## 3 Results  
The methodological approach followed in this work consisted of three steps: (a) first, the two methods (statistical moments and coherence) described in Section 2 were applied separately; (b) the obtained results were inspected and the signal windows that simultaneously exceeded the predetermined thresholds for both methods were considered; (c) the seismic signals from the selected time windows were visually inspected and their timing was searched in the seismic catalogs available online [23]; \"www.ov.ingy.it; www.emsc-csem.org/ (accessed on day December 21, 2022)\" looking for local and/or regional earthquakes. A synthetic flow diagram of the proposed procedure is shown in Figure 2. Following the calculation of the spectral parameters, all signal windows characterized by shape factor \(\delta\) and central frequency \(\Omega\) values typical of LF events (see Section 2.1) were selected in order to identify such possible seismic events. Figure 2: Flowchart of the detection procedure proposed in this work. The three identified signal windows are: 1. 2020 05 02 02:12 UTC, 2. 2020 05 02 12:49 UTC and 3. 2020 05 02 23 50 UTC. The analysis of the continuous signal showed that most of the analyzed windows are characterized by spectral parameters and coherence values typical of random seismic noise. In particular, with regard to spectral parameters, most of the signal windows show central frequency \(\Omega\) around 10 Hz and shape factors \(\delta\) greater than or equal to 0.6, as found for noise records by [PERSON] et al. [16]. As an example, we consider the spectral parameters and coherence analysis performed for May 2, 2020 (Figures 3 and 4). Figure 3 illustrates the results obtained for the three stations, BKWG, BKSG and SVAG. Plots in the top row of the figure show the results of shape factor vs. central frequency (blue points) for the three sites. Most of the dots are characterized by a central frequency greater than 6 Hz (histograms in the second row plots) and by a shape factor mostly greater than 0.5 (histograms in the bottom row plots). It is noteworthy that the three sites have different spectral features from each other, particularly with regard to the bimodal distribution of the shape factor at BSKG. Different results were expected because the spectral features of the background seismic signal are locally modified by site effects. In order to identify the windows that potentially contain signals associated with LF events, we need to inspect the results in the time domain. Figure 4 shows the two spectral parameters (central frequency and shape factor) for the BKWG station, the coherence and the average spectral amplitude vs. time evaluated for 2 May 2020. In this case, the three larger yellow symbols identify the windows that simultaneously have the features of LF events at the three stations and coherence values \(\geq\) 0.45. Figure 3: Shape factor and central frequency evaluated on one day of continuous signals recorded on 2 May 2020, at BKSG, BKWG and SVAG mobile seismic stations. In the upper part of the figure, the graphs of the shape factor vs. central frequency are shown, while in the central part and in the lower part, the histograms of the aforementioned spectral parameters are shown for the three selected stations. Figures 5-7 show the seismic signals within the selected windows. Three local earthquakes are recognized in the seismograms of the first window (Figure 5). On the three components of ground motion, the direct P and S waves are identifiable only after appropriate filtering, and the time difference Ts \(-\) Tp = 1.3 s can be estimated for the BKSG and BKWG stations. The spectral content features are consistent with LF spectral parametrization. In this case, the three events have been classified as deep LF earthquakes. The second selected window contains signals with spectral features similar to those of local LF events, but in this case, they are generated by a regional earthquake (20200502 12:51:05 UTC Mw6.6 Crete, Greece) (Figure 6).