Simultaneous estimation of glass-water distribution and PDMS-water partition coefficients of hydrophobic organic compounds using simple batch method

Polyethylene-Water and Polydimethylsiloxane-Water Partition Coefficients for Polycyclic Aromatic Hydrocarbons and Polychlorinated Biphenyls: Influence of Polymer Source and Proposed Best Available Values

For most passive sampling applications, the availability of accurate passive sampler-water partition coefficients (K_p-w ) is of key importance. Unfortunately, a huge variability exists in literature K_p-w values, in particular for hydrophobic chemicals such as polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs). This variability is a major source of concern in the passive sampling community, which would benefit from high-quality K_p-w data. Hence, in the present study "best available" PAH and PCB K_p-w values are proposed for the two most often applied passive sampling materials, that is, low-density polyethylene and polydimethylsiloxane (PDMS), based on (1) a critical assessment of existing literature data, and (2) new K_p-w determinations for polyethylene and PDMS, with both polymers coming in six different versions (suppliers, thicknesses). The experimental results indicated that K_p-w values for PDMS are independent of the source, thus allowing straightforward standardization. In contrast, K_p-w values for polyethylene from different sources differed by up to 30%. Defining best available K_p-w values for this polymer therefore may require standardization of the polymer source. Application of the proposed best available K_p-w values will substantially improve the accuracy of freely dissolved concentration results by users and the potential for comparisons across laboratories. Environ Toxicol Chem 2022;41:1370-1380. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Kinetics of Equilibrium Passive Sampling of Organic Chemicals with Polymers in Diverse Mammalian Tissues

Equilibrium passive sampling employing polydimethylsiloxane (PDMS) as a sampling phase can be used for the extraction of complex mixtures of organic chemicals from lipid-rich biota. We extended the method to lean tissues and more hydrophilic chemicals by implementing a mass-balance model for partitioning between lipids, proteins, and water in tissues and by accelerating uptake kinetics with a custom-built stirrer that effectively decreased time to equilibrium to less than 8 days even for a homogenized liver tissue with an only 4% lipid content. The partition constants log K_lipid/PDMS between tissues and PDMS were derived from measured concentration in PDMS and the mass-balance model and were very similar for 40 neutral chemicals with octanol-water partition constants 1.4 < log K_ow < 8.7, that is, log K_lipid/PDMS of 1.26 (95% CI, 1.13-1.39) for the adipose tissue, 1.16 (1.00-1.33) for the liver, and 0.58 (0.42-0.73) for the brain. This conversion factor can be applied to interpret chemical analysis and in vitro bioassays after additionally accounting for a small fraction of coextracted lipids of <0.7% of the PDMS weight. PDMS is more widely applicable for passive sampling of mammalian tissues than previously thought, both, in terms of diversity of chemicals and the range of lipid contents of tissues and, therefore, an ideal method for human biomonitoring to be combined with in vitro bioassays.

Versatile in silico modeling of partition coefficients of organic compounds in polydimethylsiloxane using linear and nonlinear methods

Environmental fate, behavior and effects of hazardous organic compounds have recently received great attention in diverse environmental phases, including water, atmosphere, soil and sediment. Considering polydimethylsiloxane (PDMS) fibers were validated for the wide application in the determination of partition behavior in passive sampling, in this work, several in silico models were established to predict PDMS-water (K_PDMS-w), PDMS-air (K_PDMS-a) and PDMS-seawater partition coefficients (K_PDMS-sw) of diverse chemicals. This is an attempt to combine conventional linear method and popular nonlinear algorithm for the estimation of partition coefficients between PDMS and different environmental media. All of the developed models showed satisfactory goodness-of-fit with high adjusted correlation coefficient (R²_adj) and were validated to be robust, stable and predictable by various internal and external validation techniques, deriving a wide series of statistical checks. Moreover, it was found that hydrophobicity, polarizability, charge distribution and molecular size of compounds contributed significantly to the model development by interpreting the selected descriptors. Based on the broad applicability domains (ADs), the current study provides suitable tools to fill the experimental data gap for other compounds and to help researchers better understand the mechanistic basis of adsorption behavior of PDMS.

