In this study, durian (Durio zibethinus Murray) skin was examined for its ability to remove methylene blue (MB) dye from simulated textile wastewater. Adsorption equilibrium and kinetics of MB removal from aqueous solutions at different parametric conditions such as different initial concentrations (2-10 mg/L), biosorbent dosages (0.3-0.7 g) and pH solution (4-9) onto durian skin were studied using batch adsorption. The amount of MB adsorbed increased from 3.45 to 17.31 mg/g with the increase in initial concentration of MB dye; whereas biosorbent dosage increased from 1.08 to 2.47 mg/g. Maximum dye adsorption capacity of the durian skin was found to increase from 3.78 to 6.40 mg/g, with increasing solution pH. Equilibrium isotherm data were analyzed according to Langmuir and Freundlich isotherm models. The sorption equilibrium was best described by the Freundlich isotherm model with maximum adsorption capacity of 7.23 mg/g and this was due to the heterogeneous nature of the durian skin surface. Kinetic studies indicated that the sorption of MB dye tended to follow the pseudo second-order kinetic model with promising correlation of 0.9836 < R(2) < 0.9918.
Biofouling control is important for effective process of membrane bioreactor (MBR). In this study, phenomena of biofouling for immersed type extended aeration MBR with two different anti-fouling aeration intensities were studied through a laboratory set up. The objectives of this study were (a) to observe biofouling phenomena of MBR that operates under different anti-fouling bubbling intensity, and simultaneously monitors performance of the MBR in organic carbon and nutrients removal; (b) to compare effectiveness of detergent and detergent-enzyme cleaning solutions in recovering biofouled membranes that operated in the extended aeration MBR. For MBR, which operated under continuous anti-fouling aeration, deposition and accumulation of suspended biomass on membrane surface were prohibited. However, flux loss was inescapable that biofilm layer was the main problem. Membrane cleaning was successfully carried out with detergent-enzyme mixture solutions and its effectiveness was compared with result from cleaning with just detergent solution.
A two-staged engineered wetland-based system was designed and constructed to treat raw domestic septage. Hydraulic loading rates (HLRs) of 8.75 and 17.5 cm/d were studied with four and eight daily dosings at the second stage of the system to investigate the influence of the regimes on septage treatment. Removal of organic matter (OM) was found to be HLR dependent, where the results indicated that the increase of HLR from 8.75 to 17.5 cm/d impaired the overall level of treatment in the wetland units. Effluent of wetland fed at HLR 17.5 cm/d presented significantly lower oxygen reduction potential and dissolved oxygen values than wetland fed at 8.75 cm/d, indicative of the occurrence of less aerobic and reductive conditions in the bed. The reoxygenation capability of the wetland units was found to be heavily affected by the dosing frequency especially under high hydraulic load (17.5 cm/d). NH3-N degradation was found to decrease with statistical importance when the wetland was flushed two times more frequently with smaller batches of influent. The number of hydraulic load fractionings did not seem to affect the level of treatments of OM and ammonia for both the wetlands fed under the lower HLR of 8.75 cm/d. Prediction of hydraulic limits and management of the feeding strategies are important in the vertical type of engineered wetlands to guarantee the treatment performance and minimize the chances of filter clogging.
In this study of coagulation operation, a comparison was made between the optimum jar test values for pH, coagulant and coagulant aid obtained from traditional methods (an adjusted one-factor-at-a-time (OFAT) method) and with central composite design (the standard design of response surface methodology (RSM)). Alum (coagulant) and polymer (coagulant aid) were used to treat a water source with very low pH and high aluminium concentration at Sri-Gading water treatment plant (WTP) Malaysia. The optimum conditions for these factors were chosen when the final turbidity, pH after coagulation and residual aluminium were within 0-5 NTU, 6.5-7.5 and 0-0.20 mg/l respectively. Traditional and RSM jar tests were conducted to find their respective optimum coagulation conditions. It was observed that the optimum dose for alum obtained through the traditional method was 12 mg/l, while the value for polymer was set constant at 0.020 mg/l. Through RSM optimization, the optimum dose for alum was 7 mg/l and for polymer was 0.004 mg/l. Optimum pH for the coagulation operation obtained through traditional methods and RSM was 7.6. The final turbidity, pH after coagulation and residual aluminium recorded were all within acceptable limits. The RSM method was demonstrated to be an appropriate approach for the optimization and was validated by a further test.
