Abstract

Mineral dust particles dominate aerosol mass in the atmosphere and directly modify Earth’s radiative balance through absorption and scattering. This radiative forcing varies strongly with mineral composition, yet there is still limited knowledge on the mineralogy of atmospheric dust. In this study, we performed X-ray diffraction (XRD) and reflectance spectroscopy measurements on 37 different atmospheric dust samples collected as airfall in an urban setting to determine mineralogy and the relative proportions of minerals in the dust mixture. Most commonly, XRD has been used to characterize dust mineralogy; however, without prior special sample preparation, this technique is less effective for identifying poorly crystalline or amorphous phases. In addition to XRD measurements, we performed visible, near-infrared, and short-wave infrared (VNIR/SWIR) reflectance spectroscopy for these natural dust samples as a complementary technique to determine minerology and mineral abundances. Reflectance spectra of dust particles are a function of a nonlinear combination of mineral abundances in the mixture. Therefore, we used a Hapke radiative transfer model along with a linear spectral mixing approach to derive relative mineral abundances from reflectance spectroscopy. We compared spectrally derived abundances with those determined semi-quantitatively from XRD. Our results demonstrate that total clay mineral abundances from XRD are correlated with those from reflectance spectroscopy and follow similar trends; however, XRD underpredicts the total amount of clay for many of the samples. On the other hand, calcite abundances are significantly underpredicted by SWIR compared to XRD. This is caused by the weakening of absorption features associated with the fine particle size of the samples, as well as the presence of dark non-mineral materials (e.g., asphalt) in these samples. Another possible explanation for abundance discrepancies between XRD and SWIR is related to the differing sensitivity of the two techniques (crystal structure vs chemical bonds). Our results indicate that it is beneficial to use both XRD and reflectance spectroscopy to characterize airfall dust, because the former technique is good at identifying and quantifying the SWIR-transparent minerals (e.g., quartz, albite, and microcline), while the latter technique is superior for determining abundances for clays and non-mineral components.

Highlights

  • Mineral dust aerosols are lofted from the surface into the atmosphere, mainly in the arid regions of the world, either affecting the area nearby or traveling long distances for global impacts (Goudie and Middleton, 2006)

  • We set out to test if VNIR/SWIR reflectance spectroscopy combined with a Hapke model and linear spectral mixing of single scattering albedo (SSA) can accurately estimate mineral abundance consistent with semi-quantitative values determined by X-ray diffraction (XRD)

  • Our analysis showed that SWIR is well-suited to identify clay phases that would be missed by XRD techniques and is a quick and effective way to survey a group of samples with little preparation

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Summary

Introduction

Mineral dust aerosols are lofted from the surface into the atmosphere, mainly in the arid regions of the world, either affecting the area nearby or traveling long distances for global impacts (Goudie and Middleton, 2006). Engelbrecht et al, 2017 performed XRD measurements on 27 dust samples collected from the Arabian Red Sea coast in order to obtain mineralogy and fractional 45 abundances of minerals In that study, they found that the dust samples were mainly dominated by quartz, feldspars, micas, clays, and halite and to a lesser extent by carbonates, iron oxides, and gypsum. VNIR/SWIR spectroscopy has not been used to study natural dust particle mineralogy; it can provide quantitative measurements and identify both amorphous and crystalline phases (Clark, 1999) This approach has been widely used to obtain mineral compositional information in laboratory and remote sensing applications with particular attention to mineral mixtures (e.g., Mustard and Pieters, 1987; Combe et al., 2008). We examined the ability of widely used spectral mixing approaches to determine if they can be used accurately to quantify mineral abundances in dust samples collected in urban settings

Sample Collection
XRD (Total Mineral Abundance)
VNIR/SWIR Reflectance Spectroscopy
Comparison of Mineral Abundances from XRD and SWIR Spectroscopy
Nature of Techniques
Limitation of Library and Modelling for Fine Grains
Contribution of Non-Mineral Constituents
Obtaining Abundances from Mid and Long-wave Infrared (MWIR-LWIR)
Findings
Conclusions
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