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17 results for “pyroclasts”
Field data collected from pyroclastic and lahar deposits of the 472 AD (Pollena) and 1631 Vesuvius eruptions
<p><strong><span>Field data collected from pyroclastic and lahar deposits of the 472 AD (Pollena) and 1631 Vesuvius eruptions</span></strong></p> <p><span>Mauro A. Di Vito<sup>1</sup>, Ilaria Rucco<sup>2</sup>, Sandro de Vita<sup>1</sup>, Domenico M. Doronzo<sup>1</sup>, Marina Bisson<sup>3</sup>, Elena Zanella<sup>4</sup></span></p> <p><sup><span>1</span></sup><span> Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Vesuviano, Napoli, Italy</span></p> <p><sup><span>2</span></sup><span> Heriot-Watt University, School of Engineering and Physical Sciences, Edinburgh, United Kingdom</span></p> <p><sup><span>3</span></sup><span> Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Pisa, Pisa, Italy</span></p> <p><sup><span>4</span></sup><span> Università di Torino, Dipartimento di Scienze della Terra, Torino, Italy</span></p> <p><span> </span></p> <p><span>This dataset is organized in an Excel file, and it includes all the data collected and reviewed during the last 20 years from drill cores, outcrops, archaeological excavations, stratigraphic trenches, and the existing literature. It focuses on the primary (pyroclastic) and secondary (lahar) deposits of the 472 AD (Pollena) and 1631 eruptions from the Somma-Vesuvius volcano. The aim is to collect stratigraphic, stratimetric, sedimentological, lithological and chronological data to generate distribution maps and to validate the numerical simulations and models for the risk assessment. In particular, this dataset is complementary to – and in support of – the full work by Di Vito et al. (2024), in which the distribution of those deposits all around the Somma-Vesuvius complex and further is presented and discussed. Such dataset was used to inform the shallow-water model of lahars by de’ Michieli Vitturi et al. (2024), which in turns was used by Sandri et al. (2024) to elaborate probabilistic maps of lahar invasion in the Somma-Vesuvius and Apennine areas.</span></p> <p><span>All the data are organized in columns: the first four aim to identify the sites, and so there is a numeric identification code (ID), the name of the site (NAME), and the metric coordinates (East-North) in the UTM WGS 84 – Zone 33 reference projection (X, Y). The last two columns are “MUNICIPALITY” and “PROVINCE” and give a spatial location to the points.</span></p> <p><span>For the two eruptions, several columns have been created:</span></p> <p><span><span>·<span> </span></span></span><span>“472_PRIM”, “1631_PRIM” and “472_ASH” and “1631_ASH” indicate, respectively, the fallout primary deposits of the eruptions and the primary ash, particularly the ash related to the last phases of the eruptions (generally phreatomagmatic).</span></p> <p><span><span>·<span> </span></span></span><span>“472_SYN” and “1631_SYN” indicate the syn-eruptive lahars related to the two eruptions, recognized from the similar composition between the primary deposit and the lahar and from the evidence of a short-term exposure between the two.</span></p> <p><span><span>·<span> </span></span></span><span>“472_POST” AND “1631_POST” indicate the post-eruptive lahars related to the two eruptions. They are considered “post” when in the deposit there are pumices belonging to older eruptions, indicating their involvement in the progressive erosion of the slopes and valleys, and when there is evidence of long periods without deposition, such as the presence of</span><span> </span><span>slightly humified surfaces or traces of human artifacts (excavations, ploughing).