Drinking water softening is an essential treatment step that provides multiple benefits, including public health, reduction of environmental impact, decrease in clogging potential and improvement in heating efficiency. With approximately 35 billion cubic meters of water being softened annually worldwide, the predominant methods are conventional lime/soda-ash softening, nanofiltration, ion exchange, and seeded crystallization through pellet-water softening. This study addresses the limitations in existing predictive models for calcium carbonate (CaCO₃) precipitation kinetics in industrial-scale pellet-water softening by experimentally investigating the integral and multivariate effects of particle-, fluid-, water matrix- and reactor properties, on CaCO₃ precipitation kinetics. Fluid characterization experiments were conducted at lab-scale continuous-stirred tank reactors (CSTR), pilot-scale plug-flow reactors (PFR), and full-scale fluidized bed reactors (FBR) at the Waternet Weesperkarspel treatment plant in Amsterdam, The Netherlands. In parallel, solid characterization was performed with image analysis software on pellets and SEM on fines extracted from water samples, where both pellet and water samples were collected during FBR experiments. The calcium removal data obtained from experiments were compared with modeled CaCO₃ precipitation rates using and extending the most recently developed water softening model for pellet-water softening. The results predominantly highlight the critical role of mixing dynamics — between softening chemicals, hard influent water and seeding material — for accurate CaCO₃ precipitation predictions across various reactor types and other reactor-specific properties such as the residence time of influent hard water. Additional enhancements can be achieved by targeting fluid properties, followed by water matrix properties, and finally particle properties, though these factors exhibit a progressively smaller impact on overall water softening improvement. By implementing these prioritized optimization strategies, the operational control strategy for calcium removal will be enhanced, leading to improvements in cost-effectiveness, sustainability, and reliability in drinking water treatment processes.

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.

In the last decade, several process modifications took place in the Loenderveen (LDV)- Weesperkarspel (WPK) Water Treatment Plant (WTP) of Waternet. There are four process modifications initiated over time: first, a shift from garnet sand to calcite pellets as seeding materials for pellet softening process. Second, the elimination of acid dosing in the pretreatment plant at Loenderveen (LVN). Third, a set point adjustment in total hardness level to 1.4 mmol/L from 1.5 mmol/L. Finally, a switch from the acid (HCl) dosing to CO2 dosing for conditioning of softened water for further treatment process. The existing pellet softening models with linear calcium carbonate crystallization kinetic (Rietveld, 2005, van Schagen et al., 2008a) describing calcium and pH profile over the height of the bed and the supersaturated calcium concentration after bypass mixed water, are not capable to cope with these process modifications. Therefore, an improved prediction model for softening process and a set of optimal operational configurations is needed. Recent researches (Chiou, 2018, Seepma, 2018) showed the first improvement path by using a prediction model based on bi-linear kinetics and hydraulics (Hout, 2016, Kramer, 2016). Hence, in this research a model is developed on the basis of new knowledge on kinetics on 4 regions depending on saturation ratio and hydraulics in the reactor and proposed optimal operational configurations. The proposed new prediction model is based on experimental data from Continuous Stirred Batch Reactor (CSTR) and Plug Flow Reactor (PFR). The chemical model is described in 4 regions depending on the level of supersaturation. The kinetic rate constants for calcium carbonate crystallization on seeding material for these 4 regions are taken from CSTR and PFR experiments. The model is calibrated and validated based on previous experimental data from WPK and full-scale treatment plant (Schooten, 1985, Seepma, 2018, Schetters, 2013). Finally, the calibrated and validated results from studied model were compared with model outcomes proposed by Rietveld., 2005. Calcium Carbonate Crystallization Potential (CCCP) is the amount of supersaturated calcium in the effluent and determines the efficiency of the entire pellet softening process. A scenario analysis is performed for summer and winter based on bypass, linear velocity and fluidized bed height, aiming for the lowest CCCP, high reliability, minimum cost and sustainability. CCCP determines the amount of chemicals used and principal cost of pellet softening process. The high reliability of the process comes from the full-scale plant operations over 30 years. The cost minimizations takes into account the chemical cost of NaOH and CO2 (dosing chemical). Ultimately, an optimal operational configuration will lead to a sustainable operational approach for pellet softening by using as little chemicals as possible. The outcomes from the scenario analysis provided an operational window of 15-25% bypass and linear flow velocity of 69-85 m/h for pellet reactors depending on temperature (0-24°C). This choice of optimal configuration comes with a cost reduction between 3-4% both in winter and summer. Previous optimum configurations suggested a bypass of 50% with linear velocity of 60-70 m/h (Rietveld, 2005) and a cost reduction of 10%. This reduction of cost is less pronounced because of process modifications, improved prediction model with 4 regional kinetics and the set of operational windows. Therefore, the process modifications induced a different set of operational criteria for optimum outcome in the pellet softening process at WPK.

