Zn (II) is one the common pollutant among heavy metals found in industrial effluents. Removal of pollutant from industrial effluents can be accomplished by various techniques, out of which adsorption ...was found to be an efficient method. Applications of adsorption limits itself due to high cost of adsorbent. In this regard, a low cost adsorbent produced from palm oil kernel shell based agricultural waste is examined for its efficiency to remove Zn (II) from waste water and aqueous solution. The influence of independent process variables like initial concentration, pH, residence time, activated carbon (AC) dosage and process temperature on the removal of Zn (II) by palm kernel shell based AC from batch adsorption process are studied systematically. Based on the design of experimental matrix, 50 experimental runs are performed with each process variable in the experimental range. The optimal values of process variables to achieve maximum removal efficiency is studied using response surface methodology (RSM) and artificial neural network (ANN) approaches. A quadratic model, which consists of first order and second order degree regressive model is developed using the analysis of variance and RSM - CCD framework. The particle swarm optimization which is a meta-heuristic optimization is embedded on the ANN architecture to optimize the search space of neural network. The optimized trained neural network well depicts the testing data and validation data with R2 equal to 0.9106 and 0.9279 respectively. The outcomes indicates that the superiority of ANN-PSO based model predictions over the quadratic model predictions provided by RSM.
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•Palm oil kernels based activated carbon as low cost agricultural adsorbent for zinc removal•Particle Swarm Optimization (PSO) embedded with artificial neural network (ANN) algorithm for search space•Novel approach to model and optimize the pollutant removal by ANN-PSO integration•Optimization of process variables for maximum removal of pollutant by Response Surface methodology (RSM)
The low-cost activated carbon was prepared from
Tamarind wood an agricultural waste material, by chemical activation with zinc chloride. Activated carbon adsorption is an effective means for reducing ...organic chemicals, chlorine, heavy metals and unpleasant tastes and odours in effluent or colored substances from gas or liquid streams. Central composite design (CCD) was applied to study the influence of activation temperature, chemical ratio of zinc chloride to
Tamarind wood and activation time on the chemical activation process of
Tamarind wood. Two quadratic models were developed for yield of activated carbon and adsorption of malachite green oxalate using Design-Expert software. The models were used to calculate the optimum operating conditions for production of activated carbon providing a compromise between yield and adsorption of the process. The yield (45.26
wt.%) and adsorption (99.9%) of the activated carbon produced at these operating conditions showed an excellent agreement with the amounts predicted by the models.
The present paper discusses response surface methodology (RSM) as an efficient approach for predictive model building and optimization of chromium adsorption on developed activated carbon. In this ...work the application of RSM is presented for optimizing the removal of Cr(VI) ions from aqua solutions using activated carbon as adsorbent. All experiments were performed according to statistical designs in order to develop the predictive regression models used for optimization. The optimization of adsorption of chromium on activated carbon was carried out to ensure a high adsorption efficiency at low adsorbent dose and high initial concentration of Cr(VI). While the goal of adsorption of chromium optimization was to improve adsorption conditions in batch process, i.e., to minimize the adsorbent dose and to increase the initial concentration of Cr(VI). In the adsorption experiments a laboratory developed Tamarind wood activated carbon made of chemical activation (zinc chloride) was used. A 2
4 full factorial central composite design experimental design was employed. Analysis of variance (ANOVA) showed a high coefficient of determination value (
R
2
=
0.928) and satisfactory prediction second-order regression model was derived. Maximum chromium removal efficiency was predicted and experimentally validated. The optimum adsorbent dose, temperature, initial concentration of Cr(VI) and initial pH of the Cr(VI) solution were found to be 4.3
g/l, 32
°C, 20.15
mg/l and 5.41 respectively. Under optimal value of process parameters, high removal (>89%) was obtained for Cr(VI).
