MEMS (Micro Electro-Mechanical Systems) sensors enable a vast range of applications: among others, the use of MEMS accelerometers for seismology related applications has been emerging considerably in the last decade. In this paper, we provide a comprehensive review of the capacitive MEMS accelerometers: from the physical functioning principles, to the details of the technical precautions, and to the manufacturing procedures. We introduce the applications within seismology and earth sciences related disciplines, namely: earthquake observation and seismological studies, seismic surveying and imaging, structural health monitoring of buildings. Moreover, we describe how the use of the miniaturized technologies is revolutionizing these fields and we present some cutting edge applications that, in the very last years, are taking advantage from the use of MEMS sensors, such as rotational seismology and gravity measurements. In a ten-year outlook, the capability of MEMS sensors will certainly improve through the optimization of existing technologies, the development of new materials, and the implementation of innovative production processes. In particular, the next generation of MEMS seismometers could be capable of reaching a noise floor under the lower seismic noise (few tenths of ng/ $\sqrt{\mathrm{Hz}}$ ) and expanding the bandwidth towards lower frequencies (∼0.01 Hz).

A properly organized seismic network is a valuable tool for monitoring seismic zones and assessing seismic hazards. In this paper we propose a new method (seismic network evaluation through simulation, SNES) to evaluate the performance of hypocenter location of a seismic network. The SNES method gives, as a function of magnitude, hypocentral depth, and confidence level, the spatial distribution of the number of active stations in the location procedure and their relative azimuthal gaps, along with confidence intervals in hypocentral parameters. The application of the SNES method also permits evaluation of the magnitude of completeness (MC), the background noise levels at the stations, and assessment of the appropriateness of the velocity model used in location routine. Italy sits on a tectonically active plate boundary at the convergence of the Eurasian and African lithospheric plates and has a high level of seismicity. In this paper, we apply the SNES method to the Italian National Seismic Network (Rete Sismica Nazionale Centralizzata dell’Istituto Nazionale di Geofisica e Vulcanologia, RSNC– INGV) which has monitored Italian seismicity since the early 1980s, following the destructive 1980 Irpinia earthquake. In recent years, the RSNC–INGV has grown significantly. In fact, in February 2010, it received signals from 305 seismic stations, 258 with wideband three-component sensors. We constructed SNES maps for magnitudes of 1.5, 2, 2.5, and 3, fixing the hypocentral depth at 10 km and the confidence level at 95%. Through the application of the SNES method, we show that the RSNC–INGV provides the best monitoring coverage in the Apennine Mountains with errors that for M 2, are less than 2 and 4 km for epicenter and hypocentral depth, respectively. At M 2.5 this seismic network is capable of constraining earthquake hypocenters to depths of about 150 km for most of the Italian Peninsula. This seismic network provides a threshold of completeness down to M 2 for almost the entire Italian territory

The dynamics governing the movement of the radon are complex and dependent on many factors. In the present study, we characterise the nature of temporal variations of 2-hourly and daily radon measurements in several monitoring sites of the Italian Radon mOnitoring Network (IRON) in Italy. By means of continuous wavelet transformation, a spectral analysis in time-frequency domain is performed. The results reveal that there are sub-daily, daily and yearly persistent periodicities that are common for all the stations. We observe structural seasonal breaks, that occur at the same frequency but at distinct time. Variations in radon concentration and local temperature are studied in terms of frequency contents and synchronicity. When analysing several long time series together, it is evident that the phase difference at low frequency movements (365-day period) between the radon and local temperature time series is depending on the sites’ location and therefore strongly controlled by local factors. This could at least partially explain the apparently contrasting results available in the literature obtained investigating smaller dataset about the relationships between temperature and radon variations. On the other hand, results show that all radon time series are characterised by marked cycles at 1 and 365-days and less evident cycles at 0.5-day and 180-days. They would be all ascribable to environmental-climatic factors: the short-period cycles to temperature and pressure variations, the long-period cycles also to seasonal rainfall variations.

At the present time, micro‐electro‐mechanical system (MEMS) accelerometers seem to provide adequate sensitivity, noise level, and dynamic range to be applicable to earthquake strong‐motion acquisition. The current common use of MEMS accelerometers in the modern mobile phone may provide a new means to easily enormously increase the number of observations when a strong earthquake occurs. However, before utilizing the signals recorded by a device, like a mobile phone equipped with a low‐cost three‐axis MEMS accelerometer for any scientific purpose, it is important to verify that the signal collected provides reliable records of ground motion. In this paper, we have tested the LIS331DLH MEMS accelerometer installed in the iPhone mobile phone using a vibrating table and the EpiSensor FBA (force‐balance accelerometer) ES‐T as the reference sensor. Our tests show that, in the typical frequency and amplitude range of interest of earthquake engineering (0.2–20 Hz and ⁠, in which is the standard gravity of acceleration, or ⁠), the LIS331DLH MEMS accelerometer has excellent frequency and phase response, comparable with that of some standard FBAs produced for strong‐motion seismology. The main drawback of the LIS331DLH MEMS accelerometer is its low sensitivity, due to the high level of instrumental self noise, and so it can be used effectively only to record moderate to strong earthquakes (M_L>5) near the epicentral area.

Summary. In this paper, we analyse the location performance of the Hellenic (Greek) Unified Seismological Network (HUSN) by Seismic Network Evaluation through

In this work, we integrate artificial and natural seismic sources data to obtain high‐resolution images of the shallow inner structure of Stromboli Volcano. Overall, we used a total of 21,953 P readings from an active seismic experiment and an additional 2731 P and 992 S readings deriving from 269 local events. The well‐defined V_p, V_s, and V_p/V_s tomograms have highlighted the following: (i) the region where magma cumulates at shallow depths (2–4 km below sea level (bsl)), forming an elongated NE‐SW high‐velocity body (V_p ≥ 6.0 km/s and V_s ≥ 3.5 km/s), with a very fast velocity core (6.5 ≤ V_p < 7.0 km/s) of ~2 km³; (ii) the presence of some near‐vertical pipe‐like structures, characterized by relatively high P velocities values, mainly linked to past activity (e.g., Strombolicchio); and (iii) a near‐vertical pipe‐like volume with high V_p/V_s (1.78 ÷ 1.85), located beneath to the craters (down to ~1.0 km bsl), overlying a deeper region (1.0 to 3.0 km bsl) with low V_p/V_s (1.64 ÷ 1.69), interpreted as the actual and preferential pathway of magma toward the surface. Our results demonstrate the importance of combining passive and active seismic data to improve, in a tomographic inversion, the resolution of the volcanic structures and to discover where magma may be stored.