Drinking water softening has primarily prioritized public health, environmental benefits, social costs and enhanced client comfort. Annually, over 35 billion cubic meters of water is softened worldwide, often utilizing three main techniques: nanofiltration, ion exchange and seeded crystallization by pellet softening. However, recent modifications in pellet softening, including changes in seeding materials and acid conditioning used post-softening, have not fully achieved desired flexibility and optimization. This highlights the need of an integral approach, as drinking water softening is just one step in the drinking water treatment chain, which includes ozonation, softening, biological active carbon filtration (BACF) and sand filtration among others. In addition, pellet softening is often practiced based on operator knowledge, lacking practical key reactor performance indicators (KPIs) for efficient control. For that reason, we propose a newly and improved integral mechanistic model designed to accurately predict (1) calcite removal rates in drinking water through seeded crystallization in pellet softening reactors, (2) the saturation of the filter bed in the subsequent treatment step, (3) values for the KPIs steering the softening efficiency. Our new mechanistic model integrates insights from hydrodynamics, thermodynamics, mass transfer kinetics, nucleation and reactor engineering, focussing on critical variables such as temperature, linear velocity, pellet particle size and saturation index with respect to calcite. Our model was validated with data from the Waternet Weesperkarspel drinking water treatment plant in Amsterdam, The Netherlands, but implies universal applicability for addressing industrial challenges beyond drinking water softening. The implementation of our model proposes five effective KPIs to optimize the softening process, chemical usage, and reactor design. The advantage of this model is that it eliminates the application of numerical methods and fills a significant gap in the field by providing predictions of the carry-over (i.e., the produced CaCO₃ fines leaving the fluidized bed) from water softening practices. With our model, the calcium removal rate is predicted with an average standard deviation (SD) of 40 % and the consequential clogging prediction of the BACF bed with an average SD of 130 %. Ultimately, our model provides crucial insights for operational management and decision-making in drinking water treatment plants, steering towards a more circular and environmentally sustainable process.

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Granular activated carbon (GAC) filtration is an important unit operation in drinking water treatment. GAC filtration is widely used for its filtration and adsorption capabilities as a barrier for undesired organic macro- and micro-pollutants. GAC filtration consists of two successive phases: adsorption and filtration, capturing the impurities from the water in conjunction with a backwash procedure in which the suspended particles are flushed out of the system. Available literature predominantly focusses on adsorption. A less frequently discussed but nevertheless equally crucial aspect of this operation is the backwash procedure of GAC beds. To prevent accumulation of suspended particles and to avoid additional operation costs, optimal backwashing is required. Another factor is sustainability: water utilities are showing increasing interest in exploring new sustainable GAC media. As these have different bed expansion tendencies due to different GAC characteristics with varying geometries, operational developments are needed for prediction models to estimate the expansion degree during backwashing. The prediction of the bed expansion of GAC is complex as the particles are non-spherical, porous and polydisperse. Through a combination of advanced particle laboratory and fluidisation experiments, we demonstrate a new approach which leads to an improved expansion prediction model for the backwashing of GAC filters.@en

Fluid flow through a bed of solid particles is an important process that occurs in full-scale water treatment operations. The Carman–Kozeny model remains highly popular for estimating the resistance across the bed. It is common practice to use particle shape factors in fixed bed state to match the predicted drag coefficient with experimentally obtained drag coefficients. In fluidised state, however, where the same particles are considered, this particle shape factor is usually simply omitted from the model without providing appropriate reasoning. In this research, it is shown that a shape factor is not a constant particle property but is dependent on the fluid properties as well. This dynamic shape factor for irregularly shaped grains increases from approximately 0.6 to 1.0 in fluidised state.

We found that unstable packed beds in moderate up-flow conditions are pseudo-fixed and in a setting state. This results in a decreasing bed voidage and simultaneously in a decreasing drag coefficient, which seems quite contradictory. This can be explained by the collapse of local channels in the bed, leading to a more uniform flow distribution through the bed and improving the available surface for flow-through. Our experimental measurements show that the drag coefficient decreases considerably in the laminar and transition regions. This is most likely caused by particle orientation, realignment and rearrangement in particles’ packing position.

