Kaan Yetilmezsoy

Response surface modeling of Pb(II) removal from aqueous solution by Pistacia vera L.: Box-Behnken experimental design.

A three factor, three-level Box-Behnken experimental design combining with response surface modeling (RSM) and quadratic programming (QP) was employed for maximizing Pb(II) removal from aqueous solution by Antep pistachio (Pistacia vera L.) shells based on 17 different experimental data obtained in a lab-scale batch study. Three independent variables (initial pH of solution (pH(0)) ranging from 2.0 to 5.5, initial concentration of Pb(II) ions (C(0)) ranging from 5 to 50 ppm, and contact time (t(C)) ranging from 5 to 120 min) were consecutively coded as x(1), x(2) and x(3) at three levels (-1, 0 and 1), and a second-order polynomial regression equation was then derived to predict responses. The significance of independent variables and their interactions were tested by means of the analysis of variance (ANOVA) with 95% confidence limits (alpha=0.05). The standardized effects of the independent variables and their interactions on the dependent variable were also investigated by preparing a Pareto chart. The optimum values of the selected variables were obtained by solving the quadratic regression model, as well as by analysing the response surface contour plots. The optimum coded values of three test variables were computed as x(1)=0.125, x(2)=0.707, and x(3)=0.107 by using a LOQO/AMPL optimization algorithm. The experimental conditions at this global point were determined to be pH(0)=3.97, C(0)=43.4 ppm, and t(C)=68.7 min, and the corresponding Pb(II) removal efficiency was found to be about 100%.

Recovery of ammonium nitrogen from the effluent of UASB treating poultry manure wastewater by MAP precipitation as a slow release fertilizer.

Magnesium ammonium phosphate hexahydrate (MgNH(4)PO(4).6H(2)O, MAP) precipitation was studied on up-flow anaerobic sludge blanket (UASB) pretreated poultry manure wastewater in a lab-scale batch study. To recover high strength of ammonium nitrogen (NH(4)(+)-N=1318 mg/L) from UASB effluent, three combinations of chemicals including MgCl(2).6H(2)O+KH(2)PO(4), MgSO(4).7H(2)O+NaHPO(4).7H(2)O, and MgO+85% H(3)PO(4) were first applied at the stoichiometric ratio (Mg(2+):NH(4)(+)-N:PO(4)(3-)-P=1:1:1) and at different pH levels ranging from 4.45 to 11. Preliminary test results indicated that maximum NH(4)(+)-N removal, as well as maximum chemical oxygen demand (COD) and color reductions, were obtained as 85.4%, 53.3% and 49.8% at pH 9.0 with the addition of MgCl(2).6H(2)O+KH(2)PO(4), respectively. The paired experimental data obtained from batch studies were statistically evaluated by a non-parametric Mann-Whitney test and a two-sample t-test. Based on the previous results, another batch experiments were then performed at pH 9.0 using MgCl(2).6H(2)O+KH(2)PO(4) for different molar ratios applied as overdose (1.2:1:1, 1.5:1:1, 1:1:1.2, 1:1:1.5) and underdose (0.5:1:1, 0.8:1:1, 1:1:0.5, 1:1:0.8). In the final step, the fertility of the MAP precipitate as struvite was also tested on the growth of three test plants including purslane (Portulaca oleracea), garden cress (Lepidum sativum) and grass (Lolium perenne). Findings of this experimental study clearly confirmed the recovering of NH(4)(+)-N from UASB pretreated poultry manure wastewater by MAP precipitation, and also the application of recovered MAP sludge as a valuable slow release fertilizer for agricultural use.

