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

Characterizing Sorption and Permeation Properties of Membrane Filters Used for Aquatic Integrative Passive Samplers

Aquatic integrative passive sampling is a promising approach to measure the time-weighted average concentration, yet our understanding for the sampling mechanisms of polar organic contaminants should be further advanced to fully exploit the potential of the method for real-world applications. This study aimed to characterize the sorption and permeation properties of poly­(ether sulfone) (PES) and poly­(tetrafluoroethylene) (PTFE) membrane filters (MFs) used for passive samplers. Batch sorption experiments with 14 probe chemicals showed that the sorption by PES was generally strong, with the respective sorption coefficients greater than the octanol–water partition coefficients by 2–3 log units. In contrast, the PTFE filter exhibited no significant sorption for all tested chemicals, representing a promising candidate MF that avoids lag-times and slow responses to fluctuating concentrations. Permeation experiments in a glass cell system and successive modeling demonstrated that, if no sorption to the MF occurs, the MF permeation of a chemical can be fully described with a first-order model that considers the transfer through the aqueous boundary layers and the diffusion in water-filled MF pores. Significant sorption to the MF coincided with substantial delay of permeation, which was successfully modeled with the local sorption equilibrium assumption. These findings have implications for improved sampler configurations and successful models for the chemical uptake

Applications of Polyparameter Linear Free Energy Relationships in Environmental Chemistry

Partitioning behavior of organic chemicals has tremendous influences on their environmental distribution, reaction rates, bioaccumulation, and toxic effects. Polyparameter linear free energy relationships (PP-LFERs) have been proven to be useful to characterize the equilibrium partitioning of organic chemicals in various environmental and technical partitioning systems and predict the respective partition coefficients. Over the past decade, PP-LFER solute descriptors for numerous environmentally relevant organic chemicals and system parameters for environmentally important partitioning systems have been determined, extending substantially the applicability of the PP-LFER approaches. However, the information needed for the use of PP-LFERs including descriptors and parameters is scattered over a large number of publications. In this work, we review the state of the art of the PP-LFER approaches in environmental chemical applications. The solute descriptors and system parameters reported in the literature and the availability of their database are summarized, and their calibration and prediction methods are overviewed. We also describe tips and pitfalls associated with the use of the PP-LFER approaches and identify research needs to improve further the usefulness of PP-LFERs for environmental chemistry

Applications of Polyparameter Linear Free Energy Relationships in Environmental Chemistry

Partitioning behavior of organic chemicals has tremendous influences on their environmental distribution, reaction rates, bioaccumulation, and toxic effects. Polyparameter linear free energy relationships (PP-LFERs) have been proven to be useful to characterize the equilibrium partitioning of organic chemicals in various environmental and technical partitioning systems and predict the respective partition coefficients. Over the past decade, PP-LFER solute descriptors for numerous environmentally relevant organic chemicals and system parameters for environmentally important partitioning systems have been determined, extending substantially the applicability of the PP-LFER approaches. However, the information needed for the use of PP-LFERs including descriptors and parameters is scattered over a large number of publications. In this work, we review the state of the art of the PP-LFER approaches in environmental chemical applications. The solute descriptors and system parameters reported in the literature and the availability of their database are summarized, and their calibration and prediction methods are overviewed. We also describe tips and pitfalls associated with the use of the PP-LFER approaches and identify research needs to improve further the usefulness of PP-LFERs for environmental chemistry

Predicting Partition Coefficients of Polyfluorinated and Organosilicon Compounds using Polyparameter Linear Free Energy Relationships (PP-LFERs)