Simultaneous quantification of humic acid-water and silanized glass-water partition constants for PCBs, PCDDs and OCDF

Super-hydrophobic organic contaminants (SHOCs) such as polychlorinated biphenyls (PCBs), polychlorinated dibenzo-p-dioxins (PCDDs) and octachlorodibenzofuran (OCDF) can sorb to dissolved hydrophobic materials including humic acids (HAs), enhancing their apparent aqueous solubility and potentially resulting in increased groundwater contamination and offsite transport. To manage risks associated with transport of and contamination by SHOCs, modelling approaches incorporating partitioning data, i.e. dissolved organic carbon-water partition constants (K_DOC), are necessary. Measurement of K_DOC can however be compromised by SHOC sorption to glassware surfaces leading to an overestimation of experimental values resulting in larger K_DOC. A method for simultaneous derivation of K_DOC and glass-water partition constants (K_GW) is described. It involves a mass balance approach combined with HA as a co-solvent at various concentrations and accounts for SHOC losses to silanized glassware. Measured log K_DOC values ranged from 5.28 to 7.64 for tetra- to decachlorinated PCBs, 6.67 to 7.93 for tetra- to octachlorinated PCDDs and 8.20 for OCDF. These data were linear functions of log K_OW and consistent with relationships reported for more polar compounds. Log K_GW (mm³ mm^-2) values (1.62 to 4.06 for PCBs, 2.96 to 3.90 for PCDDs, 3.77 for OCDF) were one order of magnitude greater compared to literature PCB borosilicate glass-water partition constants. Techniques such as those presented in this work present simple, versatile means to provide prediction of the SHOC proportion remaining in aqueous solutions after loss to glassware that was inversely related to container surface area/volume ratio and log K_OW in our study.

Prediction of polydimethylsiloxane-water partition coefficients based on the pp-LFER and QSAR models

Obtaining accurate measurements of the partition coefficients between sorbent materials and water is of major importance for the analysis of the adsorption behavior and dissolved concentrations of organic compounds in the environment. In the passive-sampling approach, polydimethylsiloxane (PDMS) has a wide range of applications. Therefore, we established a poly-parameter linear-free energy relationship (pp-LFER) and a quantitative structure-activity relationship (QSAR) model to predict the log K_PDMS-w values for a large dataset of 290 organic chemicals from 11 diverse classes. For the pp-LFER model, E (excess molar refractivity), A (molecular H-bond donor ability), V (McGowan volume), and B (the H-bond acceptor properties) were introduced as the main correlated variables. However, the obtained model is much limited in terms of acquiring available descriptors. For this reason, we developed a QSAR model, and CrippenLogP (Crippen octanol-water partition coefficient), RNCG (Relative negative charge-most negative charge/total negative charge), ATSC4e (Centered Broto-Moreau autocorrelation-lag4/weighted by Sanderson electronegativities) and GATS6p (Geary autocorrelation-lag6/weighted by polarizabilities) were selected as the significant parameters. The predictive power and functional reliability of the presented models were confirmed with validation methods as described in previous studies. The adjusted determination coefficients (R²_adj) of 0.851 and 0.922 and leave-one-out cross-validated (Q²_LOO) of 0.841 and 0.907 revealed that the models have good predictive power and generalizability. Thus, the proposed models are simple yet accurate tools for predicting the log K_PDMS-w values and providing new insights to further understand the adsorption mechanism of organic compounds.

