ADVANCING SUSTAINABILITY ASSESSMENT TECHNIQUES: Mechanistic bottom-up approaches to map material and thermodynamic flows via Process Modeling, Input-Output theory, and Computational tools

For the first time in history, the world-wide material resource use by humanity has reached a record breaking 100 giga tons (gt) along with the release of 49.30 gt of greenhouse gases and 2.10 gt of solid waste (2017). Such large-scale increases in anthropogenic emissions and waste flows could mean reaching catastrophic global temperatures and ecosystem destruction in the near future. In order to better manage resource usage and implement strategies to reduce waste flows and natural resource use intensity, a comprehensive environmental flow accounting is required, which proves to be a challenging task to accomplish. Hence, the current work aims at advancing the current techniques and reducing the efforts to map environmental flows by developing automated mechanistic and bottom-up approaches for material, thermodynamic and economic flow accounting. An integrative flow accounting framework based on process modeling, Input-Output theory and advanced thermodynamic principles is developed here that complements the existing top-down and empirical approaches. The developed techniques are demonstrated via multiple environmental sustainability assessments at high spatial, temporal, and sectoral resolutions ranging from accounting flows at a single process level to multi-regional economy-wide flows. Finally, the framework of material flow accounting was automated by building a Python based tool called - Material Flow Data Extraction and Simulator (MFDES), to reduce the time lead times of constructing material flow maps. MFDES was also implemented on a collaborative cloud platform called PIOT-Hub that generates material flow maps in the form of Physical Input-Output Tables (PIOTs). The potential applications of this research include performing environmental impact assessments of single/multiple supply chains, developing circular economy strategies, quantifying effects of renewable energy expansion, and assessing different types of sustainability policy implications. Further, the cloud-based automated tools built in this work make it possible for researchers from different areas of expertise to synergistically collaborate on large scale projects for sustainable design of emerging processes and technologies.