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Wastewater surveillance of pathogens may be a useful tool to help determine whether clinical surveillance of disease is effective or inadequate due to under-reporting and under-detection. In addition, tracking of pathogen concentrations over time could potentially provide a measure of the effectiveness of public health control measures and the impact of the gradual relaxation of these controls. Analysis of wastewater using quantitative molecular methods offers a real-time measure of infections in the community, and thus is expected to provide a more sensitive and rapid indication of changes in infection rates before such effects become detectable by clinical health surveillance. Models may help to back-calculate wastewater prevalence to population prevalence or to correct pathogen counts for wastewater catchment-specific and temporal effects. They may also help to design the wastewater sampling strategy. This article provides a brief summary of the history of pathogen wastewater surveillance to help set the context for the SARS-CoV-2 wastewater-based epidemiology (WBE) programmes currently being undertaken globally. HIGHLIGHTS A brief history of pathogen wastewater surveillance.; Context for current SARS-CoV-2 wastewater-based epidemiology (WBE) programmes.; Recommendations on research and investigation priorities.; Wide potential of modelling is presented together with remaining knowledge gaps.

Freshwater species are highly impacted by human activities and the consequences on ecosystem functioning are still not well understood. In the literature, a multitrophic perspective appears to be key to advance future biodiversity and ecosystem functioning (BEF) research. This paper aims at studying indirect effects of the synthetic hormone 17&alpha, ethinylestradiol (EE2) on a freshwater food web by creating BEF links, through the interpretation of seasonal cycles and multitrophic interactions. An ecosystem model previously developed using experimental data from a unique whole-ecosystem study on EE2 was extended with the addition of Chaoborus, an omnivorous insect. During the experimental study, a collapse of fathead minnow was measured after one year of exposure. The simulation results showed that EE2 indirect effects on other fishes (horizontal diversity) and lower trophic levels (vertical diversity) were connected to multitrophic interactions with a top-down cascade effect. The results also demonstrated that adding an omnivorous, mid-trophic level group such as Chaoborus enhances resilience. Conversely, missing such a species means that the actual resilience of an ecosystem and its functioning cannot be properly simulated. Thus, the extended ecosystem model offers a tool that can help better understand what is happening after environmental perturbations, such as with EE2.

Modelling flow rates in catchments and sewers with a conceptual, also known as hydrological, approach is widely applied if fast simulations are important. In cases where a detailed hydrodynamic model exists, it is common to start conceptualizing from this detailed counterpart. Unfortunately, no generalized procedure exists, which is surprising as this can be a complex and time-consuming task. This research work proposes a procedure that is validated with two independent combined sewer case studies. The conceptual models provide the targeted results with respect to representation of the flow rates and reduction in the computational time. As the desired performance could be reached for different levels of model aggregation, it is concluded that the conceptual model can be tailored to the points where accurate flow rates need to be predicted. Furthermore, the comparison of the conceptual model results with flow measurements highlights the importance of analyzing and eventually compensating for the limitations of the detailed model.

Five activated sludge models describing N2O production by ammonium oxidising bacteria (AOB) were compared to four different long-term process data sets. Each model considers one of the two known N2O production pathways by AOB, namely the AOB denitrification pathway and the hydroxylamine oxidation pathway, with specific kinetic expressions. Satisfactory calibration could be obtained in most cases, but none of the models was able to describe all the N2O data obtained in the different systems with a similar parameter set. Variability of the parameters can be related to difficulties related to undescribed local concentration heterogeneities, physiological adaptation of micro-organisms, a microbial population switch, or regulation between multiple AOB pathways. This variability could be due to a dependence of the N2O production pathways on the nitrite (or free nitrous acid-FNA) concentrations and other operational conditions in different systems. This work gives an overview of the potentialities and limits of single AOB pathway models. Indicating in which condition each single pathway model is likely to explain the experimental observations, this work will also facilitate future work on models in which the two main N2O pathways active in AOB are represented together.

