Relating microbial community composition to treatment performance in an ozone-biologically active carbon filtration...

Treatment trains that couple ozone (O₃) with biologically active carbon (BAC) filtration are of interest as a lower cost, more sustainable, membrane-free approach to water reuse. However, little is known about the microbial communities that are the fundamental drivers of O₃-BAC treatment. The objective of this study was to demonstrate microbial community profiling as a diagnostic tool for assessing the functionality, biological stability, and resilience of coupled physical, chemical, advanced oxidative and biological processes employed in water reuse treatment. We utilized 16S rRNA gene amplicon sequencing to profile the bacterial microbiota over time throughout a potable reuse train employing coagulation, flocculation, sedimentation, ozonation, BAC filtration, granular activated carbon (GAC) adsorption, and UV disinfection. A distinct baseline microbiota was associated with each stage of treatment (ANOSIM, p < 0.05, r-stat = 0.52), each undergoing succession with time and operational shifts. Ozonation resulted in the sharpest shifts (i.e., 83.3 % average change in Genus level relative abundances, when adjusted O₃:TOC ratio > 1), and also variance, in microbial community composition. Adjustment in O₃:TOC ratios, temperature, filter-aid polymer, monochloramine quenching agent, and empty-bed contact time also resulted in measurable changes in the baseline microbial community composition of individual processes, but to a lesser degree. Of these, supplementation of nitrogen and phosphorus resulted in the strongest bifurcation, especially in the microbial communities inhabiting the BAC (ANOSIM: p < 0.05, BAC5 r-stat = 0.32; BAC10 r-stat = 0.54) and GAC (ANOSIM: p < 0.05, GAC10 r-stat = 0.54; GAC20 r-stat = 0.63) units. Additionally, we found that the BAC microbial community was responsive to an inoculation of microbially active media, which resulted in improved TOC removal. The findings of this study improve understanding of bacterial dynamics occurring in advanced water treatment trains and can inform improved system design and operation.