Tang Yujie, Jia Mengfan, Xie Xinxin, Wang Xuedong, Zhou Zhigao, Wang Xingxiang, Ding Changfeng
State Key Laboratory of Soil & Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 211135, China; College of Resource Environment and Tourism, Capital Normal University, Beijing, 100048, China.
State Key Laboratory of Soil & Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 211135, China; Agricultural and Rural Development Service Center, Liaocheng, 252000, China.
Environ Pollut. 2025 Sep 15;381:126618. doi: 10.1016/j.envpol.2025.126618. Epub 2025 Jun 3.
In China, the co-contamination of soil with cadmium (Cd) and arsenic (As) is one of the most severe forms of combined pollution. Modeling the transfer of Cd and As from co-contaminated soil to crops has not been thoroughly studied. In this study, five soils with significant differences in physicochemical properties were selected to simulate the compound pollution conditions by exogenously adding Cd and As, and the bioaccumulation and translocation behaviors of these two elements were thoroughly investigated. The study used machine learning methods and stepwise linear regression to establish prediction models for the accumulation of Cd and As in peanut plants. The safety thresholds of Cd and As in soil based on food quality standards were then derived. The results demonstrated that peanuts exhibited significantly higher Cd accumulation capacity compared to As, with bioconcentration factors (BCFs) ranging from 0.77 to 36.55 for Cd and 0.006 to 0.449 for As. Cd was mainly translocated to peanut shoots and concentrated aboveground, while As was mainly accumulated in roots. Compared to single Cd contamination, the presence of As increased Cd concentrations in roots, shoots, shells, and kernels by up to 87.5 %, 71.3 %, 120.2 %, and 48.9 %, respectively. Conversely, the presence of Cd reduced As content in roots, shells, and kernels by up to 38.3 %, 45.5 %, and 38.1 %. Using the XGBoost and stepwise linear regression models, key factors influencing the accumulation of Cd and As in plants were identified. Additionally, corresponding regression prediction equations were developed, which explained over 0.66 of the variance in metal accumulation in peanut parts. Our derived soil safety thresholds suggest that contaminant concentrations should be more tightly controlled to reduce health risks in case of mixed contamination. This study provides new insights into soil contamination management and contributes to developing more effective contamination control strategies for co-contaminated soils.
在中国，土壤镉（Cd）和砷（As）的复合污染是最严重的复合污染形式之一。关于Cd和As从复合污染土壤向作物转移的模拟研究尚未充分开展。本研究选取了5种理化性质差异显著的土壤，通过外源添加Cd和As来模拟复合污染状况，并深入研究了这两种元素的生物累积和转运行为。该研究采用机器学习方法和逐步线性回归，建立了花生植株中Cd和As积累的预测模型。然后根据食品质量标准推导了土壤中Cd和As的安全阈值。结果表明，花生对Cd的积累能力显著高于As，Cd的生物富集系数（BCFs）为0.77至36.55，As的生物富集系数为0.006至0.449。Cd主要转运到花生地上部并在地上部积累，而As主要积累在根部。与单一Cd污染相比，As的存在使根部、地上部、果壳和果仁中的Cd浓度分别增加了87.5%、71.3%、120.2%和48.9%。相反，Cd的存在使根部、果壳和果仁中的As含量分别降低了38.3%、45.5%和38.1%。利用XGBoost和逐步线性回归模型，确定了影响植物中Cd和As积累的关键因素。此外，还建立了相应的回归预测方程，该方程解释了花生各部位金属积累方差的0.66以上。我们推导的土壤安全阈值表明，在混合污染情况下，应更严格地控制污染物浓度，以降低健康风险。本研究为土壤污染管理提供了新的见解，并有助于制定更有效的复合污染土壤控制策略。
