Paroxysmal Explosions, Lava Fountains and Ash Plumes at Etna Volcano: Eruptive Processes and Hazard Implications

Introduction

Lava fountains are a mixture of liquid clots and droplets (the pyroclasts) and magmatic gases (H₂O, CO₂, SO₂, CH₄, N₂O, HCl, HF, and CO, in order of decreasing abundance; Allard et al., 2005). They are generated when large volumes of volatiles rapidly exsolve from the magma during its ascent and decompression along the conduit (Wilson et al., 1995). The mixture of gas and pyroclasts emerges from the vent as a jet (Wilson et al., 1995), expanding vertically into an eruptive column, where three main regions can be identified. The lowest portion is the gas-thrust region, and comprises the lava fountains (Sparks et al., 1997; Bonaccorso and Calvari, 2017). Measured ascent velocities in this region are normally greater than 15 m s⁻¹ (Patrick, 2007; Patrick et al., 2007; Sahetapy-Engel and Harris, 2009), and for Etna vary between 33 and 125 m s⁻¹ (Calvari et al., 2011; Carbone et al., 2015; Giuffrida et al., 2018), but values of 170, 227, and 405 m s⁻¹ have been measured at Montserrat, Sakurajima, and Stromboli volcanoes, respectively (Clarke et al., 2002; Taddeucci et al., 2012; Tournigand et al., 2017). Above the gas-thrust is the convective region, where atmospheric mixing occurs (Sparks et al., 1997; Bombrun et al., 2018), causing a decrease in ascent velocity and lateral wind transport (Carey and Sparks, 1986). The uppermost portion is the umbrella region, where the volcanic plume reaches the zone of neutral buoyancy and spreads out laterally (Carey and Sparks, 1986; Bonadonna and Phillips, 2003). Within the buoyant umbrella region, plume rise rates are less than 15 m s⁻¹ (Patrick, 2007; Patrick et al., 2007). Volcanic plume dynamics depend closely on the interaction with the atmospheric wind field. They are classified as strong or weak depending on whether the characteristic plume rise velocity is greater or much smaller than the cross wind speed, respectively (Carey and Sparks, 1986). Thus, strong plumes vertically rise (Figure 1A), while weak plumes tend to bend over in the downwind direction (Figure 1C) which then start spreading sub-horizontally around the neutral buoyancy level (Carey and Sparks, 1986; Bonadonna and Phillips, 2003). The plume shape has significant effects on the forecast of the fallout area, which is ideally distributed all around the vent in the case of a strong plume and zero wind, and elongated downwind for a weak plume and strong wind. The stronger the wind, the narrower the resulting fallout region from the plume (Andronico et al., 2009). Interestingly enough, the wind speed has important effects not just on the fine-grained portion of the plume, but even on the bombs and ballistics, being able to transport large ejecta for several kilometers down wind, causing damage to cars, solar panels, and windows (Andronico et al., 2015). It is difficult to univocally forecast plume height because it is related to the conditions and properties of the erupting system, such as magma discharge rate (Carey and Sparks, 1986), exsolved volatiles from magma, magma/water interaction (Schmith et al., 2018), and vent geometry (either elongated fissure or near-circular conduit; Wilson and Head, 1981; Wilson et al., 1995). Given that discharge rate and ultimately erupted volume have been measured from the lava fountain height (Calvari et al., 2011; Carbone et al., 2015; Bonaccorso and Calvari, 2017), there must be a direct connection between lava fountain height and maximum plume elevation, although this last parameter is also affected by wind speed (e.g., Bonadonna et al., 2015).

Paroxysmal explosive basaltic activity, especially when occurring at frequently erupting volcanoes, can have a strong impact on the population, air traffic and public health (Andronico et al., 2008, 2009; Martin et al., 2009; Baxter, 2010; Horwell et al., 2017). During 2011–2015, Mt. Etna volcano produced 49 paroxysmal lava fountain episodes, evolving into volcanic plumes that spread for more than 9 km above sea level (a.s.l.) into the atmosphere, and with ash fallout as far as hundreds of km from the vent (e.g., Dellino and Kyriakopoulos, 2003; Azzopardi et al., 2013; Athanassiadou, 2016). It is thus of paramount importance to monitor this activity and analyse the data with the aim of developing routines or tools that might be useful for hazard assessment and impact prediction (Cannavò et al., 2017).

This paper seeks to analyse the data recorded during Etna's recent lava fountaining episodes in order to find possible relationships between measurable parameters. We have used images from the network of fixed thermal and visual cameras installed on the volcano slopes by the Istituto Nazionale di Geofisica e Vulcanologia-Osservatorio Etneo (INGV-OE), and gathered from these several parameters such as lava fountain height, exit velocity, duration of the episode, erupted volume and plume height. Among these, estimates of tephra fall volume are of paramount importance for hazard assessment and risk mitigation during future explosive events, since they are typically based on eruption intensity (eruption rate) and magnitude (total erupted mass; Walker, 1980).

We present an analysis of 44 of the 49 paroxysmal episodes occurring at Etna between 2011 and 2015; the remaining 5 could not be analyzed due to poor visibility from the ground cameras. We have used thermal and visual images recorded by the monitoring network of fixed cameras installed by INGV-OE (Andò and Pecora, 2006; Coltelli et al., 2017) to gather information about the total erupted mass and eruption rate of each episode. We have statistically analyzed the dimensional parameters extracted from the monitoring cameras, such as height of the lava fountain and ash plume vs. time, duration of each episode, erupted volume of pyroclastics (obtained from the camera images) and of lava flows (taken from available published data), time-averaged discharge rate (TADR, here referred only to the pyroclastic portion of the erupted material; Harris et al., 2007) and maximum exit velocities of both the lava fountain and plume. Following Harris et al. (2007), instantaneous effusion rate (IER) is the discharge rate from a vent averaged over a smaller unit of time when compared to TADR, which we consider as averaged over the whole duration of the explosive event. We carried out a rigorous correlation analysis on the measured parameters and tried to find a link among parameters.

