Green and efficient biosorptive removal of methylene blue by Abelmoschus esculentus seed: Process optimization and multi-variate modeling

被引:89
作者
Nayak, Ashish Kumar [1 ]
Pal, Anjali [1 ]
机构
[1] Indian Inst Technol, Civil Engn Dept, Kharagpur 721302, W Bengal, India
关键词
Methylene blue; Lady's finger (Abelmoschus esculentus); Biosorption; Response surface methodology (RSM); Artificial neural network (ANN); AQUEOUS-SOLUTION; MALACHITE GREEN; ADSORPTION CHARACTERISTICS; EXPERIMENTAL-DESIGN; ACTIVATED CARBON; HEAVY-METALS; WASTE-WATER; BASIC DYE; KINETICS; EQUILIBRIUM;
D O I
10.1016/j.jenvman.2017.05.045
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The present work explores, for the first time, the adsorptive removal of methylene blue (MB) dye from aqueous solution using different parts of abundantly available agricultural product, Abelmoschus esculentus (lady's finger), and the processed seed powder (designated as LFSP) was found as the best. The aforesaid biosorbent was characterized using field emission scanning electron microscopy (FESEM), Fourier transform infrared spectroscopy (FTIR) and pHzpc analyses. The biosorption performance was evaluated using batch studies at 303 K, at varying operating conditions such as solution pH, biosorbent dosage, initial dye concentration and contact time. The pseudo-second order kinetic model was followed during the adsorption, and it was also found that intra-particle diffusion played a prominent role in the rate-controlling step. Langmuir and Temkin isotherms were followed the best, as was evident from the lower % non-linear error values and higher degree of determination coefficients. Thermodynamic investigations revealed that the biosorption processes were spontaneous and endothermic. Using the response surface methodology (RSM), a central composite design was developed, and subsequently applied as an input for the artificial neural network (ANN) approach in order to further analyze the interactive term effects between the significant process parameters, on the maximum biosorption capacity for MB dye removal by LFSP. The non-linear error functions and linear regression coefficients on the RSM model showed its dominance behaviour over ANN model for both data fitting and estimation capabilities. Using the statistical optimization, the maximum uptake capacity was found to be 205.656 mg/g. Experiments were conducted to regenerate the adsorbent and to recover the adsorbed dye using the eluent 0.5 M HCI. Cost analysis showed that, LFSP was 7 times cheaper than commercially available activated carbons. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:145 / 159
页数:15
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