4.5 Article

Variations in Infrared Complex Refractive Index Spectra of Surface Soils from Global Dust Entrainment Regions

Journal

ATMOSPHERE
Volume 14, Issue 4, Pages -

Publisher

MDPI
DOI: 10.3390/atmos14040675

Keywords

mineral dust; transmission spectra; imaginary refractive index; real refractive index; Subtractive Kramers-Kronig (SKK); overlapping IR absorption peaks; IR spectral variability

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This study explores the spectral diversity of infrared (IR) imaginary (k) and real (n) indices of refraction for soils from global dust entrainment regions. The optical constants obtained through the KBr technique are comparable to previous studies, suggesting the reliability of the SKK method. The spectral variability observed in these soils is attributed to combinations of silicates rather than a single mineral.
We explored spectral diversity in infrared (IR, 4-25 mu m) imaginary (k) and real (n) indices of refraction (optical constants) for 26 surface soils that originated from global dust entrainment regions. The k spectra were derived from optical transmission spectra of KBr pellets containing dispersed dust and the n spectra were estimated with the subtractive Kramers-Kronig (SKK) method. We compared k and n obtained by this study with previously published values. Our optical constants from the KBr technique are comparable in magnitude and spectral shape to those from previous studies that used dust aerosols re-suspended in a chamber. This suggests that the SKK method can offer a reliable mechanism for measuring IR spectra of both optical constants for soils. The soils used here exhibit additional spectral variability compared with past studies. We note that the appearance and the shift in positions of the strongest absorption peaks are due to combinations of silicates with overlapping absorption, rather than being related to a single mineral. We note that all dust optical constants have substantially lower magnitudes compared to those of pure minerals. Our results can improve estimates of mineral dust radiative effects and support quantification of surface mineral estimates using satellite and ground-based remote sensing.

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