Characterization of Distant and Moderate Earthquakes with Inexpensive MEMS Sensors: Application to the Mw 6.3, 29th December 2020, Petrinja Event.

In this work, we evaluate the suitability of a new MEMS sensor prototype, called ASX1000 (ADEL s.r.l., Modena, Italy), for the monitoring of distant and moderate seismic events. This device is an inexpensive capacitive accelerometer with a relatively low level of instrumental noise; it can record both local and far seismic events. An experimental network built with ASX1000 MEMS, located in northern Italy, was able to record the Mw 6.3 Petrinja earthquake that occurred in December 2020; it had an epicentral distance of more than 350 km. We retrieved the strong motion parameters (PGA, pseudo-absolute velocity, and pseudo-absolute spectral acceleration) from the acceleration time histories recorded by the MEMS sensors. The obtained parameters were compared with the ones obtained by the closer high-quality seismometers, belonging to the INGV National Seismic Network. The comparison to the highest-quality sensors confirms a reasonable agreement of the inferred parameters. This work suggests that-in the near future-MEMS sensors could be adopted to integrate the existing seismic network. A denser coverage of sensors can sample more accurately the seismic wavefield, taking into account the large spatial variability of local geology and the relative differences in seismic response.

The 2020 coronavirus lockdown and seismic monitoring of anthropic activities in Northern Italy.

In March/April 2020 the Italian government drastically reduced vehicle traffic and interrupted all non-essential industrial activities over the entire national territory. Italy thus became the first country in the world, with the exception of Hubei, to enact lockdown measures as a consequence of the COVID-19 outbreak and the need to contain it. Italy is also a seismically active area, and as such is monitored by a dense permanent network of seismic stations. We analyse continuous seismic data from many stations in northern and central Italy, and quantify the impact of the lockdown on seismic ambient noise, as a function of time and location. We find that the lockdown reduces ambient noise significantly in the 1-10 Hz frequency range; because natural sources of seismic noise are not affected by the lockdown, the seismic signature of anthropic noise can be characterised with unprecedented clarity, by simply comparing the signal recorded before and after the lockdown. Our results correlate well with independent evaluations of the impact of the lockdown (e.g., cell phone displacements), and we submit that ambient-noise seismology is a useful tool to monitor containment measures such as the coronavirus lockdowns.

Chemometric data analysis application to Sparus aurata samples from two offshore farming plants along the Apulian (Italy) coastline.

The levels of polychlorodibenzo-p-dioxins (PCDDs), polychlorodibenzofurans (PCDFs), dioxin-like polychlorobiphenyls (DL-PCBs), non-dioxin-like polychlorobiphenyls (NDL-PCBs), and polybromodiphenyl ethers (PBDEs) in fish collected from two marine offshore farming plants were determined. Each sample was constituted by specimens of the same size collected at the same time in four different seasons along the farming year. The feeds given were of industrial origin and the plants were positioned in two different sites respectively exposed to different environmental characteristics. A chemometric approach was applied to interpret the subtle differences observed in fish body burdens across the three chemical groups taken into consideration. The approach consisted in a stepwise multivariate process including a hierarchical cluster analysis (CA) and a linear discriminant analysis (DA). The two main clusters determined by CA were subjected to the canonical DA, backward and forward selection procedures to select the best discriminative functions. A clear temporal and spatial discrimination was found among the samples. Across the three chemical groups, the monthly separation seemed to depend on the growth process and the main exposure was due to the feed. In addition, the two plants differed significantly from the environmental point of view and the most important discriminating group of chemicals were the NDL-PCBs. The approach resulted really effective in discriminating the subtle differences and in individuating suggestions to improve the quality of culturing conditions.