Comparative metagenomics at Solfatara and Pisciarelli hydrothermal systems in Italy reveal that ecological differences across substrates are not ubiquitous.

Introduction: Continental hydrothermal systems (CHSs) are geochemically complex, and they support microbial communities that vary across substrates. However, our understanding of these variations across the complete range of substrates in CHS is limited because many previous studies have focused predominantly on aqueous settings. Methods: Here we used metagenomes in the context of their environmental geochemistry to investigate the ecology of different substrates (i.e., water, mud and fumarolic deposits) from Solfatara and Pisciarelli. Results and Discussion: Results indicate that both locations are lithologically similar with distinct fluid geochemistry. In particular, all substrates from Solfatara have similar chemistry whereas Pisciarelli substrates have varying chemistry; with water and mud from bubbling pools exhibiting high SO4 2- and NH4 + concentrations. Species alpha diversity was found to be different between locations but not across substrates, and pH was shown to be the most important driver of both diversity and microbial community composition. Based on cluster analysis, microbial community structure differed significantly between Pisciarelli substrates but not between Solfatara substrates. Pisciarelli mud pools, were dominated by (hyper)thermophilic archaea, and on average, bacteria dominated Pisciarelli fumarolic deposits and all investigated Solfatara environments. Carbon fixation and sulfur oxidation were the most important metabolic pathways fueled by volcanic outgassing at both locations. Together, results demonstrate that ecological differences across substrates are not a widespread phenomenon but specific to the system. Therefore, this study demonstrates the importance of analyzing different substrates of a CHS to understand the full range of microbial ecology to avoid biased ecological assessments.

The first application of compositional data analysis (CoDA) in a multivariate perspective for detection of pollution source in sea sediments: The Pozzuoli Bay (Italy) case study.

In the last decades, investigating geochemistry of sea sediments has been challenging in the eastern sector of Pozzuoli Bay, source of the metal(loid)s has been a matter of debate and the proposed origin of potentially toxic elements (PTEs) has been occasionally inconsistent. In this study, compositional data analysis (CoDA) was used because the results are independent of the measurement unit, the selected subgroup of elements and the order of chemicals in the dataset. The robust variant of principal component analysis (PCA) indicated that Hg, Cd, Cu, Pb and Zn were positively correlated with mud and organic matter in the sediments deposited in front of the former industrial site. Concentrations of these metals decrease along the cores and in the distal zone. Nevertheless, Al, As, V, Fe, Cr, Ni and sand form an association along the coast which strengthens with increasing distance from fumaroles in the proximal zone. It suggests that arsenic was mainly originated from the pyroclastic deposits of Campi Flegrei and some of the seepages with hydrothermal component, supported by low contribution of the variables in robust PCA of the sediments from distal zone. Therefore, this pioneering article suggests CoDA as a powerful tool for answering the long-lasting questions over sediment geochemistry in polluted areas.

The Evolution of Covid-19 in Italy after the Spring of 2020: An Unpredicted Summer Respite Followed by a Second Wave.

The coronavirus (COVID-19) pandemic was particularly invasive in Italy during the period between March and late April 2020, then decreased in both the number of infections and in the seriousness of the illness throughout the summer of 2020. In this work, we measure the severity of the disease by the ratio of Intensive Care Units (ICU) spaces occupied by COVID-19 patients and the number of Active Cases (AC) each month from April to October 2020. We also use the ratio of the number of Deaths (D) to the number of Active Cases. What clearly emerges, from rigorous statistical analysis, is a progressive decrease in both ratios until August, indicating progressive mitigation of the disease. This is particularly evident when comparing March-April with July-August; during the summer period the two ratios became roughly 18 times lower. We test such sharp decreases against possible bias in counting active cases and we confirm their statistical significance. We then interpret such evidence in terms of the well-known seasonality of the human immune system and the virus-inactivating effect of stronger UV rays in the summer. Both ratios, however, increased again in October, as ICU/AC began to increase in September 2020. These ratios and the exponential growth of infections in October indicate that the virus-if not contained by strict measures-will lead to unsustainable challenges for the Italian health system in the winter of 2020-2021.

On the correlation between solar activity and large earthquakes worldwide.

