Characterization of Mineral Dust using XRD and Infrared Spectroscopy

Mineral dust plays a crucially important role in the Earth’s system due to having a profound impact on the energy budget of the atmosphere through its direct interactions with radiation and indirectly via its influence on formation processes of clouds and precipitation. Understanding of the mineralogy and other characteristics of particulate matter emission and dispersion from the surface is important in order to understand its impact on human health, its short and longwave scattering effects, its impact on earth’s temperature, wind, cloud, precipitation rate and climate system. Small size atmospheric particulate matter, PM₁₀ and PM_2.5 (particulate matter with aerodynamic diameter less than 10 μm and less than 2.5 μm, respectively) are regularly collected on filters and analyzed for the organic and inorganic compounds, and assessed for impacts on air quality. This paper focuses on comparison of X-Ray diffraction (XRD) and infrared (IR) spectroscopy for the analysis of airborne and terrestrial dust samples, with application to atmospheric spectral measurements of Earth. To date, spectroscopy has been performed on mineral dust in a limited number of studies. Minerals have unique and diagnostic spectral properties, and features such as the band center, strength, shape, and width are used to identify species with a high level of confidence (Kokaly et al. 2017). In the visible, near infrared, and short-wave infrared (VNIR/SWIR) (0.4 to ~2.5 μm), absorption features arise due the electron orbital configuration of transition metals (generally iron) in various crystallographic sites and from the combination and overtones of molecular vibrations from species such as hydroxyl, water, carbonate, and sulfate. The long-wave infrared (LWIR) (5 to 25 μm, or 2000 to 400 cm^-1), is sensitive to the fundamental molecular vibrations of ligand groups similar to the VNIR/SWIR. However, this region is also sensitive to vibrations of Si-O bonds in silicates. All common rock-forming silicates have diagnostic absorption features in this spectral region and their shape and wavelength location are indicative of silicate structural classes.

Four of the dust samples were collected in China, the USA, Qatar and Iraq (Engelbrecht et al. 2016), and also 37 in Ilam City, Iran. To trap dust samples in Ilam, marble dust collectors (MDCO) were used. (Goossens and Offer, 2000). A total of 41 of samples have been analyzed using VNIR/SWIR, LWIR and XRD. The samples from China, USA, Qatar and Iraq were previously examined by XRD, and initial spectral measurements were obtained to compare the minerals identified by XRD. All dust spectra show a combination of mineral features with each wavelength, being dominated by the most absorptive mineral. Spectra in the VNIR/SWIR for samples S2004 (Qatar) and S2011 (Iraq) show clear absorption attributed to calcite (CaCO₃). The band center is shifted to shorter wavelengths in sample S2011, more consistent with dolomite (CaMg(CO₃)₂ as was confirmed by XRD. All samples also had spectral features near 2.2 µm, consistent with muscovite (KAl₂(Si₃Al)O₁₀(OH,F)₂). Sample S2019 (USA) had a unique and narrow spectral feature near 2.31 µm which is consistent with sepiolite (Mg₄Si₆O₁₅(OH)₂·6H₂O), identified by XRD as a minor constituent. Quartz (SiO₂) and plagioclase ((Na,Ca)(Si,Al)₄O₈) were identified as major components in some samples, but both of these common rock-forming silicates are transparent at shorter wavelengths and will not exhibit any spectral absorption features in this range. In the LWIR all samples showed features arising from carbonate. Strong features from 3000 to 2800 cm^-1, 2750 to 2400 cm^-1, near 2150 and 1800 cm^-1 are all attributable to CO₃ bonds in carbonates. The sample S2011 sample clearly showed band offsets and additional features that identify the dominant carbonate as dolomite rather than calcite, as was identified with XRD. There was a broad absorption envelope in all samples from ~ 3800 to 2700 cm^-1 that is caused by H₂O, likely in the phyllosilicate minerals (biotite, muscovite) or amphibole. Features at wavenumbers lower ~ 1700 cm^-1 are subdued in all samples with a significant silicate component, and neither quartz nor plagioclase are obvious. This may be due to the grains being coated, or the fine grain sizes masking the spectral features. The poster will present initial results on the mineral components of samples from Ilam City. We expect to perform spectral mixture analysis to determine the relative abundances of minerals compared to those determined by XRD. These data should support modeling of atmospheric dust loading, mass balance, and radiative forcing by different atmospheric constituents.

References:

Engelbrecht, J. P., Moosmüller, H., Pincock, S., Jayanty, R. K. M., Lersch, T., and Casuccio, G.: Technical note: Mineralogical, chemical, morphological, and optical interrelationships of mineral dust re-suspensions, Atmos. Chem. Phys., 16, 10809-10830, https://doi.org/10.5194/acp-16-10809-2016, 2016. And the Supplement, Supplement of Atmos. Chem. Phys., 16, 10809–10830, 2016, http://www.atmos-chem-phys.net/16/10809/2016/ doi:10.5194/acp-16-10809-2016-supplement.

Goossens, D., Offer, Z. Y. Wind tunnel and field calibration of six aeolian dust samplers. Atmospheric Environment, v. 34, n. 7, p. 1043-1057, 2000/01/01/ 2000. ISSN 1352-2310. Disponível em: < http://www.sciencedirect.com/science/article/pii/S1352231099003763 >.

Kokaly, R.F., Clark, R.N., Swayze, G.A., Livo, K.E., Hoefen, T.M., Pearson, N.C., Wise, R.A., Benzel, W.M., Lowers, H.A., Driscoll, R.L., and Klein, A.J., 2017, USGS Spectral Library Version 7: U.S. Geological Survey Data Series 1035, 61 p., https://doi.org/10.3133/ds1035.