Application of Experimental Polystyrene Partition Constants and Diffusion Coefficients to Predict the Sorption of Neutral Organic Chemicals to Multiwell Plates in in Vivo and in Vitro Bioassays

Sorption to the polystyrene (PS) of multiwell plates can affect the exposure to organic chemicals over time in in vitro and in vivo bioassays. Experimentally determined diffusion coefficients in PS ( D_PS) were in a narrow range of 1.25 to 8.0 · 10^-16 m² s^-1 and PS-water partition constants ( K_PS/w) ranged from 0.04 to 5.10 log-units for 22 neutral organic chemicals. A kinetic model, which explicitly accounts for diffusion in the plastic, was applied to predict the depletion of neutral organic chemicals from different bioassay media by sorption to various multiwell plate formats. For chemicals with log K_ow > 3, the medium concentrations decreased rapidly and considerably in the fish embryo toxicity assay but medium concentrations remained relatively constant in the cell-based bioassays with medium containing 10% fetal bovine serum (FBS), emphasizing the ability of the protein- and lipid-rich medium to compensate for losses by multiwell plate sorption. The PS sorption data may serve not only for exposure assessment in bioassays but also to model the contaminant uptake by and release from plastic packaging material and the chemical transport by PS particles in the environment.

Applying no-depletion equilibrium sampling and full-depletion bioaccessibility extraction to 35 historically polycyclic aromatic hydrocarbon contaminated soils

Assessing the bioaccessibility of organic pollutants in contaminated soils is considered a complement to measurements of total concentrations in risk assessment and legislation. Consequently, methods for its quantification require validation with historically contaminated soils. In this study, 35 such soils were obtained from various locations in Switzerland and Cuba. They were exposed to different pollution sources (e.g., pyrogenic and petrogenic) at various distance (i.e., urban to rural) and were subject to different land use (e.g., urban gardening and forest). Passive equilibrium sampling with polyoxymethylene was used to determine freely dissolved concentrations (C_free) of polycyclic aromatic hydrocarbons (PAHs), while sorptive bioaccessibility extraction (SBE) with silicone rods was used to determine the bioaccessible PAH concentrations (C_bioacc) of these soils. The organic carbon partition coefficients of the soils were highest for skeet soils, followed by traffic, urban garden and rural soils. Lowest values were obtained from soil exposed to petrogenic sources. Applicability of SBE to quantify C_bioacc was restricted by silicone rod sorption capacity, as expressed quantitatively by the Sorption Capacity Ratio (SCR); particularly for soils with very high K_D. The source of contamination determined bioaccessible fractions (f_bioacc). The smallest f_bioacc were obtained with skeet soils (15%), followed by the pyrogenically influenced soils, rural soils, and finally, the petrogenically contaminated soil (71%). In conclusion, we present the potential and limitations of the SBE method to quantify bioaccessibility in real soils. These results can be used for additional development of this and similar bioaccessibility methods to guarantee sufficient sorption capacity to obtain reliable results.

Transferring mixtures of chemicals from sediment to a bioassay using silicone-based passive sampling and dosing

Environmental mixtures of chemicals consist of a countless number of compounds with unknown identity and quantity. Yet, chemical regulation is mainly built around the assessment of single chemicals. Existing frameworks for assessing the toxicity of mixtures require that both the chemical composition and quantity are known. Quantitative analyses of the chemical composition of environmental mixtures are however extremely challenging and resource-demanding. Bioassays may therefore serve as a useful approach for investigating the combined toxicity of environmental mixtures of chemicals in a cost-efficient and holistic manner. In this study, an unknown environmental mixture of bioavailable semi-hydrophobic to hydrophobic chemicals was sampled from a contaminated sediment in a coastal Baltic Sea area using silicone polydimethylsiloxane (PDMS) as an equilibrium passive sampler. The chemical mixture was transferred to a PDMS-based passive dosing system, and its applicability was demonstrated using green algae Tetraselmis suecica in a cell viability assay. The proportion of dead cells increased significantly with increasing exposure level and in a dose-response manner. At an ambient concentration, the proportion of dead cells in the population was nearly doubled compared to the control; however, the difference was non-significant due to high inter-replicate variability and a low number of replicates. The validation of the test system regarding equilibrium sampling, loading efficiency into the passive dosing polymer, stability of the mixture composition, and low algal mortality in control treatments demonstrates that combining equilibrium passive sampling and passive dosing is a promising tool for investigating the toxicity of bioavailable semi-hydrophobic and hydrophobic chemicals in complex environmental mixtures.