In various cases in environmental modeling, modelers need to account for multiple variables and multiple objectives in systems with many processes occurring at different time scales. To assist the modeler to choose a relevant pool of efficiency criteria, a method is proposed to identify dissimilar criteria. A total of 30 efficiency criteria used in environmental modeling are critically reviewed and classified into six groups according to different modeling objectives. After accounting for equivalence of functional form 18 criteria remain for further analysis. To quantify the dissimilarity for the remaining criteria a methodology based on the ratio of shared parameter sets in regions of good performance is proposed. Then, for a wastewater treatment plant case-study the dissimilarity of efficiency criteria is analyzed as a function of target variables and operating conditions. Display Omitted 30 efficiency criteria of model quality in environmental sciences are reviewed.After studying equivalence of functional form 18 efficiency criteria remain.A methodology is proposed to quantify dissimilarity between remaining criteria.The methodology is applied to a wastewater treatment plant case study.Dissimilarity is assessed as a function of target variables and operating conditions.

Membrane bioreactors (MBR) are being increasingly used for wastewater treatment. Mathematical modeling of MBR systems plays a key role in order to better explain their characteristics. Several MBR models have been presented in the literature focusing on different aspects: biological models, models which include soluble microbial products (SMP), physical models able to describe the membrane fouling and integrated models which couple the SMP models with the physical models. However, only a few integrated models have been developed which take into account the relationships between membrane fouling and biological processes. With respect to biological phosphorus removal in MBR systems, due to the complexity of the process, practical use of the models is still limited. There is a vast knowledge (and consequently vast amount of data) on nutrient removal for conventional-activated sludge systems but only limited information on phosphorus removal for MBRs. Calibration of these complex integrated models still remains the main bottleneck to their employment. The paper presents an integrated mathematical model able to simultaneously describe biological phosphorus removal, SMP formation/degradation and physical processes which also include the removal of organic matter. The model has been calibrated with data collected in a UCT-MBR pilot plant, located at the Palermo wastewater treatment plant, applying a modified version of a recently developed calibration protocol. The calibrated model provides acceptable correspondence with experimental data and can be considered a useful tool for MBR design and operation.

International audience; As the work of the IWA Task Group on Benchmarking of Control Strategies for wastewater treatment plants (WWTPs) is coming to an end, it is essential to disseminate the knowledge gained. For this reason, all authors of the IWA Scientific and Technical Report on benchmarking have come together to provide their insights, highlighting areas where knowledge may still be deficient and where new opportunities are emerging, and to propose potential avenues for future development and application of the general benchmarking framework and its associated tools. The paper focuses on the topics of temporal and spatial extension, process modifications within the WWTP, the realism of models, control strategy extensions and the potential for new evaluation tools within the existing benchmark system. We find that there are major opportunities for application within all of these areas, either from existing work already being done within the context of the benchmarking simulation models (BSMs) or applicable work in the wider literature. Of key importance is increasing capability, usability and transparency of the BSM package while avoiding unnecessary complexity.

International audience; This work critically reviews modelling concepts for standard activated sludge wastewater treatment processes (e.g. hydrolysis, growth and decay of organisms, etc.) for some of the most commonly used models. Based on a short overview on the theoretical biochemistry knowledge this review should help model users to better understand i) the model concepts used; ii) the differences between models and iii) the limits of the models. The seven analysed models are: (1) ASM1; (2) ASM2d; (3) ASM3; (4) ASM3+BioP; (5) ASM2d+TUD; (6) Barker&Dold model; (7) UCTPHO+. Nine standard processes are distinguished and discussed in the present work: hydrolysis; fermentation; ordinary heterotrophic organisms (OHO) growth; autotrophic nitrifying organisms (ANO) growth; OHO & ANO decay; poly-hydroxyalkanoates (PHA) storage; polyphosphate (polyP) storage; phosphorus accumulating organisms PAO) growth and PAO decay. For a structured comparison, a new schematic representation of these processes is proposed. Each process is represented as a reaction with consumed components on the left of the figure and produced components on the right. Standardised icons, based on shapes and colour codes, enable the representation of the stoichiometric modelling concepts and kinetics. This representation allows highlighting the conceptual differences of the models, and the level of simplification between the concepts and the theoretical knowledge. The model selection depending on their theoretical limitations and the main research needs to increase the model quality are finally discussed.