Large earthquakes occurring worldwide have long been recognized to be non Poisson distributed, so involving some large scale correlation mechanism, which could be internal or external to the Earth. Till now, no statistically significant correlation of the global seismicity with one of the possible mechanisms has been demonstrated yet. In this paper, we analyze 20 years of proton density and velocity data, as recorded by the SOHO satellite, and the worldwide seismicity in the corresponding period, as reported by the ISC-GEM catalogue. We found clear correlation between proton density and the occurrence of large earthquakes (M > 5.6), with a time shift of one day. The significance of such correlation is very high, with probability to be wrong lower than 10-5. The correlation increases with the magnitude threshold of the seismic catalogue. A tentative model explaining such a correlation is also proposed, in terms of the reverse piezoelectric effect induced by the applied electric field related to the proton density. This result opens new perspectives in seismological interpretations, as well as in earthquake forecast.

The COVID-19 Infection in Italy: A Statistical Study of an Abnormally Severe Disease.

We statistically investigate the Coronavirus Disease 19 (COVID-19) pandemic, which became particularly invasive in Italy in March 2020. We show that the high apparent lethality or case fatality ratio (CFR) observed in Italy, as compared with other countries, is likely biased by a strong underestimation of the number of infection cases. To give a more realistic estimate of the lethality of COVID-19, we use the actual (March 2020) estimates of the infection fatality ratio (IFR) of the pandemic based on the minimum observed CFR and analyze data obtained from the Diamond Princess cruise ship, a good representation of a "laboratory" case-study from an isolated system in which all the people have been tested. From such analyses, we derive more realistic estimates of the real extent of the infection as well as more accurate indicators of how fast the infection propagates. We then isolate the dominant factors causing the abnormal severity of the disease in Italy. Finally, we use the death count-the only data estimated to be reliable enough-to predict the total number of people infected and the interval of time when the infection in Italy could end.

Long-Term Monitoring with Fiber Optics Distributed Temperature Sensing at Campi Flegrei: The Campi Flegrei Deep Drilling Project.

Monitoring volcanic phenomena is a key question, for both volcanological research and for civil protection purposes. This is particularly true in densely populated volcanic areas, like the Campi Flegrei caldera, which includes part of the large city of Naples (Italy). Borehole monitoring of volcanoes is the most promising way to improve classical methods of surface monitoring, although not commonly applied yet. Fiber optics technology is the most practical and suitable way to operate in such high temperature and aggressive environmental conditions. In this paper, we describe a fiber optics Distributed Temperature Sensing (DTS) sensor, which has been designed to continuously measure temperature all along a 500 m. deep well drilled in the west side of Naples (Bagnoli area), lying in the Campi Flegrei volcanic area. It has then been installed as part of the international 'Campi Flegrei Deep Drilling Project', and is continuously operating, giving insight on the time variation of temperature along the whole borehole depth. Such continuous monitoring of temperature can in turn indicate volcanic processes linked to magma dynamics and/or to changes in the hydrothermal system. The developed monitoring system, working at bottom temperatures higher than 100 °C, demonstrates the feasibility and effectiveness of using DTS for borehole volcanic monitoring.

Modelling of hydrogen sulfide dispersion from the geothermal power plants of Tuscany (Italy).

We applied the Eulerian code DISGAS (DISpersion of GAS) to investigate the dispersion of the hydrogen sulfide (H2S) from 32 geothermal power plants (out of 35 active) belonging to the geothermal districts of Larderello, Travale-Radicondoli and Monte Amiata, in Tuscany (Italy). An updated geographic database, for use in a GIS environment, was realized in order to process input data required by the code and to handle the outputs. The results suggest that H2S plumes emitted from geothermal power plants are mainly concentrated around the stacks of emission (H2S concentration up to 1100µg/m3) and rapidly dilute along the dominant local wind direction. Although estimated values of air H2S concentrations are orders of magnitude higher than in unpolluted areas, they do not indicate an immediate health risk for nearby communities, under the more frequent local atmospheric conditions. Starting from the estimated values, validated by measurements in the field, we make some considerations about the environmental impact of the H2S emission in all the geothermal areas of the Tuscany region.