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

Assessing the suitability of leachability-based screening levels for per- and polyfluoroalkyl substances (PFAS) risk assessment

In recent years, soil screening levels have been adopted by regulatory agencies for certain per- and polyfluoroalkyl substances (PFAS) to assess the risk of groundwater contamination through leaching. These soil screening levels, determined using an established equilibrium-based partitioning equation, have high variability among regulatory groups largely attributed to the diverse reported partitioning coefficients in the literature. This variability between reported partitioning coefficients, and subsequently soil screening levels, is due to the complex leaching behavior of PFAS not being predicted well by the standard equilibrium-based model. This has led one regulatory group to require batch leaching to assess risk rather than setting default soil screening levels based on partitioning equations. In this work, we conducted leaching experiments on five field-sampled soils impacted by aqueous film-forming foams (AFFF), following Leaching Environmental Assessment Framework (LEAF) Method 1316 and compared the results to expected leaching utilizing an equilibrium-based partitioning equation commonly employed by regulatory agencies to establish soil screening levels. Our analysis found among the six PFAS detected in the soils, which have regulatory leaching thresholds established, the partitioning values assumed by the U.S. EPA exhibited the highest accuracy in predicting leachate concentrations. These partitioning values predicted actual leaching within a ± 20 % margin of error for approximately 50 % of sample points, highlighting limitations in relying solely on equilibrium-based partitioning values as predictors of leaching behavior. This discrepancy between predicted and actual leaching has implications for site managers and regulatory entities overseeing PFAS-contaminated sites, suggesting that soil screening level determinations for PFAS might need to be revised to account for the unique transport characteristics of PFAS.

An integrated analytical modeling framework for determining site-specific soil screening levels for PFAS

Soils at many contaminated sites have accumulated a significant amount of per- and polyfluoroalkyl substances (PFAS) and may require remediation to mitigate leaching to groundwater. USEPA's current approaches for determining soil screening levels (SSLs) were developed for non-PFAS contaminants. Because many PFAS are interfacially-active with unique leaching behaviors in soils, the current non-PFAS-specific soil screening models may not be applicable. Following USEPA's general methodology, we develop a new modeling framework representing PFAS-specific transport processes for determining site-specific SSLs for PFAS-contaminated sites. We couple a process-based analytical model for PFAS leaching in the vadose zone and a dilution factor model for groundwater in an integrated framework. We apply the new modeling framework to two typical types of contaminated sites. Comparisons with the standard USEPA SSL approach suggest that accounting for the PFAS-specific transport processes may significantly increase the SSL for some PFAS. For the range of soil properties and groundwater recharge rates examined, while SSLs determined with the new model are less than a factor of 2 different from the standard-model values for less interfacially-active shorter-chain PFAS, they are up to two orders of magnitudes greater for more interfacially-active longer-chain PFAS. The new analytical modeling framework provides an effective tool for deriving more accurate site-specific SSLs and improving site characterization and remedial efforts at PFAS-contaminated sites.

Per- and polyfluoroalkyl substances (PFAS) in final treated solids (Biosolids) from 190 Michigan wastewater treatment plants

Trends in concentration, distribution, and variability of per- and polyfluoroalkyl substances (PFAS) in biosolids are characterized using an extensive dataset of 350 samples from 190 wastewater treatment plants (WWTPs) across Michigan. All samples are comprised of final treated solids generated at the end of the wastewater treatment process. Concentrations of both individual and Σ24 PFAS are lognormally distributed, with Σ24 PFAS concentrations ranging from 1-3200 ng/g and averaging 108 ± 277 ng/g dry wt. PFAS with carboxyl and sulfonic functional groups comprise 29% and 71% of Σ24 PFAS concentrations, respectively, on average. Primary sample variability in concentration is associated with long-chain PFAS with higher tendency for partitioning to biosolids. Short-chain carboxylic compounds, most notably PFHxA, are responsible for secondary concentration variability. Usage of FTSA and PFBS replacements to long-chain sulfonic compounds also contributes to variance in biosolids concentrations. Sulfonamide precursor compounds as a collective group are detected at a similar frequency as PFOS and often have higher concentrations. Trends in PFAS enrichment for individual PFAS vary at least 3 orders-of-magnitude and generally increase with compound hydrophobicity; however, partitioning of PFAS onto solids in WWTPs is a complex process not easily described nor constrained using experimentally-derived partitioning coefficients.