Even if fouling in membrane bioreactors (MBRs) has been extensively studied during the last decade, its causes and mechanisms are not well understood yet. Furthermore, few full-scale and long-term experiments have been published, and their results do not always match with the models developed from lab-scale studies. A statistical approach linking long-term and short-term permeability evolution with operational variables in full-scale membrane bioreactors for domestic waste-water treatment is presented. Data originate from a 66,700 P.E. MBR plant monitored for more than one year. Permeability and several fouling indicators were calculated in each of the four hollow-fibre membrane tanks of the plant. The influence of SRT, temperature, MLSS, F:M ratio, iron dosing and membrane flux on daily permeability evolutions, instantaneous permeability evolution and hydraulic backwash efficiency was studied. In order to minimise the bias due to correlations between input variables, a statistical approach using principal component regression and partial least-square regression was tested. Flux, temperature, SRT and F:M ratio are the most influential input variables on long-term permeability evolutions. Iron dose and MLSS are less correlated with fouling indicators. The proposed approach may be improved by integrating the history of the membrane to better describe and predict the permeability evolution. (C) 2013 Elsevier B.V. All rights reserved.

International audience; Process models used for activated sludge, anaerobic digestion and in general wastewater treatment plant process design and optimization have traditionally focused on important biokinetic conversions. There is a growing realization that abiotic processes occurring in the wastewater (i.e. 'solvent') have a fundamental effect on plant performance. These processes include weak acid-base reactions (ionization), spontaneous or chemical dose-induced precipitate formation and chemical redox conversions, which influence pH, gas transfer, and directly or indirectly the biokinetic processes themselves. There is a large amount of fundamental information available (from chemical and other disciplines), which, due to its complexity and its diverse sources (originating from many different water and process environments), cannot be readily used in wastewater process design as yet. This position paper outlines the need, the methods, available knowledge and the fundamental approaches that would help to focus the effort of research groups to develop a physicochemical framework specifically in support of whole-plant process modeling. The findings are that, in general, existing models such as produced by the International Water Association for biological processes are limited by omission of key corrections such as non-ideal acid-base behavior, as well as major processes (e. g., ion precipitation). While the underlying chemistry is well understood, its applicability to wastewater applications is less well known. This justifies important further research, with both experimental and model development activities to clarify an approach to modeling of physicochemical processes.

Several methods to detect faults have been developed in various fields, mainly in chemical and process engineering. However, minimal practical guidelines exist for their selection and application. This work presents an index that allows for evaluating monitoring and diagnosis performance of fault detection methods, which takes into account several characteristics, such as false alarms, false acceptance, and undesirable switching from correct detection to non-detection during a fault event. The usefulness of the index to process engineering is demonstrated first by application to a simple example. Then, it is used to compare five univariate fault detection methods (Shewhart, EWMA, and residuals of EWMA) applied to the simulated results of the Benchmark Simulation Model No. 1 long-term (BSM1_LT). The BSM1_LT, provided by the IWA Task Group on Benchmarking of Control Strategies, is a simulation platform that allows for creating sensor and actuator faults and process disturbances in a wastewater treatment plant. The results from the method comparison using BSM1_LT show better performance to detect a sensor measurement shift for adaptive methods (residuals of EWMA) and when monitoring the actuator signals in a control loop (e.g., airflow). Overall, the proposed index is able to screen fault detection methods. © 2010 Wiley Periodicals, Inc., This research is supported by the Canada Research Chair in Water Quality Modeling and a NSERC Special Research Opportunities grant as part of the Canadian contribution to the European Union 6th framework project NEPTUNE. Lluis Corominas benefits from the postdoctoral fellowship "Beatriu de Pinos" of the Government of Catalonia. The authors would like to thank Ulf Jeppsson for his contribution to the development of the BSM1_LT platform and the evaluation index.

