Quantitative relationships between molecular structures, environmental temperatures and octanol-air partition coefficients of PCDD/Fs

Reliable Prediction of the Octanol-Air Partition Ratio

The octanol-air equilibrium partition ratio (K_OA ) is frequently used to describe the volatility of organic chemicals, whereby n-octanol serves as a substitute for a variety of organic phases ranging from organic matter in atmospheric particles and soils, to biological tissues such as plant foliage, fat, blood, and milk, and to polymeric sorbents. Because measured K_OA values exist for just over 500 compounds, most of which are nonpolar halogenated aromatics, there is a need for tools that can reliably predict this parameter for a wide range of organic molecules, ideally at different temperatures. The ability of five techniques, specifically polyparameter linear free energy relationships (ppLFERs) with either experimental or predicted solute descriptors, EPISuite's KOAWIN, COSMOtherm, and OPERA, to predict the K_OA of organic substances, either at 25 °C or at any temperature, was assessed by comparison with all K_OA values measured to date. In addition, three different ppLFER equations for K_OA were evaluated, and a new modified equation is proposed. A technique's performance was quantified with the mean absolute error (MAE), the root mean square error (RMSE), and the estimated uncertainty of future predicted values, that is, the prediction interval. We also considered each model's applicability domain and accessibility. With an RMSE of 0.37 and a MAE of 0.23 for predictions of log K_OA at 25 °C and RMSE of 0.32 and MAE of 0.21 for predictions made at any temperature, the ppLFER equation using experimental solute descriptors predicted the K_OA the best. Even if solute descriptors must be predicted in the absence of experimental values, ppLFERs are the preferred method, also because they are easy to use and freely available. Environ Toxicol Chem 2021;40:3166-3180. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Partitioning and removal behaviors of PCDD/Fs, PCBs and PCNs in a modern municipal solid waste incineration system

An extensive evaluation on a modern full-scale municipal solid waste incineration system was conducted for characterizing the distribution of highly toxic chlorinated aromatics, polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs), polychlorinated biphenyls (PCBs) and polychlorinated naphthalenes (PCNs), and their corresponding mass fluxes in post combustion zone. It was found that the flue gas/fly ash partitioning behaviors of chlorinated aromatics could be essentially described by their octanol-air partition coefficients (K_OA) and strongly affected by the flue gas temperature. Above 93% of chlorinated aromatics formed in boiler section was partitioned into the flue gas and transported into the subsequent flue gas cleaning system, in which above 92% of Cl_3-8DDs, Cl_3-7DFs, Cl_5-10Bs and Cl_4-8Ns in flue gas was removed by the discharge of fly ash. The results of mass flux calculation indicated that the memory effect in flue gas cleaning system remarkably elevated the emission levels of chlorinated aromatics, especially the less chlorinated ones. The memory effect should mainly result from the direct chlorination mechanism mediated by the deposited particles. In addition, activated carbon injection could cause an obvious increase in PCBs emission. The obtained results provided some important implications for further reducing the emission of highly toxic chlorinated aromatics.

QSPR versus fragment-based methods to predict octanol-air partition coefficients: Revisiting a recent comparison of both approaches

The octanol-air partition coefficient (K_OA) is useful to assess the fate of organic chemicals in the environment. Very recently, an interesting comparison of current methods to predict this property (Chemosphere 148 (2016) 118-125) highlighted a newly introduced Quantitative Structure-Property Relationship (QSPR), as a group-contribution (GC) method and a quantum chemical solvation model were reported to yield significantly less accurate results. Based on the observation that the so-called GC method investigated in this earlier study was inconsistent with the temperature dependence of K_OA, the previously recommended QSPR is presently compared to the geometrical fragment (GF) additivity scheme. In addition to providing some improvement in terms of accuracy, this fragment-based procedure exhibits many advantages in terms of simplicity, interpretability, applicability and availability.