Anaerobic digestion technology in poultry and livestock waste treatment — a literature review

A literature review has been undertaken to investigate the performance of the different anaerobic process configurations and operational conditions used in poultry and livestock waste treatment. The results of the extensive literature review showed that a wide range of different reactor volumes varying from 100 mL to 95 m 3 were utilized in the investigation of anaerobic processing of poultry manure. Retention times studied were between 13.2 h and 91 days. Most of studies were carried out under mesophilic conditions maintained between 25 and 35°C. Chemical oxygen demand (COD) removals and organic loading rate (OLR) ranged from 32 to 78%, and from 1.1 to 2.9 kg COD m—3 day—1, respectively. Biogas yields were achieved between 180 mL g—1 COD added and 74 m3 day—1 for a wide range of different reactor configurations. Up-flow anaerobic sludge blanket (UASB) seems to be a suitable process for the treatment of poultry manure wastewater and the liquid fraction of hen manure, due to its ability to maintain a sufficient amount of active biomass. The literature review showed that various reactor configurations such as fixed-film reactor, attached-film bioreactor, anaerobic rotating biological reactor, batch reactors, downflow anaerobic filter, fixed dome plant, UASB, continuously stirred tank reactor (CSTR), up-flow anaerobic filter (UAF), temperature-phased anaerobic digestion (TPAD), anaerobic hybrid reactor (AHR), and two-stage anaerobic systems are well suited to anaerobic processing of cattle manure. At both mesophilic and thermophilic conditions, high COD removals (87—95%) were achieved for treatment of cattle manure wastewaters. The COD and volatile solids (VS) reductions obtained were 37.9 to 94% and 9.6 to 92%, respectively. During the studies, OLR and retention times ranged between 0.117 and 7.3 g VS L—1 day—1 and between 0.5 and 140 days, respectively. In anaerobic processing of cattle manure, methane yields between 48 mmol CH4 L— 1 and 4681.3 m3 CH4 month— 1 were found for the corresponding reactor volumes of 120 mL and 1300 m3, respectively. In anaerobic processing of swine manure, OLR ranged from 0.9 to 15.42 g VS L—1 day— 1 at mesophilic conditions (25—35°C). The reactor volumes varied between 125 mL and 380 L. Temperature and retention times ranged from 25 to 60°C, and 0.9 to 113 days, respectively. COD and VS reductions achieved were between 57 and 78% and between 34.5 and 61%, respectively. Moreover, methane yields were obtained between 22 and 360 mL CH4 g —1 VS added. The results showed that UASB, anaerobic baffled reactors, CSTR, and anaerobic sequencing batch reactor (ASBR) were successfully utilized in anaerobic processing of swine manure at both mesophilic and thermophilic conditions.

A fuzzy-logic-based model to predict biogas and methane production rates in a pilot-scale mesophilic UASB reactor treating molasses wastewater

A MIMO (multiple inputs and multiple outputs) fuzzy-logic-based model was developed to predict biogas and methane production rates in a pilot-scale 90-L mesophilic up-flow anaerobic sludge blanket (UASB) reactor treating molasses wastewater. Five input variables such as volumetric organic loading rate (OLR), volumetric total chemical oxygen demand (TCOD) removal rate (R(V)), influent alkalinity, influent pH and effluent pH were fuzzified by the use of an artificial intelligence-based approach. Trapezoidal membership functions with eight levels were conducted for the fuzzy subsets, and a Mamdani-type fuzzy inference system was used to implement a total of 134 rules in the IF-THEN format. The product (prod) and the centre of gravity (COG, centroid) methods were employed as the inference operator and defuzzification methods, respectively. Fuzzy-logic predicted results were compared with the outputs of two exponential non-linear regression models derived in this study. The UASB reactor showed a remarkable performance on the treatment of molasses wastewater, with an average TCOD removal efficiency of 93 (+/-3)% and an average volumetric TCOD removal rate of 6.87 (+/-3.93) kg TCOD(removed)/m(3)-day, respectively. Findings of this study clearly indicated that, compared to non-linear regression models, the proposed MIMO fuzzy-logic-based model produced smaller deviations and exhibited a superior predictive performance on forecasting of both biogas and methane production rates with satisfactory determination coefficients over 0.98.

