About 50% of the drinking water in the Netherlands is centrally softened by the drinking water companies in a process known as pellet softening. In this process a base and seeding material are mixed in an upflow reactor, where subsequently CaCO3 precipitates on a seed core as pellets. The seeding material is usually sand, but recently CaCO3 was introduced as seeding material at several full scale plants. The pure calcite pellets that are produced as a by-product in these plants can be reused as seeding material, after grinding and sieving part of the produced pellets. The main advantages of this reuse are an expected significant decrease of the ecological footprint of both calcite as raw material and the drinking water treatment plants using pellet softening, and increased valorisation of the pellets. However, the handling and processing of the pellets and seeding material should be such, that microbiological and chemical contamination risks of the drinking water are negligible. This research shows that grinded and sieved CaCO3 outperforms commercial CaCO3 and that microbiological risks can be adequately controlled.@en

Softening at drinking water treatment plants is often realised by fluidised bed pellet reactors. Generally, sand is used as seeding material and pellets are produced as a by-product. To improve to sustainability, research has been carried out to replace the seeding material by re-using grained and sieved calcite pellets as seeding material. An explicit fluidisation model is developed to predict the fluid bed state in fluid bed pellet softening reactors with calcite as seeding material. The fluidisation theory is extended in a model whereby soft sensors are derived and experimentally tested for a wide range of seeding material and pellets. With the soft sensors porosity, particle size and pressure drop can explicitly be calculated. Pilot research has been carried out to calibrate and full-scale experiments to validate the fluidisation models. Four different fluidisation models were reviewed from which the original Richardson-Zaki fluid bed model has been selected as the best explicit fluidisation model to predict the porosity, particle size and pressure drop. Applying a discretisation model for the fluid bed pellet reactor, the current operation of the treatment softening can be improved by estimating the fluidisation, pressure drop behaviour and particle profile. Waternet can apply the Richardson-Zaki fluid bed model in practice for building a soft sensor to achieve optimal bed fluid conditions for the softening process.@en