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<p>Results are presented for a study of ecological technologies for adsorption treatment of wastewater containing toxic arsenic, copper, and zinc ions at a fuel and energy complex. The aim of this work was to develop an efficient and ecologically-friendly method to remove heavy metals using natural zeolites and create a numerical model of mass transfer for predicting the parameters of this process. The adsorbent studied was a modified natural clinoptilolite with high heat resistance, large surface area, and good accessibility. When the Biot number ≥50 and the Damköhler number is 1000, the adsorption proceeds efficiently with the effective diffusion coefficient as the decisive parameter. The greatest adsorption capacity for the modified clinoptilolite was 29.5 mg/g for arsenic, 34.9 mg/g for copper, and 22.7 mg/g for zinc. These results permit the use of our model for engineering calculations and optimization of wastewater treatment at fuel and energy complexess.</p>

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Numerical Modelling of Adsorption Wastewater Treatment to Remove Heavy Metals

  • 期刊论文

  • 发表日期：

    2026年1月1日

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  • F. V. Yusubov,
  • A. A. Rzaeva,
  • A. M. Yaryeva

摘要

Results are presented for a study of ecological technologies for adsorption treatment of wastewater containing toxic arsenic, copper, and zinc ions at a fuel and energy complex. The aim of this work was to develop an efficient and ecologically-friendly method to remove heavy metals using natural zeolites and create a numerical model of mass transfer for predicting the parameters of this process. The adsorbent studied was a modified natural clinoptilolite with high heat resistance, large surface area, and good accessibility. When the Biot number ≥50 and the Damköhler number is 1000, the adsorption proceeds efficiently with the effective diffusion coefficient as the decisive parameter. The greatest adsorption capacity for the modified clinoptilolite was 29.5 mg/g for arsenic, 34.9 mg/g for copper, and 22.7 mg/g for zinc. These results permit the use of our model for engineering calculations and optimization of wastewater treatment at fuel and energy complexess.