Abstract
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.