Ambient gas/particle partitioning. 3. Estimating partition coefficients of apolar, polar, and ionizable organic compounds by their molecular structure.

Environmental science & technology

PubMedID: 19368193

Arp HP, Gosses KU. Ambient gas/particle partitioning. 3. Estimating partition coefficients of apolar, polar, and ionizable organic compounds by their molecular structure. Environ Sci Technol. 2009;43(6):1923-9.
Equilibrium gas/particle partitioning coefficients of terrestrial aerosols, Kip, are dependent on various intermolecular interactions that can be quantified by experimentally determined compound-specific descriptors. For many compounds of environmental interest, such as emerging contaminants and atmospheric phototransformation products, these compound-specific descriptors are unknown or immeasurable. Often, only the molecular structure is known. Here we present the ability of two computer programs to predict equilibrium partitioning to terrestrial aerosols solely on the basis of molecular structure: COSMOtherm and SPARC. The greatest hurdle with designing such an approach is to identify suitable molecular surrogates to represent the dominating sorbing phases, which for ambient terrestrial aerosols are the water insoluble organic matter (WIOM) phase and the mixed-aqueous phase. For the WI0M phase, hypothetical urban secondary organic aerosol structural units from Kalberer et al. Science 2004, 303, 1659-1662 were investigated as input surrogates, and for the mixed-aqueous phase mildly acidic water was used as a surrogate. Using a validation data set of more than 1400 experimentally determined Kip values for polar, apolar, and ionic compounds ranging over 9 orders of magnitude (including semivolatile compounds such as PCDD/Fs, pesticides, and PBDEs), SPARC and COSMOtherm were generally able to predict Kip values well within an order of magnitude over an ambient range of temperature and relative humidity. This is remarkable as these two models were not fitted or calibrated to any experimental data. As these models can be used for potentially any organic molecule, they are particularly recommended for environmental screening purposes and for use when experimental compound descriptor data are not available.