Continuous radon monitoring during seven years of volcanic unrest at Campi Flegrei caldera (Italy)

Abstract

This is a seven-year study (1/7/2011-31/12/2017) of radon monitoring at two sites of Campi Flegrei caldera (Neaples, Southern Italy) that in the last 70 years experienced repeated phases of volcanic unrest. The sites are equipped with devices for radon detection, based on the spectrometry analysis of the α-particles of radon daughters. A hybrid method, as combination of three known methods, is applied for the identification of residuals (anomalies) and trends of the time series of Radon. The results are compared with the following indicators of current caldera unrest: the tremor caused by the major fumarolic vent registered by a seismic station; the cumulative of background seismicity; the maximum vertical deformation acquired by GPS networks during the current phase of uplift; the temperaturepressure of the hydrothermal system estimated based on gas geo-indicators. The comparisons show strong correlation among independent signals and suggest that the extension of the area affected by current campi flegrei crisis is larger than the area of seismicity and of intense hydrothermal activity from which the radon stations are 1-4 km away. These results represent an absolute novelty in the study of a such calderic area and mark a significant step forward in the use and interpretation of the radon signal.

A Google Earth Engine Tool to Investigate, Map and Monitor Volcanic Thermal Anomalies at Global Scale by Means of Mid-High Spatial Resolution Satellite Data

“…Despite the FNR higher than other areas, such as Suwanoseijima (Japan) where the FNR from L8-OLI data was estimated around 13%, the occurrence of some lava effusions inside the OL crater (e.g., [68]) indicates that events of natrocarbonatite lava, having temperatures in between 500 °C and 600 °C Despite the FNR higher than other areas, such as Suwanoseijima (Japan) where the FNR from L8-OLI data was estimated around 13%, the occurrence of some lava effusions inside the OL crater (e.g., [68]) indicates that events of natrocarbonatite lava, having temperatures in between 500 • C and 600 • C (e.g., [69]), may be detected/assessed by the tool. On the other hand, different satellite-based systems (e.g., those using TIR data) need to be used to identify low-temperature thermal anomalies, as for Campi Flegrei, where fumaroles reach temperatures up to 160 • C-165 • C (e.g., [61,70]).…”

“…The FPR was generally higher from S2-MSI data, reaching about 19.2% at Campi Flegrei when the NHI tool v.1.1 was used. In this high-risk volcanic area, which is characterized by a hydrothermal activity and whose last eruption occurred in 1538 AD (e.g., [60,61]), the tool v.1.2 was the most effective in reducing false positives occurring over cloud-edges and associated to S2-MSI data issues. The NHI tool v.1.3/1.4 was slightly less efficient in minimizing these issues (e.g., see Tolbachick).…”

Multi-Level Gas Monitoring: A New Approach in Earthquake Research

“…Zmazek et al (2003) used decision trees to predict soil radon concentrations from meteorological parameters and then compared the predicted vs. the actually observed radon values. Sabbarese et al (2020) applied a hybrid method-combining multiple linear regression, empirical mode decomposition, and support vector regression-to identify residuals and trends of radon timeseries from Campi Flegrei. A long-term increasing radon trend correlated with vertical displacement, increasing background seismicity, as well as the calculated increasing pressure and temperature of the hydrothermal system.…”

Extreme emissions from shallow water methane seepages Zelenka (Northern Bulgarian Black Sea region) before earthquake Md 4.7 August 5, 2009

“…Изследванията за прогнозиране на земетресения включват изучаване на разнообразни параметри: ниво на радон (Sabbarese et al, 2020); ниво на подпочвени води (Nakagawa et al, 2019); вариации на електромагнитно поле (Florios et al, 2020); топлинно излъчване (Wei et al, 2019); дълги вълни (Xiong, Shen, 2017); йоносферни ефекти (Kelley et al, 2017) и др. Основна пречка на изброените подходи пред разработването на прогностични методи е ниското отношение сигнал/шум.…”