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<p>The major setback during wastewater treatment is the competition from several background ions and organic acids, hindering adsorbent-pollutant interactions and reducing removal efficiency. To address this issue, it is essential to find a promising methodology that can optimize ion effects, predict adsorbents’ best removal efficiency, and determine significant influencing ions. Thus, the present study employed RSM-CCD design-based methodology with five input variables (HCO<sub>3</sub><sup>−</sup>, SO<sub>4</sub><sup>2−</sup>, NO<sub>3</sub><sup>−</sup>, Cl<sup>−</sup>, and humic acid) to simulate and optimize various wastewater environments, so as to investigate the reactivity of GSH@Fe<sub>3</sub>O<sub>4</sub> NPs for phenol red (PR) dye. The quadratic model was found to be in best agreement with the experimental data, with an <i>R</i><sup>2</sup> of 0.98. The other statistical tests and diagnostic plots also confirmed that the above model is highly reliable, accurate and provides good precision. The highest removal in a multicomponent system was predicted to be 83.09% when all the dominating species were kept at optimal points. Moreover, the experimental data fitted well for pseudo-second-order reaction, elucidating chemisorption as the major adsorption mechanism. When tested with real wastewater matrices, the PR dye removal followed the order: tap water &gt; paper and pulp wastewater &gt; sewage &gt; textile wastewater. The findings of this study can be very instrumental in strategizing the wastewater conditions and enhancing removal efficiency in treatment plants while contributing towards real-world applications and sustainable wastewater treatment practices.</p>

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Investigating the impact of multiple background species on the reactivity of GSH@Fe3O4 employing RSM-CCD design tool for the sorption of a model anionic dye

  • 期刊论文

  • 发表日期：

    2025年7月10日

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  • Monalisha Behera,
  • Sonamuni Murmu,
  • Nisha Kumari,
  • Prashant Kumar Jaiswal,
  • Ritu Singh

摘要

The major setback during wastewater treatment is the competition from several background ions and organic acids, hindering adsorbent-pollutant interactions and reducing removal efficiency. To address this issue, it is essential to find a promising methodology that can optimize ion effects, predict adsorbents’ best removal efficiency, and determine significant influencing ions. Thus, the present study employed RSM-CCD design-based methodology with five input variables (HCO3−, SO42−, NO3−, Cl−, and humic acid) to simulate and optimize various wastewater environments, so as to investigate the reactivity of GSH@Fe3O4 NPs for phenol red (PR) dye. The quadratic model was found to be in best agreement with the experimental data, with an R2 of 0.98. The other statistical tests and diagnostic plots also confirmed that the above model is highly reliable, accurate and provides good precision. The highest removal in a multicomponent system was predicted to be 83.09% when all the dominating species were kept at optimal points. Moreover, the experimental data fitted well for pseudo-second-order reaction, elucidating chemisorption as the major adsorption mechanism. When tested with real wastewater matrices, the PR dye removal followed the order: tap water > paper and pulp wastewater > sewage > textile wastewater. The findings of this study can be very instrumental in strategizing the wastewater conditions and enhancing removal efficiency in treatment plants while contributing towards real-world applications and sustainable wastewater treatment practices.