In silico investigation of gas/particle partitioning equilibrium of polybrominated diphenyl ethers (PBDEs)

Polybrominated diphenyl ethers (PBDEs), a group of typical brominated flame retardants (BFRs), have drawn an increasing concern due to their widespread manufacture, usage and disposal around the world and the frequent detection in a variety of environmental media. In the present study, we investigated the molecular mechanism of the partitioning equilibrium of PBDEs between gas and atmospheric particles, and developed a new temperature-dependent predictive model for the gas/particle partition coefficient (K_P) of these chemicals. Quantum chemical computations were implemented at B3LYP/6-31G (d,p) level of theory based on the neutral electronic ground state of PBDE congeners by Gaussian 09 software package. The model performance was assessed by different validation strategies and the application domain was defined by Williams Plot. Mechanism analysis indicated that the interactions of dispersion, electrostatic and hydrogen bond play crucial roles in the partitioning of PBDEs between the two phases. The developed model can be used to estimate the K_P values of PBDEs for which experimental measurements are restricted. Therefore, this work provides an alternative method in a regulatory context of PBDEs.

Development of polyparameter linear free energy relationship models for octanol-air partition coefficients of diverse chemicals

The octanol-air partition coefficient (K_OA) is a key parameter describing the partition behavior of organic chemicals between air and environmental organic phases. As the experimental determination of K_OA is costly, time-consuming and sometimes limited by the availability of authentic chemical standards for the compounds to be determined, it becomes necessary to develop credible predictive models for K_OA. In this study, a polyparameter linear free energy relationship (pp-LFER) model for predicting K_OA at 298.15 K and a novel model incorporating pp-LFERs with temperature (pp-LFER-T model) were developed from 795 log K_OA values for 367 chemicals at different temperatures (263.15-323.15 K), and were evaluated with the OECD guidelines on QSAR model validation and applicability domain description. Statistical results show that both models are well-fitted, robust and have good predictive capabilities. Particularly, the pp-LFER model shows a strong predictive ability for polyfluoroalkyl substances and organosilicon compounds, and the pp-LFER-T model maintains a high predictive accuracy within a wide temperature range (263.15-323.15 K).

Comparison of prediction methods for octanol-air partition coefficients of diverse organic compounds

The octanol-air partition coefficient (KOA) is needed for assessing multimedia transport and bioaccumulability of organic chemicals in the environment. As experimental determination of KOA for various chemicals is costly and laborious, development of KOA estimation methods is necessary. We investigated three methods for KOA prediction, conventional quantitative structure-activity relationship (QSAR) models based on molecular structural descriptors, group contribution models based on atom-centered fragments, and a novel model that predicts KOA via solvation free energy from air to octanol phase (ΔGO(0)), with a collection of 939 experimental KOA values for 379 compounds at different temperatures (263.15-323.15 K) as validation or training sets. The developed models were evaluated with the OECD guidelines on QSAR models validation and applicability domain (AD) description. Results showed that although the ΔGO(0) model is theoretically sound and has a broad AD, the prediction accuracy of the model is the poorest. The QSAR models perform better than the group contribution models, and have similar predictability and accuracy with the conventional method that estimates KOA from the octanol-water partition coefficient and Henry's law constant. One QSAR model, which can predict KOA at different temperatures, was recommended for application as to assess the long-range transport potential of chemicals.

Prediction of the Fate of Organic Compounds in the Environment From Their Molecular Properties: A Review

