growth-linked biodegradation of trace-level pollutants in the presence of coincidental carbon substrates and microbes

Pollutants such as pesticides and their degradation products occur ubiquitously in natural aquatic environments at trace concentrations (μg L(-1) and lower). Microbial biodegradation processes have long been known to contribute to the attenuation of pesticides in contaminated environments. However, challenges remain in developing engineered remediation strategies for pesticide-contaminated environments because the fundamental processes that regulate growth-linked biodegradation of pesticides in natural environments remain poorly understood. In this research, we developed a model framework to describe growth-linked biodegradation of pesticides at trace concentrations. We used experimental data reported in the literature or novel simulations to explore three fundamental kinetic processes in isolation. We then combine these kinetic processes into a unified model framework. The three kinetic processes described were: the growth-linked biodegradation of micropollutant at environmentally relevant concentrations; the effect of coincidental assimilable organic carbon substrates; and the effect of coincidental microbes that compete for assimilable organic carbon substrates. We used Monod kinetic models to describe substrate utilization and microbial growth rates for specific pesticide and degrader pairs. We then extended the model to include terms for utilization of assimilable organic carbon substrates by the specific degrader and coincidental microbes, growth on assimilable organic carbon substrates by the specific degrader and coincidental microbes, and endogenous metabolism. The proposed model framework enables interpretation and description of a range of experimental observations on micropollutant biodegradation. The model provides a useful tool to identify environmental conditions with respect to the occurrence of assimilable organic carbon and coincidental microbes that may result in enhanced or reduced micropollutant biodegradation.

Biodegradability of wastewater and activated sludge organics in anaerobic digestion

The investigation provides experimental evidence that the unbiodegradable particulate organics fractions of primary sludge and waste activated sludge calculated from activated sludge models remain essentially unbiodegradable in anaerobic digestion. This was tested by feeding the waste activated sludge (WAS) from three different laboratory activated sludge (AS) systems to three separate anaerobic digesters (AD). Two of the AS systems were Modified Ludzack - Ettinger (MLE) nitrification-denitrification (ND) systems and the third was a membrane University of Cape Town (UCT) ND and enhanced biological P removal system. One of the MLE systems and the UCT system were fed the same real settled wastewater. The other MLE system was fed raw wastewater which was made by adding a measured constant flux (gCOD/d) of macerated primary sludge (PS) to the real settled wastewater. This PS was also fed to a fourth AD and a blend of PS and WAS from settled wastewater MLE system was fed to a fifth AD. The five ADs were each operated at five different sludge ages (10-60d). From the measured performance results of the AS systems, the unbiodegradable particulate organic (UPO) COD fractions of the raw and settled wastewaters, the PS and the WAS from the three AS systems were calculated with AS models. These AS model based UPO fractions of the PS and WAS were compared with the UPO fractions calculated from the performance results of the ADs fed these sludges. For the PS, the UPO fraction calculated from the AS and AD models matched closely, i.e. 0.30 and 0.31. Provided the UPO of heterotrophic (OHO, fE_OHO) and phosphorus accumulating (PAO, fE_PAO) biomass were accepted to be those associated with the death regeneration model of organism "decay", the UPO of the WAS calculated from the AS and AD models also matched well - if the steady state AS model fE_OHO = 0.20 and fE_PAO = 0.25 values were used, then the UPO fraction of the WAS calculated from the AS models deviated significantly from those calculated with the AD models. Therefore in plant wide wastewater treatment models the characterization of PS and WAS as defined by the AS models can be applied without modification in AD models. The observed rate limiting hydrolysis/acidogenesis rates of the sludges are listed.

New mechanistically based model for predicting reduction of biosolids waste by ozonation of return activated sludge

Two pilot-scale activated sludge reactors were operated for 98 days to provide the necessary data to develop and validate a new mathematical model predicting the reduction of biosolids production by ozonation of the return activated sludge (RAS). Three ozone doses were tested during the study. In addition to the pilot-scale study, laboratory-scale experiments were conducted with mixed liquor suspended solids and with pure cultures to parameterize the biomass inactivation process during exposure to ozone. The experiments revealed that biomass inactivation occurred even at the lowest doses, but that it was not associated with extensive COD solubilization. For validation, the model was used to simulate the temporal dynamics of the pilot-scale operational data. Increasing the description accuracy of the inactivation process improved the precision of the model in predicting the operational data.

