The precipitation and accumulation of struvite (MgNH4PO4�6H2O) within anaerobic processes has been a costly and enigmatic problem for wastewater treatment facilities. To properly anticipate and mitigate struvite build-up, solubility models have been developed that employ equilibria software for the evaluation of equilibrium equations. Unfortunately, these programs run under the assumption that chemical equilibrium constants are single, universally accepted values, when, in reality, a significantly wide range of values have been published for many of the constants.In this study, a struvite solubility model was developed in which the equilibrium constants were treated as probability distributions within a Monte Carlo simulation in order to understand the effects of uncertainty on the precipitation potential over a range of pH (6 to 8.5), temperature (0 to 50�C), and ionic strength (0 to 1M).  Additionally, a genetic algorithm was applied to the model inputs (ammonia, magnesium, ortho-phosphate, pH, temperature, and ionic strength) to identify the conditions where the uncertainty in each constant was most significant.

Probabilistic approach to modelling struvite precipitation with uncertain equilibrium parameters

248th National Meeting (2014)

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