Bacterial degradation of perfluoroalkyl acids.

Advances in biological degradation of per- and polyfluoroalkyl substances (PFAS) have shown that bioremediation is a promising method of PFAS mineralization; however, most of these studies focus on remediation of more reactive polyfluorinated compounds. This review focuses on the defluorination of the more recalcitrant perfluorinated alkyl acids (PFAAs) by bacteria. We highlight key studies that report PFAA degradation products, specific bacteria, and relevant genes. Among these studies, we discuss trends in anaerobic versus aerobic conditions with specific bacterial species or consortia. This holistic review seeks to elucidate the state of PFAA biodegradation research and discuss the need for future research for environmental application.

Modeling the kinetics of perfluorooctanoic and perfluorooctane sulfonic acid biodegradation by Acidimicrobium sp. Strain A6 during the feammox process.

Per- and polyfluoroalkyl substances (PFAS) are emerging contaminants of concern due to their health effects and persistence in the environment. Although perfluoroalkyl acids (PFAAs), such as perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) are very difficult to biodegrade because they are completely saturated with fluorine, it has recently been shown that Acidimicrobium sp. A6 (A6), which oxidizes ammonium under iron reducing conditions (Feammox process), can defluorinate PFAAs. A kinetic model was developed and tested in this study using results from previously published laboratory experiments, augmented with results from additional incubations, to couple the Feammox process to PFAS defluorination. The experimental results show higher Feammox activity and PFAS degradation in the A6 enrichment cultures than in the highly enriched A6 cultures. The coupled experimental and modeling results show that the PFAS defluorination rate is proportional to the rate of ammonium oxidation. The ammonium oxidation rate and the defluorination rate increase monotonically, but not linearly, with increasing A6 biomass. Given that different experiments had different level of Feammox activity, the parameters required to simulate the Feammox varied between A6 cultures. Nonetheless, the kinetic model was able to simulate an anaerobic incubation system and show that PFAS defluorination is proportional to the Feammox activity.

A critical review of modeling Poly- and Perfluoroalkyl Substances (PFAS) in the soil-water environment.

Due to their health effects and the recalcitrant nature of their CF bonds, Poly- and Perfluoroalkyl Substances (PFAS) are widely investigated for their distribution, remediation, and toxicology in ecosystems. However, very few studies have focused on modeling PFAS in the soil-water environment. In this review, we summarized the recent development in PFAS modeling for various chemical, physical, and biological processes, including sorption, volatilization, degradation, bioaccumulation, and transport. PFAS sorption is kinetic in nature with sorption equilibrium commonly quantified by either a linear, the Freundlich, or the Langmuir isotherms. Volatilization of PFAS depends on carbon chain length and ionization status and has been simulated by a two-layer diffusion process across the air water interface. First-order kinetics is commonly used for physical, chemical, and biological degradation processes. Uptake by plants and other biota can be passive and/or active. As surfactants, PFAS have a tendency to be sorbed or concentrated on air-water or non-aqueous phase liquid (NAPL)-water interfaces, where the same three isotherms for soil sorption are adopted. PFAS transport in the soil-water environment is simulated by solving the convection-dispersion equation (CDE) that is coupled to PFAS sorption, phase transfer, as well as physical, chemical, and biological transformations. As the physicochemical properties and concentration vary greatly among the potentially thousands of PFAS species in the environment, systematic efforts are needed to identify models and model parameters to simulate their fate, transport, and response to remediation techniques. Since many process formulations are empirical in nature, mechanistic approaches are needed to further the understanding of PFAS-soil-water-plant interactions so that the model parameters are less site dependent and more predictive in simulating PFAS remediation efficiency.