Etna's Eruptive Activity

Before 2010, lava fountain episodes at Mt. Etna (Figures 1, 2) were an exceptional activity, normally preceding major flank eruptions, such as those in 1991-93, 2000-01, and 2002-03 (Calvari et al., 1994, 2001; Andronico et al., 2005; Andronico and Corsaro, 2011). However, between January 2011 and December 2013, a sequence of 44 such events occurred from a pit on the east flank of the South-East Crater (SEC), one of the four summit craters of Etna (Figure 2b). This activity built up a new summit cone (the New South-East Crater, NSEC, Figure 2b; Behncke et al., 2014; De Beni et al., 2015), but no major flank eruptions have followed this activity yet. Bonaccorso and Calvari (2013) explained this apparent paradox by the balance between intruded and extruded magma, which at Etna volcano has been found steady during the last 3–4 decades (Wadge and Guest, 1981; Harris et al., 2011, 2012). This steady output can result either in a few, high-output rate effusive phases, or in several, low-output rate lava fountain events (Bonaccorso and Calvari, 2013). Whatever the cause, it is clear that paroxysmal explosive activity at Etna is becoming increasingly common, thus requiring a greater effort to forecast its possible evolution.

Lava fountains are always associated with ash plumes, often disrupting the air traffic and driveability on the main highway along the east coast of Sicily, where frequent winds blow the ash and cause problems not only to traffic but also public health, agriculture, aviation, and building stability (Andronico et al., 2008; Martin et al., 2009; Baxter, 2010; Horwell et al., 2017). Eruptive columns and ash plumes, associated with the lava fountains, cause a more widespread fallout of ash transported well beyond the boundaries of Sicily and southern Italy and into Greece (Dellino and Kyriakopoulos, 2003) and Malta (Azzopardi et al., 2013).

Lava Fountaining From NSEC, 2011–2013

The 44 lava fountain (LF) episodes at the NSEC between 2011 and 2013 were preceded by deep magma uprising (Del Negro et al., 2013). We distinguished three main phases, separated by two long eruptive pauses (Table 1). The first phase lasted from 11 January 2011 to 24 April 2012, and comprised 25 LF events displaying similar features. These are: duration of the Strombolian phase preceding the paroxysmal episode (hours to days); duration of the LF event (hours); maximum height of the LF (800–1,500 m); extension of the lava flow field associated with the explosive event (1–4 km; Behncke et al., 2014); and erupted volume of pyroclastics and lava flows (~2.5 × 10⁶ m³; Calvari et al., 2011; Gouhier et al., 2012; Bonaccorso and Calvari, 2013). The first eruptive pause lasted from April 2012 to February 2013 (Table 1). During this pause, only mild and intermittent eruptive activity within the Bocca Nuova summit crater (BN; Figure 2b) occurred between July and October 2012, producing a small cinder cone and lava flow field within its crater (Cannata et al., 2015; Slatcher et al., 2015; Spampinato et al., 2015). During the period preceding the second LF phase, ground deformation data from the permanent GPS network revealed an inflation of the volcano due to the pressurization of its plumbing system (e.g., Bruno et al., 2016), whereas gas fluxes showed that no volatile-rich magma was supplied to the shallow (1–2 km below sea level, b.s.l.) volcano feeding system (Spampinato et al., 2015). This suggested that the BN eruptive activity was produced by magma already residing within the shallow plumbing system (Spampinato et al., 2015). A depressurization of the plumbing system was observed when LF activity resumed again in 19 February 2013 (Table 1), giving rise to the second eruptive phase that lasted until 27 April 2013, producing 13 additional events (Cannata et al., 2015; Spampinato et al., 2015; Bruno et al., 2016). There was another eruptive pause between April and the end of October 2013, followed by six additional paroxysmal explosive events until the end of that year. This last and third phase was very different from the previous, and comprised the most explosive end-member of the series, occurring on 23 November 2013 (Bonaccorso et al., 2014; Andronico et al., 2015; Carbone et al., 2015; Corradini et al., 2016; Montopoli, 2016). This very short but violent paroxysm produced an exceptionally high LF of over 2.5 km above the crater, and was the only one at the NSEC that did not produce lava flows (Bonaccorso et al., 2014). The third phase also displayed a unique episode (26 October 2013, Table 1) during which two craters were erupting together, with the North-East Crater (NEC) producing an ash column that flanked that of the NSEC (Andronico et al., 2018, this volume). As a result of the proximal accumulation of ballistics from the LF around the vent, a new cinder cone (the NSEC) grew on the east flank of the SEC, with a volume of 19 × 10⁶ m³ (Behncke et al., 2014) by April 2012, and growing up to 50 × 10⁶ m³ by October 2014 (De Beni et al., 2015). The shallow storage feeding these paroxysmal events, imaged from volcanic tremor and long-period seismic events, is very shallow and located within the volcanic pile between sea level and the ground surface (Cannata et al., 2015) and should represent just the final portion of the uprising path. We know very little about the episode occurring in 2014 (Table 1) because of poor weather conditions.

Lava Fountain From VOR, 3–5 December 2015

In January 2015, ash plume emissions started from the Voragine crater (VOR), after 16 years quiescence at this crater (Corsaro et al., 2017; Cannata et al., 2018). Explosive activity from this crater increased in intensity and became almost regular since 27 October, climaxing with a sequence of four paroxysmal events between 3 and 5 December (Vulpiani et al., 2016; Bonaccorso and Calvari, 2017; Neri et al., 2017). The four explosive events interrupted the usual trend of inflation observed at Mt. Etna (Aloisi et al., 2017). They were characterized by decreasing LF maximum heights (from 4.1 to 1.1 km), by lack of associated lava flows, by durations varying between 65 and 114 min, and by a total erupted volume of at least 10 × 10⁶ m³ dense rock equivalent (Bonaccorso and Calvari, 2017). The eruption columns and ash plume rose vertically with velocities between 150 and 200 m s⁻¹, and the transition from the convective to the umbrella region was observed at ~8 km height (Vulpiani et al., 2016). In about 10 min the ash plume expanded up to 10–15 km above sea level (a.s.l.; Vulpiani et al., 2016; Corsaro et al., 2017). Tephra fallout accumulated mostly within the summit crater, resulting in a fountain-fed rheomorphic lava of ~7.2 × 10⁶ m³ (Corsaro et al., 2017; Neri et al., 2017). The strain data constrained the depth of the magmatic source at ~ 1.5 km b.s.l. (Bonaccorso and Calvari, 2017). This is much deeper than the magmatic source at sea level inferred for the lava fountain episodes at the NSEC (Bonaccorso et al., 2013a,b; Cannata et al., 2015). The fast transfer from the deepest levels of the plumbing system of basic, undegassed magmas has been considered as the crucial triggering factor leading to the development of exceptionally violent volcanic phenomena (Cannata et al., 2018). Also the time scale for completely refilling the VOR system and renewing magma is very fast, being as short as a few tens of hours (Pompilio et al., 2017).

