High quality data is of crucial importance for model development: it provides a model input and is a prerequisite for model calibration and validation. Data reconciliation is often a very ...time-consuming task, so even when on-line data is available, the option is often chosen to synthetically generate data, losing a lot of information contained in the available data. This contribution showcases a Python™ package that allows a streamlined work-flow and provides possibilities for data analysis, validation and gap filling, with as main goals to use as much of the data as possible and to fill gaps in the data with a known reliability. This provides a means towards more data use and a more sound calibration and validation, while significantly reducing time spent on data reconciliation. The package is published and made openly available on GitHub. This avoids multiple implementations while being accessible to the community for suggested improvements.
•Data analysis is time-consuming, leading to the use of generated data as model input and thus to loss of information.•A Python software package with a flexible workflow is presented to analyze on-line data and fill gaps caused by filtering.•The filling algorithms implemented can be checked for their reliability when used to fill gaps in the data at hand.•The main impact for the user is increased use of information contained in the data and time saving.•The package is made openly available on GitHub and PyPI under an open GNU-GPLv3.0 license.
At wastewater treatment plants (WWTPs) aeration is the largest energy consumer. This high energy consumption requires an accurate assessment in view of plant optimization. Despite the ever increasing ...detail in process models, models for energy production still lack detail to enable a global optimization of WWTPs. A new dynamic model for a more accurate prediction of aeration energy costs in activated sludge systems, equipped with submerged air distributing diffusers (producing coarse or fine bubbles) connected via piping to blowers, has been developed and demonstrated. This paper addresses the model structure, its calibration and application to the WWTP of Mekolalde (Spain). The new model proved to give an accurate prediction of the real energy consumption by the blowers and captures the trends better than the constant average power consumption models currently being used. This enhanced prediction of energy peak demand, which dominates the price setting of energy, illustrates that the dynamic model is preferably used in multi-criteria optimization exercises for minimizing the energy consumption.
At wastewater treatment plants (WWTPs), the aerobic conversion processes in the bioreactor are driven by the presence of dissolved oxygen (DO). Within these conversion processes, the oxygen transfer ...is a rate limiting step as well as being the largest energy consumer. Despite this high importance, WWTP models often lack detail on the aeration part. An extensive measurement campaign with off-gas tests was performed at the WWTP of Eindhoven to provide more information on the performance and behaviour of the aeration system. A high spatial and temporal variability in the oxygen transfer efficiency was observed. Applying this gathered system knowledge in the aeration model resulted in an improved prediction of the DO concentrations. Moreover, an important consequence of this was that ammonium predictions could be improved by resetting the ammonium half-saturation index for autotrophs to its default value. This again proves the importance of balancing sub-models with respect to the need for model calibration as well as model predictive power.
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.
A benchmark simulation model, which includes a wastewater treatment plant (WWTP)-wide model and a rising main sewer model, is proposed for testing mitigation strategies to reduce the system's ...greenhouse gas (GHG) emissions. The sewer model was run to predict methane emissions, and its output was used as the WWTP model input. An activated sludge model for GHG (ASMG) was used to describe nitrous oxide (N(2)O) generation and release in activated sludge process. N(2)O production through both heterotrophic and autotrophic pathways was included. Other GHG emissions were estimated using empirical relationships. Different scenarios were evaluated comparing GHG emissions, effluent quality and energy consumption. Aeration control played a clear role in N(2)O emissions, through concentrations and distributions of dissolved oxygen (DO) along the length of the bioreactor. The average value of N(2)O emission under dynamic influent cannot be simulated by a steady-state model subjected to a similar influent quality, stressing the importance of dynamic simulation and control. As the GHG models have yet to be validated, these results carry a degree of uncertainty; however, they fulfilled the objective of this study, i.e. to demonstrate the potential of a dynamic system-wide modelling and benchmarking approach for balancing water quality, operational costs and GHG emissions.
The KALLISTO project aims at finding cost-efficient sets of measures to meet the Water Framework Directive (WFD) derived goals for the river Dommel. Within the project, both acute and long term ...impacts of the urban wastewater system on the chemical and ecological quality of the river are studied with an integral monitoring campaign in the urban wastewater system (WWTP and sewers) and in the river. Based on this monitoring campaign, detailed models were calibrated. These models are partly simplified and integrated in a single model, which is validated using the detailed submodels. The integrated model was used to study the potential for impact-based real-time control (RTC). Impact based RTC proved to be able to improve the quality of the receiving waters significantly, although additional measures remain necessary to be able to meet the WFD requirements.
