Trace element-based geochemical contamination characteristics and potential risks to human health: a case study from Northeast Turkey.

Trace elements measured in Artvin province soil samples in Northeast Turkey were assessed using pollution and health indices. The study area is positioned in one of the essential metallogenic belts in Turkey. This attempt is the first endeavor toward the study area in this context. The measured trace elements are As, Co, Cr, Cu, Mn, Ni, Pb and Zn, as they were assessed using pollution indices, enrichment factor, geo-accumulation index, contamination factor, and health risk assessment methods. According to the results of enrichment factor (EF), geo-accumulation index (Igeo), and contamination factor (CF), the soils of Artvin province show a slightly severe enrichment, moderately polluted and very high contaminated with arsenic, respectively. The pollution load index score (PLI) index (1.57) indicates that Artvin province is polluted in terms of trace elements. The hazard index (HI) calculated values for children and adults were 1.55 and 0.18, respectively. This revealed that the aforementioned metals can have non-carcinogenic effects (HI > 1). Total potential carcinogenic health risk (TCR) values for children and adults were 3.22 × 10-5 and 1.40 × 10-5, respectively. The non-carcinogenic risk level indicates that there may be a risk for children rather than adults.

Spatial interpolation and radiological mapping of ambient gamma dose rate by using artificial neural networks and fuzzy logic methods.

The aim of this study was to determine spatial risk dispersion of ambient gamma dose rate (AGDR) by using both artificial neural network (ANN) and fuzzy logic (FL) methods, compare the performances of methods, make dose estimations for intermediate stations with no previous measurements and create dose rate risk maps of the study area. In order to determine the dose distribution by using artificial neural networks, two main networks and five different network structures were used; feed forward ANN; Multi-layer perceptron (MLP), Radial basis functional neural network (RBFNN), Quantile regression neural network (QRNN) and recurrent ANN; Jordan networks (JN), Elman networks (EN). In the evaluation of estimation performance obtained for the test data, all models appear to give similar results. According to the cross-validation results obtained for explaining AGDR distribution, Pearson's r coefficients were calculated as 0.94, 0.91, 0.89, 0.91, 0.91 and 0.92 and RMSE values were calculated as 34.78, 43.28, 63.92, 44.86, 46.77 and 37.92 for MLP, RBFNN, QRNN, JN, EN and FL, respectively. In addition, spatial risk maps showing distributions of AGDR of the study area were created by all models and results were compared with geological, topological and soil structure.

Determination and mapping the spatial distribution of radioactivity of natural spring water in the Eastern Black Sea Region by using artificial neural network method.

In this study, radiological distribution of gross alpha, gross beta, (226)Ra, (232)Th, (40)K, and (137)Cs for a total of 40 natural spring water samples obtained from seven cities of the Eastern Black Sea Region was determined by artificial neural network (ANN) method. In the ANN method employed, the backpropagation algorithm, which estimates the backpropagation of the errors and results, was used. In the structure of ANN, five input parameters (latitude, longitude, altitude, major soil groups, and rainfall) were used for natural radionuclides and four input parameters (latitude, longitude, altitude, and rainfall) were used for artificial radionuclides, respectively. In addition, 75 % of the total data were used as the data of training and 25 % of them were used as test data in order to reveal the structure of each radionuclide. It has been seen that the results obtained explain the radiographic structure of the region very well. Spatial interpolation maps covering the whole region were created for each radionuclide including spots not measured by using these results. It has been determined that artificial neural network method can be used for mapping the spatial distribution of radioactivity with this study, which is conducted for the first time for the Black Sea Region.

Dose rate estimates and spatial interpolation maps of outdoor gamma dose rate with geostatistical methods; A case study from Artvin, Turkey.

In this study, compliance of geostatistical estimation methods is compared to ensure investigation and imaging natural Fon radiation using the minimum number of data. Artvin province, which has a quite hilly terrain and wide variety of soil and located in the north-east of Turkey, is selected as the study area. Outdoor gamma dose rate (OGDR), which is an important determinant of environmental radioactivity level, is measured in 204 stations. Spatial structure of OGDR is determined by anisotropic, isotropic and residual variograms. Ordinary kriging (OK) and universal kriging (UK) interpolation estimations were calculated with the help of model parameters obtained from these variograms. In OK, although calculations are made based on positions of points where samples are taken, in the UK technique, general soil groups and altitude values directly affecting OGDR are included in the calculations. When two methods are evaluated based on their performances, it has been determined that UK model (r = 0.88, p < 0.001) gives quite better results than OK model (r = 0.64, p < 0.001). In addition, as a result of the maps created at the end of the study, it was illustrated that local changes are better reflected by UK method compared to OK method and its error variance is found to be lower.

Radiochemical characterization of mineral waters in the Eastern Black Sea Region, Turkey.

This study has evaluated the levels of natural radionuclides and chemical components of mineral waters in the Eastern Black Sea Region (Turkey). The mean activity concentrations of (226)Ra, (232)Th, (137)Cs, (40)K, gross alpha and gross beta were found as 129, 33, 28, 714, 125 and 170 mBq L(-1), respectively. Due to consumption of mineral waters, the radiological impact of them on the inhabitants was calculated by taking the annual intake into account through ingestion of aforementioned radionuclides. The estimated effective doses from mineral water were found to be 13.20 µSv year(-1) ((226)Ra), 2.74 µSv year(-1) ((232)Th), 0.13 µSv year(-1) ((137)Cs) and 1.62 µSv year(-1) ((40)K). The overall contribution of these radionuclides to the committed effective dose from a year's consumption of mineral water in the region is therefore estimated to be only 17.69%, which is in concordance with the recommended WHO value (100 µSv year(-1)). The chemical analysis results showed that these waters contain Na, Al, P, Cl, K, Ca, V, Mn, Fe, Ni, Cu and Zn elements. These values were evaluated and compared with the internationally verified values. This study provides important information for consumers and authorities because of their internal radiochemical exposure risk from mineral water intake.