The environmental behavior, fate, and effects of polyfluorinated compounds (PFCs) and organosilicon compounds (OSCs) have received increasing attention in recent years. In this study, polyparameter linear free energy relationships (PP-LFERs) were evaluated for predicting partition coefficients of neutral PFCs and OSCs, using experimental data for fluorotelomer alcohols (FTOHs) and cyclic volatile methylsiloxanes (cVMS) reported in the literature and measured newly for this work. It was found that the recently proposed PP-LFER model that uses the McGowan characteristic volume (<i>V</i>), the logarithmic hexadecane–air partition coefficient (<i>L</i>), and three polar interaction descriptors can accurately describe partition coefficients of PFCs and OSCs. The prediction errors were <1 log unit when literature descriptors were used, and the errors were reduced to <0.2 log units on average by further optimization of the descriptors. Surprisingly, the conventional forms of PP-LFERs that include the excess molar refraction (<i>E</i>) sometimes led to substantial errors (>1 log unit) even with optimized parameters. The system parameters for octanol–water, air–water, octanol–air, oil–water, liposome–water, and organic carbon–water partition coefficients as well as the solute descriptors for FTOHs and cVMS were recalibrated in this work, which should provide even more reliable predictions of partition coefficients. The results also confirm the consistency of the published experimental partition coefficients for FTOHs and cVMS

Salting-Out Effect in Aqueous NaCl Solutions: Trends with Size and Polarity of Solute Molecules

Salting-out in aqueous NaCl solutions is relevant for the environmental behavior of organic contaminants. In this study, Setschenow (or salting-out) coefficients (<i>K</i>^s [M^–1]) for 43 diverse neutral compounds in NaCl solutions were measured using a shared headspace passive dosing method and a negligible depletion solid phase microextraction technique. The results were used to calibrate and evaluate estimation models for <i>K</i>^s. The molar volume of the solute correlated only moderately with <i>K</i>^s (<i>R</i>² = 0.49, SD = 0.052). The polyparameter linear free energy relationship (pp-LFER) model that uses five compound descriptors resulted in a more accurate fit to our data (<i>R</i>² = 0.83, SD = 0.031). The pp-LFER analysis revealed that Na⁺ and Cl^– in aqueous solutions increase the cavity formation energy cost and the polar interaction energies toward neutral organic solutes. Accordingly, the salting-out effect increases with the size and decreases with the polarity of the solute molecule. COSMO-RS, a quantum mechanics-based fully predictive model, generally overpredicted the experimental <i>K</i>^s, but the predicted values were moderately correlated with the experimental values (<i>R</i>² = 0.66, SD = 0.042). Literature data (<i>n</i> = 93) were predicted by the calibrated pp-LFER and COSMO-RS models with root mean squared errors of 0.047 and 0.050, respectively. This study offers prediction models to estimate <i>K</i>^s, allowing implementation of the salting-out effect in contaminant fate models, linkage of various partition coefficients (such as air–water, sediment–water, and extraction phase–water partition coefficients) measured for fresh water and seawater, and estimation of enhancement of extraction efficiency in analytical procedures

Experimental Determination of Polyparameter Linear Free Energy Relationship (pp-LFER) Substance Descriptors for Pesticides and Other Contaminants: New Measurements and Recommendations

Well-calibrated polyparameter linear free energy relationships (pp-LFERs) are an accurate way to predict partition coefficients (<i>K</i>) for neutral organic chemicals. In this work, pp-LFER substance descriptors of 111 environmentally relevant substances, mainly pesticides, were determined experimentally using gas chromatographic (GC) retention times and liquid/liquid partition coefficients. The complete set of descriptors for 50 compounds are being reported here for the first time. Validation of the measured substance descriptors was done by comparing predicted and experimental log <i>K</i> for the systems octanol/water (<i>K</i>_ow), water/air (<i>K</i>_wa), and organic carbon/water (<i>K</i>_oc), all of which indicated a high reliability of pp-LFER predictions based on the determined descriptors (e.g., a root mean squared error of 0.39 for log <i>K</i>_ow). The descriptors presented in this work in combination with existing pp-LFER system equations substantially extend (and in some cases correct) our knowledge on partition properties of these 111 chemicals. In addition, the results of this work provide insight on some general guidelines with respect to the method combination best suited for deriving descriptors for environmentally relevant compounds

