Iren-Adelina Moldovan

Dr. Iren-Adelina Moldovan

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Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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30 May 2022 in Sensors
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Juan José Galiana-MerinoJuan José Galiana-Merino
Juan José Galiana-Merino
SMSergio Molina
Sergio Molina
AKAlireza Kharazian
Alireza Kharazian
Victorin Emilian ToaderVictorin Emilian Toader
Victorin Emilian Toader
IMIren-Adelina Moldovan
Iren-Adelina Moldovan
IGIgor Gómez
Igor Gómez
Many previous research studies have shown how local and even regional earthquakes can significantly affect the release of radon in the soil. The aim of this work is to investigate the relationship between radon measurements and the daily seismic activity rate and develop a methodology that allows estimating the seismic activity rate using only radon measurements. To carry out this study, the earthquake catalogue of the Vrancea region (Romania) has been used to estimate the daily seismic activity rate during a given time period, in which radon measurements were also recorded, from January 2016 to September 2020. The Vrancea zone represents the most active seismic zone in Europe and is located on the eastern edge of the strongly bent Carpathian arc. In the case of the radon measurements, seasonal behaviours and linear trends due to non-seismic factors have been identified and subsequently removed. The discrete wavelet transform has been used to analyse the radon signal at two different scales: long and short periods. From the analysis carried out on a long-period scale, an approximate linear relationship has been obtained between the radon series and the daily seismic activity rate, which provides insights into the behaviour of the seismic activity in the study region with only the radon information. In addition, the study reveals certain characteristics that could be used as precursors of earthquakes at different scales: weeks in the case of the estimated daily seismic activity rate, and days in the case of the short-period signal obtained by the wavelet analysis. The results obtained for this region allow us to hope that the analysis of the radon time series can become an effective complement to the conventional seismic analysis used in operational earthquake forecasting.

24 July 2023 in Geosciences
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BEBogdan Enescu
Bogdan Enescu
GCGhita Cristian
Ghita Cristian
IMIren-Adelina Moldovan
Iren-Adelina Moldovan
MRMircea Radulian
Mircea Radulian
Background: The intermediate-depth seismicity in the Vrancea region (Romania) is characterized by localized and persistent earthquake activity that culminates about two or three times in a century with the occurrence of a large event (M ≥ 6.5). Here we have revisited some important seismicity characteristics, using earthquake catalog data spanning two different time periods: 1960–1999 and 2005–2013. Methods: we have determined the b-value of the frequency-magnitude distribution of earthquakes, using a maximum likelihood procedure, and estimated the parameter β to quantify anomalous seismicity rate decreases and increases. Results: by using data from the first period, we have confirmed the existence of a decreased b-value in the deepest part of the seismogenic zone; by using data from the second period, we have statistically confirmed the seismic quiescence that preceded the occurrence of the 1977 M7.4 Vrancea earthquake. Conclusions: the decreased b-value has been interpreted either in terms of an increased lithostatic stress with depth or as an indicator of the depth range where the next major Vrancea earthquake may occur. The time variation of the seismicity parameter β may reveal anomalous seismic quiescence and increased earthquake rates that may precede the occurrence of large earthquakes.

21 November 2016 in Annals of Geophysics
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ACAngela Petruta Constantin
Angela Petruta Constantin
IMIren-Adelina Moldovan
Iren-Adelina Moldovan
ACAndreea Craiu
Andreea Craiu
MRMircea Radulian
Mircea Radulian
CIConstantin Ionescu
Constantin Ionescu
On November 22, 2014 at 21:14:17 local hour (19:14:17 GMT) a ML=5.7 crustal earthquake occurred in the area of Marasesti city of Vrancea county (Romania) - the epicenter was located at north latitude 45.87° and east longitude 27.16°, with a focal depth of 39 km. This earthquake is the main shock of a sequence that started with this and lasted until the end of January. During the sequence, characterized by the absence of foreshocks, a number of 75 earthquakes were recorded in 72 hours, the largest of which occurred in the same day with the main shock, at 22:30 (ML= 3.1). The crustal seismicity of Vrancea seismogenic region is characterized by moderate earthquakes with magnitudes that have not exceeded MW 5.9, this value being assigned to an earthquake that occurred in historical times on March 1, 1894 (Romplus catalogue). Immediately after the 2014 earthquake occurrence, the National Institute for Earth Physics (NIEP) sent macroseismic questionnaires in all affected areas, in order to define the macroseismic field of ground shaking. According to macroseismic questionnaires survey, the intensity of epicentral area reached VI MSK, and the seismic event was felt in all the extra-Carpathian area. This earthquake caused general panic and minor to moderate damage to the buildings in the epicentral area and the northeast part of country. The main purpose of this paper is to present the macroseismic map of the earthquake based on the MSK-64 intensity scale.

