Global aerosol-type classification using a new hybrid algorithm and Aerosol Robotic Network data

Wei, Xiaoli; Cui, Qian; Ma, Leiming; Zhang, Feng; Li, Wenwen; Liu, Peng

doi:https://doi.org/10.5194/acp-24-5025-2024

Articles | Volume 24, issue 8

https://doi.org/10.5194/acp-24-5025-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-24-5025-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 24, issue 8

Research article

|

29 Apr 2024

Research article |

| 29 Apr 2024

Global aerosol-type classification using a new hybrid algorithm and Aerosol Robotic Network data

Xiaoli Wei, Qian Cui, Leiming Ma, Feng Zhang, Wenwen Li, and Peng Liu

Data sets

NASA AERONET https://aeronet.gsfc.nasa.gov/

Global aerosol-type classification using a new hybrid algorithm and Aerosol Robotic Network data [Data set] Feng Zhang et al. https://doi.org/10.5281/zenodo.10973114

Model code and software

Global aerosol-type classification using a new hybrid algorithm and Aerosol Robotic Network data Feng Zhang et al. https://doi.org/10.5281/zenodo.10972939

Short summary

A new aerosol-type classification algorithm has been proposed. It includes an optical database built by Mie scattering and a complex refractive index working as a baseline to identify different aerosol types. The new algorithm shows high accuracy and efficiency. Hence, a global map of aerosol types was generated to characterize aerosol types across the five continents. It will help improve the accuracy of aerosol inversion and determine the sources of aerosol pollution.