A thorough hydraulic analysis shows that up-flow filtration in rapid sand filters under backwash conditions causes the particle bed to collapse almost imperceptibly. In addition, an improved expression of the drag coefficient demonstrated that the Carman–Kozeny model constant, however often assumed to be constant, is in fact not constant for increasing flow rates. Furthermore, we propose a new pseudo-3D image analysis for particles with an irregular shape. In this way, we can explain the successful method using optimisation of the extended terminal sub-fluidisation wash (ETSW) filter backwashing procedure, in which turbidity and peaks in the number of particles are reduced with a positive effect on water quality.@en

In the Netherlands, central softening of drinking water is widely applied for reasons of public health, client comfort, economic and environmental benefits. Currently, the detrimental contributions of softening, in particular the use of chemicals and energy, are taken into account in the carbon footprint of the Dutch drinking water companies. The beneficial contributions have, however, until now not been included in the carbon footprint. Here, we present an attributional life cycle assessment (LCA) for the softening of drinking water, including effects at the household level and several sensitivity analyses. Five central softening methods were included (pellet reactor (PR), water storage reservoir (WSR), reverse osmosis (RO), nanofiltration (NF) and ion exchange (IEX)). Domestic softening by IEX is represented as well. Central softening, except RO, is shown to reduce the carbon footprint when effects at the household level are included. The main detrimental contributions are caused by the consumption of chemicals and energy in the softening process. The main beneficial contributions of softened water with respect to the carbon footprint are at the household level. Decreases in water hardness result in reduced scaling and give rise to a prolonged lifespan of appliances in which water is heated, reduced energy use of those appliances and less required cleaning agents. For PR and WSR a new beneficial effect was identified; carbon capture in the crystallized calcite and dissolution of CO2 into the softened water. We show that for the Dutch water companies Evides and Waternet approximately 20% and 60%, respectively, of their total carbon footprint is compensated by the net carbon benefit of softening. The net total carbon footprint of drinking water softening in the Netherlands is estimated to be −0.11 Mtonne CO2 eq./yr.@en

Liquid-solid fluidisation is frequently encountered in drinking water treatment processes, for instance in seeded crystallisation softening processes. For modest superficial fluid velocities, liquid–solid fluidisation systems are generally considered to be homogeneous, as reported in literature. However, during fluidisation experiments with calcite grains, open spaces of water can be observed between the fluidised particles, even at relatively low fluid velocities. Moreover, significant heterogeneous particle–fluid patterns are detected at higher fluid velocities. Such heterogeneous behaviour can beneficially or adversely affect the chemical crystallisation efficiency. To obtain information about voids in bulk regions, complementary Computational Fluid Dynamics - Discrete Element Method (CFD-DEM) simulations were performed and compared with the experimental results for validation. Simulations were performed using different water inlet velocities and fractionised calcite granules obtained from full-scale reactors. Here, the results are analysed using the bed height, voidage and pressure drop of the system. Furthermore, images of the experiments and simulations are visually compared for the formation of voids. The simulations showed distinct differences in void fraction in the cross-section of the column. It is shown that throughout the range of considered water velocities, heterogeneous behaviour exists and cannot be neglected. The heterogeneity and onset of fluidisation behaviour obtained from the simulations and experimental observations were compared and found to agree reasonably well.@en

