Designing Hybrid Life Cycle Assessment Models based on Uncertainty and Complexity

Published: 19-10-2020| Version 1 | DOI: 10.17632/kjzzk5v932.1
Tapajyoti Ghosh


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.


Steps to reproduce

Provided in the readme file.