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Microplastics (MPs) are emerging contaminants of global concern, posing a potential and serious threat to ecosystems and human health due to their small size, ease of migration, and slow degradation. MPs pollution control is urgently needed. Artificial intelligence (AI) is becoming increasingly integral to MPs pollution management, leveraging its superior data processing, pattern recognition, and predictive power. This paper presents a comprehensive review of recent advances in AI applications across the MPs management lifecycle, including collection and detection, source apportionment, impact assessment, and strategic intervention. The AI models utilized in each phase are comparatively evaluated, with a focus on their accuracy and limitations. This paper critically examines the extant challenges and outlines prospective development pathways, ultimately aiming to facilitate more informed and effective strategies for the scientific and intelligent management of MPs pollution.

, authors=Zheng-dong PENG¹, Dong-sheng SHEN¹, Yin-yin XU², Yu-yang LONG¹, Xiao-hui SUN², Fo-quan GU^{1, *}, authorsList=Zheng-dong PENG, Dong-sheng SHEN, Yin-yin XU, Yu-yang LONG, Xiao-hui SUN, Fo-quan GU, authorCompany=null, correspAuthors=Fo-quan GU, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1314922088708792953, articleId=1314922088184504951, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=AI在微塑料污染治理领域的应用与挑战, columnId=1240689621210820752, journalTitle=中国环境科学, columnName=新污染物, runingTitle=null, highlight=null, articleAbstract=

微塑料（MPs）是全球广泛关注的新污染物，因其体积小、易迁移、难降解等特性，对生态系统和人类健康构成潜在且严重的威胁，MPs污染治理迫在眉睫．人工智能（AI）凭借其强大的数据处理、模式识别和预测能力，在MPs污染治理领域展现出日益重要的作用．本文综述了近年来AI技术在MPs收集与检测、污染源追踪、环境影响预测、治理策略优化等MPs污染治理环节的研究进展．重点对比分析了各环节所用的AI模型及其准确性，并深入探讨了当前面临的挑战以及未来的发展方向，旨在为推动MPs污染治理的科学化和智能化提供参考借鉴．

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彭政栋（2003-），男，浙江温州人，浙江工商大学硕士研究生，主要从事固体废物资源化与无害化研究．发表论文4篇．23020160015@pop.zjgsu.edu.cn

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彭政栋（2003-），男，浙江温州人，浙江工商大学硕士研究生，主要从事固体废物资源化与无害化研究．发表论文4篇．23020160015@pop.zjgsu.edu.cn

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