谢一松等:Study on influence of different mixing rules on the aerosol components retrieval from ground-based remote sensing measurements
被阅读 1081 次
2014-08-12

Study on influence of different mixing rules on the aerosol components retrieval from ground-based remote sensing measurements
作者:Xie, YS (Xie, Yisong)[ 1,2 ] ; Li, ZQ (Li, Zhengqiang)[ 1,2 ] ; Li, L (Li, Lei)[ 1,2 ] ; Wang, L (Wang, Ling)[ 3 ] ; Li, DH (Li, Donghui)[ 1 ] ; Chen, C (Chen, Cheng)[ 1,2 ] ; Li, KT (Li, Kaitao)[ 1,2 ] ; Xu, H (Xu, Hua)[ 1 ]
ATMOSPHERIC RESEARCH
卷: 145  页: 267-278
DOI: 10.1016/j.atmosres.2014.04.006
出版年: AUG-SEP 2014

摘要
Mixing states of aerosol components significantly influence the optical, physical and radiative properties of ambient aerosols. The five-component aerosol composition model, including black carbon (BC), brown carbon (BrC), mineral dust (DU), ammonia sulfate (AS) and aerosol water (AW), is improved with considering different mixing rules in this paper. Then we retrieve the volume fractions and column mass concentrations of these aerosol components at Beijing from ground-based AERONET remote sensing measurements, such as refractive index, size distribution, and single scattering albedo. A residual minimization method is used to derive aerosol composition difference under dust, haze and clean conditions at Beijing in 2011. Three mixing rules including Maxwell-Garnett (MG), Bruggeman (BR) and Volume Average (VA) are demonstrated to have significant influences on the aerosol component retrievals. We find that over 50% difference of volume fraction of DU occurs by switching between MG and BR rules. Therefore, applicability of each mixing rule is also investigated. We propose that BR is more suitable for the dust case, MG is better than other two rules for the haze case, and VA is the best choice for the clean case. We also discuss the application scopes of different mixing rules by comparing the recovered aerosol optical parameters with AERONET observations. (C) 2014 Elsevier B.V. All rights reserved.

通讯作者地址: Li, ZQ (通讯作者)
       20 Datun Rd, Beijing 100101, Peoples R China.
地址:
[ 1 ] Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China
[ 2 ] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[ 3 ] China Meteorol Adm, Natl Satellite Meteorol Ctr, Beijing 100081, Peoples R China