Mechanistic model advancements for optimal calcium removal in water treatment: Integral operation improvements and reactor design strategies

• Published in: Water research (Oxford) 2025-01, Vol.268 (Pt B), p.122781, Article 122781
• Main Authors: Seepma, Sergěj Y.M.H., Koskamp, Janou A., Colin, Michel G., Chiou, Eleftheria, Sobhan, Rubayat, Bögels, Tim F.J., Bastiaan, Tom, Zamanian, Hadi, Baars, Eric T., de Moel, Peter J., Wolthers, Mariëtte, Kramer, Onno J.I.
• Format: Article
• Language: English
• Subjects: Calcium - chemistry; Calcium Carbonate - chemistry; Calcium carbonate crystallization and nucleation; Drinking Water - chemistry; Filtration; Fluidized bed reactor; Mechanistic prediction model; Models, Theoretical; Multiphase flow systems; Plant-Wide integral water treatment; Water Pollutants, Chemical - chemistry; Water Purification - methods; Water Softening
• ISSN: 0043-1354; 1879-2448; 1879-2448
• DOI: 10.1016/j.watres.2024.122781

•Our novel model provides new tools for improving calcium removal in water treatment.•Turning black-box methods into white-box and data-driven optimization strategies.•Proposed model offers future-proof reactor design for improved water softening.•Integral approach enhances flexibility and accuracy in water treatment operations.•Unique model integrates multiple research fields for a new water treatment approach. 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