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OTETNA: Onset Times of eruptive events at ETNA (flank eruptions since 1600 CE, summit paroxysms from 1986 to 2022 CE)
No full textThe two csv files contain the onset times of the Mt Etna eruptive events, divided into "FLANK ERUPTIONS" and "SUMMIT PAROXYSMS". The two files cover a different time window.
In particular:
- File OnsetTimes_flank.csv is a 1-column csv file containing the year (Current Era, CE) of the known flank eruptions since 1600 CE, taken from Proietti and Branca (2024).
- File OnsetTimes_paroxysm.csv is a 6-column csv file containing the year (CE), the month, the day, and, when known, the hour, the minutes and the seconds, of the known summit paroxysms from Andronico et al. (2021), Calvari et al. (2018), Calvari and Nunnari (2022) and Mereu et al. (2023). This file covers the time period 1986-2022 CE.
The files have been obtained by collating data available in the literature.
References:
- Andronico, D., Cannata, A., Di Grazia, G., and Ferrari, F.: The 1986–2021 paroxysmal episodes at the summit craters of Mt. Etna: Insights into volcano dynamics and hazard, Earth-Science Reviews, 220, 103 686, https://doi.org/https://doi.org/10.1016/j.earscirev.2021.103686, 2021.
- Calvari, S. and Nunnari, G.: Comparison between Automated and Manual Detection of Lava Fountains from Fixed Monitoring Thermal Cameras at Etna Volcano, Italy, Remote Sens., 14, 2392, https://doi.org/10.3390/rs14102392, 2022.
- Calvari, S., Cannavò, F., Bonaccorso, A., Spampinato, L., and Pellegrino, A. G.: Paroxysmal Explosions, Lava Fountains and Ash Plumes at Etna Volcano: Eruptive Processes and Hazard Implications, Front. Earth Sci., 6, 107, https://doi.org/10.3389/feart.2018.00107, 2018.
- Mereu, L., Scollo, S., Garcia, A., Sandri, L., Bonadonna, C., and Marzano, F. S.: A New Radar-Based Statistical Model to Quantify Mass Eruption Rate of Volcanic Plumes, Geophys. Re. Lett., https://doi.org/10.1029/2022GL100596, 2023.
- Proietti, C. and Branca, S.: Dataset of Etna's flank eruptive fissures of the last 4000 years, https://doi.org/10.5281/zenodo.14284932, 2024
NonLinLoc high-precision earthquake location catalog for Mount Etna (2000-2024) (Etna_NLL_SC_2000-2024)
No full textHigh-precision earthquake locations are indispensable for a wide range of seismological studies, including seismic hazard assessment, fault rupture process analysis and subsurface structural imaging.
Here we present a catalog of high-precision relocated volcano-tectonic earthquakes, recorded by the seismic network managed by Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo (INGV-OE) from 2000 to 2024 and originating on Etna volcano area.
To perform hypocentral location we adopt the NLL-SSST-coherence (NLL-SC; Lomax et al., 2022) probabilistic non-linear location method. NLL-SC is an advanced location method designed to improve precision across multiple scales. This is achieved through the correction of seismic wave travel times and the analysis of waveform similarity.
We produced a 24-year catalog of hypocentral locations for Etna volcano, representing a previously unexplored dataset using high-precision location techniques.
This comprehensive dataset not only will contribute to understanding the seismic behaviour of Etna volcano but also will plays a key role in ongoing monitoring and scientific research related to volcanic activity in the region.The NLL-SC method (Lomax & Savvaidis, 2022; Lomax et al, 2024) improves earthquake location by refining hypocenter accuracy. Based on the NonLinLoc (NLL) algorithm, a probabilistic global search technique, it estimates earthquake hypocenters using three-dimensional probability density functions (PDFs).
A key component of this method is the application of Source-Specific Station Term (SSST) corrections, which iteratively refine travel-time estimates to minimize biases from velocity model inaccuracies. Additionally, Waveform Coherence Relocation utilizes waveform similarities between nearby events to improve relative locations, enhancing the clustering of seismic events.