Hyperparameter tuning is an important process to maximize the performance of any neural network model. This present study proposed the factorial design of experiment for screening and response surface methodology to optimize the hyperparameter of two artificial neural network algorithms. Feed-forward neural network (FFNN) and radial basis function neural network (RBFNN) are applied to predict the permeate flux of palm oil mill effluent. Permeate pump and transmembrane pressure of the submerge membrane bioreactor system are the input variables. Six hyperparameters of the FFNN model including four numerical factors (neuron numbers, learning rate, momentum, and epoch numbers) and two categorical factors (training and activation function) are used in hyperparameter optimization. RBFNN includes two numerical factors such as a number of neurons and spreads. The conventional method (one-variable-at-a-time) is compared in terms of optimization processing time and the accuracy of the model. The result indicates that the optimal hyperparameters obtained by the proposed approach produce good accuracy with a smaller generalization error. The simulation results show an improvement of more than 65% of training performance, with less repetition and processing time. This proposed methodology can be utilized for any type of neural network application to find the optimum levels of different parameters.
The process for the production of biodegradable plastic material (polyhydroxyalkanoates, PHAs) from microbial cells by mixed-bacterial cultivation using readily available waste (renewable resources) is the main consideration nowadays. These observations have shown impressive results typically under high carbon fraction, COD/N and COD/P (usually described as nutrient-limiting conditions) and warmest temperature (moderate condition). Therefore, the aim of this work is predominantly to select mixed cultures under high storage responded by cultivation on a substrate - non limited in a single batch reactor with shortest period for feeding and to characterize their storage response by using specific and kinetics determination. In that case, the selected-fixed temperature is 30 degrees C to establish tropical conditions. During the accumulated steady-state period, the cell growth was inhibited by high PHA content within the cells because of the carbon reserve consumption. From the experiments, there is no doubt about the PHA accumulation even at high carbon fraction ratio. Apparently, the best accumulation occurred at carbon fraction, 160 +/- 7.97 g COD/g N (PHAmean, = 44.54% of dried cells). Unfortunately, the highest PHA productivity was achieved at the high carbon fraction, 560 +/- 1.62 g COD/g N (0.152 +/- 0.17 g/l. min). Overall results showed that with high carbon fraction induced to the cultivation, the PO4 and NO3 can remove up to 20% in single cultivation.
The objective of this study was to investigate the performance of employing H2O2 reagent in persulfate activation to treat stabilized landfill leachate. A central composite design (CCD) with response surface methodology (RSM) was applied to evaluate the relationships between operating variables, such as persulfate and H2O2 dosages, pH, and reaction time, to identify the optimum operating conditions. Quadratic models for the following two responses proved to be significant with very low probabilities (<0.0001): chemical oxygen demand (COD) and NH3-N removal. The obtained optimum conditions included a reaction time of 116 min, 4.97 g S2O8(2-), 7.29 g H2O2 dosage and pH 11. The experimental results were corresponding well with predicted models (COD and NH3-N removal rates of 81% and 83%, respectively). The results obtained in the stabilized leachate treatment were compared with those from other treatment processes, such as persulfate only and H2O2 only, to evaluate its effectiveness. The combined method (i.e., /S2O8(2-)/H2O2) achieved higher removal efficiencies for COD and NH3-N compared with other studied applications.
The removal of Reactive Black 5 dye in an aqueous solution by electrocoagulation (EC) as well as addition of flocculant was investigated. The effect of operational parameters, i.e. current density, treatment time, solution conductivity and polymer dosage, was investigated. Two models, namely the artificial neural network (ANN) and the response surface method (RSM), were used to model the effect of independent variables on percentage of dye removal. The findings of this work showed that current density, treatment time and dosage of polymer had the most significant effect on percentage of dye removal (p<0.001). In addition, interaction between time and current density, time and dosage of polymer, current density and dosage of polymer also significantly affected the percentage of dye removal (p=0.034, 0.003 and 0.024, respectively). It was shown that both the ANN and RSM models were able to predict well the experimental results (R(2)>0.8).
