This study explored the temporal and spatial variation in PM2.5 concentration and its relationship with the vegetation landscape pattern in three typical economic zones in China, which is of great significance for regional PM2.5pollution control and atmospheric environmental protection. In this study, the pixel binary model, Getis-Ord Gi* analysis, Theil-Sen Median analysis, Mann-Kendall significance test, Pearson correlation analysis, and multiple correlation analysis were used to explore the spatial cluster and spatio-temporal variation in PM2.5 and its correlation with the vegetation landscape index in the three economic zones of China on the basis of PM2.5 concentration data and MODIS NDVI data set. The results showed that PM2.5 in the Bohai Economic Rim was mainly dominated by the expansion of hot spots and the reduction in cold spots from 2000 to 2020. The proportion of cold spots and hot spots in the Yangtze River Delta showed insignificant changes. Both cold and hot spots in the Pearl River Delta had expanded. PM2.5 showed a downward trend in the three major economic zones from 2000 to 2020, and the magnitudes of increasing rates were higher in the Pearl River Delta, followed by those in the Yangtze River Delta and Bohai Economic Rim. From 2000 to 2020, PM2.5 exhibited a downward trend in the context of all vegetation coverage grades, and PM2.5 had most significantly improved within extremely low vegetation coverage in the three economic zones. On the landscape scale, PM2.5 values were mostly correlated with aggregation index in the Bohai Economic Rim, with the largest patch index in the Yangtze River Delta and Shannon's diversity in the Pearl River Delta, respectively. Under the context of different vegetation coverage levels, PM2.5showed the highest correlation with aggregation index in the Bohai Economic Rim, landscape shape index in the Yangtze River Delta, and percent of landscape in the Pearl River Delta, respectively. PM2.5 showed significant differences with vegetation landscape indices in the three economic zones. The combined effect of multiple vegetation landscape pattern indices on PM2.5 was stronger than that of the single vegetation landscape pattern index. The above results indicated that the spatial cluster of PM2.5 in the three major economic zones had changed, and PM2.5 showed a decreasing trend in the three economic zones during the study period. The relationship between PM2.5 and vegetation landscape indices exhibited obvious spatial heterogeneity in the three economic zones.
Keywords: Getis-Ord Gi* analysis; PM2.5; spatio-temporal variation; typical economic zone; vegetation landscape pattern.