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•Advanced modelling tools can be used for better investigating GHG emissions in WRRFs.•A model-based protocol was developed for mitigation of GHG emissions of WRRFs.•Detailed ...hydrodynamic studies showed great insights on the impact of mixing patterns.•Risk assessment model helped define operational conditions with high N2O emission risk.•Model-based scenario analysis was used to test the impact of mitigation strategies.
Water Resource Recovery Facilities (WRRFs) are big contributors to greenhouse gas (GHG) emissions and energy consumption. Aeration is the main source of energy consumption in these facilities and nitrous oxide (N2O) is the main form of direct emission which is produced during nitrification and denitrification processes through multiple potential pathways. Mathematical modelling is a widely used tool for optimisation of WRRFs and modelling protocols have been developed, which are widely used in the community. However, carbon footprint reduction has not been the main focus of these protocols. In this study, an innovative model-based protocol for minimising GHG emissions of WRRFs was developed using advanced mathematical modelling paradigms. The protocol was constructed based on three different cases for each of which a flow sheet model, a computational fluid dynamics (CFD) model and a knowledge-based risk assessment model were studied together with high frequency data collected by LESSDRONE (an automated wireless tool for measuring direct off-gas emissions). The risk assessment model helps identify high risk conditions while the CFD model provides valuable insights on the impact of hydrodynamics under non-ideal mixing conditions. The flow sheet model is used to test the proposed mitigation strategies and to provide in-silico data for the risk assessment model. The developed model- based protocol provides a robust guideline for water utilities to optimise their operations for minimising carbon footprint of WRRFs without compromising their removal efficiencies.
Aeration is an essential component of aerobic biological wastewater treatment and is the largest energy consumer at most water resource recovery facilities. Most modelling studies neglect the ...inherent complexity of the aeration systems used. Typically, the blowers, air piping, and diffusers are not modelled in detail, completely mixed reactors in a series are used to represent plug-flow reactors, and empirical correlations are used to describe the impact of operating conditions on bubble formation and transport, and oxygen transfer from the bubbles to the bulk liquid. However, the mechanisms involved are very complex in nature and require significant research efforts. This contribution highlights why and where there is a need for more detail in the different aspects of the aeration system and compiles recent efforts to develop physical models of the entire aeration system (blower, valves, air piping and diffusers), as well as adding rigour to the oxygen transfer efficiency modelling (impact of viscosity, bubble size distribution, shear and hydrodynamics). As a result of these model extensions, more realistic predictions of dissolved oxygen profiles and energy consumption have been achieved. Finally, the current needs for further model development are highlighted.
The wastewater industry is currently facing dramatic changes, shifting away from energy-intensive wastewater treatment towards low-energy, sustainable technologies capable of achieving energy ...positive operation and resource recovery. The latter will shift the focus of the wastewater industry to how one could manage and extract resources from the wastewater, as opposed to the conventional paradigm of treatment. Debatable questions arise: can the more complex models be calibrated, or will additional unknowns be introduced? After almost 30 years using well-known International Water Association (IWA) models, should the community move to other components, processes, or model structures like 'black box' models, computational fluid dynamics techniques, etc.? Can new data sources - e.g. on-line sensor data, chemical and molecular analyses, new analytical techniques, off-gas analysis - keep up with the increasing process complexity? Are different methods for data management, data reconciliation, and fault detection mature enough for coping with such a large amount of information? Are the available calibration techniques able to cope with such complex models? This paper describes the thoughts and opinions collected during the closing session of the 6th IWA/WEF Water Resource Recovery Modelling Seminar 2018. It presents a concerted and collective effort by individuals from many different sectors of the wastewater industry to offer past and present insights, as well as an outlook into the future of wastewater modelling.
The current model of the full-scale wastewater treatment plant (WWTP) model in Eindhoven uses a state-of-the-art model for the biological processes (ASM2d) and is calibrated for C- and N- removal in ...dry weather. However, for the ‘Kallisto’ project, which is an innovation programme aiming at a smart improvement of the surface water quality of the river Dommel by applying cost effective integrated system measures, the WWTP model needs to be improved to predict the WWTP performance under all conditions foreseen in the scenarios (e.g. storm events). A project approach was developed with parallel improvements in the different submodels, based on the interaction between submodels and the availability of several on-line sensors in influent, in-process and effluent. This is in contrast to most WWTP modelling studies, where focus is only on one submodel. It should lead to a well-balanced dynamic model that is able to predict WWTP behaviour under various conditions and that will be included in the integrated model, which will serve as an important decision support tool.
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