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Numerical models have been developed to elucidate air pollution caused by sulfate aerosols (SO 4 2- ). However, typical models generally underestimate SO 4 2- , and oxidation processes have not been validated. This study improves the modeling of SO 4 2- formation processes using the mass-independent oxygen isotopic composition [ 17 O-excess; Δ 17 O(SO 4 2- )], which reflects pathways from sulfur dioxide (SO 2 ) to SO 4 2- , at the background site in Japan throughout 2015. The standard setting in the Community Multiscale Air Quality (CMAQ) model captured SO 4 2- concentration, whereas Δ 17 O(SO 4 2- ) was underestimated, suggesting that oxidation processes were not correctly represented. The dust inline calculation improved Δ 17 O(SO 4 2- ) because dust-derived increases in cloud-water pH promoted acidity-driven SO 4 2- production, but Δ 17 O(SO 4 2- ) was still overestimated during winter as a result. Increasing solubilities of the transition-metal ions, such as iron, which are a highly uncertain modeling parameter, decreased the overestimated Δ 17 O(SO 4 2- ) in winter. Thus, dust and high metal solubility are essential factors for SO 4 2- formation in the region downstream of China. It was estimated that the remaining mismatch of Δ 17 O(SO 4 2- ) between the observation and model can be explained by the proposed SO 4 2- formation mechanisms in Chinese pollution. These accurately modeled SO 4 2- formation mechanisms validated by Δ 17 O(SO 4 2- ) will contribute to emission regulation strategies required for better air quality and precise climate change predictions over East Asia.