Models for Decarbonization in the Chemical Industry

Yao, Y., Lan, K., Graedel, T.E., & Rao, N. ORCID: https://orcid.org/0000-0003-1888-5292 (2024). Models for Decarbonization in the Chemical Industry. Annual Review of Chemical and Biomolecular Engineering 15 (1) 10.1146/annurev-chembioeng-100522-114115.

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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.

['eprint_fieldname_type' not defined]:	['eprint_typename_article' not defined]
Research Programs:	Energy, Climate, and Environment (ECE)['lib/metafield:join_subject' not defined]Energy, Climate, and Environment (ECE)['lib/metafield:join_subject_parts' not defined]Transformative Institutional and Social Solutions (TISS)
['eprint_fieldname_userid' not defined]:	Luke Kirwan
Date Deposited:	26 ['lib/utils:month_short_01' not defined] 2024 12:40
['eprint_fieldname_lastmod' not defined]:	07 ['lib/utils:month_short_10' not defined] 2024 14:06
URI:	https://pure.iiasa.ac.at/19433

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