Dust storms have a profound impact on air quality, atmospheric chemistry, and human well-being by carrying vast amounts of particles over distances of thousands of kilometers. However, the overall characteristics of these dust events and their influence on secondary pollution in the northern China region are not yet well understood, due to a lack of long-term, comprehensive observations and objective identification techniques. Based on principal component analysis combined with high-time-resolution observations of particulate matter components, here we developed a robust method to identify dust storm events and identified 14 dust events in Beijing in 2019. We further classified these 14 events into two distinct types using Lagrangian particle dispersion models and backward trajectory analysis. The first type (Type I, 9 cases) is characterized by synoptic patterns in Mongolia, originating from the north and directly impacting the Beijing area. The second type (Type II, 5 cases) involves air masses from the north or northwest that temporarily pass through polluted regions south of Beijing before being carried back into the city. Consistently, during Type I dust events, we observed a sharp decrease in secondary inorganic aerosols (SIA) from 65 % to 7 %, as well as in the sulfur oxidation ratio (SOR) and nitrogen oxidation ratio (NOR) (from 0.52 to 0.19, and 0.27 to 0.018 respectively). In contrast, during Type II dust events, SIA concentrations increased by 91 %, along with an increase in SOR (1.7 %), NOR (69 %), and f44/f43 (3.0 %), suggesting an enhancement of secondary aerosol formation resulting from the interaction between dust aerosols and gaseous anthropogenic pollutants. Our results demonstrate that dust events and the sub-type of dust events can be identified in an objective manner using the protocol developed in this study and the dynamics should be considered when discussing impacts of dust events on atmospheric chemistry.
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