Abstract
Abstract. Complex interaction between emissions, meteorology and atmospheric chemistry makes accurate predictions of particulate pollution difficult. Advanced data mining techniques can dig out potential laws from massive data, providing new possibilities for understanding the evolution and causes of particulate pollution. Based on the Granger method and block modeling analysis, this study explored the spillover effects of hourly PM2.5 to determine the specific role (i.e., overflow, bilateral, inflow and limited inflow) of each city in Hubei, China. The results suggest that the northern and central cities with high level PM concentration in Hubei have a significant spillover effect, while the eastern and southern cities generally play a role as the sink of pollutant.
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