Response surface optimization of a dynamic dye adsorption process: a case study of crystal violet adsorption onto NaOH-modified rice husk

The adsorption of crystal violet from aqueous solution by NaOH-modified rice husk was investigated in a laboratory-scale fixed-bed column. A two-level three factor (2³) full factorial central composite design with the help of Design Expert Version 7.1.6 (Stat Ease, USA) was used for optimisation of the dynamic dye adsorption process and evaluation of interaction effects of different operating parameters: initial dye concentration (100–200 mg L^?1), flow rate (10–30 mL min^?1) and bed height (5–25 cm). A correlation coefficient (R ²) value of 0.999, model F value of 1,936.59 and its low p value (<0.0001) along with lower value of coefficient of variation (1.38 %) indicated the fitness of the response surface quadratic model developed during the present study. Numerical optimisation applying desirability function was used to identify the optimum conditions for a targeted breakthrough time of 12 h. The optimum conditions were found to be initial solution pH?=?8.00, initial dye concentration?=?100 mg L^?1, flow rate?=?22.88 mL min^?1 and bed height?=?18.75 cm. A confirmatory experiment was performed to evaluate the accuracy of the optimised procedure. Under the optimised conditions, breakthrough appeared after 12.2 h and the column efficiency was determined as 99 %. The Thomas model showed excellent fit to the dynamic dye adsorption data obtained from the confirmatory experiment. Thereby, it was concluded that the current investigation gives valuable insights for designing and establishing a continuous wastewater treatment plant.     

Enhanced adsorption for Pb(II) and Cd(II) of magnetic rice husk biochar by KMnO4 modification

Environmental Science and Pollution Research - Novel KMnO4-treated magnetic biochar (FMBC) was successfully synthesized by addition of Fe(NO3)3 during carbonization and KMnO4 treatment following...     

Kinetics of basic dye (methylene blue) biosorption by giant duckweed (Spirodela polyrrhiza)

Wastewater containing pigments and/or dyes can cause serious water pollution problems in the form of reduced light penetration and photosynthesis, and the toxicity from heavy metals associated with pigments and/or dyes. Laboratory investigations, of the potential use of dried Spirodela polyrrhiza biomass as an adsorbent for the removal of the basic dye methylene blue from aqueous solution were conducted. A series of experiments were undertaken in an agitated batch adsorber to assess the effect of the system variables, i.e. sorbent dosage, pH, and contact time. The results showed that as the amount of the dried S. polyrrhiza increased, the percentage of dye sorption increased accordingly. At pH 2.0 the sorption of dye was not favorable, while the sorption at other pHs (3.0-11.0) was remarkable. There was no significant difference in the dye concentration remaining when the pH was increased from 3.0 to 11.0. The dye removal time was influenced by the initial dye concentration, and the process followed the first-order rate kinetics. The rate constants for intraparticle diffusion were 1.00 and 3.27 mg/g/min1/2 for 300 and 500 mg/l of dye, respectively.     

The use of artificial neural network (ANN) for the prediction and simulation of oil degradation in wastewater by AOP

The application of advanced oxidation process (AOP) in the treatment of wastewater contaminated with oil was investigated in this study. The AOP investigated is the homogeneous photo-Fenton (UV/H₂O₂/Fe⁺²) process. The reaction is influenced by the input concentration of hydrogen peroxide H₂O₂, amount of the iron catalyst Fe⁺², pH, temperature, irradiation time, and concentration of oil in the wastewater. The removal efficiency for the used system at the optimal operational parameters (H₂O₂?=?400 mg/L, Fe⁺²?=?40 mg/L, pH?=?3, irradiation time?=?150 min, and temperature?=?30 °C) for 1,000 mg/L oil load was found to be 72 %. The study examined the implementation of artificial neural network (ANN) for the prediction and simulation of oil degradation in aqueous solution by photo-Fenton process. The multilayered feed-forward networks were trained by using a backpropagation algorithm; a three-layer network with 22 neurons in the hidden layer gave optimal results. The results show that the ANN model can predict the experimental results with high correlation coefficient (R ²?=?0.9949). The sensitivity analysis showed that all studied variables (H₂O₂, Fe⁺², pH, irradiation time, temperature, and oil concentration) have strong effect on the oil degradation. The pH was found to be the most influential parameter with relative importance of 20.6 %.     

