Abstract <p>The complexation of organic ligands, such as aspartic acid (Asp), with copper ions (Cu<sup>2+</sup>) in aquatic systems presents emerging challenges for water treatment processes. This study experimentally and theoretically investigates the impact of Cu<sup>2+</sup>-Asp complexes on halonitromethanes (HNMs) formation during chloramination and UV<sub>254</sub>/chloramine treatment. Results demonstrated that the maximum concentrations of HNMs (e.g., CNM, DCNM, and TCNM) generated from Cu<sup>2+</sup>-Asp were 1.4-fold and 1.6-fold higher than those from Asp alone under chloramination and UV<sub>254</sub>/chloramine treatment, respectively. Neutral pH and Cu<sup>2+</sup> concentrations ranging from 1.0 to 3.0 mg L<sup>-1</sup> were identified as favorable conditions for HNMs formation. Mechanistically, the formation of a stable Cu<sup>2+</sup>-Asp complex facilitated a Cu<sup>2+</sup>/Cu<sup>1+</sup> redox cycle via Cu<sup>2+</sup>-Asp and Asp-Cu<sup>2+</sup> charge-transfer interactions. Experimental analyses revealed that the enhanced HNMs formation was primarily attributed to the generation of Cl• radicals driven by Cu<sup>1+</sup> intermediates, rather than the catalytic effect of Cu<sup>2+</sup> alone. Theoretically, machine learning models, particularly Gradient Boosting Regressor (R<sup>2</sup> = 0.968) and XGBoost (R<sup>2</sup> = 0.954), predicted HNMs formation with high accuracy, enabling optimization of disinfection parameters. Furthermore, plausible reaction pathways for HNMs formation from Asp were elucidated through experimental data and density functional theory (DFT) calculations. Finally, comparative assessments between simulated and actual water matrices confirmed the environmental relevance of the observed trends. This study offers novel insights into the catalytic and redox roles of Cu<sup>2+</sup> complexes during disinfection, advancing the mechanistic understanding, predictive modeling, and risk assessment strategies for HNMs formation in water treatment systems.</p> Graphical Abstract <p></p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Halonitromethanes Formation From Aspartic Acid in the Presence of Cu2+ During UV254/chloramine Treatment: Experimental and Computational Studies

  • Hidayat Ullah Khan,
  • Lin Deng,
  • Muhammad Asif,
  • Changbo Zhang,
  • Rajendra Prasad Singh,
  • Gongde Wu

摘要

Abstract

The complexation of organic ligands, such as aspartic acid (Asp), with copper ions (Cu2+) in aquatic systems presents emerging challenges for water treatment processes. This study experimentally and theoretically investigates the impact of Cu2+-Asp complexes on halonitromethanes (HNMs) formation during chloramination and UV254/chloramine treatment. Results demonstrated that the maximum concentrations of HNMs (e.g., CNM, DCNM, and TCNM) generated from Cu2+-Asp were 1.4-fold and 1.6-fold higher than those from Asp alone under chloramination and UV254/chloramine treatment, respectively. Neutral pH and Cu2+ concentrations ranging from 1.0 to 3.0 mg L-1 were identified as favorable conditions for HNMs formation. Mechanistically, the formation of a stable Cu2+-Asp complex facilitated a Cu2+/Cu1+ redox cycle via Cu2+-Asp and Asp-Cu2+ charge-transfer interactions. Experimental analyses revealed that the enhanced HNMs formation was primarily attributed to the generation of Cl• radicals driven by Cu1+ intermediates, rather than the catalytic effect of Cu2+ alone. Theoretically, machine learning models, particularly Gradient Boosting Regressor (R2 = 0.968) and XGBoost (R2 = 0.954), predicted HNMs formation with high accuracy, enabling optimization of disinfection parameters. Furthermore, plausible reaction pathways for HNMs formation from Asp were elucidated through experimental data and density functional theory (DFT) calculations. Finally, comparative assessments between simulated and actual water matrices confirmed the environmental relevance of the observed trends. This study offers novel insights into the catalytic and redox roles of Cu2+ complexes during disinfection, advancing the mechanistic understanding, predictive modeling, and risk assessment strategies for HNMs formation in water treatment systems.

Graphical Abstract