Reliability of environmental fate modeling results for POPs based on various methods of determining the air/water partition coefficient (log KAW)

• Published in: Atmospheric environment (1994) Vol. 73; pp. 177 - 184
• Main Authors: Odziomek, K., Gajewicz, A., Haranczyk, M., Puzyn, T.
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01-07-2013; Elsevier
• Subjects: Air–water partition coefficient; Applied sciences; Exact sciences and technology; Global environmental pollution; Multimedia mass modeling; Pollution; POPs; QSPR; QSPR; Air–water partition coefficient; Multimedia mass modeling; POPs; Multimedia model; Pollutant behavior; Partition coefficient; Modeling; Persistent organic pollutant; Air―water partition coefficient; Pollution; Environment; Phase partition; Property structure relationship; Reliability; Organic compounds
• ISSN: 1352-2310; 1873-2844
• DOI: 10.1016/j.atmosenv.2013.02.052

Air–water partition coefficient (KAW) is one of the key parameters determining environmental behavior of Persistent Organic Pollutants (POPs). Experimentally measured values of KAW are still unavailable for majority of POPs, thus alternative methods of supplying data, including Quantitative Structure–Property Relationships (QSPR) modeling, are often in use. In this paper, applicability of two QSPR methods of predicting KAW were compared with each other in the context of further application of the predicted data in environmental transport and fate studies. According to the first (indirect) method, KAW is calculated from previously predicted values of octanol–water (KOW) and octanol–air (KOA) partition coefficients. In the second (direct) approach, KAW is calculated, based on the estimated value of Henry's law constant (KH) and then adjusted to ensure its consistency with the other two partition coefficients (KOW and KOA). Although the indirect method carries theoretically twice as much error as the direct method, when the predicted values of KAW are then utilized as an input to the environmental fate model The OECD POV and LRTP Screening Tool, ver. 2.2, the indirect method elicits much higher and therefore much more restrictive values of overall persistence (POV) and transfer efficiency (TE) than its equivalent (direct method). High uncertainties related to the application of the direct method result mainly from the necessary adjustment procedure.
•We present practical recommendations for determining log KAW with use of QSPR.•We compare two strategies of deriving KAW: indirect and direct.•Indirect method uses KOW and KOA values previously predicted with QSPR.•In direct method the values of KH are predicted with QSPR and then converted into KAW.•The indirect method is more optimal than the direct approach.