By integrating these approaches, the NLL-SC method produces a more precise and internally consistent earthquake catalog, providing valuable insights into the seismotectonic processes and structural characteristics of Etna volcano area.The dataset, used as input for the new hypocentral locations consists of approximately 22,000 earthquakes recorded in the Mount Etna region from 2000 to 2024, covering a geographical area defined by latitudes 37.5°N to 37.9°N and longitudes 14.7°E to 15.3°E.
The seismic network operating during this long time period underwent several technical upgrades. From 2000 to 2024, the network transitioned from a sparse configuration primarily equipped with short-period (1s) analog sensors to a significantly denser network featuring exclusively three-component digital sensors (40s and 120s). This evolution resulted in an enhanced detection capability, enabling a minimum local magnitude (ML) threshold of approximately 0.2 to be achieved in certain areas (Ferrari et al., 2024).
The present new catalog reports, for each earthquake, different parameters as the origin time in Coordinated Universal Time (UTC), the hypocentral coordinates (latitude N and longitude E), the depth of the earthquake in kilometres b.s.l., the local magnitude (ML) and the moment magnitude (MW) as derived from Saraò et al., 2023. Additional parameters such as the number of stations used for location (NO), the root mean square of residuals (RMS), and the horizontal and vertical location errors (ERH and ERZ) are also reported together with P and S- wave arrival times.
Earthquake location accuracy through the NLL-SC method is directly dependent on the quality of the initial velocity model. For this analysis, we have adopted a smooth, 1D velocity model derived from the 1D model used at INGV-OE for monitoring purposes (see Lomax et al., 2024 and references therein).
The configuration of NLL-SC used here follows closely that of Lomax et al. (2024)
Logs of water temperature and electric conductivity of the piezometric network of the Strait of Messina area (Italy)
No full textLogs of water temperature and electric conductivity of the Strait of Messina piezometric networkHanna HI98494 multiparametric probe.
Resolution:
Temperature: 0.01 °C;
Electric conductivity: 0.001 mS/cm up to 10 mS/cm; 0.01 ms/cm up to 100 mS/cm.Structure of the Excel file:
Sheet Geographic coordinates contains piezometer ID, longitude, latitude, elevation and date of survey.
Other sheets, each named with the piezometer ID contain Depth, wtaer temperature and electric conductivity data
Earthquake Locations in the Etna Volcano using a 3D velocity model during 2005-2024 (EtnaEQ3D_2005-2024)
No full textThis catalogue presents the seismicity recorded in the Etna volcano area by the INGV-OE seismic network between 01 January 2005 and 31 December 2024. During this period, local magnitudes (ML) ranged from 0.1 to 4.8. Events were selected with at least six observations, root-mean-square time residuals (RMS) ≤ 0.50 s at the stations, and horizontal (ERH) and vertical (ERZ) location uncertainties ≤ 5.0 km.The earthquake dataset was relocated using the tomoDDPS algorithm (Zhang et al., 2009), applying a three-dimensional velocity model developed through the integration of both passive and active seismic data (Firetto Carlino et al., 2022), in order to enhance the precision of hypocentral determinations. Earthquakes' initial parameters were derived from Alparone et al. (2015, 2020a, 2020b, 2022) and Barberi et al. (2020). The tomoDDPS benefits from combining absolute travel times with differential arrival-time measurements between pairs of nearby seismic events, which follow nearly identical propagation paths to a common station. As these paths are essentially the same, any variation in arrival times can be reliably linked to the relative positions of the events in space.
The application of 3D relocation led to a more defined clustering of seismicity and produced a reduction in travel-time residuals between observed and computed data by about 37%, with a mean residual of 0.014 seconds. The final hypocentral locations show horizontal and vertical uncertainties of less than 0.8 km.