Effect of heavy metal co-contaminants on the sorption of thirteen anionic per- and poly-fluoroalkyl substances (PFAS) in soils

Understanding the sorption behavior of per- and poly-fluoroalkyl substances (PFAS) in soils are essential for assessing their mobility and risk in the environment. Heavy metals often coexist with PFAS depending on the source and history of contamination. In this study, we investigated the effect of heavy metal co-contaminants (Pb2+, Cu2+ and Zn2+) on the sorption of 13 anionic PFAS with different perfluorocarbon chain length (C3-C9) in two soils with different properties. Results revealed that Pb2+, Cu2+ and Zn2+ had little effect on the sorption of most short-chain compounds, while the presence of these heavy metals enhanced the sorption of long-chain PFAS in two soils. The distribution coefficients (Kd) of several long-chain PFAS linearly increased with increasing concentrations of heavy metal, especially in the presence of Pb2+ (ΔKd/Δ [Pb2+] > 3 for PFOS and PFNA vs <1 for PFPeS and PFHxS). While several mechanisms may have contributed to the enhancement of sorption of PFAS, the heavy metals most likely contributed through enhanced hydrophobic interactions of PFAS by neutralizing the negative charge of adsorption surfaces in soils and thus making it more favorable for their partitioning onto the solid phase. Moreover, the increase in the concentrations of heavy metals led to a decrease in the pH of the system and promoted sorption of long-chain compounds, especially in soil with lower organic carbon content. Overall, this study provides evidence that the presence of co-existing heavy metal cations in soils can significantly enhance the sorption of long-chain PFAS onto soil, thereby potentially limiting their mobility in the environment.

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

The plethora of data on PFASs in environmental samples collected in response to growing concern about these chemicals could enable the training of machine-learning models for predicting exposure risks. However, differences in sampling and analysis methods across data sets must be reconciled through data preprocessing, and little information is available about how such manipulations affect the resulting models. This study evaluates how data preprocessing influences machine-learned Bayesian network models of PFOA in groundwater. We link 19 years of PFOA measurements from Minnesota, USA, to publicly available information about potential PFOA sources and factors that may influence their environmental fate. Nine different preprocessing methods were tested, and the resulting data sets were used to train models to predict the probability of PFOA ≥ 35 ppt, the 2017 Minnesota health advisory level. Different preprocessing approaches produced varying model structures with significantly different accuracies. Nonetheless, models showed similar relationships between predictor variables and PFOA exposure risks, and all models were relatively accurate, distinguishing wells at high risk from those at low risk for 82.0% to 89.0% of test data samples. There was a trade-off between data quality and model performance since a stricter data screening strategy decreased the sample size for model training.

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

A comprehensive, generalized approach to predict the retention of per- and polyfluoroalkyl substances (PFAS) from aqueous film-forming foam (AFFF) by a soil matrix as a function of PFAS molecular and soil physiochemical properties was developed. An AFFF with 34 major PFAS (12 anions and 22 zwitterions) was added to uncontaminated soil in one-dimensional saturated column experiments and PFAS mass retained was measured. PFAS mass retention was described using an exhaustive statistical approach to generate a poly-parameter quantitative structure-property relationship (ppQSPR). The relevant predictive properties were PFAS molar mass, mass fluorine, number of nitrogens in the PFAS molecule, poorly crystalline Fe oxides, organic carbon, and specific (BET-N2) surface area. The retention of anionic PFAS was nearly independent of soil properties and largely a function of molecular hydrophobicity, with the size of the fluorinated side chain as the main predictor. Retention of nitrogen-containing zwitterionic PFAS was related to poorly crystalline metal oxides and organic carbon content. Knowledge of the extent to which a suite of PFAS may respond to variations in soil matrix properties, as developed here, paves the way for the development of reactive transport algorithms with the ability to capture PFAS dynamics in source zones over extended time frames.

Recent advances in the remediation of perfluoroalkylated and polyfluoroalkylated contaminated sites

Per- and polyfluoroalkyl substances (PFASs) are compounds used since 1940 in various formulations in the industrial and consumer sectors due to their high chemical and thermal stability. In recent years, PFASs have caused global concern due to their presence in different water and soil matrices, which threatens the environment and human health. These compounds have been reported to be linked to the development of serious human diseases, including but not limited to cancer. For this reason, PFASs have been considered as persistent organic compounds (COPs) and contaminants of emerging concern (CECs). Therefore, this work aims to present the advances in remediation of PFASs-contaminated soil and water by addressing the current literature. The performance and characteristics of each technique were addressed deeply in this work. The reviewed literature found that PFASs elimination studies in soil and water were carried out at a laboratory and pilot-scale in some cases. It was found that ball milling, chemical oxidation and thermal desorption are the most efficient techniques for the removal of PFASs in soils, however, phyto-microbial remediation is under study, which claims to be a promising technique. For the remediation of PFASs-contaminated water, the processes of electrocoagulation, membrane filtration, ozofractionation, catalysis, oxidation reactions - reduction, thermolysis and destructive treatments with plasma have presented the best results. It is noteworthy that hybrid treatments have also proved to be efficient techniques in the removal of these contaminants from soil and water matrices. Therefore, the improvisation and implication of existing techniques on a field-scale are greatly warranted to corroborate the yields obtained on a pilot- and laboratory-scale.