Martina Orlando

A thermal infrared (TIR) camera was installed at Mefite Lake in Valle d’Ansanto, Irpinia (Italy), to assess whether small variations in cold CO₂ flux can be resolved thermally. To our knowledge, this is the first systematic attempt to extract short-period degassing dynamics from TIR data at Mefite. Infrared thermal images taken over a three-hour nighttime interval revealed the spatial distribution and extent of natural CO₂ emissions. The high sampling frequency of one minute detected unexpected thermal variability from the source. The extent of temperature variations across the entire site reached almost 3 °C, with durations typically ranging from a few minutes to tens of minutes. Spectral analysis of the temperature time series reported a 1/f-type noise pattern, with significant periods of 2–3 min, 5 min, 26 min, and 61 min observed at different locations. Further intermediate periods were observed at individual points. Differences and delays in temperature variations appeared to be related to distance from the structure’s centre and the presence of water. These temperature fluctuations were interpreted as changes in the gaseous emission flow caused by a few kPa of CO₂ escaping due to pressure variations. The gas thermally interacts with the underlying soil, adding or removing heat at the surface. These results demonstrate that high-frequency infrared thermography provides a sensitive and practical tool for quantifying short-term flux variability at natural CO₂ vents and for improving the characterisation of their degassing dynamics.

The b-value of the Gutenberg-Richter law represents a fundamental parameter for characterizing earthquake size distributions and assessing crustal stress conditions.Numerous studies have demonstrated a significant relationship between the b-value and the tectonic stress regime. While low b-values are often associated with stress accumulation and potential precursors to large earthquakes, their applicability as universal precursors remains debated.This study investigates the spatial and temporal evolution of the b-value preceding large earthquakes (M≥5.5) in regions characterized by contrasting tectonic settings and fault kinematics. We examine geographically and tectonically different areas—such us Italy, China, New Zealand, and Myanmar—which encompass different stress regimes and plate boundary configurations. By systematically analyzing local seismic catalogs from these contrasting regions, we assess whether b-value variations constitute a universal feature of the seismic cycle, or are primarily modulated by region-specific crustal properties.Each study area is selected according to the seismogenic structures responsible for the target earthquakes. The completeness magnitude (Mc), defined as the lowest magnitude threshold above which the catalog reliably records all or nearly all earthquakes in the region, is rigorously determined as a function of time according to well-established methodologies.We estimate Mc using the most appropriate method for each region, including either the maximum curvature method or the 90% goodness-of-fit criteria, to ensure robust results.The b-value is subsequently estimated using the maximum likelihood approach over appropriate spatiotemporal windows preceding each mainshock.We present preliminary results showing that systematic b-value drops are observed in most cases. Our findings support the hypothesis that such variations represent a robust indicator of progressive stress accumulation. This comparative approach suggests that b-value monitoring can provide valuable precursory signals for seismic hazard assessment across different tectonic contexts.

Large recent earthquakes offer an opportunity to investigate the seismic preparatory phase from a geosystemic, multiparametric perspective, integrating lithospheric, atmospheric and ionospheric observations within the Dobrovolsky region. Using the Mw 7.1 Wushi (Xinjiang, 22 January 2024) and Mw 7.7 Myanmar (Sagaing Fault, 28 March 2025) earthquakes as natural laboratories, we jointly analyze medium‑term lithospheric signals (multi‑year) and short‑term atmospheric/ionospheric anomalies (days to months before the mainshocks). In the Wushi case, about 60 anomalies are detected: lithospheric changes persist for about one year, whereas atmospheric and ionospheric perturbations cluster within the last three months, including outgoing longwave radiation anomalies from four days before to four days after the mainshock, consistent with imminent‑stage precursors. For the Myanmar event, eleven classes of candidate precursors exhibit a characteristic sigmoid evolution in time, typical of a critical system approaching failure, and their space–time concentration supports the lithosphere–atmosphere–ionosphere coupling (LAIC) framework. A focused analysis of Swarm satellite magnetic data over the Myanmar Dobrovolsky area reveals Y‑component anomalies on 22 of 85 half‑orbits up to eight days before the earthquake; empirical magnitude estimates based on anomaly–epicentre distance yield M ≈ 7.2, in reasonable agreement with the observed M 7.7, while anomaly “energy” values cluster within a narrow range, suggesting a possible characteristic signature of seismic‑related disturbances. Overall, these case studies indicate that (i) multi‑scale, multi‑parameter anomalies often accelerate following exponential or sigmoid trends towards the mainshock, (ii) combined ground‑ and satellite‑based observations can help constrain the location of an impending event, and (iii) satellite magnetic and radiative anomalies may provide valuable input for short‑term forecasting schemes, although systematic validation on larger datasets is required before operational use.The present work has been funded by the Italian Ministry of University and Research (Pianeta Dinamico - Unitary Project) and ASI (Space It Up and LIMADOU EXPO Projects).