The hypocenters of 474 events were located above sea level, very close to the topographic surface. Since their depth could not be reliably constrained, we fixed them at the topographic elevation—which falls within the depth uncertainty range—and marked these in the notes field.The table (EtnaEQ3D_2005-2024) shows the origin time and the hypocentre parameters of locations. Specifically: ID= identification number; Date (day- month-year); Origin Time (hour, minute, second and cent); Lat = latitude north in degrees; Long = longitude east in degrees; Depth in km; ML= local magnitude; Notes=depth fixed at the topographic elevation
Meteorological dataset from INGV station at Messina headquarter
No full textoai:oedatarep-invenio-rdm.com:8n5p0-71p16Half hourly data of atmospheric pressure, air temperature and relative humidity, rainfall amountMeteorological station composed of:
1. Onset Hobo RX 2100 station - cell -4G.
2. Onset Hobo Temperature/RH 16 bit Smart Sensor, -40 °C to 75 °C (T), 0 to 100% (RH), 0.02 °C / 0.01% RH resolutions
3. Davis 0.2 mm raingauge 12 bit Smart Sensor, 0.2 mm resolution
4. Onset Hobo 12 bit Smart Barometric Pressure Sensor, 660 to 1070 mbar range, 0.1 mbar resolutionStructure of the Excel file:
Column A. Date Time (GMT+1) expresses as DD/MM/YY hh:mm
Column B. Atmospheric Pressure (hPa)
Column C. Air Temperature (°C)
Column D. Air Relative Humidity (%)
Column E. Rainfall amount (mm
Earthquake Locations in southern Tyrrhenian Sea and northern Sicily using a 3D velocity model between 1 January 2000 and 31 August 2021 (STyrr_EQ3D_2000-2021)
No full textWe computed new 3D locations for 8003 earthquakes (0.6≤M≤5.6) that occurred in the southern Tyrrhenian Sea and northern Sicily between 1 January 2000 and 31 August 2021. The events were recorded by the land seismic network managed by the INGV and a seafloor network, consisting of 14 Ocean Bottom Seismometers and Hydrophones, deployed during the Tyrrhenian Deep sea Experiment (TYDE, December 2000 – May 2001; Dahm et al., 2002; Sgroi et al., 2006) and the NEMO-SN1 seafloor observatory (October 2002 – February 2003; June 2012 - June 2013; Sgroi et al. 2021).We collected basic data (travel times) from available datasets (ISIDe Working Group, 2007) and published studies (Sgroi et al., 2006; Barberi et al., 2006; Monna et al., 2013) and processed them using the 3D velocity model of Scarfì et al. (2018) and the tomoDDPS algorithm (Zhang et al., 2009). This software has the advantage of using a combination of both absolute and differential arrival times, so that for earthquakes with closely spaced foci, travel times errors due to inaccurate velocity models in the volume outside the cluster will essentially be cancelled.
Furthermore, for 116 events, magnitude values were not available because they were located only using the seafloor network. We assigned them the value 999 and added the note "magnitude not available" in the notes field.The table (STyrr_EQ3D_2000-2021) shows the origin time and the hypocentre parameters of locations. Specifically: ID = identification number; Date (year/month/day); O.T. = Origin Time (hour, minute, second and cent); Lat = latitude north in degrees; Long = longitude east in degrees; Depth in km; MagType = duration (Md), local (ML) or moment magnitude (Mw); Magnitude; Notes = magnitude not available
Catalog of Long Period seismic events recorded at Mt. Etna during the time interval 2019-2020 (LPSEC2019_2020)
No full textThe dataset consists of Long Period (LP) seismic events recorded on Etna volcano in the time interval 1/January/2019 – 30/June/2020. The catalog includes 62052 events, each identified by the picking time to the triggering station. Beside the picking time, peak-to –peak amplitude and peak frequency parameters are also reported. The detection of the event is obtained by means of an automated system operating in near real-time that implements an energy detector. In particular, the processing system applies an STA/LTA trigger algorithm (Short-Time Average/ Long-Time Average; e.g., Trnkoczy, 2012; Sciotto et al., 2022) to the continuous seismic signal filtered in the frequency band 0.5 – 5 Hz. Seismic stations used for the detection are installed at altitudes between 2.85 – 3.04 km a.s.l. and at distance that ranges between 1 and 2.5 km from central craters of Mt. Etna. To reduce false detections and make more robust the catalog, only located LP events are included. It is noteworthy to say that amplitude variations of the volcanic tremor can mask amplitude transients and affect the LP occurrence rate. From a volcanological point of view, during the time interval January –August 2019, Etna experienced a period of intermittent intra-crateric Strombolian activity, weak ash emission or isolated explosions from the summit craters. From September 2019 and until the end of the time interval, together with an increase of volcanic tremor amplitude, this eruptive activity became almost continuous at Voragine crater and South-East crater area (see Sciotto et al., 2022 for details). LP events at Mt. Etna volcano are frequently recorded and their occurrence rate, spectral and amplitude time variation are likely to be associated with the plumbing system shallowest portion conditions (e.g., Patanè et al., 2008; Cannata et al., 2015; 2018)
