Amirkabir University of Technology Advances in Energy Sciences and Technologies 3115-9117 1 1 2025 06 01 SARA fraction measurements of Persian Gulf crude oil using LIF spectroscopy based on analysis of variance (ANOVA) 21 27 5747 10.22060/aest.2025.5747 EN Fatemeh Ahmadinouri Department of Energy Engineering and Physics, Amirkabir University of Technology (Tehran Polytechnic), P.O. Box 15875-4413, Tehran, Iran 0000-0001-7185-2479 Parviz Parvin a Department of Energy Engineering and Physics, Amirkabir University of Technology (Tehran Polytechnic), P.O. Box 15875-4413, Tehran, Iran Ahmad Reza Rabbani Petroleum Engineering Department, Amirkabir University of Technology (Tehran Polytechnic), P.O. Box 15875-4413, Tehran, Iran. Journal Article 2025 12 17 Crude oil is typically categorized into four main fractions: saturates, aromatics, resins, and asphaltenes, collectively referred to as SARA. To enable the rapid identification of these fractions, a novel on-site approach is introduced based on laser-induced fluorescence (LIF) spectroscopy. This method utilizes both the solvent (with dichloromethane, DCM) densitometry and quantum efficiency as key analytical parameters. Several crude oil samples are analyzed from different oilfields in the Persian Gulf, with optical parameters of interest i.e., peak concentration (<em>C_p</em>) and quantum efficiency (<em>Q_E</em>) giving by the experimental data. The relation between these parameters and crude oil fractions is attested through analysis of variance (ANOVA). Then, the predictive statistical models are developed to estimate the values of the crude oil fractions. The findings demonstrate that these predictive models exhibit high accuracy compared to the standard methods (ASTM D 6560 & ASTM D 4124). In fact, the proposed technique significantly reduces the testing time to less than 30 minutes. https://aest.aut.ac.ir/article_5747_56d326d8139f904b679084778f1b3285.pdf