[M-IS09] Interdisciplinary studies on pre-earthquake processes

[MIS09-P07] Soil CO₂ Flux as a Seismic Indicator: Insights from TABOO Stations and the 2016 Accumoli-Norcia Seismic Sequence

Dario Buttitta¹, *Antonio Caracausi¹, Marco Camarda¹, Lauro Chiaraluce¹, Sofia De Gregorio ¹, Rocco Favara¹, Fabio Antonino Pisciotta¹ (1.National Institute of Geophysics and Volcanology)

Keywords:Near Fault Observatories, CO2 flux monitoring, geochemical anomalies, fluids and earthquakes

Soil CO₂ flux anomalies have been associated with seismic activity, providing insight into the relationship between tectonic stress redistribution and subsurface gas migration (Chiodini et al., 2004; Caracausi et al., 2022 and 2024). This study investigates CO₂ emissions recorded for 10 years at The Alto Tiberina Near Fault Observatory (TABOO-NFO)), focusing on their correlation with major earthquakes in the Central Apennines, particularly the Mw 6.0 Accumoli (24 August 2016) and Mw 6.5 Norcia (30 October 2016) earthquakes. Our analysis identified statistically significant CO₂ flux anomalies up to 10 days before seismic events, with flux values exceeding statistical threshold and p-value test confirms that the increase in soil CO₂ flux did not occur randomly and was related to earthquake occurrence. These anomalies were consistently detected using multiple monitoring stations spatially correlated with active fault structures.The findings suggest that stress-induced permeability changes and pressure redistribution facilitate the migration of CO₂ through pre-existing pathways over a large area (up to about 100km), supporting the role of geochemical anomalies as short-term earthquake indicators (Improta et al., 2019). Our findings highlight the importance of incorporating multidisciplinary and long time series datasets to refine the study of relations between deformation, earthquake and crustal fluid migrations. Future research should prioritize the integration of discrete sampling geochemical data, expanded real-time geochemical monitoring and IA for data management and filtering together with machine learning models to improve the predictive capabilities of geochemical indicators (Chiarluce et al., 2022; Buttitta et al., 2023; Caracausi et al., 2022 and 2024). Despite the promising implications of our results, challenges remain in differentiating tectonic signals from environmental influences. However, the observed consistency of CO₂ flux anomalies across multiple seismic events reinforces their significance. These findings contribute to the broader understanding of fluid-fault interactions in seismogenic zones and emphasize the potential of geochemical monitoring in earthquake hazard assessment.
Caracausi, A., et al. (2022). Communications Earth & Environment, 3, 224. DOI: 10.1038/s43247-022-00549-9
Chiaraluce, L., et al. (2007). Journal of Geophysical Research: Solid Earth, 112, B10310. DOI: 10.1029/2007JB005015
Chiodini, G., et al. (2004). Geophysical Research Letters, 31, L07615. DOI: 10.1029/2004GL019480
Improta, L., et al. (2019). Scientific Reports, 9, 6921. DOI: 10.1038/s41598-019-43393-2