Oligomeric models for estimation of polydimethylsiloxane-water partition ratios with COSMO-RS theory: impact of the combinatorial term on absolute error

A series of 12 oligomeric models for polydimethylsiloxane (PDMS) were evaluated for their effectiveness in estimating the PDMS-water partition ratio, K_PDMS-w. Models ranging in size and complexity from the -Si(CH₃)₂-O- model previously published by Goss in 2011 to octadeca-methyloctasiloxane (CH₃-(Si(CH₃)₂-O-)₈CH₃) were assessed based on their RMS error with 253 experimental measurements of log K_PDMS-w from six published works. The lowest RMS error for log K_PDMS-w (0.40 in log K) was obtained with the cyclic oligomer, decamethyl-cyclo-penta-siloxane (D5), (-Si(CH₃)₂-O-)₅, with the mixing-entropy associated combinatorial term included in the chemical potential calculation. The presence or absence of terminal methyl groups on linear oligomer models is shown to have significant impact only for oligomers containing 1 or 2 -Si(CH₃)₂-O- units. Removal of the combinatorial term resulted in a significant increase in the RMS error for most models, with the smallest increase associated with the largest oligomer studied. The importance of inclusion of the combinatorial term in the chemical potential for liquid oligomer models is discussed.

Review of the partitioning of chemicals into different plastics: Consequences for the risk assessment of marine plastic debris

Marine plastic debris are found worldwide in oceans and coastal areas. They degrade only slowly and contain chemicals added during manufacture or absorbed from the seawater. Therefore, they can pose a long-lasting contaminant source and potentially transfer chemicals to marine organisms when ingested. In order to assess their risk, the contaminant concentration in the plastics needs to be estimated and differences understood. We collected from literature plastic water partition coefficients of various organic chemicals for seven plastic types: polydimethylsiloxane (PDMS), high-density, low-density and ultra-high molecular weight polyethylene (LDPE, HDPE, UHMWPE), polystyrene (PS), polypropylene (PP), and polyvinyl chloride (PVC). Most data was available for PDMS (1060) and LDPE (220), but much less for the remaining plastics (73). Where possible, regression models were developed and the partitioning was compared between the different plastic types. The partitioning of chemicals follows the order of LDPE≈HDPE≥PP>PVC≈PS. Data describing the impact of weathering are urgently needed.

Solubility enhancement of dioxins and PCBs by surfactant monomers and micelles quantified with polymer depletion techniques

Partitioning of super-hydrophobic organic contaminants (SHOCs) to dissolved or colloidal materials such as surfactants can alter their behaviour by enhancing apparent aqueous solubility. Relevant partition constants are, however, challenging to quantify with reasonable accuracy. Partition constants to colloidal surfactants can be measured by introducing a polymer (PDMS) as third phase with known PDMS-water partition constant in combination with the mass balance approach. We quantified partition constants of PCBs and PCDDs (log KOW 5.8-8.3) between water and sodium dodecyl sulphate monomers (KMO) and micelles (KMI). A refined, recently introduced swelling-based polymer loading technique allowed highly precise (4.5-10% RSD) and fast (<24 h) loading of SHOCs into PDMS, and due to the miniaturisation of batch systems equilibrium was reached in <5 days for KMI and <3 weeks for KMO. SHOC losses to experimental surfaces were substantial (8-26%) in monomer solutions, but had a low impact on KMO (0.10-0.16 log units). Log KMO for PCDDs (4.0-5.2) were approximately 2.6 log units lower than respective log KMI, which ranged from 5.2 to 7.0 for PCDDs and 6.6-7.5 for PCBs. The linear relationship between log KMI and log KOW was consistent with more polar and moderately hydrophobic compounds. Apparent solubility increased with increasing hydrophobicity and was highest in micelle solutions. However, this solubility enhancement was also considerable in monomer solutions, up to 200 times for OCDD. Given the pervasive presence of surfactant monomers in typical field scenarios, these data suggest that low surfactant concentrations may be effective long-term facilitators for subsurface transport of SHOCs.