Mathematical models provide insight into numerous biological, physical and chemical systems. They can be used in process design, optimisation, control and decision support, as acknowledged in many different fields of scientific research. Mathematical models do not always yield reliable results and uncertainty should be taken into account. At present, it is possible to identify some factors contributing to uncertainty, and the awareness of the necessity of uncertainty assessment is rising. In the fields of Environmental Modelling and Computational Fluid Dynamics, for instance, terminology related to uncertainty exists and is generally accepted. However, the uncertainty due to the choice of the numerical solver and its settings used to compute the solution of the models did not receive much attention in the past. A motivating example on the existence and effect of numerical uncertainty is provided and clearly shows that we can no longer ignore it. This paper introduces a new terminology to support communication about uncertainty caused by numerical solvers, so that scientists become perceptive to it.

The main requirement for metabolic flux analysis (MFA) is that the cells are in a pseudo-steady state, that there is no accumulation or depletion of intracellular metabolites. In the past, the applications of MFA were limited to the analysis of continuous cultures. This contribution introduces the concept of dynamic MFA and extends MFA so that it is applicable to transient cultures. Time series of concentration measurements are transformed into flux values. This transformation involves differentiation, which typically increases the noisiness of the data. Therefore, a noise-reducing step is needed. In this work, polynomial smoothing was used. As a test case, dynamic MFA is applied onEscherichia colicultivations shifting from carbon limitation to nitrogen limitation and vice versa. After switching the limiting substrate from N to C, a lag phase was observed accompanied with an increase in maintenance energy requirement. This lag phase did not occur in the C- to N-limitation case.

International audience; The COST/IWA Benchmark Simulation Model No 1 (BSM1) has been available for almost a decade. Its primary purpose has been to create a platform for control strategy benchmarking of activated sludge processes. The fact that the research work related to the benchmark simulation models has resulted in more than 300 publications worldwide demonstrates the interest in and need of such tools within the research community. Recent efforts within the IWA Task Group on "Benchmarking of control strategies for WWTPs" have focused on an extension of the benchmark simulation model. This extension aims at facilitating control strategy development and performance evaluation at a plant-wide level and, consequently, includes both pretreatment of wastewater as well as the processes describing sludge treatment. The motivation for the extension is the increasing interest and need to operate and control wastewater treatment systems not only at an individual process level but also on a plant-wide basis. To facilitate the changes, the evaluation period has been extended to one year. A prolonged evaluation period allows for long-term control strategies to be assessed and enables the use of control handles that cannot be evaluated in a realistic fashion in the one week BSM1 evaluation period. In this paper, the finalised plant layout is summarised and, as was done for BSM1, a default control strategy is proposed. A demonstration of how BSM2 can be used to evaluate control strategies is also given.

International audience; This study aims at synthesizing experiences in the practical application of ASM type models. The information is made easily accessible to model users by creating a database of modelling projects. This database includes answers to a questionnaire that was sent out to model users in 2008 to provide inputs for a Scientific and Technical Report of the IWA Task Group on Good Modelling Practice Guidelines for use of activated sludge models, and a literature review on published modelling projects. The database is analysed to determine which biokinetic model parameters are usually changed by modellers, in which ranges, and what values are typically used for seven selected activated sludge models. These results should help model users in the calibration step, by providing typical parameter values as a starting point and ranges as a guide. However, the proposed values should be used with great care since they are the result of averaging practical experience and not taking into account specific parameter correlations.

International audience; The quality of simulation results can be significantly affected by errors in the published model (typing, inconsistencies, gaps or conceptual errors) and/or in the underlying numerical model description. Seven of the most commonly used activated sludge models have been investigated to point out the typing errors, inconsistencies and gaps in the model publications: (1) ASM1 (Henze et al., 1987; republished in Henze et al., 2000a); (2) ASM2d (Henze et al., 1999; republished in Henze et al., 2000b); (3) ASM3 (Gujer et al., 1999; corrected version published in Gujer et al., 2000); (4) ASM3+Bio-P (Rieger et al., 2001); (5) ASM2d+TUD (Meijer, 2004); (6) New General (Barker and Dold, 1997); (7) UCTPHO+ (Hu et al., 2007). A systematic approach to verify models by tracking typing errors and inconsistencies in model development and software implementation is proposed. Then, stoichiometry and kinetic rate expressions are checked for each model and the errors found are reported in detail. An attached spreadsheet (http://www.iwaponline.com/wst/06104/0898.xls) provides corrected matrices with the calculations of all stoichiometric coefficients for the discussed biokinetic models and gives an example of proper continuity checks.

