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Preliminary retrieval of aerosol single scattering albedo in eastern China based on S5P/TROPOMI

  • role： First author第一作者
  • Affiliation：

    China University of Mining and Technology, School of Environment and Spatial Informatics, Xuzhou 221116, China

  • Email：lidinf@cumt.edu.cn
  • Introduction：李丁，研究方向为气溶胶卫星遥感。E-mail： lidinf@cumt.edu.cn
LI Ding1,  
  • role： Corresponding author通信作者
  • Affiliation：

    China University of Mining and Technology, School of Environment and Spatial Informatics, Xuzhou 221116, China

  • Email：qinkai@cumt.edu.cn
  • Introduction：秦凯，研究方向为大气环境遥感与应用。E-mail：qinkai@cumt.edu.cn
QIN Kai1*,  
  • Affiliation：

    China University of Mining and Technology, School of Environment and Spatial Informatics, Xuzhou 221116, China

XUE Yong1,  
  • Affiliation：

    German Aerospace Center (DLR), Weßling 82234, Germany

RAO Lanlan2,  
  • Affiliation：

    China University of Mining and Technology, School of Environment and Spatial Informatics, Xuzhou 221116, China

ZHANG Yishu1,  
  • Affiliation：

    China University of Mining and Technology, School of Environment and Spatial Informatics, Xuzhou 221116, China

HE Qing1

resumen

Quantitative retrieval of aerosol Single Scattering Albedo (SSA) from satellite remote sensing is important for climate assessment and air pollution control. This study developed a preliminary SSA retrieval algorithm based on S5p/TROPOMI and Aqua/MODIS in eastern China.The optical absorption of aerosol is highly sensitive in the near-ultraviolet bands, which is significantly correlated with the aerosol model, vertical profile, and corresponding aerosol loading. Considering the actual situation of aerosols in eastern China, the Optical Properties of Aerosols and Clouds aerosol model is constrained using AERONET data in eastern China to produce a more suitable aerosol type, and the corresponding vertical structure of different aerosol types is predefined using ground-based Lidar. Then, the radiative transfer model SCIATRAN is used for sensitivity analysis to further adjust the aerosol model and establish a series of look-up tables (LUTs) for different aerosol subtypes. The SSA can retrieve individual LUT at pixels with the collection of TROPOMI Ultraviolet Absorbing Index (UVAI) and MODIS AOD together. In the process, the Ångström Index values from MODIS and UVAI are used in combination for preliminary classification of aerosol type to improve the accuracy and efficiency.Compared with the ground-based observations, the coefficient of determination (R2) is 0.61, and the root mean square error is 0.05. Compared with OMI instantaneous inversion and monthly average SSA images, the distributions of TROPOMI SSA show a consistent overall trend and have better spatial continuity and larger inter-pixel variation. Further site-by-site analysis shows that the SSA and AOD are highly correlated with the type of aerosols where the site is located. The SSA in Shanghai with more sea salt aerosols is stable above 0.95, while the Beijing area is affected by multiple factors and the SSA varies greatly with time series from 0.85 to 0.98.In conclusion, the preliminary SSA retrieval algorithm based on TROPOMI in this study has good verification accuracy. Using MODIS aerosol products as input can effectively improve the accuracy of SSA inversion. The algorithm still has some uncertainties and needs to be further improved from the aspects of aerosol type and aerosol vertical profile. Nevertheless, the algorithm is helpful for the classification of aerosol types, aerosol microphysical, and optical properties of aerosol in small- and medium-scale regions.

palabra clave

remote sensing;TROPOMI;MODIS;SSA;absorbing aerosol;UVAI

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