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构建和验证参数模型,以预测土壤中的吸附

Joan Serra-Ventura¹, Miquel Vidal¹, Anna Rigol²

¹Departament d'Enginyeria Química i Química Analítica, Facultat de Química, Universitat de Barcelona (UB), Martí i Franquès 1-11, 08028 Barcelona, Spain.

The Science of the total environment

|June 14, 2024

概括

(Ra) 吸收到土壤中的程度为中度至高,并且在很大程度上是不可逆转的. ,和pH等土壤特性显著影响Ra分布,使环境风险评估的预测模型成为可能.

科学领域:

环境科学环境科学
地质化学地质化学
放射化学放射化学是指辐射化学.

背景情况:

了解自然存在的放射性核素 (NOR) 转移对于评估生态系统对自然存在的放射性核素材料 (NORM) 的暴露至关重要.
(Ra) 是一种自然存在的关键放射性核化物,其在土壤中的吸收行为决定了它的环境流动性和生物可用性.

研究的目的:

在不同类型的土壤中量化 (Ra) 的吸附和脱吸系数 (Kd).
确定影响Ra吸收的关键土壤特性,并开发Kd (Ra) 的预测模型.

主要方法:

实验室批量实验对31个土壤样本进行了测试,这些土壤样本具有不同的土壤性质.
在受控条件下测量了Ra的固体-液体分布系数 (Kd).
部分最小平方回归 (PLS) 和线性回归 (ULR,MLR) 用于模拟Ra吸收.

主要成果:

吸附是中等到高 (Kd值从10^2到10^3 L/kg) 和主要不可逆转 (脱吸<2%).
与交换地点相关的土壤特性,如Ca,Mg和pH,是Kd (Ra) 的主要驱动因素.
预测模型使用Kd (Ca+Mg),pH,Mn和表面积等参数解释了高达80%的Kd (Ra) 方差.

结论:

土壤中的吸收受到土壤化学的显著影响,特别是阴离子交换能力和pH值.
经过验证的预测模型允许使用常规土壤分析来估计 Ra 在土壤中的分布.
这些模型可以提高有关NORM的环境风险评估的准确性.

关键词:

分布系数分布系数互动互动互动预测模型的预测模型.辐射辐射辐射辐射辐射土壤土壤土壤.

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