Abstract. Atmospheric processing of mineral aerosols by acid gases (e.g., SO2, HNO3, N2O5, and HCl) may play a key role in the transformation of insoluble iron (Fe in the oxidized or ferric (III) form) to soluble forms (e.g., Fe(II), inorganic soluble species of Fe(III), and organic complexes of iron). On the other hand, mineral dust particles have a potential of neutralizing the acidic species due to the alkaline buffer ability of carbonate minerals (e.g., CaCO3 and MgCO3). Here we demonstrate the impact of dust alkalinity on the acid mobilization of iron in a three-dimensional aerosol chemistry transport model that includes a mineral dissolution scheme. In our model simulations, most of the alkaline dust minerals cannot be entirely consumed by inorganic acids during the transport across the North Pacific Ocean. As a result, the inclusion of alkaline compounds in aqueous chemistry substantially limits the iron dissolution during the long-range transport to the North Pacific Ocean: only a small fraction of iron (<0.2%) dissolves from hematite in the coarse-mode dust aerosols with 0.45% soluble iron initially. On the other hand, a significant fraction of iron (1–2%) dissolves in the fine-mode dust aerosols due to the acid mobilization of the iron-containing minerals externally mixed with carbonate minerals. Consequently, the model quantitatively reproduces higher iron solubility in smaller particles as suggested by measurements over the Pacific Ocean. It implies that the buffering effect of alkaline content in dust aerosols might help to explain the inverse relationship between aerosol iron solubility and particle size. We also demonstrate that the iron solubility is sensitive to the chemical specification of iron-containing minerals in dust. Compared with the dust sources, soluble iron from combustion sources contributes to a relatively marginal effect for deposition of soluble iron over the North Pacific Ocean during springtime. Our results suggest that more comprehensive data for chemical specificity of iron-rich dust is needed to improve the predictive capability for size-segregated soluble iron particles.