Aggregation processes are known to play an important role in volcanic particle dispersal and sedimentation. They are also a primary source of uncertainty in ash dispersal forecasting since fundamental questions, such as the timing and deposition dynamics of volcanic aggregates, still remain unanswered. Here, we applied a state-of-the-art combination of field and numerical strategies to characterize volcanic aggregates. We introduce a new category of aggregates observed with high-speed-high-resolution videos, namely cored clusters. Cored clusters are mostly sub-spherical fragile aggregates that have never been observed in the deposits nor on adhesive tape as they typically break at impact with the ground. They consist of a core particle (200–500μm) fully covered by a thick shell of particles < 90μm. The low preservation potential of cored clusters in ash deposits explains the poor documentation in the literature and the low consideration attributed so far. Cored clusters can also better explain the deposition of fine ash in proximal and medial regions and the polymodality observed in many ash deposits. In addition, numerical inversions show how cored clusters can rapidly form within 175s from eruption onset. Finally, our observations represent the first field-based evidence of the so-called rafting effect, in which the sedimentation of coarse ash in cored clusters is delayed due to aggregation

During explosive eruptions, emergency responders and government agencies need to make fast decisions that should be based on an accurate forecast of tephra dispersal and assessment of the expected impact. Here, we propose a new operational tephra fallout monitoring and forecasting system based on quantitative volcanological observations and modelling. The new system runs at the Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo (INGV-OE) and is able to provide a reliable hazard assessment to the National Department of Civil Protection (DPC) during explosive eruptions. The new operational system combines data from low-cost calibrated visible cameras and satellite images to estimate the variation of column height with time and model volcanic plume and fallout in near-real-time (NRT). The new system has three main objectives: (i) to determine column height in NRT using multiple sensors (calibrated cameras and satellite images); (ii) to compute isomass and isopleth maps of tephra deposits in NRT; (iii) to help the DPC to best select the eruption scenarios run daily by INGV-OE every three hours. A particular novel feature of the new system is the computation of an isopleth map, which helps to identify the region of sedimentation of large clasts (≥5 cm) that could cause injuries to tourists, hikers, guides, and scientists, as well as damage buildings in the proximity of the summit craters. The proposed system could be easily adapted to other volcano observatories worldwide. medium lapilli has been widely considered as a primary risk agent related to explosive volcanic activity, fallout of coarse lapilli to small blocks falling from plume margins has been underrated. As an example, during the event at Etna on 23 November 2013, clasts from several centimeters to decimeters fell within 5-6 km from the summit and hit hikers who were in the touristic areas [8]. Although the assessment of tephra fallout and dispersal in distal areas has been largely considered [9][10][11][12], the reduction of volcanic impacts in proximal areas and within the first hour from the beginning of the eruption is still a challenge. As a matter of fact, regardless of the importance of this information for emergency responders and government agencies, the operational systems capable of monitoring tephra dispersal and fallout in near-real-time (NRT) and returning the expected impact assessment are still limited and not fully adapted to the growing requirements of precision and reliability.A good example of NRT tephra detection in volcano observatories is represented by the Alaska Volcano Observatory (AVO), which monitors volcanoes within the North Pacific region [13]. The AVO system analyzes data from different satellite sensors. They use a 24/7 automated ash cloud detection algorithm that sends emails and phone text alerts to the AVO members, who are, in turn, responsible for verifying if the automatic alert can be considered as true or false [13]. The Kamchatka Volcanic Eruption Response Team (KVERT) monitors 36 active volcanoes in ...

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The process of particle aggregation significantly affects ash settling dynamics associated with volcanic explosive eruptions. Several experiments have been carried out to investigate the physics of ash aggregation and dedicated numerical schemes have been developed to produce more accurate forecasting of ash dispersal and sedimentation. However, numerical description of particle aggregation is complicated by the lack of complete datasets on natural samples required for model validation and calibration. Here we present a first comprehensive dataset for the internal structure, aerodynamical properties (e.g., size, density, terminal velocity) and grain size of constituting particles of a variety of aggregate types collected in the natural laboratory of Sakurajima Volcano (Japan). Even though the described particle clusters represent the most common types of aggregates associated with ash-rich fallouts, they are of difficult characterization due to the very low potential of preservation in tephra-fallout deposits. Properties were, therefore, derived based on a combination of high-resolution-highspeed videos of tephra fallout, scanning electron microscope analysis of aggregates collected on adhesive paper and analysis of tephra samples collected in dedicated trays. Three main types of particle clusters were recognized and quantitively characterized: cored clusters (PC3), coated particles (PC2), and ash clusters (PC1) (in order of abundance). A wide range of terminal velocities (0.5-4 m/s) has been observed for these aggregates, with most values varying between 1 and 2 m/s, while aggregate size varies between 200 and 1,200 µm. PC1, PC2, and PC3 have densities between 250 and 500, 1,500 and 2,000, and 500 and 1,500 kg/ m 3 , respectively. The size of the aggregate core, where present, varies between 200 and 750 µm and increases with aggregate size. Grain size of tephra samples was deconvoluted into a fine and a coarse Gaussian subpopulation, well correlated with the grain size of shells and of the internal cores of aggregates, respectively. This aspect, together with the revealed abundance of PC3 aggregates, reconciles the presence of a large amount of fine ash (aggregate shells) with coarse ash (aggregate cores) and better explains the grain size distribution bimodality, the high settling velocity with respect to typical PC1 velocities and the low settling velocities of large aggregates with respect to typical PC2 velocity. Furthermore, ash forming the aggregates was shown to be always finer than 45 µm, confirming the key role played by aggregation processes in fine ash deposition at Sakurajima.

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