Urban biowaste integrated management based on synergy mechanism and multi-objective optimization: A case study in Suzhou, China

New multi-source waste co-incineration and clustering park operating model for small- and medium-sized city: A case study in China

With improvements in urban waste management to promote sustainable development, an increasing number of waste types need to be sorted and treated separately. Due to the relatively low amount of waste generated in small- and medium-sized cities, separate treatment facilities for each waste type lack scale, waste is treated at a high cost and low efficiency. Therefore, industrial symbiosis principles are suggested to be used to guide collaborative waste treatment system of multi-source solid wastes, and co-incineration is the most commonly used technology. Most existing studies have focused on co-incineration of one certain waste type (such as sludge or medical waste) with municipal solid waste (MSW), but the systematic design and the comprehensive benefits on a whole city and park level have not been widely studied. Taking the actual operation of a multi-source waste co-incineration park in south-central China as an example, this study conducted a detailed analysis of the waste-energy-water metabolism process of MSW, sludge, food waste, and medical waste co-incineration. The environmental and economic benefits were evaluated and compared with the single decentralized waste treatment mode. The results showed that the multi-source waste co-incineration and clustering park operating model was comprehensively superior to the single treatment mode, greenhouse gases and human toxicity indicators were decreased by 11.87% and 295.74%, respectively, and the internal rate of return of the project was increased by 29.35%. This mainly benefits from the synergy of technical system and the economies of scale. Finally, this research proposed policy suggestions from systematic planning and design, technical route selection, and an innovative management mode in view of the potential challenges.

Mathematical optimization of waste management systems: Methodological review and perspectives for application

The transition to a circular economy through sustainable waste management (WM) follows different paths in each region, depending on its socioeconomic conditions and existing infrastructure. Mathematical optimization models are rigorous tools for informing local decision-making and identifying WM policy levers based on a variety of configurations. This review explores the pathways taken when designing WM optimization models (WM-OMs) that establish a network of waste valorization technologies. To standardize the literature review process, we propose a novel characterization method for examining, relating, and benchmarking the features of WM-OMs. After a thorough review of 58 articles published between 2015 and 2022, we assembled a comprehensive database to document the characteristics of these papers and the type of data reported in their case studies. We aim to provide a solid foundation for streamlining and enhancing future WM-OMs. Our work identifies various opportunities to improve the accuracy and reliability of WM-OMs. They include modeling thermo-chemical reactions in WM processes; considering regulatory, environmental, and political constraints; recognizing the informal sector; exploring the impact of marketing mechanisms on waste prevention and recycling; improving the traceability of case study data; specifying the rationale for uncertainty analysis (UA); and indicating the mathematical model (type, optimization algorithm, and equations). As many WM-OM authors have implemented UA without justifying their method choices, our review provides a pioneering guide for selecting the UA approach. Finally, we discuss the need for a trade-off between performance and practicality as models become more complex, making it critical to consider the specific needs of stakeholders.

Application of q-rung orthopair fuzzy based SWARA-COPRAS model for municipal waste treatment technology selection

Despite several methods available for the treatment of solid wastes, the management of municipal solid waste is still a crucial and complex process. The available methods for waste treatment range from advanced to conventional techniques. The identification of a proper method for municipal solid waste management involves several techno-eco and environmental considerations. To solve the real-world problems of municipal waste management, the research proposed an integrated q-rung orthopair fuzzy number-based stepwise weight assessment ratio analysis-complex proportional assessment (SWARA-COPRAS) mathematical model to rank the waste treatment techniques. The research aimed to develop a systematic approach for a suitable selection of waste treatment methods. Ten (10) different alternatives for waste treatments were ranked against seven (07) different techno-eco and environmental criteria. The ambiguity in the decision was handled by the q-rung orthopair fuzzy numbers. The proposed integrated model has identified upcycling and recycling of waste having priority values of 100% and 99.9%, respectively, as the suitable practices for the successful management of generated solid wastes, whereas landfilling has obtained a minimum priority value of 66.782% and, therefore, is least preferable for waste management. The ranking of the alternatives followed the sequence as upcycling > recycling > pyrolysis > hydrolysis > biotechnological > core plasma pyrolysis > incineration > composting > gasification > landfilling. The comparison between the rankings of the proposed model with other techniques has revealed that the values of Spearman's rank correlation coefficient are in the range of 0.8545 to 0.9272; thereby, the robustness of the proposed model is verified. Sensitivity analysis for the criteria weight has showed that the ranking results are influenced significantly by the change in criteria weights and suggested that an accurate estimation of the criteria weight is decisive in determining the overall ranking of the alternative. The study has provided a framework for decision-making in the technology selection for solid waste management.