Linking the IR transmittance to size and type of volcanic ash particles

Abstract

AbstractIn this work, we applied infrared spectroscopy to investigate the spectral signature of the volcanic ash particles emitted during the 21–24 July 2001 eruption at Mount Etna, in Italy. We used a Bruker Equinox‐55 Fourier transform infrared spectrometer in the range 7000–600 cm−1 (1.43–16.67 µm) and, for every collected spectrum, an image of the volcanic ash particles was recorded in the visible spectral range through the same microscope. These images were then analyzed by standard image analysis software in order to evaluate the main features of the particle: the length of the major and minor axes (Max and Min L), Feret diameter (FD), equivalent diameter (ED), and aspect ratio (AR). We measured transmission spectra in different conditions; spectra of one single particle (Single‐Particle Measurement, SPM), spectra of a number of particles from two to ten (Multi‐Particle Measurements type 1, MPM1) and of more than a hundred particles (Multi‐Particle Measurements type 2, MPM2). For SPM, Max and Min L range between 5 and 24 µm and 3.5 and 15 µm, FD ranges between 5.5 and 25 µm, ED varies between 5 and 19 µm, and AR between 0.45 and 0.95. For MPM1 and MPM2, the mean values of Max and Min L are between 4–17 µm and 3–10 µm, FD and ED between 5 and 19 µm and 3.5 and 23 µm, and AR between 0.3 and 1. The optical depth spectra as a function of the wave number clearly show the presence of the Christiansen effect that produces high transmission at a given frequency in the infrared region (Christiansen frequency). We find that the effect depends on the particle size through a linear relation. Both the Christiansen effect and their relationship with the ash particle effective radius were compared with radiative transfer model simulations using different ash refractive indexes. The combined use of the linear relationship and the spectral position of the Christiansen frequency also indicated the possibility to characterize ash type. All these information can be used to improve the IR remote sensing volcanic ash quantitative estimations.