| 基于能见度及AOD数据的北京市PM2.5浓度的反演 |
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| 引用本文： | 杨颖川,葛宝珠,郝赛宇,徐丹卉,刘颖,甘璐,王自发.基于能见度及AOD数据的北京市PM2.5浓度的反演[J].气候与环境研究,2020,25(5):521-530. |
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| 作者姓名： | 杨颖川 葛宝珠 郝赛宇 徐丹卉 刘颖 甘璐 王自发 |
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| 作者单位： | 中国科学院大气物理研究所大气边界层物理和大气化学国家重点实验室,北京 100029;中国科学院大学地球与行星科学学院,北京 100049;中国科学院大气物理研究所大气边界层物理和大气化学国家重点实验室,北京 100029;中国科学院城市环境研究所城市环境科学卓越中心,厦门 361021;国防科技大学计算机学院,长沙 410073;国家气候中心,北京 100081;北京市气象局,北京 100089;中国科学院大气物理研究所大气边界层物理和大气化学国家重点实验室,北京 100029;中国科学院大学地球与行星科学学院,北京 100049;中国科学院城市环境研究所城市环境科学卓越中心,厦门 361021 |
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| 基金项目： | 国家重点研发计划项目2018YFC0830802，中科院先导A专项XDA19040204，国家自然科学基金项目41877313、91744206，大气重污染成因与治理攻关项目DQGG0106 |
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| 摘 要： | 选择北京市为研究地区，对2014～2017年AERONET（Aerosol Robotic Network）提供的CE-318太阳光度计440 nm波段反演的气溶胶光学厚度（AOD）进行风速订正，对订正后 AOD 日均数据与同期地面监测站PM2.5日均浓度数据做季节相关性分析并建立回归模型。又引入能见度因子并利用广义差分法构建2015～2017年北京市AOD与PM2.5浓度、能见度的三元回归模型，最后将2014年数据分为污染日和非污染日分别进行模型检验。结果表明:AOD与PM2.5浓度存在显著的线性正相关性，且存在季节性差异，夏季相关性最强、秋季次之、春季和冬季最低。引入能见度因子并消除自相关后，四季的模型相对误差均显著减小，模型拟合优度显著提高。检验结果为四季整体的平均相对误差在21%～31%范围内，与前人的结果相比拟合曲线的准确性得到了明显地提高。且模型对低PM2.5浓度日的模拟效果较好，对于高PM2.5浓度日的模拟效果较差。本研究对构建北京地区PM2.5浓度长期的历史数据具有重要的科学意义。
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| 关 键 词： | 北京市 气溶胶光学厚度 PM2.5 能见度 相关性 |
| 收稿时间： | 2019/8/9 0:00:00 |
Inversion of PM2.5 Concentration in Beijing Based on Visibility and AOD Data |
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| YANG Yingchuan,GE Baozhu,HAO Saiyu,XU Danhui,LIU Ying,GAN Lu,WANG Zifa.Inversion of PM2.5 Concentration in Beijing Based on Visibility and AOD Data[J].Climatic and Environmental Research,2020,25(5):521-530. |
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| Authors: | YANG Yingchuan GE Baozhu HAO Saiyu XU Danhui LIU Ying GAN Lu WANG Zifa |
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| Institution: | State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029;College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049;State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029;Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021;College of Computer, National University of Defense Technology, Changsha 410073;National Climate Center, Beijing 100081;Beijing Meteorological Bureau, Beijing 100089; State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029;College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049;Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021 |
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| Abstract: | In this study, Beijing is selected as the research area to perform wind speed correction of the aerosol optical depth (AOD) data of the 440 nm band inversion of the CE-318 solar photometer provided by AERONET (Aerosol Robotic Network) in 2014-2017. Then, the seasonal correlation analysis and modeling of the corrected daily average AOD data and the same period ground monitoring station daily average PM2.5 concentration data are conducted. Then, the visibility factor is introduced and the generalized difference method is used to construct the ternary regression model of AOD, PM2.5, and visibility in Beijing from 2015 to 2017. Finally, the data of 2014 are divided into pollution and nonpollution days for the model tests. Results show a significant linear positive correlation between AOD and PM2.5. Moreover, the seasonal differences exhibit the strongest correlation in summer, followed by that in autumn, and the weakest correlation in spring and winter. After introducing the visibility factor and eliminating the autocorrelation, the relative error of the model in the four seasons is reduced, the goodness of fit of the model significantly improved, and the relative error ranges from 21% to 31%. Compared with the previous results, the accuracy of curve fitting has been significantly improved. Moreover, the simulation effect of the model is good for low PM2.5 concentration days but poor for high PM2.5 concentration days. This study is of scientific significance for the construction of the long-term historical data of PM2.5 in Beijing. |
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| Keywords: | Beijing Aerosol optical depth PM2 5 Visibility Correlation |
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