An improved model of calcium carbonate crystallization

Abstract

One of the main targets of Waternet, the water-cycle company of Amsterdam, is to increase the sustainability of water treatment. To achieve this goal, it is necessary to improve the efficiency and to decrease the use of chemicals during pellet softening process. However, the model of Van Schagen et al. (2008 b,c) that is currently used to optimize the pellet softening process is not predicting accurately enough the pH and calcium profile over the height of the pellet softening reactor. The calcium carbonate crystallization is calculated, in this model, using a linear relationship between the rate of crystallization and supersaturation with an additional diffusion parameter to take into account the flow conditions inside the reactor.
To determine more accurately the rate of calcium carbonate during the pellet softening process, two types of experiments were conducted during this research: STR batch and PFR fluidized bed experiments. Firstly, the experimental results were compared with the predictions of two linear models: the model of Wiechers et al. (1975) from literature and the one-rate-constant model developed in this research. Based on the results, it was concluded that it is not possible to improve the prediction of calcium carbonate crystallization kinetics if a linear model with one-rate-constant is used as proposed by Van Schagen. When the rate of crystallization is plotted against supersaturation a bending of the curve is observed at low supersaturation due to a sharp decrease in the rate of crystallization. Other researchers, such as Dreybrodt et al. (1997) has also observed that the rate of calcium carbonate crystallization is not linearly related to supersaturation when water or seeding material with inhibiting compounds is used. To describe this bending of the curve, two models were considered: the exponential model of Lasaga (1998) and the two-rate-constants model that consists of two linear equations. In this research, the two-rate-constants model was chosen instead of the exponential Lasaga model because it is easier to fit to the experimental results and gives a better overview of the dependence of the rate of crystallization from supersaturation. The two-rate-constants model significantly improves the prediction of calcium carbonate crystallization in a pellet softening fluidized bed reactor. The average relative error of this model, for the prediction of the calcium profile in a full-scale reactor, is only 2-5% while the average relative error of the one-rate-constant model is approximately 15-30%. Therefore, the two-rate-constants model predicts better the calcium carbonate crystallization and can be used to describe much more accurately the pellet softening process compared to the models found in literature.
Based on the results of the research, it can be concluded that the performance of a pellet softening fluidized bed reactor cannot be significantly improved by increasing the height of the reactor. On the other hand, it is possible that performance is enhanced by removing inhibitors such as organic carbon from the water. Nevertheless, further research is necessary to determine the effect of inhibitors, such as organic carbon, on water softening. Also, in order to determine more accurately the model parameters, the experimental set up should be adjusted in order to represent better the conditions inside a pellet softening fluidized bed reactor. In particular, increasing the height of the reactor and mixing the caustic soda at the bottom of the column is necessary.