Research on identification of air pollutants in 105 key development cities in China based on K-Means clustering
Employing the K-Means clustering method to explore the sources and distribution characteristics of air pollutant emissions in 105 key development cities in China under the effect of seasons.The results indicate that there are significant differences in the distribution of air pollutants and the main pollutants affecting air quality in various cities across different seasons,with the most severe air pollution occurring in spring and winter.The findings of this study are of great significance for environmental protection departments to enhance the environment and for residents in different regions to protect themselves.
air pollutantsair qualityseasonal effectK-Means clustering