Each Italian earthquake included in the Italian Parametric Catalogue (CPTI) is based on a single study, with its database stored in the Italian Macroseismic Database (DBMI). The DBMI contains macroseismic-intensity data for approximately 5000 Italian earthquakes. However, for the same events, numerous studies have been independently carried out over the years, with the data of such studies not having been incorporated into the DBMI. By consolidating all available data for each event, it is possible to significantly enhance the dataset used for hazard assessments and the reconstruction of local seismic histories. This approach would make studies of individual events much more robust and comprehensive. The objective of this work is to propose the integration of different macroseismic datasets for individual events by identifying criteria that can effectively merge a large number of intensity data points. A total of 45 Italian earthquakes with data from multiple sources were identified and reassessed through a rapid review process. This effort has resulted in the creation of a new dataset (https://doi.org/10.13127/macroseismic/teral024, Tertulliani et al., 2024), substantially increasing the number of macroseismic data points (MDPs) for the earthquakes covered by this study compared to in the DBMI15 (from 2892 to 9328 MDPs). Consequently, the macroseismic distributions for these 45 events have become more detailed, robust, and extensive.

Each Italian earthquake included in the Italian Parametric Catalogue (CPTI) is based on a single study, with its database stored in the Italian Macroseismic Database (DBMI). DBMI collects macroseismic intensity data from approximately 5,000 Italian earthquakes. However, for the same events, numerous studies have been independently carried out over the years in the literature whose data have not been incorporated into the DBMI. By consolidating all available data for each event, it is possible to significantly enhance the dataset used for hazard assessments and the reconstruction of local seismic histories. This approach would make studies of individual events much more robust and comprehensive. The objective of this work is to propose the integration of different macroseismic datasets for individual events by identifying criteria that can effectively merge a large number of intensity data points. A total of 45 Italian earthquakes with data from multiple sources were identified and reassessed through a rapid review process. This effort has resulted in the creation of a new dataset, substantially increasing the number of Macroseismic Data Points (MDP) for the earthquakes covered by this study compared to those in DBMI15 (from 2,892 to 9,328 MDPs). Consequently, the macroseismic distributions for these 45 events have become more detailed, robust, and extensive.

On 6 February 2023, Turkey experienced its most powerful seismic event in over 80 years, with a moment magnitude (Mw) of 7.7, followed just nine hours later by a second large earthquake with Mw 7.6. Both events struck the Kahramanmaraş province in southeastern Turkey, within the complex tectonic setting of the East Anatolian Fault Zone (EAFZ), causing widespread destruction and significant loss of life. According to lithosphere–atmosphere–ionosphere coupling (LAIC) models (e.g. Pulinets and Ouzounov, 2011), large seismic events are expected to generate a cascade of anomalies across various geophysical layers, from the lithosphere through the atmosphere to the ionosphere, as part of the earthquake preparation process. This multidisciplinary study investigates the preparatory phase of these two major earthquakes by identifying potential precursors and disturbances across these layers, in order to better understand the mechanisms linking the geospheres prior to seismic events.Our comprehensive analysis (De Santis et al., 2019) draws on multiple datasets, including ground-based and satellite observations, to detect anomalous variations in parameters such as ground surface temperature, atmospheric gases, ionosphere electron density and geomagnetic field. These anomalies show a cumulative occurrence with an accelerating trend (De Santis et al, 2017), either exponential or power-law in nature, in the days and weeks preceding the mainshock. The anomalies predominantly exhibit an upward progression from the lithosphere through the atmosphere to the ionosphere, revealing a chain of interconnected processes within these geospheres during the earthquake preparation phase.Our findings suggest that these anomalies provide valuable evidence in support of a two-way coupling model, where disturbances can propagate upward from the lithosphere. Additionally, the study highlights the potential role of fluid chemistry (Calcara, 2022), particularly the release of gases such as radon, in driving these coupling processesIn conclusion, this study underscores the significance of a multidisciplinary approach to investigating earthquake precursors across the Earth system. The identification of consistent patterns in pre-earthquake anomalies can enhance our understanding of the complex interactions within the lithosphere-atmosphere-ionosphere system and could contribute to the development of more effective early-warning systems for major seismic events.ReferencesPulinets, S.; Ouzounov, D. Lithosphere-atmosphere-ionosphere coupling (LAIC) model-an unified concept for earthquake precursors validation. J. Asian Earth Sci. 2011, 41, 371–382De Santis, A.; Abbattista, C.; Alfonsi, L.; Amoruso, L.; Campuzano, S.A.; Carbone, M.; Cesaroni, C.; Cianchini, G.; De Franceschi, G.; De Santis, A.; et al. Geosystemics View of Earthquakes. Entropy 2019De Santis A. et al., Potential earthquake precursory pattern from space: the 2015 Nepal event as seen by magnetic Swarm satellites, Earth and Planetary Science Letters, 461, 119-126, 2017Calcara, M. Chemistry in earthquake: The active chemical role of liquid and supercritical waters in microfracturing at depth. J. Seismol. 2022, 26, 1205–122

