Abstract:

Based on the air quality monitoring data in Liaoning province from 2015 to 2022, the Air Quality Composite Index (AQCI) was used as the characterization index to analyze the temporal variation of air quality, and the ArcGIS spatial autocorrelation tool was used to explore the spatial distribution characteristics of AQCI at different time scales. The results show that AQCI in Liaoning province shows a downtrend over the past 8 years, decreasing from 5.64 in 2015 to 3.55 in 2022. The excellent air quality rate steadily increased, with a 24.7% improvement in 2022 compared to 2015. The proportion of O₃, PM_2.5, and PM₁₀ as primary pollutants increased from 93.1% to 99.0%. The seasonal mean value of AQCI follows the distribution pattern of summer < autumn < spring < winter. The excellent air quality rate is highest in summer or autumn, followed by spring, and winter is lowest. The primary pollutants show seasonal fluctuations, with PM_2.5 and PM₁₀ being the main pollutants in spring, autumn, and winter, while O₃ pollution mainly occurs in summer. The monthly variation in AQCI is significant, which varies largely in different cities, with the highest values in January and the lowest values in July or August. The excellent air quality rate is lowest in January and highest in August. PM_2.5, PM₁₀, and O₃ account for more than 90% of the primary pollutants each month. The spatial aggregation characteristics of AQCI in Liaoning province are evident, with variations over time. The high-value aggregation characteristics of the central urban agglomeration are particularly significant.

Key words: Air Quality Composite Index(AQCI), Primary pollutants, Excellent air quality rate, Spatial autocorrelation