Intermolecular Interactions, Solute Descriptors, and Partition Properties of Neutral Per- and Polyfluoroalkyl Substances (PFAS)

Competitive adsorption and diffusion of methane and vapor-phase per- and polyfluoroalkyl substances in montmorillonite nano pores: Environmental implications

Vapor-phase perfluoroalkyl and polyfluoroalkyl substances (PFASs), along with methane emissions from landfills has been key contributors of their atmospheric transport and global distribution. Given the persistence, bioaccumulation, and potential health risks associated with PFAS, understanding their transport behavior in landfill gas barrier is of paramount importance. To gain a deeper understanding of the adsorption and diffusion behavior of vapor-phase PFAS in unsaturated, montmorillonite-rich clay barriers, a molecular dynamics simulation was conducted. A 5-nm montmorillonite nanopore incorporating vapor-phase PFAS (Fluorotelomer alcohol, FTOH), methane, and water molecules was modeled considering the interactions between these species. The results indicate that the presence of methane within the montmorillonite system inhibits the diffusion of both water and FTOH. Additionally, methane competes with FTOH for sorption sites, particularly at low moisture content. At 5 % moisture content, the adsorption density peak of methane is 1.5 times greater than that of FTOH due to stronger van der Waals interactions between methane and montmorillonite. However, as moisture content increases, methane adsorption weakens and becomes more dispersed within the montmorillonite pores. In contrast, FTOH retains a distinct adsorption region at 20 % moisture content, exhibiting a density peak of 0.025 g/cm3 that shifts farther from the montmorillonite surface. At high moisture content, FTOH aggregates due to the hydrophobicity of its C-F tail. These findings provide critical insights into the environmental behavior of volatile PFASs and have important implications for the design and optimization of landfill gas barriers.

Strategies to Reduce Uncertainties from the Best Available Physicochemical Parameters Used for Modeling Novel Organophosphate Esters across Multimedia Environments

Organophosphate esters (OPEs) raise growing environmental and human health concerns globally. However, numerous novel OPEs lack data on physicochemical properties, which are essential for assessing environmental fate, exposure, and risks. This study predicted water solubility (Sw), vapor pressure (Vp), octanol-water partition coefficient (Kow), and octanol-air partition coefficient (Koa) at 25 °C for 46 novel OPEs by identifying optimal in silico tools and establishing prediction strategies based on molecular weights (MWs). Prediction discrepancies between in silico tools increased with MWs and structural complexity. Method evaluations for compounds with MWs > 450 g/mol suggest that COSMOtherm is advantageous in predicting Sw and Vp for alkyl-OPEs, while SPARC is better for predicting Vp for aryl- and halogenated-OPEs. For compounds with MWs > 500 g/mol, COSMOtherm and SPARC are recommended for Kow and Koa prediction, respectively. For smaller OPEs, average values from the top three of COSMOtherm, SPARC, EPI Suite, and OPERA, ranked by validation on traditional flame retardants, are recommended. Using improper software could cause deviations in multimedia distribution and overall persistence in the environment by up to 83 and 350%, respectively. The present data and prediction strategy are useful to enhance the reliability of environmental fate, exposure, and risk assessments of various OPEs and emerging contaminants.

Impact of Persistent Endocrine-Disrupting Chemicals on Human Nuclear Receptors: Insights from In Silico and Experimental Characterization

Endocrine-disrupting chemicals (EDCs) are notable for their persistence, bioaccumulation, and associations with cancer. Human nuclear receptors (hNRs) are primary targets disrupted by these persistent EDCs, resulting in alterations to xenobiotic metabolism, lipid homeostasis, and endocrine function, which can lead to carcinogenic effects. Despite their hazardous effects, comprehensive studies on EDC interactions and their impacts on hNRs remain limited. Here, we profiled the interactions of persistent EDCs, including PFAS, plastic additives, bisphenols, polybrominated diphenyl ethers, and phthalates, with key hNRs such as PXR, CAR, PPARα, PPARγ, PPARδ, AR, and RORγt. Through controlled molecular docking simulations, we observed strong binding of the EDCs to these receptors. Further analysis showed that EDCs exhibit strong binding activity towards hNRs by preferentially interacting with hydrophobic amino acids, namely leucine, isoleucine, methionine, and phenylalanine. PFAS demonstrated the highest binding affinity, characterized by a combination of complementary hydrophobic interactions from their fluorinated carbon chains and polar interactions from their functional groups (e.g., carboxylate, sulfonate) across all receptors. Distinct polycyclic and hydrophobic trends, contributing to strong NR binding, were evident in non-PFAS and nonplastic EDCs. The hNR activity assay in HepG2 cells revealed agonistic effects of dicyclohexyl phthalate (DCHP) and di-2-ethylhexyl phthalate (DEHP) on most receptors, except for PPARα. The hNR transcription factor pathway assay in HepG2 cells demonstrated increased gene expression of VDRE and PXR, suggesting potential chronic effects on xenobiotic metabolism and calcium homeostasis. Overall, our findings demonstrate the need for further research into the endocrine disruption and carcinogenic effects of these persistent EDCs.

