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Sustainable transition to low carbon and zero waste economy requires a macroscopic evaluation of opportunities and impact of adopting emerging technologies in a region. However, a full assessment of current physical flows and wastes is a tedious task, thus leading to lack of comprehensive assessment before scale up and adoption of emerging technologies. Utilizing the mechanistic models developed for engineering and biological systems with macroeconomic framework of Input-Output models, we propose a novel integrated approach to fully map the physical economy, that automates the process of mapping industrial flows and wastes in a region. The approach is demonstrated by mapping the agro-based physical economy of the state of Illinois, USA by using mechanistic models for 10 sectors, which have high impact on waste generation. Each model mechanistically simulates the material transformation processes in the economic sector and provides the material flow information for mapping. The model for physical economy developed in the form of a Physical Input-Output Table (PIOT) captures the interindustry physical interactions in the region and waste flows, thus providing insights into the opportunities to implement circular economy strategies i.e., adoption of recycling technologies at large scale. In Illinois, adoption of technologies for industrial waste-water & hog manuremore »recycling will have the highest impact by reducing > 62 % of hog industry waste, > 99 % of soybean hull waste, and > 96 % of dry corn milling (corn ethanol production) waste reduction. Small % reduction in fertilizer manufacturing waste was also observed. The physical economy model revealed that Urea sector had the highest material use of 5.52E+08 tons and green bean farming with lowest material use of 1.30E+05 tons for the year modeled (2018). The mechanistic modeling also allowed to capture elemental flows across the physical economy with Urea sector using 8.25E+07 tons of carbon per operation-year (highest) and bean farming using 3.90E+04 tons of elemental carbon per operation-year (least). The approach proposed here establishes a connection between engineering and physical economy modeling community for standardizing the mapping of physical economy that can provide insights for successfully transitioning to a low carbon and zero waste circular economy.« less

Life Cycle Analysis (LCA) has long been utilized for decision making about the sustainability of products. LCA provides information about the total emissions generated for a given functional unit of a product, which is utilized by industries or consumers for comparing two products with regards to environmental performance. However, many existing LCAs utilize data that is representative of an average system with regards to life cycle stage, thus providing an aggregate picture. It has been shown that regional variation may lead to large variation in the environmental impacts of a product, specifically dealing with energy consumption, related emissions and resource consumptions. Hence, improving the reliability of LCA results for decision making with regards to environmental performance needs regional models to be incorporated for building a life cycle inventory that is representative of the origin of products from a certain region. In this work, we present the integration of regionalized data from process systems models and other sources to build regional LCA models and quantify the spatial variations per unit of biodiesel produced in the state of Indiana for environmental impact. In order to include regional variation, we have incorporated information about plant capacity for producing biodiesel from North and Centralmore »Indiana. The LCA model built is a cradle-to-gate. Once the region-specific models are built, the data were utilized in SimaPro to integrate with upstream processes to perform a life cycle impact assessment (LCIA). We report the results per liter of biodiesel from northern and central Indiana facilities in this work. The impact categories studied were global warming potential (kg CO2 eq) and freshwater eutrophication (kg P eq). While there were a lot of variations at individual county level, both regions had a similar global warming potential impact and the northern region had relatively lower eutrophication impacts.« less