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

Abstract

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.

Keywords

• polluted lake restoration
• phosphorus removal
• nitrogen removal
• surface water quality
• in situ remediation
• artificial aeration