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数据驱动的洞察力纳米材料对土壤过程的影响

Huiyi He¹, Yaping Lyu¹, Chen Cai¹

¹State Key Laboratory of Advanced Environmental Technology, Department of Environmental Science and Engineering, University of Science and Technology of China, Hefei 230026, China.

|February 23, 2026

概括

纳米材料 (NM) 影响土壤循环,影响化和脱. 机器学习模型将NM度确定为关键,土壤pH和NM大小不同地影响过程,有助于对生态风险进行评估.

科学领域:

环境科学环境科学
土壤科学土壤科学
生态毒理学生态毒理学

背景情况:

纳米材料 (NM) 的使用越来越多,引发了人们对其环境影响的担忧.
土壤循环对于生态系统健康至关重要,它涉及微生物介导的化和脱.
了解NM对这些过程的影响对于生态风险评估至关重要.

研究的目的:

通过元分析和机器学习 (ML) 来评估NMS对土壤化和脱的整体影响.
确定影响NM对循环过程影响的关键因素.
开发一个NM风险评估的预测性和可解释的ML框架.

主要方法:

进行元分析,综合现有关于NM效应的数据.
机器学习算法 (XGBoost,SVM,RF) 被训练来预测化和脱率的变化.
模型解释性技术 (全球和本地) 以确定关键驱动因素和相互作用.

主要成果:

XGBoost模型准确地预测了NM效应 (化R2=0.74,脱化R2=0.73).
在这两种过程中,NM度是主要的驱动因素.
土壤pH显著影响了化,而NM大小对化更为关键.
度,暴露时间和土壤纹理的相互作用影响是显著的.

结论:

建立了一个强大的和可解释的ML框架,用于预测NM对土壤循环的影响.
确定了NM对化和脱化影响的关键驱动因素.
该研究为土壤环境中纳米材料的生态风险评估提供了理论基础.

关键词:

环境风险评估环境风险评估功能交互分析功能交互分析机器学习机器学习纳米材料是一种纳米材料.气循环中的气循环

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