Camera Recorded Data

We have used the thermal and visual cameras from the INGV-OE monitoring network (Figure 2c) to acquire information about the duration of the eruptive activity, such as the start and end of the Strombolian activity preceding the paroxysm, of the lava fountain, of the lava flows, exit velocity, as well as the height of lava fountains. Table 2 reports the characteristics of the cameras used in this study. Additional information can be found in Andò and Pecora (2006) and Coltelli et al. (2017). Details on the time and kind of eruptive activity for each episode, as well as its duration, are listed in Table 1, which also contains the erupted volumes of pyroclastics for each event. These have been obtained, following the approaches of Calvari et al. (2011) and Bonaccorso and Calvari (2017), by integrating the height of the LF obtained from the saturated portion of the thermal images over time at 1 min time lapse, and using the formulas:

where U is the mean fluid exit velocity at the vent, H is the LF height, g is the gravity acceleration, V is the fluid volume (gas + pyroclastics) erupted by a LF, A is the vent surface area, and t is the duration of the LF. Vent surface area is calculated considering a circular vent with a diameter of 30 m (Calvari et al., 2011) and supposed constant. Considering a circular shape for the vent area, and multiplying the mean fluid exit velocity at the vent by the vent surface area integrated over time, we transformed the 2D view given by the camera obtaining a 3D volume estimation. The images from the thermal cameras (EMOT, ENT, EMCT, and MBT; Figure 2c, Table 2) have been used to measure the maximum height of the LF, considered as the saturated portion of each image. Saturation varies with respect to distance between 50°C for the most distant camera (ENT, 15 km; Figure 2c) to 100°C for the closest (EMOT, 3 km; Figure 2c). The error in the height measurement is ±50 m. We carefully measured the height of the saturated portion, avoiding errors due to clouds interference and to the variable position of the eruptive vent, given that the NSEC, responsible for this eruptive activity, grew by more than 190 m during the lapse of time considered here (Behncke et al., 2014). The heights of the LF at 1 min intervals have then been used to calculate the total fluid erupted volume from Equations (1) and (2), which includes both gas and pyroclastics (Calvari et al., 2011; Bonaccorso and Calvari, 2017). To obtain the volume of pyroclastics from the total volume of erupted fluid (gas + pyroclastics), we have considered 0.18% as the ratio between the volumes of magma and fluids within the eruptive column as typical for Etna's fountains (e.g., Donnadieu et al., 2016). This 0.18% between the pyroclastic portion of the LF and the total erupted fluids (gas + pyroclasts), derives from the average volumetric growth of the NSEC cone during the first 12 paroxysmal episodes. In fact, most of the LF fallout accumulates all around the vent, causing the fast growth of the NSEC cinder cone. The NSEC cone volume was measured by Behncke et al. (2014) on 31 August 2011, after 12 LF episodes from the NSEC, at ~9.5 × 10⁶ m³ dense rock equivalent (DRE). This volume is ~0.18% of the total volume of fluids (gas + pyroclastics, ~5.4 × 10⁹ m³) erupted during the first 12 LF events and obtained from Equations (1) and (2). Considering this a constant, we applied the 0.18% to all pyroclastic volume calculations of the LF episodes from the NSEC reported in Table 1. For the four paroxysmal episodes of VOR, this value has been calculated individually for each event, showing a significant variability and a general gradual decline (from 0.22 to 0.09%; Bonaccorso and Calvari, 2017). The maximum error on the pyroclastic volume calculation is reported in Table 1, and is calculated from the LF height error (±50 m) and its propagation when using Equations (1) and (2).

The lava flow volumes in Table 1 are taken from Ganci et al. (2012), Behncke et al. (2014) and De Beni et al. (2015), or are averages of more values when available. TADR is related only to the explosive component of each episode and averaged over the whole duration of the paroxysmal explosive event.

Note that the starting and ending times in Table 1 (in UT format) have been obtained from careful analysis of the images of the closest cameras (3.0 km from the vent, see Table 2), and thus refer to surface expression of the eruptive activity. As such, they could be significantly different from those obtained by geophysical data that refer to changes detected in the source region (e.g., Carbone et al., 2015; Spampinato et al., 2015; Bonaccorso and Calvari, 2017). In addition, given the change from Strombolian to LF activity is generally gradual and characterized by a transitional phase (e.g., Spampinato et al., 2008), we have taken as the starting time of the LF activity the moment when tephra fallout began spreading well outside the crater, in a way to minimize errors in volume calculations. In fact, we have observed that during the transitional phase, the jet of magma is highly collimated, and tephra fallout mainly falls back within the crater, with very little contribution to the volume accumulated on the outer flanks of the cone and beyond.

For four of the 44 eruptive episodes at NSEC between January 2011 and December 2013, we lack data because poor weather conditions hampered camera visibility throughout the entire episode. These are: 8 October 2011, 21 February 2013, 11 November 2013, and 2 December 2013 (Table 1). However, in the next section we also considered these episodes when analyzing the relationships between pause interval and total erupted volume. When instead cloud coverage was partial, we have interpolated the missing values. In addition, the 19 September 2011 event (Table 1) allowed visibility for only 7 min out of 65, thus in this case most of the erupted volume has been extrapolated on the basis of available data and must be considered a minimum, given that the climax of the LF has been lost. We have analyzed 6333 frames to extract dimensional parameters of the LF. Of these, 352 have been interpolated because of cloud cover, making a 5.6% data interpolated. The amount of interpolated frames for each LF is indicated in Table 1. However, it is worth noting that the two events of 18 April 2013 and 20 April 2013 occurred in poor weather conditions, allowing only 1/3 and 2/3 of their duration to be captured by the cameras. These two volumes must be considered as minimums. Figure 3 displays the first LF episode from NSEC (A) occurring on 12 January 2011 and (B) the first episode from VOR occurred on 3 December 2015, with the outline of the volcano and the two vent positions. Note the very different size of both the LF (in white-red) and eruptive plumes (bluish to pink).

