Remote sensing of atmospheric aerosol over China

2001 ◽  
Author(s):  
Jietai Mao ◽  
Junhua Zhang ◽  
Chengcai Li ◽  
Meihua Wang
Keyword(s):  
Remote Sensing ◽  
Atmospheric Aerosol

scholarly journals Microscopic Observations of Core‐Shell Particle Structure and Implications for Atmospheric Aerosol Remote Sensing

2018 ◽  
Vol 123 (24) ◽  
Author(s):  
Florin Unga ◽  
Marie Choël ◽  
Yevgeny Derimian ◽  
Karine Deboudt ◽  
Oleg Dubovik ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Atmospheric Aerosol ◽  
Core Shell ◽  
Particle Structure ◽  
Shell Particle ◽  
Aerosol Remote Sensing

Atmospheric aerosol–cloud-stability relationship as observed with optical and radio remote sensing techniques

1998 ◽  
Vol 49 (1) ◽  
pp. 65-76 ◽  
Author(s):  
P.C.S. Devara ◽  
G. Pandithurai ◽  
P.E. Raj ◽  
R.S. Maheskumar ◽  
K.K. Dani
Keyword(s):  
Remote Sensing ◽  
Atmospheric Aerosol ◽  
Aerosol Cloud ◽  
Remote Sensing Techniques

scholarly journals Hygroscopic growth of atmospheric aerosol particles based on active remote sensing and radiosounding measurements

2014 ◽  
Vol 7 (10) ◽  
pp. 10293-10326
Author(s):  
M. J. Granados-Muñoz ◽  
F. Navas-Guzmán ◽  
J. A. Bravo-Aranda ◽  
J. L. Guerrero-Rascado ◽  
H. Lyamani ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Aerosol Particle ◽  
Atmospheric Aerosol ◽  
Enhancement Factor ◽  
Volume Concentration ◽  
Mineral Dust ◽  
Concentration Profiles ◽  
Hygroscopic Growth ◽  
Backscatter Coefficient ◽  
Growth Effects

Abstract. A new methodology based on combining active and passive remote sensing and simultaneous and collocated radiosounding data to study the aerosol hygroscopic growth effects on the particle optical and microphysical properties is presented. The identification of hygroscopic growth situations combines the analysis of multiespectral aerosol particle backscatter coefficient and particle linear depolarization ratio with thermodynamic profiling of the atmospheric column. We analysed the hygroscopic growth effects on aerosol properties, namely the aerosol particle backscatter coefficient and the volume concentration profiles, using data gathered at Granada EARLINET station. Two study cases, corresponding to different aerosol loads and different aerosol types, are used for illustrating the potential of this methodology. Values of the aerosol particle backscatter coefficient enhancement factors range from 2.10 ± 0.06 to 3.90 ± 0.03, being similar to those previously reported in the literature. Differences in the enhancement factor are directly linked to the composition of the atmospheric aerosol. The largest value of the aerosol particle backscatter coefficient enhancement factor corresponds to the presence of sulphate and marine particles that are more affected by hygroscopic growth. On the contrary, the lowest value of the enhancement factor corresponds to an aerosol mixture containing sulphates and slight traces of mineral dust. The Hänel parameterization is applied to these case studies, obtaining results within the range of values reported in previous studies, with values of the γ exponent of 0.56 ± 0.01 (for anthropogenic particles slightly influenced by mineral dust) and 1.07 ± 0.01 (for the situation dominated by anthropogenic particles), showing the convenience of this remote sensing approach for the study of hygroscopic effects of the atmospheric aerosol under ambient unperturbed conditions. For the first time, the retrieval of the volume concentration profiles for these cases using the Lidar Radiometer Inversion Code (LIRIC) allows us to analyse the aerosol hygroscopic growth effects on aerosol volume concentration, observing a stronger increase of the fine mode volume concentration with increasing relative humidity.

Remote sensing of the middle atmospheric aerosol

1980 ◽  
Vol 118 (1) ◽  
pp. 35-57 ◽  
Author(s):  
A. L. Fymat ◽  
C. B. Smith
Keyword(s):  
Remote Sensing ◽  
Atmospheric Aerosol

Improvements for ground-based remote sensing of atmospheric aerosol properties by additional polarimetric measurements

2009 ◽  
Vol 110 (17) ◽  
pp. 1954-1961 ◽  
Author(s):  
Zhengqiang Li ◽  
Philippe Goloub ◽  
Oleg Dubovik ◽  
Luc Blarel ◽  
Wenxing Zhang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Atmospheric Aerosol ◽  
Aerosol Properties

Estimation of atmospheric aerosol composition from ground-based remote sensing measurements of Sun-sky radiometer

2017 ◽  
Vol 122 (1) ◽  
pp. 498-518 ◽  
Author(s):  
Y. S. Xie ◽  
Z. Q. Li ◽  
Y. X. Zhang ◽  
Y. Zhang ◽  
D. H. Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Atmospheric Aerosol ◽  
Aerosol Composition

Remote Sensing of Atmospheric Aerosol

2016 ◽  
pp. 341-436
Author(s):  
Alexander A. Kokhanovsky ◽  
Claudio Tomasi ◽  
Boyan H. Petkov ◽  
Christian Lanconelli ◽  
Maurizio Busetto ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Atmospheric Aerosol
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