Ultrasound-assisted oxidative desulfurization of RFCC diesel: process intensification and statistical optimization

Abstract Ultrasound-assisted oxidative desulfurization (ODS) of real residue fluid catalytic cracking (RFCC) diesel fuel was investigated using a commercial Co–Mo/Al 2 O 3 hydrotreating catalyst in the presence of hydrogen peroxide and acetic acid. The study focused on process intensification and statistical optimization rather than catalyst development. A definitive screening design was first employed to identify the most influential operational parameters affecting sulfur removal efficiency. Reaction temperature, catalyst concentration, and ultrasonic power were found to be the dominant factors, while oxidant amount, acetic acid concentration, and reaction time showed no statistically significant effect within the investigated range. Subsequently, response surface methodology was applied to model and optimize the process. The developed quadratic model exhibited good predictive capability (R 2 = 0.93; R 2 adj = 0.90), with temperature showing the strongest individual effect ( p = 0.0024), followed by significant interaction effects between catalyst concentration and temperature, and ultrasonic power and temperature. Under the optimal experimental conditions (5 g catalyst/100 mL, 112.5 V ultrasound power, 30 °C), a maximum sulfur removal of 53 % was achieved within 20 min. The response surface analysis indicated a saddle-type stationary point, suggesting that higher desulfurization efficiencies may be attainable outside the studied domain. These findings demonstrate the feasibility of combining ultrasound with oxidative treatment for sulfur reduction in real diesel feedstocks and highlight the importance of operational parameter optimization in enhancing ODS performance.