Models for Decarbonization in the Chemical Industry

Yao, Y., Lan, K., Graedel, T.E., & Rao, N. ORCID: (2024). Models for Decarbonization in the Chemical Industry. Annual Review of Chemical and Biomolecular Engineering 15 (1) 10.1146/annurev-chembioeng-100522-114115. (In Press)

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Various technologies and strategies have been proposed to decarbonize the chemical industry. Assessing the decarbonization, environmental, and economic implications of these technologies and strategies is critical to identifying pathways to a more sustainable industrial future. This study reviews recent advancements and integration of systems analysis models, including process analysis, material flow analysis, life cycle assessment, techno-economic analysis, and machine learning. These models are categorized based on analytical methods and application scales (i.e., micro-, meso-, and macroscale) for promising decarbonization technologies (e.g., carbon capture, storage, and utilization, biomass feedstock, and electrification) and circular economy strategies. Incorporating forward-looking, data-driven approaches into existing models allows for optimizing complex industrial systems and assessing future impacts. Although advances in industrial ecology-, economic-, and planetary boundary-based modeling support a more holistic systems-level assessment, more effects are needed to consider impacts on ecosystems. Effective applications of these advanced, integrated models require cross-disciplinary collaborations across chemical engineering, industrial ecology, and economics.

Item Type: Article
Research Programs: Energy, Climate, and Environment (ECE)
Energy, Climate, and Environment (ECE) > Transformative Institutional and Social Solutions (TISS)
Depositing User: Luke Kirwan
Date Deposited: 26 Jan 2024 12:40
Last Modified: 26 Jan 2024 12:40

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