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Reference data set of volcanic ash physicochemical and optical properties
Author(s) -
Vogel A.,
Diplas S.,
Durant A. J.,
Azar A. S.,
Sunding M. F.,
Rose W. I.,
Sytchkova A.,
Bonadonna C.,
Krüger K.,
Stohl A.
Publication year - 2017
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/2016jd026328
Subject(s) - volcano , volcanic ash , rhyolite , context (archaeology) , mineralogy , basalt , wavelength , mass concentration (chemistry) , geology , igneous rock , volcanic rock , materials science , geochemistry , chemistry , paleontology , optoelectronics
Uncertainty in the physicochemical and optical properties of volcanic ash particles creates errors in the detection and modeling of volcanic ash clouds and in quantification of their potential impacts. In this study, we provide a data set that describes the physicochemical and optical properties of a representative selection of volcanic ash samples from nine different volcanic eruptions covering a wide range of silica contents (50–80 wt % SiO 2 ). We measured and calculated parameters describing the physical (size distribution, complex shape, and dense‐rock equivalent mass density), chemical (bulk and surface composition), and optical (complex refractive index from ultraviolet to near‐infrared wavelengths) properties of the volcanic ash and classified the samples according to their SiO 2 and total alkali contents into the common igneous rock types basalt to rhyolite. We found that the mass density ranges between ρ = 2.49 and 2.98 g/cm 3 for rhyolitic to basaltic ash types and that the particle shape varies with changing particle size ( d < 100 μm). The complex refractive indices in the wavelength range between λ = 300 nm and 1500 nm depend systematically on the composition of the samples. The real part values vary from n = 1.38 to 1.66 depending on ash type and wavelength and the imaginary part values from k = 0.00027 to 0.00268. We place our results into the context of existing data and thus provide a comprehensive data set that can be used for future and historic eruptions, when only basic information about the magma type producing the ash is known.