In this work, a regression model obtained from response surface methodology (RSM) was proposed for the electrocoagulation (EC) treatment of textile wastewater. The Reactive Black 5 dye (RB5) was used as a model dye to evaluate the performance of the model design. The effect of initial solution pH, applied current and treatment time on RB5 removal was investigated. The total number of experiments designed by RSM amounted to 27 runs, including three repeated experimental runs at the central point. The accuracy of the model was evaluated by the F-test, coefficient of determination (R(2)), adjusted R(2) and standard deviation. The optimum conditions for RB5 removal were as follows: initial pH of 6.63, current of 0.075 A, electrolyte dose of 0.11 g/L and EC time of 50.3 min. The predicted RB5 removal was 83.3% and the percentage error between experimental and predicted results was only 3-5%. The obtained data confirm that the proposed model can be used for accurate prediction of RB5 removal. The value of the zeta potential increased with treatment time, and the X-ray diffraction pattern shows that iron complexes were found in the sludge.
This research investigated the effects of co- and counter-current flow patterns on oil-water-solid separation efficiencies of a circular separator with inclined coalescence mediums. Oil-water-solid separations were tested at different influent concentrations and flowrates. Removal efficiencies increased as influent flowrate decreased, and their correlationship can be represented by power equations. These equations were used to predict the required flowrate, Q(ss50), for a given influent suspended solids concentration C(iss) to achieve the desired effluent suspended solids concentration, C(ess) of 50 mg/L, to meet environmental discharge requirements. The circular separator with counter-current flow was found to attend removal efficiencies relatively higher as compared to the co-current flow. As compared with co-current flow, counter-current flow Q(ss50) was approximately 1.65 times higher than co-current flow. It also recorded 13.16% higher oil removal at influent oil concentration, C(io) of 100 mg/L, and approximately 5.89% higher TSS removal at all influent flowrates. Counter-current flow's better removal performances were due to its higher coalescing area and constant interval between coalescence plate layers.
Undular hydraulic jumps are characterized by a smooth rise of the free surface, followed by a train of stationary waves. These jumps sometimes occur in natural waterways and rivers. Numerical difficulties are especially distinct when the flow condition is close to the critical value because of the high sensitivity of the near-critical flow field to flow and channel conditions. Furthermore, the free surface has a wavy shape, which may indicate the occurrence of several transitions from supercritical to subcritical states and vice versa (i.e., undular hydraulic jumps). In this study, a flow model is used to predict an undular hydraulic jump in a rectangular open channel. The model is based on the general two-dimensional, Reynolds-averaged, Navier-Stokes flow equations. The resulting set of partial differential equations is solved using the FLOW-3D solver. The results are compared with the experimental data to validate the model. The comparative analysis shows that the proposed model yields good results. Several types of undular hydraulic jumps occurring in different situations are then simulated to prove the potential application of the model.
Elevated levels of nutrients in agroindustry wastewaters, and higher reliance on chlorination pose health threats due to formation of chlorinated organics as well as increased chlorination costs. Removals of ammonium and nitrate compounds were studied using activated carbon from palm shells, as adsorbent and support media. Experiments were carried out at several loadings, F:M from 0.31 to 0.58, and hydraulic residence times (HRT) of 24 h, 12 h and 8 h. Results show that the wastewater treatment process achieved removals of over 90% for COD and 62% for Total-N. Studies on removals from river water were carried out in sequencing batch reactor (SBR) and activated carbon biofilm (ACB) reactor. Removals achieved by the SBR adsorption-biodegradation combination were 67.0% for COD, 58.8% for NH3-N and 25.5% for NO3-N while for adsorption alone the removals were only 37.0% for COD, 35.2% for NH3-N and 13.8% for NO3-N. In the ACB reactor, at HRT of 1.5 to 6 h, removals ranged from 12.5 to 100% for COD, 16.7 to 100% for NO3-N and 13.5 to 100% for NH3-N. Significant decrease in removals was shown at lower HRT. The studies have shown that substantial removals of COD, NO3-N and NH3-N from both wastewater and river water may be achieved via adsorption-biodegradation by biofilm on activated carbon processes.