Focal Mechanisms in southern Tyrrhenian Sea and northern Sicily between 1 January 2000 and 31 August 2021 (STyrr_FM_2000-2021)
No full textWe computed new 268 focal mechanisms (1.3≤M≤4.6), with rays traced through the 3D velocity model of Scarfì et al. 2018, of events occurred in the southern Tyrrhenian Sea and northern Sicily between 1 January 2000 and 31 August 2021. The earthquakes were recorded by the land seismic network managed by the INGV and a seafloor network, consisting of 14 Ocean Bottom Seismometers and Hydrophones, deployed during the Tyrrhenian Deep sea Experiment (TYDE, December 2000 – May 2001; Dahm et al., 2002; Sgroi et al., 2006) and the NEMO-SN1 seafloor observatory (October 2002 – February 2003; June 2012 - June 2013; Sgroi et al. 2021).We collected basic data (travel times and first polarities) from available datasets (ISIDe Working Group, 2007) and published studies (Sgroi et al., 2006; Barberi et al., 2006; Monna et al., 2013). Then we processed them using the 3D velocity model of Scarfì et al. (2018) and the tomoDDPS algorithm (Zhang et al., 2009). This software has the advantage of using a combination of both absolute and differential arrival times, so that for earthquakes with closely spaced foci, travel times errors due to inaccurate velocity models in the volume outside the cluster will essentially be cancelled. By using FPFIT software (Reasenberg and Oppenheimer, 1985), we obtained 268 focal solutions with an average uncertainty on the orientation of the nodal planes of about 10°. These focal mechanisms can be considered representative of the kinematics characterising the southern Tyrrhenian Sea and the northern Sicily, since they are distributed in all the main seismogenically active areas of the region.The table (STyrr_FM_2000-2021) shows focal parameters of the analysed earthquakes. Specifically: ID = identification number; Date (year/month/day); O.T. = Origin Time (hour, minute, second and cent); Lat = latitude north in degrees; Long = longitude east in degrees; Depth in km; MagType = duration (Md), local (ML) or moment magnitude (Mw); Magnitude; Npol = number of polarities; Plane 1 (STRK, DIP, RAKE), Plane 2 (STRK, DIP, RAKE) = strike, dip and rake of the first and second nodal planes; P-Axis (AZM, PLNG), T-Axis (AZM, PLNG) = azimuth and plunge of the P- and T-axes; Q = quality of the focal mechanism (2 = best quality; 1 = medium quality; 0 = low quality); Cat = category of the focal mechanism (NF = normal fault, NS = normal-strike, SS = strike-slip, TF = thrust fault, TS = thrust-strike, HV = horizontal-vertical)
Etna CO2 Soil Flux 2011-2020 (ECSF 2011_2020)
No full textThe ETNAGAS network comprises 19 monitoring stations distributed across the flanks of Mount Etna, specifically designed for the continuous observation of soil-emitted carbon dioxide (CO₂). Each station is equipped with infrared (IR) sensors for the precise measurement of CO₂ concentrations, along with meteorological sensors that record key environmental parameters including air temperature, atmospheric pressure, wind speed and direction, and precipitation. These data enable the estimation of CO₂ soil fluxes through the application of the method proposed by Gurrieri and Valenza (1988) (see Methods for details). The ETNAGAS network represents a high-resolution geochemical surveillance system and constitutes an integral component of the national framework for monitoring volcanic gas emissions. Its primary objective is to contribute to the assessment of the volcanic activity state of Mount Etna through systematic and spatially distributed measurements of gaseous emissions.The monitoring stations of the ETNAGAS network were entirely developed by the Istituto Nazionale di Geofisica e Vulcanologia (INGV), Palermo section. These stations are capable of continuously measuring several environmental and geochemical parameters, including soil CO₂ concentration, atmospheric temperature, pressure, relative humidity, rainfall, wind speed, and wind direction. Data are acquired at hourly intervals and automatically transmitted to the monitoring center at INGV-Palermo. It should be noted that not all stations are equipped with the full suite of meteorological sensors.
