Inversion of Aerosol Particle Size Distribution Using an Improved Stochastic Particle Swarm Optimization Algorithm

Abstract

Aerosol particle size distribution (PSD) is one of the main influencing factors of the radiation effects and climate effects of aerosol. An improved stochastic particle swarm optimization (ISPSO) algorithm is proposed, and the PSD characteristics of aerosols were successfully retrieved from the aerosol optical depth (AOD). The performance analysis shows that the algorithm has good global search ability and convergence performance and will not fall into local optima. Then, the robustness and the ability to resist the noise of the algorithm were verified by adding random errors, using random initial values, and changing the number of samples and inversion parameters, and it was shown that the algorithm has a weak dependence on the initial value. The PSD characteristics of three typical aerosols were inverted, and the results show that the algorithm has good adaptability to the inversion of aerosol PSD. Finally, the PSD characteristics of aerosols from Xianghe and Mezaira under typical weather were inverted based on AERONET data, which shows the effectiveness and advancement of the ISPSO algorithm. This study can provide help for the obtaining of aerosol parameters under poor optical conditions.