Presence of pigments and dyes in water bodies are growing tremendously and pose as toxic materials and have severe health effects on human and aquatic creatures. Treatments methods for removal of ...these toxic dyes along with other pollutants are growing in different dimensions, among which adsorption was found a cheaper and efficient method. In this study, the performance of polyaniline-based nano-adsorbent for removal of methyl orange (MO) dye from wastewater in a batch adsorption process is studied. Along with this to minimize the number of experiments and obtain optimal conditions, a multivariate predictive model based on response surface methodology (RSM) is developed. This is compared with data-driven modeling using the artificial neural network (ANN) which is integrated with differential evolution optimization (DEO) for prediction of the adsorption of MO. The interactive effects on MO removal efficiency with respect to independent process variables were investigated. The fit of the predictive model was found to good enough with R2 = 0.8635. The optimal ANN architecture with 5-12-1 topology resulted in higher R2 and lower RMSE of 0.9475 and 0.1294 respectively. Pearson's Chi-square measure which provides a good measurement scale for weighing the goodness of fit is found to be 0.005 and 0.038 for RSM and ANN-DEO respectively, and other statistical metrics evaluated in this study further confirms that the ANN-DEO is very superior over RSM for model predictions.
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•Polyaniline nano adsorbent used for methyl orange (MO) adsorption.•Optimization of process variables for maximum removal of MO by Response Surface methodology (RSM).•Differential evolution optimization (DEO) embedded with artificial neural network (ANN) algorithm for search space.•Novel approach to model and optimize the MO removal by ANN-DEO integration.
Agriculture residues such as palm shell are one of the biomass categories that can be utilized for conversion to bio-oil by using pyrolysis process. Palm shells were pyrolyzed in a fluidized-bed ...reactor at 400, 500, 600, 700 and 800 °C with N
2 as carrier gas at flow rate 1, 2, 3, 4 and 5 L/min. The objective of the present work is to determine the effects of temperature, flow rate of N
2, particle size and reaction time on the optimization of production of renewable bio-oil from palm shell. According to this study the maximum yield of bio-oil (47.3 wt%) can be obtained, working at the medium level for the operation temperature (500 °C) and 2 L/min of N
2 flow rate at 60 min reaction time. Temperature is the most important factor, having a significant positive effect on yield product of bio-oil. The oil was characterized by Fourier Transform infra-red (FT-IR) spectroscopy and gas chromatography/mass spectrometry (GC–MS) techniques.
► This study reports the results of experimental investing of conversion palm shell into bio-oil by using pyrolysis and to find the optimum condition to produce the highest yield of bio-oil. ► Several parameters which have effect to the process such as temperature, N
2 flow rate, reaction time and particle size is will be investigated in this study. ► The outcome of this result will be important for abatement and control of increasingly waste palm shell storage problems any energy source to the world.
•About 14.72% of the total landmass in Malaysia was used for oil palm plantations.•Oil palm tree residues were pyrolyzed to produce bio-oil and bio-char.•The process was performed at a temperature of ...500°C and reaction time of 60min.•Characterization of the products was performed.
Oil palm tree residues are a rich biomass resource in Malaysia, and it is therefore very important that they be utilized for more beneficial purposes, particularly in the context of the development of biofuels. This paper described the possibility of utilizing oil palm tree residues as biofuels by producing bio-oil and bio-char via pyrolysis. The process was performed in a fixed-bed reactor at a temperature of 500°C, a nitrogen flow rate of 2L/min and a reaction time of 60min. The physical and chemical properties of the products, which are important for biofuel testing, were then characterized. The results showed that the yields of the bio-oil and bio-char obtained from different residues varied within the ranges of 16.58–43.50wt% and 28.63–36.75wt%, respectively. The variations in the yields resulted from differences in the relative amounts of cellulose, hemicellulose, lignin, volatiles, fixed carbon, and ash in the samples. The energy density of the bio-char was found to be higher than that of the bio-oil. The highest energy density of the bio-char was obtained from a palm leaf sample (23.32MJ/kg), while that of the bio-oil was obtained from a frond sample (15.41MJ/kg).
