CICLOG publishes a paper in the journal "Environmental Modeling & Assessment"

Normalization is a procedure used to convert absolute values of a system, generally expressed in different measurement scales, into normalized values, thus enabling comparison, ranking, and aggregation of attribute values. In the context of LCA, normalized results can be obtained using internal and external approaches.

There are many internal procedures, but the literature lacks discussions on how they perform in LCA contexts. Therefore, it might be challenging for decision-makers to select and apply them as Multiple Attribute Decision Making (MADM) methods.

In order to fill this research gap, Sabrina Sousa (former CICLOG Masters student), Roni Severis (currently a PhD Candidate at the lab), Dr. Sebastião Soares (CICLOG Coordinator), and other colleagues performed exploratory research aiming to compare eight procedures of internal normalization through a Monte Carlo Simulation using artificial data.

After successfully performing all methodological steps, results found by the authors indicated that all procedures of internal normalization generally present a good performance since they influence the choice of the preferable alternative in < 30% of the simulations. Additionally, only two internal normalization approaches have reduced ranking performance.

CICLOG keeps pushing on the boundaries of LCA knowledge.
Congratulations to Sabrina, Roni and Sebastião Soares for this great research!

More details? Access: https://doi.org/10.1007/s10666-021-09767-5.

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By Roni M Severis,
Florianópolis, April 21st, 2021.