Temporal variation of atmospheric aerosol size distribution at a tropical station, Mysore (12 N) from ground based sunphotometer studies

2000 ◽  
Author(s):  
B. S. N. Prasad
Keyword(s):  
Temporal Variation ◽  
Size Distribution ◽  
Atmospheric Aerosol ◽  
Aerosol Size Distribution ◽  
Tropical Station

scholarly journals Technical Note: A new SIze REsolved Aerosol Model (SIREAM)

2006 ◽  
Vol 6 (6) ◽  
pp. 11845-11875 ◽  
Author(s):  
E. Debry ◽  
K. Fahey ◽  
K. Sartelet ◽  
B. Sportisse ◽  
M. Tombette
Keyword(s):  
Size Distribution ◽  
Atmospheric Aerosol ◽  
Transport Model ◽  
Three Dimensional ◽  
Technical Note ◽  
Aerosol Size Distribution ◽  
Short Paper ◽  
Chemistry Transport Model ◽  
Aerosol Model ◽  
General Dynamic

Abstract. We briefly present in this short paper a new SIze REsolved Aerosol Model (SIREAM) which simulates the evolution of atmospheric aerosol by solving the General Dynamic Equation (GDE). SIREAM segregates the aerosol size distribution into sections and solves the GDE by splitting coagulation and condensation/evaporation. A moving sectional approach is used to describe the size distribution change due to condensation/evaporation and a hybrid method has been developed to lower the computational burden. SIREAM uses the same physical parameterizations as those used in the Modal Aerosol Model, MAM sartelet05development. It is hosted in the modeling system POLYPHEMUS (Mallet et al., 2006) but can be linked to any other three-dimensional Chemistry-Transport Model.

Vertical distribution of atmospheric aerosol size distribution over south-central New Mexico

1993 ◽  
Vol 27 (8) ◽  
pp. 1351-1362 ◽  
Author(s):  
Young J. Kim ◽  
Joe F. Boatman ◽  
Ruth L. Gunter ◽  
Dennis L. Wellman ◽  
Stan W. Wilkison
Keyword(s):  
New Mexico ◽  
Vertical Distribution ◽  
Size Distribution ◽  
Atmospheric Aerosol ◽  
Aerosol Size Distribution ◽  
South Central

Description of Atmospheric Aerosol Dynamics Using an Inverse Gaussian Distributed Method of Moments

2020 ◽  
Vol 77 (9) ◽  
pp. 3011-3031
Author(s):  
J. Shen ◽  
M. Yu ◽  
J. Lin
Keyword(s):  
Size Distribution ◽  
Method Of Moments ◽  
Lognormal Distribution ◽  
Atmospheric Aerosol ◽  
Aerosol Size Distribution ◽  
Geometric Standard Deviation ◽  
Test Cases ◽  
Size Distributions ◽  
Inverse Gaussian ◽  
Aerosol Dynamics

Abstract For nearly 60 years, the lognormal distribution has been the most widely used function in the field of atmospheric science for characterizing atmospheric aerosol size distribution. We verify whether the three-parameter inverse Gaussian distribution (IGD) is a more suitable function than the lognormal distribution for characterizing aerosol size distribution. An attractive feature of IGD is that with it a new method of moments (MOM) can be established for resolving atmospheric aerosol dynamics which is described by a kinetic aerosol dynamics equation, i.e., inverse Gaussian distributed MOM (IGDMOM). The advantage of IGDMOM is that all of its moments can be analytically calculated using a closure moment function inherited from IGD. The precision and efficiency of IGDMOM are verified by comparing it with other recognizable methods in test cases of four representative atmospheric aerosol dynamics. Several key statistical quantities determining aerosol size distributions, including kth moments (k = 0, 1/3, 2/3, and 2), geometric standard deviation, skewness, and kurtosis, are evaluated. IGDMOM has higher precision than the lognormal MOM with nearly identical efficiency. The article provides a novel alternative to atmospheric scientists for solving kinetic aerosol dynamics equations.

Multiwavelength lidar for determination of the atmospheric aerosol size distribution

2003 ◽  
Author(s):  
Krzysztof Ernst ◽  
Stanislaw Chudzynski ◽  
G. Karasinski ◽  
A. Pietruczuk ◽  
Tadeusz Stacewicz
Keyword(s):  
Size Distribution ◽  
Atmospheric Aerosol ◽  
Aerosol Size Distribution ◽  
Multiwavelength Lidar
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