GC-MS方法在船舶溢油油源鉴别中的应用研究

发布时间：2018-01-23 09:53

本文关键词： 船舶溢油油指纹 GC-MS 模糊聚类分析　出处：《集美大学》2014年硕士论文　论文类型：学位论文

【摘要】：随着航运业的快速发展，船舶溢油事故不断增加。船舶港区操作性溢油尽管溢油量小，但溢油事故多，对港区环境影响大。因此，有必要对此开展溢油油源鉴别，为海事主管部门开展溢油事故调查提供技术支撑。通过运用GC-MS方法对3条船上的12个可疑油样及4个溢油油样进行定性及定量分析，利用原始指纹图谱、相对浓度分布特征及特征比值分别对船舶不同类型的油样（燃料油、柴油、滑油）和混合油样（舱底水）进行鉴别分析，并通过这些指纹信息对单一油样和混合油样进行模糊聚类分析。研究表明：不同类型的油样之间，，组分差异较大，正构烷烃（含植烷、姥鲛烷）、多环芳烃、萜、甾类等标志性化合物的原始指纹图谱差异也较明显，故通过直观的判断即可快速有效的鉴定出溢油源；同种类型不同型号油样之间，组分差异较小，正构烷烃（含植烷、姥鲛烷）、多环芳烃、萜、甾类等标志性化合物的原始指纹图谱差异也不明显，故需基于组分的相对含量及特征比值来进行鉴定。本研究亦利用燃料油的相对浓度及特征比值数据分别进行了模糊聚类分析，并与燃料油原始指纹图谱、相对浓度分布及特征比值分析进行了对比，确定模糊聚类分析适合选取相对浓度参数；利用模糊聚类分析分别对单一溢油油样和混合溢油油样的正构烷烃（含植烷、姥鲛烷）、多环芳烃、萜、甾类等标志性化合物的相对浓度进行分析，使得溢油源与可疑油样的“亲疏远近”关系一目了然，可以更为直观、客观地进行溢油油源鉴别。
[Abstract]:With the rapid development of the shipping industry, the number of oil spill accidents is increasing. Although the oil spill in the port area is small, there are many oil spill accidents, which have a great impact on the environment of the port area. It is necessary to identify the source of oil spill and provide technical support for the investigation of oil spill accident. The qualitative and quantitative analysis of 12 suspected oil samples and 4 oil spill samples from 3 ships were carried out by using GC-MS method, and the original fingerprint was used. The relative concentration distribution characteristics and characteristic ratios were used to identify different types of oil samples (fuel oil, diesel oil, lubricating oil) and mixed oil samples (bilge water). Through these fingerprint information, the single oil sample and mixed oil sample are analyzed by fuzzy clustering. The results showed that there were significant differences in components among different types of oil samples, and the differences in the original fingerprints of n-alkanes (including phytane, prickly), polycyclic aromatic hydrocarbons (PAHs), terpenes, steroids, and other landmark compounds were also obvious. Therefore, the source of oil spill can be identified quickly and effectively by direct judgment. The difference of components between the same type and different types of oil samples was small, and the difference of the original fingerprint of n-alkanes (including phytane, mackerel, polycyclic aromatic hydrocarbons, terpenes, steroids, etc.) was not obvious. Therefore, it is necessary to identify the components based on the relative content and characteristic ratio. In this study, the relative concentration and characteristic ratio data of fuel oil are also used to carry out fuzzy cluster analysis and the original fingerprint of fuel oil. The relative concentration distribution and characteristic ratio analysis are compared, and the fuzzy cluster analysis is suitable to select the relative concentration parameters. The relative concentrations of n-alkanes (phytane, prickenane, polycyclic aromatic hydrocarbons, terpenes, steroids) of single oil spill and mixed oil spill were analyzed by fuzzy cluster analysis. It makes the relationship between oil spill source and suspected oil sample "close and distant" clear at a glance, and can be used to identify oil spill source more intuitively and objectively.
【学位授予单位】：集美大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：O657.63;U698.7

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