Discrimination of Oil, Natural Water, and Wastewater Signals through Fluorescence Spectroscopy

Abstract

Rapid detection of oil content is crucial in regions with combined sewer systems, especially during flash floods when water quantity and quality fluctuations are significant. Current commercial UV fluorescence sensors for oil tracing are often unreliable due to interference from dissolved organic matter (DOM). This thesis project investigated the application of the fluorescence intensity ratio (FIR) and absorbance intensity ratio (AIR) methodologies for the detection and differentiation of oil contamination in water matrices. FIR is a method used to quantify the concentration of specific substances in a sample by comparing the fluorescence intensity at two different emission wavelengths following excitation at a specific wavelength ((λem1/λem2) λex). AIR is a proxy for the quantum yield which is the ratio of emitted photons to absorbed photons. Through a comprehensive analysis of the fluorescence and absorption spectra of different oil types and water samples, the FIR and AIR values were calculated and compared. A comparison was made with Iratio (λ335/λ325) λ242.5nm) and two commercially available oil sensors with accuracy in differentiating and detecting oil in natural water. The results demonstrated that the FIR, AIR, and Iratio methodologies offered improved differentiation between oil types and water matrices compared to the sensors. The findings also highlighted the challenges in detecting low concentrations of oil contamination in natural water and the difficulty of tracing cutting oil using FIR and AIR. However, the Iratio method demonstrated superior performance in detecting oil content in natural water. The FIR method showed improvement in differentiating the signals of oil, wastewater, and natural water. In conclusion, the recommended approach is to first use FIR to differentiate the water matrices, followed by Iratio to detect the oil content within the matrices. Further research and development are needed to increase the robustness and reliability of these methods, including benchmarking trials with optical setup and investigation of their application in different environmental conditions and with other contaminants. Overall, this study contributes to improved accuracy in differentiating fluorescence emissions arising from oils, wastewater, and natural water.