Regression model, artificial neural network, and cost estimation for biosorption of Ni(II)-ions from aqueous solutions by Potamogeton pectinatus

Manal Fawzy, Mahmoud Nasr, Samar Adel, Shacker Helmi

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5 Citations (Scopus)

Abstract

This study investigated the application of Potamogeton pectinatus for Ni(II)-ions biosorption from aqueous solutions. FTIR spectra showed that the functional groups of –OH, C–H, –C = O, and –COO– could form an organometallic complex with Ni(II)-ions on the biomaterial surface. SEM/EDX analysis indicated that the voids on the biosorbent surface were blocked due to Ni(II)-ions uptake via an ion exchange mechanism. For Ni(II)-ions of 50 mg/L, the adsorption efficiency recorded 63.4% at pH: 5, biosorbent dosage: 10 g/L, and particle-diameter: 0.125–0.25 mm within 180 minutes. A quadratic model depicted that the plot of removal efficiency against pH or contact time caused quadratic-linear concave up curves, whereas the curve of initial Ni(II)-ions was quadratic-linear convex down. Artificial neural network with a structure of 5–6–1 was able to predict the adsorption efficiency (R2: 0.967). The relative importance of inputs was: initial Ni(II)-ions > pH > contact time > biosorbent dosage > particle-size. Freundlich isotherm described well the adsorption mechanism (R2: 0.974), which indicated a multilayer adsorption onto energetically heterogeneous surfaces. The net cost of using P. pectinatus for the removal of Ni(II)-ions (4.25 ± 1.26 mg/L) from real industrial effluents within 30 minutes was 3.4 $USD/m3.

Original languageEnglish
Pages (from-to)321-329
Number of pages9
JournalInternational Journal of Phytoremediation
Volume20
Issue number4
DOIs
Publication statusPublished - 21 Mar 2018

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Keywords

  • Agro-based sorbent
  • Ni(II)-ions biosorption
  • Statistical and intelligence models

ASJC Scopus subject areas

  • Environmental Chemistry
  • Pollution
  • Plant Science

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