CO₂ fluxes from the soil can be derived from the recorded data using the dynamic (or dilution) method described by Gurrieri and Valenza (1988). This method is based on measuring the CO₂ content in a mixture of soil gas and atmospheric air (Cd), obtained using a probe inserted approximately 50 cm into the ground. Soil gases enter the probe through its base and are mixed with ambient air; this mixture is then pumped into an infrared (IR) spectrophotometer, which measures the CO₂ concentration.
According to Gurrieri and Valenza, the measured diluted concentration (Cd) is empirically related to the actual soil CO₂ flux (ϕCO₂) through a relationship established under laboratory conditions, across a range of gas permeabilities (0.36–123 mm²) and pumping flow rates (0.4–4.0 L/min) [Camarda et al., 2006a, 2006b].
REFERENCE
• Camarda, M., S. Gurrieri, and M. Valenza (2006a), CO2 flux measurements in volcanic areas using the dynamic concentration method: Influence of soil permeability, J. Geophys. Res., 111, B05202, doi:10.1029/2005JB003898. Camarda, M., S. Gurrieri, and M. Valenza (2006b), In situ permeability measurements based on a radial gas advection model: Relationships between soil permeability and diffuse CO2 degassing in volcanic areas, Pure Appl. Geophys., 163(4), 897–914, doi:10.1007/s00024-006-0045-y.
• Gurrieri, S., and M. Valenza (1988), Gas transport in natural porous mediums: A method for measuring CO2 flows from the ground in volcanic and geothermal areas, Rend. Soc. Ital. Mineral. Petrol., 43, 1151–1158.
• Gurrieri, S., M. Liuzzo, and G. Giudice, (2008), Continuous monitoring of soil CO2 flux on Mt. Etna: The 2004–2005 eruption and the role of regional tectonics and volcano tectonics, J. Geophys. Res., 113, B09206, doi:10.1029/2007JB005003, 2008.
• Liuzzo M., Gurrieri S., Giudice G. & Giuffrida G. (2013) - Ten years of soil CO2 continuous monitoring on Mt. Etna: Exploring the relationship between processes of soil degassing and volcanic activity. Geochem. Geophys. Geosyst., 14, 2886-2899. https://doi. org/10.1002/ggge.2019
Earthquake Locations in the Peloritani Mountains and Aeolian Archipelago (NE Sicily) using a 3D velocity model during 2011-2023 (PelAeolianEQ3D_2011-2023)
No full textThis catalogue presents the seismicity selected from the database of the Istituto Nazionale di Geofisica e Vulcanologia (Alparone et al., 2023; Barberi et al., 2020; https://www.ingv.it/risorse-e-servizi/archivi-e-banche-dati), focusing on shallow crustal events (≤40 km depth) recorded from January 2011 to December 2023. Only earthquakes with at least six observations were included. During this period, local magnitudes (ML) ranged from 0.0 to 4.6.The earthquake dataset was relocated using the tomoDDPS double-difference algorithm (Zhang et al., 2009) and a 3D velocity model derived by the integration of passive and active seismic data (the last acquired during the "TOMO-ETNA experiment", FP7 "MED-SUV", Barberi et al., 2018), to improve accuracy in hypocentre localization. The algorithm combines both absolute and differential arrival-time readings from pairs of closely spaced earthquakes, having the same velocity profile along the ray-path between source and a common receiver. Since the spatial and velocity paths are nearly identical, differences in arrival times can be attributed solely to the spatial offset between seismic events. Applying the 3D relocation method resulted in a more refined clustering of seismicity, reducing travel-time residuals by approximately 59%, with a mean residual of 0.03 seconds. The final hypocentral locations show horizontal and vertical uncertainties of approximately 0.12 ± 0.05 km and 0.17 ± 0.08, respectively.The table (PelAeolianEQ3D_2011-2023) shows the origin time and the hypocentre parameters of locations. Specifically: ID = identification number; Date (day-month-year); Origin Time (hour, minute, second and cent); Lat = latitude north in degrees; Long = longitude east in degrees; Depth in km; ML = local magnitude