The ECV visual camera (Figure 2c, Table 2) has been used to extract the growing height of the eruptive plume, following the method proposed by Scollo et al. (2014). They calibrated the ECV images by projecting the plume on a vertical plane passing through the craters and parallel to the wind direction, taken from the daily wind direction forecast, thus obtaining a grid for the plume height estimation with an estimated error on the height of ±0.5 km. The ECV camera has a field of view allowing a maximum height of 9 km a.s.l., thus higher plumes are not visible. Fifteen out of the 44 episodes occurred during daytime and in good weather conditions, also enabling us to analyse the plume height growth together with LF height growth. These data are displayed in Figure 5, with the limit of 9 km a.s.l. due to the camera field of view. Note that Table 1 reports maximum plume heights, thus most of the values greater than 9 km are taken from existing literature.

In summary, we have analyzed the images of 40 eruptive episodes from the NSEC and 4 from VOR in order to obtain: (1) the duration of the Strombolian activity preceding each episode; (2) the duration of the LF; (3) the total volume of erupted pyroclastics; (4) the time-averaged discharge rate (TADR), referred just to the LF portion of each episode and averaged over the entire duration of the paroxysmal explosive phase; (5) the average and (6) maximum LF heights; (7) the maximum exit velocity of LF; (8) the duration of the lava flow output; (9) the plume type; (10) the maximum elevation of the plume (when lower than 9 km) and the plume growth for 15 events displayed in Figure 5; (11) the maximum exit velocity of the plume. Plume type is differentiated into a strong plume when vertical, intermediate when slightly inclined (~70°) downwind, and weak when markedly bent in a downwind direction (Figure 1). These results are listed in Table 1. Lava flow volumes and maximum plume heights are taken from available published data as specified in Table 1.

Statistical Approach

To make the most of the substantial set of paroxysms, we statistically characterized the measured volcanological features with the final aim of analyzing possible correlations among them. Indeed, conducting a correlation analysis that assumes the data follow a normal distribution when, in fact, the data are non-normal, can lead to inaccurate results (e.g., linear correlation analysis is not robust in the presence of non-normality; Kowalski, 1972). To avoid this potential error, we first determined the right distribution of each considered feature. For the analysis, we took into account the following nine features, listed in Table 1:

(1) the inter-time between two consecutive paroxysms;

(2) the duration of Strombolian activity before the fountaining event;

(3) the fountain duration;

(4) the duration of the lava flow accompanying the paroxysm;

(5) the mean fountain height;

(6) the maximum fountain height;

(7) the total volume of lava flow associated with the paroxysm;

(8) the total volume of erupted pyroclastics;

(9) the mean wind speed at altitude during the paroxysm.

Each feature was tested for a normal distribution. We used the Shapiro-Wilk (SW) test that is a widely used test of normality in frequency statistics (Shapiro and Wilk, 1965). The null-hypothesis of this test is that the population is normally distributed. The Shapiro-Wilk test is based on the correlation between the data and the corresponding normal scores and performs better than the Kolmogorov-Smirnov (KS) test in recognizing samples from non-normal distributions (Steinskog, 2007). We adopted a confidence level for the test of 5%.

For all the considered features, the test rejected the null-hypothesis of normality, thus we estimated the best distribution among the following ones: t location-scale (Rinne, 2011), inverse Gaussian (Chhikara and Folks, 1989), exponential (Balakrishnan and Basu, 1996), logistic and log-logistic (Balakrishnan, 1992). To this set of alternative distributions, we also added the normal distribution to confirm the SW test outcomes. Each distribution was fitted using maximum likelihood estimation. The Akaike information criterion (AIC) was then applied to choose the distribution that better describes the data. The AIC estimates the relative quality of statistical models for a given dataset (Burnham and Anderson, 2003). Given a collection of models for the data, AIC estimates the quality of each model, relative to each of the other models. Thus, AIC provides a means for model selection. The AIC corrected (AICc) for finite sample sizes is defined as:

L being the model likelihood of the estimated model parameters $\left(\widehat{\theta }\right)$, k the number of parameters, and n the sample size. For all the estimated best distributions, we calculated the first and second moments when existing and finite. Results are reported in Table 3, where it is then possible to read the estimated characteristic scales of the features.

We performed a correlation analysis to infer possible hidden relationships among the considered features. Correlation is a bivariate analysis that measures the strengths of association between two variables and the direction of the relationship. In terms of the strength of relationship, the value of the correlation coefficient varies between +1 and −1. When the value of the correlation coefficient lies around ±1, then it is said to be a perfect degree of association between the two variables. As the correlation coefficient value goes toward 0, the relationship between the two variables will be weaker (Hazewinkel, 2001). Commonly, Cohen's standard is used to evaluate the correlation coefficient to determine the strength of the relationship, or the effect size, where correlation coefficients between 0.10 and 0.29 represent a small association, coefficients between 0.30 and 0.49 represent a medium association, and coefficients of 0.50 and above represent a large association or relationship (Cohen, 1988).

There are different types of correlation methodologies. Pearson correlation (parametric test) is the most widely used correlation statistic to measure the degree of the relationship between linearly related variables (Pearson, 1895). For the Pearson correlation, both variables should be normally distributed. Other assumptions include linearity and homoscedasticity. Linearity assumes a straight-line relationship between each of the variables in the analysis and homoscedasticity assumes that data are normally distributed about the regression line (and both variables have a finite variance). These assumptions make the Pearson coefficient unreliable in case of non-normally distributed data. In order to mitigate the distribution effects, we used the Box-Cox transformation (Box and Cox, 1964) to convert the feature distributions into normal ones. In addition, we used the non-parametric tests of Spearman rank (Spearman, 1904) and Kendall rank (Kendall and Gibbons, 1990) correlations to measure the degree of association between two variables without any assumptions about the distribution of the data.

Based on the statistical analysis of the parameters obtained from analyzing the camera images, considering all the three cited coefficients, the correlation analysis confirms that the only significant/large associations are those for the self-explanatory feature pairs:

• volume of pyroclastics and fountain duration (0.66 of mean correlation);

• mean and maximum fountain heights (0.76 of mean correlation).

Nevertheless, it is important to underline that the above statistical analysis is valid for the considered set of volcanological data and should not be generalized outside the considered time interval without further accurate studies.

