[Show abstract][Hide abstract] ABSTRACT: Chemical fractionation of seven heavy metals (Cd, Cr, Cu, Mn, Ni, Pb and Zn) was studied using a modified three-step sequential procedure to assess their impacts in the sediments of the Seyhan River, Turkey. Samples were collected from six representative stations in two campaigns in October 2009 and June 2010, which correspond to the wet and dry seasons, respectively. The total metal concentrations in the sediments demonstrated different distribution patterns at the various stations. Cadmium was the only metal that was below detection at all stations during both sampling periods. Metal fractionation showed that, except for Mn and Pb, the majority of metals were found in the residual fraction regardless of sampling time, indicating that these metals were strongly bound to the sediments. The potential mobility of the metals (non-residual fractions) is reflected in the following ranking: Pb > Mn > Zn > Cu > Ni > Cr in October 2009 and Mn > Pb > Zn > Cu > Ni > Cr in June 2010. The second highest proportion of metals was bound to organic matter/sulfides, originating primarily from anthropogenic activities. Non-residual metal fractions for all stations were highest in June 2010, which may be linked to higher organic matter concentrations in the sediment samples with 1.40% and 15.1% in October 2009 and June 2010, respectively. Potential sediment toxicity was evaluated using the Risk Assessment Code (RAC). Based on RAC classification, Cd and Cr pose no risk, Cu and Ni pose low risk, Pb and Zn were classified as medium risk metals, while the environmental risk from Mn was high. In addition, based on the sediment quality guidelines (SQG), the Seyhan River can be classified as a river with no, to moderate, toxicological risks, based on total metal concentrations.
Journal of Environmental Management 09/2011; 92(9):2250-9. · 3.06 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The aim of this study was to assess the level of heavy metals (Al, Cd, Cr, Cu, Fe, Mn, Ni, Pb, and Zn) contamination and enrichment in the surface sediments of the Seyhan River, which is the receiving water body of both treated and untreated municipal and industrial effluents as well as agricultural drainage waters generated within Adana, Turkey. Sediment and water samples were taken from six previously determined stations covering the downstream of the Seyhan dam during both wet and dry seasons and the samples were then analyzed for the heavy metals of concern. When both dry and wet seasons were considered, metal concentrations varied significantly within a broad range with Al, 7210–33 967 mg kg−1 dw; Cr, 46–122 mg kg−1 dw; Cu, 6–57 mg kg−1 dw; Fe, 10 294–26 556 mg kg−1 dw; Mn, 144–638 mg kg−1 dw; Ni, 82–215 mg kg−1 dw; Pb, 11–75 mg kg−1 dw; Zn, 34–146 mg kg−1 dw in the sediments while Cd was at non‐detectable levels for all stations. For both seasons combined, the enrichment factor (EF) and the geo‐accumulation index (I geo) for the sediments in terms of the specified metals ranged from 0.56 to 10.36 and −2.92 to 1.56, respectively, throughout the lower Seyhan River. The sediment quality guidelines (SQG) of US‐EPA suggested the sediments of the Seyhan River demonstrated “unpolluted to moderate pollution” of Cu, Pb, and Zn, “moderate to very strong pollution” of Cr and Ni. The water quality data, on the other hand, indicated very low levels of these metals suggesting that the metal content in the surface sediments were most probably originating from fine sediments transported along the river route instead of water/wastewater discharges with high metal content.
CLEAN - Soil Air Water 02/2011; 39(2):185 - 194. · 2.05 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: This study investigates the predictive ability of gene-expression programming (GEP) in the estimation of methane yield (Ym) and effluent substrate (Se) produced by two anaerobic filters. The modeling study was carried out using the data obtained from two upflow anaerobic filters – one mesophilic (35°C) and one thermophilic (55°C) – operated for the treatment of paper-mill wastewater under varying organic loadings. The GEP model was composed of three inputs, hydraulic retention time (Thr), organic loading rate (Rol), and influent substrate (Si), and one output, either Se or Ym. The Stover–Kincannon model was also used for data analysis and to evaluate the prediction ability. Three statistical criteria, root mean square error (RMSE), determination coefficient (R2), and Akaike's information criteria (AIC), were the means used for comparison. The results showed that the GEP approach predicted the performance of both anaerobic filters much better than the Stover–Kincannon model.
[Show abstract][Hide abstract] ABSTRACT: Total carbon, nitrogen, and phosphate parameters were studied for the first time in the groundwater in the Silifke coastal plain, which is a RAMSAR site in Turkey. Seasonal variations of these parameters in the plain were examined based on groundwater data collected from 21 wells during the winter, spring, summer, and fall seasons. Total dissolved organic carbon (DOC), inorganic carbon (DIC), inorganic phosphate (DIP), inorganic nitrogen (DIN), and total alkalinity (TAlk) average values in the groundwater were low in all seasons (<2.2 mg/L for DOC; <54 mg/L for DIC; <0.06 mg/L for DIP; <1.5 mg/L for DIN; <232 mg/L for TAlk). The results showed a strong relationship between DIC and as expected. The results indicate that the content of these parameters in the groundwater of Silifke coastal plain pose no or little risk at present. However, computed Langelier Saturation Index (LSI) values indicated that the groundwater has a tendency to form scale and CaCO3 precipitation may occur.
