Journal
GEOLOGY
Volume 39, Issue 9, Pages 891-894Publisher
GEOLOGICAL SOC AMER, INC
DOI: 10.1130/G32016.1
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Funding
- FIRB-MIUR (Fondo per gli Investimenti della Ricerca di Base, Ministero dell'Istruzione, dell'Universita e della Ricerca)
- European Union [235338]
- Bundesexzellenzinitiative
- European Research Council
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The recent Eyjafjallajokull (Iceland) eruption strikingly underlined the vulnerability of a globalized society to the atmospheric dispersal of volcanic clouds from even moderate-size eruptions. Ash aggregation controls volcanic clouds dispersal by prematurely removing fine particles from the cloud and depositing them more proximally. Physical parameters of ash aggregates have been modeled and derived from ash fallout deposits of past eruptions, yet aggregate sedimentation has eluded direct measurement, limiting our ability to predict the dispersal of volcanic clouds. Here we use field-based, highspeed video analysis together with laboratory experiments to provide the first in situ investigation and parameterization of the physical features and settling dynamics of ash aggregates from a volcanic cloud. In May 2010, high-speed video footage was obtained of both ash particles and aggregates settling from the Eyjafjallajokull volcano eruption cloud at a distance of 7 km from the vent; fallout samples were collected simultaneously. Experimental laboratory determinations of the density, morphology, and settling velocity of individual ash particles enable their distinction from aggregates. The combination of field and experimental analyses allows a full characterization of the size, settling velocity, drag coefficient, and density distributions of ash aggregates as well as the size distribution of their component particles. We conclude that ash aggregation resulted in a tenfold increase in mass sedimentation rate from the cloud, aggravating the ash hazard locally and modifying cloud dispersal regionally. This study provides a valuable tool for monitoring explosive eruptions, capable of providing robust input parameters for models of cloud dispersal and consequent hazard forecast.
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