AUTHOR=Chen Bor-Yann , Lin Yu-Hsiu , Hsueh Chung-Chuan , Hong Jun-Ming 

TITLE=Feasibility Analysis Upon Optimal Pollutant Degradation via Compartmental Modeling

JOURNAL=Frontiers in Environmental Science

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/environmental-science/articles/10.3389/fenvs.2022.923980

DOI=10.3389/fenvs.2022.923980

ISSN=2296-665X

ABSTRACT=Due to lack of plausible kinetic modelling for contaminant attenuation, this study first proposed “biexponential disposition” model to exhibit promising feasibility of wide-ranged applications to biotic and abiotic degradation of pollutant(s).  As a consequence of under-determined systems of bisphenol A (BPA) degradation via advanced oxidation processes (AOPs), prior study proposed asymptotic approximation singular perturbation for kinetic modelling.  This study extended to provide the key performance indicator (KPI)- the area under time course (AUC) of pollutant concentrations from time zero to end-point (i.e., AUC (0~tf)), quantitatively revealing the most promising strategy for pollutant (bio)degradation.  AUC was more environmentally attractive to disclose overall efficiency than typical KPI- the percentage of pollutant removal. Compartmental modeling predicted maximal pollutant mitigation through optimal schemes of operation for global optimization.  With cases of azo dye and anthraquinone dye biodecolorization, acetaminophen (APAP), glyphosate and bisphenol A (BPA) degradation, the promising feasibility to adopt AUC for system prediction was confirmed as anticipated.  Regarding azo dye biodecolorization, as AUC and SDRmax indicated cell concentration should be considered.  Compartment kinetics could be applicable for serial acclimation of anthraquinone dye removal.  Moreover, compartmental assessment upon glyphosate and acetaminophen abiotic degradation was also feasible for further applications.  To minimize AUC for optimal degradation of pollutant, the maximal forward rate constants k1, k2 and minimal backward rate constant k3 should be satisfied simultaneously.  That is, this AUC approach might even be broadened to demonstrate overall optimization via Pontryagin’s maximum principle.