Shall we upgrade one-dimensional secondary settler models used in WWTP simulators? - An assessment of model structure uncertainty and its propagation

Dynamic calibration of a new secondary settler model using Cand. Microthrix as a predictor of settling velocity

Climate change is projected to increase the frequency of hydraulic shocks on urban water systems, affecting water resource recovery facilities (WRRFs). In these facilities, the settleability of activated sludge is a critical hydraulic bottleneck. However, to date, the dynamic prediction of hindered settling velocity (v0/rH) has remained unresolved. To address this significant knowledge gap, this study presents an assessment of microbial community predictors of hindered settling velocity. Through a regression analysis of independent laboratory and full-scale experimental data, we identified a close association between the relative abundance of Candidatus Microthrix filamentous bacteria and hindered settling velocity parameter values. While no direct association was observed between filamentous abundance and compression settling parameters, we propose linking the dynamic calibration of the compressive solid stress function to v0/rH. Notably, our results demonstrate, for the first time, the efficacy of dynamic calibration of SST models using the relative abundance of filamentous microbial predictors in a simulation model of the Kloten-Opfikon full-scale WRRF. Furthermore, besides Cand. Microthrix, Thiothrix is found to be a putative predictor for biomolecular SST calibration. These findings shed light on the potential of microbial communities to predict hindered settling velocity in WRRFs and offer valuable insights for improving wastewater treatment processes in the face of climate change challenges.

An improved 1D reactive Bürger-Diehl settler model for secondary settling tank denitrification

An improved 1D reactive settler model is pursued in order to increase the understanding of reactive settling processes and obtain a better prediction of the nitrogen mass balance in wastewater treatment systems. The developed model is based on the 1D Bürger-Diehl settler model with compression function and the Activated Sludge Model No. 1 biological reactions. Specific attention was paid in the model development phase to optimal selection of settling velocity functions and integration of the correct clarifier geometry. A unique measurement campaign was carried out with different operational scenarios to quantify the denitrification in a secondary settling tank. A detailed step-wise calibration effort demonstrated that by choosing an appropriate settling velocity function (power-law structure) and considering the true clarifier geometry allows to accurately capture the biomass concentration profile, total sludge mass, sludge blanket height, and the reaction rates. The resulting model is able to accurately describe total suspended solids (TSS) and nitrate concentration profiles throughout a settling tank under different operational conditions. As such the model can be applied in further scenario analysis and system optimization. PRACTITIONER POINTS: A unique measurement campaign was carried out to obtain detailed data for a reactive settler model development. A 1-D reactive settler model is developed based on the Bürger-Diehl framework including ASM1 biokinetics and the clarifier geometry. An extensive calibration and model selection effort was performed. The model accurately predicts measured concentration profiles in the settling tank. The developed model can be integrated in a plant-wide model to properly calculate the nitrogen mass balance of a WRRF.

Ammonia-based aeration control with optimal SRT control: improved performance and lower energy consumption

Ammonia-based aeration control (ABAC) is a cascade control concept for controlling total ammonia nitrogen (NH_x-N) in the activated sludge process. Its main goals are to tailor the aeration intensity to the NH_x-N loading and to maintain consistent nitrification, to meet effluent limits but minimize energy consumption. One limitation to ABAC is that the solids retention time (SRT) control strategy used at a water resource recovery facility (WRRF) may not be consistent with the goals of ABAC. ABAC-SRT control is a strategy for aligning the goals of ammonia-based aeration control and SRT control. A supervisory controller is used to ensure that the SRT is always optimal for ABAC. The methodology has the potential to reduce aeration energy consumption by over 30% as compared to traditional dissolved oxygen (DO) control. Practical implementation aspects are highlighted for implementation at full scale, such as proper selection of the set point for the supervisory controller, proper calculation of the rate of change in sludge inventory, using a mixed liquor suspended solids (MLSS) controller, and tuning of the controllers. In conclusion, ABAC-SRT is a promising approach for coordinated control of SRT, total ammonia nitrogen, and dissolved oxygen in the activated sludge process that balances both treatment performance and energy savings.

On constitutive functions for hindered settling velocity in 1-D settler models: Selection of appropriate model structure

Advanced 1-D models for Secondary Settling Tanks (SSTs) explicitly account for several phenomena that influence the settling process (such as hindered settling and compression settling). For each of these phenomena a valid mathematical expression needs to be selected and its parameters calibrated to obtain a model that can be used for operation and control. This is, however, a challenging task as these phenomena may occur simultaneously. Therefore, the presented work evaluates several available expressions for hindered settling based on long-term batch settling data. Specific attention is paid to the behaviour of these hindered settling functions in the compression region in order to evaluate how the modelling of sludge compression is influenced by the choice of a certain hindered settling function. The analysis shows that the exponential hindered settling forms, which are most commonly used in traditional SST models, not only account for hindered settling but partly lump other phenomena (compression) as well. This makes them unsuitable for advanced 1-D models that explicitly include each phenomenon in a modular way. A power-law function is shown to be more appropriate to describe the hindered settling velocity in advanced 1-D SST models.