Partitioning of Neutral Organic Compounds to Structural Proteins

Protein–water partition coefficients (<i>K</i>_pw) of neutral organic chemicals were measured using muscle proteins (from chicken, fish, and pig), collagen and gelatin. <i>K</i>_pw values for these structural proteins were consistently lower than those of bovine serum albumin (BSA), indicating that the use of BSA as a model protein leads to an overestimation of <i>K</i>_pw for structural proteins. Differences in <i>K</i>_pw between chicken, fish, and pig muscle proteins were small. Across the structural proteins, <i>K</i>_pw values were often in the order: muscle proteins > collagen ≥ gelatin. Differences in <i>K</i>_pw between the structural proteins were relatively large (<2 log units) for nonpolar compounds, and much smaller or insignificant for polar compounds. There were correlations between log <i>K</i>_pw of muscle proteins and log <i>K</i>_ow (<i>R</i>₂ = 0.83–0.86, SD: 0.35–0.40, <i>n</i> = 45–46). The polyparameter linear free energy relationship (PP-LFER) models fit even better to the data (<i>R</i>² = 0.95, SD: 0.22). The good model fitting suggests that the reversible binding to muscle proteins can be considered to be nonspecific binding. There was an indication that some chemicals may sorb irreversibly to muscle proteins, which needs further research. We found that the partitioning to muscle protein is typically weaker than that to lipids, but that the protein partitioning of an H-bond donor compound can be as strong as the storage lipid partitioning

Determination of Polyparameter Linear Free Energy Relationship (pp-LFER) Substance Descriptors for Established and Alternative Flame Retardants

Polyparameter linear free energy relationships (pp-LFERs) can predict partition coefficients for a multitude of environmental and biological phases with high accuracy. In this work, the pp-LFER substance descriptors of 40 established and alternative flame retardants (e.g., polybrominated diphenyl ethers, hexabromocyclododecane, bromobenzenes, trialkyl phosphates) were determined experimentally. In total, 251 data for gas-chromatographic (GC) retention times and liquid/liquid partition coefficients (<i>K</i>) were measured and used to calibrate the pp-LFER substance descriptors. Substance descriptors were validated through a comparison between predicted and experimental log <i>K</i> for the systems octanol/water (<i>K</i>_ow), water/air (<i>K</i>_wa), organic carbon/water (<i>K</i>_oc) and liposome/water (<i>K</i>_lipw), revealing a high reliability of pp-LFER predictions based on our descriptors. For instance, the difference between predicted and experimental log <i>K</i>_ow was <0.3 log units for 17 out of 21 compounds for which experimental values were available. Moreover, we found an indication that the H-bond acceptor value (<i>B</i>) depends on the solvent for some compounds. Thus, for predicting environmentally relevant partition coefficients it is important to determine <i>B</i> values using measurements in aqueous systems. The pp-LFER descriptors calibrated in this study can be used to predict partition coefficients for which experimental data are unavailable, and the predicted values can serve as references for further experimental measurements

Equilibrium Sorption of Structurally Diverse Organic Ions to Bovine Serum Albumin

Reliable partitioning data are essential for assessing the bioaccumulation potential and the toxicity of chemicals. In contrast to neutral organic chemicals, the partitioning behavior of ionogenic organic chemicals (IOCs) is still a black box for environmental scientists. Partitioning to serum albumin, the major protein in blood plasma, strongly influences the freely dissolved concentration of many chemicals (including IOCs), which affects their transport and distribution in the body. Because consistent data sets for partitioning of IOCs are rarely available, bovine serum albumin-water partition coefficients (<i>K</i>_BSA/w) were measured in this study for 45 anionic and 4 cationic organic chemicals, including various substituted benzoic and naphthoic acids, sulfonates and several pesticides and pharmaceuticals. The results of this study suggest that binding to BSA is substantially influenced by the three-dimensional structure of the chemicals and the position of substitutions on the sorbing molecules. For example, we found a difference of >1.5 log units between isomeric chemicals such as 3,4-dichlorobenzoic acid and 2,6-dichlorobenzoic acid, and 1-naphthoic acid and 2-naphthoic acid. Conventional modeling approaches (e.g., based on octanol–water partition coefficients) poorly predict log <i>K</i>_BSA/w of organic ions (<i>R</i>² ≤ 0.5), partially because they do not capture the observed steric effects. Hence, alternative modeling strategies will be required for accurate prediction of serum albumin-water partition coefficients of organic ions