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Most identification methods for marine oil spills rely on single-dimensional chemical fingerprinting that is ineffective for weathered oil. A quantitative identification method is proposed in this study based upon multi-dimensional chemical fingerprinting composed of diagnostic ratios, wavelet coefficient, and the Ni/V. Twenty oil samples were used including 6 marine fuels, 7 Middle Eastern crude oils, and 7 non-Middle East crude oils. Diagnostic ratios were discussed using partial least square analysis, and fluorescence spectra were analyzed by db7 wavelet basis of 6-layers in the discrete wavelet transform. The first principal component and the wavelet coefficient at 354 ± 2 nm were combined with Ni/V and optimized by an exhaustive method as variables to establish the Fisher discriminant model. The developed model had 100% accuracy for modeled oil samples and for non-modeled crude oil before and after weathering, respectively, with 83.3% accuracy for non-modeled or short-term weathered marine fuel. The accuracy was 3% higher than reported in the literature. [ABSTRACT FROM AUTHOR]