Application of artificial neural network for prediction of Pb(II) adsorption characteristics

The adsorption of Pb(II) onto the surface of microwave-assisted activated carbon was studied through a two-layer feedforward neural network. The activated carbon was developed by microwave activation of Acacia auriculiformis scrap wood char. The prepared adsorbent was characterized by using Brunauer–Emmett–Teller (BET) surface area analyzer, scanning electron microscope (SEM), and X-ray difractometer. In the present study, the input variables for the proposed network were solution pH, contact time, initial adsorbate concentration, adsorbent dose and temperature, whereas the output variable was the percent Pb(II) removal. The network had been trained by using different algorithms and based on the lowest mean squared error (MSE) value and validation error, resilient backpropagation algorithm with 12 neurons in the hidden layer was selected for the present investigation. The tan sigmoid and purelin transfer function were used in the hidden and the output layers of the proposed network, respectively. The model predicted and experimental values of the percent Pb(II) removal were also compared and both the values were found to be in reasonable agreement with each other. The performance of the developed network was further improved by normalizing the experimental data set and it was found that after normalization, the MSE and validation error were reduced significantly. The sensitivity analysis was also performed to determine the most significant input parameter.     

Discoloration of methylene blue and wastewater from a plant by a Fe/Cu bimetallic system

Using a Fe/Cu bimetallic system (Fe/Cu system), the discoloration of both methylene blue in aqueous solution and the colored wastewater from a plant was investigated under the anaerobic condition in batch or continuous reactors. Results show that the Fe/Cu system effectively removed the color with over 88% of color removal efficiency for both methylene blue solution and the wastewater from the plant in batch test. Color removal efficiencies increased rapidly with Fe/Cu dosage and reaction time, respectively, at initial time and slowly to stable values. Optimum pH was neutral range. In addition, in continuous test it also removed the color of the wastewater from the plant with 63% of discoloring efficiency under the condition of 2 h of hydraulic retention time and neutral range of pH (7.0-8.3). High discoloring efficiencies with low chemical oxygen demand removal efficiencies were found in all experiments. The reduction of chromophores in pollutants was the main mechanism of the discoloration in the Fe/Cu system.     

Adsorption and photocatalytic properties of porphyrin loaded MIL-101 (Cr) in methylene blue degradation

Environmental Science and Pollution Research - In this study for the very first time, zinc tetraphenylporphyrin (ZnTPP) was loaded into MIL-101 (Zn[TPP]@MIL-101) to perform an adsorptive and...     

Predictive modeling of sorption and desorption of a reactive azo dye by pumpkin husk

The use of effective disposal of redundant pumpkin husk (PH) to remove pollutants is an important issue for environmental protection and utilization of resource. The aim of this study was to remove a potentially toxic reactive azo dye, Reactive Red (RR) 120, by widespread PH as a low-cost adsorbent. Particle size, adsorbent dose, pH, temperature, initial dye concentration, and contact time affected the sorption process. Amine, amide, hydroxyl, and carboxyl groups of PH played significant roles on the sorption process. Rapid sorption occurred within the first 2 min and equilibrium was reached within 60 min. Sorption kinetic was well represented by logistic equation. Generated secondary logistic model can be used to describe effects of initial dye concentration, contact time, and temperature by a single equation with high R ² value. Monolayer sorption capacity was found as 98.61 mg g^-1. Activation energy, thermodynamic, and desorption studies showed that this process was physical, endothermic, and spontaneous. This study indicated that redundant PH as a low-cost adsorbent had a great potential for the removal of RR 120 as an alternative eco-friendly process.     

