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.     

松树锯末对亚甲基蓝（MB）的吸附研究

采用松树锯末以及改性松树锯末对模拟废水中的亚甲基蓝进行吸附实验研究。研究结果表明,当亚甲基蓝的初始浓度为50 mg/L、pH为6、锯末投加量为1 g/L时,改性前后的锯末对亚甲基蓝的吸附量最大,分别为29.9 mg/g和60.6 mg/g。同时,对改性前后的锯末做了吸附等温线拟合及动力学研究。结果表明,吸附等温线均能很好地符合Langmuir吸附模式,吸附过程符合拟二级动力学方程。     

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...     

海藻酸纤维动态吸附废水中亚甲基蓝染料

自制了海藻酸纤维并从动态吸附方面研究了海藻酸纤维对阳离子染料亚甲基蓝的吸附性能,采用2种动力学模型(Thomas模型和Yoon-Nelson模型)对不同浓度的亚甲基蓝染料溶液动态吸附曲线进行了分析.结果表明,Thomas模型和Yoon-Nelson模型对海藻酸纤维吸附亚甲基蓝染料都有较高的拟合度,由2种模型分析得出的海...     

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.     

改性甘薯渣对亚甲基蓝的吸附特性及吸附机制

以甘薯渣作为材料,针对亚甲基蓝溶液初始浓度、溶液pH、改性甘薯渣加入量、吸附温度、吸附时间各因素对吸附率的影响进行实验,进一步对影响显著的初始浓度、加入量、时间采用二次正交旋转组合设计优化,得到浓度80 mg·L-1、加入量1.0 g、时间1 h时预测最大吸附率96.25%,实测95.89%,二者吻合。改性甘薯渣对亚甲基蓝吸附过程符合Freundlich等温式及准二级动力学模型,说明其吸附过程由化学速率控制的多位点物理化学混合吸附。据Langmuir等温式计算饱和吸附量为20.16 mg·g-1。SEM观测得知改性甘薯渣处理后疏松多孔的表面有利于吸附。经FTIR可知,羟基、羧基在吸附过程中有主要作用。     

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.     

基于过碳酸钠的类Fenton体系对亚甲基蓝的降解动力学

采用改良低温结晶法制备过碳酸钠(sodium percarbonate,SPC),对其进行XRD表征,并用以作为氧化剂构建类Fenton体系(SPC/Fe2+)降解亚甲基蓝(MB),对其降解的影响因素及反应动力学进行了研究。结果表明,在该体系中,当溶液初始pH分别为2~10时,亚甲基蓝的去除率在1 min时均可达到97%以上,说明该体系可高效去除水体中的亚甲基蓝,反应速率快,且过碳酸钠的使用可以拓宽Fenton反应的pH范围。该反应的最佳工艺条件为0.75 g·L-1硫酸亚铁,300 mg·L-1过碳酸钠,亚甲基蓝去除率在反应10 min后可达99.0%。亚甲基蓝在该体系中的降解遵循二级反应动力学方程,反应速率常数分别为64.50×10-3 L·(mol·s)-1,快于Fenton体系的17.83×10-3 L·(mol·s)-1。该体系反应活化能为16.6 kJ·mol-1,远小于Fenton体系(46.234 kJ·mol-1),说明以过碳酸钠为氧化剂更有利于非均相类Fenton反应的发生。     

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...     

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...     

H_4SiW_(12)O_(40)/TiO_2/beads光催化降解亚甲基蓝的研究

以钛酸四丁酯为原料,空心微珠为载体,采用溶胶-凝胶法制备TiO2/beads光催化剂载体,然后浸渍法制备出H4SiW12O40/TiO2/beads表面负载修饰型复合光催化剂,并运用SEM、XRD、FT-IR和DRS对催化剂进行表征和分析.研究了H4SiW12O40/TiO2/beads对亚甲基蓝降解的光催化活性,考察了光强度、pH值、曝气量、底物浓度和催化剂用量等对催化效率的影响.实验结果表明,在中性条件下,H4SiW12O40/TiO2/beads催化剂的投加量为0.25 g/L,浓度为7.5 mg/L的亚甲基蓝溶液在250 W的紫外灯和600 W的可见光灯下光照60 min降解率分别可达到94.5%和55%.     

改性炭化谷壳负载纳米Fe3O4对含As(V)废水的吸附性能

以谷壳为原料,通过600℃缺氧高温热解制备一种炭化谷壳（CRH-I）,并利用CRH-I通过改性负载方法获得另一种新型的负载纳米Fe3O4的碱改性炭化谷壳（CRH-II）。经过对比表面积进行表征分析发现,CRH-II相较CRH-I的BET比表面积增大约30%,达到182 m2·g-1,微比表面积和微孔体积都扩大了6倍左右。FTIR分析结果表明,相比CRH-I,CRH-II分子间的羧基和酚羟基官能团有所增加,产生了芳构化反应和脂肪醚类物质。吸附实验表明,相对CRH-I而言,CRH-II对As（V）的吸附率明显提高。pH=2时,CRH-II对溶液中As（V）的吸附率达到98.3%;但是As的吸附率随着溶液pH值升高而逐渐降低,pH=11时下降最为明显,吸附率只有63.4%。CRH-II吸附反应满足准动力学二级方程,其相关系数为R2=0.999;在不同温度下,将CRH-II对As（V）的吸附验数据进行Langmuir方程和Freundlich等温方程拟合,结果更符合Langmuir方程;在25℃时,相关系数R2=0.985。解吸吸附实验证明,CRH-II依然具备良好的吸附性能,且再生吸附性能稳定。     

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.     

复合型CoO/TiO2光催化剂降解亚甲基蓝动力学研究

以钛酸四丁酯为前驱体,采用溶胶凝胶法,制备了CoO掺杂的TiO2光催化剂。利用X射线衍射（XRD）、扫描电镜（SEM）、透射电镜（TEM）、紫外可见漫反射（UV-vis DRS）对催化剂进行了分析、表征。以中压汞灯为光源,研究了亚甲基蓝（MB）在CoO/TiO₂微粒水悬浮液中的降解动力学。结果表明：所制备的催化剂活性组分主要是锐钛矿型的二氧化钛和CoO固溶体,粒径为25～30 nm,分布均匀。亚甲基蓝的光催化降解动力学满足一级动力学,在一定的浓度范围内,反应速率常数随初始浓度增大而减少,适当的掺钴量可以有效地提高TiO₂光催化活性,其最佳掺杂量重量百分比为0.25%。     

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.