Chemometrics-Assisted Effect-Directed Analysis of Crude and Refined Oil Using Comprehensive Two-Dimensional Gas Chromatography-Time-of-Flight Mass Spectrometry

被引:32
作者
Radovic, Jagos R. [1 ]
Thomas, Kevin V. [2 ]
Parastar, Hadi [3 ]
Diez, Sergi [1 ]
Tauler, Roma [1 ]
Bayona, Josep M. [1 ]
机构
[1] IDAEA CSIC, Dept Environm Chem, Barcelona 08034, Spain
[2] Norwegian Inst Water Res, NIVA, N-0349 Oslo, Norway
[3] Sharif Univ Technol, Dept Chem, Tehran 111553516, Iran
关键词
POLYCYCLIC AROMATIC-HYDROCARBONS; QUANTITATIVE-ANALYSIS; JET FUEL; TOXICITY; RESOLUTION; RECEPTOR; QUANTIFICATION; IDENTIFICATION; SEDIMENTS; TOXICANTS;
D O I
10.1021/es404859m
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
An effect-directed analysis (EDA) of fresh and artificially weathered (evaporated, photooxidized) samples of North Sea crude oil and residual heavy fuel oil is presented. Aliphatic, aromatic, and polar oil fractions were tested for the presence of aryl hydrocarbon receptor (AhR) agonist and androgen receptor (AR) antagonist, demonstrating for the first time the AR antagonist effects in the aromatic and, to a lesser extent, polar fractions. An extension of the typical EDA strategy to include an N-way partial least-squares (N-PLS) model capable of relating the comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC X GC-TOFMS) data set to the bioassay data obtained from normal-phase LC fractions is proposed. The predicted AhR binding effects in the fresh and artificially weathered aromatic oil fractions facilitated the identification of alkyl-substituted three- and four-ring aromatic systems in the active fractions through the weighting of their contributions to the observed effects. A N-PLS chemometric model is demonstrated as a potentially useful strategy for future EDA studies that can streamline the compound identification process and provide additional reduction of samples' complexity. The AhR binding effects of the suspected compounds predicted by N-PLS and identified by GC X GC-TOFMS were confirmed using quantitative structure-activity relationship (QSAR) estimates.
引用
收藏
页码:3074 / 3083
页数:10
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