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<p>This study selected tetracycline (TC) and typical heavy metals (Cu, Pb, Zn, Ni) to investigate TC adsorption behavior and mechanism on riparian soil of typical water bodies under heavy metal coexistence via adsorption experiments. Key factors including solution pH and heavy metal concentration were examined, and the heavy metal "bridge bonding–competitive" dual mechanism was elucidated by combining isothermal adsorption and kinetic model analyses. Additionally, a backpropagation-based artificial neural network (ANN) prediction model was constructed with inputs including pH, heavy metal type and concentration, achieving accurate prediction of TC adsorption behavior (R<sup>2</sup> &gt; 0.95). Results showed heavy metals significantly affected TC adsorption in the order: Cu (Qₑ = 4.425&#xa0;mg·kg⁻<sup>1</sup>) &gt; Pb (Qₑ = 3.380&#xa0;mg·kg⁻<sup>1</sup>) &gt; Zn (Qₑ = 1.474&#xa0;mg·kg⁻<sup>1</sup>) &gt; Ni (Qₑ = 1.372&#xa0;mg·kg⁻<sup>1</sup>). Low-concentration Cu<sup>2</sup>⁺/Pb<sup>2</sup>⁺ promoted adsorption via "bridge bonding", while high concentrations inhibited it by competing for sites. In contrast, low-concentration Zn<sup>2</sup>⁺/Ni<sup>2</sup>⁺ inhibited adsorption via competition, while high concentrations promoted it by neutralizing soil surface negative charges—Ni<sup>2</sup>⁺ showed the weakest promotion due to its tendency to form stable complexes. Kinetic and isothermal processes were better fitted by the pseudo-first-order (PFO) and Freundlich models, respectively. This study reveals TC adsorption regularities on riparian soil of typical water bodies under combined pollution, providing a theoretical basis for understanding environmental behavior of heavy metal–antibiotic complexes in soil. The established ANN model offers an effective tool for related environmental risk assessment and remediation.</p>

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Investigation of the Effects of Heavy Metal Pollution on Tetracycline Adsorption Behavior and Its Mechanisms in Riparian Zone Soils

  • 期刊论文

  • 发表日期：

    2026年3月20日

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  • Jian Wang,
  • Hao Chen,
  • Xinyu Xia,
  • Lingyun Guo,
  • Na Luo,
  • Yuming Yao

摘要

This study selected tetracycline (TC) and typical heavy metals (Cu, Pb, Zn, Ni) to investigate TC adsorption behavior and mechanism on riparian soil of typical water bodies under heavy metal coexistence via adsorption experiments. Key factors including solution pH and heavy metal concentration were examined, and the heavy metal "bridge bonding–competitive" dual mechanism was elucidated by combining isothermal adsorption and kinetic model analyses. Additionally, a backpropagation-based artificial neural network (ANN) prediction model was constructed with inputs including pH, heavy metal type and concentration, achieving accurate prediction of TC adsorption behavior (R2 > 0.95). Results showed heavy metals significantly affected TC adsorption in the order: Cu (Qₑ = 4.425 mg·kg⁻1) > Pb (Qₑ = 3.380 mg·kg⁻1) > Zn (Qₑ = 1.474 mg·kg⁻1) > Ni (Qₑ = 1.372 mg·kg⁻1). Low-concentration Cu2⁺/Pb2⁺ promoted adsorption via "bridge bonding", while high concentrations inhibited it by competing for sites. In contrast, low-concentration Zn2⁺/Ni2⁺ inhibited adsorption via competition, while high concentrations promoted it by neutralizing soil surface negative charges—Ni2⁺ showed the weakest promotion due to its tendency to form stable complexes. Kinetic and isothermal processes were better fitted by the pseudo-first-order (PFO) and Freundlich models, respectively. This study reveals TC adsorption regularities on riparian soil of typical water bodies under combined pollution, providing a theoretical basis for understanding environmental behavior of heavy metal–antibiotic complexes in soil. The established ANN model offers an effective tool for related environmental risk assessment and remediation.