Simulation of dust aerosol particles based on different geometric models

Dust aerosols have significant implications for atmospheric radiative transfer and human health. Therefore, the establishment of suitable geometric models to accurately simulate their non-spherical characteristics is crucial for investigating radiative transfer and improving remote sensing retrieval of dust aerosols. For this reason, in this study, the sphere, ellipsoid, super-spheroidal model and fractal models are used to simulate non-spherical sand and dust particles, and the scattering phase matrix is calculated by using the Discrete Dipole Approximation (DDA) method, and finally, the computed light scattering data are systematically compared with the feldspathic particles measured data from the Amsterdam database. The results show that the super-spheroidal model performs optimally in the simulation of the total scattering intensity and the line polarization characteristics, with root-mean-square errors as low as 0.0762 and 0.0654, respectively; The fractal model exhibits a significant advantage in polarization scattering moment characteristics, with a correlation coefficient that is 52.3% higher than that of the conventional spherical model, while the traditional spherical and ellipsoidal models lead to large systematic errors due to structural simplification. This study provides theoretical support for improving the accuracy of optical inversion of sand and dust aerosols and proposes an optimization direction for multi-model fusion.

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Publication Details

Published
2025-08-03
DOI
https://doi.org/10.1109/iciea65512.2025.11148469
Primary Topic
Atmospheric aerosols and clouds
Type
article
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Simulation of dust aerosol particles based on different geometric models

Shaocheng Xie, Shu‐Hua Chen, P. Chen, Hongfei Wang et al.
Atmospheric aerosols and clouds
article

Simulation of dust aerosol particles based on different geometric models

Shaocheng Xie, Shu‐Hua Chen, P. Chen, Hongfei Wang, Hu Zhao, Chunhui Li
article en

Abstract

Dust aerosols have significant implications for atmospheric radiative transfer and human health. Therefore, the establishment of suitable geometric models to accurately simulate their non-spherical characteristics is crucial for investigating radiative transfer and improving remote sensing retrieval of dust aerosols. For this reason, in this study, the sphere, ellipsoid, super-spheroidal model and fractal models are used to simulate non-spherical sand and dust particles, and the scattering phase matrix is calculated by using the Discrete Dipole Approximation (DDA) method, and finally, the computed light scattering data are systematically compared with the feldspathic particles measured data from the Amsterdam database. The results show that the super-spheroidal model performs optimally in the simulation of the total scattering intensity and the line polarization characteristics, with root-mean-square errors as low as 0.0762 and 0.0654, respectively; The fractal model exhibits a significant advantage in polarization scattering moment characteristics, with a correlation coefficient that is 52.3% higher than that of the conventional spherical model, while the traditional spherical and ellipsoidal models lead to large systematic errors due to structural simplification. This study provides theoretical support for improving the accuracy of optical inversion of sand and dust aerosols and proposes an optimization direction for multi-model fusion.

North Minzu University (CN)
Openalex Percentile: Top 77%
Atmospheric aerosols and clouds
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