In drinking water treatment plants, multiphase flows are a frequent phenomenon. Examples of such flows are pellet-softening and filter backwashing where liquid-solid fluidisation is applied. A better grasp of these fluidisation processes is needed to be able to determine optimal hydraulic states. In this research, models were developed, and experiments performed to gain such hydraulic knowledge. As a result, treatment processes can be made more flexible. In a rapidly changing environment, drinking water production must be flexible to ensure robustness and to tackle challenges related to sustainability and long-term changes. In the hydraulic models, the voidage in the fluidised bed and the particle size of the suspended granules are crucial variables. Voidage prediction is challenging as the fluidised bed is a dynamic environment showing highly heterogeneous behaviour that is hard to describe with an effective model. And particle size causes a conundrum due to the irregular shapes of the applied granules. Through the combination of hydraulic dimensionless Reynolds and Froude numbers, an accurate voidage prediction model has now been developed. With a straightforward pseudo-3D image analysis for non-spherical particles measuring particle mass and density, the dimensioned shapes of, for instance, ellipsoids can be determined. Particle shape factors included in models are not constant as is commonly believed, but dynamic. Applying advanced computational fluid dynamics simulations confirmed significant heterogeneous particle-fluid patterns in fluidised beds. Comprehensive sedimentation experiments showed that the average drag coefficient and terminal setting velocity of individual grains can be estimated reasonably well, but with a significant degree of data spread around the mean values. For engineering purposes, this is relevant information which should be taken into consideration. A new soft-sensor was designed to determine the voidage gradient and particle size profile in a fluidised bed. The expansion degree of highly erratic, polydisperse and porous granular activated carbon grains can be predicted with a model, but in full-scale processes the grains are subject to change, and therefore it is most likely that the prediction accuracy will deteriorate rapidly. For reliable drinking water quality, smart models provide solutions to complex challenges, but they are only effective when they are calibrated and validated in advanced pilot plants and are applied in full-scale processes with diligence and commitment on the part of multidisciplinary teams.@en

Liquid-solid fluidisation is frequently encountered in drinking water treatment processes, often to obtain a large liquid-solid interfacial surface area. A large surface area is crucial for optimal seeded crystallisation in full-scale softening reactors. Due to crystallisation, particles grow and migrate to a lower zone in the reactor which leads to a stratified bed. Larger particles adversely affect the surface area. To maintain optimal process conditions in the fluidised beds, information is needed about the distribution of particle size, local voidage and available surface area, over the reactor height.

In this work, a sensor is developed to obtain the hydraulic state gradient, based on Archimedes’ principle. A cylindrical heavy object is submerged in the fluidised bed and lowered gradually while its weight is measured at various heights using a sensitive force measuring device.

Based on accurate fluidisation experiments with calcite grains, the voidage is determined and a straightforward empirical model is developed to estimate the particle size as a function of superficial fluid velocity, kinematic viscosity, suspension density, voidage and particle density. The surface area and specific space velocity can be estimated accordingly, which represent key performance indicators regarding the hydraulic state of the fluidised bed reactor. The prediction error for voidage is 5 ± 2 % and for particle size 9 ± 4 %.

The newly developed soft sensor is a more time-effective method for obtaining the hydraulic state in full-scale liquid-solid fluidised bed reactors.@en

Natural particles are frequently applied in drinking water treatment processes in fixed bed reactors, fluidised bed reactors, and sedimentation processes to clarify water and to concentrate solids. When particles settle, it has been found that, in terms of hydraulics, natural particles behave differently when compared to perfectly round spheres. To estimate the terminal settling velocity of single solid particles in a liquid system, a comprehensive collection of equations is available. For perfectly round spheres, the settling velocity can be calculated quite accurately. However, for naturally polydisperse non-spherical particles, experimentally measured settling velocities of individual particles show considerable spread from the calculated average values.

This work aims to analyse and explain the different causes of this spread. To this end, terminal settling experiments were conducted in a quiescent fluid with particles varying in density, size, and shape. For the settling experiments, opaque and transparent spherical polydisperse and monodisperse glass beads were selected. In this study, we also examined drinking-water-related particles, like calcite pellets and crushed calcite seeding material grains, which are both applied in drinking water softening. Polydisperse calcite pellets were sieved and separated to acquire more uniformly dispersed samples. In addition, a wide variety of grains with different densities, sizes, and shapes were investigated for their terminal settling velocity and behaviour. The derived drag coefficient was compared with well-known models such as the one of Brown and Lawler (2003).

