Polyparameter Linear Free Energy Research Articles

Chlorpyrifos fate in the Arctic: Importance of analyte structure in interactions with Arctic dissolved organic matter

The insecticide and current use pesticide chlorpyrifos (CLP) is transported via global distillation to the Arctic where it may pose a threat to this ecosystem. CLP is readily detected in Arctic environmental compartments, but current research has not studied its partitioning between water and dissolved organic matter (DOM) nor the role of photochemistry in CLP's fate in aquatic systems. Here, the partition coefficients of CLP were quantified with various types of DOM isolated from the Arctic and an International Humic Substances Society (IHSS) reference material Suwannee River natural organic matter (SRNOM). While CLP readily partitions to DOM, CLP exhibits a significantly higher binding constant with Arctic lacustrine DOM relative to fluvial DOM or SRNOM. The experimental partitioning coefficients (KDOC) were compared to a calculated value estimated using poly parameter linear free energy relationship (pp-LFER) and was found to be in good agreement with SRNOM, but none of the Arctic DOMs. We found that Arctic KDOC values decrease with increasing SUVA254, but no correlations were observed for the other DOM compositional parameters. DOM also mediates the photodegradation of CLP, with stark differences in photo-kinetics using Arctic DOM isolated over time and space. This work highlights the chemo-diversity of Arctic DOM relative to IHSS reference materials and highlights the need for in-depth characterization of DOM that transcends the current paradigm based upon terrestrial and microbial precursors.

Performance evaluation and prediction of activated carbon for VOCs via experiments and LFER methods

Due to the diversity and fluidity of volatile organic compounds (VOCs), it is difficult to conduct experimental studies on activated carbon (AC) used to capture VOCs in industry. Therefore, predicting the adsorption capacity of AC for VOCs is of great significance for evaluating the adsorption performance of AC and developing its promising applications. Herein, based on the experimental data of dynamic adsorption, the poly parameter linear free energy relationship (pp-LFER) model was developed to quantify the interactions between VOCs and AC. Through the dynamic adsorption curves of 25 VOCs on a fixed bed packed with the AC, the partition coefficient (PC) and adsorption capacity (q) of AC for VOCs were calculated, and the pp-LFER equations used to predict them were established. For the PC values, the pp-LFER model consists of the excess molar refractive index (E), molar polarizability (S), hydrogen-bond acidity (A), and logarithmic hexadecane-air partition coefficient (L), and the R2 of it was 0.86. For the ln q values, the developed model can predict it in R2 of 0.83, and the increased adsorption capacity was predominantly attributed to the dispersive interaction (lL). Finally, the internal and external validation results confirmed that the developed models have reliability, robustness, and predictability.

Versatile in silico modeling of XAD-air partition coefficients for POPs based on abraham descriptor and temperature

The concentration of persistent organic pollutants (POPs) makes remarkable difference to environmental fate. In the field of passive sampling, the partition coefficients between polystyrene-divinylbenzene resin (XAD) and air (i.e., KXAD-A) are indispensable to obtain POPs concentration, and the KXAD-A is generally thought to be governed by temperature and molecular structure of POPs. However, experimental determination of KXAD-A is unrealistic for countless and novel chemicals. Herein, the Abraham solute descriptors of poly parameter linear free energy relationship (pp-LFER) and temperature were utilized to develop models, namely pp-LFER-T, for predicting KXAD-A values. Two linear (MLR and LASSO) and four nonlinear (ANN, SVM, kNN and RF) machine learning algorithms were employed to develop models based on a data set of 307 sample points. For the aforementioned six models, R2adj and Q2ext were both beyond 0.90, indicating distinguished goodness-of-fit and robust generalization ability. By comparing the established models, the best model was observed as the RF model with R2adj = 0.991, Q2ext = 0.935, RMSEtra = 0.271 and RMSEext = 0.868. The mechanism interpretation revealed that the temperature, size of molecules and dipole-type interactions were the predominant factors affecting KXAD-A values. Concurrently, the developed models with the broad applicability domain provide available tools to fill the experimental data gap for untested chemicals. In addition, the developed models were helpful to preliminarily evaluate the environmental ecological risk and understand the adsorption behavior of POPs between XAD membrane and air.

Predicting the Gas/Particle Distribution of SVOCs in the Indoor Environment Using Poly Parameter Linear Free Energy Relationships.

