Spatiotemporal Variation and Coupling Relationship Between Air Quality and Environment-Urban-Economy-Associated Factors: A Case Study of 31 Provinces in China During 2015~2022

In this study, global spatial autocorrelation, local spatial autocorrelation, Spearman correlation analysis, gray correlation analysis, entropy weight method, and the gravity model were used to analyze the spatiotemporal variation and environment-urban-economy-associated factors of air quality of 31 provinces in China during 2015~2022. From 2015 to 2022, the Air Quality Index (AQI) exhibited a downward trend in 30 out of 31 Chinese provinces, with the exception of Shaanxi Province. Concurrently, the annual average concentrations of PM 2.5 , PM 10 , SO 2 , NO 2 , and CO declined across the study period. High-high clusters and low-high outliers were observed in northern China, whereas low-low clusters and high-low outliers were distributed in southern China. Twelve provinces (38.7%) showed positive correlation (0.095~0.95), 18 provinces (58.1%) showed negative correlation (−0.76~0.095), and only Anhui showed no correlation between AQI and O 3 . The comprehensive AQI quality presented a dual-core model in Sichuan (in the southwest) and Henan (in the central part) of China, while the comprehensive AQI improvement rate presented a single-core model in Jiangsu in the east of China. The gravity models incorporating AQI and GDP revealed that both air quality and economic performance improved over the study period. The spatial pattern of pollution evolved from a multi-core structure to a non-core structure, whereas the pattern of economic growth transitioned from a non-core structure to a dual-core structure, with the Beijing-Tianjin-Hebei region and the Yangtze River Delta emerging as the primary urban agglomerations.