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Microbial responses to combined oxidation and catalysis treatment of 1,4-dioxane and co-contaminants in groundwater and soil
- Miao, Yu, Johnson, Nicholas W., Heck, Kimberly, Guo, Sujin, Powell, Camilah D., Phan, Thien, Gedalanga, Phillip B., Adamson, David T., Newell, Charles J., Wong, Michael S., Mahendra, Shaily
- Frontiers of environmental science & engineering 2018 v.12 no.5 pp. 2
- Devosia, Massilia, Sphingomonas, biodegradation, biodiversity, bioinformatics, catalysts, catalytic activity, chemical treatment, community structure, dioxane, discriminant analysis, groundwater, hydrogen peroxide, metagenomics, microbial communities, microbiome, microorganisms, oxidation, soil, volatile organic compounds
- Post-treatment impacts of a novel combined hydrogen peroxide (H₂O₂) oxidation and WOₓ/ZrO₂ catalysis used for the removal of 1,4-dioxane and chlorinated volatile organic compound (CVOC) contaminants were investigated in soil and groundwater microbial community. This treatment train removed ~90% 1,4-dioxane regardless of initial concentrations of 1,4-dioxane and CVOCs. The Illumina Miseq platform and bioinformatics were used to study the changes to microbial community structure. This approach determined that dynamic shifts of microbiomes were associated with conditions specific to treatments as well as 1,4-dioxane and CVOCs mixtures. The biodiversity was observed to decrease only after oxidation under conditions that included high levels of 1,4-dioxane and CVOCs, but increased when 1,4-dioxane was present without CVOCs. WOₓ/ZrO₂ catalysis reduced biodiversity across all conditions. Taxonomic classification demonstrated oxidative tolerance for members of the genera Massilia and Rhodococcus, while catalyst tolerance was observed for members of the genera Sphingomonas and Devosia. Linear discriminant analysis effect size was a useful statistical tool to highlight representative microbes, while the multidimensional analysis elucidated the separation of microbiomes under the low 1,4-dioxane-only condition from all other conditions containing CVOCs, as well as the differences of microbial population among original, post-oxidation, and post-catalysis states. The results of this study enhance our understanding of microbial community responses to a promising chemical treatment train, and the metagenomic analysis will help practitioners predict the microbial community status during the post-treatment period, which may have consequences for long-term management strategies that include additional biodegradation treatment or natural attenuation.