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Model-driven experimental evaluation of struvite nucleation, growth and aggregation kinetics

Galbraith, S.C., Schneider, P.A.ORCID: 0000-0002-0964-1328 and Flood, A.E. (2014) Model-driven experimental evaluation of struvite nucleation, growth and aggregation kinetics. Water Research, 56 . pp. 122-132.

Link to Published Version: https://doi.org/10.1016/j.watres.2014.03.002
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Abstract

Nutrient stewardship is emerging as an issue of global importance, which will drive the development of nutrient recovery in the near to medium future. This will impact wastewater treatment practices, environmental protection, sustainable agriculture and global food security. A modelling framework for precipitation-based nutrient recovery systems has been developed, incorporating non-ideal solution thermodynamics, a dynamic mass balance and a dynamic population balance to track the development of the precipitating particles. The mechanisms of crystal nucleation and growth and, importantly, aggregation are considered. A novel approach to the population balance embeds the nucleation rate into the model, enabling direct regression of its kinetic parameters. The case study chosen for the modelling framework is that of struvite precipitation, given its wide interest and commercial promise as one possible nutrient recovery pathway. Power law kinetic parameters for nucleation, crystal growth and particle aggregation rates were regressed from an ensemble data set generated from 14 laboratory seeded batch experiments using synthetic solutions. These experiments were highly repeatable, giving confidence to the regressed parameter values. The model successfully describes the dynamic responses of solution pH, the evolving particle size distribution subject to nucleation, growth and aggregation effects and the aqueous magnesium concentration in the liquid phase. The proposed modelling framework could well be extended to other, more complex systems, leading to an improved understanding and commensurately greater confidence in the design, operation and optimisation of large-scale nutrient recovery processes from complex effluents.

Publication Type: Journal Article
Publisher: Elsevier BV
Copyright: © 2014 Elsevier Ltd.
URI: http://researchrepository.murdoch.edu.au/id/eprint/38215
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