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Treffer: Advanced composting simulation technologies: A systematic review of methodological frameworks and applications.

Title:
Advanced composting simulation technologies: A systematic review of methodological frameworks and applications.
Authors:
Li MX; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, PR China., Wang N; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, PR China., Xie YY; Power China Zhongnan Engineering Corporation Limited, Changsha, 410014, PR China., Ye MY; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, PR China., Xi BD; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, PR China., Chen WM; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, PR China. Electronic address: 13920101810@163.com., Zhou Q; School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, 100083, PR China; Laboratory of Environmental Technology, INET, Tsinghua University, Beijing, 100084, PR China. Electronic address: zhouqi2019@pku.edu.cn., Hu JL; School of Mechanical Engineering, Beijing Institute of Petrochemical Technology, Beijing, 102617, PR China., Hou JQ; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, PR China.
Source:
Journal of environmental management [J Environ Manage] 2026 Jan 20; Vol. 399, pp. 128676. Date of Electronic Publication: 2026 Jan 20.
Publication Model:
Ahead of Print
Publication Type:
Journal Article; Review
Language:
English
Journal Info:
Publisher: Academic Press Country of Publication: England NLM ID: 0401664 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1095-8630 (Electronic) Linking ISSN: 03014797 NLM ISO Abbreviation: J Environ Manage Subsets: MEDLINE
Imprint Name(s):
Original Publication: London ; New York, Academic Press.
Contributed Indexing:
Keywords: CFD; Composting; Kinetic modeling; Machine learning; Simulation
Entry Date(s):
Date Created: 20260121 Latest Revision: 20260121
Update Code:
20260122
DOI:
10.1016/j.jenvman.2026.128676
PMID:
41564487
Database:
MEDLINE

Weitere Informationen

The conventional composting systems face technical limitations due to the complex substrates and nonlinear biochemical dynamics, resulting in unstable efficiency. The integration of computational approaches has advanced process simulation capabilities, creating novel opportunities for system optimization and performance enhancement. This study provides a comprehensive critical analysis of simulation methodologies applied to composting systems, with a focus on reaction kinetic modeling, multiphase computational fluid dynamics (CFD) simulations, and machine learning approaches. Unlike conventional reviews that adopt a singular perspective, this work not only examines the theoretical foundations and distinct advantages of each method, such as the mechanistic interpretability of mathematical models, the multi-physical field representation capability of CFD, and the data-driven modeling strengths of machine learning, but also clarifies the positioning and boundaries of each approach in terms of modeling logic, applicability, and interdisciplinary integration. Advancing these simulation technologies holds significant promise not only for process optimization but also for enhancing the environmental sustainability and resource efficiency of organic waste management, thereby contributing to broader circular economy objectives. Finally, we propose several promising research directions, including multi-physics coupled modeling that integrates biochemical and transport interactions, digital twin architectures enabling cyber-physical system integration, and a carbon emission accounting system aligned with carbon neutrality goals. This review will provide theoretical foundations for precision control in industrial-scale composting operations, bridging the gap between computational simulation and practical engineering implementation, thereby fostering the intelligent evolution of organic waste treatment.
(Copyright © 2026 Elsevier Ltd. All rights reserved.)

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.