Landfill leachate is one of the most recalcitrant wastes for biotreatment and can be considered a potential source of contamination to surface and groundwater ecosystems. In the present study, Fenton oxidation was employed for degradation of stabilized landfill leachate. Response surface methodology was applied to analyze, model and optimize the process parameters, i.e. pH and reaction time as well as the initial concentrations of hydrogen peroxide and ferrous ion. Analysis of variance showed that good coefficients of determination were obtained (R2 > 0.99), thus ensuring satisfactory agreement of the second-order regression model with the experimental data. The results indicated that, pH and its quadratic effects were the main factors influencing Fenton oxidation. Furthermore, antagonistic effects between pH and other variables were observed. The optimum H2O2 concentration, Fe(II) concentration, pH and reaction time were 0.033 mol/L, 0.011 mol/L, 3 and 145 min, respectively, with 58.3% COD, 79.0% color and 82.1% iron removals.
Electrocoagulation (EC) is employed to investigate the energy consumption (EnC) of synthetic wastewater. In order to find the best process conditions, the influence of various parameters including initial pH, initial dye concentration, applied voltage, initial electrolyte concentration, and treatment time are investigated in this study. EnC is considered the main criterion of process evaluation in investigating the effect of the independent variables on the EC process and determining the optimum condition. Evolutionary polynomial regression is combined with a multi-objective genetic algorithm (EPR-MOGA) to present a new, simple and accurate equation for estimating EnC to overcome existing method weaknesses. To survey the influence of the effective variables, six different input combinations are considered. According to the results, EPR-MOGA Model 1 is the most accurate compared to other models, as it has the lowest error indices in predicting EnC (MARE = 0.35, RMSE = 2.33, SI = 0.23 and R2 = 0.98). A comparison of EPR-MOGA with reduced quadratic multiple regression methods in terms of feasibility confirms that EPR-MOGA is an effective alternative method. Moreover, the partial derivative sensitivity analysis method is employed to analyze the EnC variation trend according to input variables.
The present work was aimed at evaluating the multi-metals column adsorption of lead(II), cadmium(II) and manganese(II) ions onto natural bentonite. The bentonite clay adsorbent was characterized for physical and chemical properties using X-ray diffraction, X-ray fluorescence, Brunauer-Emmett-Teller surface area and cation exchange capacity. The column performance was evaluated using adsorbent bed height of 5.0 cm, with varying influent concentrations (10 mg/L and 50 mg/L) and flow rates (1.4 mL/min and 2.4 mL/min). The result shows that the breakthrough time for all metal ions ranged from 50 to 480 minutes. The maximum adsorption capacity was obtained at initial concentration of 10 mg/L and flow rate of 1.4 mL/min, with 2.22 mg/g of lead(II), 1.71 mg/g of cadmium(II) and 0.37 mg/g of manganese(II). The order of metal ions removal by natural bentonite is lead(II) > cadmium(II) > manganese(II). The sorption performance and the dynamic behaviour of the column were predicted using Adams-Bohart, Thomas, and Yoon-Nelson models. The linear regression analysis demonstrated that the Thomas and Yoon-Nelson models fitted well with the column adsorption data for all metal ions. The natural bentonite was effective for the treatment of wastewater laden with multi-metals, and the process parameters obtained from this work can be used at the industrial scale.
Palm shell activated carbon was modified via surface impregnation with polyethyleneimine (PEI) to enhance removal of Cu(2+) from aqueous solution in this study. The effect of PEI modification on batch adsorption of Cu(2+) as well as the equilibrium behavior of adsorption of metal ions on activated carbon were investigated. PEI modification clearly increased the Cu(2+) adsorption capacities by 68% and 75.86% for initial solution pH of 3 and 5 respectively. The adsorption data of Cu(2+) on both virgin and PEI-modified AC for both initial solution pH of 3 and 5 fitted the Langmuir and Redlich-Peterson isotherms considerably better than the Freundlich isotherm.