Understanding the partitioning of semi volatile organic compounds (SVOCs) between gas phase and particle phase is essential for exposure analysis and risk assessment in the indoor environment. Numerous attempts have been made to calculate gas/particle partitioning coefficients Kip. Single-parameter adsorption and absorption models, which relate Kip to the vapor pressure Ps or the octanol/air distribution coefficient KOA are usually applied. In this work we use poly parameter Linear Free Energy Relationships (pp-LFER) to describe the partitioning behavior of 14 SVOCs with high relevance for the indoor environment. The pp-LFER concept is based on Abraham descriptors and considers interactions between molecule and particle by separate parameters. van der Waals interactions can be approximated by the logarithm of the hexadecane/air partitioning coefficient (log KHdA = L), which is a key parameter for the 14 polar but nonionizable organic esters being studied here. For many of the examined compounds experimentally determined L-values were not available and had to be measured using gas chromatography. It is shown that the pp-LFER method is a strong alternative to single-parameter approaches and gives reliable coefficients for gas/particle distribution in the indoor environment.

Organophosphate Ester Transport, Fate, and Emissions in Toronto, Canada, Estimated Using an Updated Multimedia Urban Model.

Organophosphate esters (OPEs), used as flame retardants and plasticizers, occur at relatively high concentrations in urban air and surface waters. We tested the hypothesis that some OPEs could be considered persistent and mobile organic compounds (PMOCs), using the poly parameter linear free energy relationship-modified Multimedia Urban Model (ppLFER-MUM) in Toronto, Canada, as a case study. Modeled air emissions of ∑6OPEs of 3300 (190-190 000) kg yr-1 were 10-100 times higher than emissions of polychlorinated biphenyls (∑5PCBs) and polybrominated diphenyl ethers (∑5PBDEs). Model results suggested that measured ∑6OPE stream concentrations of ∼2000 ng L-1 originate from emissions to urban air transferred to water mostly via precipitation. Water transport removed 7-28% of total air inputs compared to 0.1-10% for PCBs and 2-10% for PBDEs. Chlorinated OPEs were efficiently transported via surface water due to their persistence and high solubility. Loadings of ∑6OPEs to Lake Ontario from wastewater treatment plants, streams, and atmospheric deposition were 70%, 18%, and 13%, respectively, of ∑6OPE loadings of 3100 (1200-45 000) kg yr-1. Our results support the hypothesis that three chlorinated OPEs, tris(2-chloroethyl)phosphate phosphate (TCEP), tris(chloroisopropyl)phosphate (TCiPP), and tris(1,3-dichloroisopropyl)phosphate (TDCiPP), fit the profile of PMOCs due to their mobility and persistence in surface waters.

Approaches for estimating PUF-air partitions coefficient for semi-volatile organic compounds: A critical comparison

Partition coefficients between polyurethane foam (PUF) and air (KPUF-Air) are important when using PUF as a passive air sampler for semi-volatile organic compounds (SVOCs) and when considering the fate of SVOCs indoors where PUF is a common material. Here, KPUF-Air for selected SVOCs was estimated using published methods, since measured data are unavailable for most of these compounds. Estimates of KPUF-Air were within one order of magnitude for SVOCs having values of log octanol-air partition coefficient (KOA) of 5, but differed by nearly three orders of magnitude for SVOCs with log KOA of 12. Of all the methods, the correlation developed using experimental measurements gave the lowest estimates for the high KOA compounds, likely because the compounds did not reach equilibrium throughout the PUF sample. The surface area/volume ratio of the PUF sample was shown to influence the observed correlation, a reflection of the equilibration status of the PUF. For quantitative comparison, the poly parameter linear free energy relationship (pp-LFER) model of Kamprad and Goss (2007) was used here as a “surrogate” standard. The correlations developed with vapor pressure and KOA produced estimates that were closest to those obtained using the pp-LFER model. COSMO-RS theory, in which intimate and unimpeded contact is assumed between the compound in air and PUF molecules, gave lower estimates for low KOA compounds, but good average agreement for high KOA compounds. When used in modeling applications, the selection of the method for estimating KPUF-Air should reflect the configuration of the products containing PUF and the model assumptions regarding compound homogeneity within the PUF.

Modeling Nonlinear Adsorption with a Single Chemical Parameter: Predicting Chemical Median Langmuir Binding Constants.

