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基于AERONET 的北京地区气溶胶光学特性分析
引用本文:葛鹏,张天舒,付毅宾,项衍.基于AERONET 的北京地区气溶胶光学特性分析[J].大气与环境光学学报,2021,16(1):18-27.
作者姓名:葛鹏  张天舒  付毅宾  项衍
作者单位:1 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, 中国科学院环境光学与技术重点实验室, 安徽 合肥 230031;2.中国科学技术大学, 安徽 合肥 230026
基金项目:Supported by National Key Research and Development Project
摘    要:利用 AERONET 北京站点 2016 年 1 月-2018 年 12 月的数据产品, 分析了北京地区气溶胶光学厚度 (AOD)、 Angstrom ¨ 波长指数 α、粒径谱分布的季节特性; 同时选取典型污染天气条件下的数据, 分析了不同季节主控污染物的 类型, 并使用相应雷达比对比反演激光雷达消光结果。研究结果表明: 北京地区 AOD 季节变化特征明显, 主要表现为 春、夏季大, 秋、冬季小, 其中夏季 (0.83) 显著高于其他季节; α 表现出与 AOD 一致的变化规律, 春季最低 (α = 0.95), 表明北京春季受沙尘影响显著, 为主要污染物; 而夏季最大 (α = 1.23), 表明沙尘影响迅速减弱, 细粒子颗粒物占主导, 符合温带季风气候的特点; AOD 和 α 关系图中, 不同污染物分布特征存在差异, 可通过阈值法对污染物进行分类。此 外, 以两种典型污染情况为例, 使用不同雷达比反演激光雷达的消光系数的结果表明, 可以使用太阳光度计数据对反 演参数进行优化。

关 键 词:气溶胶光学厚度  Angstrom  ¨  波长指数  雷达比  北京  
收稿时间:2020-03-03
修稿时间:2020-03-30

Aerosol Optical Properties in Beijing Based on AERONET
GE Peng,ZHANG Tianshu,FU Yibin,XIANG Yan.Aerosol Optical Properties in Beijing Based on AERONET[J].Journal of Atmospheric and Environmental Optics,2021,16(1):18-27.
Authors:GE Peng  ZHANG Tianshu  FU Yibin  XIANG Yan
Affiliation:1.Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China;2.University of Science and Technology of China, Hefei 230026, China
Abstract:Using the data of Aerosol Robotic Network (AERONET) in Beijing site from January 2016 to December 2018, the seasonal characteristics of aerosol optical depth (AOD), Angstrom exponent ¨ α, size distribution in Beijing were analyzed. Meanwhile, the characteristics of contaminant and lidar ratio were analyzed under typical pollution conditions. The results show that the seasonal variation of AOD in Beijing is obvious, its value is higher in spring and summer than autumn and winter. Especially in summer, the value (0.83) is significantly higher. The variation of Angstrom exponent ¨ α shows the similar regularity with AOD, with the lowest in spring (α=0.95) and the largest in summer (α=1.23), indicating that the main pollutant is dust in spring and fine particle in summer regarding to the typical temperate monsoonal climate. The diagram of AOD and α shows that the distribution of different pollutants have different characteristics, thresholding method can be used to classify the pollutant. Moreover, lidar data in two typical pollution cases was analyzed and the extinction coefficients were obtained by using different lidar ratios, and it shows that the solar photometer data can be used to optimize the inversion parameters
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