A predictive model for ammonium removal in polishing ponds operated in sequential bath mode

Abstract

The magnitude of pH changes in polishing ponds can be predicted by simple stoichiometric rules if the extent of processes affecting this parameter is known. Thus, the objective of this article was to develop a model that predicts pH variation and ammonia desorption in polishing ponds in sequential batches, depending on the rates of processes that affect pH in ponds and to evaluate the influence of temperature and depth on these processes. As the temperature conditions change during the year, for model validation, tests were carried out under two medium temperature conditions (hot period and cold period) and four lakes with depths between 0.2 and 1.0 m. The proposed model is validated by the good correspondence between the simulated and experimentally obtained values for the two temperature conditions and for both periods. For the hot period, the model excelled, presenting a high linear correlation, always with R 2 above 0.90 for all ponds. For the cold period, the lowest R 2 obtained was 0.74 for the four lakes. Thus, the proposed model is suitable to describe the pH variation and ammonia desorption in polishing ponds in sequential batches, at all analyzed depths and under both temperature conditions. HIGHLIGHTS A predictive model of pH variation and ammonia removal for sequential batch polishing ponds was developed.; The model showed a high correlation between simulated and experimental values. Finding out how in SBPP the removal of ammonia takes place through volatilization.; The predictive model can be used in SBPP for various conditions (temperature, depth, sewage characteristics) to obtain the retention time required for ammonia removal with good accuracy.; The results indicate that SBPP requires a much smaller area than WSP, still showing ammonia removal.;

Keywords

• ammonia desorption
• ph elevation
• polishing ponds
• predictive models
• sequential batch