Feasibility Analysis Upon Optimal Pollutant Degradation via Compartmental Modeling

Abstract

Due to a lack of plausible kinetic modeling for contaminant attenuation, this study first proposed a “bi-exponential disposition” model to demonstrate the feasibility of wide-ranging applications for the biotic and abiotic degradation of pollutant(s). As a consequence of under-determined systems of bisphenol A (BPA) degradation via advanced oxidation processes (AOPs), a previous study proposed asymptotic approximation singular perturbation for kinetic modeling. The present study extended this model to provide the key performance indicator (KPI); namely, the area under the time course (AUC) of pollutant concentrations from time zero to the endpoint (i.e., AUC0→tf), quantitatively revealing the most promising strategy for pollutant (bio)degradation. Compared to the typical KPI (percentage of pollutant removal), AUC better illustrated the overall efficiency. Compartmental modeling predicted maximal pollutant mitigation through optimal schemes of operation for global optimization. The feasibility of adopting AUC for system prediction was confirmed in cases of azo and anthraquinone dye biodecolorization and acetaminophen (APAP), glyphosate, and bisphenol A (BPA) degradation. Regarding azo dye biodecolorization, the AUC and SDRmax indicated the need to consider cell concentrations. Compartment kinetics could be used for the serial acclimation of anthraquinone dye removal. Moreover, compartmental assessment upon glyphosate and acetaminophen abiotic degradation was also feasible for further applications. To minimize the AUC for optimal degradation of A⇌k3k1B→k2C, the maximal forward rate constants k1 and k2 and minimal backward rate constant k3 should be satisfied simultaneously. Thus, this AUC approach might be broadened to demonstrate overall optimization via Pontryagin’s maximum principle.