大气与环境光学学报 ›› 2021, Vol. 16 ›› Issue (1): 28-34.

• 环境光学监测技术 • 上一篇    下一篇

北京地区春季重污染过程污染特征及其光学特性分析

李若飞1, 张学海1;2∗, 段金龙1, 刘 澍1   

  1. 1 河南工业大学信息科学与工程学院, 河南 郑州 450001; 2 中国科学院合肥物质科学研究院安徽光学精密机械研究所, 中国科学院大气光学重点实验室, 安徽 合肥 230031
  • 收稿日期:2019-10-10 修回日期:2019-11-23 出版日期:2021-01-28 发布日期:2021-02-02
  • 通讯作者: E-mail: zhangxuehai2012@163.com E-mail:zhangxuehai2012@163.com
  • 作者简介:李若飞 ( 1998- ), 女, 陕西延安人, 本科生, 主要从事地图学与地理信息系统方面的的研究。 E-mail: 1924691217@qq.com
  • 基金资助:
    国家自然科学基金青年基金;河南省科技攻关项目;省属高校基本科研业务费专项资金项目青年支持计划;河南工业大学高层次人才科研启动基金项目

Pollution and Optical Characteristics of Heavy Pollution Process in Beijing Area in Spring

LI Ruofei1, ZHANG Xuehai1;2∗, DUAN Jinlong1, LIU Shu1   

  1. 1 School of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China; 2 Key Laboratory of Atmospheric Optics, Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China
  • Received:2019-10-10 Revised:2019-11-23 Published:2021-01-28 Online:2021-02-02
  • Contact: Xue-hai ZHANG E-mail:zhangxuehai2012@163.com
  • Supported by:
    Supported by National Natural Science Foundation of China Youth Fund (国家自然科学基金青年基金, 41701237), Scientific and Technological Project of Henan Province (河南省科技攻关项目, 182102310999), Youth Support Program for Special Funds for the Fundamental Research Funds for the Provincial Universities (省属高校基本科研业务费专项资金项目青年支持计划, 2017QNJH02), Doctoral Scientific Research Start-up Foundation from Henan University of Technology (河南工业大学高层次人才科研启动基金项目, 2017BS026)

摘要: 针对北京地区 2018 年 3 月 29 日-4 月 10 日的一次完整重污染过程, 利用空气质量监测数据及 AERONET 北 京站观测数据开展其污染特征及光学特性分析, 并结合 HYSPLIT 气流后向轨迹模式, 对此次重污染期间大气颗粒 物时空传输特征进行了综合研究。结果表明: 北京地区此次重污染过程以弱吸收性细模态气溶胶为主; 重污染期间 PM2:5 浓度和气溶胶光学特性受天气影响非常明显; AEORNET 得到的气溶胶光学特性结果与地面空气监测站监测数 据吻合良好, 表明 AERONET 能在重污染过程气溶胶光学特性研究中发挥重要作用。

关键词: 大气污染, 气溶胶, 光学特性, 污染特征

Abstract: A heavy air pollution process in Beijing was observed from March 29 to April 10, 2018, and its pollution characteristics and optical characteristics were analyzed by using air quality monitoring data and the observation data of AERONET Beijing station. Combined with HYSPLIT airflow backward track mode, the temporal and  spatial transport characteristics of atmospheric particles during this heavy pollution were comprehensively studied. The results show that, the heavy pollution process was dominated by fine mode aerosols with weak absorption, and the PM2:5 concentration and aerosol optical characteristics were significantly affected by the meteorological element during the pollution process. The results also show that the results from AERONET are in good agreement with those from the ground air monitoring stations, which indicates that AERONET results can be adapted to the study of aerosol optical characteristics in heavy air pollution process.

Key words: air pollution, aerosol, optical characteristics, pollution characteristics

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