Sequential kinetic parameter estimation of anaerobic fluidized bed bioreactor using an optimization technique

Mathematical model parameters for the methanogenic degradation of propylene glycol were estimated in a sequential manner by means of an optimization technique. Model parameters determined from an initial experimental data set using one bioreactor were then verified with the results from a second bioreactor. The proposed methodology is a useful tool to obtain model parameters for continuous flow reactors with completely mixed regime. Abbrevations: S – substrate concentration (mg COD l^–1); S _in – influent substrate concentration (mg COD l^–1); D _L – dilution rate (day^–1); – stoichiometric coefficients (ND); nx – number of microbial species (ND); X _S – fixed biomass concentration (mg biomass l^–1); X _L – suspended biomass concentration of (mg biomass l^–1); k _d – decay rate of biomass (day^–1); b _S – specific detachment rate of biofilm (day^–1); – specific growth rate of biomass (day^–1); _m – maximum specific growth rate of biomass (day^–1); K _S – half saturation constant (mg COD l^–1); K _I – inhibition constant (mg COD l^–1).     

Comparison of static and dynamic respirometry for the determination of stoichiometric and kinetic parameters of a nitrifying process

Respirometry consists in the measurement of the biological oxygen consumption rate under well-defined conditions and has been used for the characterization of countless biological processes. In the field of biotechnology and applied microbiology, several respirometry methods are commonly used for the determination of process parameters. Dynamic and static respirometry, which are based on oxygen measurements with or without continuous aeration, respectively, are the methods most commonly used. Additionally to several respirometry methods, different methods have also been developed to retrieve process parameters from respirometric data. Among them, methods based on model fitting and methods based on the injection of substrate pulse at increasing concentration are commonly used. An important question is then; what respirometry and data interpretation methods should be preferably used? So far, and despite a growing interest for respirometry, relatively little attention has been paid on the comparison between the different methods available. In this work, both static and dynamic respirometry methods and both interpretation methods; model fitting and pulses of increasing concentration, were compared to characterize an autotrophic nitrification process. A total of 60 respirometry experiments were done and exhaustively analysed, including sensitivity and error analyses. According to the results obtained, the substrate affinity constant (K _S ) was better determined by static respirometry with pulses of increasing concentration and the maximum oxygen uptake rate (OUR _ex.max ) was better determined by dynamic respirometry coupled to fitting procedure. The best method for combined K _S and OUR _ex.max determination was static respirometry with pulses of increasing concentration.     

Comparison between a moving bed membrane bioreactor and a conventional membrane bioreactor on membrane fouling

A membrane bioreactor filled with carriers instead of activated sludge named a moving bed membrane bioreactor (MBMBR) was investigated to minimize the effect of suspended solids on membrane fouling. The MBMBR and a conventional membrane bioreactor (CMBR) were operated in parallel for about two months. Unexpectedly, the rate of membrane fouling in MBMBR was about three times of that in CMBR. MBMBR showed a higher cake layer resistance than CMBR due to plenty of filamentous bacteria inhabited in suspended solids in MBMBR. Protein and polysaccharide contents of soluble EPS in MBMBR were obviously larger than those in CMBR. It could be speculated that the overgrowth of filamentous bacteria in MBMBR resulted in severe cake layer and induced a large quantity of EPS, which deteriorated the membrane fouling.     

Comparative kinetic study between moving bed biofilm reactor-membrane bioreactor and membrane bioreactor systems and their influence on organic matter and nutrients removal

New technologies regarding wastewater treatment have been developed. Among these technologies, the moving bed biofilm reactor combined with membrane bioreactor (MBBR-MBR) is a recent solution alternative to conventional processes. This paper presents the results obtained from three wastewater treatment plants working in parallel. The first wastewater treatment plant consisted of a membrane bioreactor (MBR), the second one was a MBBR-MBR system containing carriers both in anoxic and aerobic zones, and the last one consisted of a MBBR-MBR system which contained carriers only in the aerobic zone. The reactors operated with a hydraulic retention time of 26.47 h. During the study, the difference between the experimental plants was not statistically significant concerning organic matter and nutrients removal. However, different tendencies regarding nutrients removal are shown by the three wastewater treatment plants. In this sense, the performances in terms of nitrogen and phosphorus removal of the MBBR-MBR system which contained carriers only in the aerobic zone (67.34 ± 11.22% and 50.65 ± 11.13%, respectively) were slightly better than those obtained from another experimental plants. As a whole, the pilot plant which consisted of a MBR showed better performance from the point of view of the kinetics of the heterotrophic and autotrophic biomass with values of μ_m,H = 0.00858 h⁻¹, μ_m,A = 0.07646 h⁻¹, K_M = 2.37 mg O₂ L⁻¹ and K_NH = 1.31 mg N L⁻¹.     

