TAN Liju, ZHAO Ruxiang, YIN Xiaonan, ZHANG Haijiang, WANG Jiangtao. Establishment and application of an intelligent treating method for oil spill identification[J]. Acta Oceanologica Sinica, 2018, 37(11): 116-122. doi: 10.1007/s13131-018-1254-9
Citation: TAN Liju, ZHAO Ruxiang, YIN Xiaonan, ZHANG Haijiang, WANG Jiangtao. Establishment and application of an intelligent treating method for oil spill identification[J]. Acta Oceanologica Sinica, 2018, 37(11): 116-122. doi: 10.1007/s13131-018-1254-9

Establishment and application of an intelligent treating method for oil spill identification

doi: 10.1007/s13131-018-1254-9
  • Received Date: 2017-12-21
  • In the identifying process of an oil spill accident, manual integral and artificial visual comparison are commonly used at present to determine the oil spill sources, these methods are time-consuming and easily affected by human factors. Therefore, it is difficult to achieve the purpose of rapid identification of an oil spill accident. In this paper, an intelligent method of automatic recognition, integration and calculation of diagnostic ratio of Gas Chromatography-Mass Spectrometer (GC/MS) spectrum are established. Firstly, four hundreds of samples collected around the world were analyzed using a standard method and Retention time locking technology (RTL) was applied to reduce the change of retention time of GC/MS spectrum. Secondly, the automatic identification, integration of n-alkanes, biomarker compounds, polycyclic aromatic hydrocarbons and calculation of the diagnostic ratios were realized by MATLAB software. Finally, a database of oil fingerprints were established and applied successfully in a spill oil accident. Based on the new method and database, we could acquire the diagnostic ratios of an oil sample and find out the suspected oil within a few minutes. This method and database can improve the efficiency in spilled oil identification.
  • loading
  • Al-Kaabi N S, Kristensen M, Zouari N, et al. 2017. Source identification of beached oil at Al Zubarah, Northwestern Qatar. Journal of Petroleum Science and Engineering, 149:107-113, doi: 10.1016/j.petrol.2016.10.034
    Bayona J, Domínguez C, Albaigés J. 2015. Analytical developments for oil spill fingerprinting. Trends in Environmental Analytical Chemistry, 5:26-34, doi: 10.1016/j.teac.2015.01.004
    Christensen J H, Tomasl G, Hansen A B. 2005. Chemical fingerprinting of petroleum biomarkers using time warping and PCA. Environmental Science Technology, 39(1):255-260, doi: 10.1021/es049832d
    Dahlman G, Kienhuis P G M. 2016. Development and application of online computerized oil spill identification-COSIWeb. Standard Handbook Oil Spill Environmental Forensics (Second Edition), 729-745
    Daling P S, Faksness L G, Hansen A B, et al. 2002. Improved and standardized methodology for oil spill fingerprinting. Environmental Forensics, 3(3-4):263-278
    European Committee for Standardization. 2012. CEN/TR 15522-2 Oil spill identification-Waterborne petroleum and petroleum products-Part 2:Analytical methodology and interpretation of results based on GC-FID and GC-MS low resolution analyses. Brussels, Belgium:European Committee for Standardization
    General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China. 2007. GB/T 21247-2007 Specifications for identification system of spilled oils on the sea (in Chinese). Beijing:China Standard Press
    Qin Cuihong. 2015. Oil fingerprint digital identification methods of spilled oil. Energy Conservation & Environmental Protection in Transportation (in Chinese), (2):51-55
    Staniloae D, Petrescu B, Patroescu C. 2001. Pattern recognition based software for oil spills identification by gas-chromatography and IR spectrophotometry. Environmental Forensics, 2(4):363-366, doi: 10.1006/enfo.2001.0060
    Stouts S A, Uhler A D, McCarthy K J. 2001. A strategy and methodology for defensibly correlating spilled oil to source candidates. Environmental Forensics, 2(1):87-98, doi: 10.1006/enfo.2001.0027
    Sun Peiyan, Bao Mutai, Gao Zhenhui, et al. 2004. Identification of crude oil in Bohai Sea by gas chromatogram fingerprint. Periodical of Ocean University of China (in Chinese), 34(Sup.):23-26
    Sun Peiyan, Bao Mutai, Wang Xinping, et al. 2006. Existing state of spilled oil identification and oil fingerprint database construction at home and abroad. Journal of Xi'an Shiyou University (Natural Science Edition) (in Chinese), 21(5):72-75, 78
    Sun Peiyan, Wang Xinping, Zhou Qing, et al. 2012. Management system of fast analysis and identification of information visualization of oil fingerprint. Marine Environmental Science (in Chinese), 31(5):729-732
    Sun Peiyan, Zhao Yuhui, Cao Lixin, et al. 2011. Repeatability limit comparison method of diagnostic ratios in oil fingerprint identification. Marine Environmental Science (in Chinese), 30(1):110-113, 117
    Wang Zhendi. 2003. Fate and identification of spilled oils and petroleum products in the environment by GC-MS and GC-FID. Energy Source, 25(6):491-508, doi: 10.1080/00908310390195570
    Wang Zhendi, Fingas M. 1997. Developments in the analysis of petroleum hydrocarbons in oils, petroleum products and oil-spill-related environmental samples by gas chromatography. Journal of Chromatography A, 774(1-2):51-78
    Wang Zhendi, Fingas M, Lambert P, et al. 2004. Characterization and identification of the Detroit River mystery oil spill (2002). Chromatography, 1038(1-2):201-214
    Wang Zhendi, Fingas M, Lanadriault M, et al. 1995. Identification of alkylbenzenes and direct determination of BETX and BETX+C3-Benzenes in oils by GC/MS. Analytical Chemistry, 67(19):3491-3500, doi: 10.1021/ac00115a018
    Wang Zhendi, Fingas M, Lanadriault M, et al. 1999. Source identification of an unknown spilled oil from Quebec (1998) by unique biomarkers and diagnostic ratios of "Source-Specific Marker" Compounds. Environmental Technology, 20(8):851-862
    Wang Zhendi, Stout S. 2007. Oil Spill Environmental Forensics:Fingerprinting and Source Identification. Boston, MA:Academic Press, 344
    Xu Weichao. 2012. A review on correlation coefficients. Journal of Guangdong University of Technology (in Chinese), 29(3):12-17
    Yang Baijuan, Xu Xiaoqin, Li Qingling, et al. 2008. Application of oil spill identification by GCMS-A case study. Marine Environmental Science (in Chinese), 27(6):661-665, 670
    Zhang Haijiang, Wang Chuanyuan, Zhao Ruxiang, et al. 2016. New diagnostic ratios based on phenanthrenes and anthracenes for effective distinguishing heavy fuel oils from crude oils. Marine Pollution Bulletin, 106(1-2):58-61
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (521) PDF downloads(572) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return