Procedures for accurately predicting linear partition coefficients onto various sorbents (e.g., organic carbon, soils, clay) are reliable and well established. However, similar procedures for the prediction of sorption parameters of nonlinear isotherm models are not. The purpose of this paper is to present a procedure for predicting nonlinear isotherm parameters, specifically the median Langmuir binding constants, K̃L, obtained utilizing the single-chemical parameter log-normal Langmuir isotherm developed in the accompanying work. A reduced poly parameter linear free energy relationship (pp-LFER) is able to predict median Langmuir binding constants for graphite, charcoal, and Darco granular activated carbon (GAC) adsorption data. For the larger F400 GAC data set, a single pp-LFER model was insufficient, as a plateau is observed for the median Langmuir binding constants of larger molecular volume sorbates. This volumetric cutoff occurs in proximity to the median pore diameter for F400 GAC. A log-linear relationship exists between the aqueous solubility of these large compounds and their median Langmuir binding constants. Using this relationship for the chemicals above the volumetric cutoff and the pp-LFER below the cutoff, the median Langmuir binding constants can be predicted with a root-mean square error for graphite (n = 13), charcoal (n = 11), Darco GAC (n = 14), and F400 GAC (n = 44) of 0.129, 0.307, 0.407, and 0.424, respectively.

Understanding and Modeling Removal of Anionic Organic Contaminants (AOCs) by Anion Exchange Resins

Ionic organic contaminants (OCs) are a growing concern for water treatment and the environment and are removed inefficiently by many existing technologies. This study examined removal of anionic OCs by anion exchange resins (AXRs) as a promising alternative. Results indicate that two polystyrene AXRs (IRA910 and IRA96) have higher sorption capacities and selectivity than a polyacrylate resin (A860). For the polystyrene resins, selectivity follows: phenolates ≥ aromatic dicarboxylates > aromatic monocarboxylates > benzenesulfonate > aliphatic carboxylates. This trend can be explained based on hydration energy, the number of exchange groups, and aromaticity and hydrophobicity of the nonpolar moiety (NPM) of the anions. For A860, selectivity only varies within a narrow range (0.13-1.64). Despite the importance of the NPM of the anions, neutral solutes were sorbed much less, indicating synergistic combinations of electrostatic and nonelectrostatic interactions in the overall sorption. By conducting multiple linear regression between Abraham's descriptors and nature log of selectivity, induced dipole-related interactions and electrostatic interactions were found to be the most important interaction forces for sorption of the anions, while solute H-bond basicity has a negative effect. A predictive model was then developed for carboxylates and phenolates based on the poly parameter linear free energy relationships established for a diverse range of 16 anions and 5 neutral solutes, and was validated by accurate prediction of sorption of five test solutes within a wide range of equilibrium concentrations and that of benzoate at different pH.

Interaction Mechanisms and Predictive Model for the Sorption of Aromatic Compounds onto Nonionic Resins

Understanding interaction mechanisms between porous sorbents and organic compounds is important in selecting or custom-synthesizing an appropriate sorbent. In this study, sorption isotherms of a set of 14 (XAD-4&7) or 11 (MN200) aromatic compounds were measured for three nonionic resins, and a phase conversion approach (from aqueous phase to n-hexadecane or gas phase) was applied to separate sorbate-sorbent interactions from the overall involved interactions. Subsequently, contributions of individual interactions to the overall ΔG were quantified by poly parameter linear free energy relationships (pp-LFERs). Cavity energy (V), energy costs for creating cavities in bulk water, is the dominant driving force for the sorption from aqueous phase. Meanwhile, sorption was substantially abated by H-bonding accepting capacities of the solutes (B) due to the high electron accepting capacity of water molecules. Solute’s H-bonding donating capacity (A) and polarity/polarizability (S) are predominantly responsible for the n-hexadecane or gas-phase converted sorptions; V is also important in the gas-phase converted sorption. XAD-7 has larger A and S coefficients than XAD-4 and MN200 for both the original and converted analyses, while the opposite is true for V coefficients. More promisingly, a predictive model, developed based on the sorption of 7 simple aromatic compounds by the resins, can accurately estimate the sorption behaviors of 7 other relatively complex aromatic compounds within a wide range of concentrations.

