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At the local scale, interconnected production, consumption, waste management, and other man-made technological components interact with local ecosystem components to form a local production system. The purpose of this work is to develop a framework for the conceptual characterization and mathematical modeling of a local production system to support the assessment of process and component options that potentially create symbiosis between industry and ecosystem. This framework has been applied to a case study to assess options for the establishment of a local energy production system that involves a heathland ecosystem, bioenergy production, and wastewater treatment. We found that the framework is useful to analyze the two-way interactions between these components in order to obtain insight into the behavior and performance of the bioenergy production system. In particular, the framework enables exploring the levels of the ecosystem states that allow continuous provisioning of resources in order to establish a sustainable techno-ecological system

Society currently relies heavily on centralized production and large scale distribution infrastructures to meet growing demands for goods and services, which causes socioeconomic and environmental issues, particularly unsustainable resource supply. Considering local production systems as a more sustainable alternative, this paper presents an insight-based approach to the integrated design of local systems providing food, energy, and water to meet local demands. The approach offers a new hierarchical and iterative decision and analysis procedure incorporating design principles and ability to examine design decisions, in both synthesis of individual yet interconnected subsystems and integrated design of resource reuse across the entire system. The approach was applied to a case study on design of food-energy-water system for a locale in the U.K.; resulting in a design which significantly reduced resource consumption compared to importing goods from centralized production. The design process produced insights into the impact of one decision on other parts of the problem, either within or across different subsystems. The result was also compared to the mathematical programming approach for whole system optimization from previous work. It was demonstrated that the new approach could produce a comparable design while offering more valuable insights for decision makers.