Optimizing stabilization of waste-activated sludge using Fered-Fenton process and artificial neural network modeling (KSOFM,MLP)

Sludge management is a fundamental activity in accordance with wastewater treatment aims. Sludge stabilization is always considered as a significant step of wastewater sludge handling. There has been a progressive development observed in the approach to the novel solutions in this regard. In this research, based on own initially experimental results in lab-scale regarding Fered-Fenton processes in view of organic loading (volatile-suspended solids, VSS) removal efficiency, a combination of both methods towards proper improving of excess biological sludge stabilization was investigated. Firstly, VSS removal efficiency has been experimentally studied in lab-scale under different operational conditions taking into consideration pH [Fe²⁺]/[H₂O₂], detention time [H₂O₂], and current density parameters. Therefore, the correlations of the same parameters have been determined by utilizing Kohonen self-organizing feature maps (KSOFM). In addition, multi-layer perceptron (MLP) has been employed afterwards for a comprehensive evaluation of investigating parameters correlation and prediction aims. The findings indicated that the best proportion of iron to hydrogen peroxide and the optimum pH were 0.58 and 3.1, respectively. Furthermore, maximum retention time about 6 h with a hydrogen peroxide concentration of 1,568 mg/l and a current density of 650–750 mA results to the optimum VSS removal (efficiency equals to 81 %). The performance of KSOFM and MLP models is found to be magnificent, with correlation ranging (R) from 0.873 to 0.998 for the process simulation and prediction. Finally, it can be concluded that the Fered-Fenton reactor is a suitable efficient process to reduce considerably sludge organic load and mathematical modeling tools as artificial neural networks are impressive methods of process simulation and prediction accordingly.     

Application of a combined response surface methodology (RSM)-artificial neural network (ANN) for multiple target optimization and prediction in a magnetic coagulation process for secondary effluent from municipal wastewater treatment plants

Environmental Science and Pollution Research - In this study, an enhanced coagulation-flocculant process incorporating magnetic powder was used to further treat the secondary effluent of domestic...     

Impacts of Meteorological Factors on PM10: Artificial Neural Networks (ANN) and Multiple Linear Regression (MLR) Approaches

In this study, prediction capacities of multi-linear regression (MLR) and artificial neural networks (ANN) onto coarse particulate matter (PM₁₀) concentrations were investigated. Different meteorological factors on particulate pollution were chosen for operating variables in the model analyses. Two different regions (urban and industrial) were identified in the region of Kocaeli, Turkey. All data sets were obtained from air quality monitoring network of the Ministry of Environment and Urban Planning, and 120 data sets were used in the MLR and ANN models. Regression equations explained the effects of the meteorological factors in MLR analyses. In the ANN model, backpropagation network with two hidden layers has achieved the best prediction efficiency. Determination coefficients and error values were examined for each model. ANN models displayed more accurate results compared to MLR.     

The development and application of a simplified ozone modeling system (SOMS)

This paper describes the development and evaluation of a computationally efficient semi-empirical photochemical model that can be used as a screening tool to obtain quick estimates of the effect of a large number of VOC and NO_x emission control strategies on ozone concentrations. Selected control strategies can subsequently be examined with a more complex model. The model is one component of an ozone management system, the regional ozone decision model (RODM), designed to examine the costs and environmental consequences of alternate ozone abatement strategies.The model was developed by systematic simplification of a detailed photochemical model. At each step of the simplification, the simplified model was tested against observations and against results from the detailed model. The first major simplification was the introduction of a highly parameterized chemistry mechanism, originally developed by Azzi et al. (1992 Proc. 11th Int. Clean Air Conf., 4th Regional IUAPPA Conf.). This modification resulted in a factor of 5 improvement in the computational efficiency of the model. The model with the simplified chemistry was then tested by applying it to a photochemical oxidant episode in the San Joaquin Valley of California. Further improvements in computational speed and efficiency were obtained by uncoupling the chemistry from the transport of VOC and NO_x.     

