Major eruptive style changes induced by structural modifications of a shallow conduit system: the 2007–2012 Stromboli case

Calvari, Sonia; Bonaccorso, Alessandro; Madonia, Paolo; Neri, Marco; Liuzzo, Marco; Salerno, Giuseppe; Behncke, B.; Caltabiano, Tommaso; Cristaldi, Antonio; Giuffrida, Giovanni; Spina, Alessandro La; Marotta, Enrica; Ricci, T.; Spampinato, Letizia

doi:10.1007/s00445-014-0841-7

Cited by 52 publications

(84 citation statements)

References 63 publications

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“…In the figure, we compare our lidar-based CO 2 fluxes with independent estimates, in which the CO 2 flux was derived by multiplying the CO 2 /SO 2 ratio of the plume by the SO 2 flux. This latter approach has been used at volcanoes for years (Aiuppa, 2015), and at Stromboli involves use of two fully automated Multi-GAS instruments, operating on the volcano's summit to measure the in-plume CO 2 /SO 2 ratio (Figure 2A; Aiuppa et al, 2009Aiuppa et al, , 2010aCalvari et al, 2014). This is combined with SO 2 fluxes, delivered from either the FLAMES network of scanning UV spectrometers (Burton et al, 2009) or from UV camera observations (Tamburello et al, 2012), to obtain the CO 2 flux.…”

Section: Discussionmentioning

confidence: 99%

New Advances in Dial-Lidar-Based Remote Sensing of the Volcanic CO2 Flux

et al. 2017

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We report here on the results of a proof-of-concept study aimed at remotely sensing the volcanic CO 2 flux using a Differential Adsorption lidar (DIAL-lidar). The observations we report on were conducted in June 2014 on Stromboli volcano, where our lidar (LIght Detection And Ranging) was used to scan the volcanic plume at ∼3 km distance from the summit vents. The obtained results prove that a remotely operating lidar can resolve a volcanic CO 2 signal of a few tens of ppm (in excess to background air) over km-long optical paths. We combine these results with independent estimates of plume transport speed (from processing of UV Camera images) to derive volcanic CO 2 flux time-series of ≈16-33 min temporal resolution. Our lidar-based CO 2 fluxes range from 1.8 ± 0.5 to 32.1 ± 8.0 kg/s, and constrain the daily averaged CO 2 emissions from Stromboli at 8.3 ± 2.1 to 18.1 ± 4.5 kg/s (or 718-1565 tons/day). These inferred fluxes fall within the range of earlier observations at Stromboli. They also agree well with contemporaneous CO 2 flux determinations (8.4-20.1 kg/s) obtained using a standard approach that combines Multi-GAS-based in-plume readings of the CO 2 /SO 2 ratio (≈8) with UV-camera sensed SO 2 fluxes (1.5-3.4 kg/s). We conclude that DIAL-lidars offer new prospects for safer (remote) instrumental observations of the volcanic CO 2 flux.Keywords: volcanic CO 2 , DIAL-lidar, Stromboli, remote sensing, CO 2 flux INTRODUCTION A major step forward in ground-based volcano monitoring has recently arisen from the advent of modern instrumental techniques and networks for volcanic gas observations (Galle et al., 2010;Oppenheimer et al., 2014;Saccorotti et al., 2014;Fischer and Chiodini, 2015). Such technical advances provide improved temporal resolution relative to traditional direct sampling techniques (Symonds et al., 1994;Giggenbach, 1996). As longer-term volcanic gas records increase in number and quality, full empirical evidence is finally emerging for increased CO 2 flux emissions prior to eruption of mafic to intermediate volcanoes (Aiuppa, 2015). Precursory plume CO 2 flux increases have been now detected at several volcanoes, including Etna (Aiuppa et al., 2008;Patanè et al., 2013), Kilauea (Poland et al., 2012), Redoubt (Werner et al., 2013), Turrialba (de Moor et al., 2016a), and Poas (de Moor et al., 2016b).At Stromboli (in Italy), however, CO 2 flux observations have been particularly valuable for interpreting, and eventually predicting, the volcano's behavior (Aiuppa et al., 2010a Stromboli, the "regular" mild strombolian activity is occasionally interrupted by larger-scale vulcanian-style explosions, locally referred as "major explosions" or (in the most extreme events) "paroxysms" (Rosi et al., 2006(Rosi et al., , 2013Andronico and Pistolesi, 2010;Pistolesi et al., 2011;Pioli et al., 2014). These explosions, although short-lived (tens of seconds to a few minutes), represent a real hazard for local populations, tourists and volcanologists, since they produce fallout of coarse pyroclastic materials over w...

