Analyzing transient respirometric data by analytical algorithm for Monod kinetic parameters.

Water Sci Technol

Department of Public Health, China Medical University, 91 Hsueh-Shih Rd., Taichung 404, Taiwan, ROC E-mail:

Published: January 2020

This study aims to develop an analytical algorithm with oxygen update (O) data obtained from transient respirometric measurement. Based on Monod kinetics, this study formulates a novel two-phase analytical model for an oxygen uptake rate plot (OUR vs. O) obtained by respirometric techniques. The first phase is a hyperbolic equation relating to exogenous and endogenous respiration, while the second phase is a linear equation for endogenous respiration only. An algorithm was therefore developed to analyze four Monod parameters by locating the best phase-separating point at which the absolute average relative error (ARE) of OUR is minimized. An analysis using test data on acetate verified that the algorithm is capable of transient kinetic parameter estimation with an ARE below 5-10%. A sensitivity analysis on domestic wastewater coupled with a Monte Carlo simulation concluded that the kinetic test must be conducted at a relatively high initial substrate level (S/X ≧ 1 and S/K ≧ 10) for reliable parameter estimation. Moreover, it is crucial to conduct the kinetic test with sufficient and acclimated seed culture for the degradation of substrate. The results of this study can be used to develop an automatic transient kinetic analyzer with modern programmable respirometers.

Download full-text PDF

Source
http://dx.doi.org/10.2166/wst.2020.125DOI Listing

Publication Analysis

Top Keywords

transient respirometric
8
analytical algorithm
8
endogenous respiration
8
transient kinetic
8
parameter estimation
8
kinetic test
8
kinetic
5
analyzing transient
4
respirometric data
4
data analytical
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!