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Severe haze events have many adverse effects on agricultural production and human activity. Haze events are often associated with specific patterns of atmospheric circulation. Therefore, studying the relationship between atmospheric circulation and haze is particularly important for early warning and forecasting of urban haze events. In order to study the relationship between multi-scale atmospheric circulation and severe haze events in autumn and winter in Shanghai, China, we used a T-mode objective classification method to classify autumn and winter atmospheric circulation patterns into six types based on sea level pressure data from 2007 to 2016 in the Shanghai area. For the period between September 2016 and February 2017, we used the Allwine–Whiteman method to classify the local wind in Shanghai into three categories: stagnation, recirculation, and ventilation. By further studying the PM2.5 concentration distribution, visibility distribution, and other meteorological characteristics of each circulation type (CT) and local wind field type, we found that the Shanghai area is most prone to severe haze when exposed to certain circulation patterns (CT1, CT2, and CT4), mainly associated to the cold air activity and the displacement of the high pressure system relative to Shanghai. We also found that the local wind fields in the Shanghai area are dominated by recirculation and stagnation events. These conclusions were further verified by studying a typical pollution process in Shanghai in November 2016 and the pollutant diffusion path using the HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory model) simulation model.

The issue of air pollution has attracted more and more attention. Understanding how to predict air quality based on weather conditions has strong practical significance. For the first time, this paper combines weather circulation with climate prediction models to explore long-term air quality predictions. Using the T-mode (time realizations in columns) objective circulation classification method, we classified the weather circulation affecting Beijing, China, according to nine categories of predominant weather conditions. PM2.5, NO2, SO2, and CO concentration distributions for these nine circulation patterns were also determined. When the Beijing area was controlled by northwestern low pressure, a high-pressure rear, or a weak pressure field, the PM2.5 concentrations were higher, while high-pressure systems and a high-pressure rear were mostly associated with relatively high NO2, SO2, and CO concentrations. The concentrations of these pollutants under high-pressure fronts and northwestern high-pressure settings were low. Using the FLEXPART-WRF model to simulate the 48 h backward trajectory of the highest PM2.5 concentration under the nine circulation patterns from 2015 to 2021, we obtained the trap time of pollutants per unit concentration (imprint analysis) and determined the particle trap area under each circulation pattern. When using the EC-Earth climate prediction model, the daily circulation field during the Beijing Winter Olympics was forecasted, and the nine circulation patterns were compared. The corresponding circulation pattern in Beijing during the 2022 Winter Olympics should be conducive to the diffusion of pollutants and, therefore, the air quality is expected to be good.

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