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Inversion algorithm for non-spherical dust particle size distributions

  • Siyu Cai
  • Jiandong MaoEmail author
  • Hu Zhao
  • Chunyan Zhou
  • Xin Gong
  • Hongjiang Sheng
Regular Paper
  • 16 Downloads

Abstract

Dust particles are the main aerosol component of the atmosphere, and can influence human, environmental, and ecological health. Particle size distribution is an important aerosol micro-physical parameter that denotes the concentration distribution of particles of different radii and can determine the extinction characteristics of these particles. In traditional inversion algorithms, the aerosol is generally assumed to be spherical according to Mie theory, and the relationship between aerosol optical thickness and particle size distribution is described by the Fredholm integral equation of the first kind. For non-spherical dust particles, this spherical assumption is obviously unreasonable and yields unreliable results. Therefore, we developed an algorithm assuming non-spherical particles for inversion of dust particle size distributions. In the case of non-spherical particles, the extinction efficiency factor kernel functions of the ellipsoid were calculated using the anomalous diffraction approximation method, and the kernel function of Mie scattering theory was substituted with these new kernel functions. Moreover, the Phillips–Twomey method was employed to solve the Fredholm integral equation of the first kind using aerosol optical thickness data from a CE-318 sun photometer. To verify the feasibility of the anomalous diffraction approximation method, experiments were carried out under sunny, dusty, windy and hazy weather conditions. These experiments showed that the extinction kernel function for non-spherical particles obtained using the anomalous diffraction approximation method is suitable for inversion of non-spherical dust particle size distributions under different weather conditions in the Yinchuan area.

Keywords

Dust aerosol Non-spherical particle Anomalous diffraction approximation Particle size distribution 

Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 61765001 and 61565001), Leading Talents of Scientific and Technological Innovation of Ningxia, Plan for Leading Talents of the State Ethnic Affairs Commission of the People’s Republic of China, Scientific Research Project of North Minzu University (No. 2016GQR07) and the Innovation Team of Lidar Atmosphere Remote Sensing of Ningxia.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflicts of interest.

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Copyright information

© The Optical Society of Japan 2019

Authors and Affiliations

  1. 1.School of Electrical and Information EngineeringNorth Minu UniversityYinchuanChina

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