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地质风化和采矿影响下稻田土壤中的镉积累:空间分布模式、生物累积预测和安全土地利用。

Cadmium accumulation in paddy soils affected by geological weathering and mining: Spatial distribution patterns, bioaccumulation prediction, and safe land usage.

机构信息

Institute of Karst Geology, Chinese Academy of Geological Sciences, 50 Qixing Road, Guilin, Guangxi 541004, PR China.

School of Earth Sciences and Resources, China University of Geosciences, Beijing 100083, PR China.

出版信息

J Hazard Mater. 2023 Oct 15;460:132483. doi: 10.1016/j.jhazmat.2023.132483. Epub 2023 Sep 7.

Abstract

The abnormal enrichment of cadmium (Cd) in soil caused by rock weathering and mining activities is an issue in southern China. Although the soil Cd content in these regions is extremely high, the bioavailability of Cd in the soils differs significantly. The carbonate area (CBA) and tin-mining area (TIA) in Hezhou City were investigated to determine the primary features of soil Cd mobility in these regions and improve environmental management. Lateral and vertical spatial distributions revealed different accumulation and migration mechanisms of soil Cd in the CBA and TIA. Further analyses revealed that mining activities and geological weathering resulted in different soil geochemical parameters, thus yielding significantly lower levels of Cd in rice grains in the CBA than in the TIA. The random forest (RF) model predicted the bioaccumulation factor (BAF) (R = 0.69) better than the support vector machine (SVM) model (R = 0.68). Subsequently, a novel land management scheme was proposed based on soil Cd and the prediction of Cd in rice to optimize the spatial resources of agricultural land and ensure the safety of rice for consumption. This study provides a novel approach for land management in Cd-contaminated areas.

摘要

岩石风化和采矿活动导致的土壤中镉(Cd)的异常富集是中国南方的一个问题。尽管这些地区的土壤 Cd 含量极高,但土壤中 Cd 的生物有效性却有很大差异。本研究以贺州市碳酸盐区(CBA)和锡矿区(TIA)为研究对象,探讨了该地区土壤 Cd 迁移的主要特征,以期为环境管理提供参考。水平和垂直空间分布揭示了 CBA 和 TIA 中土壤 Cd 积累和迁移机制的不同。进一步分析表明,采矿活动和地质风化导致土壤地球化学参数存在差异,从而使得 CBA 地区水稻籽粒中的 Cd 含量明显低于 TIA 地区。随机森林(RF)模型预测生物累积因子(BAF)(R = 0.69)的效果优于支持向量机(SVM)模型(R = 0.68)。随后,根据土壤 Cd 含量和水稻 Cd 预测值,提出了一种新的土地管理方案,以优化农业土地的空间资源,确保食用大米的安全。本研究为 Cd 污染区的土地管理提供了一种新的方法。

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