Energy optimization of a wastewater treatment plant based on energy audit data: small investment with high return.

Ambitious energy targets in the 2020 European climate and energy package have encouraged many stakeholders to explore and implement measures improving the energy efficiency of water and wastewater treatment facilities. Model-based process optimization can improve the energy efficiency of wastewater treatment plants (WWTP) with modest investment and a short payback period. However, such methods are not widely practiced due to the labor-intensive workload required for monitoring and data collection processes. This study offers a multi-step simulation-based methodology to evaluate and optimize the energy consumption of the largest Italian WWTP using limited, preliminary energy audit data. An integrated modeling platform linking wastewater treatment processes, energy demand, and production sub-models is developed. The model is calibrated using a stepwise procedure based on available data. Further, a scenario-based optimization approach is proposed to obtain the non-dominated and optimized performance of the WWTP. The results confirmed that up to 5000 MWh annual energy saving in addition to improved effluent quality could be achieved in the studied case through operational changes only.

Integrated ecological modelling for evidence-based determination of water management interventions in urbanized river basins: Case study in the Cuenca River basin (Ecuador).

The growth of urbanization worldwide has contributed to the deterioration of the ecological status of water bodies. Efforts at improving the ecological status have been made either in isolated form or by means of integrated measures by stakeholders, but in many cases, these measures have not been evaluated to determine their benefit. In this study, we implemented a scenario analysis to restore the ecological water quality in the Cuenca River and its tributaries, which are located in the southern Andes of Ecuador. For this analysis, an integrated ecological model (IEM) was developed. The IEM linked an urban wastewater system (IUWS) model, which gave satisfactory results in its calibration and validation processes, with ecological models. The IUWS is a mechanistic model that incorporated the river water quality model, a wastewater treatment plant (WWTP) with activated sludge technology, and discharges from the sewage system. The ecological status of the waterways was evaluated with the Andean Biotic Index (ABI), which was predicted using generalized linear models (GLMs). The GLMs were calculated with physicochemical results from the IUWS model. Four scenarios that would enhance the current ecological water quality were analyzed. In these scenarios, the inclusion of a new WWTP with carbon, and with carbon and nitrogen removal as well as the addition of retention tanks before the discharges of combined sewer overflows (CSOs) were assessed. The new WWTP with carbon and nitrogen removal would bring about a better restoration of the ecological water quality due to better nitrogen removal. The retention tanks would help to enhance the ecological status of the rivers during rainy seasons. The integrated model implemented in this study was shown to be an essential tool to support decisions in the Cuenca River basin management.

Modelling gas-liquid mass transfer in wastewater treatment: when current knowledge needs to encounter engineering practice and vice versa.

Gas-liquid mass transfer in wastewater treatment processes has received considerable attention over the last decades from both academia and industry. Indeed, improvements in modelling gas-liquid mass transfer can bring huge benefits in terms of reaction rates, plant energy expenditure, acid-base equilibria and greenhouse gas emissions. Despite these efforts, there is still no universally valid correlation between the design and operating parameters of a wastewater treatment plant and the gas-liquid mass transfer coefficients. That is why the current practice for oxygen mass transfer modelling is to apply overly simplified models, which come with multiple assumptions that are not valid for most applications. To deal with these complexities, correction factors were introduced over time. The most uncertain of them is the α-factor. To build fundamental gas-liquid mass transfer knowledge more advanced modelling paradigms have been applied more recently. Yet these come with a high level of complexity making them impractical for rapid process design and optimisation in an industrial setting. However, the knowledge gained from these more advanced models can help in improving the way the α-factor and thus gas-liquid mass transfer coefficient should be applied. That is why the presented work aims at clarifying the current state-of-the-art in gas-liquid mass transfer modelling of oxygen and other gases, but also to direct academic research efforts towards the needs of the industrial practitioners.

The future of WRRF modelling - outlook and challenges.

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.

Tanks in series versus compartmental model configuration: considering hydrodynamics helps in parameter estimation for an N2O model.

