Applications

APPLICATIONS

Attempts to improve the sensitivity of the instruments and the sensitivity of the instruments to unexpected phenomena have produced some useful applications.

The electrodynamic pluviometer

The sensitivity of CIEN station electrodes to rainfall was converted in a project with the aim of

building a new type of rain-gauge. The project was financed by the Umbria Region and developed

at the "Andrea Bina" observatory in Perugia, from 2013 to 2015. The Bina Observatory is today

dedicated to the seismic monitoring of the Perugia territory, but in the past, it was devoted to

meteorological research with the invention of the first rain rate meter by Father Benedetto Castelli

and Galileo Galilei in 1639, and the Paoloni's anemometer in 1930. In July 2016 a patent was filed

for the new instrument measuring the rain rate, with a temporal scale up to seconds and a

completely solid-state device. The environment today is even more susceptible to landslides and

floods, therein constituting a danger to the safety of persons. In fact, storms can produce unexpected

and localized heavy concentrations of rainfall. A network of low-cost instruments able to measure

rapid heavy rainfall over large areas would allow to assess dangerous events. Radars can only

partially satisfy the necessity of extended monitoring as they are highly inaccurate at measuring the

amount of rainfall on irregular surfaces. Moreover, radars which are known to be associated with

health risks, must satisfy numerous restrictions when placed near populated areas. Radars are

costly to maintain and a significant environmental impact. This rain gauge is small in dimensions,

can be easily fastened to a common sill and connected to a PC by a USB or used with a wireless

solution. The invention is made up of two discs of different diameters joined by a rod of about 10 cm.

The flat circular disk of a few square centimeters which constitutes the sensor is placed at the top

with its axis parallel to the vertical axis (see the picture on the right). The disk having a larger

diameter acts as the anchoring base and contains the electronics of the device. This disc is

characterized by holes at more points so to be able to fasten it to various solutions. Patent No. 102016000077834 was approved in January 2019.

Forecasting strong earthquakes

The statistical correlation calculated over more than 16 years of data collecting the time difference between strong earthquake occurrence and electron burst detection, which was demonstrated to exist with particle loss anticipating seismic activity of about 2 - 3 hours, opens a question: could it be used for future strong earthquake forecasting?

Taking into account that a physical model is essential for proving that a statistical correlation corresponds to a phenomenological link, the response is affirmative. It can be realized by calculating the probability of an earthquake event throughout the relationship between the covariance and cross-correlation (corr). This method is completely general and applicable to every couple of correlate events, even if they are unitary events. The cross-correlation is

where cov is the covariance, and where P(EQ) and P(EB) are the independent probabilities of earthquakes (EQ) and electron bursts (EB) occurrence, respectively. The conditional probability

This means that, if a correlation exists between EQs and EBs, and the time difference is chosen to be that of correlations between EQ and EB events, the probability of a strong EQ is increased of a term proportional to the correlation. The number of false alarms can be estimated in a programmed experiment (see Fidani, 2018).

The performance of a specific method is carried out through the statistical parameters that can be evaluated in this example, such as: the success rate P(EQ|EB), the false alarm rate 1 – P(EQ|EB), the alarming rate is P(EB) + corr(EQ,EB)√[1 – P(EQ)]P(EB)[1 – P(EB)]/P(EQ), the failure rate is 1 – P(EB) – corr(EQ,EB)√[1 – P(EQ)]P(EB)[1 – P(EB)]/P(EQ), and the probability gain (see Fidani, 2021)

If two dependent precursors EB and EC that generate alarms in the same space-time volume are considered, which means for example electron bursts EB and magnetic pulses EC, where electron bursts can be physically induced due to magnetic pulses (see Fidani, 2021), the conditional probability on EQ can be calculated by probability gains GEB and GEC due to electron bursts and magnetic pulses, respectively. Given the observations of an event in the set of both precursors EB and EC, the combined probability gain can be expressed as

which is useful as the observation of ECs on the Earth's surface can occur when a NOAA satellite is not in a suitable position to reveal the possibly induced EBs. Moreover, magnetic detectors can not be installed at some positions offshore, or are not able to detect ECs where there are EQs. In other words, EBs and ECs can compensate for the gaps one each other in a forecasting experiment, where the space-time volume is very large.

Time-delayed mutual information and transfer entropy have also been calculated analytically for binary events, which are useful for the non-linear complex dynamical system such as the lithosphere-ionosphere system. The time-delayed mutual information can be expressed using G as:

I(EQ;EB) = − G P(EQ)P(EB) log {[1/ G − P(EQ)][1 − G P(EB)]} − log {[1 − P(EQ)][1 − P(EB)]} +
+ P(EQ) log {[1 − P(EQ)][1 − G P(EB)]} + P(EB) log {[1 − P(EB)][1 − G P(EQ)]} +
+ {1 − P(EB) − P(EQ)[1 − G P(EB)]} log {1 − P(EB) − P(EQ)[1 − G P(EB)]},

Instead, transfer entropy can be calculated including correlations between consecutive earthquake events, and between consecutive earthquakes and electron bursts. The expression can be found in Fidani, 2022.

Radon safety

Radon is present everywhere on the Earth's surface and comes mainly from granite and volcanic basements as well as certain building materials. Radon can accumulate in confined spaces, especially in homes and underground places like cellars, and can pose a risk to health. The ALGADE detector installed at Gubbio Station to monitor Radon emission during seismic activity is able to keep the gas level under control in a cellar that is always closed (see Alberi et al., 2019).