Effect of o-phenylenediamine on Cu adsorption and desorption in red soil and its uptake by paddy rice (Oryza sativa)

A study was carried out of Cu adsorption and desorption processes in red soil as affected by o-phenylenediamine (o-PD) in the range 0-80 mg/l. The results indicated that the presence of o-PD enhanced Cu adsorption in red soil in weakly acid media, meanwhile, desorption percentage of Cu from soil, extracted by 1.0 M MgCl(2), also increased when Cu adsorption in soil occurred in the presence of o-PD. The response of paddy rice to Cu in red soil shows that Cu toxicity was mitigated in the presence of o-PD and that the Cu concentration in rice straw decreased with increasing concentration of o-PD from 0 to 4.0 mmol/kg in soil. The fractions of background Cu in soil did not change noticeably in the presence of o-PD, whereas the effect of o-PD on the fractions of added Cu was significant. It was found that the exchangeable and carbonate bound Cu fractions decreased and the fraction of Cu bound to Fe-Mn oxides and organic matter increased with increasing o-PD concentration in soil when Cu was added at the same rate. Copper concentration in rice straw was significantly correlated with exchangeable Cu (r=0.961) and carbonate bound Cu (r=0.959) in soil. This result implicates that the behavior of Cu in soil is likely to be affected by organic pollutants containing amino groups.     

Breakthrough Curves Characterization and Identification of an Unknown Pollution Source in Groundwater System Using an Artificial Neural Network (ANN)

Contamination of groundwater constrains its uses and poses a serious threat to the environment. Once groundwater is contaminated, the cleanup may be difficult and expensive. Identification of unknown pollution sources is the first step toward adopting any remediation strategy. The proposed methodology exploits the capability of a universal function approximation by a feed-forward multilayer artificial neural network (ANN) to identify the sources in terms of its location, magnitudes, and duration of activity. The back-propagation algorithm is utilized for training the ANN to identify the source characteristics based on simulated concentration data at specified observation locations in the aquifer. Uniform random generation and the Latin hypercube sampling method of random generation are used to generate temporal varying source fluxes. These source fluxes are used in groundwater flow and the transport simulation model to generate necessary data for the ANN model-building processes. Breakthrough curves obtained for the specified pollution scenario are characterized by different methods. The characterized breakthrough curves parameters serve as inputs to ANN model. Unknown pollution source characteristics are outputs for ANN model. Experimentation is also performed with different number of training and testing patterns. In addition, the effects of measurement errors in concentration measurements values are used to show the robustness of ANN based methodology for source identification in case of erroneous data.     

Application of Cordia trichotoma sawdust as an effective biosorbent for removal of crystal violet from aqueous solution in batch system and fixed-bed column

Environmental Science and Pollution Research - In this work, for the first time, Cordia trichotoma sawdust, a residue derived from noble wood processing, was applied as an alternative biosorbent...     

Efficiency of a cleanup technology to remove mercury from natural waters by means of rice husk biowaste: ecotoxicological and chemical approach