International audience; This paper serves as a problem statement of the issues surrounding uncertainty in wastewater treatment modelling. The paper proposes a structure for identifying the sources of uncertainty introduced during each step of an engineering project concerned with model-based design or optimisation of a wastewater treatment system. It briefly references the methods currently used to evaluate prediction accuracy and uncertainty and discusses the relevance of uncertainty evaluations in model applications. The paper aims to raise awareness and initiate a comprehensive discussion among professionals on model prediction accuracy and uncertainty issues. It also aims to identify future research needs. Ultimately the goal of such a discussion would be to generate transparent and objective methods of explicitly evaluating the reliability of model results, before they are implemented in an engineering decision-making context.

In different river catchments in Europe, pesticide concentrations in surface waters frequently exceed the standards, possibly resulting in negative impacts on aquatic fauna and flora. Pesticides can enter river systems both immediately after application, i.e. as a direct loss, or with some time delay due to runoff or leaching. We define a direct loss as the sum of point losses and drift losses on an application day that will reach the river immediately after or during application. Point losses are due to the clean-up of spray equipment, leaking tools, waste water treatment plants etc. Different studies demonstrated the importance of direct losses. In small river systems, their contribution accounts for 30 to 90% of the pesticide load to surface water. As many studies and models only partly take into account these direct losses or even not at all, we attempted to model the dynamic occurrence of pesticides also coming from these sources. For this purpose, some modifications and extensions to the SWAT (Soil and Water Assessment Tool) model were made. Special attention was paid to closing mass balances and implementing an estimator for total direct losses, drift and point losses. To verify the modifications we focused on the use of the herbicide atrazine in the Nil, a small and hilly river basin in the centre of Belgium. The modified SWAT code resulted in a better correspondence between measured and simulated atrazine concentrations and loads, in particular for direct losses. For the year 1998, the Nash-Sutcliffe coefficient improved from a value of -2.63 to 0.66. In addition, the modelling results of the test case revealed that the contribution of drift losses to the total pesticide load in the river system is rather small: even without a 'non spray zone', they account for only 1% of the total load. Point sources, on the other hand, contribute for 22% up to 70% of the pesticide load and need to be considered in pesticide pollution management. The resulting model needs further testing for other pesticides and other catchments. In future, the model can be used for comparison of different measures that can be taken to minimise pesticide fluxes towards river systems and in performing realistic risk assessments.

Over a decade ago, the concept of objectively evaluating the performance of control strategies by simulating them using a standard model implementation was introduced for activated sludge wastewater treatment plants. The resulting Benchmark Simulation Model No 1 (BSM1) has been the basis for a significant new development that is reported on here: Rather than only evaluating control strategies at the level of the activated sludge unit (bioreactors and secondary clarifier) the new BSM2 now allows the evaluation of control strategies at the level of the whole plant, including primary clarifier and sludge treatment with anaerobic sludge digestion. In this contribution, the decisions that have been made over the past three years regarding the models used within the BSM2 are presented and argued, with particular emphasis on the ADM1 description of the digester, the interfaces between activated sludge and digester models, the included temperature dependencies and the reject water storage. BSM2-implementations are now available in a wide range of simulation platforms and a ring test has verified their proper implementation, consistent with the BSM2 definition. This guarantees that users can focus on the control strategy evaluation rather than on modelling issues. Finally, for illustration, twelve simple operational strategies have been implemented in BSM2 and their performance evaluated. Results show that it is an interesting control engineering challenge to further improve the performance of the BSM2 plant (which is the whole idea behind benchmarking) and that integrated control (i.e. acting at different places in the whole plant) is certainly worthwhile to achieve overall improvement.

