Network science and Life Cycle Assessment
Network science studies systems made up of interconnected components. Components are represented as nodes and their relationships as links. Metrics such as degree and betweenness centrality can help identify highly connected components or those that play an important role in the movement of information and resources.
This perspective can complement Life Cycle Assessment (LCA), which also deals with complex systems of interdependent processes, products and flows.
Applications to LCA results
A network can represent relationships between processes and flows in a product system. Analysing these connections helps explore how processes relate to one another and identify relevant pathways. Sankey diagrams and other network visualisations can make relationships easier to interpret than tables alone.
Applications to life cycle inventories
Network science can also be applied to life cycle inventories (LCIs). Activities, products and flows can be represented as nodes connected through supply and use relationships. The resulting structure can help explore database connectivity, identify patterns and support data-quality analysis.
A network representation does not replace data assessment and does not, by itself, demonstrate the environmental relevance of a process. Results depend on how nodes and links are defined, the granularity of the data and the metrics selected.
Its main value is to offer another perspective on complex systems. Combining network analysis with LCA expertise can help practitioners identify patterns, develop hypotheses and better communicate the interdependencies embedded in models.