- By:
- Davis, Maggie R; Conrad, Steve
- Page Number:
- 739-748
- Book Title:
- Augmented Intelligence in Systems Engineering and Engineered Systems: The Proceedings of the 2025 Conference on Systems Engineering Research
- Publication Date:
- August 20, 2026
- Publisher Location:
- Springer, Cham, Switzerland
- Conference Name:
- Conference on Systems Engineering Research (CSER)
- Conference Location:
- Los Angeles, California, United States of America
- Conference Sponsor:
- Stevens Institute of Technology and the University of Southern California
- View DOI Listing:
- https://doi.org/10.1007/978-3-032-12309-1_50
Abstract
The challenge addressed in this research centres on the need to choose between several biomass sources and energy production processes, while supporting rural economies and resilience of forest systems. A key barrier to effective decision-making for strategies using biomass is the lack of standardized and transparent life cycle assessment (LCA) baselines. These baselines are critical for assessing the impacts of biomass strategies but often vary due to regional factors and chosen simplifying assumptions of the LCAs. However, omitting key variables can mean the LCA omits key feedback and balancing loops relevant to fully assessing impacts of the change or test scenario. To address these complexities, this project employs a systems engineering approach: visual systems mapping. This technique is used to define the boundaries and dynamic behaviours of LCA baselines, enhancing transparency. By examining five literature sources and their documented baseline scenarios, the systems mapping case-studies demonstrates an approach to documenting and archiving these baselines. Recommendations are that visual systems mapping should be used to document key assumptions, such as baselines, of LCAs. Further, where possible open data repositories should hold key information about LCA baselines and reproducible workflows (e.g., using open-source tools) should be used to improve transparency and comparability in LCAs. Given the consensus within the broader scientific community on the importance of replicable data practices, this research reinforces the need for standardized frameworks and systems engineering tools in LCAs. This research demonstrates a pathway to more transparent, standardized, and comparable LCAs, that may bolster decisions for biomass systems.