A sensitivity analysis showed that the spread is caused, to a lesser extent, by variations in fluid properties, measurement errors, and wall effects. Natural variations in specific particle density, path trajectory instabilities, and distinctive multi-particle settling behaviour caused a slightly larger degree of the spread. In contrast, a greater spread is caused by variations in particle size, shape, and orientation.

In terms of robust process designs and adequate process optimisation for fluidisation and sedimentation of natural granules, it is therefore crucial to take into consideration the influence of the natural variations in the settling velocity when using predictive models of round spheres.@en

Eind 2014 ontstond de Contactgroep Drinkwater Technologen in Nederland en Vlaanderen uit een fusie tussen de contactgroepen ontharding en filtratie. Technologen van tien Nederlandse en vier Vlaamse waterbedrijven en kennisinstituut KWR delen actief kennis over (drink)watertechnologie.@en

In full-scale drinking water production plants in the Netherlands, central softening is widely used for reasons related to public health, client comfort, and economic and environmental benefits. Almost 500 million cubic meters of water is softened annually through seeded crystallisation in fluidised bed reactors. The societal call for a circular economy has put pressure on this treatment process to become more sustainable. By optimising relevant process conditions, the consumption of chemicals can be reduced, and raw materials reused. Optimal process conditions are feasible if the specific crystallisation surface area in the fluidised bed is large enough to support the performance of the seeded crystallisation process. To determine the specific surface area, crucial variables including voidage and particle size must be known. Numerous models can be found in the literature to estimate the voidage in liquid-solid fluidisation processes. Many of these models are based on semi-empirical porous-media-based drag relations like Ergun or semi-empirical terminal-settling based models such as Richardson-Zaki and fitted for monodisperse, almost perfectly round particles. In this study, we present new voidage prediction models based on accurate data obtained from elaborate pilot plant experiments and non-linear symbolic regression methods. The models were compared with the most popular voidage prediction models using different statistical methods. An explicit model for voidage estimation based on the dimensionless Reynolds and Froude numbers is presented here that can be used for a wide range of particle sizes, fluid velocities and temperatures and that can therefore be directly used in water treatment processes such as drinking water pellet softening. The advantage of this model is that there is no need for applying numerical solutions; therefore, it can be explicitly implemented. The prediction errors for classical models from the literature lie between 2.7 % and 11.4 %. With our new model, the voidage prediction error is reduced to 1.9 %.@en

A novel effective drag relation for liquid-solid fluidisation is proposed, suitable for application in full-scale installations. This is achieved by presenting new insights related to the influence of the temporal-spatial heterogeneity on the effective hydrodynamic drag for large fluidised systems. While heterogeneous flow behaviour can be predicted increasingly accurately in CFD simulations that explicitly model the heterogeneous solids distribution, for the operation of many large-scale applications it is infeasible to perform such computationally intensive simulations. Therefore, there is a clear need for full-scale drag relations that effectively take into account the heterogeneous behaviour and irregular spatial particle distributions. Our new drag relation is based on a large set of experiments, which shows that the degree of overall expansion is not only dependent on the ratio of laminar-turbulent flow, but also on the amount of homogenous versus heterogeneous flow, which is not included in current full-scale drag relations. To include the effect of heterogeneity, the standard drag relation, based on the Reynolds number, is extended with a specific type of Froude number. Because fully turbulent flow regimes are rare in applications of liquid-solid fluidisation, our focus is not on the turbulent flow regime but instead on laminar and transitional flow regimes. In these regimes, three types of models are investigated. The first type is based on a theoretical similarity with terminal settling, the second is based on the semi-empirical Carman-Kozeny model, and the third is based on empirical equations using symbolic regression techniques. For all three types of models, coefficients are calibrated on experimental data with monodisperse and almost spherical glass beads. The models are validated with a series of calcium carbonate grains applied in drinking water treatment processes as well as data obtained from the literature. Using these models, we show that the voidage prediction average relative error decreases from approximately 5% (according to the best literature equations which use Reynolds number only) to 1-2% (using both Reynolds and Froude number). This implies that our new models are more suitable for operational control in full-scale fluidised bed applications, such as pellet softening in drinking water treatment processes.@en