Decolorization and COD reduction of UASB pretreated poultry manure wastewater by electrocoagulation process : A post-treatment study

The performance of electrocoagulation (EC) technique for decolorization and chemical oxygen demand (COD) reduction of anaerobically pretreated poultry manure wastewater was investigated in a laboratory batch study. Two identical 15.7-L up-flow anaerobic sludge blanket (UASB) reactors were first run under various organic and hydraulic loading conditions for 216 days. Effects of operating parameters such as type of sacrificial electrode material, time of electrolysis, current density, initial pH, and electrolyte concentration were further studied to optimize conditions for the post-treatment of UASB pretreated poultry manure wastewater. Preliminary tests conducted with two types of sacrificial electrodes (Al and Fe) resulted that Al electrodes were found to be more effective for both COD and color removals than Fe electrodes. The subsequent EC tests performed with Al electrodes showed that optimal operating conditions were determined to be an initial pH of 5.0, a current density of 15mA/cm(2), and an electrolysis time of 20min. The results indicated that under the optimal conditions, about 90% of COD and 92% of residual color could be effectively removed from the UASB effluent with the further contribution of the EC technology used as a post-treatment unit. In this study, the possible acute toxicity of the EC effluent was also evaluated by a static bioassay test procedure using guppy fish (Lebistes reticulatus). Findings of this study clearly indicated that incorporation of a toxicological test into conventional physicochemical analyses provided a better evaluation of final discharge characteristics.

Migration behavior of landfill leachate contaminants through alternative composite liners

Four identical pilot-scale landfill reactors with different alternative composite liners were simultaneously operated for a period of about 540 days to investigate and to simulate the migration behaviors of phenolic compounds (phenol, 2-CP, 2-MP, 3-MP, 4-MP, 2-NP, 4-NP, 2,4-DNP, 2,4-DCP, 2,6-DCP, 2,4,5-TCP, 2,4,6-TCP, 2,3,4,6-TeCP, PCP) and heavy metals (Pb, Cu, Zn, Cr, Cd, Ni) from landfill leachate to the groundwater. Alternative landfill liners of four reactors consist of R1: Compacted clay liner (10 cm+10 cm, k=10(-8)m/sn), R2: Geomembrane (2 mm HDPE)+compacted clay liner (10 cm+10 cm, k=10⁻⁸ m/sn), R3: Geomembrane (2 mm HDPE)+compacted clay liner (10 cm, k=10⁻⁸ m/sn)+bentonite liner (2 cm)+compacted clay liner (10 cm, k=10⁻⁸ m/sn), and R4: Geomembrane (2 mm HDPE)+compacted clay liner (10 cm, k=10⁻⁸ m/sn)+zeolite liner (2 cm)+compacted clay liner (10 cm, k=10⁻⁸ m/sn). Wastes representing Istanbul municipal solid wastes were disposed in the reactors. To represent bioreactor landfills, reactors were operated by leachate recirculation. To monitor and control anaerobic degradation in the reactors, variations of conventional parameters (pH, alkalinity, chloride, conductivity, COD, TOC, TKN, ammonia and alcaly metals) were also investigated in landfill leachate samples. The results of this study showed that about 35-50% of migration of organic contaminants (phenolic compounds) and 55-100% of migration of inorganic contaminants (heavy metals) to the model groundwater could be effectively reduced with the use of bentonite and zeolite materials in landfill liner systems. Although leachate contaminants can reach to the groundwater in trace concentrations, findings of this study concluded that the release of these compounds from landfill leachate to the groundwater may potentially be of an important environmental concern based on the experimental findings.

Appraisal of potential environmental risks associated with human antibiotic consumption in Turkey.

A comprehensive analysis of Turkish antibiotic data was conducted to evaluate potential environmental risks associated with antibiotic consumption in Turkey for year 2007. Antibiotics were defined for systemic use or group J01 of the WHO Anatomical Therapeutic Chemical (ATC) classification system. Total emissions and prescriptions for each ATC group were classified separately into 17 different J01 categories and three forms of medication (capsule/tablets, injectables and suspensions). Capsules and tablets were found as the most emitted form of medication in year 2007, with a total emission rate of about 585.5 tons/year (76%). Total antibiotic emission rates including all forms of medications were determined to be about 664.2 tons/year (86%) and 110.1 tons/year (14%) for adult and pediatric patients, respectively. An environmental risk assessment of 8 human antibiotics was conducted according to the EU draft guidance (CEC/III/5504/94, draft 6, version 4) and the risk was indicated by the ratio of predicted environmental concentration (PEC) to predicted no effect concentration (PNEC) for the aquatic environment. Available acute and chronic toxicity data were collected from the open peer-reviewed literature to derive PNEC. Risk quotients (PEC/PNEC) were then calculated for 8 pharmaceutical substances. PEC/PNEC ratio exceeded 1.0 for beta-lactams (cephalosporins and penicillins), fluoroquinolones, macrolides and aminoglycosides. The findings of this study concluded that the release of these compounds from wastewater treatment plants may potentially be of an important environmental concern based on todays use of antibiotics in Turkey.

