Estimating dissolved organic carbon partition coefficients for nonionic organic chemicals

被引:282
|
作者
Burkhard, LP [1 ]
机构
[1] US EPA, Off Res & Dev, Natl Hlth & Environm Effects Res Lab, Mid Continent Ecol Div, Duluth, MN 55804 USA
关键词
D O I
10.1021/es001269l
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
A literature search was performed for dissolved organic carbon/water partition coefficients for nonionic organic chemicals (K-DOC), and K-DOC data were taken from more than 70 references. The K-DOC data were evaluated as a function of the 1-octanol/water partition coefficients (K-OW). A predictive relationship of K-DOC = 0.08K(OW) with 95% confidence limits of a factor of 20 in either direction was developed using K-DOC data based upon naturally occurring dissolved organic carbon. Inclusion of K-DOC data for Aldrich humic acid, a reagent-grade organic carbon, resulted in a slightly different predictive relationship of K-DOC = 0.11K(OW) with 95% confidence limits of a factor of 14 in either direction. The large uncertainties in these relationships are, in part, caused by the variability in structure and composition of dissolved organic carbon (DOC) in sediments, soils, and surface waters. This variability is not accounted for by the hydrophobicity parameter. For individual chemicals, ranges in K-DOC values approaching 2 orders of magnitude were observed among investigations using Aldrich humic acid as the DOC. These large ranges of K-DOC values suggest that measurement techniques are also, in part, responsible for the large uncertainties in these relationships.
引用
收藏
页码:4663 / 4668
页数:6
相关论文
共 50 条
  • [1] Predicting dissolved organic carbon partition and distribution coefficients of neutral and ionizable organic chemicals
    Vitale, Chiara Maria
    Di Guardo, Antonio
    SCIENCE OF THE TOTAL ENVIRONMENT, 2019, 658 : 1056 - 1063
  • [2] Development of the fragment constant method for estimating the partition coefficients of nonionic organic mixtures
    Lin, Z
    Yu, H
    Gao, S
    Cheng, J
    Wang, L
    ARCHIVES OF ENVIRONMENTAL CONTAMINATION AND TOXICOLOGY, 2001, 41 (03) : 255 - 260
  • [3] Development of the fragment constant method for estimating the partition coefficients of nonionic organic mixtures
    Lin Z.
    Yu H.
    Gao S.
    Cheng J.
    Wang L.
    Archives of Environmental Contamination and Toxicology, 2001, 41 (3) : 255 - 260
  • [4] Estimating the organic carbon partition coefficient and its variability for hydrophobic chemicals
    Seth, R
    Mackay, D
    Muncke, J
    ENVIRONMENTAL SCIENCE & TECHNOLOGY, 1999, 33 (14) : 2390 - 2394
  • [5] A review of the predictive models estimating association of neutral and ionizable organic chemicals with dissolved organic carbon
    Vitale, Chiara Maria
    Di Guardo, Antonio
    SCIENCE OF THE TOTAL ENVIRONMENT, 2019, 666 : 1022 - 1032
  • [6] PREDICTING PARTITION-COEFFICIENTS OF NONIONIC ORGANIC POLLUTANTS BY EFFECTIVE POLARITY
    XING, BS
    MCGILL, WB
    DUDAS, MJ
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 1994, 207 : 72 - ENVR
  • [7] Biotransformation of trace organic chemicals in the presence of highly refractory dissolved organic carbon
    Hellauer, Karin
    Mayerlen, Sara Martinez
    Drewes, Joerg E.
    Huebner, Uwe
    CHEMOSPHERE, 2019, 215 : 33 - 39
  • [8] Estimating the polyethylene-water partition coefficients of organic chemicals using comprehensive 2D gas chromatography
    Tcaciuc, A. Patricia
    Nelson, Robert K.
    Reddy, Christopher M.
    Gschwend, Philip M.
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2012, 244
  • [9] Prediction of octanol-water partition coefficients of organic chemicals by QSAR models
    Noorizadeh, Hadi
    Sajjadifar, Sami
    Farmany, Abbas
    Sobhanardakani, S.
    TOXICOLOGICAL AND ENVIRONMENTAL CHEMISTRY, 2013, 95 (08): : 1267 - 1278
  • [10] COMPUTER-PROGRAM FOR THE ESTIMATION OF PARTITION-COEFFICIENTS OF ORGANIC-CHEMICALS
    MCCALL, PJ
    LASKOWSKI, DA
    SWANN, RL
    DISHBURGER, HJ
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 1980, 180 (AUG): : 26 - PEST