Limitations of Current Approaches for Predicting Groundwater Vulnerability from PFAS Contamination in the Vadose Zone

Abstract

This column reviews the general features of PHT3D Version 2, a reactive multicomponent transport model that couples the geochemical modeling software PHREEQC-2 (Parkhurst and Appelo 1999) with three-dimensional groundwater flow and transport simulators MODFLOW-2000 and MT3DMS (Zheng and Wang 1999). The original version of PHT3D was developed by Henning Prommer and Version 2 by Henning Prommer and Vincent Post (Prommer and Post 2010). More detailed information about PHT3D is available at the website http://www.pht3d.org.The review was conducted separately by two reviewers. This column is presented in two parts.

Role of Mineral–Organic Interactions in PFAS Retention by AFFF-Impacted Soil

“…Complete retention ( M R = 100%) was a rare exception, even for those that had eight fluorinated carbons (Figure ). Overall, the retention of anionic C ≤ 7 PFAS did not correlate with the OC content in any of the four soil columns (Figure ), indicating that, in low OC systems at least, OC content is not predictive for PFAS retention. ,− , …”

“…Overall, the retention of anionic C ≤ 7 PFAS did not correlate with the OC content in any of the four soil columns (Figure 3), indicating that, in low OC systems at least, OC content is not predictive for PFAS retention. 22,[28][29][30]32 In the case of zwitterionic PFAS, complete retention (M R = 100%) was the norm (Figure 3) with a minority of zwitterionic PFAS breaking through (M R < 100%) after five pore volumes of water. The spread in M R was greatest for C ≤ 4 zwitterionic PFAS.…”

“…To date, organic carbon (OC) − and the length of the fluorinated carbon chain (as a proxy for molecular hydrophobicity) are viewed as the primary features related to PFAS partitioning to soil, , especially for PFAS with more than six or seven fluorinated carbons. − However, recent analyses of published soil partitioning coefficients for anionic PFAS indicate that, in soils with less than 5% OC, the fluorinated tail–OC relationship is not a robust predictor of sorption, , with one study reporting little change in sorption with increasing OC content . Several investigators also noted that the quality of the OC as opposed to the quantity alone may be a better predictor of anionic PFAS sorption. ,− Other researchers, using column and batch-based experiments suggest that soil constituents and interaction mechanisms other than strict hydrophobic partitioning to OC were likely responsible for PFAS sorption.…”

Influence of Tension-Driven Flow on the Transport of AFFF in Unsaturated Media

“…The extensive application of aqueous film-forming foams (AFFF) containing per- and polyfluoroalkyl substances (PFAS) for extinguishing hydrocarbon-based fires, along with other surfactants and solvents, has led to their widespread distribution in a variety of environmental media. − AFFF solutions can infiltrate into the vadose zone and become a major reservoir for PFAS release and thus serve as a long-term source of groundwater contamination. − PFAS-contaminated aquifers that also serve as a drinking water source can result in a primary PFAS exposure route for humans. − …”

Predicting Groundwater PFOA Exposure Risks with Bayesian Networks: Empirical Impact of Data Preprocessing on Model Performance

“…Traditionally, contaminant occurrence in groundwater is predicted using mechanistic models based on physicochemical properties of the contaminant and aquifer. , However, building such models to predict PFOA fate and transport is challenged by the wide variety of potential sources, complex chemical mixtures typically present in those sources, potential for pollutant cotransport, and lack of accurate parameters describing related physicochemical processes (such as sorption at fluid-water and solid–water interfaces) in real-world and highly heterogeneous subsurface media . For example, a recent case study evaluation of a mechanistic model for predicting PFOA occurrence in Michigan’s Huron River watershed concluded that the model “underestimated the magnitude of PFOA concentration due to a lack of information from diffusive sources and historical loads” …”