In the present work, the efficiency of rice husk to remove Hg(II) from river waters spiked with realistic environmental concentrations of this metal (μg L^?1 range) was evaluated. The residual levels of Hg(II) obtained after the remediation process were compared with the guideline values for effluents discharges and water for human consumption, and the ecotoxicological effects using organisms of different trophic levels were assessed. The rice husk sorbent proved to be useful in decreasing Hg(II) contamination in river waters, by reducing the levels of Hg(II) to values of ca. 8.0 and 34 μg L^?1, for an Hg(II) initial concentration of 50 and 500 μg L^?1, respectively. The remediation process with rice husk biowaste was extremely efficient in river waters spiked with lower levels of Hg(II), being able to eliminate the toxicity to the exposed organisms algae Pseudokirchneriella subcapitata and rotifer Brachionus calyciflorus and ensure the total survival of Daphnia magna species. For concentrations of Hg(II) tenfold higher (500 μg L^?1), the remediation process was not adequate in the detoxification process, still, the rice husk material was able to reduce considerably the toxicity to the bacteria Vibrio fischeri, algae P. subcapitata and rotifer B. calyciflorus, whose responses where fully inhibited during its exposure to the non-remediated river water. The use of a battery of bioassays with organisms from different trophic levels and whose sensitivity revealed to be different and dependent on the levels of Hg(II) contamination proved to be much more accurate in predicting the ecotoxicological hazard assessment of the detoxification process by means of rice husk biowaste.     

Seizure modeling of Pb(II) and Cd(II) from aqueous solution by chemically modified sugarcane bagasse fly ash: isotherms, kinetics, and column study

Heavy metal pollution is a common environmental problem all over the world. The purpose of the research is to examine the applicability of bagasse fly ash (BFA)—an agricultural waste of sugar industry used for the synthesis of zeolitic material. The zeolitic material are used for the uptake of Pb(II) and Cd(II) heavy metal. Bagasse fly ash is used as a native material for the synthesis of zeolitic materials by conventional hydrothermal treatment without (conventional zeolitic bagasse fly ash (CZBFA)) and with electrolyte (conventional zeolitic bagasse fly ash in electrolyte media (ECZBFA)) media. Heavy metal ions Pb(II) and Cd(II) were successfully seized from aqueous media using these synthesized zeolitic materials. In this study, the zeolitic materials were well characterized by different instrumental methods such as Brunauer–Emmett–Teller, XRF, Fourier transform infrared spectroscopy, powder X-ray diffraction, and scanning electron microscopic microphotographs. The presence of analcime, phillipsite, and zeolite P in adsorbents confirms successful conversion of native BFA into zeolitic materials. Seizure modeling of Pb(II) and Cd(II) was achieved by batch sorption experiments, isotherms, and kinetic studies. These data were used to compare and evaluate the zeolitic materials as potential sorbents for the uptake of heavy metal ions from an aqueous media. The Langmuir isotherm correlation coefficient parameters best fit the equilibrium data which indicate the physical sorption. Pseudo-second-order and intra-particle diffusion model matches best which indicates that the rate of sorption was controlled by film diffusion. The column studies were performed for the practical function of sorbents, and breakthrough curves were obtained, which revealed higher sorption capacity as compared to batch method. Synthesized zeolitic material (CZBFA and ECZBFA), a low-cost sorbent, was proven as potential sorbent for the uptake of Pb(II) and Cd(II) heavy metal ions.     

Investigations on mobility of carbon colloid supported nanoscale zero-valent iron (nZVI) in a column experiment and a laboratory 2D-aquifer test system

Nanoscale zero-valent iron (nZVI) has recently gained great interest in the scientific community as in situ reagent for installation of permeable reactive barriers in aquifer systems, since nZVI is highly reactive with chlorinated compounds and may render them to harmless substances. However, nZVI has a high tendency to agglomerate and sediment; therefore it shows very limited transport ranges. One new approach to overcome the limited transport of nZVI in porous media is using a suited carrier colloid. In this study we tested mobility of a carbon colloid supported nZVI particle “Carbo-Iron Colloids” (CIC) with a mean size of 0.63 μm in a column experiment of 40 cm length and an experiment in a two-dimensional (2D) aquifer test system with dimensions of 110?×?40?×?5 cm. Results show a breakthrough maximum of 82 % of the input concentration in the column experiment and 58 % in the 2D-aquifer test system. Detected residuals in porous media suggest a strong particle deposition in the first centimeters and few depositions in the porous media in the further travel path. Overall, this suggests a high mobility in porous media which might be a significant enhancement compared to bare or polyanionic stabilized nZVI.