Among the natural disasters that occurred in Europe in modern times, the earthquakes of February and March 1783 are certainly the most well-known and studied. This is due to their vast European resonance, the wealth of documentary material produced about the event, and the complexity and audacity of the recovery plan for the province developed by the Neapolitan government authorities. The seismic sequence is currently reported in seismic catalogs with five main shocks occurring between February 5 and March 28, 1783, with magnitudes ranging between 5.1 and 7.1. Despite the wealth of documentary evidence and the extensive scholarly literature that has emerged, significant gaps remain in our understanding of this seismic sequence. These limitations arise primarily from the inherent challenge of distinguishing between the effects of individual earthquakes and assessing the cumulative impact of successive shocks (Stucchi and Rovida, 2008; Guidoboni and Valensise, 2015; Tertulliani et al., 2018). Therefore, a long-term study was undertaken to re-examine what was already known, starting from existing sources, and to enrich the documentary heritage through new basic research, with the aim of increasing the number of macroseismic observations. This work presents the analysis of information relating to approximately 565 localities, based on a hypothetical chronological reconstruction of the sequence's shocks, which takes into account the impact of cumulative damage caused by multiple shocks when assigning macroseismic intensity. Through this approach, the shocks already present in the catalogs were reconstructed as faithfully as possible, using a richer knowledge framework compared to the past. The assignment of macroseismic intensities, according to the MCS and EMS-98 scales, has allowed for the construction of a new and broader macroseismic dataset and the proposal of a new interpretation of the sequence, highlighting the problems connected to the assignment of intensities.

Due to the significant earthquake-related perturbations observed in the ionosphere by ground-based stations and space-borne satellites, scientists have increasingly focused on the studying the possible coupling mechanism among lithosphere, atmosphere and ionosphere. In this work, we contribute to this research, analyzing the phase of preparation of the 2022 Ms6.8 Luding (China) earthquake with a multi-parameter and multi-level approach from ground and satellite data taken in lithosphere, atmosphere and ionosphere, including the b value, earth resistivity, ELF magnetic field emissions, atmospheric electric field, surface temperature, foF2 from Ionosonde, GNSS TEC, magnetic field and electron density from CSES and Swarm satellites, etc. The results are encouraging confirming a chain of processes starting from ground and proceeding to the above atmosphere and ionosphere.

On 6 February 2023, Turkey experienced its most powerful earthquake in over 80 years, with a moment magnitude (Mw) of 7.7. This was then followed by a second earthquake of Mw 7.6 just nine hours later. According to the lithosphere–atmosphere–ionosphere coupling (LAIC) models, such a significant seismic activity is expected to cause anomalies across various observables, from the Earth’s surface to the ionosphere. This multidisciplinary study investigates the preparatory phase of these two major earthquakes by identifying potential precursors across the lithosphere, atmosphere, and ionosphere. Our comprehensive analysis successfully identified and collected various anomalies, revealing that their cumulative occurrence follows an accelerating trend, either exponential or power-law. Most anomalies appeared to progress from the lithosphere upward through the atmosphere to the ionosphere, suggesting a sequential chain of processes across these geospheres. Notably, some anomalies deviated from this overall trend, manifesting as oscillating variations. We propose that these anomalies support a two-way coupling model preceding major earthquakes, highlighting the potential role of fluid chemistry in facilitating these processes.

This paper presents an analysis of anomalies detected during the preparatory phase of the 9 November 2022 M_L = 5.7 earthquake, occurring approximately 30 km off the coast of the Marche region in the Adriatic Sea (Italy). It was the largest earthquake in Italy in the last 5 years. According to lithosphere–atmosphere–ionosphere coupling (LAIC) models, such earthquake could induce anomalies in various observable variables, from the Earth’s surface to the ionosphere. Therefore, a multiparametric and multilayer approach based on ground and satellite data collected in each geolayer was adopted. This included the revised accelerated moment release method, the identification of anomalies in atmospheric parameters, such as Skin Temperature and Outgoing Longwave Radiation, and ionospheric signals, such as Es and F2 layer parameters from ionosonde measurements, magnetic field from Swarm satellites, and energetic electron precipitations from NOAA satellites. Several anomalies were detected in the days preceding the earthquake, revealing that their cumulative occurrence follows an exponential trend from the ground, progressing towards the upper atmosphere and the ionosphere. This progression of anomalies through different geolayers cannot simply be attributed to chance and is likely associated with the preparation phase of this earthquake, supporting the LAIC approach.