Operational control strategy on optimal calcium removal in drinking water treatment processes
Insights from reactor experiments, modelling and particle characterization
Sergěj Y.M.H. Seepma (Waternet, Universiteit Utrecht)
Janou A. Koskamp (Universiteit Utrecht)
Michel G. Colin (Waternet)
Eleftheria Chiou (Waternet, TU Delft - Water Management)
Rubayat Sobhan (TU Delft - Water Management, Waternet)
Tim F.J. Bögels (Waternet, Universiteit Utrecht)
Tom Bastiaan (Waternet, Universiteit Utrecht)
Hadi Zamanian (Waternet)
Eric T. Baars (Waternet)
Peter J. de Moel (Waternet, Omnisys)
Mariëtte Wolthers (Universiteit Utrecht)
Onno J.I. Kramer (Waternet, Queen Mary University of London, TU Delft - Complex Fluid Processing)
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Abstract
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.
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