Lava Fountain Average Height vs. Plume Maximum Height

We investigated the relationship between the average height of the LF (H_F) and the maximum height that reaches the plume (H_P). The average heights of the LF are derived from the thermal images at 1 min intervals. Regarding the measurement of the maximum heights of the plume, in the current literature the work presenting the most complete and detailed catalog is the one published by Scollo et al. (2014), which reports the height measurements of the plume of 19 LF from 10 April 2011 to 27 April 2013. For each event considered, in their Table 1 the Authors reported three heights respectively estimated from: (1) ECV camera, which, however, cuts the image to 9 km a.s.l.; (2) the MODIS satellite; (3) the SEVIRI satellite. The heights measured with greater precision are those seen by ECV, which records the peak in elevation when below 9 km. Then, with less precision, is the value obtained by MODIS, which has less frequency of satellite passages (and therefore fewer images; 1 every 15 min with 1 km of spatial resolution in the thermal infrared; Corradini et al., 2016). Finally, with even less precision, is the value obtained by SEVIRI, which has a spatial resolution of 3 km and records images every 15 min (Ganci et al., 2012). To obtain a more robust dataset, we therefore used the values obtained from ECV measurements, when H_P was less than 9 km in height, and for other cases (H_P > 9 km) we considered the value from MODIS and alternatively, if this was not available, the value of SEVIRI (Table 4). For a few cases (Table 4) where ECV camera images saturated at 9 km a.s.l., but with the satellite passage providing a lower height because their passage was temporarily distant from the LF climax, we used the ECV camera height. We did not consider the 19 September 2011 and 08 October 2011 episodes due to cloudy weather. Moreover, for the LF of 12 January 2011, we used the plume height reported in Calvari et al. (2011); for the LF of 23 October 2011, we considered the plume height measured by SEVIRI and reported in Guerrieri et al. (2015); for the LF of 23 November 2013, we considered the height inferred by Corradini et al. (2016) by using a multi-sensor approach considering different satellite instruments such as Meteosat, MODIS and SEVIRI, and finally for the four events of the VOR of 3–5 December 2015, we used the plume heights reported in Vulpiani et al. (2016), obtained by three radar systems (at C and X band) operated by the Italian Department of Civil Protection (Table 4).

The relationship between H_F and H_P has some limitations. In fact, it considers a heterogeneous set of data because heights from ECV camera saturate at 9 km a.s.l., and in these cases it is necessary to consider this underestimated value or to resort to the satellites that have a greater resolution error, when often their passage in time is not perfectly synchronous with the maximum height reached by the plume. Despite these limitations, the relationship presents an interesting correlation (Figure 4) with a good R² of 0.78 for the overall average (Equation 4), and 0.91 for the VOR events only (Equation 5). This provides a useful tool to make a rough forecast of the maximum height reached by the plume once the fountain, well after its initial phase, stabilizes its explosive power and thus its average height, which can be accurately measured in real-time by the cameras monitoring system.

The equations expressing these relationships are:

This equals to:

Time-Dependent Relation Between Lava Fountain and Plume Heights

For 15 of the 49 eruptive events, occurring during daytime and with good weather conditions, we also managed to obtain the growing height of the plume over time from the analysis of the images recorded by the ECV camera (Table 2). This allows a view of the eruptive plume up to about 9 km a.s.l., estimated using the scheme proposed by Scollo et al. (2014).

The comparison between height of the LF and height of the ash plume is shown in the graphs of Figure 5. Although with the limit of the 9 km caused by the camera field of view, from the analysis of Figure 5 it is possible to observe different behaviors. A first class of events comprises 7 LF (10 April 2011, 20 August 2011, 29 August 2011, 8 September 2011, 18 March 2012, 18 April 2013, and 4 December 2015; Figure 5), where the ash plume stays above the 9 km threshold for most of the duration of the LF. These are all strong plumes (Figure 1A) formed in wind conditions variable between 2.69 and 8.69 m s⁻¹ and with TADR, calculated only for the explosive portion, between 96 and 157 m³ s⁻¹, and with the outsider event of 4 December 2015 which displayed the exceptional value of 561 m³ s⁻¹ (Table 1). A second class of events comprises the two events of 9 July 2011 and 12 August 2011 (Figure 5), where the plume remained above 9 km for a short period of time (30 and 52 min, respectively) during the climax reached by the lava fountains, and decreased soon after and while the LF was still on going. These two events are both strong plumes formed in wind conditions of 3.99 and 7.99 m s⁻¹, and having TADR of 110 and 99 m³ s⁻¹, respectively, thus comparable to the range of the first class. A different pattern is shown by the 6 events of 4 March 2012, 12 April 2012, 3 April 2013, 12 April 2013, 27 April 2013, and 23 November 2013, where the height of the ash plume increases and decreases together with the height of the LF (Figure 5). It is worth noting that the 27 April 2013 plume decline after the end of the LF is not reported in Figure 5 because it has been observed from thermal images and not from the ECV camera, given that it occurred during the evening and hence with no visibility from this camera. These are intermediate to weak plumes (Figures 1B,C) formed in wind conditions comprised between 3.22 and 21.78 m s⁻¹ and displaying TADR between 23 and 171 m³ s⁻¹. Thus, from an overall view of these data, it appears that conditions of strong wind (above ~10 m s⁻¹) or low TADR (below 100 m³ s⁻¹), or a combination of these two factors, might favor weak to intermediate plumes that decrease in height soon after or together with the end of the LF. Conversely, conditions of high TADR (above 100 m³ s⁻¹) and slight wind (below ~10 m s⁻¹), or a combination of these two factors, involves the formation of strong plumes, with plume heights above 9 km maintained even during the phase of waning LF height (Figure 5).

