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.     

Analysis of Heavy Metals in the Endometrial Tissue Using Electron Microscope

Objective This study was done to estimate whether heavy metals in the air may affect endometrial chemical composition. Materials and Methods A total of 30 albino Wistar rats were employed and randomly divided into three groups. The rats of Group 1 and 2 were acutely and sub-chronically exposed to the gas form of heavy metals, respectively. Group 3 was used as a control group. Endometrial tissue worth of heavy metals of the groups was measured in through using scanning electron microscope. Results A statistically no significant difference was found for endometrial chemical composition of all of the heavy metals (chrome, manganese, iron, cobalt, nickel, zinc and lead) between group 1 and 2 (p > 0.05). On the other hand, there was statistically significant difference for all of the heavy metals between group 1 and group 3 (p < 0.05), while there was statistically significant difference for chrome, manganese, iron, cobalt and nickel (p < 0.05), but zinc and lead (p > 0.05) between group 2 and 3. Conclusion Air pollutants of Pb and Zn resulting mostly from combustion of fossil fuels and certain special industrial process in Kirikkale may be a risk factor for the high pregnancy loses by changing endometrial homeostasis.     

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.     

Estimation of suspended sediment concentration from turbidity measurements using artificial neural networks

Suspended sediment concentration (SSC) is generally determined from the direct measurement of sediment concentration of river or from sediment transport equations. Direct measurement is very costly and cannot be conducted for all river gauge stations. Therefore, correct estimation of suspended sediment amount carried by a river is very important in terms of water pollution, channel navigability, reservoir filling, fish habitat, river aesthetics and scientific interests. This study investigates the feasibility of using turbidity as a surrogate for SSC as in situ turbidity meters are being increasingly used to generate continuous records of SSC in rivers. For this reason, regression analysis (RA) and artificial neural networks (ANNs) were employed to estimate SSC based on in situ turbidity measurements. The SSC was firstly experimentally determined for the surface water samples collected from the six monitoring stations along the main branch of the stream Harsit, Eastern Black Sea Basin, Turkey. There were 144 data for each variable obtained on a fortnightly basis during March 2009 and February 2010. In the ANN method, the used data for training, testing and validation sets are 108, 24 and 12 of total 144 data, respectively. As the results of analyses, the smallest mean absolute error (MAE) and root mean square error (RMSE) values for validation set were obtained from the ANN method with 11.40 and 17.87, respectively. However these were 19.12 and 25.09 for RA. It was concluded that turbidity could be a surrogate for SSC in the streams, and the ANNs method used for the estimation of SSC provided acceptable results.     

Spatial distribution and source identification of trace elements in topsoil from heavily industrialized region,Aliaga, Turkey

Topsoil samples (n?=?40) were collected from a heavily industrialized region in Turkey. The region includes several scrap processing iron–steel plants with electric arc furnaces (EAFs), a petroleum refinery, a petrochemical complex, steel rolling mills, a natural gas-fired power plant, ship-breaking yards and very dense transportation activities. The region has undergone a rapid transition from an agricultural region to a heavily industrialized region in the last three decades. Collected soil samples were analyzed for 48 trace elements using inductively coupled plasma-mass spectrometry (ICP-MS). The elemental distribution pattern in the region indicated that Nemrut area with dense iron–steel production activities was a hotspot for elemental pollution. In addition to crustal elements, concentrations of anthropogenic trace elements (i.e., Fe, Zn, Pb, Mn, Cu, Cd, Cr and Mo) were very high in the area influencing many parts of the region. Elemental compositions of fugitive sources polluting the soil (i.e., paved and unpaved roads, slag piles, EAFs filter dust piles and coal piles) were also determined. The methods (enrichment factors [EFs] and the index of geoaccumulation [I _geo]) used for determination of pollution status of soil showed that Cr, Ag, Zn, As and Pb were the strongly contaminating elements for the region. Principal component analysis (PCA) clearly indicated that anthropogenic sources (steel production, refinery and petrochemical processes and traffic) were important sources in this region.     

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.     

Influences of urban wastewaters on the stream water quality: a case study from Gumushane Province, Turkey

Urban wastewater in Turkey is primarily discharged without treatment to marine environments, streams and rivers, and natural and artificial lakes. Since it has been well established that untreated effluent in multi-use waters can have acute and chronic impacts to both the environment and human health, it is important to evaluate the consequences of organic enrichment relative to the structure and function of aquatic environment. We investigated the impacts of untreated municipal wastewater discharge from the city of Gumushane in the Eastern Black Sea Region of Turkey on the surface water quality of the stream Harsit. Several key water-quality indicators were measured: chemical oxygen demand (COD), ammonium nitrogen (NH ₄ ⁺ –N), nitrite nitrogen (NO ₂ ^? –N), nitrate nitrogen (NO ₃ ^? –N), total Kjeldahl nitrogen (TKN), total nitrogen (TN), orthophosphate phosphorus (PO ₄ ^3? –P), methylene blue active substances (MBAS), water temperature (t), pH, dissolved oxygen (DO), and electrical conductivity (EC). The monitoring and sampling studies were conducted every 15 days from March 2009 to February 2010 at three longitudinally distributed stations. While t, pH, DO, and EC demonstrated relatively little variability over the course of the study, other parameters showed substantial temporal and spatial variations. The most dramatic differences were noted in COD, NH ₄ ⁺ –N, NO ₂ ^? –N, TKN, TN, PO ₄ ^3— P, and MBAS immediately downstream of the wastewater discharge. Concentration increases of 309 and 418 % for COD, 5,635 and 2,162 % for NH ₄ ⁺ –N, 2,225 and 674 % for NO ₂ ^? –N, 283 and 478 % for TKN, 208 and 213 % for PO ₄ ^3? –P, and 535 and 1,260 % for MBAS were observed in the summer and autumn, respectively. These changes were associated with greatly diminished seasonal stream flows. Based on NO ₂ ^? –N, TKN, PO ₄ ^3— P, and MBAS concentrations, it was concluded that Harsit stream water was correctly classified as polluted. The most telling parameter, however, was NH ₄ ⁺ –N, which indicated highly polluted waters in both the summer and autumn. The elevated concentrations of both P and N in the downstream segment of the stream triggered aggressive growth of submerged algae. This eutrophication of river systems is highly representative of many urban corridors and is symptomatic of ongoing organic enrichment that must be addressed through improved water treatment facilities.