سابِق|تال

Tropospheric NO2 column density retrieval from the GF-5 EMI data

  • role： First author第一作者
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

    University of Chinese Academy of Sciences, Beijing 100049, China

  • Email：chenglx@radi.ac.cn
  • Introduction：程良晓，1991年生，男，博士研究生，研究方向为大气环境遥感。E-mail：chenglx@radi.ac.cn
CHENG Liangxiao12,  
  • role： Corresponding author通信作者
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

  • Email：taojh@aircas.ac.cn
  • Introduction：陶金花，1978年生，女，副研究员，研究方向为大气遥感反演方法研究和应用。E-mail：taojh@aircas.ac.cn
TAO Jinhua1*,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

YU Chao1,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

ZHANG Ying1,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

FAN Meng1,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

    National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, China

WANG Yapeng13,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

    University of Chinese Academy of Sciences, Beijing 100049, China

CHEN Yuanlin12,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

ZHU Lili1,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

GU Jianbin1,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

    University of Chinese Academy of Sciences, Beijing 100049, China

CHEN Liangfu12

ملخص

Significant impact of NO2 on global atmospheric environment and human health necessitate accurate monitoring of NO2. On the one hand, people can study and analyze their generation and extinction laws, distribution characteristics, diffusion, and transmission characteristics. On the other hand, it can provide decision-making basis for the formulation of pollutant discharge policy and pollution control program. However, the number of ground-based air quality monitoring stations has been increasing, providing abundant NO2 ground observation data. Large-scale monitoring of NO2 emissions requires the development of other monitoring methods. Satellite instruments covering the ultraviolet and visible spectrum have been widely used to detect the concentration of NO2 column in the atmosphere with the advantage of wide-range observation. to further strengthen the domestic air quality monitoring, and improve the air quality in China, the Environmental Trace Gas Monitoring Instrument (EMI) onboard the Chinese GaoFen-5 (GF-5) satellite was launched on May 9, 2018. It is a nadir-viewing wide-field hyperspectral spectrometer, which measures the earth’s backscattered radiation in the ultraviolet and visible spectrum and is designed for atmospheric trace gas detection. Based on the measured spectrum of EMI VIS1 channel, the tropospheric NO2 Vertical Column Density (VCD) was retrieved by Differential Optical Absorption Spectrometry (DOAS) method, which consists of three key steps, namely, spectral fitting, Stratosphere-Troposphere Separation (STS), and tropospheric Air Mass Factor (AMF) calculations. After spectral fitting, a stripe correction scheme was developed for the stripe phenomenon that appears in the initial fitted NO2 SCD. The current advanced STREAM algorithm was used to estimate the stratospheric NO2 concentration, and the TM5 NO2 profile with higher spatial resolution was used in the calculation of tropospheric AMF. The retrieval results of tropospheric NO2 VCD based on EMI were presented, and the results were cross-verified with NO2 products from international similar instruments, i.e., OMI and TROPOMI. From a larger spatial scale, EMI can reflect the global distribution of typical NO2 pollution city sources. In terms of regional scale, the daily spatial distribution correlation coefficients between EMI and TROPOMI in different regions are greater than 0.9. On a monthly time scale, EMI and OMI (TROPOMI) show consistent spatial distribution in the four urban agglomerations of China, and the average spatial correlation coefficient is 0.8 (0.87). The regional mean bias between EMI and OMI (TROPOMI) is within 11.3% (9.5%). The time series analysis of the Pearl River Delta region shows that EMI has high consistency (r=0.89) with TROPOMI. The ground-based MAX-DOAS observation results are also used for validation. The ground validation results show that the EMI retrieval results have high correlation coefficient (0.96) and approximately 35% underestimated. This study proves EMI’s ability in global NO2 monitoring. In the future, domestic instruments similar to EMI are carried out on the GF-5 (02) satellite and the atmospheric environmental monitoring satellite (AEMS), which contributes continuously to China’s trace gas detection. Therefore, this study can provide reference for the design of next similar instruments and the development of corresponding NO2 retrieval algorithm in China.

مفهوم

remote sensing;GF-5;EMI;NO2;DOAS

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