@article{YU2026, 
author = {Furong YU and Linzhen QU and Huawei YI and Yangyang CUI and Xulong ZHAO and Lijun ZHU and Yifeng XUE},
title = {Analysis of characteristics and causes of heavy air pollution in Shijingshan District, Beijing: evidence from three pollution episodes in 2024},
year = {2026},
journal = {Journal of Capital Normal University (Natural Science Edition)},
volume = {47},
number = {3},
pages = {127-136},
keywords = {heavy air pollution, HYSPLIT model, regional transport, meteorological conditions, vehicular emissions},
url = {https://www.sciopen.com/article/10.19789/j.1004-9398.2026.03.012},
doi = {10.19789/j.1004-9398.2026.03.012},
abstract = {Although air quality in Beijing has improved year by year, regional heavy air pollution episodes still occur in autumn and winter. Investigating the characteristics, influencing factors, and causes of such typical regional-scale heavy pollution events is of great significance for formulating differentiated control strategies. This study focuses on Shijingshan District and analyzes three heavy pollution episodes that occurred in 2024, comparing them with non-pollution periods. The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model was employed to calculate 72 h backward trajectories for source attribution, while real-time traffic flow monitoring was conducted on major local roads during the pollution episodes. In addition, meteorological factors such as wind speed and boundary layer height were analyzed to explore their correlations with pollutant concentrations. Results indicate that PM2.5 was the dominant pollutant, with the three heavy pollution episodes increasing the monthly mean concentration by 30.8%-44.1%. NO2 exhibited both pronounced evening peaks and stepwise declines, along with spatial variability. Regional transport pathways determined pollutant accumulation characteristics, with short-distance low-altitude transport contributing 77.0%. Wind speed and boundary layer height had significant dilution effects, showing stable negative correlations with NO2, whereas PM2.5 displayed stage-dependent relationships, reflecting uncertainties in the meteorological dilution effect. Although local vehicular emissions exerted some influence on air quality, they were not the dominant factor during heavy pollution episodes. Instead, regional pollutant accumulation, atmospheric transformation, and unfavorable dispersion conditions were identified as the main causes.}
}