Airborne Measurement in the Ash Plume from Mount Sakurajima: Analysis of Gravitational Effects on Dispersion and Fallout. (19th October 2014)

• Record Type: Journal Article
• Authors: Eliasson, Jonas; Yoshitani, Junichi; Weber, Konradin; Yasuda, Nario; Iguchi, Masato; Vogel, Andreas
• Other Names: Cairo Francesco Academic Editor.
• Is Part Of: International journal of atmospheric sciences. Volume 2014(2014)
• Publication Date: 2014-10-19
• Subjects: Atmospheric physics -- Periodicals; Atmospheric chemistry -- Periodicals; Atmospheric chemistry; Atmospheric physics; Periodicals; Electronic journals; 551.5
• DOI: 10.1155/2014/372135
• Languages: English
• ISSNs: 2314-4122

Abstract

Abstract : Volcanic ash concentrations in the plume from Sakurajima volcano in Japan are observed from airplanes equipped with optical particle counters and GPS tracking devices. The volcano emits several puffs a day. The puffs are also recorded by the Sakurajima Volcanological Observatory. High concentrations are observed in the puffs and fallout driven by vertical air current, called streak fallout. Puffs dispersion is analyzed by the classical diffusion-advection method and a new gravitational dispersion method. The fluid mechanic of the gravitational dispersion, streak fallout, and classical diffusion-advection theory is described in three separate appendices together with methods to find the time gravitational dispersion constant and the diffusion coefficient from satellite photos. The diffusion-advection equation may be used to scale volcanic eruptions so the same eruption plumes can be scaled to constant flux and wind conditions or two eruptions can be scaled to each other. The dispersion analyses show that dispersion of volcanic plumes does not follow either theories completely. It is most likely diffusion in the interface of the plume and the ambient air, together with gravitational flattening of the plumes core. This means larger boundary concentration gradients and smaller diffusion coefficients than state of the art methods can predict.