Air quality assessment in Beijing based on cloud model - Weidong Rao; Jialu Li; Hankun Guo (Scientific Reports)
Abstract This research employs the cloud model method to assess the outdoor air quality in Beijing over the past ten years. The study establishes standard and evaluation clouds for major air pollutants and constructs a comprehensive evaluation cloud model for the Air Quality Index (AQI) using aggregation functions and cloud model attributes. A novel normal cloud similarity measurement method based on the second-order Fréchet distance is adopted to conduct annual assessments. The core findings indicate a significant improvement in Beijing’s air quality, with the AQI showing a continuous downward trend from moderate pollution in 2014 to mild pollution in 2023. Specific pollutants such as $$PM_{10}$$ , $$PM_{2.5}$$ , and $$SO_2$$ have shown marked reductions, transitioning from good or light pollution levels to excellent ratings. The cloud model method effectively captures the probabilistic nature of pollutant concentrations, providing a more nuanced and rigorous assessment compared to traditional methods. These results validate the effectiveness and precision of the cloud model approach, offering actionable insights for environmental management and policy development.