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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.

A (non-exhaustive) survey of new and existing technologies for the monitoring of wastewater treatment plants is presented. Emphasis is given to the way these sensors can provide insight in the ongoing (bio-) processes. Three different uses for sensors can be found: for monitoring (operator support), in automatic control systems and as tools for plant auditing/optimization/modelling by consultants. From this, sensors have been classified in two basic types: (i) reliable, simple and low maintenance sensors for day-to-day monitoring and control and (ii) advanced, higher maintenance sensors that are used in auditing, model calibration and optimisation. The paper is organized according to the typical unit processes of biological wastewater treatment systems: anaerobic digestion, activated sludge, nutrient removal and sedimentation. Attention is drawn to a number of practical problems associated with the use of sophisticated sensors in the harsh (dirty) conditions of wastewater treatment processes. The use of autocalibration and built-in sensor checks, cleaning systems and reliable sample preparation units is illustrated. The paper ends with a discussion of the applicability of the different sensors.

Today, the main concepts required for describing the dynamics of drainage in an entire urban area are known and models are available that can reasonably simulate the behaviour of the urban water system. Still, such integrated modelling is a complex exercise not only due to the sheer size of the model, but also due to the different modelling approaches that reflect the history of the sub-models used and of the purpose they were built for. The paper reviews the state of the art in deterministic modelling, outlines experiences and discusses problems and future developments.

The objective of this paper was to investigate the usefulness of new multi-criteria measures to evaluate a control strategy through the Benchmark protocol. Using a case study in which respirometry-based control strategies are evaluated, the proposed measures were calculated. An economic index including weighted investment and operating costs (termed Total Cost Index – TCI) appears more powerful than a grey-scale presentation approach. Using the latter approach, it is hard to reflect the relative importance of the criteria investigated, which makes practical decisions rather difficult. In addition, a Robustness Index (RI) is proposed that allows us to evaluate the transferability of control strategies to situations different from the ones defined in the benchmark protocol. Finally, the case study shows that it may be advisable to replace the currently used open loop benchmark reference by a plant in which dissolved oxygen is controlled in all aerated reactors. This quite simple strategy also turned out to be the best one among all evaluated strategies.

A researcher or practitioner can employ a biofilm model to gain insight into what controls the performance of a biofilm process and for optimizing its performance. While a wide range of biofilm-modeling platforms is available, a good strategy is to choose the simplest model that includes sufficient components and processes to address the modeling goal. In most cases, a one-dimensional biofilm model provides the best balance, and good choices can range from hand-calculation analytical solutions, simple spreadsheets, and numerical-method platforms. What is missing today is clear guidance on how to apply a biofilm model to obtain accurate and meaningful results. Here, we present a five-step framework for good biofilm reactor modeling practice (GBRMP). The first four steps are (1) obtain information on the biofilm reactor system, (2) characterize the influent, (3) choose the plant and biofilm model, and (4) define the conversion processes. Each step demands that the model user understands the important components and processes in the system, one of the main benefits of doing biofilm modeling. The fifth step is to calibrate and validate the model: System-specific model parameters are adjusted within reasonable ranges so that model outputs match actual system performance. Calibration is not a simple ‘by the numbers’ process, and it requires that the modeler follows a logical hierarchy of steps. Calibration requires that the adjusted parameters remain within realistic ranges and that the calibration process be carried out in an iterative manner. Once each of steps 1 through 5 is completed satisfactorily, the calibrated model can be used for its intended purpose, such as optimizing performance, trouble-shooting poor performance, or gaining deeper understanding of what controls process performance.

This paper provides a comprehensive summary on modelling of micro-pollutants' (MPs) fate and transport in wastewater. It indicates the motivations of MP modelling and summarises and illustrates the current status. Finally, some recommendations are provided to improve and diffuse the use of such models. In brief, we conclude that, in order to predict the contaminant removal in centralised treatment works, considering the dramatic improvement in monitoring and detecting MPs in wastewater, more mechanistic approaches should be used to complement conventional, heuristic and other fate models. This is crucial, as regional risk assessments and model-based evaluations of pollution discharge from urban areas can potentially be used by decision makers to evaluate effluent quality regulation, and assess upgrading requirements, in the future.

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 waten 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.

Regulatory water quality limits are extended from the wastewater resource recovery facility (WRRF) to the sewer system. It is thus necessary to properly integrate those systems for the evaluation of the overall emissions to the receiving water. The integration of the sewer system and the WRRF, however, leaves us with multiple potential options to reduce these emissions. The proposed approach builds on previous research using global sensitivity analysis (GSA) as a screening method for available control handles. It considers parameter and input uncertainty to select control handles that generate large benefits even if the model differs from reality. Results from a real-life case study indicate that the three top-rated handles are comparably effective for all considered uncertainty and variability scenarios. But the results also showed that this does not apply to lower-rated handles.

Life cycle assessment (LCA) allows evaluating the potential environmental impacts of a product or a service in relation to its function and over its life cycle. In past LCAs applied to wastewater treatment plants (WWTPs), the system function definition has received little attention despite its great importance. This has led to some limitations in LCA results interpretation. A new methodology to perform LCA on WWTPs is proposed to avoid those limitations. It is based on net environmental benefit (NEB) evaluation and requires assessing the potential impact of releasing wastewater without and with treatment besides assessing the impact of the WWTP's life cycle. The NEB allows showing the environmental trade-offs between avoided impact due to wastewater treatment and induced impact by the WWTP's life cycle. NEB is compared with a standard LCA through the case study of a small municipal WWTP consisting of facultative aerated lagoons. The NEB and standard LCA show similar results for impact categories solely related to the WWTP's life cycle but differ in categories where wastewater treatment environmental benefit is accounted for as NEB considers influent wastewater quality whereas standard LCA does not.

Continuous monitoring of water quality creates huge amounts of data and therefore requires new concepts to guarantee high data quality and to prevent data graveyards. Monitoring stations commonly used in practice today suffer from insufficient flexibility and a lack of standardization. That is, although a lot of monitoring tasks are comparable and should lead to robust and powerful platforms, most monitoring stations are case specific developments. In this paper the underlying ideas of a new generation of monitoring networks is described. First a problem analysis of monitoring stations typically seen in current river monitoring practice is outlined, then the monEAU vision on monitoring networks will be discussed together with an overview of a planned system set-up with innovative data evaluation concept.