Banana production is very important for the Ecuadorian national income, but it is also a potential source of river pollution in the country. Current research is focusing on the use of GIS to perform pesticide assessment of a river basin that includes banana as its main agricultural activity. The Agricultural Non Point Source Model (AGNPS) is being used to perform pesticide assessment in the basin. The model structure and type of needed data was identified. By applying GIS methodology, a complete set of cartographical information was obtained to supply input data to the pesticide model. In addition, ready-to-print maps were useful by-products for farmers.

The dynamic behaviour of pesticides in river systems strongly depends on varying climatological conditions and agricultural management practices. To describe this behaviour at the river-basin scale, integrated hydrological and water quality models are needed. A crucial step in understanding the various processes determining pesticide fate is to perform a sensitivity analysis. Sensitivity analysis for hydrology and pesticide supply in SWAT (Soil and Water Assessment Tool) will provide useful support for the development of a reliable hydrological model and will give insight in which parameters are most sensitive concerning pesticide supply towards rivers. The study was performed on the Nil catchment in Belgium. In this study we utilised an LH-OAT sensitivity analysis. The LH-OAT method combines the One-factor-At-a-Time (OAT) design and Latin Hypercube (LH) sampling by taking the Latin Hypercube samples as initial points for an OAT design. By means of the LH-OAT sensitivity analysis, the dominant hydrological parameters were determined and a reduction of the number of model parameters was performed. Dominant hydrological parameters were the curve number (CN2), the surface runoff lag (surlag), the recharge to deep aquifer (rchrg_dp) and the threshold depth of water in the shallow aquifer (GWQMN). Next, the selected parameters were estimated by manual calibration. Hereby, the Nash–Sutcliffe coefficient of efficiency improved from an initial value of −22.4 to +0.53. In the second part, sensitivity analyses were performed to provide insight in which parameters or model inputs contribute most to variance in pesticide output. The results of this study show that for the Nil catchment, hydrologic parameters are dominant in controlling pesticide predictions. The other parameter that affects pesticide concentrations in surface water is ‘apfp_pest’, which meaning was changed into a parameter that controls direct losses to the river system (e.g., through the clean up of spray equipment, leaking tools, processing of spray waste on paved surfaces). As a consequence, it is of utmost importance that hydrology is well calibrated while––in this case––a correct estimation of the direct losses is of importance as well. Besides, a study of only the pesticide related parameters, i.e. application rate (kg/ha), application time (day), etc., reveals that the application time has much more impact than the application rate, which has itself a higher impact than errors in the daily rainfall observations.

Modelling activated sludge systems has gained an increasing momentum after the introduction of activated sludge models (ASMs) in 1987. Application of dynamic models for full-scale systems requires essentially a calibration of the chosen ASM to the case under study. Numerous full-scale model applications have been performed so far which were mostly based on ad hoc approaches and expert knowledge. Further, each modelling study has followed a different calibration approach: e.g. different influent wastewater characterization methods, different kinetic parameter estimation methods, different selection of parameters to be calibrated, different priorities within the calibration steps, etc. In short, there was no standard approach in performing the calibration study, which makes it difficult, if not impossible, to (1) compare different calibrations of ASMs with each other and (2) perform internal quality checks for each calibration study. To address these concerns, systematic calibration protocols have recently been proposed to bring guidance to the modeling of activated sludge systems and in particular to the calibration of full-scale models. In this contribution four existing calibration approaches (BIOMATH, HSG, STOWA and WERF) will be critically discussed using a SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis. It will also be assessed in what way these approaches can be further developed in view of further improving the quality of ASM calibration. In this respect, the potential of automating some steps of the calibration procedure by use of mathematical algorithms is highlighted.

