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

Abstract

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.

Organic Carbon/Water and Dissolved Organic Carbon/Water Partitioning of Cyclic Volatile Methylsiloxanes: Measurements and Polyparameter Linear Free Energy Relationships

“…The largest errors occurred in the predictions of log K DOC , but RMSEs for the new PP-LFERs are in all cases less than 0.5 log units (Figure 3 C and D). Including our new measurements of K OC for cVMS and PCBs in the training set of Bronner et al 29 and recalculating the solvent descriptors ( Figure S2) also improved the fit to our measurements of K OC …”

“…The data set of Bronner et al 29 has a smaller range of log K OC spanning from 0.64 to 4.39. All our measurements are higher than 4.39 and therefore they could be considered outside the application domain of the Bronner et al 29 PP-LFER.…”

Comparison of Atmospheric Travel Distances of Several PAHs Calculated by Two Fate and Transport Models (The Tool and ELPOS) with Experimental Values Derived from a Peat Bog Transect

“…The K OC values at 25 °C were estimated using a poly-parameter linear free energy relationship (pp-LFER) [33] and solute descriptors from Absolv online [34]. While ELPOS has a built-in routine to adjust these coefficients to a user-supplied temperature, The Tool requires the user to supply temperature-adjusted input information.…”

A linear solvation energy relationship model of organic chemical partitioning to particulate organic carbon in soils and sediments

“…The assumption implicit in Equation 1 is that all particulate organic carbon, regardless of origin or composition, has the same affinity for a particular chemical. Nguyen et al [16], Niederer et al [18], Park and Lee [26], Baker et al [27], Poole and Poole [28], Endo et al [29], and Bronner and Goss [30] presented models based on a linear solvation energy relationship (LSER), the model that is the focus of the present study. Models for K OC have been presented using quantitative structure-activity relationships, including molecular connectivity indices, correlations using the octanol-water partition coefficient, and correlations with the solubility of the compounds [12,16,19,22,24].…”