Abstract
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 the Life Cycle Assessment (LCA), normalized results can be obtained using internal and external approaches. The latter requires normalization factors gathered within a precise spatial context (e.g., a country), and this data usually originates from environmentally aware nations. However, several countries, such as Brazil, lack this sort of data; therefore, it is more difficult to apply representative external normalization factors. Alternatively, one may apply an internal normalization approach since the analysis of the data is specific to individual assessments, thus simplifying LCA in “non-normalized” countries. Since there are many internal procedures and the literature lacks discussions on how they perform in LCA contexts, 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, we performed exploratory research aiming to compare eight procedures of internal normalization through a Monte Carlo Simulation using artificial data. Results indicate that 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. On the other hand, the least influential procedures on the final ranking of alternatives were Vector Normalization and Simple Normalization using the maximum value as a reference.
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Data and material are available upon request.
Notes
Simple Normalization: 1. Using the maximum value as a reference—SNm; 2. Using the sum as a reference—SNs; 3. Using a baseline—SNb; 4. Linear Normalization—LN; 5. Vector Normalization—VN; 6. Z-Score Normalization—ZN; 7. Sigmoid Normalization—SgN; 8. Decimal Scaling Normalization—DN.
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Acknowledgements
The authors would like to thank Dr. Vamilson Prudêncio da Silva Júnior for his technical support in develo** the simulation tool used in this paper.
Funding
This study was funded by the Brazilian education and research agencies “Coordination for the Improvement of Higher Education Personnel (CAPES)” and the “National Council for Scientific and Technological Development (CNPq).”
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Highlights
• In LCA, the procedure of internal normalization is recommended whenever countries lack external normalization factors.
• Different internal normalization procedures are tested and compared through simulations in an exploratory study.
• Internal normalization procedures provide good performance for Multi-Criteria Analysis towards the best alternative.
• Vector Normalization and Simple (maximum value) Normalization procedures influence the ranking of alternatives the least.
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Sousa, S.R., Soares, S.R., Moreira, N.G. et al. Internal Normalization Procedures in the Context of LCA: A Simulation-Based Comparative Analysis. Environ Model Assess 26, 271–281 (2021). https://doi.org/10.1007/s10666-021-09767-5
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DOI: https://doi.org/10.1007/s10666-021-09767-5