Using the quantitative ion character-activity relationships (QICAR) model to predict the solid-liquid release of...

Dissolved metals in the soil's liquid phase are more easily absorbed by biological tissues, thus posing potential risks to living organisms. Therefore, studying the solid-liquid partition coefficient (K_d) of metals in the soil helps understand their environmental risks. We collected 102 K_d data of metals in soil from the literature to build a quantitative ion character-activity relationship model (s-QICAR) based on the metals' physicochemical properties. Correlation analysis showed ten elemental physicochemical properties related to K_d, including covalent bond index, atomic mass, and first hydrolysis constant, with R² = 0.502-0.989. Through comparative screening, 39s-QICAR models were finally established, including covalent bond index and first hydrolysis constant. The established s-QICAR model predicted the K_d values of Mo, Sb, and La in the 39 soil samples, ranging from 21 to 19978. Finally, a coupling analysis was conducted between K_d-metal and soil physicochemical properties. The s-QICAR model with covalent bond index as the independent variable was mainly affected by soil pH and cation exchange capacity, while the s-QICAR model with first hydrolysis constant was influenced primarily by clay content. Therefore, this study established a predictive model for soil K_d, providing a basis for soil environmental risk assessment and management. ENVIRONMENTAL IMPLICATION: Dissolved metals present in the soil liquid phase are more easily absorbed by biological tissues, thus posing potential risks to living organisms. Therefore, studying the solid-liquid partition coefficient (K_d) of metals in the soil helps understand their environmental risks. Common K_d values are obtained by measuring the content of soil solid and liquid phase metals. However, this method is time-material consuming. We study the relationship between element properties and their K_d, then establish a model that does not rely on measured data to predict K_d of soil elements, providing a basis for soil environmental risk assessment and management.