Publication Date:
2024-06-26
Description:
Variations in the CO2 dissolved in water springs have long been observed near the epicenters of moderate and strong earthquakes. In a recent work focused on data collected during the
2017–2021 period from a monitoring site in the Northern Apennines, Italy, we noticed a significant
correlation between CO2 anomalies and moderate-to-weak seismic activity. Here, we extended this
analysis by focusing on data collected from the same site during a different period (2010–2013) and
by integrating the CENSUS method with an artificial neural network (ANN) in the already-tested
protocol. As in our previous work, a fit of the computed residual CO2 distributions allowed us to
evidence statistically relevant CO2 anomalies. Thus, we extended a test of the linear dependence
of these anomalies to seismic events over a longer period by means of binary correlations. This
new analysis also included strong seismic events. Depending on the method applied, we observed
different time lags. Specifically, using the CENSUS methodology, we detected a CO2 anomaly one
day ahead of the earthquake and another anomaly eleven days ahead. However, no anomaly was
observed with the ANN methodology. We also investigated possible correlations between CO2
concentrations and rain events and between rain events and earthquakes, highlighting the occurrence
of a CO2 anomaly one day after a rain event of at least 10 mm and no linear dependence of seismic
and rain events. Similar to our previous work, we achieved a probability gain of around 4, which is
the probably of earthquake increases after CO2 anomaly observations.
Description:
Published
Description:
739
Description:
OST3 Vicino alla faglia
Description:
JCR Journal
Keywords:
CO2 anomalies
;
continuous monitoring
;
small earthquakes
;
statistical correlations
;
04.06. Seismology
Repository Name:
Istituto Nazionale di Geofisica e Vulcanologia (INGV)
Type:
article
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