Practical identifiability and uncertainty analysis of the one-dimensional hindered-compression continuous settling model

The practical application of the one-dimension hindered-compression settling models remains a challenge, since the model calibration strongly depends on experimental observations with limited information. In this study, the identifiability of parameter subsets of the hindered-compression models is evaluated for various experimental layouts. Global sensitivity analysis is used to preliminarily select the influential parameters which can be reasonably estimated, while the identifiability analysis of parameter subsets is conducted based on the local sensitivity functions and collinearity measures. The batch settling curve observations are informative for calibrating hindered parameters, and to determine the compression parameters, the concentration profile observations may need to be collected. For different experimental layouts, at least three parameters are identifiable, and the number of identifiable parameters can potentially increase to five, if both batch settling curve and concentration observations are available. The parameter subset identifiability is sensitive to the choice of initial parameter values, and determining the initial values of hindered parameters and gel concentration by measuring the hindered settling velocities and the top concentration of the static sediment respectively allows efficient reduction of the sensitivity. Parameter subset estimates are sensitive to the values of fixed parameters, and reliable estimation of identifiable parameter subsets is possible to significantly decrease model prediction uncertainties.

CFD-aided modelling of activated sludge systems - A critical review

Nowadays, one of the major challenges in the wastewater sector is the successful design and reliable operation of treatment processes, which guarantee high treatment efficiencies to comply with effluent quality criteria, while keeping the investment and operating cost as low as possible. Although conceptual design and process control of activated sludge plants are key to ensuring these goals, they are still based on general empirical guidelines and operators' experience, dominated often by rule of thumb. This review paper discusses the rationale behind the use of Computational Fluid Dynamics (CFD) to model aeration, facilitating enhancement of treatment efficiency and reduction of energy input. Several single- and multiphase approaches commonly used in CFD studies of aeration tank operation, are comprehensively described, whilst the shortcomings of the modelling assumptions imposed to evaluate mixing and mass transfer in AS tanks are identified and discussed. Examples and methods of coupling of CFD data with biokinetics, accounting for the actual flow field and its impact on the oxygen mass transfer and yield of the biological processes occurring in the aeration tanks, are also critically discussed. Finally, modelling issues, which remain unaddressed, (e.g. coupling of the AS tank with secondary clarifier and the use of population balance models to simulate bubbly flow or flocculation of the activated sludge), are also identified and discussed.

iCFD: Interpreted Computational Fluid Dynamics - Degeneration of CFD to one-dimensional advection-dispersion models using statistical experimental design - The secondary clarifier

The present study aims at using statistically designed computational fluid dynamics (CFD) simulations as numerical experiments for the identification of one-dimensional (1-D) advection-dispersion models - computationally light tools, used e.g., as sub-models in systems analysis. The objective is to develop a new 1-D framework, referred to as interpreted CFD (iCFD) models, in which statistical meta-models are used to calculate the pseudo-dispersion coefficient (D) as a function of design and flow boundary conditions. The method - presented in a straightforward and transparent way - is illustrated using the example of a circular secondary settling tank (SST). First, the significant design and flow factors are screened out by applying the statistical method of two-level fractional factorial design of experiments. Second, based on the number of significant factors identified through the factor screening study and system understanding, 50 different sets of design and flow conditions are selected using Latin Hypercube Sampling (LHS). The boundary condition sets are imposed on a 2-D axi-symmetrical CFD simulation model of the SST. In the framework, to degenerate the 2-D model structure, CFD model outputs are approximated by the 1-D model through the calibration of three different model structures for D. Correlation equations for the D parameter then are identified as a function of the selected design and flow boundary conditions (meta-models), and their accuracy is evaluated against D values estimated in each numerical experiment. The evaluation and validation of the iCFD model structure is carried out using scenario simulation results obtained with parameters sampled from the corners of the LHS experimental region. For the studied SST, additional iCFD model development was carried out in terms of (i) assessing different density current sub-models; (ii) implementation of a combined flocculation, hindered, transient and compression settling velocity function; and (iii) assessment of modelling the onset of transient and compression settling. Furthermore, the optimal level of model discretization both in 2-D and 1-D was undertaken. Results suggest that the iCFD model developed for the SST through the proposed methodology is able to predict solid distribution with high accuracy - taking a reasonable computational effort - when compared to multi-dimensional numerical experiments, under a wide range of flow and design conditions. iCFD tools could play a crucial role in reliably predicting systems' performance under normal and shock events.

