Statistical optimization of nZVI chemical synthesis approach towards P and NO3 removal from aqueous solutions: Cost-effectiveness & parametric effects

Ibrahim Maamoun, Ramadan Eljamal, Osama Eljamal

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1 Citation (Scopus)

Abstract

This study aims to conduct statistical optimization of nZVI synthesis parameters towards the removal efficiency of phosphorus (P) and nitrate (NO3), considering for the first time the cost-effectiveness index. The detailed statistical analysis was implemented to evaluate the main effects and interactions of eight synthesis parameters, including reductant concentration (RC), reductant delivery rate (RDR), reductant liquid volume (RLV), pH, aging time (AGT), mixing speed (MS), temperature (T), and precursor concentration (PC). Results revealed that the experimental optimization of the synthesis factors improved the removal efficiency of NO3 and P by 27 and 9%, respectively, with respect to that before the optimization. ANOVA statistical results indicated the significance of RP (%) and RNO3 (%) models with F-values of 4.480 × 108 and 23,755.08, respectively. Moreover, the p-values of all the eight main linear effects were less than 0.05 in both two models of RP (%) and RNO3 (%). However, most of the interaction parameters were not statistically significant (higher than 0.05) in the case of RNO3 (%), which is unlike RP (%) where all interaction parameters were statistically significant (less than 0.05). The normal probability plots of factors effects provided significant evidence of the significance of the investigated parameters RC had the highest positive statistically significant effect on RP (%) followed by RLV, RDR, MS and T. In case of RNO3 (%), RLV had the highest positive significant effect, followed by AGT > RDR > pH > T > MS. The cost-effective optimal constraints in this study resulted in the best economically optimized values of the nZVI synthesis parameters in terms of higher reactivity and reduced synthesis cost.

Original languageEnglish
Article number137176
JournalChemosphere
Volume312
DOIs
Publication statusPublished - Jan 2023

All Science Journal Classification (ASJC) codes

  • Environmental Engineering
  • Environmental Chemistry
  • Chemistry(all)
  • Pollution
  • Public Health, Environmental and Occupational Health
  • Health, Toxicology and Mutagenesis

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