The choice of the spatial submodel of a water resource recovery facility (WRRF) model should be one of the primary concerns in WRRF modelling. However, currently used mechanistic models are limited by an over-simplified representation of local conditions. This is illustrated by the general difficulties in calibrating the latest N2O models and the large variability in parameter values reported in the literature. The use of compartmental model (CM) developed on the basis of accurate hydrodynamic studies using computational fluid dynamics (CFD) can take into account local conditions and recirculation patterns in the activated sludge tanks that are important with respect to the modelling objective. The conventional tanks in series (TIS) configuration does not allow this. The aim of the present work is to compare the capabilities of two model layouts (CM and TIS) in defining a realistic domain of parameter values representing the same full-scale plant. A model performance evaluation method is proposed to identify the good operational domain of each parameter in the two layouts. Already when evaluating for steady state, the CM was found to provide better defined parameter ranges than TIS. Dynamic simulations further confirmed the CM's capability to work in a more realistic parameter domain, avoiding unnecessary calibration to compensate for flaws in the spatial submodel.

A novel high-throughput method for kinetic characterisation of anaerobic bioproduction strains, applied to Clostridium kluyveri.

Hexanoic acid (HA), also called caproic acid, can be used as an antimicrobial agent and as a precursor to various chemicals, such as fuels, solvents and fragrances. HA can be produced from ethanol and acetate by the mesophilic anaerobic bacterium Clostridium kluyveri, via two successive elongation steps over butyrate. A high-throughput anaerobic growth curve technique was coupled to a data analysis framework to assess growth kinetics for a range of substrate and product concentrations. Using this method, growth rates and several kinetic parameters were determined for C. kluyveri. A maximum growth rate (µmax) of 0.24 ± 0.01 h-1 was found, with a half-saturation index for acetic acid (KS,AA) of 3.8 ± 0.9 mM. Inhibition by butyric acid occurred at of 124.7 ± 5.7 mM (KI,BA), while the final product, HA, linearly inhibited growth with complete inhibition above 91.3 ± 10.8 mM (KHA of 10.9*10-3 ± 1.3*10-3 mM-1) at pH = 7, indicating that the hexanoate anion also exerts toxicity. These parameters were used to create a dynamic mass-balance model for bioproduction of HA. By coupling data collection and analysis to this modelling framework, we have produced a powerful tool to assess the kinetics of anaerobic micro-organisms, demonstrated here with C. kluyveri, in order further explore the potential of micro-organisms for chemicals production.

Understanding the effects of bulk mixing on the determination of the affinity index: consequences for process operation and design.

The main objective of this study is to demonstrate the importance of mixing conditions as a source of inconsistencies between half-saturation indices in comparable systems (e.g. conventional activated sludge, membrane bioreactor) when operated at different conditions or different scales. As proof-of-principle, an exemplary system consisting of the second vessel of a hybrid respirometer has been studied. The system has been modeled both using an integrated computational fluid dynamics (CFD)-biokinetic model (assumed to represent the physical system) and a tanks-in-series, completely stirred tank reactor biokinetic model (representing the applied model). The results show that different mixing conditions cause deviations in the half-saturation indices calculated when matching the applied model to the physical system performance. Additionally, sensor location has been shown to impact the calculation of half-saturation indices in the respirometric system. This will only become more pronounced at larger scales. Thus, mixing conditions clearly affect operation and design of wastewater treatment reactors operated at low substrate concentrations. Both operation and design can be improved with the development and application of integrated CFD-biokinetic or compartmental models.

Towards improved accuracy in modeling aeration efficiency through understanding bubble size distribution dynamics.

Aeration is the largest energy consumer in most water and resource recovery facilities, which is why oxygen transfer optimization is fundamental to improve energy efficiency. Although oxygen transfer is strongly influenced by the bubble size distribution dynamics, most aeration efficiency models currently do not include this influence explicitly. In few cases, they assume a single average bubble size. The motivation of this work is to investigate this knowledge gap, i.e. a more accurate calculation of the impact of bubble size distribution dynamics on oxygen transfer. Experiments were performed to study bubble size distribution dynamics along the height of a bubble column at different air flow rates for both tap water and solutions that mimic the viscosity of activated sludge at different sludge concentrations. Results show that bubble size is highly dynamic in space and time since it is affected by hydrodrynamics and the viscosity of the liquid. Consequently, oxygen transfer also has a dynamic character. The concept of a constant overall volumetric oxygen transfer coefficient, KLa, can thus be improved. A new modeling approach to determine the KLa locally based on bubble size distribution dynamics is introduced as an alternative. This way, the KLa for the entire column is calculated and compared to the one measured by a traditional method. Results are in good agreement for tap water. The modeled KLa based on the new approach slightly overestimates the experimental KLa for solutions that mimic the viscosity of activated sludge. The difference appears to be lower when the air flow rate increases. This work can be considered as a first step towards more accurate and rigorous mechanistic aeration efficiency models which are based on in-depth mechanism knowledge. This is key for oxygen transfer optimization and consequently energy savings.

