Artie McFerrin Department of Chemical Engineering, Texas A&M University, Jack E. Brown Chemical Engineering Building, 3122 TAMU, 100 Spence St., College Station, TX 77843, United States; Texas A&M Energy Institute, Texas A&M University, 1617 Research Pkwy, College Station, TX 77843, United States.
Texas A&M Energy Institute, Texas A&M University, 1617 Research Pkwy, College Station, TX 77843, United States.
Sci Total Environ. 2021 Nov 10;794:148726. doi: 10.1016/j.scitotenv.2021.148726. Epub 2021 Jun 29.
The current linear "take-make-waste-extractive" model leads to the depletion of natural resources and environmental degradation. Circular Economy (CE) aims to address these impacts by building supply chains that are restorative, regenerative, and environmentally benign. This can be achieved through the re-utilization of products and materials, the extensive usage of renewable energy sources, and ultimately by closing any open material loops. Such a transition towards environmental, economic and social advancements requires analytical tools for quantitative evaluation of the alternative pathways. Here, we present a novel CE system engineering framework and decision-making tool for the modeling and optimization of food supply chains. First, the alternative pathways for the production of the desired product and the valorization of wastes and by-products are identified. Then, a Resource-Task-Network representation that captures all these pathways is utilized, based on which a mixed-integer linear programming model is developed. This approach allows the holistic modeling and optimization of the entire food supply chain, taking into account any of its special characteristics, potential constraints as well as different objectives. Considering that typically CE introduces multiple, often conflicting objectives, we deploy here a multi-objective optimization strategy for trade-off analysis. A representative case study for the supply chain of coffee is discussed, illustrating the steps and the applicability of the framework. Single and multi-objective optimization formulations under five different coffee-product demand scenarios are presented. The production of instant coffee as the only final product is shown to be the least energy and environmental efficient scenario. On the contrary, the production solely of whole beans sets a hypothetical upper bound on the optimal energy and environmental utilization. In both problems presented, the amount of energy generated is significant due to the utilization of waste generated for the production of excess energy.
当前线性的“开采-制造-废弃-消耗型”模式导致了自然资源的枯竭和环境恶化。循环经济（Circular Economy，CE）旨在通过构建具有修复性、再生性和环境友好性的供应链来解决这些问题。这可以通过产品和材料的再利用、可再生能源的广泛使用以及最终通过关闭任何开放的物质循环来实现。向环境、经济和社会进步的这种转变需要分析工具来定量评估替代途径。在这里，我们提出了一种新的循环经济系统工程框架和决策工具，用于建模和优化食品供应链。首先，确定了生产所需产品和废物及副产品增值的替代途径。然后，利用基于资源-任务-网络（Resource-Task-Network）的表示方法来捕捉所有这些途径，在此基础上开发了一个混合整数线性规划模型。该方法允许对整个食品供应链进行全面建模和优化，考虑到其任何特殊特性、潜在约束以及不同的目标。考虑到通常 CE 会引入多个、常常相互冲突的目标，我们在这里部署了一种多目标优化策略来进行权衡分析。讨论了咖啡供应链的一个代表性案例研究，说明了该框架的步骤和适用性。提出了在五种不同的咖啡产品需求情景下的单目标和多目标优化公式。仅生产速溶咖啡作为唯一最终产品的方案被证明是能源和环境效率最低的方案。相反，仅生产整个咖啡豆设定了最佳能源和环境利用的假设上限。在所提出的两个问题中，由于利用了生产过剩能源所产生的废物来产生能量，因此产生的能量数量是显著的。
