Databank transfer-of-information, shortcut and exact estimators used in the wastewater biological treatment process identification

The biological treatment is the most complex step in removing organic and inorganic pollutants from wastewaters, being very sensitive to input-flow oscillations, operating conditions, and biomass evolution. Sudden increases in substrate concentration or some inhibitory substances, deterioration of the biomass, or few observed species, all of these lead to a difficult process modelling and need repeated biokinetics identification for each waste and biomass type. However, the bioprocess numerical analysis is crucial for obtaining significant improvements in the wastewater treatment (WWT) plant performances and safety indices even under imperfect data. The paper exemplifies an advanced route to quickly on-line identify the biodegradation characteristics of new substrates processed by a series of perfectly mixed aeration basins with biomass recycle. The Monod kinetics is recursively identified by using the available collection of plant previous transient operating data and a robust shortcut estimator (MIP). The approximate solution is periodically refined with an exact nonlinear estimator (NLS), checked for consistency and significance versus prior information, and stored in databanks.