Abstract

Substances with different absorption spectra have different backscatter spectra. If the range of sounding wavelengths is narrow, but includes evident absorption bands of an aerosol substance, then this substance can be detected from the backscattering spectrum. This is a ground for the use of the differential scattering (DICS) technique for the detection of known organic compounds in natural and anthropogenic aerosol. CO<sub>2</sub> lasers with the wavelength tuning range 9–11 &mu;m, which includes the absorption bands of many organic substances, are apparently the most suitable for DICS implementation. It should be borne in mind that when the imaginary part of the refractive index changes (for example, when an absorbing substance is added to a water drop), the real part of the refractive index is also changes. For large particles (r &ge; 10 &mu;m), even small changes in the refractive index significantly affect the backscattering efficiency. The accuracy of the literature data is insufficient for preliminary (a priori) calculation of aerosol backscatter coefficients. Therefore, the development of DICS requires extensive field measurements and their complex mathematical processing with the use of machine learning algorithms. This research sets out the task of systematization of the backscattering radiation by atmospheric aerosol with different organic substances and finding out the wave lengths where the backscatter signal is higher than the selective and continuum atmospheric molecular absorption.

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