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Rapid fingerprinting technology of heavy oil spill by mid-infrared spectroscopy.
Zhang, Lujun; Huang, Xiaodong; Fan, Xinmin; He, Weidong; Yang, Chun; Wang, Chunyan.
Afiliação
  • Zhang L; Department of Physics and Optoelectronic Engineering, Weifang University, Weifang, People's Republic of China.
  • Huang X; Department of Physics and Optoelectronic Engineering, Weifang University, Weifang, People's Republic of China.
  • Fan X; Department of Physics and Optoelectronic Engineering, Weifang University, Weifang, People's Republic of China.
  • He W; Department of Physics and Optoelectronic Engineering, Weifang University, Weifang, People's Republic of China.
  • Yang C; Emergencies Science and Technology Section, Science and Technology Branch, Environment Canada, Ottawa, Canada.
  • Wang C; Department of Physics and Optoelectronic Engineering, Weifang University, Weifang, People's Republic of China.
Environ Technol ; 42(2): 270-278, 2021 Jan.
Article em En | MEDLINE | ID: mdl-31169447
With the increase of unconventional oil production and transportation, the detection methods of light crude oil have been challenged. Mid-Infrared spectroscopy can reflect the functional group of the oil related samples, which has strong absorption signals with distinguishable peaks featured as a fast, economy, and robust technique. Nevertheless, the previous study and application of oil relevant samples, such as petroleum chemical industry online monitoring, are mainly based on Near-infrared spectroscopy. Recently, the rapid development of the spectral instrument manufacturing and the data analysis methods provides a more comprehensive technical support for the rapid and accurate identification of marine oil spill by Mid-infrared spectroscopy. In this paper, 10 crude oil samples were selected for infrared spectroscopy detection, and the results were analysed and compared with those of gas chromatography flame ionization detection method. The character information of the IR spectra and GC/FID chromatograms were extracted and classified both by principal component analysis and partial least squares regression. Under the condition of small sample size, the recognition accuracy was up to 100%. The results show that the mid-infrared method combined with chemometrics can be expected to achieve rapid, accurate and economical identification of heavy oil species.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Petróleo / Poluição por Petróleo Idioma: En Revista: Environ Technol Assunto da revista: SAUDE AMBIENTAL / TOXICOLOGIA Ano de publicação: 2021 Tipo de documento: Article País de publicação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Petróleo / Poluição por Petróleo Idioma: En Revista: Environ Technol Assunto da revista: SAUDE AMBIENTAL / TOXICOLOGIA Ano de publicação: 2021 Tipo de documento: Article País de publicação: Reino Unido