• DocumentCode
    3690420
  • Title

    Inversion of aerosol size distribution by using genetic algorithms and multi-sensor data

  • Author

    Ma Yingying;Gong Wei;Wang Lunche;Yan Fa

  • Author_Institution
    State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    2238
  • Lastpage
    2241
  • Abstract
    In this article, we introduce the genetic algorithm into the inversion of aerosol size distribution. We are often faced with limited or insufficient observations in remote sensing and the observations are contaminated. The particle spectrum extinction equation is an ill-posed integral equation of the extinction inversion method[1]. To overcome the ill-posed nature, we use a double logarithmic normal distribution function to express the aerosol size distribution. To obtain the optimal solution, we introduce the genetic algorithm to gain the minimum sum of squared errors. Our method can improve accuracy and reduce the computational difficulty. The assumption of parameters in the bimodal distribution function is important to the inversion results. The aerosol size distribution obtained from the GRIMM 180 PM monitor and the TSI Scanning mobility particle sizers is compared with that computed via the method proposed by Dubovik and King(2000)[2]. Obvious difference has been discovered between aerosol size distribution on the ground and in the total atmospheric column. As a result, it is necessary to develop multi-wavelength and multi-function lidar to get observe the three-dimensional distribution characteristics of aerosol.
  • Keywords
    "Aerosols","Atmospheric measurements","Genetic algorithms","Optical variables measurement","Particle measurements","Optical scattering","Switched-mode power supply"
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International
  • ISSN
    2153-6996
  • Electronic_ISBN
    2153-7003
  • Type

    conf

  • DOI
    10.1109/IGARSS.2015.7326251
  • Filename
    7326251