The bioavailability and mobility of copper (Cu) in soil play a crucial role in its toxicity and impact on soil organisms. Humic substances, with their abundant functional groups and unique pore structure, have demonstrated the ability to effectively mitigate the toxic effects of heavy metals in soil. This study explores the potential of a soluble humic substance (HS) derived from leonardite for Cu removal from contaminated soils. The effects of various washing conditions, such as concentration and washing cycles, on removal efficiency were assessed. The results showed that a single washing with HS solution achieved an optimal removal efficiency of 37.5% for Cu in soil, with a subsequent reuse achieving a removal efficiency of over 30.5%. To further enhance Cu removal efficiency, a two-step soil washing approach using a chemical reductant NH₂OH·HCl coupled with an HS solution (NH₂OH·HCl + HS) was employed, resulting in an increased removal efficiency to 53.0%. Furthermore, this approach significantly reduced the plant availability and bioaccessibility of Cu by 13.6% and 11.4%, respectively. Compared to a single washing with NH₂OH·HCl, both HS and NH₂OH·HCl + HS increased the soil pH and organic matter content. These findings suggest that the two-step soil-washing approach using NH₂OH·HCl + HS effectively removed Cu from polluted soil. This study demonstrates the potential of humic substances as environmentally friendly materials for remediating heavy metal-polluted soil, promoting green and sustainable applications in soil remediation practices.

The urgency of addressing farmland contamination is undeniable. However, the environmental impacts associated with soil remediation, especially during the production of remediation materials, are often overlooked. This study seeks to fill this gap by conducting a comprehensive environmental impact assessment of remediation material production processes. We apply a Life Cycle Assessment (LCA) framework, enhanced by a multi-objective optimization model combining the Analytic Hierarchy Process (AHP) and Techniques for Order Preference by Similarity to an Ideal Solution (TOPSIS). This method enables the integration of multiple environmental indicators into a high-dimensional reference system, reducing subjectivity in decision-making. The study focuses on the environmental impacts of 11 types of biochar materials used in soil remediation. Among these, alkali-modified biochar loaded with nano TiO₂ exhibited the highest environmental impact index. Sensitivity analysis further confirmed the robustness of the method, with impact variations ranging from 0.44 to 0.52, suggesting the model’s reliability in comparing different remediation materials. Our findings highlight the significant environmental variability between remediation materials and underscore the necessity of incorporating comprehensive environmental assessments in material selection processes. This study provides a valuable framework for optimizing the environmental sustainability of soil remediation efforts.