微塑料(MPs)具有吸附重金属(HMs)的潜力,导致水生和陆地环境的综合污染威胁。然而,由于MP/HM特性和实验条件的复杂性,关于HMs在MPs上吸附的研究通常会产生不一致的发现。为了解决这个问题,我们在机器学习的辅助下进行了全面的荟萃分析,分析了一个数据集,该数据集包括来自134个参考文献的3340条记录.结果表明,聚酰胺(PA)(ES=-1.26)对常用的HMs(如Pb,Cd,Cu,和Cr),这主要归因于C=O和N-H基团的存在。相比之下,聚氯乙烯(PVC)表现出较低的吸附能力,但其表面的卤素原子产生的吸附强度最强。就HMs而言,与类金属和金属氧阴离子相比,金属阳离子更容易被MPs吸附,Pb(ES=-0.78)表现出最显著的吸附。随着pH值和温度的升高,HMs的吸附最初增加,随后减少。使用随机森林模型,我们根据MP/HM的性质和实验条件准确地预测了MP的吸附容量。影响HM在MPs上吸附的主要因素是HM和MP浓度,MP的比表面积,和pH。此外,表面络合和静电相互作用是Pb和Cd吸附的主要机制,表面官能团是影响MPs机制的主要因素。这些发现提供了MPs和HMs之间相互作用的定量总结,有助于我们理解与其相关性相关的环境行为和生态风险。
Microplastics (MPs) have the potential to adsorb heavy metals (HMs), resulting in a combined pollution threat in aquatic and terrestrial environments. However, due to the complexity of MP/HM properties and experimental conditions, research on the adsorption of HMs onto MPs often yields inconsistent findings. To address this issue, we conducted a comprehensive meta-analysis assisted with machine learning by analyzing a dataset comprising 3340 records from 134 references. The results indicated that polyamide (PA) (ES = -1.26) exhibited the highest adsorption capacity for commonly studied HMs (such as Pb, Cd, Cu, and Cr), which can be primarily attributed to the presence of C=O and N-H groups. In contrast, polyvinyl chloride (PVC) demonstrated a lower adsorption capacity, but the strongest adsorption strength resulting from the halogen atom on its surface. In terms of HMs, metal cations were more readily adsorbed by MPs compared with metalloids and metal oxyanions, with Pb (ES = -0.78) exhibiting the most significant adsorption. As the pH and temperature increased, the adsorption of HMs initially increased and subsequently decreased. Using a random forest model, we accurately predicted the adsorption capacity of MPs based on MP/HM properties and experimental conditions. The main factors affecting HM adsorption onto MPs were HM and MP concentrations, specific surface area of MP, and pH. Additionally, surface complexation and electrostatic interaction were the predominant mechanisms in the adsorption of Pb and Cd, with surface functional groups being the primary factors affecting the mechanism of MPs. These findings provide a quantitative summary of the interactions between MPs and HMs, contributing to our understanding of the environmental behavior and ecological risks associated with their correlation.