The effect of wind speed on the plume style is clearly visible when comparing the LF events on 12 May 2011 and on 19 July 2011 (Figure 6). It is worth noting here that wind speed is sampled every 3 h, thus we lack details of wind variability during an event, and we consider it constant throughout a paroxysmal event. The first event occurred in low wind conditions (7.13 m s⁻¹), with LF maximum height of 880 m, and average of ~300 m, and with a TADR of 135 m³ s⁻¹ (Table 1), allowing the gradual development of a strong plume rising vertically from the vent. As the eruptive phase proceeded, we observed at first, between 00:00 and 01:02, intermittent minor ash emissions (Figure 6A) accompanied by a Strombolian to transitional phase, followed between 01:02 and 01:17 by the formation of a weak plume (Figure 6B) inclined westward (left) by about 45°; between 01:18 and 01:26 (Figure 6C) it passed to an intermediate plume with inclination of ~70° westward; and from 01:26 to 3:21 giving rise to a strong plume rising vertically from the vent (Figure 6D) and spreading laterally (Figure 6E); between 3.21 and 3:44 the plume again became transitional (Figure 6F) until the end of the eruptive event. An opposite example is given by the event of 19 July 2011, which had a similar TADR (121 m³ s⁻¹, Table 1) and a slightly greater vertical extension of the LF height (1,040 m maximum, 487 m average; Table 1), but whose plume formed in conditions of stronger wind (15.05 m s⁻¹). The activity started as pulsating and increasing ash emissions between 00:00 and 00:29 (Figure 6G), passing to weak plume (bent about 45° eastward, Figure 6H) between 00:29 to 01:38 (with LF about 800 m high), and again at pulsating and decreasing ash emissions between 01:38 and 02:18 (Figure 6I), until the end of the event. Thus, Figure 6 displays the importance of wind speed and IER in determining the plume style, passing from no plume to weak, intermediate and then to strong plume with increasing IER (from 43 to 67, 85 and 130 m³ s⁻¹, respectively) and in conditions of low wind (7.13 m s⁻¹, Table 1 and Figures 6A–E). Vice-versa, the opposite change occurs when IER vanishes (Figures 6E,F, from 119 to 0 m³ s⁻¹). On the contrary, if wind speed is strong (15.05 m s⁻¹ in the case of the 19 July 2011 event, Table 1 and Figures 6G–I), then also a powerful LF ~800 m high (with IER up to 158 m³ s⁻¹, Figure 6H) is unable to form a strong plume (Figures 6G–I). It is worth noting that the two events reported in Figure 6 have very similar TADR and durations (averaged over the whole duration of the explosive event, 135 and 121 m³ s⁻¹, and durations of 8,220 and 7,800 s, respectively; Table 1) but wind speed is two-fold during the second case (7.13 vs. 15.05 m s⁻¹; Table 1).

Discussion

In this paper, we have analyzed 44 paroxysmal explosive events occurring at Mt. Etna between 2011 and 2015, with the aim of analyzing the eruptive process and finding simple relationships among easily measurable parameters that might be useful for hazard assessment and risk mitigation. Using the images recorded by the network of thermal and visual cameras (Figure 2c, Table 2), we have characterized each event, extracting the parameters listed in Table 1. They are: the vent that produced the event (NSEC, VOR or NEC); duration of the Strombolian phase preceding the LF event; starting and ending time and duration of each LF event; volume of erupted pyroclastics and its maximum error; TADR; maximum and average height of the LF; maximum speed of the LF; the lava flow duration when associated to the explosive event; lava flow volume (taken from available published data, as detailed in Table 1 caption); plume type (either strong, intermediate or weak, see Figure 1); maximum plume heights (from available published data, detailed in Table 1 caption, or from our measurements using the ECV camera image); maximum velocity of plume growth; and wind speed.

Etna's LFs are significantly different from their Hawaiian counterpart. The main difference is the shape of the vent, which is normally linear (fissure) in Hawaii (e.g., Parcheta et al., 2012), and localized (circular vent or bocca) at Etna (e.g., Calvari et al., 2011). In addition, Hawaiian LFs are normally 200–400 m high (Head and Wilson, 1987; Wolfe et al., 1988), whereas on Etna we measured LF up to 3–4 km in height during the lapse of time here considered (Table 1). It is worth noting that during the explosive activity of Kilauea observed on 17 May 2018, when a summit circular vent was active within the Halemaumau Crater (Patrick et al., 2016), a more than 9 km high ash plume was reported¹ This suggests that, considering all other parameters as steady, a circular vent might promote a greater vertical distribution of the erupted ash when compared to a fissure.

Even more than vent geometry, LF heights depend primarily on the amount of exsolved volatiles (Head and Wilson, 1987), with H₂O being the most abundant (92–96 mol%) and turning to zero as soon as the paroxysm ends (Allard et al., 2005). Etnean magmas are very water-rich basalts, with 3.4 wt% H₂O (Métrich et al., 2004) when compared to their Hawaiian counterpart (0.6–0.8 wt% H₂O; Head and Wilson, 1987), thus confirming that LF height can be used as a reliable indication of exsolved magma gas (water) content (Head and Wilson, 1987).

Using the scheme proposed by Newhall and Self (1982), we have used the erupted volume as the primary parameter for estimating the Volcanic Explosivity Index (VEI) of each event. We have attributed to erupted volumes <0.5 × 10⁶ m³ and/or durations of < 1 h a VEI = 2; VEI = 4 for volumes greater than 2.0 × 10⁶ m³ and/or durations > 3 h; and VEI = 3 for all events in between these two end-members. Most of the explosive events listed in Table 1 can be classified as eruptions having VEI 3, based on their durations (1–3 h), erupted volumes (between 0.5 and 2 × 10⁶ m³) and eruptive column height (3–15 km). Only a few (e.g., 18 February 2011) have erupted volumes so small (~95 × 10³ m³) to be classified as having VEI = 2 (Table 5). Table 5 lists an estimation of VEI for each of the LF events occurring at Etna between 2011 and 2015.

For the events 16, 29, 40, 44, and 45 (Tables 1, 5) where no volumes are available, VEI has been suggested on the basis of duration. Observing the results displayed in Table 5, the first phase of activity, from 11 January 2011 to 24 April 2012, is characterized by 20 VEI 3 plus 4 VEI 2 and 1 VEI 4 events, indicating a steady-state of the volcano as already proposed by Bonaccorso and Calvari (2013) on the basis of just volume estimations. The second phase, from 19 February to 27 April 2013, is very short and comprises 7 VEI 2 and 6 VEI 3 events, suggesting that a new input of gas-rich magma entered the shallow supply system (Bruno et al., 2016) that emptied during the July-October 2012 mainly effusive BN activity (Cannata et al., 2015; Slatcher et al., 2015; Spampinato et al., 2015). The third phase, from 26 October to December 2013, showed a significant change in the supply system, involving more than one crater (26 October 2013 event, Table 1) and comprising the most explosive NSEC event (23 November 2013, Table 1) during which no lava flows have been erupted. This phase comprises 3 VEI 4 and 3 VEI 3 events, is more powerful and variable, and forecasts the activation of the deeper storage and of the VOR crater that was inactive since 1999 (Corsaro et al., 2017; Cannata et al., 2018). The fourth and final phase here considered (3–5 December 2015, Table 1) produced 2 VEI 4 and 2 VEI 3 events (Table 5) and high volumes erupted in a short time. Also this phase is followed by a mainly effusive eruption, with the degassed magma being quietly erupted by VOR during 17–25 May 2016 (Edwards et al., 2018). Thus, the estimation of VEI over time gives insights on the state of the volcano and its changes, with a steady-state displayed by constant and low VEI (2–3), and significant changes in the supply system marked by an increase in VEI (3–4).