Nitrifying activity monitoring and kinetic parameters determination in a biofilm airlift reactor by respirometry

The applicability of batch respirometry, as a simple technique for monitoring off-line nitrifying activity and kinetic parameters, was evaluated using two sets of ammonia and nitrite concentrations. The O₂ uptake rate (OUR) profiles obtained from the assays were adjusted to a substrate inhibition model. The maximum specific ammonia-oxidizing biomass activity (r_Smax) was 0.079 g N-NH₄ ⁺ g VSS^–1 d^–1 with a half saturation coefficient (K_S) of 11 mg N-NH₄ ⁺ l^–1 and an inhibition coefficient (K_i) of 3300 mg N-NH₄ ⁺ l^–1. Besides, the maximum specific value of nitrite-oxidizing activity was 0.082 g N-NO₂ ^– g VSS^–1 d^–1 with a K_S of 4.1 mg N-NO₂ ^– l^–1 and K_i of 1400 mg N-NO₂ ^– l^–1.     

Comparison between a moving bed membrane bioreactor and a conventional membrane bioreactor on organic carbon and nitrogen removal

A membrane bioreactor filled with carriers instead of activated sludge named a moving bed membrane bioreactor (MBMBR) was investigated for simultaneously removing organic carbon and nitrogen in wastewater. Its performance was compared with a conventional membrane bioreactor (CMBR) at various influent COD/TN ratios of 8.9–22.1. The operational parameters were optimized to increase the treatment efficiency. COD removal efficiency averaged at 95.6% and 96.2%, respectively, for MBMBR and CMBR during the 4 months experimental period. The MBMBR system demonstrated good performance on nitrogen removal at different COD/TN ratios. When COD/TN was 8.9 and the total nitrogen (TN) load was 7.58 mg/l h, the TN and ammonium nitrogen removal efficiencies of the MBMBR were maintained over 70.0% and 80.0%, respectively, and the removed total nitrogen (TN) load reached to 5.31 mg/l h. Multifunctional microbial reactions in the carrier, such as simultaneous nitrification and denitrification (SND), play important roles in nitrogen removal. In comparison, the CMBR did not perform so well. Its TN removal was not stable, and the removed total nitrogen (TN) load was only 1.02 mg/l h at COD/TN ratio 8.9. The specific oxygen utilization rate (SOUR) showed that the biofilm has a better microbial activity than an activated sludge. Nevertheless, the membrane fouling behavior was more severe in the MBMBR than in the CMBR due to a thick and dense cake layer formed on the membrane surface, which was speculated to be caused by the filamentous bacteria in the MBMBR.     

Investigation of parameters affecting a fixed bed bioreactor process for recombinant cell lines

A BHK 21 cell line expressing a recombinant antibody was grown in a fixed bed reactor (FBR) system using a porous support made of Siran glass beads. The contribution of five process variables (bead and inoculum sizes; circulation and dilution rates; glutamine concentration of the feed) to the productivity of the process (defined as production rate, effluent product concentration or yield of product on medium supplied) was investigated using a partial factorial experimental design. Individually, none of the variables tested had a significant affect upon productivity. The combination of smaller bead and inoculum sizes, higher circulation and dilution rates, plus higher feed glutamine concentration gave a markedly higher productivity than any other combination of variable levels tested. This combination of variable levels suggested that better results shold be obtained using a fluidised bed reactor system. However, comparison of the productivities of the two systems showed that the FBR gave the better results. This result can be explained in terms of the relationship of Qs_rAb to .Abbreviations C concentration - D dilution rate - FBR fixed bed bioreactor - FIBR fluidised bed bioreactor - Gln glutamine - Qs cell specific rate - Qv volumetric rate - rAb recombinant antibody - X_v viable cell density - specific growth rate     

A kinetic model for methanogenesis from whey permeate in a packed bed immobilized cell bioreactor

The fermentation kinetics of methane production from whey permeate in a packed bed immobilized cell bioreactor at mesophilic temperatures and pHs around neutral was studied. Propionate and acetate were the only two major organic intermediates found in the methanogenic fermentation of lactose. Based on this finding, a three-step reaction mechanism was proposed: lactose was first degraded to propionate, acetate, CO(2), and H(2) by fermentative bacteria; propionate was then converted to acetate by propionate-degrading bacteria; and finally, CH(4) and CO(2) were produced from acetate, H(2), and CO(2) by methanogenic bacteria. The second reaction step was found to be the rate-limiting step in the overall methanogenic fermentation of lactose. Monod-type mathematical equations were used to model these three step reactions. The kinetic constants in the models were sequentially determined by fitting the mathematical equations with the experimental data on acetate, propionate, and lactose concentrations. A mixed-culture fermentation model was also developed. This model simulates the methanogenic fermentation of whey permeate very well.     

