Kinetics and Thermodynamics of Copper and Zinc Adsorption from Aqueous Solutions Using Leonardite: Response Surface Methodology Modeling

Document Type : Research Paper

Authors

1 Soil and water research department, West Azerbaijan Agricultural and Natural Resources Research and Education Center, ARREO, Urmia, Iran.

2 Department of Soil Science, Faculty of Agriculture, Urmia University, Urmia

3 Department of Soil Science, Faculty of Agriculture, Urmia University,

Abstract

The adsorption process using low-cost and readily available adsorbents is an effective method for removing heavy metals from contaminated aqueous solutions. In this study, leonardite as organic adsorbent used the adsorption of copper (Cu) and zinc (Zn) from aqueous solutions. The effect of contact time on the adsorption of Cu and Zn by leonardite was investigated. The adsorption capacity for these elements was determined at various time intervals and analyzed using kinetic models. The adsorption data at different temperatures (283, 293, 303, and 313 K) were fitted to the Langmuir, Freundlich, Temkin, and Dubinin–Radushkevich adsorption isotherm models. To evaluate the effect of independent variables pH, ionic strength, and initial concentration Response Surface Methodology (RSM) based on a Box-Behnken design was employed. The results indicated that adsorption increased with longer contact times and was best described by the pseudo-second-order kinetic model (R² = 0.99). Furthermore, the Langmuir isotherm provided the best fit for the adsorption data of both Cu and Zn (R² = 0.94–1.00). The adsorption capacity of Cu was higher than that of Zn, with maximum Langmuir adsorption capacities at 20°C of 13.80 mg g-1 for Zn and 16.23 mg g-1 for Cu. Thermodynamic parameters confirmed that the adsorption process for both metals was spontaneous and endothermic. The most influential parameter on adsorption was the initial metal concentration. Adsorption of Cu and Zn increased with higher initial metal concentration and pH but decreased with increasing ionic strength. Therefore, leonardite can be considered an effective and functional material for adsorbing heavy metals, including Cu and Zn, from contaminated water sources.

Keywords

Main Subjects

Introduction

The contamination of water resources by heavy metals, particularly from industrial, mining, and agricultural activities, poses a severe environmental and public health threat. Among these pollutants, copper (Cu) and zinc (Zn) are of significant concern due to their dual nature as essential micronutrients and toxic elements at elevated concentrations. Adsorption using low-cost and readily available adsorbents presents a promising and efficient technique for wastewater remediation. Leonardite, a naturally oxidized form of lignite rich in humic substances, has emerged as a potential cost-effective adsorbent due to its high cation exchange capacity and abundance of functional groups. This study comprehensively investigates the adsorption process of Cu and Zn ions onto leonardite, with the primary objectives of evaluating the kinetics and equilibrium of adsorption and optimizing the process parameters using Response Surface Methodology (RSM).

Methods
Batch adsorption experiments were conducted to assess the effects of contact time (kinetics), initial metal concentration, solution temperature (283, 293, 303, and 313 K), pH, and ionic strength. The leonardite adsorbent was characterized, and its metal uptake capacity was measured. Kinetic data were analyzed using pseudo-first-order, pseudo-second-order, Elovich, and power function models. Equilibrium isotherm data were fitted to Langmuir, Freundlich, Temkin, and Dubinin–Radushkevich models. Thermodynamic parameters (ΔG°, ΔH°, ΔS°) were calculated from temperature-dependent studies. For the optimization of Cu adsorption, a Box-Behnken Design (BBD) under the RSM framework was employed. Three independent variables initial solution pH, ionic strength, and initial metal concentration were varied, and their individual and interactive effects on the adsorption efficiency were statistically modeled and analyzed.

Results

The adsorption capacity for both Cu and Zn increased with contact time, reaching equilibrium. The kinetic data were best described by the pseudo-second-order model (R² > 0.99), suggesting chemisorption as the rate-limiting step. The equilibrium adsorption isotherm data showed an excellent fit to the Langmuir model (R² between 0.94 and 1), indicating monolayer adsorption on a homogeneous surface. The maximum Langmuir adsorption capacity at 20°C was found to be 16.23 mg/g for Cu and 13.80 mg/g for Zn, demonstrating a higher affinity of leonardite for copper ions. Thermodynamic analysis revealed negative ΔG° values (confirming the spontaneity of the process) and positive ΔH° values (indicating an endothermic nature). The RSM analysis confirmed that initial metal concentration and pH had the most significant positive effects on adsorption yield, while increased ionic strength negatively impacted the process due to competitive ion effects. The model derived from BBD effectively predicted the optimal conditions for maximum Cu removal.

Conclusions

Leonardite proves to be an effective, low-cost, and accessible adsorbent for the removal of Cu and Zn ions from contaminated aqueous solutions. The adsorption process is spontaneous, endothermic, and follows pseudo-second-order kinetics and Langmuir isotherm behavior. The successful application of RSM based on a Box-Behnken Design provides a robust statistical framework for optimizing critical operating parameters, thereby enhancing the process efficiency and paving the way for scalable applications. This study recommends leonardite as a sustainable and practical material for the remediation of heavy metal-laden water, particularly in scenarios requiring the selective removal of copper and zinc.

Funding

This article was conducted with the financial and moral support of the Vice Chancellor for Research of Urmia University. Financial support for this research was provided by Urmia University, Faculty of Agriculture in the form of research for the first author's student thesis and also research for other authors.

Author Contributions

 “Conceptualization, Marziyeh Piri, and Ebrahim Sepehr; methodology; software, Marziyeh Piri, and Ebrahim Sepehr; validation, Marziyeh Piri; formal analysis, Marziyeh Piri; investigation, Marziyeh Piri, and Ebrahim Sepehr; resources, Marziyeh Piri; data curation, Marziyeh Piri; writing original draft preparation, Marziyeh Piri; writing review and editing, Marziyeh Piri; funding acquisition, Urmia university. All authors have read and agreed to the published version of the manuscript.”

Declaration of Generative AI and AI-assisted technologies in the writing process

During the preparation of this work the author(s) not used AI-assisted technologies in the writing process.

Acknowledgements

The authors would like to thank the Urmia University for the financial support for this research project and for equipping the soil chemistry laboratory. The authors would like to thank all participants of the present study.

Ethical considerations

This study was approved by the Ethics Committee of Urmia University for the doctoral dissertation. The authors adhered to the highest standards of academic integrity, strictly avoiding any form of data fabrication, falsification, plagiarism, or research misconduct.

Conflict of interest

The author declares no conflict of interest

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Iranian Journal of Soil and Water Research
Volume 57, Issue 2
May 2026
Pages 449-465

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