In Bangladesh, groundwater from shallow aquifers is used for communal drinking water supply on a large scale. This water is often polluted by naturally occurring arsenic, causing the largest scale poisoning through drinking water in the world (D. v. Halem, S. Bakker, G. Amy, & J. Van Dijk, 2009). In this report, a highly arsenic affected area in Bangladesh has been investigated. The main objective of this research is to obtain more insight in the three aspects of the DELTAP project: geology, water quality monitoring and safe water supply. It is aimed to analyse the relation between arsenic contamination and the local geology, to monitor the drinking water quality using mobile applications and to design and construct a water treatment unit. An important aspect of this research is to develop a monitoring and maintenance protocol in order to ensure safe water supply in the future. In the study area, 150 households have been selected and the water quality has been tested. The water quality has been assessed by measuring four chemical parameters and five physical parameters, using simple strip tests and mobile water quality applications. The results of the strip tests have been compared to the results of ICP-MS analysis in order to check the performance of the tests and the mobile apps. The arsenic and iron strip tests showed good performance. However, the manganese and mmonium strip tests did not perform well. Furthermore, no relations between the presence of arsenic and other chemicals have been found. It can be concluded that simple strip tests in combination with mobile applications are a promising tool for water quality monitoring, applying the Mobile Crowd Participation strategy. Since arsenic in groundwater has a geological origin, the relation between arsenic concentration in the groundwater and geology should be understood distinctly. In order to get a better understanding of this relationship, multiple tools and theories have been investigated and tested. Firstly, a geo information system has been used to map arsenic concentrations that have been obtained from the performed water quality tests. Based on the spatial analysis of the arsenic concentrations, three drillings have been performed: one drilling in a high, medium and low arsenic contaminated area. By use of the SASMIT tool, a link between sediment colour and arsenic contamination has been observed. Furthermore, geomorphological data and satellite images have been used to identify geological features in landscape which could also be linked to arsenic levels. The sediment colour found in drillings is in good accordance with the arsenic levels found in groundwater and thus, proves to be a useful tool to predict arsenic concentrations in the fieldwork area. However, the geological features in the research area are hard to identify and link to the measured arsenic concentrations. A water treatment unit has been designed and constructed in order to provide safe water to 5 to 10 households. Based on the iron and arsenic concentrations from the ICP-MS results and on practical considerations, a suitable location for the water treatment unit has been selected. The ratio of these parameters is important to remove arsenic from the groundwater efficiently. The water treatment unit is based on oxidation of arsenic along with iron and subsequent filtration with a rapid sand filter. Both chemical and biotic oxidation of arsenic and iron are ensured by setting up a biofilm carrier column before the rapid sand and anthracite filter unit. Finally, a parallel resin column has been installed to remove the residual arsenic. The water quality throughout the system varied substantially during the timeline of the project. The produced safe water at the end of the fieldwork did not meet the drinking water standards set by the WHO. Nevertheless, several recommendations have been provided and, in the future, more intensive backwash of the water treatment unit might be the key to produce and distribute safe water. Overall, a deeper knowledge on arsenic contamination and their effects have been achieved, and the improvement of the Bangladeshis live quality has been attempted.