In this study, a response surface methodology (RSM) approach using central composite design (CCD) was investigated to develop a mathematical model and to optimize the effects of pH, adsorbent amount and temperature related to the hexavalent chromium removal by biosorption on peanut shells (PSh). The highest removal percentage of 30.28% was found by the predicted model under the optimum conditions (pH of 2.11, 0.73 g of PSh and 37.2 °C) for a 100 mg/L initial Cr(VI) concentration, which was very near to the experimental value (29.92%). The PSh was characterized by SEM, EDX, FTIR, BET, XRD analyses. Moreover, a Langmuir isotherm fitted well (R2 = 0.992) with the experimental data, and the maximum adsorption capacity was discovered to be 2.48 and 3.49 mg/g respectively at 25 and 45 °C. Kinetic data were well foreseen by pseudo second order. Thermodynamic study depicted that biosorption of Cr(VI) onto PSh was spontaneous and endothermic. Regeneration of the PSh using NaOH showed a loss <5% in the Cr(VI) removal efficiency up to three recycle runs. In summary, the Cr(VI) removal onto economic, sensitive and selective biosorbent (PSh) was optimized using CCD to study biosorption behaviors.
Water pollution during festival periods is a major problem in all festival cities across the world. Reliable prediction of water pollution is essential in festival cities for sewer and wastewater management in order to ensure public health and a clean environment. This article aims to model the biological oxygen demand (BOD(5)), and total suspended solids (TSS) parameters in wastewater in the sewer networks of Karbala city center during festival and rainy days using structural equation modeling and multiple linear regression analysis methods. For this purpose, 34 years (1980-2014) of rainfall, temperature and sewer flow data during festival periods in the study area were collected, processed, and employed. The results show that the TSS concentration increases by 26-46 mg/l while BOD(5) concentration rises by 9-19 mg/l for an increase of rainfall by 1 mm during festival periods. It was also found that BOD(5) concentration rises by 4-17 mg/l for each increase of 10,000 population.
Temperature variation is an important factor in Everglade wetlands ecology. A temperature fluctuation from 17 degrees C to 32 degrees C recorded in the Everglades may have significant impact on fish dynamics. The short life cycles of some of Everglade fishes has rendered this temperature variation to have even more impacts on the ecosystem. Fish population dynamic models, which do not explicitly consider seasonal oscillations in temperature, may fail to describe the details of such a population. Hence, a model for fish in freshwater marshes of the Florida Everglades that explicitly incorporates seasonal temperature variations is developed. The model's main objective is to assess the temporal pattern of fish population and densities through time subject to temperature variations. Fish population is divided into 2 functional groups (FGs) consisting of small fishes; each group is subdivided into 5-day age classes during their life cycles. Many governing sub-modules are set directly or indirectly to be temperature dependent. Growth, fecundity, prey availability, consumption rates and mortality are examples. Several mortality sub-modules are introduced in the model, of which starvation mortality is set to be proportional to the ratio of prey needed to prey available at that particular time step. As part of the calibration process, the model is run for 50 years to ensure that fish densities do not go to extinction, while the simulation period is about 8 years. The model shows that the temperature dependent starvation mortality is an important factor that influences fish population densities. It also shows high fish population densities at some temperature ranges when this consumption need is minimum. Several sensitivity analyses involving variations in temperature terms, food resources and water levels are conducted to ascertain the relative importance of temperature dependence terms.
The removal of natural organic matter (NOM) using a continuous flow fixed bed granular activated carbon (GAC) column was studied and the results were then fitted with the Adams-Bohart, Bed-Depth-Service-Time and Clarks models. The GAC, KI-6070 and KI-8085 used in the study had external surface areas of 277 m2/g and 547 m2/g, respectively. Adsorption of NOM by the GAC was complex and involved more than one rate-limiting step. The critical bed depths for KI-6070 and KI-8085 were 0.24 m and 0.3 m, respectively. The Clark model was more effective in simulating the absorbent breakthrough process as compared to the Adams-Bohart model. The lower empty bed contact time (EBCT) i.e. 15 minutes gave a better fit to the Clark Model as compared to EBCT of 20 and 30 minutes.