A document by Mohammad Reza Sadrian. Click on the document to view its contents.

Direct radiative forcing is a major impact of atmospheric dust aerosols. Mineral dust is an important aerosol component that interacts with both incoming and outgoing radiation, modulating radiative fluxes on Earth and its atmosphere. Dust radiative impact directly depends on the particles physico-chemical characteristics (e.g. mineralogy, shape, size) which are the main source of uncertainties. Spectral signatures of dust particles in the visible/short-wave infrared (V/SWIR) and long-wave infrared (LWIR) are linked to mineral composition and variability. Obtaining the precise spectral signature and size distribution of dust particles can result in accurate derivation of refractive indices which are used as inputs to model radiative forcing. In this work, V/SWIR and LWIR reflectance spectra of heterogeneous dust samples from the United States, East Asia, and Middle East were analyzed for their mineral abundances. For this study we used global well-characterized soil samples with comparable mineral compositions to windblown dust. The soil samples cover a wide range of mineral compositions and represent both arid and semi-arid regions [J P Engelbrecht et al., 2016]. Our preliminary analysis used linear spectral mixing for both V/SWIR and LWIR reflectance spectra. This approach is the simplest method to determine mineral abundances from reflectance spectra. While this resulted in a very low RMSE for the fit between the sample and modeled spectra, modeled spectra did not match band centers and strengths for all features. We also converted reflectance spectra to continuum removed (CR) and mean optical path (MOPL) which have the potential to eliminate nonlinear effects (e.g. multiple scattering) in spectral mixing. These approaches, which modify the reflectance hull, significantly weakened or removed the calcite absorption features at 2375 nm. Because these samples are very fine grained (< 38 µm [J P Engelbrecht et al., 2016]) multiple scattering effects are expected to be important for both V/SWIR and LWIR spectral ranges and as our initial results show linear mixing is insufficient to produce reasonable mineral abundances. Our next efforts will include full radiative transfer models of the measured spectra which we will present at the meeting.

Mineral dust particles are ubiquitous in the atmosphere and can be transported vast distances affecting climate, air quality, and human health on a global scale. Mineralogical composition has a substantial impact on dust properties and their effects. Natural dust samples are both fine-grained and composed of many different minerals. Most commonly, X-ray diffraction (XRD) has been used to characterize dust mineralogy; however, this technique is less effective for identifying poorly crystalline or amorphous phases. We used Fourier Transform Infrared (FTIR) spectroscopy as a complementary method to identify minerals and their abundances. Long wave infrared (LWIR) spectra (2.5 to 25 μm) are sensitive to molecular bonds rather than crystallography providing additional details. We performed both XRD and reflectance spectroscopy to characterize 37 atmospheric dust samples collected in Ilam City, Iran. The dominant minerals in these samples are quartz, feldspar (albite), calcite and clays (illite, montmorillonite, kaolinite). LWIR reflectance is strongly dependent on particle size but published data of pure silicate minerals in the size range of the Ilam samples (0-63 μm) still show characteristic signatures between 8 and 10 µm (Salisbury et al. 1991; Wenrich and Christensen, 1996). Surprisingly, diagnostic silicate features were not observed in any of the samples although carbonate and OH bonds in the clay minerals were readily identified. Past studies have shown that porosity, grain size and packing can reduce the spectral contrast in the LWIR and additional effects include grain coatings or the interaction of multiple minerals. We also identify a peak at 7.8 µm which may be attributed to anomalous dispersion or the interaction of quartz and calcite in this spectral range. In order to understand the absence of Si-O features we made transmission measurements of representative samples in KBr pellets. Transmission is not influenced by multiple scattering and should clearly detect fundamental Si-O absorptions. Transmission spectra show broad features that include contributions from all silicate minerals (quartz, feldspar and clays) both near 10 μm and at longer wavelengths. We are using various spectral modeling techniques and will compare abundances derived from reflectance and transmission measurements.

Mineral dust particles originate from a variety of arid regions around the world. Mineral dust directly modifies the 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 global dust source regions. Previously, 65 surface soil samples were collected worldwide, sieved to < 38 μm fraction and analyzed using XRD, SEM and re-suspended to determine scattering and absorption coefficients at three visible wavelengths (Engelbrecht et al. Atmos. Chem. Phys. 16, 2016). This dust collection represents global surface soils with comparable mineral compositions to windblown dust. For this research, we measured spectra of 26 of these samples selected from major dust source regions with compositional diversity. We measured these samples using laboratory reflectance spectroscopy in the visible and near-infrared (0.4 to 2.5 μm, VNIR) and long-wave infrared (2.5 to 25 μm, LWIR). These data are relevant to satellite imaging spectrometers, but will particularly inform measurements planned for EMIT and SBG. We compared the measured spectra to standard spectral libraries to identify dominant materials and to compare and contrast these with the major minerals identified via XRD. VNIR spectral analysis detected diagnostic absorptions for minerals such kaolinite, calcite, hematite, and goethite. Common silicates, quartz and feldspar, are abundant in the majority of these samples and are expected to have diagnostic features in the LWIR. LWIR reflectance is strongly dependent on particle size (e.g. Salisbury et al., 1991), though the 0-74 μm grain size fraction of pure silicate minerals still show characteristic signatures between 8 and 10 µm. Surprisingly, diagnostic silicate features were not observed in many of the samples. We identified quartz absorptions between 4.8 and 5.4 μm and at 14.3 μm. We are still trying to understand why the fundamental vibrational features of silicates are obscured, but it may be related to multiple overlapping features in mixtures, grain coatings, or anomalous dispersion. LWIR spectra also revealed numerous diagnostic carbonate features, particularly those near 4, 5.6, and 11.4 μm. We also identified carbonate in several samples where it had not been identified with XRD.