Evaluation of the efficiency of chlorpyrifos-ethyl remediation by Methylobacterium radiotolerans and Microbacterium arthrosphaerae using response of some biochemical biomarkers

Environmental Science and Pollution Research - This study reveals out detoxifying and antioxidant enzyme response of Gammarus pulex exposed/polluted to chlorpyrifos-ethyl insecticide before and...     

Analysis of factors affecting industrial symbiosis collaboration

Environmental Science and Pollution Research - The rapidly increasing population causes an increase in consumption amounts day by day. This leads to negative effects such as the reduction of...     

Filyos River Streamflow Reconstruction from Tree‐Ring Chronologies with Nonparametric Approaches

The article presents nonparametric methods based on K nearest neighbors (KNNs), modified KNNs, and local polynomial techniques to reconstruct streamflow ensembles from tree‐ring data in Filyos River region (Turkey). Three methods were tested using cross‐validation for the overlap period, 1963‐1997 for which the tree‐ring and streamflow data are available. It was found that for the study where the length of the overlap period was limited, a nonparametric method based on a local polynomial technique provides simulations that have a slightly better solution than the other methods. After verification using standard statistical techniques, these methods were utilized to develop streamflow reconstructions from tree‐ring data for the paleo‐hydrologic period (1657‐1963). These reconstructions of seasonal low and high flows were discussed with the obtained flood duration curve. They were also compared with the historical archives and other tree‐ring reconstructions data available in the same river. Overall, the utility and limitations of these methods and the resulting streamflow simulations were discussed to assess the long‐term discharge behavior of Filyos River and to evaluate water supply reliability.     

Magnetic nanoparticles coated with aminated polymer brush as a novel material for effective removal of Pb(II) ions from aqueous environments

Environmental Science and Pollution Research - In the present study, a poly (vinylbenzyl chloride) grafted Fe3O4 nanoparticle (Fe3O4@PVBC) was prepared by surface-initiated reversible addition...     

Energy and exergy analysis of a heat storage tank with a novel eutectic phase change material layer of a solar heater system

Solar energy is one of the most important renewable energy sources, but it is not available every time and every season. Thus, storing of solar energy is important. One of the popular methods of heat storage is use of phase change materials (PCMs) which have large thermal energy storage capacity. In this study, the heat storage tank in a domestic solar water heating system was chosen as control volume. The experiments were performed in the province of Elaz?g, Turkey, in November when solar radiation was weak due to cloudy sky. The heat storage tank of the system was modified to fill PCM between insulation and hot water part. A few PCMs which are Potassium Fluoride, Lithium Metaborate Dihydrate, Strontium Hydroxide Octahydrate, Barium Hydroxide Octahydrate, Aluminum Ammonium Sulfate, and Sodium Hydrogen Phosphate were analyzed to proper operating conditions using a Differential Scanning Calorimeter (DSC) and the best PCM was obtained with the Aluminum Ammonium Sulfate and Sodium Hydrogen Phosphate mixture. Thus, eutectic PCM was obtained and used in a heat storage tank of the solar water heating system. Energy and exergy analysis of heat storage tank was performed with and without the PCM. Energy and exergy analysis has shown that the heat storage tank with the PCM is more efficient than without the PCM and the maximum exergy efficiency was obtained as 22% with the heat storage tank with the PCM.     

Precipitable water modelling using artificial neural network in Çukurova region

Precipitable water (PW) is an important atmospheric variable for climate system calculation. Local monthly mean PW values were measured by daily radiosonde observations for the time period from 1990 to 2006. Artificial neural network (ANN) method was applied for modeling and prediction of mean precipitable water data in Çukurova region, south of Turkey. We applied Levenberg–Marquardt (LM) learning algorithm and logistic sigmoid transfer function in the network. In order to train our neural network we used data of Adana station, which are assumed to give a general idea about the precipitable water of Çukurova region. Thus, meteorological and geographical data (altitude, temperature, pressure, and humidity) were used in the input layer of the network for Çukurova region. Precipitable water was the output. Correlation coefficient (R²) between the predicted and measured values for monthly mean daily sum with LM method values was found to be 94.00% (training), 91.84% (testing), respectively. The findings revealed that the ANN-based prediction technique for estimating PW values is as effective as meteorological radiosonde observations. In addition, the results suggest that ANN method values be used so as to predict the precipitable water.     

Genotoxic effects of water pollution on two fish species living in Karasu River,Erzurum, Turkey

Karasu River, which is the only river in the Erzurum plain, is the source of the Euphrates River (Eastern Anatolia of Turkey). The river is in a serious environmental situation as a result of pollution by agricultural and industrial sewage and domestic discharges. The present study aims to evaluate genotoxic effects of toxic metals in chub, Leuciscus cephalus, and transcaucasian barb, Capoeta capoeta, collected from contaminated site of the Karasu River, in comparison with fish from an unpolluted reference site. Heavy metal concentrations in surface water of the river were determined. The condition factor (CF) was taken as a general biomarker of the health of the fish, and genotoxicity assays such as micronucleus (MN) and other nuclear abnormalities (NA) were carried out on the fish species studied. MN and NA such as kidney-shaped nucleus, notched nucleus, binucleated, lobed nucleus, and blebbed nucleus were assessed in peripheral blood erythrocytes, gill epithelial cells, and liver cells of the fish. A significant decrease in CF values associated with a significant elevation in MN and NA frequencies was observed in fish collected from the polluted sites compared with those from the reference site. Results of the current study show the significance of integrating a set of biomarkers to identify the effects of anthropogenic pollution. High concentrations of heavy metals have a potential genotoxic effects, and the toxicity is possibly related to industrial, agricultural, and domestic activities.     

National assessment of sea level rise using topographic and census data for Turkish coastal zone

Turkish coastal zone elevation to sea level rise was illustrated by using digital elevation model and Geographical information systems methods. It was intended to determine several parameters such as population, settlements, land use, wetlands, contribution to national agricultural production and taxes at risk by using high resolution SRTM topographic, orthorectified Landsat Thematic Mapper Mosaics and census data with GIS methods within 0-10 m elevation of national level. All parameters were examined for coastal cities, coastal districts, settlements and villages' status. As a result of the analysis of data set, it was found that approximately 7,319 km(2) of land area lies below 10 m contour line in Turkey, and is hence highly vulnerable to sea-level rise. 28 coastal cities, 191 districts and 181 villages or towns are located below 10 m contour line in study area. In the short term, for the struggle of negative impact of sea level rise, the findings suggest that the Ministry of Environment should declare new areas as protection areas and develop special environmental programs for national level.     

Evaluation of surface water quality characteristics by using multivariate statistical techniques: A case study of the Euphrates river basin, Turkey

The surface water quality of the Euphrates river basin in Turkey are evaluated by using the multivariate statistical techniques known as factor analysis (FA) and multidimensional scaling (MDS) analysis. When FA was applied to the water quality data obtained from the 15 different surface water quality monitoring stations, two factors were identified, which were responsible from the 86.02% of the total variance of the water quality in the Euphrates river basin. The first factor called the urban land use factor explained 44.20% of the total variance and the second factor called the agricultural use factor explained 41.81% of the total variance. MDS technique showed that electrical conductivity (EC), percent sodium (Na%) and total salt are the most important variables causing difference in the water quality analysis.