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AbstractA pore-scale contamination model is developed to resolve the physicochemical processes in the anode catalyst layer for a deeper insight into the hydrogen sulfide (H2S) contamination mechanism. The present model is based on lattice Boltzmann method (LBM) and a novel iteration algorithm is coupled to overcome the time-scale issue in LBM which can extend its application. The microstructure of CL is stochastically reconstructed considering the presence of carbon, Pt, ionomer, and pores. The proposed model is validated by comparing the experimental data and can accurately predict the effect of H2S contamination on performance with time. The results show that the fuel cell performance is not sensitive to the anode Pt loading under the clean fuel condition as the hydrogen oxidation reaction is easy to activate. However, higher Pt loading can effectively prolong the operation time under the H2S contamination by providing a larger buffer reactive area and a lower H2S concentration condition. Furthermore, the H2S contamination in the fuel gas should be strictly restricted as it directly affects the poisoning rate and significantly affects the operation time. Graphical abstract Physicochemical processes in the ACL with reactant transport through micro porous layer (MPL) to active Pt sites