Kinetic and stoichiometric parameters estimation in a nitrifying bubble column through "in-situ" pulse respirometry

This article proposes a simple "in-situ" pulse respirometric method for the estimation of four important kinetic and stoichiometric parameters. The method is validated in a suspended biomass nitrifying reactor for the determination of (i) maximum oxygen uptake rate (OUR(ex)max), (ii) oxidation yield (f(E)), (iii) biomass growth yield (f(S)), and (iv) affinity constant (K(S)). OUR(ex)max and f(E) were directly obtained from respirograms. In the presented case study, a minimum substrate pulse of 10 mgNH(4) (+)-N L(-1) was necessary to determine OUR(ex)max which was 61.15 +/- 4.09 mgO(2) L(-1) h(-1) (5 repetitions). A linear correlation (r(2) = 0.93) obtained between OUR(ex)max and the biomass concentration in the reactor suggests that biomass concentration can be estimated from respirometric experiments. The substrate oxidation yield, f(E), was determined along 60 days of continuous operation with an average error of 5.6%. The biomass growth yield was indirectly estimated from the substrate oxidation yield f(E). The average obtained value (0.10 +/- 0.04 mgCOD mg(-1)COD) was in accordance with the f(S) estimation by the traditional COD mass balance method under steady-state conditions (0.09 +/- 0.01). The affinity constant K(S) was indirectly estimated after fitting the ascending part of the respirogram to a theoretical model. An average value of 0.48 +/- 0.08 mgNH(4) (+)-N L(-1) was obtained, which is in the range of affinity constants reported in the literature for the nitrification process (0.16-2 mgNH(4) (+)-N L(-1)).     

Detecting and quantifying global instability during a dynamic task using kinetic and kinematic gait parameters

ObjectivesInstability during gait can be identified in many different ways. Recent studies have suggested utilizing spatiotemporal parameters to detect instability during gait. Detecting instability using kinetic and kinematic gait parameters has not yet been examined fully. In addition, these studies have not yet identified measures that are capable of assessing the magnitude of instability. The objective of the present study was to identify kinetic and kinematic gait parameters that can best identify instability and quantify its magnitude.MethodsTen healthy men underwent successive gait analysis testing under three controlled settings: (1) Stage 0 instability (control setting), (2) Stage 1 instability and (3) Stage 2 instability. The levels of instability were precisely applied with the use of a controlled perturbation device (AposTherapy System). Differences between all stages and between stages were identified using Friedman and Wilcoxon tests.ResultsStride-to-stride variability (STSV) in kinetic and kinematic measures increased significantly between stages 0 and 1 or between stages 0 and 2 for almost all parameters (all P<0.05). A significant increase between stage 0 and both stages 1 and 2 was found for knee flexion moment, knee varus moment, knee flexion angle and hip adduction angle. The increase between stages 1 and 2 was variable. Only the knee varus moment parameter showed a significant increase in STSV between stages 1 and 2 (P=0.026).ConclusionsAlmost all kinetic and kinematic gait parameters are sensitive to changes in global instability in a dynamic task. The most sensitive are parameters measured at the knee. Of these, STSV in knee varus moment can be used to quantify the magnitude of dynamic instability.     

Identification of the catalytic mechanism and estimation of kinetic parameters for fumarase

The enzyme fumarase catalyzes the reversible hydration of fumarate to malate. The reaction catalyzed by fumarase is critical for cellular energetics as a part of the tricarboxylic acid cycle, which produces reducing equivalents to drive oxidative ATP synthesis. A catalytic mechanism for the fumarase reaction that can account for the kinetic behavior of the enzyme observed in both isotope exchange studies and initial velocity studies has not yet been identified. In the present study, we develop an 11-state kinetic model of the enzyme based on the current consensus on its catalytic mechanism and design a series of experiments to estimate the model parameters and identify the major flux routes through the mechanism. The 11-state mechanism accounts for competitive binding of inhibitors and activation by different anions, including phosphate and fumarate. The model is identified from experimental time courses of the hydration of fumarate to malate obtained over a wide range of buffer and substrate concentrations. Further, the 11-state model is found to effectively reduce to a five-state model by lumping certain successive steps together to yield a mathematically less complex representation that is able to match the data. Analysis suggests the primary reaction route of the catalytic mechanism, with fumarate binding to the free unprotonated enzyme and a proton addition prior to malate release in the fumarate hydration reaction. In the reverse direction (malate dehydration), malate binds the protonated form of the enzyme, and a proton is generated before fumarate is released from the active site.     

