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<p>Plastic pollution has emerged as a critical global environmental challenge due to the persistence, chemical complexity and resistance of synthetic polymers to natural degradation, resulting in the widespread accumulation of micro- and nanoplastics across terrestrial and aquatic ecosystems. Conventional plastic management approaches, including landfilling, incineration and physicochemical treatments, remain limited due to high energy demands, economic constraints and the generation of secondary pollutants. This review critically synthesizes current advances in microbial biodegradation, focusing on mechanistic pathways encompassing abiotic pretreatment, enzymatic depolymerization and microbial assimilation. It further emphasizes the use of artificial intelligence (AI) in the microbial degradation pathways providing a novel perspective that bridges experimental microbiology with data-driven enzyme discovery and process optimization. AI-based tools are critically evaluated for their ability to predict enzyme function, design microbial consortia and optimize degradation pathways, while also addressing current limitations related to data quality, model interpretability and experimental validation. Furthermore, this review identifies key research gaps, including the lack of standardized methodologies, limited scalability of laboratory findings and insufficient techno-economic assessments. These interdisciplinary advancements contribute toward the practice of sustainable plastic waste management and align strongly with the goals of United Nations Sustainable Development Goals (SDGs), particularly, SDG 6 for clean water and sanitation, SDG 12 for responsible consumption and production of plastic polymers and SDG 13 for sustainable climate.</p>

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Plastic pollution and its global environmental impacts: a comprehensive review of microbial biodegradation mechanisms, plastic-degrading enzymes, emerging biotechnological strategies and artificial intelligence-driven approaches for sustainable plastic waste management

  • 期刊论文

  • 发表日期：

    2026年5月22日

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  • Rahel Debbarma,
  • Bibhab Kumar Lodh,
  • Tarun Kanti Bandyopadhyay,
  • Swarup Biswas,
  • Soma Nag

摘要

Plastic pollution has emerged as a critical global environmental challenge due to the persistence, chemical complexity and resistance of synthetic polymers to natural degradation, resulting in the widespread accumulation of micro- and nanoplastics across terrestrial and aquatic ecosystems. Conventional plastic management approaches, including landfilling, incineration and physicochemical treatments, remain limited due to high energy demands, economic constraints and the generation of secondary pollutants. This review critically synthesizes current advances in microbial biodegradation, focusing on mechanistic pathways encompassing abiotic pretreatment, enzymatic depolymerization and microbial assimilation. It further emphasizes the use of artificial intelligence (AI) in the microbial degradation pathways providing a novel perspective that bridges experimental microbiology with data-driven enzyme discovery and process optimization. AI-based tools are critically evaluated for their ability to predict enzyme function, design microbial consortia and optimize degradation pathways, while also addressing current limitations related to data quality, model interpretability and experimental validation. Furthermore, this review identifies key research gaps, including the lack of standardized methodologies, limited scalability of laboratory findings and insufficient techno-economic assessments. These interdisciplinary advancements contribute toward the practice of sustainable plastic waste management and align strongly with the goals of United Nations Sustainable Development Goals (SDGs), particularly, SDG 6 for clean water and sanitation, SDG 12 for responsible consumption and production of plastic polymers and SDG 13 for sustainable climate.