Streamlining Linear Free Energy Relationships of Proteins through Dimensionality Analysis and Linear Modeling

Linear free energy relationships (LFERs) are pivotal in predicting protein-water partition coefficients, with traditional one-parameter (1p-LFER) models often based on octanol. However, their limited scope has prompted a shift toward the more comprehensive but parameter-intensive Abraham solvation-based poly-parameter (pp-LFER) approach. This study introduces a two-parameter (2p-LFER) model, aiming to balance simplicity and predictive accuracy. We showed that the complex six-dimensional intermolecular interaction space, defined by the six Abraham solute descriptors, can be efficiently simplified into two key dimensions. These dimensions are effectively represented by the octanol-water (log Kow) and air-water (log Kaw) partition coefficients. Our 2p-LFER model, utilizing linear combinations of log Kow and log Kaw, showed promising results. It accurately predicted structural protein-water (log Kpw) and bovine serum albumin-water (log KBSA) partition coefficients, with R2 values of 0.878 and 0.760 and root mean squared errors (RMSEs) of 0.334 and 0.422, respectively. Additionally, the 2p-LFER model favorably compares with pp-LFER predictions for neutral per- and polyfluoroalkyl substances. In a multiphase partitioning model parametrized with 2p-LFER-derived coefficients, we observed close alignment with experimental in vivo and in vitro distribution data for diverse mammalian tissues/organs (n = 137, RMSE = 0.44 log unit) and milk-water partitioning data (n = 108, RMSE = 0.29 log units). The performance of the 2p-LFER is comparable to pp-LFER and significantly surpasses 1p-LFER. Our findings highlight the utility of the 2p-LFER model in estimating chemical partitioning to proteins based on hydrophobicity, volatility, and solubility, offering a viable alternative in scenarios where pp-LFER descriptors are unavailable.

Remediation of per- and polyfluoroalkyl substances (PFAS) contaminated soil via soil washing with various water-organic solvents

The feasibility of soil washing for remediating PFAS-contaminated clay soil using various water-organic solvents was systematically investigated based on the combination of batch and column tests. Batch tests using 22 types of solvents highlighted that 0 % (water) and 5 % solvents could effectively extract PFCAs (≤ C9), while long-chain PFCAs (≥ C10) and PFSAs required 80 % solvents for optimal extraction, with efficiency in the order of EtOH ≤ MeOH < Acetonitrile (ACN), suggesting a strong correlation with carbon chain lengths and functional head groups. Column tests with six selected washing solutions indicated rapid desorption of PFOA and PFOS initially, peaking at liquid-to-solid (L/S) ratios of 3-4 for 0 % and 5 % solutions, and at an L/S ratio of 1 for 80 % solutions. To remediate 1 kg-dry soil to meet the legislatively permissible levels for groundwater in Japan (PFOA + PFOS < 50 ng/L), 11 L of 0 % solution (water) or 5 L of 80 % ACN are required for washing out PFOA, while 62 L of 0 % solution (water) or 53 L of 80 % ACN for PFOS. Future research should address the treatment of PFAS-rich wastewater generated from washing PFAS-contaminated soils and the impacts of washing solutions on soil.

