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首页> 外文会议>Proceedings of the Twenty-eighth Arctic and Marine Oilspill Program(AMOP) Technical Seminar vol.1 >Chemical Fingerprinting of Terpanes and Steranes by Chromatographic Alignment and Principal Component Analysis
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Chemical Fingerprinting of Terpanes and Steranes by Chromatographic Alignment and Principal Component Analysis

机译：色谱和主成分分析法对萜类和甾类的化学指纹图谱

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The complex patterns of biomarker terpane and sterane isomers were used for oil hydrocarbon fingerprinting by time warping and PCA. The study is an extension of a previous fingerprinting study for distinguishing and identifying the source of oil spill samples, based solely on the sterane isomer profiles. The fingerprinting method consists of GC-MS/SIM analysis, pre-processing of chromatograms and principal component analysis (PCA) of selected chromatographic regions. The preprocessing step is comprised of baseline removal by calculating the first derivatives, retention time alignment using correlation optimized warping (COW) and data normalization. Preprocessed and combined sections of chromatograms of m/z 191 (terpanes) and m/z 217 (steranes) for 82 oil samples (spill and source oils) were analyzed by weighted least squares - PCA (WLS-PCA). Oil spill samples, collected from the coastal environment in the weeks after the Baltic Carrier oil spill, 29th March 2001, clustered with oil samples from the tank of the Baltic Carrier along the four significant principal components. Likewise, two independent spill samples from a previous Round-Robin exercise organized by SINTEF, Norway clustered with their corresponding source oils from the Norwegian sector of the North Sea, Oseberg East and Oseberg Field Center.rnThe four principal components were interpreted as: boiling point range, clay content, marine or terrestrial organic matter, and maturity based on differences in the terpane and sterane isomer patterns. In summary, this method offers a fast and objective procedure for analyzing chromatograms with more comprehensive data usage compared to other fingerprinting methods.
机译：生物标志物萜烯和甾烷异构体的复杂模式通过时间扭曲和PCA用于石油烃指纹图谱。该研究是先前指纹研究的扩展，该研究仅基于甾烷烃异构体谱图来区分和识别溢油样品的来源。指纹分析方法包括GC-MS / SIM分析，色谱图的预处理和所选色谱图区域的主成分分析（PCA）。预处理步骤包括通过计算一阶导数进行基线去除，使用相关优化翘曲（COW）进行保留时间对齐以及数据归一化。通过加权最小二乘-PCA（WLS-PCA）分析m / z 191（萜烯）和m / z 217（甾烷）的色谱图的预处理部分和合并部分。 2001年3月29日波罗的海运输船漏油后几周从沿海环境中收集的漏油样本与来自波罗的海运输船油箱的石油样本沿四个重要的主要部分聚集在一起。同样，挪威SINTEF之前进行的一次循环法演习中的两个独立的溢油样本与来自北海，Oseberg East和Oseberg油田中心的挪威部门相应的源油聚集在一起.rn这四个主要成分被解释为：沸点范围，粘土含量，海洋或陆地有机物，以及基于萜烯和甾烷异构体模式差异的成熟度。总而言之，与其他指纹方法相比，该方法提供了一种快速客观的方法来分析具有更全面数据使用情况的色谱图。

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