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Journal of Hazardous MaterialsVolume 363, 5 February 2019, Pages 366-375

A new approach for modelling and optimization of Cu(II) biosorption from aqueous solutions using sugar beet shreds in a fixed-bed column(Article)

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  • University of Novi Sad, Faculty of Technology Novi Sad, Bulevar cara Lazara 1, 21 000 Novi Sad, Serbia

Abstract

The potential use of sugar beet shreds for copper ions removal from aqueous solution in a fixed-bed column was investigated. Experiments were performed using Box-Behnken experimental design on three levels and three variables: concentration of the inlet solution (50–150 mg L−1), adsorbent dosage (8–12 g) and pH of the inlet solution (4.0–5.0). The obtained breakthrough curves were fitted with two common empirical models, Bohart-Adams and dose-response. Observing the asymmetric shape of the breakthrough curves, the new mathematical model was proposed. The new model proposes the breakthrough curve composed of two parts, sum of which gives the asymmetrical S-shaped curve, accurately matching experimental data. Regarding the lowest SSer (7.8·10-4) and highest R2 (0.9998), new model exhibited the best fit comparing to the commonly used models. RSM and ANN modelling were employed for process variables evaluation and optimization. The most influential parameter exhibiting negative influence on target response (critical time) was concentration of the inlet solution, while the adsorbent dosage exhibited positive influence. Optimization procedure revealed that the highest critical time (341.4 min) was achieved at following conditions: C0 = 50 mg·L-1, ma = 12 g and pH 4.53 by ANN, while RSM considered pH as insignificant factor and obtained 314.8 min as the highest response. © 2018 Elsevier B.V.

Author keywords

Artificial neural networkCopper biosorptionModellingOptimizationResponse surface methodology

Indexed keywords

Engineering controlled terms:AdsorptionBiosorptionDesign of experimentsMetal ionsModelsNeural networksOptimizationSolutionsSugar beets
Engineering uncontrolled termsBox-Behnken experimental designBreak through curveFixed bed columnsNew mathematical modelOptimization proceduresProcess VariablesResponse surface methodologySugar beet shreds
Engineering main heading:Copper compounds
EMTREE drug terms:adsorbentcupric ioncopper
GEOBASE Subject Index:aqueous solutionartificial neural networkbreakthrough curveconcentration (composition)copperdose-response relationshipexperimental designexperimental studyoptimizationresponse surface methodologysorptiontuber
EMTREE medical terms:adsorptionaqueous solutionArticleartificial neural networkbiosorptionmathematical modelpHprocess optimizationresponse surface methodsugar beetbeetchemical modelchemistryisolation and purificationwater pollutant
Species Index:Beta vulgaris subsp. vulgaris
MeSH:AdsorptionBeta vulgarisCopperModels, ChemicalNeural Networks, ComputerWater Pollutants, Chemical

Chemicals and CAS Registry Numbers:

copper, 15158-11-9, 7440-50-8;

Copper; Water Pollutants, Chemical

Funding details

Funding sponsor Funding number Acronym
Ministarstvo Prosvete, Nauke i Tehnološkog RazvojaAPV 142-451-3591/2017-01/02,III43005MPNTR
Provincial Secretariat for Higher Education and Scientific Research, Autonomous Province of Vojvodina
  • 1

    This research was supported by the grants III43005 ( Ministry of Education, Science and Technological Development, Republic of Serbia ) and APV 142-451-3591/2017-01/02 ( Provincial Secretariat for Higher Education and Scientific Research ).

  • ISSN: 03043894
  • CODEN: JHMAD
  • Source Type: Journal
  • Original language: English
  • DOI: 10.1016/j.jhazmat.2018.09.068
  • PubMed ID: 30321841
  • Document Type: Article
  • Publisher: Elsevier B.V.

  Bera, O.; University of Novi Sad, Faculty of Technology Novi Sad, Bulevar cara Lazara 1, 21 000 Novi Sad, Serbia;
© Copyright 2018 Elsevier B.V., All rights reserved.

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