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LPLaura Petrescu
Laura Petrescu
IMIren-Adelina Moldovan
Iren-Adelina Moldovan
We designed a convolutional neural network application to detect seismic precursors in geomagnetic field records. Earthquakes are among the most destructive natural hazards on Earth, yet their short-term forecasting has not been achieved. Stress loading in dry rocks can generate electric currents that cause short-term changes to the geomagnetic field, yielding theoretically detectable pre-earthquake electromagnetic emissions. We propose a CNN model that scans windows of geomagnetic data streams and self-updates using nearby earthquakes as labels, under strict detectability criteria. We show how this model can be applied in three key seismotectonic settings, where geomagnetic observatories are optimally located in high-seismicity-rate epicentral areas. CNNs require large datasets to be able to accurately label seismic precursors, so we expect the model to improve as more data become available with time. At present, there is no synthetic data generator for this kind of application, so artificial data augmentation is not yet possible. However, this deep learning model serves to illustrate its potential usage in earthquake forecasting in a systematic and unbiased way. Our method can be prospectively applied to any kind of three-component dataset that may be physically connected to seismogenic processes at a given depth.

13 August 2021 in Atmosphere
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Victorin Emilian ToaderVictorin Emilian Toader
Victorin Emilian Toader
AMAndrei Mihai
Andrei Mihai
IMIren-Adelina Moldovan
Iren-Adelina Moldovan
CIConstantin Ionescu
Constantin Ionescu
MAMarmureanu Alexandru
Marmureanu Alexandru
ILIosif Lingvay
Iosif Lingvay
Large-scale radon monitoring is carried out due to the fact that it is directly responsible for public health. European Directive 2013/59/EURATOM has been transposed into the legislation of several countries and provides for the need for long-term monitoring of radon in homes and workplaces by setting the average annual reference level at 300 Bq/m3. At the same time, radon is a precursor factor, its emission being correlated with seismic and volcanic activity. In this case, the protection of the population is ensured by a forecast similar to a meteorological one. The NIEP (National Institute for Earth Physics) is developing a multidisciplinary real-time monitoring network in the most dangerous seismic area in Romania, Vrancea. This is located at the bend of the Carpathian Mountains and is characterized by deep earthquakes (over 80 km), with destructive effects over large distances. Implementing a multidisciplinary monitoring network that includes radon, involves finding the locations and equipment that will give the best results. There is no generic solution for achieving this, because the geological structure depends on the monitoring area, and in most cases the equipment does not offer the ability to transmit data in real time. The positioning of the monitoring stations was based on fault maps of the Vrancea area. Depending on the results, some of the locations were changed in pursuit of a correlation with zonal seismicity. Through repeated tests, we established the optimal sampling rate for minimizing errors, maintaining measurement accuracy, and ensuring the detection of anomalies in real time. The radon 222Rn was determined by the number of counts and ROI1 (region of interest) values, depending on the particularities of the equipment. Finally, we managed to establish a real-time radon monitoring network which transmits data to geophysical platforms and makes correlations with the seismicity in the Vrancea area. The equipment, designed to store data for long periods of time then manually download it with manufacturers’ applications, now works in real time, after we implemented software designed specifically for this purpose.

27 December 2020 in Atmosphere
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Victorin Emilian ToaderVictorin Emilian Toader
Victorin Emilian Toader
VNVictor Nicolae
Victor Nicolae
IMIren-Adelina Moldovan
Iren-Adelina Moldovan
CIConstantin Ionescu
Constantin Ionescu
MAMarmureanu Alexandru
Marmureanu Alexandru
This study analyzes the possibility to use geophysical and geochemical parameters in an OEF (Operational Earthquake Forecasting) application correlated with short-term changes in seismicity rates using a magnitude–frequency relationship. Tectonic stress over the limits of rock elasticity generates earthquakes, but it is possible that the emission of gases increases as a result of the breaking process. The question is how reliable is the emission of radon-222 and Carbon Dioxide (CO2), with effects on air ionization and aerosol concentration, in an OEF application? The first step is to select the seismic area (in our study this is the Vrancea area characterized by deep earthquakes at the bend of the Carpathian Mountains), then determine the daily and seasonal evolution of the forecast parameters, their deviations from the normal level, the short-term changes in seismicity rates using a magnitude–frequency relationship and finally to correlate the data with recorded seismic events. The results of anomaly detection, effect evaluation and data analysis alert the beneficiaries specialized in emergency situations (Inspectorate for Emergency Situations, organizations involved in managing special events). Standard methods such as the standard deviation from the mean value, time gradient, cross correlation, and linear regression are customized for the geological specificity of the area under investigation. For detection we use the short-time-average through long-time-average trigger (STA/LTA) method on time-integral data and the daily–seasonal variation of parameters is correlated with atmospheric conditions to avoid false decisions. The probability and epistemic uncertainty of the gas emissions resulting from this study, in addition to other precursor factors such as air ionization, time between earthquakes, temperature in the borehole, telluric currents, and Gutenberg Richter “a-b” parameters, act as inputs into a logical decision tree, indicating the possibility of implementing an OEF application for the Vrancea area. This study is novel in its analysis of the Vrancea area and performs a seismic forecasting procedure in a new form compared to the known ones.