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

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

[img] PDF (Published Version) - Published Version
Restricted to Repository staff only

View at Publisher Website: http://dx.doi.org/10.1016/j.watres.2014....
 
43
5


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.

Item ID: 38585
Item Type: Article (Research - C1)
ISSN: 1879-2448
Keywords: struvite; nutrient recovery; population balance; nucleation, growth and aggregation; process model; parameter estimation
Date Deposited: 29 Apr 2015 03:58
FoR Codes: 09 ENGINEERING > 0904 Chemical Engineering > 090409 Wastewater Treatment Processes @ 33%
09 ENGINEERING > 0904 Chemical Engineering > 090410 Water Treatment Processes @ 33%
09 ENGINEERING > 0907 Environmental Engineering > 090701 Environmental Engineering Design @ 34%
SEO Codes: 96 ENVIRONMENT > 9611 Physical and Chemical Conditions of Water > 961101 Physical and Chemical Conditions of Water for Urban and Industrial Use @ 75%
97 EXPANDING KNOWLEDGE > 970112 Expanding Knowledge in Built Environment and Design @ 25%
Downloads: Total: 5
More Statistics

Actions (Repository Staff Only)

Item Control Page Item Control Page