Modelling and Optimization of the Removal of Congo-Red Dye from Waste Water Using Agricultural Waste
Journal of Chemical, Environmental and Biological Engineering
Volume 1, Issue 1, June 2017, Pages: 1-7
Received: Oct. 22, 2016; Accepted: Nov. 2, 2016; Published: Dec. 14, 2016
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Authors
Adepoju Tunde Folorunsho, Department of Chemical and Petrochemical Engineering, Akwa-Ibom State University, Ikot Akpaden, Mkpat Enin L.G.A., Nigeria
Uzono Romokere Isotuk, Department of Chemical and Petrochemical Engineering, Akwa-Ibom State University, Ikot Akpaden, Mkpat Enin L.G.A., Nigeria
Akwayo Iniobong Job, Department of Chemical and Petrochemical Engineering, Akwa-Ibom State University, Ikot Akpaden, Mkpat Enin L.G.A., Nigeria
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Abstract
The continuous utilization of dye in the industries and commodity products has necessitate its development by sustainable approach. However, for the success and commercialization of these products, their cost of production should be compared to the existing products available in the market. To do these, there is a need to introduce cheap feedstock for Congo red dye removal (CDRRR). Its optimization will ease the process of production and give the optimum acceptable yield. Result showed that highest CRDRR yield was 104.00 (mg/L) at pH(X1) = 1, AD(X2) = 0 and Time (X3) = -1, respectively. Box-Behnken response surface methodology (BBSRM) predicted a yield of 91.233 (mg/L) for CRDRR at X1 = -0.423, X2 = -1.00 and X3 = -1.00 variables condition, which was validated as 90.87 (mg/L). ANN genetic algorithm predicted CRDRR of 92.561 (mg/L) at variables condition X1 = -0.567, X2 = -0.89 and X3 = -1.00, which was validated as 91.53 (mg/L). Modelling and optimization derived equations that showed the relationship between the CRDRR and variables (X1, X2 and X3) in term of coded for RSM: CRDRR(%)= 92.67+0.72X1-5.67X2+6.50X3-7.66X1X2-4.59X1X3+6.20X2X3-0.35X1 2-1.14X22-0.12X32; actual factors for ANN: CRDRR(%)=55.70808+7.18508X1+9.74067X2+5.77729X3-3.40222X1X2-1.22467X1X3+6.61867X2X3-0.039194X12-2.02711X22-0.078560 The study concluded that agro waste is suitable feedstock for Congo red dye removal and the statistical software proved suitable for modelling and optimization.
Keywords
Congo- Red Dye, Agricultural Waste, Optimisation, Modelling, Response Surface Methodology, Artificial Neural Network
To cite this article
Adepoju Tunde Folorunsho, Uzono Romokere Isotuk, Akwayo Iniobong Job, Modelling and Optimization of the Removal of Congo-Red Dye from Waste Water Using Agricultural Waste, Journal of Chemical, Environmental and Biological Engineering. Vol. 1, No. 1, 2017, pp. 1-7. doi: 10.11648/j.jcebe.20170101.11
Copyright
Copyright © 2016 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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