Life cycle optimization oriented to sustainable waste management and circular economy : A review

Copyright © 2024 Elsevier Ltd. All rights reserved.

Bibliographische Detailangaben
Veröffentlicht in:Waste management (New York, N.Y.). - 1999. - 191(2025) vom: 01. Jan., Seite 89-106
1. Verfasser: Zhao, Dandan (VerfasserIn)
Weitere Verfasser: Chen, Yong, Yuan, Haoran, Chen, Dezhen
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2025
Zugriff auf das übergeordnete Werk:Waste management (New York, N.Y.)
Schlagworte:Journal Article Review Circular economy Life cycle optimization Life cycle sustainability analysis Multi-objective optimization Sustainable development Waste management Solid Waste
Beschreibung
Zusammenfassung:Copyright © 2024 Elsevier Ltd. All rights reserved.
Life cycle optimization (LCO) is an effective decision-making method combining life cycle assessment and optimization, which is capable of adjusting system configurations to meet specified sustainability goals. This study analyzed the status quo of LCO studies related to sustainable waste management and the circular economy. Most studies have focused on simultaneously optimizing environmental and economic objectives, whereas few have considered social impacts. Greenhouse gas emissions is the most commonly used environmental indicator in optimization, followed by the endpoint single-score indicator. A static deterministic model is often employed to formulate an LCO problem, while uncertainty and dynamic models are less frequently applied but cause concerns. To deal with multi-objective optimization, the ε-constraint method and non-dominated sorting genetic algorithm are popular. Waste LCO has been mainly applied to macro system planning, such as integrated municipal solid waste management systems, biowaste supply chains, waste-to-energy systems, and waste-to-resource networks, aiming to determine optimal waste allocation, facility capacity/location, technology choice, etc. It is occasionally used in optimizing process structure, operating conditions, blending ratio of feedstocks, and product development. Future research should focus on exploring the integration of more environmental and social indicators into multi-objective optimization, modeling under uncertainty, dynamic LCO, process and product optimization, and addressing the lack of multi-scale studies
Beschreibung:Date Completed 01.12.2024
Date Revised 05.12.2024
published: Print-Electronic
Citation Status MEDLINE
ISSN:1879-2456
DOI:10.1016/j.wasman.2024.11.001