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Drugs, encompassing various chemical compounds from natural sources, lab synthesis, or genetic engineering, elicit different biological responses in living organisms. Some of these responses are desirable or therapeutic, while others are undesirable. The primary goal of administering a drug is to achieve a therapeutic effect, that is, to address a specific disease or health condition. Any concurrent effects outside of this therapeutic outcome are considered undesirable. These undesirable...
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Models for Decarbonization in the Chemical Industry.

Yuan Yao1,2, Kai Lan1, Thomas E Graedel1

  • 1Center for Industrial Ecology, Yale School of the Environment, Yale University, New Haven, Connecticut, USA;

Annual Review of Chemical and Biomolecular Engineering
|January 25, 2024
PubMed
Summary

This study reviews systems analysis models for decarbonizing the chemical industry, integrating technologies like carbon capture and biomass feedstock. Advanced models aid in optimizing sustainable industrial pathways.

Keywords:
chemical industryclimate changedecarbonization technologiesgreenhouse gas emissionsindustrial ecologymodeling

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Area of Science:

  • Industrial Chemistry and Engineering
  • Environmental Science and Sustainability
  • Systems Analysis and Modeling

Background:

  • The chemical industry faces significant pressure to decarbonize, necessitating evaluation of various technologies and strategies.
  • Assessing the environmental and economic implications of decarbonization is crucial for a sustainable industrial future.
  • Systems analysis models are key tools for evaluating these complex implications.

Purpose of the Study:

  • To review advancements and integration of systems analysis models for chemical industry decarbonization.
  • To categorize models by analytical methods and application scales for key decarbonization technologies and circular economy strategies.
  • To highlight the need for data-driven, holistic approaches and cross-disciplinary collaboration.

Main Methods:

  • Review of systems analysis models: process analysis, material flow analysis, life cycle assessment, techno-economic analysis, and machine learning.
  • Categorization of models based on analytical methods and scales (micro-, meso-, macroscale).
  • Integration of forward-looking, data-driven approaches into existing models.

Main Results:

  • Identification and categorization of models applicable to carbon capture, storage, and utilization (CCSU), biomass feedstock, and electrification.
  • Demonstration of how integrated models can optimize complex industrial systems and assess future impacts.
  • Recognition of advances in industrial ecology, economic, and planetary boundary-based modeling for holistic assessment.

Conclusions:

  • Advanced, integrated systems analysis models are essential for navigating chemical industry decarbonization pathways.
  • Further research is needed to incorporate ecosystem impacts into these holistic assessments.
  • Cross-disciplinary collaboration among chemical engineering, industrial ecology, and economics is vital for effective model application.