Projects / Programmes source: ARIS

Identification of the anomalies in radon transport caused by seismic activity

Research activity

Code Science Field Subfield
1.04.00  Natural sciences and mathematics  Chemistry   

Code Science Field
P400  Natural sciences and mathematics  Physical chemistry 
P305  Natural sciences and mathematics  Environmental chemistry 
radon, mercury, air, thermal water, anomalies, seismic activity, correlation
Evaluation (rules)
source: COBISS
Researchers (11)
no. Code Name and surname Research area Role Period No. of publicationsNo. of publications
1.  06264  PhD Tadej Dolenec  Geology  Researcher  2004 - 2006  483 
2.  15723  Petra Dujmović    Technical associate  2004 - 2007  81 
3.  19724  Vesna Fajon    Technical associate  2004 - 2007  296 
4.  05027  PhD Milena Horvat  Chemistry  Researcher  2004 - 2007  1,887 
5.  01345  PhD Ivan Kobal  Chemistry  Researcher  2004 - 2006  478 
6.  15814  PhD Jože Kotnik  Geology  Researcher  2004 - 2007  387 
7.  18545  PhD Jasmina Kožar Logar  Physics  Researcher  2004 - 2005  171 
8.  19822  Barbara Svetek    Technical associate  2004 - 2007  89 
9.  10968  PhD Janja Vaupotič  Chemistry  Head  2004 - 2007  604 
10.  19246  PhD Boris Zmazek  Chemistry  Researcher  2004 - 2007  124 
11.  24016  MSc Mladen Živčić  Geology  Researcher  2004 - 2007  253 
Organisations (1)
no. Code Research organisation City Registration number No. of publicationsNo. of publications
1.  0106  Jožef Stefan Institute  Ljubljana  5051606000  90,724 
In the selected karst caves, mercury and radon and its decay products together with their unattached fracion in air, air temperature and relative humidity, barometric pressure will be measured. Also outdoor air temperature and barometric pressure, rainfall, will be recorded. By analysing time series of measured parametrs, we will obtain their mutual correlation and identify anomalies in Rn and Hg levels, possibly related to seismic activity. At selected sites, Rn and Hg will be measured in soil gas and in thermal/mineral waters. Also recorded will be hydrometeorological parameters, such as air, soil and water tempearture, barometric and hydrostatic pressure, wind speed and direction, which play a crucial role in the transport of Rn and Hg in the ground, and their exhalation into the atmosphere. We shall analyse time series of Rn and Hg levels and pay special attention to those fluctuations not undrestood merely on the basisi of hydrometeorlogical effects but possibly related to earthquakes, activity of faults or earth avalanches. For data evaluation, machine learning methods will be used, among them preferencially the regression trees.
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