牡丹江市PM2.5输送路径及贡献源研究

doi:10.3969/j.issn.1673-503X.2025.01.006

摘要/Abstract

摘要： 利用2014—2023年黑龙江省牡丹江市大气环境监测和常规气象数据以及美国国家环境预报中心提供的全球数据同化系统GDAS数据,对6种主要大气污染物的特征进行分析,并探讨了气象要素与PM_2.5浓度之间的相关性。结合后向轨迹数值模型(HYSPLIT)以及贡献源分析(PSCF)和轨迹浓度分析(CWT)等方法,对典型重污染天气期间PM_2.5的输送路径和贡献源进行了研究。结果表明:近10 a牡丹江出现污染天气个例中,PM_2.5浓度超标天数最多,是影响大气环境质量的首要污染物,其中2014—2017年PM_2.5污染发生频率高、持续时间长、污染程度重。后向轨迹分析表明,来自偏西和西南方向的PM_2.5污染轨迹输送路径对牡丹江的大气污染有着重要影响;在典型重污染天气的PM_2.5输送轨迹中,长距离轨迹占比34.33%,其代表地区为蒙古国高原、西伯利亚南部等地,中短距离轨迹占比为65.67%,代表地区为哈尔滨、长春及延边自治州等地。贡献源分析显示,辽宁北部和吉林延边朝鲜族自治州等地的老工业城市污染源对牡丹江的PM_2.5浓度贡献概率最大(WPSCF>0.9),同时也是影响PM_2.5浓度的关键贡献源之一(WCWT>100)。

关键词: PM_2.5, 聚类轨迹, 贡献源分析

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

中图分类号:

于海军, 张礼宝, 赵玲, 钟波. 牡丹江市PM_2.5输送路径及贡献源研究[J]. 气象与环境学报, 2025, 41(1): 50-57.

YU Haijun, ZHANG Libao, ZHAO Ling, ZHONG Bo. PM_2.5 transport pathway and contribution sources in Mudanjiang[J]. Journal of Meteorology and Environment, 2025, 41(1): 50-57.

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