How well-mixed is well mixed? Hydrodynamic-biokinetic model integration in an aerated tank of a full-scale water resource recovery facility.

Current water resource recovery facility (WRRF) models only consider local concentration variations caused by inadequate mixing to a very limited extent, which often leads to a need for (rigorous) calibration. The main objective of this study is to visualize local impacts of mixing by developing an integrated hydrodynamic-biokinetic model for an aeration compartment of a full-scale WRRF. Such a model is able to predict local variations in concentrations and thus allows judging their importance at a process level. In order to achieve this, full-scale hydrodynamics have been simulated using computational fluid dynamics (CFD) through a detailed description of the gas and liquid phases and validated experimentally. In a second step, full ASM1 biokinetic model was integrated with the CFD model to account for the impact of mixing at the process level. The integrated model was subsequently used to evaluate effects of changing influent and aeration flows on process performance. Regions of poor mixing resulting in non-uniform substrate distributions were observed even in areas commonly assumed to be well-mixed. The concept of concentration distribution plots was introduced to quantify and clearly present spatial variations in local process concentrations. Moreover, the results of the CFD-biokinetic model were concisely compared with a conventional tanks-in-series (TIS) approach. It was found that TIS model needs calibration and a single parameter set does not suffice to describe the system under both dry and wet weather conditions. Finally, it was concluded that local mixing conditions have significant consequences in terms of optimal sensor location, control system design and process evaluation.

Towards advanced aeration modelling: from blower to bubbles to bulk.

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.

Hurdles in the investigation of influent fractionation for measurement campaigns under diluted wastewater conditions.

Evaluating the performance of a wastewater treatment plant (WWTP) requires a good characterization of the biodegradable substrate entering the plant. As is generally acknowledged, the wastewater characteristics under rain or storm weather conditions vary significantly from dry weather conditions but this is rarely accounted for in modelling exercises. In order to address this defect, a measurement campaign was set up and samples were analysed using respirometric assays. In this paper, some hurdles regarding measurement campaigns under dilute wastewater conditions and a better exploration of the impact of using respirometric assays are described and discussed. The dependence of the heterotrophic yield on different substrates severely hampers the evaluation of the respirograms under dilute wastewater conditions. In addition, the low load conditions limit the application of the assays due to insufficient sensitivity of the experiment and uncontrolled oxygen inputs. The results clearly demonstrate the need for further research in order to allow for a proper evaluation of WWTP performance under rain and storm weather conditions.

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.

Modeling the anaerobic digestion of cane-molasses vinasse: extension of the Anaerobic Digestion Model No. 1 (ADM1) with sulfate reduction for a very high strength and sulfate rich wastewater.

This research presents the modeling of the anaerobic digestion of cane-molasses vinasse, hereby extending the Anaerobic Digestion Model No. 1 with sulfate reduction for a very high strength and sulfate rich wastewater. Based on a sensitivity analysis, four parameters of the original ADM1 and all sulfate reduction parameters were calibrated. Although some deviations were observed between model predictions and experimental values, it was shown that sulfates, total aqueous sulfide, free sulfides, methane, carbon dioxide and sulfide in the gas phase, gas flow, propionic and acetic acids, chemical oxygen demand (COD), and pH were accurately predicted during model validation. The model showed high (±10%) to medium (10%-30%) accuracy predictions with a mean absolute relative error ranging from 1% to 26%, and was able to predict failure of methanogenesis and sulfidogenesis when the sulfate loading rate increased. Therefore, the kinetic parameters and the model structure proposed in this work can be considered as valid for the sulfate reduction process in the anaerobic digestion of cane-molasses vinasse when sulfate and organic loading rates range from 0.36 to 1.57 kg [Formula: see text]  m(-3) d(-1) and from 7.66 to 12 kg COD m(-3) d(-1), respectively.

From the affinity constant to the half-saturation index: understanding conventional modeling concepts in novel wastewater treatment processes.

