Periodicity in Volcanic Gas Plumes: a Review and Analysis

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Periodicity in Volcanic Gas Plumes: a Review and Analysis geosciences Review Periodicity in Volcanic Gas Plumes: A Review and Analysis Tom D. Pering 1,* , Tehnuka Ilanko 1 and Emma J. Liu 2,3 1 Department of Geography, University of Sheffield, Sheffield S10 2TN, UK; t.ilanko@sheffield.ac.uk 2 Department of Earth Sciences, University of Cambridge, Cambridge CB2 3EQ, UK; [email protected] 3 Department of Earth Sciences, University College London, London WC1E 6BS, UK * Correspondence: t.pering@sheffield.ac.uk Received: 18 July 2019; Accepted: 4 September 2019; Published: 10 September 2019 Abstract: Persistent non-explosive passive degassing is a common characteristic of active volcanoes. Distinct periodic components in measurable parameters of gas release have been widely identified over timescales ranging from seconds to months. The development and implementation of high temporal resolution gas measurement techniques now enables the robust quantification of high frequency processes operating on timescales comparable to those detectable in geophysical datasets. This review presents an overview of the current state of understanding regarding periodic volcanic degassing, and evaluates the methods available for detecting periodicity, e.g., autocorrelation, variations of the Fast Fourier Transform (FFT), and the continuous wavelet transform (CWT). Periodicities in volcanic degassing from published studies were summarised and statistically analysed together with analyses of literature-derived datasets where periodicity had not previously been investigated. Finally, an overview of current knowledge on drivers of periodicity was presented and discussed in the framework of four main generating categories, including: (1) non-volcanic (e.g., atmospheric or tidally generated); (2) gas-driven, shallow conduit processes; (3) magma movement, intermediate to shallow storage zone; and (4) deep magmatic processes. Keywords: volcanic plumes; periodicity; basaltic volcanism; passive degassing; fluid dynamics 1. Introduction Active volcanoes commonly exhibit persistent (i.e., continuous or quasi-continuous) emission of gases from summit vents or fumaroles (Figure1). Persistently degassing volcanoes are typically those erupting magmas with lower silica contents—i.e., basalts, basaltic-andesites, and andesites—and thus, lower viscosities. In contrast to more silicic magmas where gas bubbles remain strongly coupled to the melt, low magma viscosities permit efficient fluid-melt separation [1,2] and allow bubbles to move independently of the melt. Once nucleated, bubbles in magma can grow either by diffusion of volatiles into the bubble, decompression, and coalescence, before either bursting at the magma surface or undergoing explosive fragmentation [3–5]. Volcanic gas emissions are predominantly composed of water vapor (H2O), carbon dioxide (CO2), and sulfur dioxide (SO2, or in reduced form, hydrogen sulfide, H2S), with SO2 being the easiest to resolve against background atmospheric concentrations and therefore, generally the target gas used for emissions measurements [6]. Present generally in trace quantities are halogen compounds such as chlorine, fluorine, bromine, and iodine, the latter of which is highly reactive in the atmosphere forming gaseous species such as bromine monoxide (BrO), and iodine monoxide (IO) [7–9]. The relative ease of measuring SO2, compared to other major gas species, has meant that this gas is often the target for remote sensing. Prior to the development of ultra violet (UV) camera technology [10,11], measurement techniques were constrained by sampling rate and therefore lacked Geosciences 2019, 9, 394; doi:10.3390/geosciences9090394 www.mdpi.com/journal/geosciences Geosciences 2019, 9, 394 2 of 24 Geosciencesthe temporal 2019, resolution 9, 394 to detect rapid changes in SO2 flux. For example, Differential Optical Absorption2 of 25 Spectroscopy (DOAS) could at best achieve resolutions of minutes because of the need to traverse or Spectroscopyscan gas plumes (DOAS) [12–14 could]. Now, at withbest achieve the advent resolutions of UV cameras, of minutes which because generally of the acquire need atto frequenciestraverse or scanapproaching gas plumes 1 Hz, [12–14]. periodic Now, components with the advent (oscillations) of UV cameras, in gas flux which are resolvable generally onacquire timescales at frequencies of 10 s to approaching1000 s [6,15–19 1 ].Hz, periodic components (oscillations) in gas flux are resolvable on timescales of 10 s to 1000The s [6,15–19]. existence of longer timescale periodicity in volcanic outgassing on the order of days to monthsThe wasexistence first identified of longer at timescale well-studied periodicity systems in with volcanic long monitoringoutgassing on timeseries, the order e.g., of Kdays¯ılauea, to