Paper
28 March 2003 Results of experimental observations and mathematical simulation of distribution of acidic atmospheric impurities in the region of Southern Baikal
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Abstract
In an outcome of two-years observations in the region of Southern Baikal, experimental data about inter-annual variability of 7-10 day's average concentrations of some acid gases, as well as main ions in soluble faction of atmospheric aerosols and in rains. The evaluations of a dry deposition amount are represented, in comparision with the measured wet deposition. In the summer period the dry and wet deposition in considered region are close on magnitude, but in an annual sum the dry deposition essentially predominates because of their highest contribution in the winter period. As a whole, the results are satisfactorily agreed with obtained earlier observations in different parts of the Baikal region. In addition to experimental studies, the accounts with the help of the mathematical model based on numerical solution of the spatial non-linear non-stationary semi-empirical equation of a turbulent diffusion of impurity were made. In an outcome of conducted numerical experiments with the model the spatial fields of monthly average concentration of both sulphur and nitrogen compounds and a small gas components of the atmosphere over considered region were obtained.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
L. P. Golobokova, T. V. Khodzher, N. A. Kobeleva, Vladimir L. Makukhin, O. G. Netcvetaeva, and V. A. Obolkin "Results of experimental observations and mathematical simulation of distribution of acidic atmospheric impurities in the region of Southern Baikal", Proc. SPIE 5027, Ninth Joint International Symposium on Atmospheric and Ocean Optics/Atmospheric Physics. Part II: Laser Sensing and Atmospheric Physics, (28 March 2003); https://doi.org/10.1117/12.497295
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KEYWORDS
Ions

Sulfur

Nitrogen

Atmospheric optics

Atmospheric particles

Mathematical modeling

NOx

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