</span></p> <p><span><span>·<span> </span></span></span><span>“EROSION_fallout_472” refers to the sites where it was possible to find erosional unconformities between the pyroclastic deposit of the 472 AD eruption and the lahar, as well as between the lower and upper lahar flow units. The erosional features are for example the lack of one or more primary eruptive layers (eroded by the overlying deposit), a change in the granulometry, or lateral discontinuity of the deposit. </span></p> <p><span><span>·<span> </span></span></span><span>“Pdyn (kPa)”, “v (m/s)”, “C (%)” and “T” are all the parameters quantified to validate the numerical models and to assess the hazard from lahars. Pdyn is the flow dynamic pressure, which represents the capability of the flow to entrain a clast, and it depends on the velocity (v) and the flow density, which in turn results from a combination of the density of the particles and the water through the “C (%)”, that is the particle volume concentration. To calculate the flow dynamic pressure and the velocity, the parameters taken into account are the dimensions of the biggest clasts and the nature of the clasts (limestone, ceramic, brick, tephra, lava, sandstone, iron) found in the lahar deposits. The concentration is estimated considering some sites in which the flow expands in correspondence with some obstacles (for example a Roman wall). This can be assumed to be the initial height of the flow before the emplacement. Finally, “T” refers to the estimated deposition temperature of the deposit quantified by the magnetic analysis, in particular in some sites where the lahar interacted with anthropogenic structures.</span></p> <p><span><span>·<span> </span></span></span><span>“DEPOSIT (472)” indicates the type of lahar deposit (syn- or post-eruptive) of the 472 AD eruption in which the fragments were found.</span></p> <p><span><span>·<span> </span></span></span><span>“MULTIPLE LAHAR UNITS” indicates the sites in which multiple flow units are vertically identified in the lahar deposits. They are generally a result of rapid and progressive aggradation of multiple flow pulses, each one resulting from single-pulse “en masse” emplacement</span><span>.</span></p>
Database of pyroclastic cover deposit thickness measurements (PT-Cam) in peri-volcanic areas of Campania (Italy)
<p>In an eruptive event, tephra deposits (i.e. ash and pumice) disperse in the atmosphere and deposit on the ground surface according to the speed and direction of the wind. Because the geotechnical and hydraulic properties of the unconsolidated pyroclastic fall deposits usually differ from the bedrock, their spatial thickness significantly influences geomorphological and hydrogeological processes such as landscape evolution, erosion, landslide, and hillslope hydrogeology.</p> <p>The PT-Cam database presents the thickness of tephra deposits (i.e. the unconsolidated materials over the bedrock) in Campania region (Italy), measured through in-situ investigations of some territories around the Somma-Vesuvius, Campi Flegrei, Roccamonfina, and Ischia volcanoes during the last decades. The measurements were conducted with probing tests, dynamic penetration tests, trenches, man-made pits, seismic surveys, and outcrops.</p> <p>Explanation for database attribute:</p> <ul> <li>CODE: identification code of the measurement;</li> <li>z: measured thickness expressed in cm;</li> <li>type_z: thickness type (i.e. if investigation has reached to the bedrock the type is “total” otherwise it is “partial”);</li> <li>type_investigation: method of in-situ investigation;</li> <li>locality: municipality to which the measurement point belongs;</li> <li>Longitude, Latitude: km coordinates in UTM WGS 84 system.</li> </ul>
Data for "Multi-band Spectropolarimetric Image Data of Lunar Maria, Pyroclastics, Fresh Craters, and Swirl Materials"
