Experimental Analysis on the Optimal Excitation Wavelength for Fine-Grained Identification of Refined Oil Pollutants on Water Surface Based on Laser-Induced Fluorescence

• Published in: Journal of fluorescence Vol. 32; no. 1; pp. 257 - 265
• Main Authors: Xie, Ming, Jia, Yunpeng, Li, Ying, Cai, Xiaohua, Cao, Kai
• Format: Journal Article
• Language: English
• Published: New York Springer US 2022; Springer Nature B.V
• Subjects: Analytical Chemistry; Biochemistry; Biological and Medical Physics; Biomedical and Life Sciences; Biomedicine; Biophysics; Biotechnology; Excitation; Excitation spectra; Identification methods; Laser induced fluorescence; Oil spills; Original Article; Pollutants; Portable equipment; Wavelengths; Oil spill; Laser-induced fluorescence; Oil types classification; Fluorometric spectra analysis; Fine-grained classification
• ISSN: 1053-0509; 1573-4994
• DOI: 10.1007/s10895-021-02849-3

Laser-induced fluorescence (LIF) is an effective and all-weather oil spill identification method that has been widely applied for oil spill monitoring. However, the distinguishability on oil types was seldom considered while selecting the excitation wavelengths. This study is intended to find the optimal excitation wavelength for fine-grained classification of refined oil pollutants using LIF by comparing the distinguishability of fluorometric spectra under various excitation wavelengths on some typical types of refined oil samples. The results show that the fluorometric spectra of oil samples significantly vary under different excitation wavelengths, and the four types of oil applied in this study are most likely to be distinguished under the excitation wavelengths of 395 nm and 420 nm. This study is expected to improve the ability of oil types identification using LIF method without increasing time or other cost, and also provide theoretical basis for the development of portable LIF devices for oil spill types identification.