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Improved method for estimating bioconcentration/bioaccumulation factor from octanol/water partition coefficient

Authors

  • William M. Meylan,

    1. Syracuse Research Corporation, Environmental Science Center, 6225 Running Ridge Road, North Syracuse, New York 13212, USA
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  • Philip H. Howard,

    1. Syracuse Research Corporation, Environmental Science Center, 6225 Running Ridge Road, North Syracuse, New York 13212, USA
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  • Robert S. Boethling,

    Corresponding author
    1. U.S. Environmental Protection Agency, Office of Pollution Prevention and Toxics, 401 M Street, SW, Washington, DC 20460
    • U.S. Environmental Protection Agency, Office of Pollution Prevention and Toxics, 401 M Street, SW, Washington, DC 20460
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  • Dallas Aronson,

    1. Syracuse Research Corporation, Environmental Science Center, 6225 Running Ridge Road, North Syracuse, New York 13212, USA
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  • Heather Printup,

    1. Syracuse Research Corporation, Environmental Science Center, 6225 Running Ridge Road, North Syracuse, New York 13212, USA
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  • Sybil Gouchie

    1. Syracuse Research Corporation, Environmental Science Center, 6225 Running Ridge Road, North Syracuse, New York 13212, USA
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Abstract

A compound's bioconcentration factor (BCF) is the most commonly used indicator of its tendency to accumulate in aquatic organisms from the surrounding medium. Because it is expensive to measure, the BCF is generally estimated from the octanol/water partition coefficient (Kow), but currently used regression equations were developed from small data sets that do not adequately represent the wide range of chemical substances now subject to review. To develop an improved method, we collected BCF data in a file that contained information on measured BCFs and other key experimental details for 694 chemicals. Log BCF was then regressed against log Kow and chemicals with significant deviations from the line of best fit were analyzed by chemical structure. The resulting algorithm classifies a substance as either nonionic or ionic, the latter group including carboxylic acids, sulfonic acids and their salts, and quaternary N compounds. Log BCF for nonionics is estimated from log Kow and a series of correction factors if applicable; different equations apply for log Kow 1.0 to 7.0 and >7.0. For ionics, chemicals are categorized by log Kow and a log BCF in the range 0.5 to 1.75 is assigned. Organometallics, nonionics with long alkyl chains, and aromatic azo compounds receive special treatment. The correlation coefficient (r2 = 0.73) and mean error (0.48) for log BCF (n = 694) indicate that the new method is a significantly better fit to existing data than other methods.

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