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AI applications and challenges in addressing microplastic pollution
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Zheng-dong PENG1, Dong-sheng SHEN1, Yin-yin XU2, Yu-yang LONG1, Xiao-hui SUN2, Fo-quan GU1, *
China Environmental Science | 2026, 46(1) : 399 - 408
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China Environmental Science | 2026, 46(1): 399-408
• Emerging Contaminants •
AI applications and challenges in addressing microplastic pollution
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Zheng-dong PENG1, Dong-sheng SHEN1, Yin-yin XU2, Yu-yang LONG1, Xiao-hui SUN2, Fo-quan GU1, *
Affiliations
  • 1.Zhejiang Provincial Key Laboratory of Solid Waste Treatment and Recycling, Zhejiang Engineering Research Center of Non-ferrous Metal Waste Recycling, School of Environmental Science and Engineering, Zhejiang Gongshang University, Hangzhou 310012, China
  • 2.Ecological Environmental Monitoring Center of Zhejiang Province, Hangzhou 310012, China
Published: 2026-01-20
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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.

artificial intelligence  /  deep learning  /  MPs  /  model
彭政栋, 沈东升, 徐茵茵, 龙於洋, 孙晓慧, 古佛全. AI在微塑料污染治理领域的应用与挑战. 中国环境科学, 2026 , 46 (1) : 399 -408 .
Zheng-dong PENG, Dong-sheng SHEN, Yin-yin XU, Yu-yang LONG, Xiao-hui SUN, Fo-quan GU. AI applications and challenges in addressing microplastic pollution[J]. China Environmental Science, 2026 , 46 (1) : 399 -408 .
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Year 2026 volume 46 Issue 1
56
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  • Receive Date：2025-06-09
  • Online Date：2026-10-08
  • Published：2026-01-20
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  • Received：2025-06-09
Funding
Affiliations
    1.Zhejiang Provincial Key Laboratory of Solid Waste Treatment and Recycling, Zhejiang Engineering Research Center of Non-ferrous Metal Waste Recycling, School of Environmental Science and Engineering, Zhejiang Gongshang University, Hangzhou 310012, China
    2.Ecological Environmental Monitoring Center of Zhejiang Province, Hangzhou 310012, China
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Citations
表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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