Assessment of some trace heavy metals and radioactivity concentration in water of Bendimahi River Basin (Van, Turkey)

The levels of heavy metals were determined in the water of Bendimahi River Basin, statistically analysed and compared to natural gross radioactivity concentration. Fifteen samples of water were collected from Bendimahi River and Van Lake for two seasons in 2005. Water samples were analyzed for eight trace elements and concluded together with gross-alpha and gross-beta radioactivity concentrations. Atomic absorption spectrometry (AAS) was used to determine the concentrations of heavy metals in water samples collected from Bendimahi River basin. Correlation analysis was made for radioactivity and heavy metal concentrations and the Pearson correlation coefficients between gross-alpha and gross-beta radioactivity and heavy metal were determined. The concentrations of all metals were found to be higher than WHO, EC, EPA and TSE-266 guidelines for drinking water, except for Zn and Cu. Generally, the heavy metal concentrations in water samples obtained in May and in August were found to be in sequence of Fe>Zn>Pb>Cr>Cu>Mn>Co>Cd and Fe>Zn>Cu>Pb>Cr>Mn>Co>Cd, respectively. The gross-alpha and gross-beta activity concentration varies between 0.063 and 0.782, 0.021 and 0.816 Bq l(-1) in samples collected in May, and 0.009 and 0.037, 0.081 and 3.116 Bq l(-1) in samples collected in August.     

Gross alpha and beta radioactivity concentration in water, soil and sediment of the Bendimahi River and Van Lake (Turkey)

The concentrations of the natural radioactivity in water, soil and sediment samples collected from Bendimahi River which originates near the Tendürek Mountain (Van, Turkey), its tributaries and Van Lake (Turkey) were measured. The gross-alpha and gross-beta radioactivity concentrations were investigated in May and August in 2005. Determination of the gross-alpha and gross-beta radioactivity of river water, soil and sediment samples was obtained by using gas-flow proportional counter, PIC-MPC 9604-alpha/beta counter. In water samples, the obtained results show that in May; gross-alpha and gross-beta activity concentrations varied between 0.063-0.782 and 0.021-0.816 Bq l(-1) and in August the values were 0.009-0.037 and 0.081-3.116 Bq l(-1), respectively. The gross-alpha and gross-beta activity concentrations in soil samples ranged from 0.800 to 4.277 Bq g(-1) and 0.951 to 11.773 Bq g(-1) in May and 0.686 to 4.713 Bq g(-1) and 0.073 to 9.524 Bq g(-1) in August, respectively. Concentrations ranging from 0.782 to 4.596 Bq g(-1) and from 0.482 to 10.372 Bq g(-1) in May and from 0.580 to 5.824 Bq g(-1) and from 0.303 to 9.702 Bq g(-1) in August for gross-alpha and gross-beta radioactivity were observed in sediments, respectively.     

An indicative method for determination of the most hazardous changes in slopes of the subsidence basins in underground coal mining area in Ostrava (Czech Republic)

Considering growing population and decreasing mineral resource reserves, the issue of undermining has been and shall remain very topical. This study aims to identify the mutual connections between mined out panels of a deposit and the final manifestations on the ground surface related to deep black coal mining. On the grounds of the identified connections, the study describes a method to simplify a common evaluation of undermined areas according to building site categories. Within the study, a demarcation of the areas was conducted in two localities in Czech Republic influenced by the effects of undermining in the Upper-Silesian Basin. In the allotment of the CSM Mine, an area unsuitable for founding structures was defined from the centre of the worked out workings to the distance of 175 m from the panel's edge, for which the corresponding break angle is 78.3°. Similarly, in the allotment of the Paskov Mine, an area unsuitable for founding structures was determined to the distance of 500 m from the panel's edge, for which the corresponding break angle is 50.2°. This demarcation may be implemented prior to deposit mining being aware of several physical-mechanical parameters of rocks in the deposit's overburden. Having mined out a particular section of a deposit, it is recommended to verify the values of break angle using the method described herein. The study may be applied as a relatively fast and effective method to evaluate future land use for planning.     