Improved prediction of PFAS partitioning with PPLFERs and QSPRs

Per- and polyfluoroalkyl substances (PFAS) are chemicals of high concern and are undergoing hazard and risk assessment worldwide. Reliable physicochemical property (PCP) data are fundamental to assessments. However, experimental PCP data for PFAS are limited and property prediction tools such as quantitative structure-property relationships (QSPRs) therefore have poor predictive power for PFAS. New experimental data from Endo 2023 are used to improve QSPRs for predicting poly-parameter linear free energy relationship (PPLFER) descriptors for calculating water solubility (SW), vapor pressure (VP) and the octanol-water (KOW), octanol-air (KOA) and air-water (KAW) partition ratios. The new experimental data are only for neutral PFAS, and the QSPRs are only applicable to neutral chemicals. A key PPLFER descriptor for PFAS is the molar volume and this work compares different versions and makes recommendations for obtaining the best PCP predictions. The new models are included in the freely available IFSQSAR package (version 1.1.1), and property predictions are compared to those from the previous IFSQSAR (version 1.1.0) and from QSPRs in the US EPA's EPI Suite (version 4.11) and OPERA (version 2.9) models. The results from the new IFSQSAR models show improvements for predicting PFAS PCPs. The root mean squared error (RMSE) for predicting log KOWversus expected values from quantum chemical calculations was reduced by approximately 1 log unit whereas the RMSE for predicting log KAW and log KOA was reduced by 0.2 log units. IFSQSAR v.1.1.1 has an RMSE one or more log units lower than predictions from OPERA and EPI Suite when compared to expected values of log KOW, log KAW and log KOA for PFAS, except for EPI Suite predictions for log KOW which have a comparable RMSE. Recommendations for future experimental work for PPLFER descriptors for PFAS and future research to improve PCP predictions for PFAS are presented.

Effect of physicochemical parameters on the occurrence of per- and polyfluoroalkyl substances (PFAS) in aquatic environment

Perfluoroalkyl substances (PFAS) and their distribution in aquatic environments have been studied extensively, but more information is needed to link these occurrences to their physicochemical characteristics. Understanding how these parameters influence PFAS can help predict their fate, mobility, and occurrences in water. This study reviewed the influence of physicochemical parameters on the occurrences of PFAS in aquatic environment using the relevant keywords to retrieve articles from databases spanning mostly between 2017 and 2024. The result suggests that high pH, turbidity, and dissolved oxygen, give high concentration of PFAS, while high electrical conductivity, temperature and salinity give low PFAS concentration in the water. Therefore, monitoring and safeguarding the aquatic bodies for human and environmental safety is imperative. Future studies should include the effects of the physicochemical properties on PFAS occurrences in the natural environment and focus on an organism's distinctive characteristics to comprehend the bioaccumulation and biomagnification of PFAS in them and environmental matrices.

Evaluation of the Goss-modified solvation parameter model for the characterization of biphasic systems and descriptor assignments

The solvation parameter model uses six descriptors identified as excess molar refraction, E, dipolarity/polarizability, S, overall hydrogen-bond acidity, A, overall hydrogen-bond basicity, B, McGowan's characteristic volume, V, and the gas-liquid partition constant on hexadecane at 25 °C, L to model the distribution of neutral compounds in biphasic systems. Abraham's version of this model uses all six descriptors with two separate linear free energy relationship models for the transfer of compounds from a gas phase to a condensed phase and between condensed phases. Goss proposed a modification to this model that uses a single calibration model regardless of the physical state for each phase and five of the descriptors employed in Abraham's model (E descriptor is eliminated). The capability of Abraham's model and the Goss-modified model to characterize the contribution of intermolecular interaction to retention for gas and reversed-phase liquid chromatographic systems and distribution in liquid-liquid partition systems is evaluated using the WSU compound descriptor database. These more accurate values for the Abraham descriptors have not been utilized previously for the evaluation of the Goss-modified model and should be more capable of discerning subtle differences in model performance. It is shown that model quality defined by statistical parameters favors Abraham's model over the Goss-modified model with differences in model quality greater for systems in which Abraham's model indicates a significant contribution from electron lone pair interactions and for systems in which one phase is a solvent containing perfluoroalkyl substituents. There is a small systematic difference for the terms describing the combined contributions of cavity formation and dispersion interactions and for interactions of a dipole-type. The contribution of hydrogen-bonding interactions is virtually identical for the two models. The model intercepts are generally different and potentially assigned to a larger contribution from lack-of-fit for the Goss-modified model. Although the Abraham model descriptors have been routinely employed for applications using the Goss-modified model the possibility that Goss-model specific descriptors should be employed was evaluated. Using the Solver method and Goss-model specific calibration models for chromatographic and liquid-liquid partition systems a new set of Goss-specific descriptors was calculated for 28 varied compounds. These descriptors show good statistical agreement with the Abraham descriptor values with an average deviation of 0.009, -0.003, -0.004, and -0.023, respectively, for the S, A, B, and L descriptors, corresponding to a relative absolute deviation in percent of 2.2 %, 3.9 %, 4.3 %, and 1.2 %, respectively.

