Spatial-temporal analysis and projection of extreme particulate matter (PM10 and PM2.5) levels using association rules: A case study of the Jing-Jin-Ji region, China

The Jing-Jin-Ji region of Northern China has experienced serious extreme PM concentrations, which could exert considerable negative impacts on human health. However, only small studies have focused on extreme PM concentrations. Therefore, joint regional PM research and air pollution control has become an urgent issue in this region. To characterize PM pollution, PM10 and PM2.5 hourly samples were collected from 13 cities in Jing-Jin-Ji region for one year. This study initially analyzed extreme PM data using the Apriori algorithm to mine quantitative association rules in PM spatial and temporal variations and intercity influences. The results indicate that 1) the association rules of intercity PM are distinctive, and do not completely rely on their spatial distributions; 2) extreme PM concentrations frequently occur in southern cities, presenting stronger spatial and temporal associations than in northern cities; 3) the strength of the spatial and temporal associations of intercity PM2.5 are more substantial than those of intercity PM10. •The extreme PM level over Jing-Jin-Ji region of China was investigated.•Spatial and temporal associations of intercity PM were mined using Apriori algorithm.•Cross spatial and temporal associations of PM10 and PM2.5 were also mined.•Extreme PM frequency and intercity association strength was quantitatively estimated.