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Industrial sectors such as urban centers, chemical companies, manufacturingfacilities, and microgrids are actively exploring strategies to help reducetheir carbon footprint. For instance, university campuses are complex urbandistricts (involving collections of buildings and utility systems) that areseeking to reduce carbon footprints that originate from diverse activities(e.g., transportation operations and production of heating, cooling, and powerutilities). This work presents an optimization framework to identify technologypathways that enable decarbonization of complex industrial sectors. Theframework uses a graph abstraction that compactly captures interdependenciesbetween diverse products and technologies as well as diverse externalities(e.g., market, policy, and carbon prices). Duality analysis reveals that theformulation can be interpreted as an economy, market, or value chain that usestechnologies to generate economic value (wealth) by transforming basic productsinto higher value products. This interpretation also reveals that theformulation identifies pathways that maximize the profit of stakeholders, helpsreveal the inherent value (prices) of intermediate products, and helps analyzethe impact of externalities and technology specifications on product values.Our developments are illustrated via a case study involving a prototypicaluniversity campus that seeks to identify pathways that reduce its carbonfootprint (e.g., via electrification and deployment of hydrogen technologies).We use the framework to determine carbon tax values, technology specifications,and investment budgets that activate different technology pathways and thatachieve different levels of decarbonization.

Graph-Based Optimization for Technology Pathway Analysis: A Case Study in Decarbonization of University Campuses