<p>This data repository contains the georeferenced spectropolarimetric data analyzed in the following article:</p> <p>Wöhler, C., Arnaut, M., Bhatt, M., 2024. Multi-band Spectropolarimetry of Lunar Maria, Pyroclastics, Fresh Craters, and Swirl Material. Astronomical Journal, accepted for publication.</p> <p>The data products are available in separate .zip archives in GEOTIFF and BSQ format. Each .zip archive contains data from eight different observations:</p> <table> <tbody> <tr> <td>Dataset</td> <td>Date</td> <td>UT time</td> <td>Phase angle</td> </tr> <tr> <td>20221114_WOP</td> <td>Nov 14th, 2022</td> <td>05:20</td> <td>64°</td> </tr> <tr> <td>20221216_WOP</td> <td>Dec 16th, 2022</td> <td>04:10</td> <td>88°</td> </tr> <tr> <td>20230225_AT</td> <td>Feb 25th, 2023</td> <td>19:20</td> <td>108°</td> </tr> <tr> <td>20230227_AT</td> <td>Feb 27th, 2023</td> <td>21:44</td> <td>85°</td> </tr> <tr> <td>20230228_AT</td> <td>Feb 28th, 2023</td> <td>19:33</td> <td>74°</td> </tr> <tr> <td>20230302_MV</td> <td>Mar 2nd, 2023</td> <td>19:03</td> <td>52°</td> </tr> <tr> <td>20230302_AT</td> <td>Mar 2nd, 2023</td> <td>19:10</td> <td>52°</td> </tr> <tr> <td>20230402_AT</td> <td>Apr 2nd, 2023</td> <td>20:03</td> <td>38°</td> </tr> </tbody> </table> <p> </p> <p>Data products of spectropolarimetric image analysis in GEOTIFF and BSQ format<br>=============================================================================</p> <p>Prefix 1: Date of data acquisition (YYYYMMDD)<br>Prefix 2: Area (WOP: Western Oceanus Procellarum; MV: Mare Vaporum; AT: Atlas)</p> <p>F : image intensity (5 bands) [DN]<br>P : degree of linear polarization (DoLP) (5 bands)<br>W : angle of linear polarization (AoLP) (5 bands) [degrees]<br>GS : relative grain size (5 bands)<br>logGS: logarithm of relative grain size (5 bands)<br>UE : across-band Umov exponent (1 band)<br>UEres: residual of across-band Umov exponent (1 band)<br>PCAP : scores on the first three principal components derived from the DoLP (3 bands) <br>PCAW : scores on the first three principal components derived from the AoLP (3 bands)<br>CIM : cluster index map (1 band)</p> <p><br>The longitude ranges of the maps are as follows:</p> <p>WOP: Longitude=[-70 -35], Latitude=[2 33]<br>MV : Longitude=[-13 12], Latitude=[-2 17]<br>AT : Longitude=[35 60], Latitude=[40 55]</p> <p>All maps are in simple cylindrical projection with a resolution of 30 pixels per degree.</p> <p>The CIM maps are provided in uint8 numerical format.<br>All other maps are provided in single-precision (32-bit) floating point numerical format.<br>The BSQ files are in binary format without header. Matlab example:<br>BSQ=multibandread('20230302_AT_P__Latitude_35_60__Latitude_35_60.bsq',[750 750 5],'single',0,'bsq','ieee-le');</p> <p> </p>
Vapor bubbles and velocity control on the cooling rates of lava and pyroclasts during submarine eruptions
<p>These dataset contains videos (.mp4) of experiments and the time-temperature data (.txt) measured during the experiments. Each video starts when the sample is completely submerged in the water. The temperature data represents the full experimental duration, where a spike in water temperature data to about 27 deg C on average indicates the synchronization process between the video and the data. </p>
Text-fig. 3. Distribution of main types of volcanoes in the NearShore Volcanic Belt of Eastern Sikhote-Alin' (Eocene–Neogene). 1 – Central volcanoes (partly preserved); 2 – Central volcanoes (destructed); 3 – Shield and gentle sloping volcanoes with a dolerite or trachy-basaltic neck on the top; 4 – Lava and scoria cones; 5 – Pyroclastic, tuffaceous coarse- and fine-grained terrigenous sedimentary rocks, partly with plant-bearing levels; 6 – Eruption centers of plateau-basalts and the direction of lava flows; 7 – Main Late Cenozoic basaltic plateaus; 8 – Fumarol fields; 9 – Hot springs. in Mid-Latitude Palaeogene Floras Of Eurasia Bound To Volcanic Settings And Palaeoclimatic Events - Experience Obtained From The Far East Of Russia (Sikhote-Alin') And Central Europe (Bohemian Massif)
Text-fig. 3. Distribution of main types of volcanoes in the NearShore Volcanic Belt of Eastern Sikhote-Alin' (Eocene–Neogene). 1 – Central volcanoes (partly preserved); 2 – Central volcanoes (destructed); 3 – Shield and gentle sloping volcanoes with a dolerite or trachy-basaltic neck on the top; 4 – Lava and scoria cones; 5 – Pyroclastic, tuffaceous coarse- and fine-grained terrigenous sedimentary rocks, partly with plant-bearing levels; 6 – Eruption centers of plateau-basalts and the direction of lava flows; 7 – Main Late Cenozoic basaltic plateaus; 8 – Fumarol fields; 9 – Hot springs.