It is recognised that there is a need for a proper treatment and transparency of uncertainty in risk assessment and management, especially in view of the upcoming proposed new chemical policy REACH, which delegates the responsibility for conducting risk assessments to industry. The current EU risk assessment for new and existing substances is largely deterministic and prudential measures are implicitly embedded in calculation schemes and rules. In this paper, a more probabilistic approach to risk assessment is advocated. The advantage is twofold: 1) inherent variability and other uncertainty pertaining to exposure and effects are transparently taken into account, while at the same time 2) issues of caution are explicitly transferred to the risk management phase. The result of a probabilistic risk assessment as suggested is improved transparency with quantitative and qualitative uncertainty estimates. Such uncertainty information can be used to discuss precautionary measures in the context of risk management.

The goal of this work is the development of a suitable monitoring module, which is to be the first module of an integrated fault detection and control system for the SHARON process. To model the process properly, different PCA models are tested. As a first step, PCA is used in an iterative manner to exclude data not considered to represent normal operational conditions and process behaviour from the original data set. To improve the performance of the identified model, it is decided to account for dynamics in the SHARON process by means of auto-regressive exogenous (ARX) structuring of data before the identification. A fruitful replacement of missing values for this purpose is done by means of a static PCA model. It is shown that the different criteria used in model selection lead to the same DPCA model. In this paper all steps of the monitoring module design are explained and the performance of different models is analyzed.

International audience; This note presents and compares two models to predict the equilibrium temperature in aerated basins. They differ by their degree of complexity and therefore by the input data they require. Both models were able to estimate the temperature of an industrial aerated lagoon, the more complex model giving, in addition, a complete breakdown of the heat exchanges.

This paper illustrates the modeling and the control of the equalization system of a full scale industrial wastewater treatment plant. The structure of the system is very specific and a number of difficulties are pointed out and then solved using an optimal controller associated with a fuzzy based supervisory system. Simulation results are presented and evaluated.

This paper describes the design and evaluation of a control system for an equalization system at the wastewater treatment plant of a pharmaceutical production facility. The design includes actuator fault tolerance, and measures are included to deal with physical constraints and changing operating conditions. A combination of linear quadratic techniques, fuzzy logic and disturbance accomodation theory is used. The controller is evaluated through simulation and is currently under full-scale test.

The paper presents a concise overview of respirometric experiments for the calibration of ASM1. First, the popularity of respirometry is explained by its historical impact and its sensitivity and robustness. The body of the text consists of a systematic overview of existing methods for assessment of nearly all ASM1: (i) component concentrations in sludge and waste water; and (ii) biokinetic and stoichiometric parameters. Real-life examples illustrate the methods. A difference is made between direct methods that use explicit calculations and optimisation methods that require numerical optimisation algorithms. It is stressed that the latter approach is especially useful to extract multiple parameters and component concentrations from single respirometric experiments. Finally, the importance of reflecting on the translation of lab-scale respirometric results to a full-scale model is stressed.

The steps of calibration/confirmation of models in a suggested 11-step procedure for analysis, planning and implementation of integrated urban wastewater management systems is focused upon in this paper. Based on ample experience obtained in comprehensive investigations throughout Europe recommendations have been formulated for design of measuring campaigns. The inclusion of iteration in the overall planning of measuring campaigns is advised and the use of preliminary sensitivity analysis is shown to allow maximisation of information retrieval from experimental efforts. Case studies covering problems related to suspended solids, specific contaminants, hygienic hazards and total pollutant loss illustrate the recommendations presented.

Many respirometry-based control strategies have been proposed in the literature but few successful practical implementations or even simulation-based evaluations have been reported. The state-of-the-art provides insufficient justification for the development of a how-to-do procedure for such control strategies in full scale. It is, therefore, expected that carefully conducted simulation studies will greatly support the evaluation of proposed strategies and, eventually, the implementation in practice. These studies should be based on a rigorous methodology including simulation model, plant layout, controller and test procedure. This paper describes the development of such a methodology, termed “benchmark”. The benchmark is evaluated on the basis of a respirometry-based control strategy from the literature. Some simulation results are shown and modifications to the strategy imperative to the implementation in the benchmark are discussed. It is concluded that the benchmark provides a convenient means to perform a number of tests with the implemented control strategy. The benchmark should be further developed and tested.