Abstract: This study utilized atmospheric environmental monitoring data and routine meteorological data in Mudanjiang,Heilongjiang province from 2014 to 2023,as well as global data assimilation system (GDAS) data provided by the National Centers for Environmental Prediction in the United States,to analyze the characteristics of six major atmospheric pollutants and investigate the correlation between meteorological elements and PM_2.5 concentration.By combining methods such as the Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT),Potential Source Contribution Function (PSCF),and Concentration Weighted Trajectory (CWT),the transport paths and contribution sources of PM_2.5 during typical heavy air pollution periods were studied.The results showed that among the pollution events in Mudanjiang over the past 10 years,days with excessive PM_2.5 concentration ocurred most frequently,making it the primary pollutant affecting the atmospheric environment quality.Particularly,from 2014 to 2017,PM_2.5 pollution occurred frequently,lasted for a long time,and was usually severe.Backward trajectory analysis indicated that the transport paths of PM_2.5 pollution in the west and southwest directions had a significant impact on atmospheric pollution in Mudanjiang.In the transport trajectories of typical heavy pollution events,long-distance trajectories accounted for 34.33%,with representing regions including the Mongolian Plateau and southern Siberia,while medium and short-distance trajectory accounted for 65.67%,with representing regions such as Harbin,Changchun,and Yanbian Korean Autonomous Prefecture.Contribution source analysis revealed that pollution sources from old industrial cities in northern Liaoning province and Yanbian Prefecture in Jilin province contributed the most to PM_2.5 concentration in Mudanjiang (WPSCF>0.9),and they were also the key contribution sources for PM_2.5 concentration (WCWT >100).

Key words: PM_2.5, Clustering trajectories, Contribution source analysis