4.7 Article

SSP silicone-, lipid- and SPMD-water partition coefficients of seventy hydrophobic organic contaminants and evaluation of the water concentration calculator for SPMD

期刊

CHEMOSPHERE
卷 223, 期 -, 页码 748-757

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chemosphere.2019.01.164

关键词

Passive sampling; Freely dissolved; Partition coefficient; Hydrophobic organic compounds; Lipid; Semi-permeable membrane device

资金

  1. Czech Science Foundation [GACR 15-16512S]
  2. Czech Ministry of Education, Youth and Sports [LM2015051]
  3. European Structural and Investment Funds, Operational Programme Research, Development, Education [CZ.02.1.01/0.0/0.0/16_013/0001761]

向作者/读者索取更多资源

Passive sampling is increasingly applied for monitoring neutral hydrophobic compounds (HOC) in various environmental media like water, sediment, air and also soft biota tissue. Passive samplers for HOC are often constructed from permeable polymers like silicone and polyethylene (PE), while also SPMD are often applied. Their HOC uptake can be converted to freely dissolved or equivalent lipid-based concentrations using appropriate partition coefficients with or without the use of kinetic uptake models to adjust for non-equilibrium. To facilitate such conversions for seventy HOC partition coefficients are derived by combining polymer-water for Altesil (TM) silicone and PE, with new and earlier published polymer-polymer, polymer-lipid partition coefficients. Derived SSP silicone-water, lipid-water (K-lip/w), and SPMD-water (K-spmd/w) partition coefficients demonstrate good agreement with literature data, except for K-spmd/w. For SPMD, this work demonstrates a linear K-spmd/w - K-ow relationship (R-2 = 0.99) in contrast to the parabolic K-spmd/w - K-ow relationship utilized in the USGS SPMD Water Concentrations Calculator. Following a thorough evaluation of this Calculator it is recommended that in combination with revised K-spmd/w, a radical different model approach should be used for obtaining accurate water concentrations from passive sampling with SPMD. (C) 2019 Elsevier Ltd. All rights reserved.

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