Társilo Girona

Understanding the mechanisms that control the start-up of volcanic unrest is crucial to improve the forecasting of eruptions at active volcanoes. Among the most active volcanoes in the world are the so-called persistently degassing ones (e.g., Etna, Italy; Merapi, Indonesia), which emit massive amounts of gas during quiescence (several kilotonnes per day) and erupt every few months or years. The hyperactivity of these volcanoes results from frequent pressurizations of the shallow magma plumbing system, which in most cases are thought to occur by the ascent of magma from deep to shallow reservoirs. However, the driving force that causes magma ascent from depth remains unknown. Here we demonstrate that magma ascent can be triggered by the passive release of gas during quiescence, which induces the opening of pathways connecting deep and shallow magma reservoirs. This top-down mechanism for volcanic eruptions contrasts with the more common bottom-up mechanisms in which magma ascent is only driven by processes occurring at depth. A cause-effect relationship between passive degassing and magma ascent can explain the fact that repose times are typically much longer than unrest times preceding eruptions and may account for the so frequent unrest episodes of persistently degassing volcanoes.

Many active volcanoes around the world release passively large amounts of gas between eruptions. Monitoring how these gas emissions fluctuate over time is crucial to infer the physical processes occurring within volcanic conduits and reservoirs. Here we report a new method to capture remotely the spectral properties of the emissions of H₂O, the major component of most volcanic plumes. The method is based on a new theoretical model that correlates the volcanogenic water content of condensed volcanic plumes with the intensity of the light scattered by the droplets moving with the gas. In turn, we show that light intensity of the plume, and thus steam pulses time series, can be obtained with a proper analysis of digital images. The model is experimentally validated by generating condensed plumes with an ultrasonic humidifier, and then the method is applied to the gas plumes of Erebus and Mayon volcanoes. Our analysis reveals three main features: (1) H₂O time series are composed of numerous periodic components of finite duration; (2) some periodic components are common in H₂O and SO₂ time series, but others are not; and (3) the frequency spectra of the H₂O emissions follow a well‐defined fractal distribution, that is, amplitude (Δ) and frequency (ν) are correlated by means of power laws (Δ ∝ ν^γ), with exponent γ ≈ − 1 for Erebus and for Mayon. These findings suggest that quiescent degassing emerges from the complex coupling between different processes occurring within magma plumbing systems. Our method is ideal for real‐time monitoring of high‐frequency H₂O cycles at active volcanoes.

Many active volcanoes around the world alternate episodes of unrest and mildly explosive eruptions with quiescent periods dominated by abundant but passive gas emissions. These are the so‐called persistently degassing volcanoes, and well‐known examples are Mayon (Philippines) and Etna (Italy). Here, we develop a new lumped‐parameter model to investigate by how much the gas released during quiescence can decrease the pressure within persistently degassing volcanoes. Our model is driven by the gas fluxes measured with monitoring systems and takes into account the size of the conduit and reservoir, the viscoelastic response of the crust, the magma density change, the bubble exsolution and expansion at depth, and the hydraulic connectivity between reservoirs and deeper magma sources. A key new finding is that, for a vast majority of scenarios, passive degassing reduces the pressure of shallow magma reservoirs by several MPa in only a few months or years, that is, within the intereruptive timescales of persistently degassing volcanoes. Degassing‐induced depressurization could be responsible for the subsidence observed at some volcanoes during quiescence (e.g., at Satsuma‐Iwojima and Asama, in Japan; Masaya, in Nicaragua; and Llaima, in Chile), and could play a crucial role in the onset and development of the physical processes which may in turn culminate in new unrest episodes and eruptions. For example, degassing‐induced depressurization could promote magma replenishment, induce massive and sudden gas exsolution at depth, and trigger the collapse of the crater floor and reservoir roof.

Modeling the diffusion of elements in olivine from volcanic rocks has recently become one of the most useful techniques to determine the timescales of the processes that occur in magma reservoirs before eruptions. However, many potential users are not versed in the numerical methods needed to solve the diffusion equation for timescale determinations. Here we present DIPRA (Diffusion Process Analysis), a user‐friendly computer tool that models easily and intuitively the olivine chemical zoning by performing an automatic, visual, and quick fit to the natural profiles. The code is developed under a finite difference scheme and allows simultaneous modeling of diffusion of Fe, Mg, Mn, Ni, and Ca. DIPRA accounts for most variables that affect the diffusivity, including temperature, pressure, oxygen fugacity, major element composition, and anisotropy. Initial and boundary conditions can be done as complex as desired, including changing boundary composition with time. Such versatility allows modeling the large variety of scenarios that are characteristic of volcanic systems. We also have implemented a methodology to estimate objectively the uncertainties of the timescales from the uncertainties of the data and temperature. We expect that our application will increase the number and quality of timescale determinations from crystal zoning studies. It may be also useful as a teaching resource for higher education courses.