Nitrification is usually the bottleneck of biological nitrogen removal processes. In SBRs systems, it is not often enough to monitor dissolved oxygen, pH and ORP to spot problems which may occur in nitrification processes. Therefore, automated supervision systems should be designed to include the possibility of monitoring the activity of nitrifying populations. Though the applicability of set-point titration for monitoring biological processes has been widely demonstrated in the literature, the possibility of an automated procedure is still at its early stage of industrial development. In this work, the use of an at-line automated titrator named TITAAN (TlTrimetric Automated ANalyser) is presented. The completely automated sensor enables us to track nitrification rate trend with time in an SBR, detecting the causes leading to slower specific nitrification rates. It was also possible to perform early detection of toxic compounds in the influent by assessing their effect on the nitrifying biomass. Nitrifications rates were determined with average errors ± 10% (on 26 tests), never exceeding 20% as compared with UV-spectrophotometric determinations. © IWA Publishing 2008.

Automatic set-point titration for monitoring nitrification in SBRs

Pirani M.;Ratini P.;
2008

Abstract

Nitrification is usually the bottleneck of biological nitrogen removal processes. In SBRs systems, it is not often enough to monitor dissolved oxygen, pH and ORP to spot problems which may occur in nitrification processes. Therefore, automated supervision systems should be designed to include the possibility of monitoring the activity of nitrifying populations. Though the applicability of set-point titration for monitoring biological processes has been widely demonstrated in the literature, the possibility of an automated procedure is still at its early stage of industrial development. In this work, the use of an at-line automated titrator named TITAAN (TlTrimetric Automated ANalyser) is presented. The completely automated sensor enables us to track nitrification rate trend with time in an SBR, detecting the causes leading to slower specific nitrification rates. It was also possible to perform early detection of toxic compounds in the influent by assessing their effect on the nitrifying biomass. Nitrifications rates were determined with average errors ± 10% (on 26 tests), never exceeding 20% as compared with UV-spectrophotometric determinations. © IWA Publishing 2008.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11566/300688
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