CLEAN - Soil Air Water 12/2010; 38(12):1137 - 1145. · 2.05 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: In this study the performance of the upflow anaerobic filter (UAF) reactor treating cyanide was simulated using three different neural network techniques (ANNs) – multi-layer perceptron (MLP) neural network, radial basis neural network (RBNN), and generalized regression neural network (GRNN). The performance of UAF reactor over a period of 130 days at different cyanide concentrations was evaluated with these robust models. Influent chemical oxygen demand (CODin), hydraulic retention time (HRT), and influent cyanide concentration (CNin) were the inputs of the models, whereas the output variable was effluent chemical oxygen demand (CODeff). The models’ results were compared with each other using four statistical criteria – root mean square error (RMSE), mean absolute error (MAE), mean absolute relative error (MARE), and determination coefficient (R2). The results showed that the MLP neural network with Levenberg–Marquardt algorithm was found to be better than the RBNN and GRNN techniques.
Advances in Engineering Software 07/2010; · 1.22 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The Silifke plain is located near the coast of the Mediterranean Sea in Turkey. The delta in the plain is a highly fertile land that supports the agriculture of more than twenty types of crop. Some trace element content of the groundwater samples taken from the existing wells in this area are analyzed using inductively coupled plasma optical emission spectrometry (ICP-OES). The mean levels (ppm) of boron (B), barium (Ba), iron (Fe), manganese (Mn), lead (Pb), zinc (Zn), total chromium (TCr), cadmium (Cd), copper (Cu), aluminum (Al), and nickel (Ni) were obtained for the sampling points in the area for four seasons. Groundwater samples taken in the study area don't exhibit significantly elevated levels of these elements during a period of twelve months between December 2007 and November 2008. Furthermore, all of the elements exhibit values lower than 0.005 ppm, with the exception of B, Ba, and Fe. The results demonstrate that although these three elements produce the highest values, most are found to be appropriate for activities such as irrigation and human consumption in terms of trace elements.
CLEAN - Soil Air Water 03/2010; 38(3):221 - 224. · 2.05 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Hydrochemical characterization of the Silifke Plain coastal aquifer was accomplished in this research in order to investigate the water quality of groundwater. The aquifer is located along the Mediterranean coast and forms one of the most productive aquifers in Turkey. Groundwater samples were collected from the aquifer as monthly between December 2007 and November 2008 for 12 months. Twenty one artesian wells were chosen and water sampling was made once a month. The values of electrical conductivity (EC) and pH as well as main anions and cations were determined twice for each month. Based on the observations in the water wells, the EC, sodium adsorption rate (SAR), and chloride (Cl−) concentrations varied between 437 and 3480 µS/cm, 0.13 and 23.1, and 25 and 1661 mg Cl−/L, respectively. Deterioration of water quality was observed in some areas very close to the sea due to seawater intrusion and intense use of groundwater for irrigation.
[Show abstract][Hide abstract] ABSTRACT: Two anaerobic filters, one mesophilic (35 degrees C) and one thermophilic (55 degrees C), were operated with a papermill wastewater at a series of organic loadings. The hydraulic retention time (HRT) ranged from 6 to 24 h with organic loading rates (OLR) 1.07-12.25 g/l per day. At loading rates up to 8.4 g COD/l d, there was no difference in terms of the removal of soluble COD (SCOD) and gas production. At the higher organic loading rate, the SCOD removal performance of thermophilic digester was slightly better compare to mesophilic digester. Similar trend was also observed in terms of the daily methane production. The stability of thermophilic digester was also better than mesophilic digester particularly for the higher organic loadings. Volatile fatty acid accumulation was observed in the effluent of the mesophilic filter at the higher organic loading rates. The Stover-Kincannon model was applied to both digesters and it was found that model was applicable to both digesters for papermill wastewater. K(B) and U(max) constants from the Stover-Kincannon model were also derived.
[Show abstract][Hide abstract] ABSTRACT: Water treatment works using coagulation/flocculation in the process stream will generate a waste sludge. The works in Adana, Turkey uses ferric chloride. The potential for using this sludge for the treatment of reactive, direct, disperse, acidic, and basic dyestuffs by coagulation and sorption has been investigated. The sludge acted as a coagulant and removed colour with excellent removal efficiencies being obtained for basic, disperse and direct dyes. The optimum conditions were a pH value of 5 and a sludge dose of 2000 mg l(-1). Mediocre results were obtained for acidic and reactive dyes. The efficiency of the sludge was also compared with alum and ferric chloride for the same group of dyes. The sludge was also used as a coagulant to treat the wastewater from a textile factory. At doses of 2000-4000 mg l(-1), the sludge was as effective as ferric chloride and alum at removing COD. Sorption tests showed that the disperse and reactive dyes did not bind to the sludge. Langmuir and Freundlich constants were determined for the other three types of dye. Rate constants for the adsorption were determined using the Lagergren equation.