The complexity of pH effects in this model system arises from multiple interacting factors, including pH-dependent thermodynamics and reaction kinetics of multiple steps, and pHdependent LRE effects. This situation has motivated us to build a hierarchical model in an incremental manner allowing different factors that control the overall pH effect to be disentangled. Our analysis began with exclusive consideration of the microkinetics in perchlorate solutions, in which the specific adsorption of electrolyte anions can be avoided. Based on this L2 modeling, we obtained the intrinsic activity-pH relation without accounting for the LRE. As shown in Figure , the intrinsic activity-pH relation is bell-shaped with a peak at pH = 6, which is inconsistent with the observed trapezoidal shape. We then added mass transport effects to the model, namely, modeling on the L3. Figure indicates that the pH at the reaction plane (pHRP) is much lower than the pH in the bulk solution (pHbulk), as the FAOR generates protons. Moreover, the pHRP remains almost constant at pHRP = 4 in the range of 5 < pHbulk <11. This local pH shift induces a transformation of the activity-pH relation from bell shape to trapezoidal shape, yielding qualitative agreement with the experimental trend (Figure ). For the activity-pH relation in phosphate solution, there are two additional electrolyte effects, i.e., the buffering effect and the specific adsorption of phosphate anions. By incorporating both effects, we captured the experimental trends in phosphate solution with the activity being lower than that in perchlorate solution and the activity-pH relation being bell-shaped (Figure ). Furthermore, the site-blocking effect of the specific adsorption of phosphate anions was revealed to be the determining factor.