大气与环境光学学报 ›› 2021, Vol. 16 ›› Issue (3): 186-196.

• “高分五号卫星大气数据反演”专辑 • 上一篇    下一篇

基于EMI 观测华北平原对流层NO2 的时空变化研究


赵 冉1;2, 张成歆3∗, 吴 跃4, 孙中平4, 刘 诚2;3   


  1. 1 中国科学技术大学环境科学与光电技术学院, 安徽 合肥 230026; 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, 中国科学院环境光学与技术重点实验室, 安徽 合肥 230031; 3 中国科学技术大学精密机械与精密仪器系, 安徽 合肥 230026; 4 生态环境部卫星环境应用中心, 北京 100094
  • 收稿日期:2020-10-26 修回日期:2021-01-13 出版日期:2021-05-28 发布日期:2021-05-28
  • 通讯作者: E-mail: zcx2011@ustc.edu.cn E-mail:zcx2011@mail.ustc.edu.cn
  • 作者简介:赵 冉 (1997 - ), 女, 安徽六安人, 硕士研究生, 主要从事卫星光谱遥感方面的研究。 E-mail: zr1997@mail.ustc.edu.cn
  • 基金资助:
    Supported by the National Earth Observation Data Center(国家对地观测科学数据中心开放基金项目, NODAOP2020013), China Postdoctoral Science Foundation(中国博士后科学基金, 2020TQ0320), the National Key Research and Development Plan(国家重点研发计划, 2017YFC0210002, 2017YFB0503900-4-2, 2018YFC0213104, 2016YFC0203302, 2017YFC0212800), National Natural Science Foundation of China(国 家 自 然 科 学 基 金, 41720501, 51778596, 41977184), the Major Scientific and Technological Projects in Anhui Province(安徽省科技重大专项, 18030801111), Beautiful China Ecological Civilization Construction Science and Technology Project(美丽中国生态文明建设科技工程专项, XDA23020301), the National Key Project for Causes and Control of Heavy Air Pollution of China(国家大气重污染成因与治理攻关项目, DQGG0102, DQGG0205), the Major Projects of High Resolution Earth Observation Systems of National Science and Technology of China(国家高分辨率对地观测重大科技专项项目“ 环境保护遥感动态监测信息服务系 统”, 二期, 05-Y30B01-9001-19/20-3)

Analysis of Spatio-Temporal Variations of Tropospheric Nitrogen Dioxide in the North China Plain Based on EMI

ZHAO Ran1;2, ZHANG Chengxin3∗, WU Yue4, SUN Zhongping4, LIU Cheng2;3   

  1. 1 School of Environmental Science and Optoelectronic Technology, University of Science and Technology of China, Hefei 230026, China; 2 Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, HFIPS, Chinese Academy of Sciences, Hefei 230031, China; 3 Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China; 4 Ministry of Ecology and Environment Center for Satellite Application on Ecology and Environment, Beijing 100094, China
  • Received:2020-10-26 Revised:2021-01-13 Published:2021-05-28 Online:2021-05-28
  • Contact: Chengxin /ZHANG E-mail:zcx2011@mail.ustc.edu.cn

摘要: 利用中国科学技术大学开发的 GF-5/EMI 对流层 NO2 柱总量产品, 结合排放清单和地面降水、气温数据, 研 究了 2019 年 1–8 月华北平原对流层 NO2 的时空变化趋势。结果表明, NO2 污染集中在河南省、河北省和天津市, 河 南省焦作市 (1.670×1016 molecules·cm−2) 和河北省石家庄市 (1.426×1016 molecules·cm−2) 尤为严重; 周变化总体呈现“ 反周末效应”, 但部分农业城市趋势相反; 月变化从 1 月 (1.635×1016 molecules·cm−2) 起持续下降, 8 月降至最低水平 (1.839×1015 molecules·cm−2), 与月降水、月气温的相关系数分别为 −0.8622 (p = 0.0059 < 0.01) 和 −0.9162 (p = 0.0014 < 0.01), 与人为生活源月排放的相关系数为 0.9778 (p = 2.69×10−5 < 0.01); 以天津市为代表的华北平原工业城市污染 严重, 在未来大气污染治理中需继续关注。

关键词: 对流层, 高分五号, 华北平原, NO2 污染

Abstract: Using GF-5/EMI tropospheric NO2 columns product developed by University of Science and Technology of China, combined with the emission inventory, surface precipitation and temperature data, the spatio-temporal variations of tropospheric NO2 that is in the North China Plain (NCP) from January to August 2019 are studied. The results show that NO2 pollution is concentrated in Henan, Hebei and Tianjin, especially in Jiaozuo, Henan (1.670×1016 molecules·cm−2) and Shijiazhuang, Hebei (1.426×1016 molecules·cm−2). The weekly changes generally show “reverse-weekend effect”, but the trend in some agricultural cities is opposite. The monthly change decreases continuously from January (1.635×1016 molecules·cm−2) to the lowest level in August (1.839×1015 molecules·cm−2). The correlation coefficient with monthly precipitation and temperature are −0.8622 (p = 0.0059 < 0.01) and −0.9162 (p = 0.0014 < 0.01), respectively, and with anthropogenic monthly emissions is 0.9778 (p = 2.69×10−5 < 0.01). The industrial cities in NCP, represented by Tianjin, are seriously polluted, which need to be paid more attention to on the prevention and control of air pollution in the future.

Key words: troposphere, GF-5, the North China Plain, NO2 pollution

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