Microthrix parvicella abundance associates with activated sludge settling velocity and rheology - Quantifying and modelling filamentous bulking

The objective of this work is to identify relevant settling velocity and rheology model parameters and to assess the underlying filamentous microbial community characteristics that can influence the solids mixing and transport in secondary settling tanks. Parameter values for hindered, transient and compression settling velocity functions were estimated by carrying out biweekly batch settling tests using a novel column setup through a four-month long measurement campaign. To estimate viscosity model parameters, rheological experiments were carried out on the same sludge sample using a rotational viscometer. Quantitative fluorescence in-situ hybridisation (qFISH) analysis, targeting Microthrix parvicella and phylum Chloroflexi, was used. This study finds that M. parvicella - predominantly residing inside the microbial flocs in our samples - can significantly influence secondary settling through altering the hindered settling velocity and yield stress parameter. Strikingly, this is not the case for Chloroflexi, occurring in more than double the abundance of M. parvicella, and forming filaments primarily protruding from the flocs. The transient and compression settling parameters show a comparably high variability, and no significant association with filamentous abundance. A two-dimensional, axi-symmetrical computational fluid dynamics (CFD) model was used to assess calibration scenarios to model filamentous bulking. Our results suggest that model predictions can significantly benefit from explicitly accounting for filamentous bulking by calibrating the hindered settling velocity function. Furthermore, accounting for the transient and compression settling velocity in the computational domain is crucial to improve model accuracy when modelling filamentous bulking. However, the case-specific calibration of transient and compression settling parameters as well as yield stress is not necessary, and an average parameter set - obtained under bulking and good settling conditions - can be used.

Impact on sludge inventory and control strategies using the benchmark simulation model no. 1 with the Bürger-Diehl settler model

An improved one-dimensional (1-D) model for the secondary clarifier, i.e. the Bürger-Diehl model, was recently presented. The decisive difference to traditional layer models is that every detail of the implementation is in accordance with the theory of partial differential equations. The Bürger-Diehl model allows accounting for hindered and compressive settling as well as inlet dispersion. In this contribution, the impact of specific features of the Bürger-Diehl model on settler underflow concentration predictions, plant sludge inventory and mixed liquor suspended solids based control actions are investigated by using the benchmark simulation model no. 1. The numerical results show that the Bürger-Diehl model allows for more realistic predictions of the underflow sludge concentration, which is essential for more accurate wet weather modelling and sludge waste predictions. The choice of secondary settler model clearly has a profound impact on the operation and control of the entire treatment plant and it is recommended to use the Bürger-Diehl model as of now in any wastewater treatment plant modelling effort.

A new settling velocity model to describe secondary sedimentation

Secondary settling tanks (SSTs) are the most hydraulically sensitive unit operations in biological wastewater treatment plants. The maximum permissible inflow to the plant depends on the efficiency of SSTs in separating and thickening the activated sludge. The flow conditions and solids distribution in SSTs can be predicted using computational fluid dynamics (CFD) tools. Despite extensive studies on the compression settling behaviour of activated sludge and the development of advanced settling velocity models for use in SST simulations, these models are not often used, due to the challenges associated with their calibration. In this study, we developed a new settling velocity model, including hindered, transient and compression settling, and showed that it can be calibrated to data from a simple, novel settling column experimental set-up using the Bayesian optimization method DREAM(ZS). In addition, correlations between the Herschel-Bulkley rheological model parameters and sludge concentration were identified with data from batch rheological experiments. A 2-D axisymmetric CFD model of a circular SST containing the new settling velocity and rheological model was validated with full-scale measurements. Finally, it was shown that the representation of compression settling in the CFD model can significantly influence the prediction of sludge distribution in the SSTs under dry- and wet-weather flow conditions.

Research advances and challenges in one-dimensional modeling of secondary settling tanks--a critical review

Sedimentation is one of the most important processes that determine the performance of the activated sludge process (ASP), and secondary settling tanks (SSTs) have been frequently investigated with the mathematical models for design and operation optimization. Nevertheless their performance is often far from satisfactory. The starting point of this paper is a review of the development of settling theory, focusing on batch settling and the development of flux theory, since they played an important role in the early stage of SST investigation. The second part is an explicit review of the established 1-D SST models, including the relevant physical law, various settling behaviors (hindered, transient, and compression settling), the constitutive functions, and their advantages and disadvantages. The third part is a discussion of numerical techniques required to solve the governing equation, which is usually a partial differential equation. Finally, the most important modeling challenges, such as settleability description, settling behavior understanding, are presented.

