Joint Multi-Optimization of an Extremophilic Microbial Bioanode for Mitigation of Mixed Hazardous Azo Dyes in Textile Synthetic Wastewater

Abstract

Bioelectrochemical systems (BESs), rather than physicochemical processes, are used for wastewater remediation, electricity production, and zero carbon dioxide emission. Textile effluents contain organic and inorganic compounds that can fuel BESs. The main goal of this study was to understand the interplay between the anode material, its surface area, the potential applied to the working electrode (WE), and the concentration of the co-substrate, and how these factors lead to the formation of highly efficient thermohalophilic bioanodes (THB) retrieved from Chott El Djerid (SCD) hypersaline sediment for the treatment of synthetic textile wastewater. To this end, twenty-seven bioanode formation experiments were designed using a Box-Behnken matrix and response surface methodology to understand concomitant interactions. All experiments were conducted in electrochemical reactors of final volume 750 mL inoculated with 80% of enrichment medium containing three azo dyes at a concentration of 300 ppm and 20% of biocatalyst microbial SCD source, at 45 °C. The optimal levels were predicted using NemrodW software as carbon felt (CF) anode material, 6 cm2 anode surface, 7 g/L glucose concentration, and −0.1 V applied potential. These theoretical results were experimentally validated, using maximum current output of 5.23 ± 0.30 A/m2, decolorization rate of 100%, and a chemical oxygen demand (COD) removal rate of 96 ± 1%. Illumina Miseq results revealed that bacterial community harbored the bioanode was dominated at phylum level by Firmicutes (67.1%). At the species level, the biofilm was mainly colonized by Orenia metallireducens species (59.5%). Obtained findings show a promising application of THB in the degradation of recalcitrant molecules as well as for the energy recovery.

Keywords

• bioelectrochemical degradation
• hypersaline sediment
• azo dyes
• response surface methodology
• energy recovery
• metagenomic analysis