Calibration and validation of a phenomenological influent pollutant disturbance scenario generator using full-scale data

The objective of this paper is to demonstrate the full-scale feasibility of the phenomenological dynamic influent pollutant disturbance scenario generator (DIPDSG) that was originally used to create the influent data of the International Water Association (IWA) Benchmark Simulation Model No. 2 (BSM2). In this study, the influent characteristics of two large Scandinavian treatment facilities are studied for a period of two years. A step-wise procedure based on adjusting the most sensitive parameters at different time scales is followed to calibrate/validate the DIPDSG model blocks for: 1) flow rate; 2) pollutants (carbon, nitrogen); 3) temperature; and, 4) transport. Simulation results show that the model successfully describes daily/weekly and seasonal variations and the effect of rainfall and snow melting on the influent flow rate, pollutant concentrations and temperature profiles. Furthermore, additional phenomena such as size and accumulation/flush of particulates of/in the upstream catchment and sewer system are incorporated in the simulated time series. Finally, this study is complemented with: 1) the generation of additional future scenarios showing the effects of different rainfall patterns (climate change) or influent biodegradability (process uncertainty) on the generated time series; 2) a demonstration of how to reduce the cost/workload of measuring campaigns by filling the gaps due to missing data in the influent profiles; and, 3) a critical discussion of the presented results balancing model structure/calibration procedure complexity and prediction capabilities.

Enhanced biological phosphorus removal and its modeling for the activated sludge and membrane bioreactor processes

A modified activated sludge process (ASP) for enhanced biological phosphorus removal (EBPR) needs to sustain stable performance for wastewater treatment to avoid eutrophication in the aquatic environment. Unfortunately, the overall efficiency of the EBPR in ASPs and membrane bioreactors (MBRs) is frequently hindered by different operational/system constraints. Moreover, although phosphorus removal data from several wastewater treatment systems are available, a comprehensive mathematical model of the process is still lacking. This paper presents a critical review that highlights the core issues of the biological phosphorus removal in ASPs and MBRs while discussing the inhibitory process requirements for other nutrients' removal. This mini review also successfully provided an assessment of the available models for predicting phosphorus removal in both ASP and MBR systems. The advantages and limitations of the existing models were discussed together with the inclusion of few guidelines for their improvement.

Integration of freshwater environmental policies and wastewater treatment plant management

In the last decade the political awareness of river water quality issues has grown substantially over the world and legislation is accordingly adapting. In the European Union (EU), two different directives regulate separately the characteristics of the discharged water and the chemical status of the receiving freshwater ecosystem. On the one hand, the characteristics of the urban effluents are regulated by the EU Directive 91/271/EEC, which defines limits on different elements set in the form of both static emission limits and minimum percentage load reductions. On the other hand, the characteristics of the receiving freshwater ecosystems are described in the EU Water Framework Directive (2000/60/EEC), which sets minimum 'good' chemical and ecological status in water bodies that should be achieved by 2015, and aims for an ecosystem-based management. With the support of an example, we show that there is a gap in these EU environmental policies leading to non-integrated management, which may result on adverse environmental and economical consequences. We believe that these policies should be updated and tuned to account for an integrated perspective, allowing a more efficient and sustainable management of wastewater treatment plants, maximizing the ecological, economical and social benefits of the system as a whole.

Modelling the population dynamics and metabolic diversity of organisms relevant in anaerobic/anoxic/aerobic enhanced biological phosphorus removal processes

In this study, enhanced biological phosphorus removal (EBPR) metabolic models are expanded in order to incorporate the competition between polyphosphate accumulating organisms (PAOs) and glycogen accumulating organisms (GAOs) under sequential anaerobic/anoxic/aerobic conditions, which are representative of most full-scale EBPR plants. Since PAOs and GAOs display different denitrification tendencies, which is dependent on the phylogenetic identity of the organism, the model was separated into six distinct biomass groups, constituting Accumulibacter Types I and II, as well as denitrifying and non-denitrifying Competibacter and Defluviicoccus GAOs. Denitrification was modelled as a multi-step process, with nitrate (NO(3)), nitrite (NO(2)), nitrous oxide (N(2)O) and di-nitrogen gas (N(2)) being the primary components. The model was calibrated and validated using literature data from enriched cultures of PAOs and GAOs, obtaining a good description of the observed biochemical transformations. A strong correlation was observed between Accumulibacter Types I and II, and nitrate-reducing and non-nitrate-reducing PAOs, respectively, where the abundance of each PAO subgroup was well predicted by the model during an acclimatization period from anaerobic-aerobic to anaerobic-anoxic conditions. Interestingly, a strong interdependency was observed between the anaerobic, anoxic and aerobic kinetic parameters of PAOs and GAOs. This could be exploited when metabolic models are calibrated, since all of these parameters should be changed by an identical factor from their default value. Factors that influence these kinetic parameters include the fraction of active biomass, relative aerobic/anoxic fraction and the ratio of acetyl-CoA to propionyl-CoA. Employing a metabolic approach was found to be advantageous in describing the performance and population dynamics in such complex microbial ecosystems.