Recent advances in plastic waste management: A systems-level framework for circular plastic economy strategies—A state-of-the-art review

Plastic waste accumulation represents a persistent environmental challenge driven by rapidly increasing polymer production, short product lifecycles, and insufficient end-of-life management. Although the circular economy emphasizes recyclability and material value retention, real-world plastic waste streams are highly heterogeneous, contaminated, and economically constrained, limiting the effectiveness of single-pathway solutions. This review synthesizes recent advances and provides a systems-level assessment of scalable plastic waste management strategies under circular economy constraints, evaluating mechanical, chemical, thermochemical, and biological treatment routes in terms of material circularity, scalability, environmental trade-offs, and deployment limits. Reported studies indicate that artificial intelligence (AI)-assisted sorting systems can achieve classification accuracies exceeding 90-98%, while optimized hybrid recycling and logistics strategies can improve material recovery efficiencies by approximately 20-50% under controlled implementation conditions. Particular attention is given to the conditional role of microbial and enzymatic degradation, where engineered enzymatic and microbial systems have demonstrated 20-60% improvements in degradation performance compared with conventional baseline processes, although these pathways remain unsuitable as universal circular solutions due to kinetic, material, and infrastructural constraints. AI is examined as a cross-cutting enabler that supports waste sorting, process optimization, life-cycle assessment, and decision-making under uncertainty, with fuzzy logic and hybrid AI frameworks highlighted for their robustness in nonlinear and data-scarce waste systems. By synthesizing technological, economic, and policy barriers, the review clarifies key trade-offs between recyclability and degradability and positions energy recovery and biodegradation as complementary, residual pathways within a hierarchy-driven circular economy. Priority research and implementation opportunities are identified, including hybrid bio-thermochemical processing, AI-assisted system integration, standardized performance metrics, and coordinated policy instruments. Overall, this comprehensive review provides a coherent framework for environmentally grounded, data-informed, and scalable plastic waste management, supporting the transition from fragmented approaches toward integrated circular plastic systems.

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Publication Details

Journal
Journal of Environmental Management
Published
2026-03-12
DOI
https://doi.org/10.1016/j.jenvman.2026.129282
Primary Topic
Microplastics and Plastic Pollution
Type
article
Field-Weighted Citation Impact
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article

Recent advances in plastic waste management: A systems-level framework for circular plastic economy strategies—A state-of-the-art review

Rania Al-Tohamy, Sameh S. Ali, Haixin Jiao, Jianzhong Sun et al.
Journal of Environmental Management
Microplastics and Plastic Pollution
article

Recent advances in plastic waste management: A systems-level framework for circular plastic economy strategies—A state-of-the-art review

Rania Al-Tohamy, Sameh S. Ali, Haixin Jiao, Jianzhong Sun, Min Xiong
article en

Abstract

Plastic waste accumulation represents a persistent environmental challenge driven by rapidly increasing polymer production, short product lifecycles, and insufficient end-of-life management. Although the circular economy emphasizes recyclability and material value retention, real-world plastic waste streams are highly heterogeneous, contaminated, and economically constrained, limiting the effectiveness of single-pathway solutions. This review synthesizes recent advances and provides a systems-level assessment of scalable plastic waste management strategies under circular economy constraints, evaluating mechanical, chemical, thermochemical, and biological treatment routes in terms of material circularity, scalability, environmental trade-offs, and deployment limits. Reported studies indicate that artificial intelligence (AI)-assisted sorting systems can achieve classification accuracies exceeding 90-98%, while optimized hybrid recycling and logistics strategies can improve material recovery efficiencies by approximately 20-50% under controlled implementation conditions. Particular attention is given to the conditional role of microbial and enzymatic degradation, where engineered enzymatic and microbial systems have demonstrated 20-60% improvements in degradation performance compared with conventional baseline processes, although these pathways remain unsuitable as universal circular solutions due to kinetic, material, and infrastructural constraints. AI is examined as a cross-cutting enabler that supports waste sorting, process optimization, life-cycle assessment, and decision-making under uncertainty, with fuzzy logic and hybrid AI frameworks highlighted for their robustness in nonlinear and data-scarce waste systems. By synthesizing technological, economic, and policy barriers, the review clarifies key trade-offs between recyclability and degradability and positions energy recovery and biodegradation as complementary, residual pathways within a hierarchy-driven circular economy. Priority research and implementation opportunities are identified, including hybrid bio-thermochemical processing, AI-assisted system integration, standardized performance metrics, and coordinated policy instruments. Overall, this comprehensive review provides a coherent framework for environmentally grounded, data-informed, and scalable plastic waste management, supporting the transition from fragmented approaches toward integrated circular plastic systems.

Journal of Environmental ManagementVol. 404
Jiangsu University (CN), Tanta University (EG), Yancheng Institute of Technology (CN)
Responsible consumption and production
Openalex Percentile: Top 28%
Microplastics and Plastic Pollution
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