Text-fig. 3. Textures of main volcaniclastic deposits exposed in abandoned Ludvíkovice quarry. a: radial cracks surrounding some boulders (see arrows) in hot lahar deposit. b: jig-saw fit of fractures (see arrows) within a mega-block of debris-avalanche deposit. c: pseudo-fiamme texture of compacted argillized pumice-fall deposit. d: trachybasaltic lapilli-stone of phreato-magmatic eruption. e: palaeo-relief developed and buried within the pyroclastic unit. f: diagonal bedding in fluvial volcanigenic sandstones. g: diluted and fine-grained lahars embedded in volcanigenic sandstones. in A New Oligocene Flora From Ludvíkovice Near Děčín (České Středohoří Mts., The Czech Republic)
Text-fig. 3. Textures of main volcaniclastic deposits exposed in abandoned Ludvíkovice quarry. a: radial cracks surrounding some boulders (see arrows) in hot lahar deposit. b: jig-saw fit of fractures (see arrows) within a mega-block of debris-avalanche deposit. c: pseudo-fiamme texture of compacted argillized pumice-fall deposit. d: trachybasaltic lapilli-stone of phreato-magmatic eruption. e: palaeo-relief developed and buried within the pyroclastic unit. f: diagonal bedding in fluvial volcanigenic sandstones. g: diluted and fine-grained lahars embedded in volcanigenic sandstones.
Datasets for "Dynamics and deposits of pyroclastic density currents in magmatic and phreatomagmatic eruptions revealed by a two-layer depth-averaged model"
<p>Dataset for the manuscript entitled "Dynamics and Deposits of Pyroclastic Density Currents in Magmatic and Phreatomagmatic Eruptions Revealed by a Two-Layer Depth-Averaged Model" by H. A. Shimizu, T. Koyaguchi, and Y. J. Suzuki for submission in Geophysical Research Letter. This contains datasets for each run.</p>
Thermomagnetic and thermal demagnetization data from lithic clasts in pyroclastic density current deposits emplaced during the 1980 eruption at Mt. St. Helens
<p>This dataset includes thermomagnetic and thermal demagnetization data from lithic clasts collected within pyroclastic density current deposits of the 1980 eruption at Mt. St. Helens. All magnetic measurements were performed at the Paleomagnetic Laboratory of the University of Roma Tre.</p> <p>The susceptibility vs temperature curves (thermomagnetic_data.zip) and stepwise thermal demagnetization data (MSH*.zip, where * denotes the sampling site) can be both viewed with Notepad or similar programs, and analyzed via the Cureval and Remasoft software, respectively (downloadable at: https://www.agico.com).</p> <p>Thermomagnetic_data.zip contains the baseline FUR10_18, which should be subtracted to the susceptibility values of each sample.</p>
Data for the article "The Apparent Absence of Kilometer-sized Pyroclastic Volcanoes on Mercury: Are We Looking Right? "
<p>This file contains numerical data which has been used for generation of Figure 1, 2 and 3 in the paper "The Apparent Absence of Kilometer-sized Pyroclastic Volcanoes on Mercury: Are We Looking Right?"</p> <p>The profiles in files associated with Figure 3 are provided for the volume of 4.2 km<sup>3</sup>.</p>
Dataset and Software: Heat Transfer in Pyroclastic Density Current - Ice Interactions: Insights from Experimental and Numerical Simulations
<p>This repository contains experiment data and executable MATLAB codes for the research article 'Heat Transfer in Pyroclastic Density Current - Ice Interactions: Insights from Experimental and Numerical Simulations'.</p> <p>Contained within the experiment data file Valeetal_Data.Zip are:</p> <ul> <li>Temperature, melt and steam data separated by particle type. See files: <ul> <li>Ballotini_Data_Valeetal</li> <li>Pumice_Data_Valeetal</li> <li>Ruapehu_Data_Valeetal</li> </ul> </li> <li>Melt and steam summary data plots. See file: <ul> <li>Data_Plots_Valeetal</li> </ul> </li> <li>Document with figures to demonstrate system behaviours. See file: <ul> <li>Valeetal_SI01_JGR</li> </ul> </li> </ul> <p>Contained within the model data file Model_Repository.zip are simulation data and codes that implement, process, and plot numerical solutions to the mathematical model. See README.txt for a brief description of each file.</p> <p> </p>
Coupled monitoring of soil moisture and suction in pyroclastic air-fall silty soils
