Determination of nitrification kinetics by the ANITA-DOstat biosensor

Ficara, Elena; Rocco, A.; Rozzi, A.

doi:10.2166/wst.2000.0254

Cited by 15 publications

(6 citation statements)

References 4 publications

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“…DO-stat and pH-stat techniques can be performed on the same sample and their results combined to allow for the simultaneous assessment of both ammonium and nitrite oxidations kinetics leading to very reproducible estimates of both ammonium and nitrite oxidisers kinetic parameters (Ficara et al 2000).…”

Section: The Automatic Ph/do-stat Titrator Prototypementioning

confidence: 99%

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Automatic set-point titration for monitoring nitrification in SBRs

Fiocchi

Ficara

Bonelli

et al. 2008

Water Science and Technology

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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 (TITrimetric 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.

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Section: The Automatic Ph/do-stat Titrator Prototypementioning

confidence: 99%

“…: Massone et al 1998;Ficara & Rozzi 2001Yuan & Bogaert 2001;Rozzi et al 2004); † biomass treatment capacity, in terms of process rate (e.g. Ramadori et al 1980;Massone et al 1996;Bogaert et al 1997;Gernaey et al 1998;Ficara et al 2000;Foxon et al 2002;Petersen et al 2002).…”

Section: Introductionmentioning

confidence: 99%

Automatic set-point titration for monitoring nitrification in SBRs

Fiocchi

Ficara

Bonelli

et al. 2008

Water Science and Technology

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“…This idea was then extensively developed and results on the estimation of nitrification rate and to ammonia concentration can be found in the literature [3]. Later, DO-stat titration was also applied and coupled with pH-stat titration [4] to the monitoring of the whole nitrification process, which includes a second oxygen consuming step, i.e. the oxidation of nitrites to nitrates.…”

Section: Applications Of Set-point Titration To Bioprocesses Involved In Wastewater Treatmentmentioning

confidence: 99%

Development of hardware sensors for the online monitoring of SBR used for the treatment of industrial wastewaters

Canziani¹,

Ficara²,

Fiocchi³

et al. 2008

Mathematical and Computer Modelling of Dynamical Systems

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The main challenge in the management of a sequencing batch reactor, for the biological treatment of urban and industrial wastewaters, is to ensure stable treatment efficiency under highly variable influent quality and quantity. To cope with this challenge, online instrumentation is fundamental, since it allows to characterize both influent variability and process efficiency. The more the online data are closely correlated with influent quality and SBRs treatment capacity, the more straightforward is the implementation of control strategies based on these data. In this paper, two monitoring techniques are described, which allow to obtain influent-related and process-related data: set-point titration and UV spectrophotometry. Despite the very different measuring principles, both techniques were successfully applied to SBRs monitoring and control leading to comparable results.

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“…Titrimetry is a validated technique for nitrification rate measurement [22,23] and for the estimation of AOB kinetic parameters, however, it has never been used to evaluate the effect of both sudden and gradual temperature changes on AOB activity.…”

Section: Introductionmentioning

confidence: 99%

Applicability of the Arrhenius model for ammonia oxidizing bacteria subjected to temperature time gradients

Mannucci

Munz

Mori

et al. 2014

Front. Environ. Sci. Eng.

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The aim of this work is to identify the range of applicability of Arrhenius type temperature dependence for Ammonia Oxidizing Bacteria (AOB) subjected to temperature time gradients through continuous titrimetric tests. An innovative online differential titrimetric technique was used to continuously monitor the maximum biologic ammonia oxidation rate of the biomass selected in a pilot scale membrane bioreactor, as a function of temperature time gradients. The monitoring technique is based on the measurement of alkalinity and hydrogen peroxide consumption rates in two parallel reactors operated in nonlimiting substrate conditions for AOB; both reactors were continuously fed with mixed liquor and in one of them AOB were inhibited with allylthiourea. The effects of temperature decrease rates in the range 1 to 4°C$h -1 were evaluated by controlling the titrimetric reactor in the temperature range 10°C-20°C. The dependence of growth kinetics on temperature time gradients and the range of applicability of Arrhenius model for temperature dependency of AOB growth kinetics were assessed. The Arrhenius model was found to be accurate only with temperature gradients lower than 2°C$h -1 . The estimated Arrhenius coefficients (θ) were shown to increase from 1.07 to 1.6 when the temperature decrease rate reached 4°C$h -1 .

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Determination of nitrification kinetics by the ANITA-DOstat biosensor

Cited by 15 publications

References 4 publications

Automatic set-point titration for monitoring nitrification in SBRs

Automatic set-point titration for monitoring nitrification in SBRs

Development of hardware sensors for the online monitoring of SBR used for the treatment of industrial wastewaters

Applicability of the Arrhenius model for ammonia oxidizing bacteria subjected to temperature time gradients

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