A virtual lab (MOOC) for students chemical, civil or mechanical engineering. Students are introduced with a fluidised bed reactor (multiphase flow). This expansion column represents a liquid-solid fluidisation process applied in drinking water treatment processes. The knowledge you will gain will help you develop and improve your competence profile of a highly qualified chemical engineer. Students are informed with short lectures (films): https://doi.org/10.4121/12881009 and a manual (document). Several assignments must be completed based on recorded laboratory experiments.@en

Een maatschappijbrede levenscyclusanalyse (LCA) van ontharding van drinkwater laat zien: (1) dat ontharden met bijna alle (centrale) technieken netto CO2-uitstoot reduceert, (2) vastlegging van CO2 in kalkpellets en water een significante, tot nu toe vergeten bijdrage levert, en (3) dat er potentieel een nog grotere winst (decentraal) te behalen is bij de consument.@en

One of the most popular and frequently used models for describing homogeneous liquid-solid fluidised suspensions is the model developed by Richardson & Zaki in 1954. The superficial fluid velocity and terminal settling velocity together with an index makes it possible to determine the fluid porosity in a straightforward way. The reference point for the Richardson-Zaki model is the terminal settling velocity at maximum porosity conditions. To be able to predict porosity in the proximity of minimum fluidisation conditions, either the minimum fluidisation velocity must be known or the Richardson-Zaki index must be very accurate. To maintain optimal process and control conditions in multiphase drinking water treatment processes, the porosity is kept relatively low. Unfortunately, the Richardson-Zaki index models tends to overestimate the minimum fluidisation velocity and therefore also results in less accurate predictions with respect to porosity values. We extended the Richardson-Zaki model with proven hydraulics-based models. The minimum fluidisation velocity is acquired using the model proposed by Kozeny (1927), Ergun (1952) and Carman (1937). The terminal settling velocity is obtained through the model developed by Brown & Lawler (2003), which is an improved version of the well-known model developed by Schiller & Naumann (1933). The proposed models are compared with data from expansion experiments with calcium carbonate grains, crushed calcite and garnet grains applied in drinking water softening using the fluidised bed process. With respect to porosity, prediction accuracy is improved, with the average relative error decreasing from 15% to 3% when the classic Richardson-Zaki model is extended with these hydraulics-based models. With respect to minimum fluidisation velocity, the average relative error decreases from 100% to 12%. In addition, simplified analytical equations are given for a straightforward estimation of the index n.

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Waternet haalt kalk uit drinkwater, met alle voordelen voor het milieu, voor de volksgezondheid, voor onze portemonnee en ook nog eens voor ons uiterlijk. Sinds kort wordt calciet uit ons drinkwater namelijk ook verwerkt in scrubcrème. @en

For an accurate prediction of the porosity of a liquid-solid homogenous fluidized bed, various empirical prediction models have been developed. Symbolic regression machine learning techniques are suitable for analyzing experimental fluidization data to produce empirical expressions for porosity as a function not only of fluid velocity and viscosity but also of particle size and shape. On the basis of this porosity, it becomes possible to calculate the specific surface area for reactions for seeded crystallization in a fluidized bed.@en

