Sjenica, a newly identified radon priority area in Serbia, and radon data correlated with geological parameters using the multiple linear regression model

2019
Authors
Žunić, Zora S.Stojanovska, Zdenka A.
Boev, Blažo
Šorša, Ajka

Čeliković, Igor T.

Ćurguz, Zoran
Ronnquist, Tryggve
Janićijević, Aco

Alavantić, Dragan

Article (Published version)

Metadata
Show full item recordAbstract
The paper deals with the analysis of the annual indoor radon concentrations variations due to different geological parameters of Sjenica community, Western Serbia. The measured Rn-222 concentrations were ranging from 10 to 1130 Bq/m(3). In 14% of the buildings, the radon action level of 300 Bq/m(3) is exceeded, indicating that Sjenica community could be characterized as a radon priority area. Each of 35 measuring location was georeferenced and corresponding lithostratigraphic units and geological period was assigned. Data were analyzed using the multiple linear regression (MLR) method and two predictive models were developed. The MLR model generated by the geological periods explained 17% of the radon variability while, the better one, was the lithostratigraphic MLR model, which explained 52% of the radon variability. Analysis has shown that lithostratigraphic units are important parameters in the prediction of radon levels.
Keywords:
Radon priority area / Sjenica / schools / geology / multiple linear regressionSource:
Carpathian Journal of Earth and Environmental Sciences, 2019, 14, 1, 235-244Publisher:
- North Univ Baia Mare, Baia Mare
Funding / projects:
- An integral study to identify the regional genetic and environmental risk factors for the common noncommunicable diseases in the human population of Serbia - INGEMA_S (RS-41028)
- Nuclear physics, methods and application (RS-171018)
DOI: 10.26471/cjees/2019/014/075
ISSN: 1842-4090
WoS: 000454673000023
Scopus: 2-s2.0-85059907374
Institution/Community
Tehnološko-metalurški fakultetTY - JOUR AU - Žunić, Zora S. AU - Stojanovska, Zdenka A. AU - Boev, Blažo AU - Šorša, Ajka AU - Čeliković, Igor T. AU - Ćurguz, Zoran AU - Ronnquist, Tryggve AU - Janićijević, Aco AU - Alavantić, Dragan PY - 2019 UR - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/4340 AB - The paper deals with the analysis of the annual indoor radon concentrations variations due to different geological parameters of Sjenica community, Western Serbia. The measured Rn-222 concentrations were ranging from 10 to 1130 Bq/m(3). In 14% of the buildings, the radon action level of 300 Bq/m(3) is exceeded, indicating that Sjenica community could be characterized as a radon priority area. Each of 35 measuring location was georeferenced and corresponding lithostratigraphic units and geological period was assigned. Data were analyzed using the multiple linear regression (MLR) method and two predictive models were developed. The MLR model generated by the geological periods explained 17% of the radon variability while, the better one, was the lithostratigraphic MLR model, which explained 52% of the radon variability. Analysis has shown that lithostratigraphic units are important parameters in the prediction of radon levels. PB - North Univ Baia Mare, Baia Mare T2 - Carpathian Journal of Earth and Environmental Sciences T1 - Sjenica, a newly identified radon priority area in Serbia, and radon data correlated with geological parameters using the multiple linear regression model EP - 244 IS - 1 SP - 235 VL - 14 DO - 10.26471/cjees/2019/014/075 ER -
@article{ author = "Žunić, Zora S. and Stojanovska, Zdenka A. and Boev, Blažo and Šorša, Ajka and Čeliković, Igor T. and Ćurguz, Zoran and Ronnquist, Tryggve and Janićijević, Aco and Alavantić, Dragan", year = "2019", abstract = "The paper deals with the analysis of the annual indoor radon concentrations variations due to different geological parameters of Sjenica community, Western Serbia. The measured Rn-222 concentrations were ranging from 10 to 1130 Bq/m(3). In 14% of the buildings, the radon action level of 300 Bq/m(3) is exceeded, indicating that Sjenica community could be characterized as a radon priority area. Each of 35 measuring location was georeferenced and corresponding lithostratigraphic units and geological period was assigned. Data were analyzed using the multiple linear regression (MLR) method and two predictive models were developed. The MLR model generated by the geological periods explained 17% of the radon variability while, the better one, was the lithostratigraphic MLR model, which explained 52% of the radon variability. Analysis has shown that lithostratigraphic units are important parameters in the prediction of radon levels.", publisher = "North Univ Baia Mare, Baia Mare", journal = "Carpathian Journal of Earth and Environmental Sciences", title = "Sjenica, a newly identified radon priority area in Serbia, and radon data correlated with geological parameters using the multiple linear regression model", pages = "244-235", number = "1", volume = "14", doi = "10.26471/cjees/2019/014/075" }
Žunić, Z. S., Stojanovska, Z. A., Boev, B., Šorša, A., Čeliković, I. T., Ćurguz, Z., Ronnquist, T., Janićijević, A.,& Alavantić, D.. (2019). Sjenica, a newly identified radon priority area in Serbia, and radon data correlated with geological parameters using the multiple linear regression model. in Carpathian Journal of Earth and Environmental Sciences North Univ Baia Mare, Baia Mare., 14(1), 235-244. https://doi.org/10.26471/cjees/2019/014/075
Žunić ZS, Stojanovska ZA, Boev B, Šorša A, Čeliković IT, Ćurguz Z, Ronnquist T, Janićijević A, Alavantić D. Sjenica, a newly identified radon priority area in Serbia, and radon data correlated with geological parameters using the multiple linear regression model. in Carpathian Journal of Earth and Environmental Sciences. 2019;14(1):235-244. doi:10.26471/cjees/2019/014/075 .
Žunić, Zora S., Stojanovska, Zdenka A., Boev, Blažo, Šorša, Ajka, Čeliković, Igor T., Ćurguz, Zoran, Ronnquist, Tryggve, Janićijević, Aco, Alavantić, Dragan, "Sjenica, a newly identified radon priority area in Serbia, and radon data correlated with geological parameters using the multiple linear regression model" in Carpathian Journal of Earth and Environmental Sciences, 14, no. 1 (2019):235-244, https://doi.org/10.26471/cjees/2019/014/075 . .