As the fast development of offshore oil exploitation and maritime transportation, oil spill events caused by leakages from platforms and collisions of ships frequently occurred and negatively affected maritime transportation and ocean environment (Fingas and Brown, 2013a; Alves et al., 2016). With the awareness of the destructive impacts of oil spills, the detection and prevention of oil spill events have become an important and interdisciplinary topic. Thanks to the international cooperation on the oil spill prevention and response, such as the International Convention on Oil Pollution Preparedness, Response, and Co-operation (OPRC), the number of large oil spill events has significantly decreased in the past few decades. However, medium and small oil spill events (from 7 to 700 ton) still occurred frequently and endangered ocean environment (ITOPE, 2021). Besides the collisions of ships, medium and small oil spill events could also be caused by load, unload, ballast, fuel charging, tank cleaning, and various maritime activities. Refined oil, such as diesel, gasoline, and lubricant, are commonly witnessed in medium and small oil spill events (Loh et al., 2021).
Oil types identification is a fine-grained classification problem that can help determine the source of leakage and the plan for responses. Chemical methods, such as chromatographic/mass spectroscopic analysis on oil samples (Texeira et al., 2014; Bayona et al., 2015), and “oil spill fingerprint” methods (Christensen and Tomasi, 2016; Liu et al., 2017; Boehmer- Christiansen, 2008) can provide accurate inferences on oil spill types. However, these methods usually require in situ sampling and large analytical equipment. Thus, they could be time-consuming, and usually not fit for medium and small oil spill events. It is necessary to develop a fast and accurate method for oil types identification in medium and small oil spill events.
Almost all types of petroleum hydrocarbons (PHCs) have unique fluorometric characteristics, which can be used for PHC identification on soil, sea water, ice, and other complicated background (Fingas and Brown, 2013b; Araújo et al., 2021). Therefore, laser-induced fluorescence (LIF) is an effective, all-weather oil spill identification method that has been widely applied for oil spill monitoring (Hou et al., 2017, 2019). Although LIF could effectively identify the present of oil pollutants, it is difficult to provide fine-grained classification between various types of oil that have similar fluorometric spectra. In order to solve this problem, Chekalyuk and Hafez (2013) proposed an “Advanced Laser Fluorometry” (ALF) method by using laser with multiple excitation wavelengths. However, both LIF and ALF methods overlooked the selection of excitation wavelengths: they usually determine the excitation wavelength based on laser frequency doubling of the equipment or excitation efficiency of the material (Brown and Fingas, 2003). Distinguishability is seldom considered while selecting excitation wavelength. In order to have a comprehensive understanding on the characteristics of LIF, researchers combined the fluorometric spectra under different excitation wavelengths and formed excitation-emission matrix (EEM) (Baszanowska and Otremba). EEM introduces additional information in the dimension of excitation wavelength, and thus potentially improves the accuracy of oil types identification (Christensen et al., 2005). However, the measurements of EEM are also costly, time-consuming, and difficult to applied in real situation (especially for medium and small oil spill event) (Hou et al., 2017).
Considering the limitations in the previous works on LIF and EEM, this study is intended to compare the distinguishability of fluorometric spectra under various excitation wavelengths on some typical refine oil samples, and find the optimal excitation wavelength for oil types identification using LIF. By examining and analysing EEMs of different oil types, this study is expected to improve the ability of oil spill classification using LIF method without increasing time or other cost. Furthermore, this study is expected to provide theoretical basis for the development of portable LIF devices for oil spill identification.