Microwave pyrolysis is a very effective technique to convert organic waste into energy rich products. In the present work micro porous and carbonaceous OPS char was synthesized by microwave pyrolysis ...technique. OPS char yield and its BET surface area was investigated as a function of process parameters to make the microwave pyrolysis of OPS more efficient. Both of these quantities were found to be affected by the process parameters. With the rise in microwave power (MWP) and radiation time (RT), OPS char yield was lowered while increase N2 flow rate (NFR) increased the OPS char yield slightly. Extreme values of either of the process parameter was seen to lower the BET surface area of OPS char. Response Surface Methodology (RSM), was used to optimize the process parameters for maximized OPS char yield and its BET surface area. Regression models for the OPS char yield and its BET surface area were also developed in this study. These regression models were having high Fischer test value & lower p-value which ensure its reliability and applicability. ANOVA analysis of the experimental data provided the process parameters to achieve maximized OPS char yield (60.93%) and BET surface area (250.03 m2/g). The predicted results were validated and it was found that the experimental data varied only by 5.99% in yield and 6.34% in BET surface area from the predicted values.
In this work, the adsorption of lead(II) was studied on activated carbon prepared from
Tamarind wood with zinc chloride activation. Adsorption studies were conducted in the range of 10–50
mg/l ...initial lead(II) concentration and at temperature in the range of 10–50
°C. The experimental data were analyzed by the Freundlich isotherm and the Langmuir isotherm. Equilibrium data fitted well with the Langmuir model and Freundlich model with maximum adsorption capacity of 43.85
mg/g. The rates of adsorption were found to confirm to pseudo-second-order kinetics with good correlation and the overall rate of lead(II) uptake was found to be controlled by pore diffusion, film diffusion and particle diffusion, throughout the entire adsorption period. Boyd plot confirmed that external mass transfer was the rate-limiting step in the sorption process. Different thermodynamic parameters, viz., Δ
H°, Δ
S° and Δ
G° have also been evaluated and it has been found that the sorption was feasible, spontaneous and endothermic in nature. The results indicate that the
Tamarind wood activated could be used to effectively adsorb lead(II) from aqueous solutions.
In this work palm shell waste was pyrolyzed to produces bio-oil. The effects of several parameters on the pyrolysis efficiency were tested to identify the optimal bio-oil production conditions. The ...tested parameters include temperature, N
2 flow rate, feed-stock particle size, and reaction time. The experiments were conducted using a fix-bed reactor. The efficient response surface methodology (RSM), with a central composite design (CCD), were used for modeling and optimization the process parameters. The results showed that the second-order polynomial equation explains adequately the non-linear nature of the modeled response. An
R
2 value of 0.9337 indicates a sufficient adjustment of the model with the experimental data. The optimal conditions found to be at the temperature of 500 °C, N
2 flow rate of 2 L/min, particle size of 2 mm and reaction time of 60 min and yield of bio-oil was approximately obtained 46.4 wt %. In addition, Fourier Transform infra-red (FT-IR) spectroscopy and gas chromatography/mass spectrometry (GC–MS) were used to characterize the gained bio-oil under the optimum condition.
► The RSM, with a CCD, was used for modeling and optimization for bio-oil synthesis. ► The obtained model explains adequately the non-linear nature. ► An
R
2 value of 0.9337 ensures a sufficient adjustment of the model. ► It explains the importance of the experimental factors, their interactions.
An adsorbent prepared from sugarcane bagasse with chemical activation by zinc chloride was used to study its sorption potential on removing chromium(VI). In this work the application of response ...surface methodology (RSM) is presented for optimization of removal of Cr(VI) ions from aqua solutions using activated carbon as adsorbent. While the goal of adsorption of chromium optimization was to improve adsorption conditions in batch process, i.e., to minimize the adsorbent dose and to increase the initial concentration of Cr(VI). A 24 full factorial central composite design experimental design was employed. Analysis of variance (ANOVA) showed a high coefficient of determination value (R2=0.99) and satisfactory prediction second-order regression model was derived. Maximum chromium removal efficiency was predicted and experimentally validated. The optimum adsorbent dose, temperature, initial concentration of Cr(VI) and initial pH of the Cr(VI) solution were found to be 6.85g/L, 40 degree C, 77.5mg/l, and 8.58 respectively. Under optimal value of process parameters, high removal (>87%) was obtained for Cr(VI).