A comprehensive review of quantitative structure-activity relationships (QSAR) allowing the prediction of the fate of organic compounds in the environment from their molecular properties was done. The considered processes were water dissolution, dissociation, volatilization, retention on soils and sediments (mainly adsorption and desorption), degradation (biotic and abiotic), and absorption by plants. A total of 790 equations involving 686 structural molecular descriptors are reported to estimate 90 environmental parameters related to these processes. A significant number of equations was found for dissociation process (pKa), water dissolution or hydrophobic behavior (especially through the KOW parameter), adsorption to soils and biodegradation. A lack of QSAR was observed to estimate desorption or potential of transfer to water. Among the 686 molecular descriptors, five were found to be dominant in the 790 collected equations and the most generic ones: four quantum-chemical descriptors, the energy of the highest occupied molecular orbital (EHOMO) and the energy of the lowest unoccupied molecular orbital (ELUMO), polarizability (α) and dipole moment (μ), and one constitutional descriptor, the molecular weight. Keeping in mind that the combination of descriptors belonging to different categories (constitutional, topological, quantum-chemical) led to improve QSAR performances, these descriptors should be considered for the development of new QSAR, for further predictions of environmental parameters. This review also allows finding of the relevant QSAR equations to predict the fate of a wide diversity of compounds in the environment.

Field determination and QSPR prediction of equilibrium-status soil/vegetation partition coefficient of PCDD/Fs

Characterizing pseudo equilibrium-status soil/vegetation partition coefficient KSV, the quotient of respective concentrations in soil and vegetation of a certain substance at remote background areas, is essential in ecological risk assessment, however few previous attempts have been made for field determination and developing validated and reproducible structure-based estimates. In this study, KSV was calculated based on measurements of seventeen 2,3,7,8-substituted PCDD/F congeners in soil and moss (Dicranum angustum), and rouzi grass (Thylacospermum caespitosum) of two background sites, Ny-Ålesund of the Arctic and Zhangmu-Nyalam region of the Tibet Plateau, respectively. By both fugacity modeling and stepwise regression of field data, the air-water partition coefficient (KAW) and aqueous solubility (SW) were identified as the influential physicochemical properties. Furthermore, validated quantitative structure-property relationship (QSPR) model was developed to extrapolate the KSV prediction to all 210 PCDD/F congeners. Molecular polarizability, molecular size and molecular energy demonstrated leading effects on KSV.

Estimation of the physicochemical properties of PCDD/Fs using three-dimensional holographic vector of atomic interaction field

Polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) are a group of important persistent organic pollutants. In the present study, the three-dimensional holographic vector of atomic interaction field (3D-HoVAIF) method is used to describe the chemical structures of PCDD/Fs. After variable screening using a stepwise multiple regression (SMR) technique, the linear relationships among six physicochemical properties of PCDD/Fs and 3D-HoVAIF descriptors are built using a partial least-squares (PLS) regression model. The results show that the 3D-HoVAIF descriptors can be used to express the quantitative structure-property relationships of PCDD/Fs. The predictive capabilities of the models have also been confirmed by leave-one-out cross-validation. The optimum model has been used to estimate values for PCDD/Fs for which no experimental data on physicochemical properties are available. Supplemental materials are available for this article. Go to the publisher's online edition of Journal of Environmental Science and Health: Part A to view the free supplemental file.

Use of quantitative-structure property relationship (QSPR) and artificial neural network (ANN) based approaches for estimating the octanol-water partition coefficients of the 209 chlorinated trans-azobenzene congeners

