Spatio-temporal characteristics and convergence trends of PM2.5 pollution: A case study of cities of air pollution transmission channel in Beijing-Tianjin-Hebei region, China

Abstract Air pollution prevention and control of cities of “air pollution transmission channel in Beijing-Tianjin-Hebei area” (hereafter “2 + 26” cities) is of great significance to ensure the achievement of the goal of “defending the blue sky”. Based on the monitoring real-time data for PM2.5 concentrations for the period of 2015–2018, this research in the first stage applied kernel density estimation analysis, empirical orthogonal function analysis, centroid shift and spatial autocorrelation analysis to investigate the spatio-temporal characteristics of PM2.5 concentrations of the “2 + 26” cities. In the second stage, it employed spatial econometric models to examine the convergence of PM2.5 concentrations across cities. The findings are as follows. (1) Yearly average PM2.5 concentrations of the “2 + 26” cities were reduced substantially. Moreover, they presented seasonal variation patterns, with a peak in winter and a nadir in summer. (2) The results of the centroid shifts revealed that the pollution centroid of the entire region was located in the borders between Xingtai and Handan. Besides, it moved towards southwest. (3) PM2.5 concentrations exhibited positive spatial autocorrelation. (4) The developments of the standard deviation and the estimated kernel density distributions showed that there existed σ convergence. The results of the spatial β convergence models showed that it had both absolute and conditional β convergence. In addition, the convergence speed in winter was slower than that in the other seasons. (5) To conclude, greater efforts and stricter measures to control air pollution of the “2 + 26” cities notably in winter should be strengthened and reinforced.