Literature DB >> 31674363

Improved algorithm of aerosol particle size distribution based on remote sensing data.

Qing Yan, Huige Di, Jing Zhao, Xiaonan Wen, Yufeng Wang, Yuehui Song, Dengxin Hua.   

Abstract

The optical parameters (extinction or backscatter coefficients) of multi-wavelength beams can be used for the retrieval of the aerosol particle size distribution (APSD). An improved algorithm for APSD and aerosol microphysical parameters (AMPs) is studied and discussed by using only multi-wavelength extinction coefficients data. The regularized algorithm and prior value are combined for the retrieval of APSD and AMPs. The regularization algorithm, based on minimum discrepancy principle and averaging procedure, is used for the retrieval of fine-mode APSD and an averaging procedure that can achieve stable outputs is proposed. The 1% averaging result near the minimum of the discrepancy is selected and verified. Based on the inversion results of fine mode from the regularization algorithm, the lognormal distribution with a prior value (model radius) is applied to reconstruct the coarse mode of APSDs through fitting the data. The comprehensive application of the regularization algorithm and averaging process improves the stability of the inversion in the fine mode, and the use of the prior value broadens the inversion radius range of APSD. The complex refractive index need not be assumed for this method. The inversion error for different types of aerosols is analyzed and studied. The reliability of the algorithm is tested and verified by many typical APSDs and the measured APSDs by particle size spectrometer in different pollution days. The algorithm sensitivity analysis is also provided and discussed. The algorithm can obtain reliable inversion of APSD and AMPs with large radius range.

Year:  2019        PMID: 31674363     DOI: 10.1364/AO.58.008075

Source DB:  PubMed          Journal:  Appl Opt        ISSN: 1559-128X            Impact factor:   1.980


  1 in total

1.  Atmospheric aerosol particle size distribution from Lidar data based on the lognormal distribution mode.

Authors:  Yuchen Shi; Wenqing Liu; Yunsheng Dong; Xuesong Zhao; Yan Xiang; Tianshu Zhang; Lihui Lv
Journal:  Heliyon       Date:  2022-07-19
  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.