Polychlorinated azobenzenes (PCABs) can be found as contaminant by products in 3,4-dichloroaniline and its derivatives and in the herbicides Diuron, Linuron, Methazole, Neburon, Propanil and SWEP. Trans congeners of PCABs are physically and chemically more stable and so are environmentally relevant, when compared to unstable cis congeners. In this study, to fulfill gaps on environmentally relevant partitioning properties of PCABs, the values of n-octanol/water partition coefficients (log K(OW)) have been determined for 209 congeners of chloro-trans-azobenzene (Ct-AB) by means of quantitative structure-property relationship (QSPR) approach and artificial neural networks (ANN) predictive ability. The QSPR methods used based on geometry optimalization and quantum-chemical structural descriptors, which were computed on the level of density functional theory (DFT) using B3LYP functional and 6-311++G basis set in Gaussian 03 and of the semi-empirical quantum chemistry method (PM6) of the molecular orbital package (MOPAC). Polychlorinated dibenzo-p-dioxins (PCDDs), -furans (PCDFs) and -biphenyls (PCBs), to which PCABs are related, were reference compounds in this study. An experimentally obtained data on physical and chemical properties of PCDD/Fs and PCBs were reference data for ANN predictions of log K(OW) values of Ct-ABs in this study. Both calculation methods gave similar results in term of absolute log K(OW) values, while the models generated by PM6 are considered highly efficient in time spent, when compared to these by DFT. The estimated log K(OW) values of 209 Ct-ABs varied between 5.22-5.57 and 5.45-5.60 for Mono-, 5.56-6.00 and 5.59-6.07 for Di-, 5.89-6.56 and 5.91-6.46 for Tri-, 6.10-7.05 and 6.13-6.80 for Tetra-, 6.43-7.39 and 6.48-7.14 for Penta-, 6.61-7.78 and 6.98-7.42 for Hexa-, 7.41-7.94 and 7.34-7.86 for Hepta-, 7.99-8.17 and 7.72-8.20 for Octa-, 8.35-8.42 and 8.10-8.62 for NonaCt-ABs, and 8.52-8.60 and 8.81-8.83 for DecaCt-AB. These log K(OW) values shows that Ct-ABs are compounds of relatively low environmental mobility (log K(OW) > 4.5) and of significant bioaccumulation potential.

Prediction of supercooled liquid vapor pressures and n-octanol/air partition coefficients for polybrominated diphenyl ethers by means of molecular descriptors from DFT method

The molecular geometries of 209 polybrominated diphenyl ethers (PBDEs) were optimized at the B3LYP/6-31G level with Gaussian 98 program. The calculated structural parameters were taken as theoretical descriptors to establish two novel QSPR models for predicting supercooled liquid vapor pressures (P(L)) and octanol/air partition coefficients (K(OA)) of PBDEs based on the theoretical linear solvation energy relationship (TLSER) model, respectively. The two models achieved in this work both contain three variables: most negative atomic partial charge in molecule (q(-)), dipole moment of the molecules (mu) and mean molecular polarizability (alpha), of which R(2) values are both as high as 0.997, their root-mean-square errors in modeling (RSMEE) are 0.069 and 0.062 respectively. In addition, the F-value of two models are both evidently larger than critical values F(0.05) and the variation inflation factors (VIF) of variables herein are all less than 5.0, suggesting obvious statistic significance of the P(L) and K(OA) predicting models. The results of Leave-One-Out (LOO) cross-validation for training set and validation with external test set both show that the two models obtained exhibited optimum stability and good predictive power. We suggest that the QSPRs derived here can be used to predict accurately P(L) and K(OA) for non-tested PBDE congeners from Mono-BDEs to Hepta-BDEs and from Mono-BDEs to Hexa-BDEs, respectively.

QSPR/QSAR models for prediction of the physicochemical properties and biological activity of polybrominated diphenyl ethers

Polybrominated diphenyl ethers (PBDEs) are a group of important persistent organic pollutants. In the present study, geometrical optimization and electrostatic potential calculations have been performed for all 209 PBDE congeners at the HF/6-31G level of theory. A number of statistically-based parameters have been obtained. Linear relationships between gas-chromatographic relative retention time (RRT), n-octanol/air partition coefficient (lgK(OA)), 298 K supercooled liquid vapour pressures (lgp(L)), Henry's law constant (lgH) and Ah receptor binding affinity (-lgRBA) of PBDEs and the structural descriptors have been established by multiple regression method. The result shows that the quantities derived from electrostatic potential V(s,max),V(s,min),Pi, Sigma V+(S), V-(S) , nu, sigma 2(tot), and N-(v), together with the molecular volume (Vmc) can be well used to express the quantitative structure-property relationships of PBDEs, which proves the general applicability of this parameter set to a great extent. Good predictive capabilities have also been demonstrated. Based on these equations, the predicted values have been presented for those PBDE congeners whose experimentally determined physicochemical properties are unavailable. The QSAR model for the Ah receptor binding affinity is relatively poor, which can be ascribed to the complexity of factors which affect biological activity and the limitations of the present parameter set in describing steric characters of the molecule.

