(361f) A Computational Platform for Assessing Organic Waste Management Strategies in the Food-Energy-Water Nexus
In the field of process systems engineering, many works have studied the design and optimization of supply chains of organic waste management. A generalized modeling network has been proposed to capture the fundamental elements in the supply chain . In addition, there are numerous case studies which focus on a specific spatial area and contain different types of biomass as basic feedstock, such as cow manure, wastewater sludge, and crop residues [6,7]. These case studies demonstrate how appropriate waste processing can achieve monetary savings and environmental improvement for communities, and how this information is valuable for different stakeholders and policy-makers. However, such types of work highly rely on dependable data inputs, especially in product conversion factors and product conversion costs. And for some cutting-edge technologies (e.g. struvite recovery, co-digestion of different feedstocks), it is difficult to get trustable data.
To provide best practices for integrating computational and experimental work in organic waste and nutrient management science, and to enhance stakeholder engagement, we have developed an easy-to-use computational platform. The platform has two modes: a demo mode and an expert mode. In the demo mode, we have included results and conclusions from several pre-solved cases to allow stakeholders to do parametric studies and observe how individual-level changes (e.g., investment on certain technologies) can impact the whole supply chain system. And in the expert mode, the stakeholders are able to define the scope of their own organic waste management problem using a graphic interface and upload their own data (e.g., product conversion factors for certain technologies). Some basic databases containing data from published literature, the technical support for modeling and solving the supply chain problem will be provided. The results visualization is also automated using a back-end GIS tool. The capability of this platform will be discussed, and a simple tutorial will be given.
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