Collaborative Innovation Center for Advanced Nuclear Energy Technology, INET, Tsinghua University, Beijing 100084, China.
Collaborative Innovation Center for Advanced Nuclear Energy Technology, INET, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Radioactive Waste Treatment, INET, Tsinghua University, Beijing 100084, China.
J Hazard Mater. 2021 Jan 15;402:123709. doi: 10.1016/j.jhazmat.2020.123709. Epub 2020 Aug 19.
Microplastics pollution and their interaction with heavy metal ions have gained global concern. It is essential to develop models to predict the sorption capacity of heavy metal ions onto microplastics in global aquatic environments, and to connect the laboratory study results with the field measurement results. In this paper, the artificial neural networks (ANN) models were established based on literature data. for The results showed that the ANN model could predict the sorption capacity of heavy metal ions (including Cd, Pb, Cr, Cu, and Zn) onto microplastics in the global environments with high correlation coefficient (R) values (0.926∼0.994). The predicted sorption capacity was influenced by the initial concentration of heavy metal ions and the salinity in surrounding water. The predicted sorption capacity in rivers and lakes was higher than that in the ocean. Aged microplastics had higher affinity to heavy metal ions than virgin microplastics. The predicted sorption capacity of Cd, Pb, and Zn ions onto large microplastics (5 mm) was less than 0.12 μg/g. The predicted amount was in agreement with the field measurement results, suggesting that the laboratory studies can provide useful information for projecting the sorption capacity of heavy metal ions onto microplastics in global aquatic environments.
微塑料污染及其与重金属离子的相互作用引起了全球关注。开发模型来预测全球水生环境中重金属离子对微塑料的吸附能力，并将实验室研究结果与现场测量结果联系起来是至关重要的。本文基于文献数据建立了人工神经网络（ANN）模型。结果表明，ANN 模型可以用高相关系数（R）值（0.926∼0.994）预测重金属离子（包括 Cd、Pb、Cr、Cu 和 Zn）在全球环境中对微塑料的吸附能力。预测的吸附能力受重金属离子初始浓度和周围水盐度的影响。河流和湖泊中的预测吸附能力高于海洋。老化的微塑料对重金属离子的亲和力高于原始微塑料。Cd、Pb 和 Zn 离子对大微塑料（5mm）的预测吸附能力小于 0.12μg/g。预测的数量与现场测量结果一致，表明实验室研究可为预测全球水生环境中重金属离子对微塑料的吸附能力提供有用信息。
