Model predictive control of two-step nitrification and its validation via short-cut nitrification tests
Short-cut nitrification (SCN) is shown to be an attractive technology due to its savings in aeration and external carbon source addition cost. However, the shortage of excluding nitrite nitrogen as a model state in an Activated Sludge Model limits the model predictive control of biological nitrogen removal via SCN. In this paper, a two-step kinetic model was developed based on the introduction of pH and temperature as process controller, and it was implemented in an SBR reactor. The simulation results for optimizing operating conditions showed that with increasing of dissolved oxygen (DO) the rate of ammonia oxidation and nitrite accumulation firstly increased in order to achieve a SCN process. By further increasing DO, the SCN process can be transformed into a complete nitrification process. In addition, within a certain range, increasing sludge retention time and aeration time are beneficial to the accumulation of nitrite. The implementation results in the SBR reactor showed that the data predicted by the kinetic model are in agreement with the data obtained, which indicate that the two-step kinetic model is appropriate to simulate the ammonia removal and nitrite production kinetics.