Development of predictive models for silicone rubber-water partition coefficients of hydrophobic organic contaminants

被引:4
作者
Sun, Huichao [1 ]
Yang, Xianhai [2 ]
Li, Xuehua [3 ]
Jin, Xiaochen [3 ,4 ]
机构
[1] Liaoning Normal Univ, Sch Life Sci, Dalian 116081, Peoples R China
[2] Nanjing Univ Sci & Technol, Sch Environm & Biol Engn, Jiangsu Key Lab Chem Pollut Control & Resources R, Nanjing 210094, Jiangsu, Peoples R China
[3] Dalian Univ Technol, Sch Environm Sci & Technol, Key Lab Ind Ecol & Environm Engn MOE, Dalian 116024, Peoples R China
[4] George Washington Univ, Dept Civil & Environm Engn, Washington, DC 20052 USA
基金
中国国家自然科学基金;
关键词
LOW-DENSITY POLYETHYLENE; POLYOXYMETHYLENE PASSIVE SAMPLERS; SEMIPERMEABLE-MEMBRANE DEVICES; DIFFERENT VALIDATION CRITERIA; REAL EXTERNAL PREDICTIVITY; QSAR MODELS; POLYCHLORINATED-BIPHENYLS; ENERGY RELATIONSHIPS; DIVERSE SET; EQUILIBRIUM;
D O I
10.1039/c9em00343f
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
The silicone rubber passive sampling technique is extensively applied to monitor the aqueous freely dissolved concentration of hydrophobic organic compounds (HOCs). The silicone rubber-water partition coefficient (K-srw) is an important parameter to accurately measure the concentrations of chemicals using passive sampling devices. In this study, two theoretical linear solvation energy relationship (TLSER) models and a quantitative structure-property relationship (QSPR) model were developed for predicting the K-srw of HOCs. The 119 model compounds studied here included 31 personal care products, such as musks, UV-filters, and organophosphate flame retardants, as well as "conventional" pollutants, such as polycyclic aromatic hydrocarbons and polychlorinated biphenyls. The statistical parameters indicated that the final QSPR model with seven descriptors for all 119 chemicals had a satisfactory goodness-of-fit (R-adj(2) = 0.898), robustness (Q(LOO)(2) = 0.881) and predictive ability (Q(ext-F1,2,3)(2) = 0.897-0.926). In comparison, the results of one TLSER model with four descriptors for 113 chemicals (R-adj(2) = 0.826, Q(LOO)(2) = 0.790, Q(ext-F1,2,3)2 = 0.805-0.837) and another TLSER model with one descriptor for 5 chemicals (R-adj(2) = 0.747, Q(LOO)(2) = 0.647) were also acceptable. The applicability domains of the obtained models covered chemicals containing hydroxyl, imino groups, carbonyl groups, ether bonds, halogen atoms, sulfur atoms, phosphorus atoms, nitro groups, and cyano groups. In addition, the structural features governing the partition behavior of chemicals between silicone rubber and water were explored through interpretation of appropriate mechanisms.
引用
收藏
页码:2020 / 2030
页数:11
相关论文
共 86 条
[1]   Passive sampling for target and nontarget analyses of moderately polar and nonpolar substances in water [J].
Allan, Ian J. ;
Harman, Christopher ;
Ranneklev, Sissel B. ;
Thomas, Kevin V. ;
Grung, Merete .
ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY, 2013, 32 (08) :1718-1726
[2]  
[Anonymous], [No title captured]
[3]  
[Anonymous], 2007, OECD Environment Health and Safety Publications Series on Testing and Assessment, DOI DOI 10.1787/9789264085442-EN
[4]   A GMDH-type neural network with multi-filter feature selection for the prediction of transition temperatures of bent-core liquid crystals [J].
Antanasijevic, Davor ;
Antanasijevic, Jelena ;
Pocajt, Viktor ;
Uscumlic, Gordana .
RSC ADVANCES, 2016, 6 (102) :99676-99684
[5]   Mechanisms and modeling of halogenated aliphatic contaminant adsorption by carbon nanotubes [J].
Apul, Onur Guven ;
Zhou, Yang ;
Karanfil, Tanju .
JOURNAL OF HAZARDOUS MATERIALS, 2015, 295 :138-144
[6]   Dissolved PCBs, PAHs, and HCB in pore waters and overlying waters of contaminated harbor sediments [J].
Booij, K ;
Hoedemaker, JR ;
Bakker, JF .
ENVIRONMENTAL SCIENCE & TECHNOLOGY, 2003, 37 (18) :4213-4220
[7]   Spiking of performance reference compounds in low density polyethylene and silicone passive water samplers [J].
Booij, K ;
Smedes, F ;
van Weerlee, EM .
CHEMOSPHERE, 2002, 46 (08) :1157-1161
[8]   Passive Sampling in Regulatory Chemical Monitoring of Nonpolar Organic Compounds in the Aquatic Environment [J].
Booij, Kees ;
Robinson, Craig D. ;
Burgess, Robert M. ;
Mayer, Philipp ;
Roberts, Cindy A. ;
Ahrens, Lutz ;
Allan, Ian J. ;
Brant, Jan ;
Jones, Lisa ;
Kraus, Uta R. ;
Larsen, Martin M. ;
Lepom, Peter ;
Petersen, Joerdis ;
Proefrock, Daniel ;
Roose, Patrick ;
Schaefer, Sabine ;
Smedes, Foppe ;
Tixier, Celine ;
Vorkamp, Katrin ;
Whitehouse, Paul .
ENVIRONMENTAL SCIENCE & TECHNOLOGY, 2016, 50 (01) :3-17
[9]   Performance of passive sampling with low-density polyethylene membranes for the estimation of freely dissolved DDx concentrations in lake environments [J].
Borrelli, Raffaella ;
Tcaciuc, A. Patricia ;
Verginelli, Iason ;
Baciocchi, Renato ;
Guzzella, Licia ;
Cesti, Pietro ;
Zaninetta, Luciano ;
Gschwend, Philip M. .
CHEMOSPHERE, 2018, 200 :227-236
[10]   QSAR modeling of nanomaterials [J].
Burello, Enrico ;
Worth, Andrew P. .
WILEY INTERDISCIPLINARY REVIEWS-NANOMEDICINE AND NANOBIOTECHNOLOGY, 2011, 3 (03) :298-306