Radioactivity of the soil in Vojvodina (northern province of Serbia and Montenegro)

The widespread public belief that during the bombardment of Vojvodina (Yugoslavia) this region was contaminated by depleted uranium has recently raised public concern with respect to the potential contamination of agricultural products due to soil radioactivity. Based on the gamma-spectrometric analysis of 50 soil samples taken from the region of Vojvodina we concluded that there is no increase of radioactivity that could endanger the food production. Taking into account the transfer factors of 137Cs to plants, the measured activity concentrations of this isotope should not endanger the health safety of the produced food. No traces of depleted uranium have been found. The natural radioactivity levels are compared with the results form other countries.     

Influence of suspended clay minerals and humic matter on the solid phase extraction efficiency of selected pesticides from water

The purpose of this investigation was to determine the influence of humic acids (HA) and Ca-montmorillonite (CaM) on the solid-phase extraction (SPE) efficiency of atrazine, alachlor and alpha-cypermethrin from water samples at various pH-values. The nature and intensity of binding of the studied pesticides to CaM were determined by X-ray diffraction analysis and termogravimetric analysis (TGA) test. The studied pesticides eluted from discs were analysed by thin-layer chromatography (TLC). The effects of CaM and humic acid were generally pH-dependent and acted independently in extraction efficiency influence. Lower recovery of pesticides was observed at higher pH values when CaM was > or =0.1 g and was attributed to greater dispersion of clay, increased surface area and subsequent adsorption. Concentrations of dissolved organic carbon (DOC) in humic acid had less effect on the extraction efficiency when water was at pH 8 compared to water at pH 2, which was probably due to greater nonpolar interactions of the pesticides to the charge-neutralized humic acid molecule.     

Impact of a severe flood on large-scale contamination of arable soils by potentially toxic elements (Serbia)

Environmental Geochemistry and Health - Extreme flooding in May, 2014 affected the sub-catchments of six major rivers in Serbia. The goal of the study was to evaluate the contents of potentially...     

Socio-demographic determinants of municipal waste generation: case study of the Czech Republic

Journal of Material Cycles and Waste Management - Increasing pressure of the European Union on diverting municipal waste from landfills requires an active role of households and commands a radical...     

Factors associated with driving under the influence of alcohol

Objective: This study examined the risk factors of driving under the influence of alcohol (DUI) among drivers of specific vehicle categories (DSC). On the basis of this research, the variables related to DUI and involvement in traffic crashes were defined. The analysis was conducted for car drivers, bicyclists, motorcyclists, bus drivers, and truck drivers.

Method: The research sample included drivers involved in traffic crashes on the territory of Serbia in 2016 (60,666). Two types of analyses were conducted in this study. Logistic regression established the correlation between DUI and DSC and the The Technique for Order of Preference by Similarity to Ideal Solution (Multi-criteria decision making) method was applied to consider the scoring and explore the potential for the prevalence of DUI on the basis of 2 data sets (DUI and non DUI).

Results: The study results showed that driver error and male drivers were the 2 most significant risk factors for DUI, with the highest scores and potential for prevalence. The nonuse of restraint systems, driver experience, and driver age are the factors with a significant prediction of involvement in an accident and an insignificant prediction of DUI.

Conclusions: Following the development of the logistic prediction models for DUI drivers, testing of the model was conducted for 3 control driver groups: Car, motorcycle, and bicycle. The prediction model with a probability greater than 50% showed that 77% of car drivers were under the influence of alcohol. Similarly, the prediction percentage for motorcyclists and bicyclists amounted to 71 and 67%, respectively. The recommendation of the study is that drivers whose DUI probability is above 50% should be potentially suspected of DUI. The results of this study can help to understand the problem of DUI among specific driver categories and detect DUI drivers, with the aim of creating successful traffic safety policy.