ARTIFICIAL INTELLIGENCE-BASED PREDICTION MODELS FOR ENVIRONMENTAL ENGINEERING

A literature survey was conducted to appraise the recent applications of artiflcal intelligence (AI)-based modeling studies in the environmental engineer- ing fleld. A number of studies on artiflcial neural networks (ANN), fuzzy logic and adaptive neuro-fuzzy systems (ANFIS) were reviewed and important aspects of these models were highlighted. The results of the extensive literature survey showed that most AI-based prediction models were implemented for the solution of water/wastewater (55.7%) and air pollution (30.8%) related environmental prob- lems compared to solid waste (13.5%) management studies. The present literature review indicated that among the many types of ANNs, the three-layer feed-forward and back-propagation (FFBP) networks were considered as one of the simplest and the most widely used network type. In general, the Levenberg-Marquardt algo- rithm (LMA) was found as the best-suited training algorithm for several complex and nonlinear real-life problems of environmental engineering. The literature sur- vey showed that for water and wastewater treatment processes, most of AI-based prediction models were introduced to estimate the performance of various biolog- ical and chemical treatment processes, and to control e†uent pollutant loads and ∞owrates from a speciflc system. In air polution related environmental problems, forecasting of ozone (O3) and nitrogen dioxide (NO2) levels, daily and/or hourly particulate matter (PM2:5 and PM10) emissions, and sulfur dioxide (SO2) and car- bon monoxide (CO) concentrations were found to be widely modeled. For solid waste management applications, reseachers conducted studies to model weight of waste generation, solid waste composition, and total rate of waste generation.

A neural network-based approach for the prediction of urban SO2 concentrations in the Istanbul metropolitan area

A three-layer Artificial Neural Network (ANN) model was developed to forecast air pollution levels. The subsequent SO2 concentration (24-hour averaged) being the output parameter of this study was estimated by seven input parameters such as preceding SO2 concentrations (24-hour averaged), average daily temperature, sea-level pressure, relative humidity, cloudiness, average daily wind speed and daily dominant wind direction. After Backpropagation training combined with Principal Component Analysis (PCA), the proposed model predicted subsequent SO2 values based on measured data. ANN testing outputs were proven to be satisfactory with correlation coefficients of about 0.770, 0.744 and 0.751 for the winter, summer and overall data, respectively.

Integration of kinetic modeling and desirability function approach for multi-objective optimization of UASB reactor treating poultry manure wastewater.

An integrated multi-objective optimization approach within the framework of nonlinear regression-based kinetic modeling and desirability function was proposed to optimize an up-flow anaerobic sludge blanket (UASB) reactor treating poultry manure wastewater (PMW). Chen-Hashimoto and modified Stover-Kincannon models were applied to the UASB reactor for determination of bio-kinetic coefficients. A new empirical formulation of volumetric organic loading rate was derived for the first time for PMW to estimate the dimensionless kinetic parameter (K) in the Chen-Hashimoto model. Maximum substrate utilization rate constant and saturation constant were predicted as 11.83 g COD/L/day and 13.02 g COD/L/day, respectively, for the modified Stover-Kincannon model. Based on four process-related variables, three objective functions including a detailed bio-economic model were derived and optimized by using a LOQO/AMPL algorithm, with a maximum overall desirability of 0.896. The proposed optimization scheme demonstrated a useful tool for the UASB reactor to optimize several responses simultaneously.