Linear unmixing of fine particulate materials: implications for compositional analyses of primitive asteroids

<p>Linear least squares unmixing of infrared spectra is a fast and effective way to spectrally estimate the modal mineral abundances of laboratory samples and remotely-sensed surfaces to within 5% on average [e.g., 1]. This technique has been applied to spectra of whole rocks, coarse particulates, meteorites, and the Martian surface to successfully determine modal abundances [e.g., 1-3]. With the recent arrival of NASA’s OSIRIS-REx spacecraft to asteroid 101955 Bennu, the OSIRIS-REx Thermal Emission Spectrometer (OTES) has been providing a wealth of data to interpret using spectral unmixing techniques [e.g., 4].</p> <p>The assumption of linear spectral unmixing allows for the deconvolution of a mixed spectrum if the individual spectra and particle sizes of the pure end members are present within a spectral library. By implementing a weighted linear least squares (WLS) unmixing algorithm, one is able to deconvolve these mixed spectra into areal percentages of each endmember with the underlying assumption that this then corresponds to the volume percentages [e.g., 1-3]. At thermal infrared (TIR) wavelengths, end member spectra of coarse particulates combine linearly due to high absorption coefficients and relatively small mean optical paths, which limits most of the volumetric scattering [e.g., 1-3]. Linearity in the TIR region continues as particle size decreases until the wavelength of light approaches the particle size, at this point particles become optically thin and non-linear behavior (e.g., volumetric scattering) is observed. However, Ramsey and Christensen [1] demonstrated that when unmixing fine particulates (10 – 20 μm) with a spectral library of end members at the same particle size linear unmixing can still be used to estimate modal mineral abundances.</p> <p>In this study we investigate the effectiveness of a linear least squares unmixing approach to estimate mineral abundances for samples dominated by fine particulates (< 38 μm). We use a WLS algorithm and a spectral library of fine particulate pure minerals to unmix spectra of a suite of fine particulate, primitive asteroid analogs. Results from this investigation have implications for the interpretation of spectral observations of primitive asteroids that have a layer of fine particulate regolith.</p> <p>[1] Ramsey M. S. and Christensen P. R. (1998) JGR, 103, 577-596. [2] Hamilton V. E. and Christensen P. R. (2000) JGR, 105, 9717-9733. [3] Rogers A. D. and Aharonson O. (2008) JGR, 113,EO6S14. [4] Hamilton V. E. et al. (2019) Nature Astron., 3, 332-340.</p>

Seasonal variation in concentration and metallic constituents of atmospheric particulates near the western coast of central Taiwan

In addition to determining the concentration and metallic constituents of particulate matter at Taichung Harbor in central Taiwan, this study attempts to characterize the mass, metallic elements, composition and concentrations of total suspended particulates (TSP), fine particles and coarse particles. Statistical approaches, such as the Spearman tests, were also adopted to determine the seasonal variations of concentrations of these pollutants. Experimental results indicate that the mean TSP, fine particulate and coarse particulate concentrations in spring and winter are higher than in summer and autumn on the western coast of central Taiwan. Spearman statistical analysis of metallic elements Mn and Pb showed high concentration coefficients for fine and coarse particulates on the western coast of central Taiwan. The order of mean metallic concentrations in TSP, coarse particulates and fine particles was Fe-Zn-Mg-Cu-Cr-Mn-Pb in TSP, Fe-Cu-Zn-Mg-Mn-Pb-Cr in coarse particulates and Fe-Cu-Mg-Pb-Zn-Mn-Cr in fine particulates.