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Quantifying fat, oil, and grease deposit formation kinetics

Iasmin, Mahbuba, Dean, Lisa O., Ducoste, Joel J.
Water research 2016 v.88 pp. 786-795
calcium, calcium chloride, calcium sulfate, canola, computer software, crystallization, fatty acid composition, hydrolysis, ions, mechanistic models, pH, saponification, sewage systems, tallow, temperature, triacylglycerols, United States
Fat, oil, and grease (FOG) deposits formed in sanitary sewers are calcium-based saponified solids that are responsible for a significant number of nationwide sanitary sewer overflows (SSOs) across United States. In the current study, the kinetics of lab-based saponified solids were determined to understand the kinetics of FOG deposit formation in sewers for two types of fat (Canola and Beef Tallow) and two types of calcium sources (calcium chloride and calcium sulfate) under three pH (7 ± 0.5, 10 ± 0.5, and ≈14) and two temperature conditions (22 ± 0.5 and 45 ± 0.5 °C). The results of this study displayed quick reactions of a fraction of fats with calcium ions to form calcium based saponified solids. Results further showed that increased palmitic fatty acid content in source fats, the magnitude of the pH, and temperature significantly affect the FOG deposit formation and saponification rates. The experimental data of the kinetics were compared with two empirical models: a) Cotte saponification model and b) Foubert crystallization model and a mass-action based mechanistic model that included alkali driven hydrolysis of triglycerides. Results showed that the mass action based mechanistic model was able to predict changes in the rate of formation of saponified solids under the different experimental conditions compared to both empirical models. The mass-action based saponification model also revealed that the hydrolysis of Beef Tallow was slower compared to liquid Canola fat resulting in smaller quantities of saponified solids. This mechanistic saponification model, with its ability to track the saponified solids chemical precursors, may provide an initial framework to predict the spatial formation of FOG deposits in municipal sewers using system wide sewer collection modeling software.