The "affinity constant" (KS) concept is applied in wastewater treatment models to incorporate the effect of substrate limitation on process performance. As an increasing number of wastewater treatment processes rely on low substrate concentrations, a proper understanding of these so-called constants is critical in order to soundly model and evaluate emerging treatment systems. In this paper, an in-depth analysis of the KS concept has been carried out, focusing on the different physical and biological phenomena that affect its observed value. By structuring the factors influencing half-saturation indices (newly proposed nomenclature) into advectional, diffusional and biological, light has been shed onto some of the apparent inconsistencies present in the literature. Particularly, the importance of non-ideal mixing as a source of variability between observed KS values in different systems has been illustrated. Additionally, discussion on the differences existent between substrates that affect half-saturation indices has been carried out; it has been shown that the observed KS for some substrates will reflect transport or biological limitations more than others. Finally, potential modeling strategies that could alleviate the shortcomings of the KS concept have been provided. These could be of special importance when considering the evaluation and design of emerging wastewater treatment processes.

Development and assessment of an integrated ecological modelling framework to assess the effect of investments in wastewater treatment on water quality.

Worldwide, large investments in wastewater treatment are made to improve water quality. However, the impacts of these investments on river water quality are often not quantified. To assess water quality, the European Water Framework Directive (WFD) requires an integrated approach. The aim of this study was to develop an integrated ecological modelling framework for the River Drava (Croatia) that includes physical-chemical and hydromorphological characteristics as well as the ecological river water quality status. The developed submodels and the integrated model showed accurate predictions when comparing the modelled results to the observations. Dissolved oxygen and nitrogen concentrations (ammonium and organic nitrogen) were the most important variables in determining the ecological water quality (EWQ). The result of three potential investment scenarios of the wastewater treatment infrastructure in the city of Varazdin on the EWQ of the River Drava was assessed. From this scenario-based analysis, it was concluded that upgrading the existing wastewater treatment plant with nitrogen and phosphorus removal will be insufficient to reach a good EWQ. Therefore, other point and diffuse pollution sources in the area should also be monitored and remediated to meet the European WFD standards.

Balancing effluent quality, economic cost and greenhouse gas emissions during the evaluation of (plant-wide) control/operational strategies in WWTPs.

The objective of this paper was to show the potential additional insight that result from adding greenhouse gas (GHG) emissions to plant performance evaluation criteria, such as effluent quality (EQI) and operational cost (OCI) indices, when evaluating (plant-wide) control/operational strategies in wastewater treatment plants (WWTPs). The proposed GHG evaluation is based on a set of comprehensive dynamic models that estimate the most significant potential on-site and off-site sources of CO2, CH4 and N2O. The study calculates and discusses the changes in EQI, OCI and the emission of GHGs as a consequence of varying the following four process variables: (i) the set point of aeration control in the activated sludge section; (ii) the removal efficiency of total suspended solids (TSS) in the primary clarifier; (iii) the temperature in the anaerobic digester; and (iv) the control of the flow of anaerobic digester supernatants coming from sludge treatment. Based upon the assumptions built into the model structures, simulation results highlight the potential undesirable effects of increased GHG production when carrying out local energy optimization of the aeration system in the activated sludge section and energy recovery from the AD. Although off-site CO2 emissions may decrease, the effect is counterbalanced by increased N2O emissions, especially since N2O has a 300-fold stronger greenhouse effect than CO2. The reported results emphasize the importance and usefulness of using multiple evaluation criteria to compare and evaluate (plant-wide) control strategies in a WWTP for more informed operational decision making.

On data requirements for calibration of integrated models for urban water systems.

Modeling of integrated urban water systems (IUWS) has seen a rapid development in recent years. Models and software are available that describe the process dynamics in sewers, wastewater treatment plants (WWTPs), receiving water systems as well as at the interfaces between the submodels. Successful applications of integrated modeling are, however, relatively scarce. One of the reasons for this is the lack of high-quality monitoring data with the required spatial and temporal resolution and accuracy to calibrate and validate the integrated models, even though the state of the art of monitoring itself is no longer the limiting factor. This paper discusses the efforts to be able to meet the data requirements associated with integrated modeling and describes the methods applied to validate the monitoring data and to use submodels as software sensor to provide the necessary input for other submodels. The main conclusion of the paper is that state of the art monitoring is in principle sufficient to provide the data necessary to calibrate integrated models, but practical limitations resulting in incomplete data-sets hamper widespread application. In order to overcome these difficulties, redundancy of future monitoring networks should be increased and, at the same time, data handling (including data validation, mining and assimilation) should receive much more attention.

Towards a generalized physicochemical framework.

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.