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郑州市冬季大气PM2.5传输路径和潜在源分析
引用本文:段时光,姜楠,杨留明,张瑞芹. 郑州市冬季大气PM2.5传输路径和潜在源分析[J]. 环境科学, 2019, 40(1): 86-93
作者姓名:段时光  姜楠  杨留明  张瑞芹
作者单位:郑州大学化学与分子工程学院, 郑州 450001;郑州大学环境科学研究院, 郑州 450001;郑州大学化学与分子工程学院, 郑州 450001;郑州大学环境科学研究院, 郑州 450001;郑州大学化学与分子工程学院, 郑州 450001;郑州大学环境科学研究院, 郑州 450001;郑州大学化学与分子工程学院, 郑州 450001;郑州大学环境科学研究院, 郑州 450001
基金项目:国家重点研发计划;郑州市大气颗粒物源解析项目
摘    要:针对郑州市2017年12月~2018年2月的冬季气象数据和大气污染物质量浓度在线监测数据,分析了气象条件对颗粒物浓度的影响.通过混合型单粒子拉格朗日综合轨迹(HYSPLIT)方法模拟了郑州市冬季48 h的气流后向轨迹,同时进行了聚类分析,并使用潜在源贡献因子(PSCF)方法和浓度权重轨迹(CWT)方法分析了郑州市冬季PM_(2.5)的潜在污染来源和不同潜在源区对郑州市大气PM_(2.5)浓度的贡献.结果表明,低风速、高湿度和较少的降水是造成颗粒物污染严重的重要气象因素;超过60%的后向轨迹来自西北方向,其次是来自京津地区的轨迹占比为25.6%,而来自南边和东边的轨迹只占7.5%和6.1%,但对应着较高的PM_(2.5)浓度;郑州市冬季PM_(2.5)的潜在源区主要是北部的京津冀传输通道城市,包括焦作、开封、新乡、鹤壁、濮阳、安阳、邯郸和邢台,此外,相邻省份包括山西省、湖北省和安徽省部分区域对郑州市大气PM_(2.5)污染水平也有着较大的影响和贡献.

关 键 词:细颗粒物  后向轨迹  聚类分析  潜在源贡献因子(PSCF)  浓度权重轨迹(CWT)
收稿时间:2018-05-22
修稿时间:2018-07-13

Transport Pathways and Potential Sources of PM2.5 During the Winter in Zhengzhou
DUAN Shi-guang,JIANG Nan,YANG Liu-ming and ZHANG Rui-qin. Transport Pathways and Potential Sources of PM2.5 During the Winter in Zhengzhou[J]. Chinese Journal of Environmental Science, 2019, 40(1): 86-93
Authors:DUAN Shi-guang  JIANG Nan  YANG Liu-ming  ZHANG Rui-qin
Affiliation:College of Chemistry and Molecular Engineering, Zhengzhou University, Zhengzhou 450001, China;Research Institute of Environmental Science, Zhengzhou University, Zhengzhou 450001, China,College of Chemistry and Molecular Engineering, Zhengzhou University, Zhengzhou 450001, China;Research Institute of Environmental Science, Zhengzhou University, Zhengzhou 450001, China,College of Chemistry and Molecular Engineering, Zhengzhou University, Zhengzhou 450001, China;Research Institute of Environmental Science, Zhengzhou University, Zhengzhou 450001, China and College of Chemistry and Molecular Engineering, Zhengzhou University, Zhengzhou 450001, China;Research Institute of Environmental Science, Zhengzhou University, Zhengzhou 450001, China
Abstract:In this study, meteorological and air mass concentration data of Zhengzhou from December 2017 to February 2018 (winter) were used to quantify the influence of meteorological factors on the PM. The Hybrid Single-Particle Lagrangian Integrated Trajectory model was used to analyze the 48-hour backward trajectories and the cluster method was applied to classify the airflow backward trajectory. Moreover, the potential source contribution function and concentration-weighted trajectory analysis were applied to evaluate the transport pathways and sources of PM2.5 in Zhengzhou. The results show that the heavy pollution in Zhengzhou during winter is mainly due to the low wind speed, high relative humidity, and low precipitation. The cluster analysis revealed that up to 60% of the back trajectories came from the northwest and 25.56% of the back trajectories came from the Beijing-Tianjin area. The airflow trajectories from the south and east account for 7.5% and 6.1% with higher PM2.5 concentrations. The main potential sources of PM2.5 in Zhengzhou during winter are located in Beijing-Tianjin-Hebei air pollution transmission channel cities including Jiaozuo, Kaifeng, Xinxiang, Hebi, Puyang, Anyang, Handan, and Xingtai. The adjacent provinces, including Shanxi, Hubei, and Anhui, also have great influence on the PM2.5 in Zhengzhou.
Keywords:PM2.5  backward trajectory  cluster analysis  potential source contribution function (PSCF)  concentration-weighted trajectory (CWT)
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