Statistical estimation of parameters in a phylogenetic tree using a dynamic model of the substitutional process

Using a modified version of the substitutional process proposed by Neyman, we estimate the parameters of the phylogenetic tree made up of three species (or groups of species). The parameters estimated are the rate of substitution of amino acids along a protein and the ratio of the times of divergence of the species (or group of species). A method is given for determining the tree structure when it is not known. Both the maximum likelihood and Bayes methods are used in the estimation. The basic model of the substitutional process within the proteins is validated by showing that the estimates of the ratio of the times of divergence of three species computed from two different protein molecules (haemoglobin α and fibrinopeptides) are within one standard deviation of each other. Next we consider the construction of the correct phylogenetic tree made up of three or more taxonomic categories like phyla or class utilizing the structure of the various types of protein molecules of the species in the three categories. The generalization of the procedure for the construction of the entire phylogenetic tree is also indicated. The main advantage of this method of tree construction over the traditional method is that the latter method can use the information of only one type of protein (for example cytochrome c) while the method of this paper can use all the available data from the different molecules. We also discuss the recent controversy over the constancy of the molecular clock.     

Least-squares estimation of batch culture kinetic parameters

This article concerns the development of a simple and effective least-squares procedure for estimating the kinetic parameters in Monod expressions from batch culture data. The basic approach employed in this work was to translate the problem of parameter estimation to a mathematical model containing a single decision variable. The resulting model was then solved by an efficient one-dimensional search algorithm which can be adapted to any microcomputer or advanced programmable calculator. The procedure was tested on synthetic data (substrate concentrations) with different types and levels of error. The effect of endogeneous respiration on the estimated values of the kinetic parameters was also assessed. From the results of these analyses the least-squares procedure developed was concluded to be very effective.     

Biodegradation of dichloromethane in waste water using a fluidized bed bioreactor

Summary Biological treatment of a synthetic waste water containing 120 mM dichloromethane (10.2g/l) was carried out under aerobic conditions using dichloromethane-degrading bacteria as an inoculum. The bacteria were adsorbed to support particles and grown in a fluidized bed bioreactor. Charcoal and sand particles were compared as support materials with regard to abrasion, the maximum degradation rate for dichloromethane and the stability of the biological activity in the system.The use of charcoal led to the incorporation of coal dust into the biomass and to an uncontrollable thickness of the biofilm. Therefore the system became unstable and the biological activity decreased. In contrast sand as support material was indifferent to abrasion and allowed biofilm thickness to be controlled. The dichloromethane degrading capacity of the bioreactor increased during the first 30 days. It reached a steady state level of 1.6 g CH₂Cl₂/lxh. Dichloromethane concentration in the effluent was <0.01 mM (<0.85 mg/l) and consequently the degradation efficiency better than 99.99%.     

Optimal parametric sensitivity control for the estimation of kinetic parameters in bioreactors

In this paper the well-known problem of optimal input design is considered. In particular, the focus is on input design for the estimation of kinetic parameters in bioreactors. The problem is formulated as follows: given the model structure (f,g), which is assumed to be affine in the input, and the specific parameter of interest theta;(k) find a feedback law that maximizes the sensitivity of the model output to the parameter under different flow conditions in the bioreactor and, possibly, minimize the input or state costs. Analytical solutions to these problems are presented. As an example a bioreactor with a biomass that grows according to the well-known Monod kinetics is considered.     

WebCell: a web-based environment for kinetic modeling and dynamic simulation of cellular networks

SUMMARY: WebCell is a web-based environment for managing quantitative and qualitative information on cellular networks and for interactively exploring their steady-state and dynamic behaviors in response to systemic perturbations. It is designed as a user-friendly web interface, allowing users to efficiently construct, visualize, analyze and store reaction network models, thereby facilitating kinetic modeling and in silico simulation of biological systems of interest. A collected model library is also available to provide comprehensive implications for cellular dynamics of the published models.