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This work shows the results for the first time of calibrating and validating a mathematical model, capable of predicting the amounts of O 3  and O 2  necessary to reduce pollution levels in a lake based on the chemical oxygen demand (COD), biochemical oxygen demand (BOD 5 ), total nitrogen (TN), total phosphorus (TP) and fecal coliforms (FC) concentrations. The model was designed to treat a natural or artificial lake as though it were an aerated lagoon operating as an idealized continuous flow complete-mix reactor. The O 3  yield constant for eliminating the non-biodegradable fraction of COD and for deactivating fecal coliforms were laboratory derived and calibrated with field values. Based on the field parameters, the model accurately predicted a reduction in BOD 5 , COD, TN, TP and FC of 53%, 51%, 39%, 42% and 98%, respectively. The model proved to be effective in predicting O 2  and O 3  demand and time of recovery of a polluted water body.

Predictive modeling to determine oxygen and ozone doses applicable to in situ remediation of polluted water bodies