Sustainable Process Integration Laboratory - SPIL, NETME Centre, Faculty of Mechanical Engineering, Brno University of Technology - VUT Brno, Technická 2896/2, 616 00 Brno, Czech Republic.
Sustainable Process Integration Laboratory - SPIL, NETME Centre, Faculty of Mechanical Engineering, Brno University of Technology - VUT Brno, Technická 2896/2, 616 00 Brno, Czech Republic.
Sci Total Environ. 2020 Jan 20;701:134652. doi: 10.1016/j.scitotenv.2019.134652. Epub 2019 Nov 1.
Municipal solid waste (MSW) is one of the issues associated with the growth of economic and urban population. The aim of this study is to develop an integrated design of waste management systems in support of a Circular Economy by P-graph (a bipartite graphical optimisation tool) as an effective decision support tool. The case study considers four MSW compositions based on different country income levels. Solving the P-graph model identifies the most suitable treatment approaches, considering the economic balance between the main operating cost, type, yield, quality of products, as well as the GHG emission (externality cost). The identification of near-optimal solutions by P-graph is useful in dealing with the trade-offs between conflicting objectives, e.g. local policy and practical implementation, that are difficult to monetise. For a lower-income country, the optimal solution includes a combination of at source separation, recycling, incineration (heat, electricity), anaerobic digestion (biofuel, digestate) and the landfill. It avoids an estimated 411 kg CO/t of processed MSW and achieves a potential profit of 42 €/t of processed MSW. The optimisation generally favours mechanical biological treatment as the country income level rises, which affects the composition of the MSW. The relative prices of biofuel, electricity and heat (>20%) cause a significant impact on the highest-ranking treatment structure and overall profit. This study shows that the developed framework by P-graph is an effective tool for MSW systems planning. For future study, localised data inputs can be fed into the proposed framework for a customised solution and economic feasibility assessment.
城市固体废物（MSW）是与经济和城市人口增长相关的问题之一。本研究旨在通过 P 图（一种双边图形优化工具）开发支持循环经济的废物管理系统的综合设计，作为一种有效的决策支持工具。该案例研究考虑了基于不同国家收入水平的四种 MSW 成分。通过求解 P 图模型，可以确定最合适的处理方法，考虑主要运营成本、类型、产量、产品质量以及温室气体排放（外部性成本）之间的经济平衡。P 图确定的近最优解决方案有助于处理相互冲突的目标之间的权衡，例如难以货币化的地方政策和实际实施。对于低收入国家，最佳解决方案包括源头分类、回收、焚烧（热能、电能）、厌氧消化（生物燃料、消化物）和垃圾填埋场的组合。它避免了估计为 411kg CO/t 加工后的 MSW，并实现了 42 欧元/t 加工后的 MSW 的潜在利润。随着国家收入水平的提高，优化通常有利于机械生物处理，这会影响 MSW 的组成。生物燃料、电力和热能的相对价格（>20%）对排名最高的处理结构和整体利润产生重大影响。本研究表明，P 图开发的框架是 MSW 系统规划的有效工具。对于未来的研究，可以将本地化的数据输入到拟议的框架中，以进行定制解决方案和经济可行性评估。
