Hybrid modeling of counterion mass transfer in a membrane-supported biofilm reactor

Abstract This paper presents a hybrid mechanistic/statistical model for predicting counterion fluxes across an ion-exchange membrane in a membrane-supported biofilm reactor. The model was calibrated with operating data for the removal of nitrate and perchlorate from a simulated contaminated drinking water stream. Two different modeling strategies were tested: a cooperative parallel hybrid model and a competitive mixture-of-experts (MOE) structure both joining a mechanistic Donnan-dialytic transport model and a multivariate projection to latent structures (PLS) model. The MOE structure proved to be a better predictive tool since it combines the two hybrid model elements in a mediated network. The PLS model was used to identify the process variables that are responsible for the mechanistic model inaccuracy. The results showed that biocompartment physicochemical data need to be considered in the modeling of the transport of counterions across the membrane, especially in situations in which the target counterion (e.g., perchlorate or nitrate) is metabolically reduced in the biocompartment. By using this strategy, the complex biofilm contribution to the transport was accounted for, without the need of developing mechanistic models built on simplified and/or inaccurate assumptions.

[1]  G. Quinn,et al.  Experimental Design and Data Analysis for Biologists , 2002 .

[2]  M. Reis,et al.  Removal of mono-valent oxyanions from water in an ion exchange membrane bioreactor: influence of membrane permselectivity. , 2008, Water research.

[3]  W. Blaedel,et al.  Mechanism of trace counterion transport through ion-exchange membranes , 1969 .

[4]  V. Nikonenko,et al.  Dependence of composition of anion-exchange membranes and their electrical conductivity on concentration of sodium salts of carbonic and phosphoric acids , 2001 .

[5]  W J Krzanowski,et al.  Cross-Validation for Choosing the Number of Important Components in Principal Component Analysis. , 1995, Multivariate behavioral research.

[6]  Pedro M. Saraiva,et al.  Hybrid Models Combining Mechanistic Models with Adaptive Regression Splines and Local Stepwise Regression , 2003 .

[7]  S. Feyo de Azevedo,et al.  Knowledge based modular networks for process modelling and control , 2001 .

[8]  N. M. Faber,et al.  Uncertainty estimation for multivariate regression coefficients , 2002 .

[9]  Andrew G. Livingston,et al.  Novel membrane bioreactor for detoxification of VOC wastewaters: Biodegradation of 1,2-dichloroethane , 1995 .

[10]  Michael I. Jordan,et al.  Task Decomposition Through Competition in a Modular Connectionist Architecture: The What and Where Vision Tasks , 1990, Cogn. Sci..

[11]  Andrej-Nikolai Spiess,et al.  An evaluation of R2 as an inadequate measure for nonlinear models in pharmacological and biochemical research: a Monte Carlo approach , 2010, BMC pharmacology.

[12]  M. Reis,et al.  Simultaneous removal of perchlorate and nitrate from drinking water using the ion exchange membrane bioreactor concept. , 2006, Water research.

[13]  Thomas P. Ryan,et al.  Modern Regression Methods , 1996 .

[14]  S. Lanteri,et al.  Selection of useful predictors in multivariate calibration , 2004, Analytical and bioanalytical chemistry.

[15]  Michele Forina,et al.  Chemometric Study and Validation Strategies in the Structure-Activity Relationships of New Cardiotonic Agents , 1997 .

[16]  John W. Shanahan,et al.  Influence of a nitrifying biofilm on local oxygen fluxes across a micro-porous flat sheet membrane , 2006 .

[17]  Marcel Mulder,et al.  Basic Principles of Membrane Technology , 1991 .

[18]  M. Reis,et al.  Ion Exchange Membrane Bioreactor for Selective Removal of Nitrate from Drinking Water: Control of Ion Fluxes and Process Performance , 2002, Biotechnology progress.

[19]  Bruce E. Rittmann,et al.  THE MEMBRANE BIOFILM REACTOR IS A VERSA TILE PLATFORM FOR WATER AND WASTEWATER TREATMENT , 2007 .

[20]  Hua Ye,et al.  Modelling nutrient transport in hollow fibre membrane bioreactors for growing three-dimensional bone tissue , 2006 .

[21]  E N Pistikopoulos,et al.  Prediction of optimal biofilm thickness for membrane‐attached biofilms growing in an extractive membrane bioreactor , 2000, Biotechnology and bioengineering.

[22]  Rui Oliveira,et al.  Multivariate statistical modelling of mass transfer in a membrane-supported biofilm reactor , 2011 .

[23]  B. Glennon,et al.  Review of membrane aerated biofilm reactors , 1999 .

[24]  P. Pavasant,et al.  Substrate counterdiffusion and reaction in membrane-attached biofilms : mathematical analysis of rate limiting mechanisms , 2000 .

[25]  João G Crespo,et al.  Non-mechanistic modelling of complex biofilm reactors and the role of process operation history. , 2005, Journal of biotechnology.

[26]  E. Casey,et al.  Studies on the effect of concentration of a self-inhibitory substrate on biofilm reaction rate under co-diffusion and counter-diffusion configurations , 2009 .

[27]  Dwight Merunka,et al.  Neural networks and the multinomial logit for brand choice modelling: a hybrid approach , 2000 .

[28]  M. Reis,et al.  Mechanism of charged pollutants removal in an ion exchange membrane bioreactor: drinking water denitrification. , 2000, Biotechnology and bioengineering.

[29]  V. Voller,et al.  Advective flow through membrane-aerated biofilms Modeling results , 2006 .

[30]  D. F. Morrison,et al.  Multivariate Statistical Methods , 1968 .

[31]  R. Juang,et al.  Role of membrane-attached biofilm in the biodegradation of phenol and sodium salicylate in microporous membrane bioreactors , 2006 .

[32]  Mark A. Kramer,et al.  Modeling chemical processes using prior knowledge and neural networks , 1994 .

[33]  M. Forina,et al.  Iterative predictor weighting (IPW) PLS: a technique for the elimination of useless predictors in regression problems , 1999 .

[34]  Michael I. Jordan,et al.  Hierarchical Mixtures of Experts and the EM Algorithm , 1994, Neural Computation.

[35]  John F. MacGregor,et al.  Jackknife and bootstrap methods in the identification of dynamic models , 2001 .

[36]  Rasmus Bro,et al.  The N-way Toolbox for MATLAB , 2000 .

[37]  H. Bohn.  Consider biofiltration for decontaminating gases , 1992 .

[38]  M. Reis,et al.  Removal of trace mono-valent inorganic pollutants in an ion exchange membrane bioreactor: analysis of transport rate in a denitrification process , 2003 .

[39]  S. Wold,et al.  PLS-regression: a basic tool of chemometrics , 2001 .

[40]  D. Massart,et al.  Elimination of uninformative variables for multivariate calibration. , 1996, Analytical chemistry.

[41]  M. Gerardi.  Nitrification and Denitrification in the Activated Sludge Process , 2002 .