The application of energy-saving policies in buildings could lead to a decrease in the air exchange rate in dwellings, which could consequently lead to an increase in indoor radon concentration and, therefore, to an increase in resident exposure to ionizing radiation. The aim of the research presented in this paper is to investigate radiological exposure to residents due to the usage of different granites commonly used in Serbia as a building material. From the total of 10 analysed granite samples, a wide range of radon and thoron exhalation rates were found: from <161 μBq m⁻² s⁻¹ to 5220 ± 200 μBq m⁻² s⁻¹ and from <7 mBq m⁻² s⁻¹ to 5140 ± 320 mBq m⁻² s⁻¹, respectively. Assuming a low air exchange rate of 0.2 h⁻¹, the contribution of the measured granite material to the indoor radon concentration could go up to 150 Bq m⁻³. The estimated annual effective doses due to exposure to radon and thoron exhalation from the granite samples were (0.05–3.79) mSv and (<0.01–1.74) mSv, respectively. The specific activity of radionuclides ranged from 6.6 ± 0.5 Bq kg⁻¹ to 131.8 ± 9.4 Bq kg⁻¹ for ²²⁶Ra, from 0.5 ± 0.1 Bq kg⁻¹ to 120.8 ± 6.5 Bq kg⁻¹ for ²³²Th, and from 0.22 ± 0.01 Bq kg⁻¹ to 1321 ± 86 Bq kg⁻¹ for ⁴⁰K. The obtained external hazard index ranged from 0.03 to 1.48, with three samples above or very close to the accepted safety limit of 1. In particular, dwellings with a low air exchange rate (causing elevated radon) could lead to an elevated risk of radiation exposure.

Magnesium ferrite (MgFe2O4) particles were synthetized by sol-gel method and used in the decolorization of the Acid Violet 109 (anthraquinone dye, AV109) water solutions' by combination of adsorption and heterogeneous Fenton process. The material's morphology and elemental analysis of the surface were revealed by Scanning electron microscopy and Energy Dispersive Spectroscopy (SEM/EDS). The X-Ray Diffraction (XRD) technique was used to analyze the crystallographic phase. In the first part of the decolorization experiment, the adsorption ability of the synthesized particles was investigated. During the adsorption study influence of pH was investigated. In the second part of the decolorization experiment, the effects of the various parameters on the Fenton process were studied such as the initial concentrations of hydrogen peroxide, dye, and magnesium ferrite particles. Influence of magnesium ferrite particles structure, pH value and reaction temperature were also investigated. The decolorization reaction was followed by UV-Visible (UV-Vis) spectrophotometry. At optimal conditions, the dye decolorization was 99.1% (55.4% by adsorption and 43.7% by the Fenton process). Both the adsorption and the Fenton process obey second-order kinetics.

Magnesium ferrite (MgFe2O4) particles were synthetized by sol-gel method and used in the decolorization of the Acid Violet 109 (anthraquinone dye, AV109) water solutions' by combination of adsorption and heterogeneous Fenton process. The material's morphology and elemental analysis of the surface were revealed by Scanning electron microscopy and Energy Dispersive Spectroscopy (SEM/EDS). The X-Ray Diffraction (XRD) technique was used to analyze the crystallographic phase. In the first part of the decolorization experiment, the adsorption ability of the synthesized particles was investigated. During the adsorption study influence of pH was investigated. In the second part of the decolorization experiment, the effects of the various parameters on the Fenton process were studied such as the initial concentrations of hydrogen peroxide, dye, and magnesium ferrite particles. Influence of magnesium ferrite particles structure, pH value and reaction temperature were also investigated. The decolorization reaction was followed by UV-Visible (UV-Vis) spectrophotometry. At optimal conditions, the dye decolorization was 99.1% (55.4% by adsorption and 43.7% by the Fenton process). Both the adsorption and the Fenton process obey second-order kinetics.

The application of the principal component analysis and artificial neural network method in forecasting 137Cs behaviour in the air as the function of meteorological parameters is presented. The model was optimized and tested using 137Cs specific activities obtained by standard gamma-ray spectrometric analysis of air samples collected in Belgrade (Serbia) during 2009-2011 and meteorological data for the same period. Low correlation (r = 0.20) between experimental values of 137Cs specific activities and those predicted by artificial neural network was obtained. This suggests that artificial neural network in the case of prediction of 137Cs specific activity, using temperature, insolation, and global Sun warming does not perform well, which can be explained by the relative independence of 137Cs specific activity of particular meteorological parameters and not by the ineffectiveness of artificial neural network in relating these parameters in general.