Nitrogen removal from water, either potable or domestic and industrial wastewater, has become mandatory for the protection of the environment and public health. Biological nitrogen removal is achieved by the combination of two processes: nitrification and denitrification. Nitrification consists in the sequential oxidation of ammonium-nitrogen to nitrite and finally to nitrate-nitrogen and is catalyzed by autotrophic microorganisms under aerobic conditions. Denitrification, on the other hand, consists in the reduction of produced nitrate-nitrogen finally to nitrogen gas under anoxic conditions and is catalyzed by heterotrophic, facultative aerobic microorganisms.In the recent years, considerable attention has been paid to the usage of a treatment system called Sequencing Batch Reactor (SBR), instead of the typical continuous flow system. SBR system operation consists in wastewater treatment through a sequence of discrete process periods in a single basin.Significant research effort has been spent in finding alternative carbon sources for denitrification and bypassing the nitratification process. Both goals are attractive from an economic point of view due to the minimization of the operational cost of the process.The present work aims to the study of the performance of an SBR for nitrogen removal by using, endogenous carbon sources for denitrification and operational strategies that promote nitratification bypass. The experimental work showed that nitrogen removal is achievable with satisfactory performance using operational strategy with a small aerobic:anoxic phase duration ratio of 1:3. Moreover, implementation of multiple aerobic/anoxic pairs with the same aerobic:anoxic phase ratio leads to nitratification bypass, giving excellent performance in terms of nitrogen removal.Aiming towards minimization of the operational cost (that of aeration) while ensuring acceptable effluent quality (ammonium concentration under a limit level), an adaptive optimization algorithm was implemented to a nitrifying SBR. The ability of the algorithm to handle disturbances in the influent ammonium-nitrogen concentration, leading the system to its new optimal operation point after the introduction of each disturbance, is demonstrated.
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