Estimating Phospholipid Membrane Water Partition Coefficients Using Comprehensive Two-Dimensional Gas Chromatography
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Author(s)
Tcaciuc, Alexandra Patricia
Nelson, Robert Gregory
Reddy, Christopher M.
Gschwend, Philip M.
Date Issued
March 2012
Journal
Environmental Science and Technology
Publisher
American Chemical Society (ACS)
Citation
Tcaciuc, A. Patricia, Robert K. Nelson, Christopher M. Reddy, and Philip M. Gschwend. Estimating Phospholipid Membrane–Water Partition Coefficients Using Comprehensive Two-Dimensional Gas Chromatography. Environmental Science & Technology 46(6): 3449–3456, 2012.
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Author's final manuscript
Abstract
Recent studies have shown that membrane–water partition coefficients of organic chemicals can be used to predict bioaccumulation and type I narcosis toxicity more accurately than the traditional K[subscript OW]-based approach. In this paper, we demonstrate how comprehensive two-dimensional gas chromatography (GC × GC) can be used to estimate such membrane–water partition coefficients (K[subscript PLW]s), focusing in particular on phosphatidyl choline based lipids. This method performed well for a set of 38 compounds, including polycyclic aromatic hydrocarbons, polychlorinated benzenes and biphenyls, and substituted benzenes including some phenols and anilines. The average difference between the estimated and the measured log K[subscript PLW] values of 0.47 log units is smaller than in the case of a log K[subscript OW] correlation approach but larger than seen using a polyparameter linear free energy relationship based approach. However, the GC × GC based method presents the advantage that it can be applied to mixtures of chemicals that are not completely identified, such as petroleum hydrocarbon mixtures. At the same time, our application of the GC × GC method suffered larger errors when applied to certain hydrogen bonding compounds due to the inability of the GC × GC capillary columns phases that we used to interact with analytes via hydrogen bond donation/electron acceptance.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Sloan School of Management
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DOI of Published Version
https://doi.org/10.1021/es203792e
