| Literature DB >> 34767127 |
Ming Xie1, Yunpeng Jia1, Ying Li2, Xiaohua Cai1, Kai Cao1.
Abstract
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.Entities:
Keywords: Fine-grained classification; Fluorometric spectra analysis; Laser-induced fluorescence; Oil spill; Oil types classification
Year: 2021 PMID: 34767127 DOI: 10.1007/s10895-021-02849-3
Source DB: PubMed Journal: J Fluoresc ISSN: 1053-0509 Impact factor: 2.217