A Streamlined Mathematical Approach for Estimating H2S Removal Kinetics in Zinc Oxide Packed Beds from Industrial Data

نویسندگان

1 Department of Process Engineering, Shiraz Petrochemical Complex, Shiraz, I.R. IRAN

2 Department of Chemical Engineering, School of Engineering, Yasouj University, Yasouj, I.R. IRAN

doi
10.30492/ijcce.2025.2056047.7052
چکیده

Sulfur compounds, especially hydrogen sulfide, are well-known catalyst poisons in steam reforming processes as they reduce catalytic activity, accelerate carbon deposition, and increase the risk of overheating in reformer tubes. Implementing a kinetic model based on real industrial operating conditions enables a more accurate prediction of the desulfurization process. For this purpose, the present study aims to develop a detailed and streamlined kinetic model for H2S adsorption on zinc oxide under industrial operating conditions. Process datasets were collected over a 44-month operational period in a fixed-bed reactor. Kinetic behavior was evaluated using the unreacted shrinking core, grain, and random pore models, while catalyst deactivation effects were incorporated into the H2S adsorption kinetic analysis. To simplify the modeling process while accounting for catalyst decay, a kinetic modeling strategy was employed that directly integrates the relevant reaction kinetics into the deactivation behavior. The obtained results showed that the random pore model adequately describes the adsorption of hydrogen sulfide on zinc oxide, and that the intrinsic and apparent reaction rates of H2S removal exhibit a first-order dependence on the H2S concentration. Our analysis determined the activation energies for the reaction and catalyst decay were 22.528 and 36.780 kJ/mol, respectively. Besides, the kinetic reaction rate constant at 375°C and the Redlich-Peterson isotherm constant were 0.325 1/s and 0.0015 1/s, respectively. Additionally, the frequency factor for the reaction was estimated as 0.00495 1/s, and the deactivation rate constant was found to be 0.0432 1/h. The breakthrough curve generated using the kinetic parameters of the random pore model showed good compatibility with the measured process data. These findings enhance process reliability by mitigating catalyst deactivation and thermal risks associated with sulfur breakthrough. They provide valuable insights for optimizing sulfur removal strategies and extending catalyst life in industrial reforming operations.