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Section: Discussionmentioning

confidence: 99%

New Advances in Dial-Lidar-Based Remote Sensing of the Volcanic CO2 Flux

et al. 2017

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“…Debris cone material likely reached the sea, but tsunami waves were not recorded. Growth stages of this debris talus at Stromboli are a common phenomenon related to the explosive activity, which produces accumulation of volcaniclastic debris around the active craters (Calvari et al 2014). Contrariwise, the roto-translational slides occurred at the onset of the [2002][2003]2007 and 2014 flank eruptions, characterized by magma propagation from the central conduit towards the NEC (Di Traglia et al 2014Traglia et al , 2015.…”

Section: Stromboli Debris Talus Roto-translational Slidementioning

confidence: 99%

Guidelines on the use of inverse velocity method as a tool for setting alarm thresholds and forecasting landslides and structure collapses

et al. 2016

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Predicting the time of failure is a topic of major concern in the field of geological risk management. Several approaches, based on the analysis of displacement monitoring data, have been proposed in recent years to deal with the issue. Among these, the inverse velocity method surely demonstrated its effectiveness in anticipating the time of collapse of rock slopes displaying accelerating trends of deformation rate. However, inferring suitable linear trend lines and deducing reliable failure predictions from inverse velocity plots are processes that may be hampered by the noise present in the measurements; data smoothing is therefore a very important phase of inverse velocity analyses. In this study, different filters are tested on velocity time series from four case studies of geomechanical failure in order to improve, in retrospect, the reliability of failure predictions: Specifically, three major landslides and the collapse of an historical city wall in Italy have been examined. The effects of noise on the interpretation of inverse velocity graphs are also assessed. General guidelines to conveniently perform data smoothing, in relation to the specific characteristics of the acceleration phase, are deduced. Finally, with the aim of improving the practical use of the method and supporting the definition of emergency response plans, some standard procedures to automatically setup failure alarm levels are proposed. The thresholds which separate the alarm levels would be established without needing a long period of neither reference historical data nor calibration on past failure events.

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“…Unrests at Stromboli are characterized by changes in the background activity of the volcano in terms of frequency and intensity of the Strombolian explosions. On average, during the background activity, the explosions occur at a rate of \10 events/hour, shifting to a rate of [14 events/hour during unrests (measured by thermal cameras, Calvari et al 2014). This shift is commonly associated with changes in the features of the erupted products Houghton 2005, 2007;D'Oriano et al 2011) and in the parameters monitored by the geophysical (Casagli et al 2007;Ripepe et al 2009;Calvari et al 2014;Coppola et al 2012;Di Traglia et al 2014b) and geochemical monitoring network (Aiuppa et al 2009(Aiuppa et al , 2011Inguaggiato et al 2011).…”

Section: Geological and Volcanological Backgroundmentioning

confidence: 99%

“…Time series data were synthesized to daily displacement values spanning from January 1, 2010, to August 7, 2014. Data from Di Traglia et al ( , 2014aTraglia et al ( , b, c, 2015 revealed that remarkable inflation of the crater terrace area occurred in three different periods ( Similarly, three periods of volcanic unrest were defined by several authors based on the observation of intense volcanic activity (Coppola et al 2012;Calvari et al 2014;Di Traglia et al 2014a, b, c, 2015Rizzo et al 2015;Calvari et al 2016):…”

Section: The Gbinsar Systemmentioning

confidence: 99%

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A statistical-based approach for determining the intensity of unrest phases at Stromboli volcano (Southern Italy) using one-step-ahead forecasts of displacement time series

2016

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The evaluation of the intensity of unrest phases at active volcanoes is a crucial topic in volcano hazard studies. This is particularly troublesome in the case of persistently active volcanoes like Stromboli (Southern Italy), where intense eruptive summit activity (overflows, strong spattering, powerful explosions) has in some cases anticipated a flank eruption. In this context, a new approach for the analysis of displacement data is introduced. Daily displacements of the Stromboli crater terrace measured between January 1, 2010, and August 7, 2014, by a ground-based interferometric synthetic aperture radar system were compared, in retrospect, to displacement predictions provided by an autoregressive integrated moving average-based model. The methodology consisted in assessing when the actual displacements exceeded a fixed probability threshold for the forecasts (*95 %). Two sets of data were consequently produced: (1) series of residuals between actual displacements and model threshold (''anomalies'') and (2) series of normalized residuals between actual displacements and model threshold (''normalized anomalies''). This permitted to statistically identify and quantify the anomalous deformation at the crater terrace over the reference time interval of the analysis. Anomalies started to occur before each period of intense volcanic activity, highlighting the possibility to discern between background activity and unrest. Moreover, results indicated that the inflation of the crater terrace during the preparatory phase of the 2014 flank eruption was characterized by the greatest amount of anomalous deformation.

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Major eruptive style changes induced by structural modifications of a shallow conduit system: the 2007–2012 Stromboli case

Cited by 52 publications

References 63 publications

New Advances in Dial-Lidar-Based Remote Sensing of the Volcanic CO2 Flux

New Advances in Dial-Lidar-Based Remote Sensing of the Volcanic CO2 Flux

Guidelines on the use of inverse velocity method as a tool for setting alarm thresholds and forecasting landslides and structure collapses

A statistical-based approach for determining the intensity of unrest phases at Stromboli volcano (Southern Italy) using one-step-ahead forecasts of displacement time series

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