Environomic multi-objective optimization of an eco-industrial park

A circular economy refers to an industrial economy with a cradle to cradle vision, shifting from the use of fossil fuels towards renewable energy, minimizing the use of toxic chemicals and reducing waste by recycling through careful system design. The concept of a circular economy is based on the study of non-linear, in particular living systems, with a major outcome being the optimisation of systems rather than of the individual components which make up each system. Industrial symbiosis (IS) is the exchange of energy, waste and by-products among industries in order to add value, while reducing costs and environmental impacts. This is consistent with the principles of a circular economy, and is a stepping stone towards the design of sustainable economies and policies. In the scope of this study, the use of local and renewable resources and the development of industrial ecology can contribute to the decrease of environmental impacts of a living, interactive system, on a given territory. A process system design framework is developped to model a superstructure that contains the list of possible options for the system. The LCA is used to calculate the environmental impacts of a product or a service. The method requires certain adjustments in order to assess the impacts of a spatially delimited system. The design of such system can be done by combining Life Cycle Assessment (LCA) that can provide a clear and structured framework to assess the environmental impacts of the system and process system design methods that applies mathematical programing techniques to systematically design territorial configurations using costs and thermo-chemical or physical models. The new method allows to generate the most attractive scenarios for the systems using a systematic modeling framework and using an optimisation approach that allows to generate a limited set of pareto optimal configurations that can then be evaluated to identify the most attractive solution. The method has been successsfully applied on a case study of a city with 100,000 inhabitants.