<p>The dataset contains the experimental field data coming from the automatic monitoring of the annual hydrological response of a shallow deposit in loose pyroclastic soils located in a mountainous area of Campania, Southern Italy. The monitoring station is installed at about 650 m a.s.l. along the northern slope of mount Cornito, about 2 km east of the town of Cervinara, that in December 1999 was involved in a rainfall-induced flowslide. The collected field data consist in: i) precipitations (measured by a rain gauge), ii) soil moisture contents (measured by TDR probes) and iii) soil matric suctions (measured by “Jet-fill” tensiometers). Suction and moisture sensors have been installed at the same depths and connected to a Campbell Scientific Inc. CR-1000 Data Logger, that allows the automatic acquisition and storage of data.</p> <p>Furthermore, the results of some laboratory flume tests carried out on a small-scale slope, reconstituted with volcanic ashes from the same site and from a nearby slope, subjected to an artificial rainwater infiltration, are attached too. Soil matric suction and moisture content were respectively measured by a miniaturised tensiometer and a TDR probe installed close to each other.</p>
Experimental modelling of tsunamis generated by pyroclastic density currents: the effects of particle size distribution on wave generation
<p><strong>Data set for experimental videos modelling the entrance of a fluidised granular flow into the water.</strong></p> <p>The data set includes:</p> <ul> <li>a MATLAB script to calculated theoretical volume and density of a non-fluidised mixture.</li> <li>Properties of the fluidised granular flows on the fluidising ramp: volume, density, thickness, flow and impact Froude numbers, kinetic energy of the fluidised flows.</li> <li>Properties of the surface elevation: surface elevation at x = 1.6m away from the shoreline, velocity of the leading wave, maximum/minimum amplitudes, potential energy of the generated waves and the energy transfer between the flow and the water column.</li> <li>Properties of the underwater gravity current - displacement, velocity and thickness of the underwater velocity current.</li> <li>a MATLAB script to visualise the surface elevation.</li> </ul>
The fragmentation-induced fluidization of pyroclastic density currents - dataset
<p>These are the data behind the study entitled "The Fragmentation-Induced Fluidization of Pyroclastic Density Currents".</p>
Supplementary figures for Stationary surface waves and antidunes in dense pyroclastic density currents
<p>Supplementary files for EarthArXiv submission</p>
Hydraulic hysteresis of unsaturated pyroclastic soils: experimental investigation and model calibration
<p>In many geotechnical applications, especially in the study of weather-induced landslides, a reliable soil hydraulic characterization under unsaturated conditions is required. Currently, the experimental techniques neglecting hydraulic hysteresis represent the greatest limitation to landslide forecasting. Here, experimental data from a new procedure to obtain an unsaturated soil hydraulic characterization are reported. These allows us to evaluate the soil hydraulic properties not only along the main drying path but also along wetting/drying cycles. Pyroclastic soil samples collected at a test site located at Mount Faito in the Campania region (southern Italy) were tested. The experimental investigation consisted of a forced evaporation test followed by a number of wetting-drying cycles. </p>
Spontaneous Unsteadiness and Sorting in Pyroclastic Density Currents and their Deposits - Data
<p>Dataset accompanying Spontaneous Unsteadiness and Sorting in Pyroclastic Density Currents and their Deposits, in <em>Particulate Gravity Currents in the Environment.</em></p> <p> </p> <p>Raw experiment images and videos for selected runs. Run list included as csv file, with links to externally hosted videos.</p>
Calibration of TDR probes for water content measurements in partially saturated pyroclastic slope
<p>The file contains raw and processed data. The raw data consists of measurements of the soil dielectric constant and the soil samples weight. The data was processed in order to relate the soil dielectric constant to the soil volumetric water content. The calibrated relations are also found in the file.</p>
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