Designing Hybrid Life Cycle Assessment Models based on Uncertainty and Complexity

This dataset contains Matlab code for the case study example provided in the paper "Designing Life Cycle Assessment Models based on
Uncertainty and Complexity". This paper describes a framework for hybrid life cycle model generation by selecting activities
based on their importance, parametric uncertainty, and contribution to network complexity. The importance
of activities is determined by structural path analysis - which then guides the construction of life cycle models
based on uncertainty and complexity indicators. Information about uncertainty is from the available life cycle
inventory, complexity is quantified by cost or granularity. The life cycle model is developed in a hierarchical
manner by adding the most important activities until error requirements are satisfied or network complexity
exceeds user-specified constraints. The framework is applied to an illustrative example for building a hybrid LCA
model. Since this is a constructed example, the results can be compared with the actual impact, to validate
the approach. This application demonstrates how the algorithm sequentially develops a life cycle model of
acceptable uncertainty and network complexity.