Van een afstand in de ruimte ziet onze aarde er blauw uit. Je zou het daarom misschien niet verwachten, maar onze mooie planeet is toch heel erg droog. Met een toenemende wereldbevolking en een wens naar meer welvaart neemt de ‘water-stress’ steeds meer toe en dit betreft vooral zoet en schoon water. Het milieu wordt zwaarder belast met een scala aan chemische stoffen die op hun beurt een bedreiging vormen voor de volksgezondheid. Onze eerste primaire levensbehoefte is gezond drinkwater en dit vinden we in de westerse wereld heel vanzelfsprekend. Echter, op iets meer dan twee uur vliegen is het maar de vraag of het verstandig is om uit de kraan te drinken. In toenemende mate moeten er steeds complexere stoffen uit het water worden gehaald en dit vraagt steeds meer van de chemische zuiveringen bij de bereiding van drinkwater. In deze masterclass wordt aan de hand van de geschiedenis van Nederlands eerste waterleidingbedrijf uitgelegd hoe betrouwbaar drinkwater door de tijd heen werd bereid en hoe Nederland heden ten dage in staat is om het beste drinkwater van de wereld te bereiden. Ons drinkwater heeft vergelijkbare kwaliteit als flesjeswater alleen is het drinkwater uit de kraan veel goedkoper en duurzamer. Nederland als Deltaland, is een waterexpert en deelt en verspreidt deze kennis internationaal. Kennis dient te stromen. Deze masterclass gaat tevens in op het onderwerp duurzaamheid en drinkwater. Als wij willen dat volgende generaties ook zorgeloos uit de kraan kunnen blijven drinken moeten we duurzamer gaan werken. Waterbedrijven dragen hier al aan bij en vinden steeds betere oplossingen om de waterzuiveringsprocessen duurzaam te maken. De ontharding van drinkwater is hier een goed voorbeeld van. Bij het zachter maken van drinkwater worden er ook reststoffen geproduceerd. Van deze reststoffen worden nu weer nuttige grondstof van gemaakt en zo dragen we bij aan een circulaire economie. Naast de geschiedenis en de duurzaamheid gaat deze masterclass ook in op de processen van drinkwaterbereiding. De drinkwaterbereiding is een combinatie van zowel chemische, fysische als biologische processen en naast een circulaire aanpak ook een kwestie van een interdisciplinair aanpak. De masterclass “Gezond drinkwater - Een doorkijk door de tijd van gezond drinkwater” biedt u als docent kennis in diverse facetten van gezond drinkwater. De kennis die u bij deze masterclass op doet is heel geschikt om in uw eigen lespraktijk op uw eigen school uit te dragen. @en

One of the most popular and frequently used models for describing homogeneous liquid-solid fluidised suspensions is the model developed by Richardson & Zaki in 1954. The superficial fluid velocity and terminal settling velocity together with an index, make it possible to determine the fluid porosity in a straightforward way. To maintain optimal process and control conditions in multiphase drinking water treatment processes, the porosity is kept relatively low. Unfortunately, the Richardson-Zaki index models tend to overestimate the minimum fluidisation velocity and therefore also result in less accurate predictions with respect to porosity values. We extended the Richardson-Zaki model with proven hydraulics-based models. The proposed models are compared with data from expansion experiments with grains applied in drinking water softening using the fluidised bed process. The porosity prediction error decreases from 15% to 3% and the minimum fluidisation velocity error from 100% to 12%.@en

Bij een verstoring van de waterkwaliteit hebben de mensen op het crisiscentrum van Waternet baat bij informatie over de omvang en de locatie van deze verstoring. Het door Waternet in samenwerking met de Hogeschool Utrecht ontwikkelde Waterkwaliteitsverstoringsmodel geeft op basis van tijd de vereiste informatie. Met dit beslissingsondersteunend model kunnen er adequate maatregelen worden genomen om de verstoring te beheersen en de volksgezondheid wat betreft de drinkwaterkwaliteit te waarborgen. Waternet heeft het model in de praktijk succesvol getest.@en

The literature provides a comprehensive collection of equations to estimate the terminal settling velocity of single solid particles in a liquid system. The settling velocity for perfectly round spheres can accurately be calculated. In the contrary for natural imperfect particles the experimentally measured settling velocity deviates considerably compared the calculated value. In drinking water treatment processes natural particles are frequently applied in up flow fluidisation processes and in addition sedimentation processes are applied to clarify water and to concentrate solids.@en