Each paroxysmal event is characterized by three phases, clearly visible in Figure 5: (1) an initial gradual increase of the LF heights; (2) a climax; and (3) a sharply declining phase often accompanied by lava flow output, as already observed by Ganci et al. (2012). These phases, following Head and Wilson (1987), reveal: (1) an initial low gas content release, during the eruption of the gas-poor magma resident in the shallow supply system and left over after the end of the previous explosive event; (2) the output of the gas-rich magma pocket intruded into the system and accumulated at depth to form a foam layer (Allard et al., 2005; Calvari et al., 2011); and (3) the exhaustion of the gas within the magma and the fast passage to either strombolian or effusive conditions.

The two sequences described here, produced by the NSEC (40 events) and by VOR (4 events) displayed very different features. Figure 3 clearly depicts the different size between the first event occurring at the NSEC in 2011 (Figure 3A) and the first event of VOR in 2015 (Figure 3B), with greater size of both LF and ash plume for the VOR event. In addition, the events from VOR occurred in a very short time (3 days), had TADR comprised between 199 and 776 m³ s⁻¹ and maximum height of the LF between 1,123 and 4,100 m, and durations of 3,900–6,840 s, and did not produce lava flows (Table 1). By contrast, the events produced by the NSEC occurred in 3 years, had much lower TADR (23–171 m³ s⁻¹) and maximum heights of the LF (176–1,950 m), and greater durations (1,740–65,100 s), were accompanied by lava flow output, with the outsider event of 23 November 2013, which, unlike all other NSEC events, did not erupt lava flows and had LF that reached the huge elevation of 3,400 m above the crater, when all other NSEC events were normally in the range 800–1,200 m (Table 1). The two different features are compatible with the different depth of the source region, much deeper for VOR (1.5 km b.s.l.; Bonaccorso and Calvari, 2017) and shallower for NSEC (Bonaccorso et al., 2013a,b; Cannata et al., 2015). The deeper source for VOR also results in a more primitive erupted magma (Corsaro et al., 2017). It is worth noting that VOR erupted just pyroclastics, whereas NSEC had weaker LF generally accompanied by the output of degassed lava flows.

All LF events have displayed an associated ash plume, whose size and shape depends essentially on the interplay between the volume of pyroclastics erupted in the unit of time (IER, here calculated at 1 min intervals; Harris et al., 2007) and the wind speed affecting the summit of the volcano at the time of eruption (Bonadonna and Phillips, 2003). Table 1 shows that in general at Mt. Etna, low wind speed (<10 m s⁻¹) results in strong plumes, whereas high wind speed (>10 m s⁻¹) causes weak plumes, although some exceptions occur. The importance of wind speed is revealed by the examples displayed in Figure 6, showing two events with similar duration, TADR and maximum height of the LF, but very different wind speed. Figure 6 shows that, during a single event formed in conditions of low wind (< 10 m s⁻¹), the passage from weak to intermediate and then to a strong plume occurs at increasing IER (or LF height), and vice-versa (Figures 6A–F). By contrast, if a similar event develops in conditions of strong wind (>10 m s⁻¹), then the resulting plume will be weak (Figures 6G–I). This is in agreement with the predictive models of Bursik (2001) and Woodhouse et al. (2013), who found that windy conditions require an order of magnitude increase in the source mass flux to obtain equivalent rise heights.

These results stress that evaluating paroxysmal explosive activity just on the basis of the total mass eruption rate (e.g., Corsaro et al., 2017), which is averaged over the whole duration of the event, only gives a general idea of the strength of an event. In addition, this parameter being calculated once that the eruption is finished, cannot be used for hazard purposes. If these data are made available in real time, for example using an automated routine (e.g., Cannavò et al., 2017), it is extremely important to take into account the IER measured on a much shorter lapse of time (Harris et al., 2007), given that it is ideally the instantaneous release of pyroclastics that, in steady wind conditions, defines the passage from weak to strong plume and vice-versa.

The statistical analysis on the parameters obtained from the analysis of the camera images and listed in Table 1 confirms that the only significant associations are those for the feature pairs:

• volume of pyroclastics and fountain duration (0.66 of mean correlation);

• Mean and maximum fountain heights (0.76 of mean correlation).

The measurement of maximum plume height is a difficult parameter to obtain, because at present ground cameras have limits due to their field of view (9 km a.s.l. for the ECV camera used in this study, Table 2), and satellite data depend on the proximity of the satellite overpass with respect to the climax of the explosive phase, whose duration is usually quite short at Etna (Table 1). However, even with all these limits, if we select the available data opportunely as we did in Table 4, then it is possible to find a good relation between maximum plume height and average LF height, which is even better if we consider only the explosive events of VOR, during which no lava flows were involved.

In fact, using selected published parameters of H_p (Table 4), we were able to find two empirical formulas that relate the maximum height of the plume with the average LF height, and these might be used for forecasting a plume extent as soon as the average height of the lava fountain stabilizes. Equation (6) can be used if the eruptive crater is unknown, because for example of poor weather conditions, or if the erupting crater is the NSEC. In cases of paroxysms fed by VOR, instead it is better to use Equation (7), which also gives a lower error in the estimation of plume height.

For the lower correlation between H_p and H_F observed for the NSEC events, we consider that lava flows, spreading mainly within the Valle del Bove depression on the east flank of the volcano, where winds normally also blow the ash plume, might heat the atmosphere and increase the duration of the ash plume at high elevations. Using the regression line of these data (Figure 4 and Equations 6 and 7) as a general formula applicable during the earlier phases of a future eruption, we can forecast the maximum elevation that an ash plume may attain as soon as the lava fountain has reached its climax, measuring this elevation from the thermal images recorded by the monitoring cameras. In addition, knowing wind speed and direction, we can immediately forecast the sector of the volcano that will be involved by ash fallout and its extension.

Figure 5 shows that plume formation is often as quick as lava fountain formation, although ash fallout on the flanks of the volcano can be observed with 20–30 min delay, as a function of wind speed. However, weak to intermediate plumes tend to decline rapidly as soon as the paroxysm ends, whereas strong plumes tend to keep the elevation of >9 km a.s.l. for most of the duration of the eruptive event, thus increasing the possibility that fine ash transported at high elevations into the atmosphere is dispersed by wind for greater distances.