Prediction of environmental partition coefficients and the Henry's law constants for 135 congeners of chlorodibenzothiophene

Polychlorinated dibenzothiophenes (PCDTs) could be classified as persistent organic pollutants (POPs) in the environment and are particularly interesting due to their structural resemblance to highly toxic dioxins. We show here some basic environmental properties such as n-octanol water (K(OW)), n-octanol/air (K(OA)) and air/water (K(AW)) partition coefficients as well as Henry's law constants (K(H)) for all 135 congeners of chlorodibenzothiophene. Predictions were made by regression of principal components (PCR) and with aid of a set of standard chemicals, for which physical-chemical properties are well featured. Computed K(OW), K(OA), K(AW) and K(H) values for mono-CDTs ranged, respectively, between 4.66 and 4.71, 7.48 and 7.55, -2.84 and -2.82, 3.56 and 3.74; for di-CDTs between 5.02 and 5.28, 8.03 and 8.29, -3.01 and -2.95, 2.42 and 2.75; for tri-CDTs between 5.53 and 5.70, 8.65 and 8.87, -3.2 and -3.11, 1.58 and 1.92; for tetra-CDTs between 5.95 and 6.13, 9.27 and 9.50, -3.39 and -3.27, 1.02 and 1.33; for penta-CDTs between 6.38 and 6.51, 9.88 and 10.05, -3.54 and -3.45, 0.72 and 0.88; for hexa-CDTs between 6.83 and 6.97, 10.54 and 10.66, -3.72 and -3.64, 0.47 and 0.56; for hepta-CDTs between 7.28 and 7.35, 11.12 and 11.20, -3.81 and -3.87, 0.33 and 0.38; for octa-CDT 7.74, 11.78, -4.04 and 0.23. An estimated value of the three types of partition coefficient and Henry's law constants suggest that polychlorinated dibenzothiophenes are lipophilic and semi-volatile persistent organic pollutants. Their mobility in the environment seems to be very similar to that of some well-known POPs such as polychlorinated dibenzofurans, -dibenzo-p-dioxins, and -biphenyls or organochlorine pesticides.

Prediction of octanol--air partition coefficients of semivolatile organic compounds based on molecular connectivity index

A new method has been developed to describe the quantitative relationship between the octanol-air partition coefficients and molecular connectivity indexes of semivolatile organic compounds such as polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs), polychlorinated naphthalenes (PCNs), polycyclic aromatic hydrocarbons (PAHs), chlorobenzenes (CBs), polybrominated diphenyl ethers (PBDEs). The stepwise multiple linear regression was used to derive six equations with correlation coefficients greater than 0.99 except for PBDEs' (0.96). The largest relative error is 4.6%, and the standard deviation is less than 1.83 log units. Compared with the data obtained from the relevant experiments, the results of prediction are very accurate.

Quantitative predictive models for octanol-air partition coefficients of polybrominated diphenyl ethers at different temperatures

Quantitative predictive models for octanol-air partition coefficients of polybrominated diphenyl ethers at different environmental temperatures (T) were developed. Partial least squares (PLS) regression was used for model development. A list of 18 theoretical molecular structural descriptors was screened by PLS analysis. The optimal model was selected from the one containing nine theoretical molecular descriptors and 1/T as predictor variables. The cross-validated Q(2)(cum) value for the optimal model is 0.975, indicating a good predictive ability and stability of the model. Intermolecular dispersive interactions play a leading role in governing the magnitude of logK(OA). The lower the E(LUMO) (the energy of the lowest unoccupied molecular orbital), the greater the intermolecular interactions between octanol and PCB molecules, and thus the greater the logK(OA) values.