monthsHawaii [was20] andfirst Soufriere identified Hills at well-studied Volcano, Montserrat systems [with21]. Whilstlong monitoring low frequency timeseries, periodic e.g., components Kīlauea, Hawaiiare widely [20] thought and Soufriere to originate Hills Volcano, from deep Montserrat processes [21]. related Whilst to large-scale low frequency magma periodic movement components [22,23], arehigh widely frequency thought signals to originate can be derivedfrom deep from processes a wide related range of to potential large-scale drivers magma [16 movement]. The causes [22,23], and highimplications frequency of short-periodsignals can be cycles derived have from yet toa bewide compared range of in potential detail across drivers volcanoes. [16]. The causes and implications of short-period cycles have yet to be compared in detail across volcanoes. Figure 1. 1. ExampleExample plumes plumes from from four four volcanoes: volcanoes: (a) Sabancaya, (a) Sabancaya, in April in April2018, showing 2018, showing a passive a passive plume duringplume duringintermittent intermittent explosive explosive activity, activity, (b) Yasur, (b) Yasur, in July in July 2018, 2018, with with strombolian strombolian explosion explosion pulses pulses emanating from from the crater ap approximatelyproximately every minute, ( c)) Stromboli, Stromboli, in in June June 2018, 2018, showing showing passive passive degassing in between the st strombolianrombolian explosions, and and ( dd)) Fuego, Fuego, in in November 2017, showing clear clear periodic degassing from Strombolian explosionsexplosions occurring approximately everyevery 8–108–10 min.min. The detection of periodic behavior is not restricted to SO2 flux measurements alone, and periodicity The detection of periodic behavior is not restricted to SO2 flux measurements alone, and periodicitycan also be identifiedcan also inbe timeseriesidentified of in molar timeseries gas ratios of molar [16,24– gas27]. ratios Open-Path [16,24–27]. Fourier Open-Path Transform InfraredFourier TransformSpectroscopy Infrared (OP-FTIR) Spectroscopy can capture (OP-FTIR) high temporal can capt resolutionure high datasetstemporal of resolution molar gas datasets ratios for of a molar broad gasrange ratios of gases, for a broad including range trace of gases, species including such as chlorinetrace species [28–32 such]. In as combination chlorine [28–32]. with thermodynamicIn combination withmodels thermodynamic of volatile solubility, models molar of volatile gas ratios solubility, can be directly molar relatedgas ratios to thecan pressure be directly (depth) related of gas-melt to the pressureseparation (depth) and are of thereforegas-melt criticalseparation to the and identification are therefore and critical tracking to the of identification new magma inputsand tracking and their of newsubsequent magma ascentinputs throughand their the subsequent shallow magmatic ascent through system the [33 shallow–36] or tomagmatic discriminate system between [33–36] redox- or to discriminateand solubility-driven between processesredox- and [24 solubility-driven,37]. processes [24,37]. This review summarizes the literature associated with with the full range of currently resolvable periodicities within volcanic degassing timeseries, timeseries, starting starting with with an an overview overview of of the methods for detecting periodicity. 2 Geosciences 2019, 9, 394 3 of 24 2. Methods for Detecting Periodicity 2.1. Spectral Analysis The presence of periodicity within volcanic gas datasets is quantified based on the principle of spectral analysis, or frequency analysis, whereby timeseries data are decomposed into a series of waves of known wavelength and amplitude, to determine the strength of different frequencies within discrete datasets. Spectral analysis is commonly performed using one of two main groups of techniques (summarized in Table1): the fast Fourier transform (FFT) [ 38–43], and the wavelet transform [16,44–49]. The continuous wavelet transform (CWT) is increasingly preferred because it offers additional degrees of freedom, such that the temporal persistence of periodic components can be investigated in detail, particularly where those components exhibit non-stationary characteristics [16,19,24,48–51]. When conducting spectral analysis, we can only consider a maximum cycle length of half the dataset length; this is termed the Nyquist criterion [52]. For example, with a dataset 1000 s in length, the maximum detectable period would be 500 s. However, as this would only allow two complete periodic cycles, it is often preferable and advisable to set the cut-off at a frequency higher than the Nyquist limit, for example at three or four complete periodic cycles. This principle is applicable to all spectral analysis techniques, including the CWT. Autocorrelation, or serial correlation,
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