First Evolution of Radon Concentrations Spatial Distribution based on the
geological parameters and multiple linear regression method in schools
of Sjenica community, Western Serbia (Balkan area)
Purpose: The paper deals with the analysis of radon survey in 34 schools
over Sjenica community, in West Serbia, aiming at systematically continuation
of previously performed surveys
(2008-2010)
in the 340 schools
in
South
Serbia,
as
the project
activities
(Serbian
Ministry
of
Education
Since
and Technical Development) considering
optimization of
the
design of a national survey and improving the knowledge of radon distribution
in Serbia. In addition , the results of this survey triggered, based
on
Sjenica (Pestar)
region complex geology and measured annual Rn
concentrations,
an attempt of
the
explanation
of radon
spatial
variation
in Sjenica community by multivariable linear regression (MLR) method in
total of 36 public buildings investigated (beside schools, the kindergarten
and meterological station).
Argumatation: Schools are workplaces which are subject to Rn regulations
(EC 2014,BSS).Among other, the
BSS require
establishing reference
levels
for long-term
indoor
Rn
concentration,
not
exceeding
300
Bq/m3
for
both
dwellings
and workplaces.
The
36
public buildings were surveyed
the whole
year
in
the Sjenica
community in
West Serbia
by long
term
measurements
with CR-39 detectors (commercially
named Gamma
1, Landaurer, Sweden).
Sjenica community is
the largest
community
of
1059 km2
surface in Serbia and it was found that indoor radon
(Rn)
lower
than 100 Bq/m3 are most probable and although with lower probability,that
Rn higher
than
action
level
of 300
Bq/m3could occur
in
14%
of
the
buildings , indicating potential of the
investigated
area as high
natural
background
area.
The
highest
measured
indoor
Rn
concentration
was 1130 Bq/m3.
Conclusion: The predictive model was developed, in order to determine
how geological parameters best merge to explain the indoor radon
concentrations. The results of this investigation highlight that it is possible
to predict indoor radon concentrations using the geological data to an
acceptable level of accuracy with a limited number of measurements.
There is potential of the investigated area as high natural background
area
