Literature DB >> 16300816

Optimizing experimental design to estimate ammonia and nitrite oxidation biokinetic parameters from batch respirograms.

Kartik Chandran1, Barth F Smets.   

Abstract

Knowledge of relative NH(4+)-N to NO(2-)-N oxidation and NO(2-)-N to NO(3-)-N oxidation dynamics is essential before application of either single-step or two-step nitrification models to fit batch nitrification respirograms. We have previously shown that two step nitrification models based on respirometry permit the estimation of kinetic parameters for both nitrification steps from a single respirogram associated with NH(4+)-N to NO(3-)-N oxidation. However, two-step model parameter estimates are meaningful only under circumstances when the respirograms contain sufficient kinetic information pertaining to both steps. In this study, we present an operationally amenable extant batch nitrification respirometric assay to engender maximal information content in the resulting respirograms with respect to both constituent nitrification steps. The developed design consists of an initial NH(4+)-N pulse to a nitrifying biomass sample followed by an additional NO(2-)-N pulse at an optimal time point, which can be rigorously determined by maximizing the value of the determinant of the Fisher information matrix, Det(F) or, alternatively, by visually identifying the point of NH(4+)-N depletion during the respirometric assay. The proposed design is applicable for accurate determination of the Monod kinetic parameter estimates for both nitrification steps from batch respirograms even when the pseudo-first order rate coefficients for the two nitrification steps are nearly equal; a condition under which standard NH(4+)-N to NO(3-)-N respirograms typically lack information with respect to NO(2-)-N oxidation.

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Year:  2005        PMID: 16300816     DOI: 10.1016/j.watres.2005.10.001

Source DB:  PubMed          Journal:  Water Res        ISSN: 0043-1354            Impact factor:   11.236


  8 in total

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Journal:  PLoS One       Date:  2011-06-16       Impact factor: 3.240

7.  A systematic model identification method for chemical transformation pathways - the case of heroin biomarkers in wastewater.

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8.  Synthetic Microbial Ecology: Engineering Habitats for Modular Consortia.

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Journal:  Front Microbiol       Date:  2017-06-16       Impact factor: 5.640

  8 in total

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