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Enviroscore: normalization, weighting, and categorization algorithm to evaluate the relative environmental impact of food and drink products

A 5-scale label that relativizes the environmental impact of a given product referred to the impact of the European food basket is proposed. It was developed based on the Product Environmental Footprint methodology with the following stepwise approach. First, a set of normalization and weighting fac...

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Autores principales: Ramos, Saioa, Segovia, Lucia, Melado-Herreros, Angela, Cidad, Maite, Zufía, Jaime, Vranken, Liesbet, Matthys, Christophe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9700787/
https://www.ncbi.nlm.nih.gov/pubmed/36433991
http://dx.doi.org/10.1038/s41538-022-00165-z
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author Ramos, Saioa
Segovia, Lucia
Melado-Herreros, Angela
Cidad, Maite
Zufía, Jaime
Vranken, Liesbet
Matthys, Christophe
author_facet Ramos, Saioa
Segovia, Lucia
Melado-Herreros, Angela
Cidad, Maite
Zufía, Jaime
Vranken, Liesbet
Matthys, Christophe
author_sort Ramos, Saioa
collection PubMed
description A 5-scale label that relativizes the environmental impact of a given product referred to the impact of the European food basket is proposed. It was developed based on the Product Environmental Footprint methodology with the following stepwise approach. First, a set of normalization and weighting factors were defined to aggregate all the environmental impact categories into a single dimensionless index referred to as the European food basket, coined the European Food Environmental Footprint Single Index (EFSI). Next, the effectiveness of the EFSI index was evaluated by assessing the distribution of the EFSI results on 149 hypothetical food items and comparing it with the results obtained with EC Single Score. Finally, the thresholds to translate the EFSI index into the 5-scale Enviroscore (A, B, C, D, and E) were established and validated using the Delphi method. Results indicated that both, Enviroscore and EFSI, were able to account for impact variability between and within food products. Differences on the final score were observed due to the type of products (vegetables vs. animal products), the country of origin and the mean of transportation. Regarding country of origin, results indicated that differences in water stress impact category were better captured by the EFSI index (r = 0.624) than by the EC Single Score (r = 0.228). Finally, good agreement achieved with the Delphi method (weighted Kappa 0.642; p = 0.0025), ensures the acceptability of the Enviroscore. In conclusion, this study developed a method to communicate environmental impact assessment in a front-of-packaging label.
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spelling pubmed-97007872022-11-27 Enviroscore: normalization, weighting, and categorization algorithm to evaluate the relative environmental impact of food and drink products Ramos, Saioa Segovia, Lucia Melado-Herreros, Angela Cidad, Maite Zufía, Jaime Vranken, Liesbet Matthys, Christophe NPJ Sci Food Article A 5-scale label that relativizes the environmental impact of a given product referred to the impact of the European food basket is proposed. It was developed based on the Product Environmental Footprint methodology with the following stepwise approach. First, a set of normalization and weighting factors were defined to aggregate all the environmental impact categories into a single dimensionless index referred to as the European food basket, coined the European Food Environmental Footprint Single Index (EFSI). Next, the effectiveness of the EFSI index was evaluated by assessing the distribution of the EFSI results on 149 hypothetical food items and comparing it with the results obtained with EC Single Score. Finally, the thresholds to translate the EFSI index into the 5-scale Enviroscore (A, B, C, D, and E) were established and validated using the Delphi method. Results indicated that both, Enviroscore and EFSI, were able to account for impact variability between and within food products. Differences on the final score were observed due to the type of products (vegetables vs. animal products), the country of origin and the mean of transportation. Regarding country of origin, results indicated that differences in water stress impact category were better captured by the EFSI index (r = 0.624) than by the EC Single Score (r = 0.228). Finally, good agreement achieved with the Delphi method (weighted Kappa 0.642; p = 0.0025), ensures the acceptability of the Enviroscore. In conclusion, this study developed a method to communicate environmental impact assessment in a front-of-packaging label. Nature Publishing Group UK 2022-11-24 /pmc/articles/PMC9700787/ /pubmed/36433991 http://dx.doi.org/10.1038/s41538-022-00165-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Ramos, Saioa
Segovia, Lucia
Melado-Herreros, Angela
Cidad, Maite
Zufía, Jaime
Vranken, Liesbet
Matthys, Christophe
Enviroscore: normalization, weighting, and categorization algorithm to evaluate the relative environmental impact of food and drink products
title Enviroscore: normalization, weighting, and categorization algorithm to evaluate the relative environmental impact of food and drink products
title_full Enviroscore: normalization, weighting, and categorization algorithm to evaluate the relative environmental impact of food and drink products
title_fullStr Enviroscore: normalization, weighting, and categorization algorithm to evaluate the relative environmental impact of food and drink products
title_full_unstemmed Enviroscore: normalization, weighting, and categorization algorithm to evaluate the relative environmental impact of food and drink products
title_short Enviroscore: normalization, weighting, and categorization algorithm to evaluate the relative environmental impact of food and drink products
title_sort enviroscore: normalization, weighting, and categorization algorithm to evaluate the relative environmental impact of food and drink products
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9700787/
https://www.ncbi.nlm.nih.gov/pubmed/36433991
http://dx.doi.org/10.1038/s41538-022-00165-z
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