&lt;title&gt;Remote sensing of atmospheric aerosols with the use of a white-light femtosecond laser: numerical simulation&lt;/title&gt;

Matvienko, Gennadii G.; Veretennikov, V. V.; Krekov, G. M.; Krekova, M. M.

doi:10.1117/12.563134

Cited by 6 publications

(8 citation statements)

References 3 publications

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“…The strong white light continuum generated by a filament in air can be exploited for remote atmospheric diagnostics (Rairoux et al, 2000;Matvienko et al, 2003;Kasparian et al, 2003).Among the most attractive features of this promising method for analyzing air pollution, one should note its capability of providing 3D-range resolved measurements of concentrations of gaseous and solid particles in a single shot (Frejafon et al, 1998). Filament based LIDAR techniques are advantageous with respect to conventional LIDAR techniques since the entire spectrum can be acquired in one shot, while by conventional LIDAR, a tunable source must be used so as to scan the wavelength.…”

Section: White Light Continuum Light Detection and Ranging Techniquesmentioning

confidence: 99%

Femtosecond filamentation in transparent media

2007

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Section: White Light Continuum Light Detection and Ranging Techniquesmentioning

confidence: 99%

Femtosecond filamentation in transparent media

2007

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“…However, systems based on broadband coher ent radiation sources are now used in the practice of optical sensing; they are full of potentialities for the optical monitoring of large particles of natural and anthropogenic origin (cloud, fog, dust particles, etc.) [15]. In view of this, selecting spectral sensing ranges for such sources we will follow only the requirement that they fit into the "transparency window" of a gas dust plume emitted into the atmosphere by cement plants.…”

Section: Selection Of the Spectral Sensing Rangesmentioning

confidence: 98%

“…Available and developed sources of coherent broadband radiation within the spectral range, sensi tive relative to large particles (λ > 1 μm), are full of potentialities for the environmental monitoring of dis persive industrial aerosols [14,15]. In view of this, it is necessary to develop a methodological basis for reli able interpretation of location measurements with sys tems based on the above sources.…”

Section: S a Lysenko And M M Kugeikomentioning

confidence: 99%

Retrieval of the mass concentration of dust in industrial emissions from optical sensing data

Lysenko

Kugeiko

2012

Atmos Ocean Opt

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A statistical microphysical model of the dust, emitted into the atmosphere by cement enterprises, is developed, which allows for possible variations in the chemical composition of particles, their concentra tions, and size distribution function. An ensemble of microphysical parameters of dust was simulated and the extinction coefficient was calculated at wavelengths of 0.355, 0.532, 1.064, 1.25, 1.56, 1.67, and 2.14 μm from the "windows of transparency" of exhaust gas at cement enterprises. The errors of retrieval of the mass con centration of dust from the data of optical sensing at wavelengths of a Nd:YAG laser with third harmonic gen eration, are estimated on the basis of a multiple regression method. The sets of two (0.532 and 2.14 μm) and three (0.532, 1.56, and 2.14 μm) wavelengths of optical sensing are ascertained, which are optimal in terms of their information content about the concentration and the resistance of the corresponding solutions of the inverse problem to measurement errors, and the effect of dust particle shape. Dependencies of errors of con centration retrieval, from the extinction coefficient at optimal wavelengths, on the optical measurement error are calculated. A tight correlation between the dust concentration and its extinction coefficient at a wave length of 2.14 μm was derived; it allows retrieval of the concentration from fixed frequency optical sensing data with an error of about 8%.

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“…Actually, if we write Eq. (17) for two allowed transitions J1 and J2, than their ratio is a functional dependence on (23) 180 + 7e at excitation by the linearly polarized light; and for the shifted spectrum of Raman radiation g(i9) = K (1 + -1-2 (24) at excitation by the natural light, g() = K(1_2) (25) at excitation by the linearly polarized light. random sampling process because of relatively small ar << as .…”

Section: Model Of the Mediummentioning

confidence: 99%

<title>Simulation of Raman lidar multiple-scattering return</title>

Krekov

Krekova

2004

SPIE Proceedings

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The paper discusses various aspects of statistical modeling of transspectral processes used in laser sensing of the meteorological parameters of the atmosphere. The need in invoking the rigorous apparatus of the Monte Carlo methods arises if meteorological lidars are operated under the conditions of the cloudy atmosphere, when the role of the multiply scattered component of a lidar signal becomes significant. The particular attention is paid to construction of algorithms for modeling of radiative transfer processes. The importance of correct choice of the model of elastic and inelastic molecular scattering is demonstrated. In particular, in simulation of photon scattering angles in the process of Markovian wandering, the form of the scattering phase function should be taken adequate to the conditions of Raman excitation. The results of methodic calculations are presented and compared with the data of other authors. Based on the results obtained, some features of formation of the multiple-scattering background in Raman sensing channels are established.

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<title>Remote sensing of atmospheric aerosols with the use of a white-light femtosecond laser: numerical simulation</title>

Cited by 6 publications

References 3 publications

Femtosecond filamentation in transparent media

Femtosecond filamentation in transparent media

Retrieval of the mass concentration of dust in industrial emissions from optical sensing data

<title>Simulation of Raman lidar multiple-scattering return</title>

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