Experimental Solubility Approach to Determine PDMS-Water Partition Constants and PDMS Activity Coefficients

Freely dissolved aqueous concentration and chemical activity are important determinants of contaminant transport, fate, and toxic potential. Both parameters are commonly quantified using Solid Phase Micro-Extraction (SPME) based on a sorptive polymer such as polydimethylsiloxane (PDMS). This method requires the PDMS-water partition constants, KPDMSw, or activity coefficient to be known. For superhydrophobic contaminants (log KOW >6), application of existing methods to measure these parameters is challenging, and independent measures to validate KPDMSw values would be beneficial. We developed a simple, rapid method to directly measure PDMS solubilities of solid contaminants, SPDMS(S), which together with literature thermodynamic properties was then used to estimate KPDMSw and activity coefficients in PDMS. PDMS solubility for the test compounds (log KOW 7.2-8.3) ranged over 3 orders of magnitude (4.1-5700 μM), and was dependent on compound class. For polychlorinated biphenyls (PCBs) and polychlorinated dibenzo-p-dioxins (PCDDs), solubility-derived KPDMSw increased linearly with hydrophobicity, consistent with trends previously reported for less chlorinated congeners. In contrast, subcooled liquid PDMS solubilities, SPDMS(L), were approximately constant within a compound class. SPDMS(S) and KPDMSw can therefore be predicted for a compound class with reasonable robustness based solely on the class-specific SPDMS(L) and a particular congener's entropy of fusion, melting point, and aqueous solubility.

Trace analysis of hydrophobic micropollutants in aqueous samples using capillary traps

Studying the fate of persistent organic pollutants (POPs) in glacier environments scientist face the challenge of snow and ice samples, in which concentrations of these pollutants are at the ultra-trace level and the amount of sample available is often very limited. We have improved an extraction method for hydrophobic organic pollutants such as polychlorinated biphenyls (PCBs) in aqueous media to meet the requirements of these challenging samples. It is based on partitioning of the analytes from the water into the polydimethylsiloxane (PDMS) coating of an open tubular-fused-silica capillary. By comparison with conventional liquid-liquid extraction, we validated the method for six indicator PCBs, covering a wide range of polarity. The new method has very low detection limits of 10-20pg/L for the investigated PCBs, a small uncertainty between 9% and 37%, depending on concentration, and requires a small sample volume of less than one liter. Further, it is characterized by easy handling and reduced organic solvents consumption. The method is comparatively insensitive to contamination, reproducible, and suitable for a wide range of applications.

Passive sampling methods for contaminated sediments: practical guidance for selection, calibration, and implementation

This article provides practical guidance on the use of passive sampling methods (PSMs) that target the freely dissolved concentration (Cfree ) for improved exposure assessment of hydrophobic organic chemicals in sediments. Primary considerations for selecting a PSM for a specific application include clear delineation of measurement goals for Cfree , whether laboratory-based "ex situ" and/or field-based "in situ" application is desired, and ultimately which PSM is best-suited to fulfill the measurement objectives. Guidelines for proper calibration and validation of PSMs, including use of provisional values for polymer-water partition coefficients, determination of equilibrium status, and confirmation of nondepletive measurement conditions are defined. A hypothetical example is described to illustrate how the measurement of Cfree afforded by PSMs reduces uncertainty in assessing narcotic toxicity for sediments contaminated with polycyclic aromatic hydrocarbons. The article concludes with a discussion of future research that will improve the quality and robustness of Cfree measurements using PSMs, providing a sound scientific basis to support risk assessment and contaminated sediment management decisions.