Enhanced attenuation (EA) to manage PFAS plumes in groundwater

REMEDIATION-THE JOURNAL OF ENVIRONMENTAL CLEANUP COSTS TECHNOLOGIES & TECHNIQUES(2022)

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摘要
Remediation of per- and polyfluoroalkyl substances (PFAS) in groundwater is particularly challenging because of their unique chemical and fate and transport properties. Many conventional in-situ remediation technologies, commonly applied to address other groundwater contaminants, have proven ineffective for treatment of PFAS. Given their stability, destruction of PFAS in-situ has remained elusive as an in-situ treatment option. Consequently, new approaches to manage PFAS groundwater plumes are of great interest to environmental practitioners. We propose that enhancing PFAS retention can play an important role in reducing PFAS mass flux and providing long-term protection of downgradient groundwater receptors. Enhanced retention of PFAS fits directly into the enhanced attenuation (EA) framework, an established groundwater remediation strategy that was developed in the first decade of the 2000s for other groundwater contaminants. In this paper, we propose eight EA approaches for PFAS in groundwater, including technologies that are currently being implemented at PFAS sites (e.g., injection of particulate carbon amendments), applications of conventional remediation technologies to PFAS sites (e.g., capping to retain PFAS in the vadose zone), and novel, innovative approaches (e.g., intentional food grade LNAPL emplacement to retain PFAS) for enhanced PFAS retention. These EA approaches leverage the properties of PFAS to (i) facilitate sorption to conventional and novel sorbents, (ii) concentrate PFAS at air/water interface via gas sparging, and/or (iii) encourage retention via tidal pumping and PFAS salting out processes. For each of the proposed EA approaches, we describe the methodology or concept and discuss the key processes, potential applications, anticipated increases in PFAS retention compared to natural systems, potential challenges, alternate designs, and current likelihood of large-scale adoption.
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