For Etna, and using the examples described in this paper, we can infer that wind speed <10 m s⁻¹ generally results in strong to intermediate plumes, whereas wind speed >10 m s⁻¹ is normally associated with weak plumes. A second parameter, important for defining plume formation, is IER, whose effect is shown in Figure 6. An increasing IER in low wind conditions will give rise to weak, intermediate and then strong plumes with elevation greater than 9 km, with the opposite trend observed when IER vanishes. In conditions of strong wind instead, the plume remains below 9 km and we usually observe just weak plumes. More data, especially from satellite combined with simultaneous ground measurements, and especially with frequently measured wind speed data, are necessary to improve our ability to forecast the extension and growth of ash plumes associated with lava fountains on Etna and other volcanoes.

Equations (6) and (7) can be used for hazard purposes to calculate the maximum height that the ash plume will attain. They have the great advantage of being applied as soon as the LF mean height has been reached. We will use Equation (6) for events where is the NSEC erupting, and Equation (7) when the crater involved is VOR. Two other possibilities are to use the formula proposed by Sparks et al. (1997):

where H is maximum column height (in km) and TADR is mean discharge rate (m³ s⁻¹), or a similar equation proposed by Woodhouse et al. (2013):

where Q is source mass flux measured in kilograms per second, obtained from TADR and from magma density, considered as 2,650 kg m³ (Table 5). However, Equations (8) and (9) are impossible to use for hazard purposes because in order to know the value of TADR or Q, we need to wait until the end of the LF event. Table 5 presents a comparison between the plume heights from available literature, with those obtained using our Equation (6) for events 1–45 and Equation (7) for the events 46–49 and with values obtained using Equation (8) proposed by Sparks et al. (1997) and Equation (9) proposed by Woodhouse et al. (2013). As reported in Table 5, the values from Sparks et al. (1997) mostly result underestimated, whereas those from Woodhouse et al. (2013) are much closer to those obtained from our formulas. However, we must consider that the equation from Sparks et al. (1997) has been obtained using a number of mostly plinian eruptions from several different volcanoes, whereas our equations have been calibrated for Etna. Thus, for hazard purposes, we suggest to interpolate data collected from a single volcano in order to obtain a suitable empirical relationship.

Final Remarks

Etna's LFs are significantly different from their Hawaiian counterpart. The main difference is the shape of the vent, which is normally a fissure in Hawaii, and a circular vent or bocca at Etna. Hawaiian LFs are normally 200–400 m high, whereas on Etna we measured LF up to 3–4 km in height during the lapse of time here considered (Table 1). Considering all other parameters as steady, we suggest that a circular vent might promote a greater vertical distribution of the erupted ash when compared to a fissure.

Even more than vent geometry, LF heights depend primarily on the amount of exsolved volatiles, with H₂O being the most abundant (92–96 mol%) and turning to zero as soon as the paroxysm ends. Etnean magmas are very water-rich basalts, with 3.4 wt% H₂O (Métrich et al., 2004) when compared to their Hawaiian counterpart (0.6–0.8 wt% H₂O; Head and Wilson, 1987), thus confirming that LF height can be used as a reliable indication of exsolved magma gas (water) content (Head and Wilson, 1987).

In this paper, we have presented an analysis of the images recorded by Etna's web cameras aimed at quantifying the paroxysmal explosive events occurring between 2011 and 2015. The measured parameters are listed in Table 1 and their range of variability is reported in Table 3. The 44 events here described (Table 1) can be divided into two groups: the events from the NSEC normally have VEI 2–3 and lower LF heights, longer event duration, and lower TADR than the events produced by VOR. This is consistent with a deeper source region for the VOR events (e.g., Bonaccorso and Calvari, 2017) allowing deeper, more primitive and gas rich magma to rise rapidly along the conduit (Corsaro et al., 2017; Pompilio et al., 2017), resulting in more hazardous VEI 3–4 eruptions.

An analysis of the measured parameters did not find ready correlations between them, if we exclude those that are directly connected. This is probably due to the many variables affecting the impact of each event, with wind speed and IER playing an important role in defining the maximum extension and style of an ash plume. However, from the data presented, we can observe that in general at Mt. Etna wind speed greater than 10 m s⁻¹ produces a weak plume that bends and is elongated along the wind direction, whereas wind speed below 10 m s⁻¹ results in strong to intermediate plumes, causing a lower impact on the population (because the ash fallout is mainly concentrated around the crater, although the upper portion of the eruptive column comprising the fine-grained particles is always affected by wind, see Figure 1A) but a greater effect on aviation (because the elevation of the ash plume is greater).

For Etna, and using the examples described in this paper, we can infer that wind speed <10 m s⁻¹ generally results in strong to intermediate plumes, whereas wind speed > 10 m s⁻¹ is normally associated with weak plumes (Figure 7A). A second parameter, important for defining plume formation, is IER (Figure 6). An increasing IER in low wind conditions will give rise to weak, intermediate and then strong plumes with elevation greater than 9 km, with the opposite trend observed when IER vanishes. In conditions of strong wind instead, the plume remains below 9 km and we usually observe just weak plumes. We have found a simple relationship between plume and LF heights that could be used for hazard assessment as soon as the LF average height is reached, expressed by the (Equations 6 and 7; Figure 7B). The results are better for VOR, because the events produced by this crater did not involve emission of lava flows, thus the whole volume erupted went into the proximal fallout and ash plume. On the contrary, all paroxysms produced by the NSEC, apart from that of 23 November 2013 (Bonaccorso et al., 2014), were associated with lava flow output, thus also involving the emission of degassed magma at the end of each event. In addition, the lava flow spreading mainly within the Valle del Bove, on the east flank of the volcano, where winds normally blow the ash plume, causes heat release and then possibly a plume staying at high elevation for longer time when compared to VOR. More data are necessary to improve our knowledge of these events and our ability to predict their impact, especially by comparing both satellite and ground data and having more frequent wind speed measurements.

Author Contributions

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We thank T. Caltabiano for extracting wind speed and direction from meteorological data provided by the Hydro-Meteorological Service of the Emilia-Romagna Regional Agency for Environmental Protection (ARPA-SIM), and E. Pecora, E. Biale, and M. Prestifilippo for the camera network maintenance. We thank S. Conway for revising the text. A previous version of the manuscript was significantly improved by the comments of two reviewers.

Footnotes

References