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COMPARISON OF THE OCTANOL-AIR PARTITION COEFFICIENT AND LIQUID-PHASE VAPOR PRESSURE AS DESCRIPTORS FOR PARTICLE/GAS PARTITIONING USING LABORATORY AND FIELD DATA FOR PCBS AND PCNS
Citation:
Falconer, R L. AND T. Harner. COMPARISON OF THE OCTANOL-AIR PARTITION COEFFICIENT AND LIQUID-PHASE VAPOR PRESSURE AS DESCRIPTORS FOR PARTICLE/GAS PARTITIONING USING LABORATORY AND FIELD DATA FOR PCBS AND PCNS. ATMOSPHERIC ENVIRONMENT 34(23):4043-4046, (2000).
Impact/Purpose:
The goal of this task is to contribute to a better understanding of human exposure to pesticides, especially for small children by developing methods to characterize sources and pathways in and around the residential environment. We will support the science behind FQPA and assist the Office of Pesticide Programs (OPP) in the development of guidelines for the assessment of residential exposure to pesticides. Specific research objectives include: (i) to evaluate and develop methods for measuring pesticides in air using passive/diffusive samplers. Assess and refine devices for the collection of surface transferable pesticide residues and to establish transfer efficiencies; (ii) to develop and apply analytical methods for new and emerging pesticides using both gas and liquid chromatographic methods in support of the National Exposure Research Laboratory's (NERL) Human Exposure Measurement Project; and, (iii) to conduct pilot studies investigating chiral chromatographic methods.
Description:
The conventional Junge-Pankow adsorption model uses the sub-cooled liquid vapor pressure (pLo) as a correlation parameter for gas/particle interactions. An alternative is the octanol-air partition coefficient (Koa) absorption model. Log-log plots of the particle-gas partition coefficient versus pLo were previously made for partitioning data from controlled laboratory studies, resulting in separate trend lines for different ortho-substituted PCB classes. The same plots applied to field data for PCBs and PCNs resulted in separate regression lines with slopes that were statistically different at the 99% confidence level. When Koa is used as the correlation parameter, these differences are resolved showing the ability of the model to reduce variability both within a compound class and between compound classes. The Koa model is also preferred because it uses parameters that can be measured directly (Koa and fom), unlike the parameters of the Junge-Pankow model which must be estimated.
The research described herein was developed by the author, an employee of the US Environmental Protection Agency, in her previous position. It was conducted independently of EPA employment and has not been subjected to Agency's peer and administrative review. Therefore, the conclusions and opinions drawn are solely those of the author and should not be construed to reflect the views of the Agency.