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Predictive and estimation model of Cd, Ni, and Zn bioaccumulations in maize based on diffusive gradients in thin films

估计 材料科学 薄膜 环境科学 经济 纳米技术 管理
作者
Rui Chen,Xiulin Mu,Jiaxing Liu,Nuo Cheng,Rongguang Shi,Miaomiao Hu,Zhuoran Chen,Hao Wang
出处
期刊:Science of The Total Environment [Elsevier BV]
卷期号:860: 160523-160523 被引量:14
标识
DOI:10.1016/j.scitotenv.2022.160523
摘要

Consumption of maize contaminated with heavy metals such as cadmium, nickel, and zinc threaten human health. For situ measuring the bioavailability of heavy metals, the diffusive gradients in thin films (DGT) is superior to other traditional methods. It is also important to find a method for predicting heavy metal enrichment in maize based on the DGT method. In this study, field surveys were conducted in the main maize producing areas of Tianjin, China. Heavy metal concentrations in maize grains were predicted by coupling DGT with traditional extraction methods. The results show that coupling DGT with soil solution can significantly improve prediction accuracy (Cd-R2 = 0.908, Ni-R2 = 0.903, and Zn-R2 = 0.904). This indicated that DGT and soil solution were feasible predictors of heavy metal concentration in maize. The DGT induced fluxes in soil/sediment (DIFS) model was used to simulate the uptake process of heavy metals by DGT, and better reveal the desorption processes of heavy metals in soils. DIFS-based desorption processes were employed to characterize the resupply ability of heavy metals in soils. The coupling of DGT and DIFS parameters provided the best prediction accuracy in this study (Cd-R2 = 0.920, Ni-R2 = 0.928, and Zn-R2 = 0.908). Predictions are slightly weaker for Zn than for Cd and Ni (Cd-P < 0.01, Ni-P < 0.01, and Zn-P < 0.05). The reason is that the average resupply type of Cd and Ni in soil is partially sustained while Zn is resupplied via diffusion only. The desorption rate k-1 can excellently improve the prediction accuracy of DGT, which avoids the disadvantage that soil solution does not consider desorption. The coupling of DGT and DIFS parameters provides an accurate and reliable method for predicting heavy metal enrichment in maize.
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