Health risk assessment in an area of dental fluorosis disease from high fluoride drinking water: a case study from southeastern Türkiye.

This study focuses on identifying fluoride (F‒) concentrations and its health risk assessment (HRA) in drinking water sources in south-eastern Türkiye. Groundwater quality was assessed using some graphical approaches such as Schoeller and Piper diagrams and GIS mapping. Average daily exposure dosages through oral and dermal contact exposure routes were considered to determine the potential health risk of F‒ in groundwater. Groundwater samples were taken from 53 points in spring, summer, autumn, and winter seasons. The results showed that the average annual F‒ concentrations in water resources in the study area were 0.26‒3.62 mg/L. According to the HRA results, the highest F‒ health risk in this region was observed in children, followed by teenagers and adults. This study indicated that there is a strong relationship between the high health risk (4.28 > 3.5) in children and dental fluorosis caused by high F‒ concentration in groundwater.

Evaluation of pollution indicators and transported sediment content in agricultural drainage waters for reuse as irrigation, Harran Plain, Turkey.

The aim of this study is to determine the variation of certain pollution indicators and the level of sediment carried within drainage channel discharge waters following irrigation of fields on the Harfran Plain during the irrigation season. In this context, water samples were taken from 27 stations in total, including 26 drainage channels and 1 irrigation water channel (reference point), for 6 months between May 2020 and October 2020, and determined parameters were measured. Areal distribution maps were prepared with the ArcGIS program in order to better visually present the pollution level across the plain with the obtained data. The monthly changes of the analysis parameters and the significance level of the differences between the stations were determined using ANOVA analysis and the correlations between the measured parameters were determined using the Pearson correlation matrix SPSS package program. Evaluated on the basis of these areal distribution maps, it can be seen that the agricultural drainage waters of the Harran Plain are not suitable for irrigation in terms of five pollution indicators (pH, conductivity (EC), turbidity (Turb), sodium (Na+), and nitrate (NO3-)). Some sampling points in terms of pH (D9, R), conductivity (D10, D20), turbidity (all points) and Na + (as sodium adsorption rate) (D20) are in the "high usage restriction" category. In terms of conductivity, five points (D12, D13, D14, D15, D18); all points in terms of bicarbonate (HCO3-); and three points (D10, D12, D18) in terms of Na+ (as SAR) are classified as "low-medium usage restriction". According to the One-way ANOVA test performed to determine the differences between the points, there is a significant difference (p < 0.05) between the sampling points for all the following values: EC, dissolved oxygen (DO), Turb, Na+, HCO3-, chloride (Cl-), sulphate (SO42-), NO3-, pH, and transported sediment (TS), within the 95% confidence interval. In the test performed to determine the differences between the months, at the 95% confidence interval there is a significant difference (p < 0.05) between the months for parameters such as water temperature (WT), pH, DO, Turb, HCO3-, NO3-, and TS. There is a strong positive correlation between EC and Na+, Cl-, and NO3- (r = 0.785-0.915) and Turb and TS (r = 0.725). With regard to sustainable agricultural practice for the plain, it is thought that the obtained results will contribute to administrative decision-making at a variety of management levels.

Novel machine learning techniques based hybrid models (LR-KNN-ANN and SVM) in prediction of dental fluorosis in groundwater.

Studies have shown that excessive intake of fluoride into human body from drinking water may cause fluorosis adversely affects teeth and bones. Fluoride in water is mostly of geological origin and the amounts depend highly on many factors such as availability and solubility of fluoride minerals as well as hydrogeological and geochemical conditions. Chemical methods usually accomplish fluoride analysis in drinking water. The chemical methods are expensive, labor-intensive and time-consuming in general although accurate and reliable results are obtained. An alternative cost-effective approach based on machine learning (ML) technique is investigated in this study. Furthermore, most effective input parameters are selected via proposed Simulated Annealing (SA) search scheme. Selected subset (SAR, K+, NO3-, NO2-, Mn, Ba and Fe) by SA algorithm exhibited high correlation coefficient values of 0.731 and strong t test scores of 5.248. On the other hand, most frequently selected individual features were identified as NO3-, NO2-, Fe and SAR by vote map. The results of experiments revealed that selected feature subset improves the prediction performance of the learning models while feature size is reduced substantially. Thus it eventually enabled determination of fluoride in a cheap, fast and feasible way.

Water quality of Mediterranean coastal plains: conservation implications from the Akyatan Lagoon, Turkey.

The water quality of the Akyatan Lagoon was characterized using hydrochemical methodology. The lagoon is located on the Mediterranean coast and is the largest wetland ecosystem in Turkey. In addition, the lagoon is classified as a hyper-salinity wetland. Water samples were collected monthly between December 2007 and November 2008. Eleven stations within the lagoon were determined, and triplicate grab samples were obtained from each station to characterize water quality as follows: T °C, pH, total alkalinity (TAlk), dissolved oxygen (DO), total dissolved solids (TDS), salinity, electrical conductivity (EC), and main anions, including chloride (Cl(-)), nitrates (NO3 (-)), and sulfate (SO4 (2-)). Results from selected stations indicated varying TDS, EC, salinity, and Cl(-) concentrations, from 20,892 to 175,824 mg/L, from 35.7 to 99.6 mS/cm, from 22.3 to 71.0 ppt, and from 14,819 to 44,198 mg Cl(-)/L, respectively. Data indicated that the spatial distribution of water quality parameters was significantly affected by freshwater input via the constructed drainage channels which collect water from a catchment area and discharge water into the lagoon as a point source, thus preventing drainage water to reach the lagoon as a nonpoint source.