Experimentally Determined Soil Organic Matter–Water Sorption Coefficients for Different Classes of Natural Toxins and Comparison with Estimated Numbers

Although natural toxins, such as mycotoxins or phytoestrogens are widely studied and were recently identified as micropollutants in the environment, many of their environmentally relevant physicochemical properties have not yet been determined. Here, the sorption affinity to Pahokee peat, a model sorbent for soil organic matter, was investigated for 29 mycotoxins and two phytoestrogens. Sorption coefficients (K(oc)) were determined with a dynamic HPLC-based column method using a fully aqueous mobile phase with 5 mM CaCl(2) at pH 4.5. Sorption coefficients varied from less than 10(0.7) L/kg(oc) (e.g., all type B trichothecenes) to 10(4.0) L/kg(oc) (positively charged ergot alkaloids). For the neutral compounds the experimental sorption data set was compared with predicted sorption coefficients using various models, based on molecular fragment approaches (EPISuite's KOCWIN or SPARC), poly parameter linear free energy relationship (pp-LFER) in combination with predicted descriptors, and quantum-chemical based software (COSMOtherm)). None of the available models was able to adequately predict absolute K(oc) numbers and relative differences in sorption affinity for the whole set of neutral toxins, largely because mycotoxins exhibit highly complex structures. Hence, at present, for such compounds fast and consistent experimental techniques for determining sorption coefficients, as the one used in this study, are required.

Predicting Sorption of Pesticides and Other Multifunctional Organic Chemicals to Soil Organic Carbon

Chemicals of current environmental concern are often multifunctional and more polar and more complex than classical pollutants such as polychlorinated biphenyls (PCB) or polycyclic aromatic hydrocarbons (PAH). Traditional models for predicting the partitioning in the environment such as group contribution methods or correlations with octanol-water partitioning cannot be expected to work well for such complex chemicals. In contrast, poly parameter Linear Free Energy Relationships (pp-LFERs) have been proven to describe partitioning of polar and nonpolar chemicals in all kinds of sorbing systems. Here, a pp-LFER model for soil-water partitioning was calibrated with data for 79 polar and nonpolar compounds that cover a very wide range of the relevant intermolecular interactions. The data set used for the model calibration in this work is more diverse and covers a wider range of the chemical space than other pp-LFERs published so far. Subsequently, the experimental data for about 50 pesticides and pharmaceuticals -not involved in the model calibration- were used as independent validation of this new calibrated model. The model performs well with a standard error of 0.25 log units for fitting the calibration data and with a root-mean-square error of 0.4 log units for the pesticides and pharmaceuticals. The validation with the independent data set for pesticides and pharmaceuticals also shows that the pp-LFER model reported here performs better compared to earlier published pp-LFER models and to the traditional log Kow correlation.

Theoretical and Experimental Simulation of the Fate of Semifluorinated n-Alkanes during Snowmelt

Semifluorinated n-alkanes (SFAs) are highly fluorinated anthropogenic chemicals that are released into the environment through their use in ski waxes. Nothing is known about their environmental partitioning in general and their fate during snowmelt in particular. Properties were estimated for a range of SFAs with different chain lengths and degrees of fluorination using the SPARC calculator and poly parameter linear free energy relationships (ppLFERs). The calculations resulted in very low water solubility and vapor pressures and, consequently, high log KOW and log KOA values. Artificially produced snow in a cold room was spiked with a range of SFAs and subsequently melted with infrared lamps. Melt water, particles, and air samples taken during melting were analyzed. Both calculations and experiments showed that SFAs used in ski waxes will bind to particles or snow grain surfaces during snowmelt and thus are predicted to end up on the soil surface in skiing areas.

Ambient Gas/Particle Partitioning. 2: The Influence of Particle Source and Temperature on Sorption to Dry Terrestrial Aerosols

In a companion paper we reported that, for apolar and most polar compounds, the dominating sorption mechanism governing ambient gas/particle partitioning under dry conditions is absorption into a water-insoluble organic matter (WIOM) phase, whereas under moist conditions, polar and ionized compounds can partition additionally into a mixed-aqueous phase. In order to understand how sorption into the WIOM varies for particles from diverse terrestrial locations, we looked at over 500 equilibrium gas/particle partitioning constants, Kip, measured at a specific temperature and relative humidity (15 degrees C, 50% RH), covering aerosol samples from all seasons and various locations. The data indicate that for every sample the WIOM exhibits similar intermolecular interactions with gas-phase organic compounds. For a given compound, the Kip values usually vary within a factor 3 for different aerosol samples, though they could vary by up to an order of magnitude. This is most likely due to variations in the WIOM weight fraction. Fitted poly parameter linear free energy relationships (PP-LFERs) were validated by giving good predictions of Kip values for many SVOCs in the literature, including n-alkanes, organochlorines, PCBs, though not PAHs as much of the particle-bound PAHs are likely nonexchangeable with the air phase. This study also investigated the influence of temperature on partitioning to WIOM, and found thatthe temperature dependence of Kip values can be reasonably predicted using the pure compound's enthalpy of vaporization.