Significance of settling model structures and parameter subsets in modelling WWTPs under wet-weather flow and filamentous bulking conditions

Current research focuses on predicting and mitigating the impacts of high hydraulic loadings on centralized wastewater treatment plants (WWTPs) under wet-weather conditions. The maximum permissible inflow to WWTPs depends not only on the settleability of activated sludge in secondary settling tanks (SSTs) but also on the hydraulic behaviour of SSTs. The present study investigates the impacts of ideal and non-ideal flow (dry and wet weather) and settling (good settling and bulking) boundary conditions on the sensitivity of WWTP model outputs to uncertainties intrinsic to the one-dimensional (1-D) SST model structures and parameters. We identify the critical sources of uncertainty in WWTP models through global sensitivity analysis (GSA) using the Benchmark simulation model No. 1 in combination with first- and second-order 1-D SST models. The results obtained illustrate that the contribution of settling parameters to the total variance of the key WWTP process outputs significantly depends on the influent flow and settling conditions. The magnitude of the impact is found to vary, depending on which type of 1-D SST model is used. Therefore, we identify and recommend potential parameter subsets for WWTP model calibration, and propose optimal choice of 1-D SST models under different flow and settling boundary conditions. Additionally, the hydraulic parameters in the second-order SST model are found significant under dynamic wet-weather flow conditions. These results highlight the importance of developing a more mechanistic based flow-dependent hydraulic sub-model in second-order 1-D SST models in the future.

Bayesian treatment of model uncertainty for partially applicable models

This article discusses how analyst's or expert's beliefs on the credibility and quality of models can be assessed and incorporated into the uncertainty assessment of an unknown of interest. The proposed methodology is a specialization of the Bayesian framework for the assessment of model uncertainty presented in an earlier paper. This formalism treats models as sources of information in assessing the uncertainty of an unknown, and it allows the use of predictions from multiple models as well as experimental validation data about the models' performances. In this article, the methodology is extended to incorporate additional types of information about the model, namely, subjective information in terms of credibility of the model and its applicability when it is used outside its intended domain of application. An example in the context of fire risk modeling is also provided.

Removal of ibuprofen and its transformation products: experimental and simulation studies

Pharmaceutically active compounds (PhACs) deserve attention because of their effect on ecosystems and human health, as well as their continuous introduction into the aquatic environment. Classification schemes are suggested to characterise their biological degradation, e.g., based on pseudo-first-order kinetics, but these schemes can vary significantly, presumably due to pharmaceutical loads, sludge characteristics and experimental conditions. Degradation data for PhAC transformation products (TPs) are largely lacking. The present work focuses not only on the biodegradation of the pharmaceutical compound ibuprofen but also on its best-known TPs (i.e., carboxyl ibuprofen and both hydroxyl ibuprofen isomers). Ibuprofen is one of the most commonly consumed PhACs and can be found in different environmental compartments. The experiment performed consisted of a set of aerated batch tests with different suspended solid and ibuprofen concentrations to determine the influence of these parameters on the calculated biodegradation constant (K(biol)). Sampling of the liquid phase at different scheduled times was assessed, removal efficiencies were calculated and pseudo-first-order kinetics were adjusted to obtain experimental K(biol) values for the parent compound and its TPs. The experimental data were successfully fitted to ASM-based models, with K(biol) values for the target compounds ranging from almost 1 to 17 L gSST(-1) d(-1), depending on the concentrations of the biomass and ibuprofen. This work provides innovative knowledge not only regarding the removal of TPs but also the formation kinetics of these TPs.

ICA and me--a subjective review

ICA - instrumentation, control and automation - is a hidden technology. It is ubiquitous in all industrial processes, including water and wastewater treatment systems. Still, as long as everything works fine, it is not noted but when things go wrong it will be observed. ICA has now about forty years of history in water and wastewater systems and is well recognized. One early attitude was that ICA will be a necessary burden to be added to a plant in order to correct for a poor design. However, the key reason for ICA is the fact that all processes are subject to disturbances, externally via the wastewater influent, from the customers in a water supply system, or from operations in one unit process that will propagate as a disturbance to another unit within a plant. This paper is an attempt to describe the development of ICA in water and wastewater systems. Most of it is based on personal experiences with all their limitations. No single paper can fairly describe the development that is documented in thousands of research papers, practiced by so many operators and process engineers and implemented in so many treatment systems. Still, the hope is that the paper can give a flavour of the most important ingredients of this fascinating development.