The Stockholm Convention at a Crossroads: Questionable Nominations and Inadequate Compliance Threaten Its Acceptance and Utility

Twenty years since coming into force, the Stockholm Convention has become a "living" global agreement that has allowed for the addition of substances that are likely, as a result of their long-range environmental transport (LRET), to lead to significant adverse effects. The recent listing of the phenolic benzotriazole UV-328 in Annex A and a draft nomination of three cyclic volatile methylsiloxanes (cVMS) for Annex B draw attention to the fact that many chemicals are subject to LRET and that this can lead to questionable nominations. The nomination of UV-328 and the draft nomination of cVMS also raise the spectre of regrettable substitutions. At the same time, atmospheric monitoring across the globe reveals that environmental releases of several unintentionally produced POPs listed in Annex C, such as hexachlorobenzene and hexachlorobutadiene, are continuing unabated, highlighting shortcomings in the enforcement of the minimum measures required under Article 5. There is also no evidence of efforts to substitute a chemical whose use has been known for three decades to unintentionally produce polychlorinated biphenyls. These developments need to be rectified to safeguard the long-term viability and acceptance of a global treaty of undeniable importance.

Polyparameter Linear Free Energy Relationships for Partitioning of Neutral Organic Compounds to Storage Lipids

Storage lipids are an important compartment in the bioaccumulation of neutral organic compounds. Reliable models for predicting storage lipid-water and storage lipid-air partition coefficients (Kislip/w and Kislip/a), as well as their temperature dependence, are considered useful. Polyparameter linear free energy relationships (PP-LFERs) are accurate, general, and mechanistically clear models for predicting partitioning-related physicochemical quantities. About a decade ago, PP-LFERs were calibrated for Kislip/w at the physiological temperature of 37 °C. However, to date, a comprehensive collection and sufficiently reliable PP-LFERs for Kislip/w and Kislip/a at the most common standard temperature of 25 °C are still lacking. In this study, experimentally based Kislip/w and/or Kislip/a values at 25 °C for 278 compounds were extensively collected or converted from the literature. Subsequently, PP-LFERs were calibrated for Kislip/w and Kislip/a at 25 °C, performing well over 10 orders of magnitude with root-mean-square errors of 0.17-0.21 log units for compounds with reliable descriptors. Furthermore, standard internal energy changes of transfer from water or air to storage lipids for 158 compounds were derived and used to calibrate PP-LFERs for estimating the temperature dependence of Kislip/w or Kislip/a. Additionally, using PP-LFERs, low-density polyethylene was confirmed to be a better storage lipid analogue than silicone and polyoxymethylene in the equilibrium passive sampling of nonpolar and H-bond acceptor polar compounds.

Hydrophobic Sorption Properties of an Extended Series of Anionic Per- and Polyfluoroalkyl Substances Characterized by C18 Chromatographic Retention Measurement

Partitioning from water to nonaqueous phases is an important process that controls the behavior of contaminants in the environment and biota. However, for ionic chemicals including many perfluoroalkyl and polyfluoroalkyl substances (PFAS), environmentally relevant partition coefficients cannot be predicted using the octanol/water partition coefficient, which is commonly used as a hydrophobicity indicator for neutral compounds. As an alternative, this study measured C18 liquid chromatography retention times of 39 anionic PFAS and 20 nonfluorinated surfactants using isocratic methanol/water eluent systems. By measuring a series of PFAS with different perfluoroalkyl chain lengths, retention factors at 100% water (k0) were successfully extrapolated even for long-chain PFAS. Molecular size was the most important factor determining the k0 of PFAS and non-PFAS, suggesting that the cavity formation process is the key driver for retention. Log k0 showed a high correlation with the log of partition coefficients from water to the phospholipid membrane, air/water interface, and soil organic carbon. The results indicate the potential of C18 retention factors as predictive descriptors for anionic PFAS partition coefficients and the possibility of developing a more comprehensive multiparameter model for the partitioning of anionic substances in general.