Ambient air quality and asthma cases in Niğde, Turkey

Urban air quality is one of the key factors affecting human health. Turkey has transformed itself into an urban society over the last 30 years. At the same time, air pollution has become a serious impairment to health in many urban areas in the country. This is due to many reasons. In this study, a nonparametric evaluation was conducted of health effects that are triggered by urban air pollution. Ni?de, the city which is the administrative centre of Nigde province was chosen of the effects of air pollution since, like many central Turkish cities, it is situated on a valley where atmospheric inversion occurs. In this paper, the relationship between ambient urban air quality, namely PM₁₀ and sulphur dioxide (SO₂), and human health, specifically asthma, during the winter season is examined. Air pollution data and asthma cases from 2006 to 2010 are covered in this study. The results of our study indicate that total asthma cases reported in Nigde between 2008 and 2010 were highly dependent on ambient SO₂ concentration. More asthma cases were recorded when 30 μg?m^?3 or higher SO₂ was present in the ambient air than those recorded under cleaner ambient air conditions. Moreover, it was determined that in Nigde in 2010, asthma cases reported in males aged between 45 and 64 were closely correlated with ambient SO₂ (α?=?0.05).     

Organophosphate dichlorvos induced dose‐related differential alterations in lipid levels and lipid peroxidation in various regions of the fish brain and spinal cord

Abstract

The effect of dichlorvos (DDVP) (0–0, dimethyl 2: 2‐dichlorovinyl phosphate), on various lipid fractions and lipid peroxidation in the discrete areas of the brain and spinal cord were studied in the fresh water teleost (Heteropneustes fossilis). Fishes were exposed to three different doses (3.0, 6.0 and 9.0 ppm) of DDVP daily for 7 days. Dose‐related increase in the levels of total lipids, cholesterol and esterified fatty acids was detected in the fore brain, optic lobes, cerebellum, medulla oblongata and spinal cord. However, phospholipids were significantly decreased in the aforementioned regions of the central nervous system. The rate of lipid peroxidation was significantly increased in all the regions of the CNS.     

Prediction of Ambient PM10 and Toxic Metals Using Artificial Neural Networks

Abstract

In this study, an artificial neural network is employed to predict the concentration of ambient respirable particu-late matter (PM₁₀) and toxic metals observed in the city of Jaipur, India. A feed-forward network with a back-propagation learning algorithm is used to train the neural network the behavior of the data patterns. The meteorological variables of wind speed, wind direction, relative humidity, temperature, and time are taken as input to the network. The results indicate that the network is able to predict concentrations of PM₁₀ and toxic metals quite accurately.     

Farmers’ perception of sustainable agriculture and its determinants: a case study in Kahramanmaras province of Turkey

The primary purpose of this study was to assess in quantitative terms farmers’ perceptions of sustainable agriculture and to determine how those are influenced by different socio-economic characteristics and information-seeking behavior of the farmers. The study was conducted in Kahramanmaras province of Turkey and comprised a stratified sample of 208 farmers from four districts of the province. The farmers rated each of the 21 selected sustainable agricultural practices for importance on a 5-point scale, and the total of these ratings formed the sustainable agriculture perception index. The index score was calculated for each farmer and was treated as the dependent variable in the stepwise regression analysis procedure. The independent variables were such socio-economic characteristics as the farming system, the total and irrigated area of the farm, membership of a cooperative society and participation in village administration, and age, education, and income of the farmer; components of information-seeking behavior included use of the mass media (newspapers, radio, and television), use of the Internet, travel, and participation in farming events. The results of the study showed that the higher the socio-economic status (more frequent contact with extension services, higher education, ownership of land, etc.) and the greater the access to information, the greater the perceived importance of sustainable agricultural practices. It is concluded that if policy-makers and extension organizations concentrate on these factors, they are more likely to succeed in making farmers more favorably disposed toward sustainable agriculture.     

Assessing different sources of uncertainty in hydrological projections of high and low flows: case study for Omerli Basin,Istanbul, Turkey

This study investigates the assessment of uncertainty contribution in projected changes of high and low flows from parameterization of a hydrological model and inputs of ensemble regional climate models (RCM). An ensemble of climate projections including 15 global circulation model (GCM)/RCM combinations and two bias corrections (change factor (CF) and bias correction in mean (BC)) was used to generate streamflow series for a reference and future period using the Hydrologiska Byråns Vattenbalansavdelning (HBV) model with the 25 best-fit parameter sets based on four objective functions. The occurrence time of high flows is also assessed through seasonality index calculation. Results indicated that the inputs of hydrological model from ensemble climate models accounts for greater contribution to the uncertainty related to projected changes in high flows comparing to the contribution from hydrological model parameterization. However, the uncertainty contribution is opposite for low flows, particularly for CF method. Both CF and BC increases the total mean variance of high and low flows. The variability in the occurrence time of high flows through RCMs is greater than the variability resulted from hydrological model parameters with and without statistical downscaling. The CF provides more accurate timing than BC and it shows the most pronounced changes in flood seasonality.