生态与农村环境学报2025，Vol.41Issue(11)：1381-1392,12.DOI:10.19741/j.issn.1673-4831.2025.0427
土壤和地下水污染溯源技术进展及多技术集成框架探讨
Advances in Soil and Groundwater Pollution Source Tracking and a Multi-technology Integration Framework
摘要
Abstract
In recent years,accelerated industrialization and urbanization have intensified soil and groundwater contamina-tion,posing serious threats to environmental safety and public health.Accurate and efficient source-tracking technologies are therefore critical for effective remediation and responsibility attribution.Conventional tracing approaches,such as sta-tistical analyses,pollutant fingerprinting,and inverse transport modeling,typically rely on a single medium and a single method.Emerging techniques,including remote sensing,geophysical methods,and machine learning algorithms,have at-tracted growing attention,each offering distinct strengths and constraints for specific application scenarios.However,the complexity of pollution sources and the high heterogeneity of environmental media continue to hinder practical tracing ef-forts,which are often constrained by limited data resolution,high costs,and challenges in method integration.To address these challenges,this study proposes a high-precision,multi-technology integration framework for tracing soil and ground-water pollution sources.By reinforcing multi-source data fusion,the framework simultaneously lowers costs and enhances the precision of source apportionment,thereby improving the applicability and smart capabilities of source-tracking technol-ogies and providing robust technical support for soil and groundwater pollution prevention and control.关键词
溯源/受体模型/稳定同位素/遥感技术/机器学习/多技术集成Key words
source apportionment/receptor models/stable isotopes/remote sensing/machine learning/multi-technology integration分类
资源环境引用本文复制引用
王轶冬,王晓雪,侯德义..土壤和地下水污染溯源技术进展及多技术集成框架探讨[J].生态与农村环境学报,2025,41(11):1381-1392,12.基金项目
国家自然科学基金项目(42225703) （42225703）
