## 1 Introduction  
In recent years, oil spills have occurred frequently, causing enormous damage to the marine environment and the socio-economy. Therefore, it is of considerable significance for emergency treatment of oil spill accidents to quickly determine the source and total amount of oil spills by using accurate qualitative and quantitative analysis. However, the oil components and their changes are complicated. The ability to promptly discriminate oil species and determine the oil concentrations in seawater accordingly is a critical issue for current research.  
At present, conventional methods to achieve this include gas chromatography-mass spectroscopy (GC-MS), gas chromatography-flame ionization detection (GC-FID), and so on [1; 2; 3; 4; 5; 6]. With the advantages of high sensitivity, good selectivity, and high analytical efficiency, these methods have been considered as the most reliable methods for oil spill analysis. However, these instruments are expensive, and the pre-treatment of samples is complicated. Therefore, the above techniques are challenging to use to meet online monitoring requirements.  
Due to the presence of polycyclic aromatic compounds in petroleum, most petroleum can emit fluorescence. Fluorescence detection technologies can be applied to oil monitoring. The main fluorescence methods include Synchronization Fluorescence Spectrum (SFS) [7; 8; 9], Excitation EmissionMatrix (EEM) [10], and Time-Resolved Fluorescence (TRF) [11; 12]. Some researchers studied the rapid measurement of oil concentration in water by using three-dimensional fluorescence spectroscopy and PARAFAC algorithm with the interference of a variation of dissolved organic matter [13]. The fluorescence and light scattering combined with artificial neural networks were used to quickly determine the total oil concentration in water [14]. Fluorescence spectroscopy does not destroy the sample structure and does not require pretreatment of the sample. The measurement process is convenient and has high sensitivity and accuracy.  
Fluorescence intensity is liner with oil concentration in water only when the sample concentration is low. Therefore, conventional fluorescence technology can be used to dilute the sample to a linear concentration range for measurement. However, oils contain a variety of Polycyclic Aromatic Hydrocarbons (PAHs) components. When the oil concentration is high, the lower ring PAHs will produce fluorescence quenching, resulting in the remaining fluorescent information only representing the higher ring PAHs. Some researchers have found a phenomenon where the spectra are reliant on the concentration of multi-PAHs, which was called \"red-shift behavior\" [15; 16]. Thus, fluorescence spectra of one certain concentration level are difficult to use to fully represent the fluorescence characteristics of oil samples. It is hard to judge whether the oil concentration or the oil species causes a change in spectral shape.  
To address this problem, a three-dimension concentration-emission matrix (CEM) spectrum was constructed by obtaining the fluorescence emission spectra at 10 series of concentrations. The CEM has been interpolated in the concentration interval and the spectral matrix of the test samples or weathering samples are compared to the database of interpolated CEM generated above. The maximum similarity coefficient (more than 0.9) means the closest matching species and the corresponding concentrations are the concentration of the sample. The quantitative results were evaluated based on recovery rate and relative error of prediction.