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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Article
Author(s)
Nathaniel J. Barnes, Alan R. Bowers and Matthew P. Madolora
Full-Text PDF XML 621 Views
DOI:10.17265/2162-5298/2018.10.002
Affiliation(s)
Department of Civil and Environmental Engineering, Vanderbilt University, Nashville, TN 37235, USA
ABSTRACT
In wastewater
facilities, struvite (MgNH4PO4·6H2O)
precipitation and subsequent accumulation within sludge processing can be an
expensive nuisance or a pathway to orthophosphate reclamation and beneficial
reuse. Predictive solubility models developed in the past have been
computationally intensive, highly conservative, and have employed uncertain
equilibrium constants for the evaluation of solution saturation. The StrPI
(Struvite Precipitation Index) developed in this study is a new,
computationally light framework for predicting struvite precipitation based on
saturation pH. The model permits process-specific calibration (i.e. StrPI plus
a correction pH) to deal with the highly variable characteristics of wastewater
streams and to eliminate the pH-independent overprediction inherent in existing
solubility models. Verification of this model was performed across a range of
waste compositions, ionic strengths, and root-mean-square velocity gradients
using data from both synthetic laboratory experiments and field tests. The
StrPI framework was found to be an effective and uncomplicated predictor of
struvite precipitation in both environments.
KEYWORDS
Struvite precipitation, scaling, recovery, equilibrium modeling, wastewater.
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