Abstract
Monitoring soil CO2 diffuse degassing areas has become more relevant in the last decades to understand seismic and/or volcanic activity. These studies are specially valuable for volcanic areas without visible manifestations of volcanism, such as fumaroles or thermal springs. The development and installation of permanent soil CO2 flux instruments has allowed to acquire long time series in different volcanic environments, and the results obtained highlight the influence of environmental variables on the gas flux variations. A permanent soil CO2 flux station is installed at Caldeiras da Ribeira Grande area since June 2010. This degassing site is located in the north flank of Fogo Volcano, a polygenetic volcano at S. Miguel Island (Azores archipelago, Portugal). The station performs measurements based on the accumulation chamber method and has coupled several meteorological sensors. Average soil CO2 flux and soil temperature values around 1165 g m-2 d-1 and 33oC, respectively, were measured in this site between June 2010 and June 2017. This study discusses different statistical approaches applied to the long time series recorded in this degassing area, focusing on the application of stepwise multivariate regression analysis, wavelets and Fast Fourier Transform to understand the CO2 flux variations and to detect eventual anomalous periods that can represent deep changes in the volcano feeding reservoirs. Multivariate regression analysis shows that about 47% of the soil CO2 flux variations are explained by the effect of the soil and air temperature, wind speed and soil water content. Spectral analysis highlights the existence of 24 h cycles in the soil CO2 flux time series, mainly during the summer period. The models proposed have been applied on a near real-time automatic monitoring system and implementation of these approaches will be profitable in any volcano observatory of the world.
Highlights
Volcanic gas emissions may occur as visible manifestations, such as fumaroles, gas vents, and bubbling springs, or as invisible emissions through diffuse degassing (Fischer and Chiodini, 2015 and references therein)
Despite all the useful information obtained with these stations for the seismo-volcanic monitoring, the recorded soil CO2 flux values have showed that gas fluxes are highly influenced by environmental factors, such as meteorological changes, which can be responsible for more than 50% of the gas flux variations (Granieri et al, 2003, 2010; Viveiros et al, 2009, 2015a)
Despite the fact that several filtering techniques have been already applied to soil CO2 flux time series, the present study focuses on an automatic filtering that may be used as routine in the volcano observatories to identify anomalous gas values and contribute to recognize unrest episodes
Summary
Volcanic gas emissions may occur as visible manifestations, such as fumaroles, gas vents, and bubbling springs, or as invisible emissions through diffuse degassing (Fischer and Chiodini, 2015 and references therein). Different statistical methodologies have been applied to filter the recorded CO2 time series in order to remove the external influences and produce a gas flux sign that may represent deep changes (e.g., Granieri et al, 2003; Viveiros et al, 2008, 2015a; Cannata et al, 2010; Liuzzo et al, 2013; Lelli and Raco, 2017). Despite the fact that several filtering techniques have been already applied to soil CO2 flux time series, the present study focuses on an automatic filtering that may be used as routine in the volcano observatories to identify anomalous gas values and contribute to recognize unrest episodes
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