Identification and Determination of Oil Pollutants Based on 3-D Fluorescence Spectrum Combined with Self-weighted Alternating Trilinear Decomposition Algorithm

Abstract

Oil pollution seriously endangers the biological environment and human health. Due to the diversity of oils and the complexity of oil composition, it is of great significance to identify the oil contaminants. The 3-D fluorescence spectrum combined with a second order correction algorithm was adopted to measure an oil mixture with overlapped fluorescence spectra. The self-weighted alternating trilinear decomposition (SWATLD) is a kind of second order correction, which has developed rapidly in recent years. Micellar solutions of #0 diesel, #93 gasoline and ordinary kerosene in different concentrations were made up. The 3-D fluorescence spectra of the mixed oil solutions were measured by a FLS920 fluorescence spectrometer. The SWATLD algorithm was applied to decompose the spectrum data. The predict concentration and recovery rate obtained by the experiment show that the SWATLD algorithm has advantages of insensitivity to component number and high resolution for mixed oils.

Rapid Investigation of Oil Pollution in Water-Combined Induced Fluorescence and Random Sample Consensus Algorithm

“…During the measurement process of lower mass concentration solutions, the fluorescence intensity measured by the system demonstrates a linear relationship with the mass concentration of the solution, given by the equation [30] as follows:…”