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Life Cycle Inventory Availability: Status and Prospects for Leveraging New Technologies
Mark Mba Wright1, Eric C D Tan2, Qingshi Tu3
1Mechanical Engineering, Iowa State University, Ames, Iowa 50014, United States.
ACS Sustainable Chemistry & Engineering
|February 28, 2025
Summary
Life cycle assessment (LCA) data is crucial for sustainability. This study addresses challenges in life cycle inventory (LCI) databases and proposes using IoT, machine learning, and blockchain to improve data quality and accessibility.
Area of Science:
- Environmental Science
- Sustainability Studies
- Data Science
Background:
- Growing demand for Life Cycle Assessments (LCA) necessitates robust Life Cycle Inventory (LCI) data.
- Existing LCI databases face challenges in data gaps, transparency, and uncertainty.
Purpose of the Study:
- To summarize current challenges in LCI databases.
- To survey novel techniques for LCI data generation, dissemination, and validation.
- To propose future directions for LCI development.
Main Methods:
- Literature review and analysis of current LCI database challenges.
- Survey and discussion of emerging technologies for LCI data management.
- Proposal of future research and development pathways.
Main Results:
- Identified key data gaps, transparency issues, and uncertainty factors in current LCI databases.
- Highlighted novel techniques and technologies for LCI data improvement.
- Outlined future directions leveraging IoT, machine learning, and blockchain.
Conclusions:
- Advanced technologies like IoT, machine learning, and blockchain can significantly enhance LCI data quality and accessibility.
- Improved LCI data will facilitate more accurate and reliable LCA studies.
- Addressing current challenges is vital for advancing sustainability assessments.
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