Parametric optimization and MCR-ALS kinetic modeling of electro oxidation process for the treatment of textile wastewater

Parminder Kaur, Monzur A. Imteaz, Mika Sillanpää, Vikas Kumar Sangal, Jai Prakash Kushwaha

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)

Abstract

Kinetic modeling using multivariate curve resolution-alternating least squares (MCR-ALS) was performed successfully for the electro oxidation (EO) treatment of textile wastewater. The present study represents the monitoring of the % degradation and kinetics of the EO reaction during the treatment of textile effluent. Optimum condition was found to be t ​= ​130 ​min, i ​= ​1.41 A, pH ​= ​5.41 and Retention time ​= ​143 ​min. At this optimum condition, the degradation suggested by response surface methodology (RSM) under central composite design (CCD) was 86%. A good correlation was observed between the predicted and experimental % degradation at the optimum value of process parameters. Spectrophotometric data of EO process during the treatment of textile effluent was analyzed during MCR-ALS. ALS optimization was performed by applying a series of constraints. The initial and final concentration of the pollutants along with the kinetic parameters were successfully resolved. The performance of kinetic modeling on predicting EO treatment was evaluated by a lack of fit in % experimental (1.215) and explained variance (99.98%).

Original languageEnglish
Article number104027
JournalChemometrics and Intelligent Laboratory Systems
Volume203
DOIs
Publication statusPublished - 15 Aug 2020
Externally publishedYes

Keywords

  • Electro oxidation
  • Kinetic parameters
  • Kinetic-modeling
  • MCR-ALS
  • RSM
  • Spectrophotometric data

ASJC Scopus subject areas

  • Analytical Chemistry
  • Software
  • Computer Science Applications
  • Process Chemistry and Technology
  • Spectroscopy

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