Introduction
The planet is under unprecedented pressure. There is a growing body of evidence on how climate change, water scarcity, deforestation and pollution of ecosystems will compromise the capacity for nations to feed future generations1,2,3,4,5.
In this critical situation, food production and consumption have been reported as primary drivers of the human impact on the environment6. Food production accounts for 20 to 30% of the overall impact caused by human activities in the European Union7. In particular, food sector generates around 14 billion metric tons of carbon dioxide equivalents (CO2 eq) and it is responsible for the 26% of anthropogenic GHG emissions, 32% of global terrestrial acidification, and 78% of eutrophication8. Moreover, according to the Food and Agriculture Organization9, ~2.6 thousand km3 of water are consumed annually for agricultural purposes, 70% of the total water withdrawals.
Unlike other manufacturing sectors, food production is very heterogeneous in terms of efficiency, production practices, company size or seasonality1,10. Thus, the same final product could have different environmental performances depending on the origin or the production processes8. For instance, products with improvements in agricultural practices11, energy and water savings strategies12, food waste reduction13,14; or shorten distribution distances15 could significantly lower environmental degradation. Hence, a major change in the way food is currently produced and consumed is of tremendous importance to reduce environmental degradation and achieving Sustainable Development Goals (SDGs)16,17,18.
In this sense, Life Cycle Assessment (LCA)19 appears as a robust methodology for evaluating the overall environmental impact of a certain product or service and for identifying the potential environmental reduction due to the implementation of different environmental improvement strategies on manufacturing and supply-chain management20.
However, although assessing the life cycle of food products has been widely used for research or operational purposes, there are some limitations when communicating those results to final consumers:
- For instance, conventional approaches only communicate one environmental impact categories, being climate change usually communicated. Although studies concluded that carbon labeling could significantly reduce the carbon footprint of the food basket21,22,23, the benefit claimed may result in an undue transfer of impacts, ignoring the increase of other negative environmental impacts in the production chain.
- Other limitation with existing methods is that most of them focused on just one type of product. For example, in 201724 demonstrated the effectiveness of communicating carbon footprint of milk to change consumer attitude. However, product-specific labeling does not allow comparison between products and thus, has a limited effect on the pursued radical change of dietary patterns. For instance, when providing category specific thresholds, it may introduce the perception that a ‘sustainable beef’ is less harmful for the environment than an ‘unsustainable banana’ although with the former having higher impact in all environmental impact categories.
- Additionally, existing environmental impact information systems of food products lack a robust science-based method and have low scientific community support25 and are usually reduced to a self-declaration (ecolabel Type III) with limited application to the consumers market26. For instance, the recently developed Eco-Score27. Even though it is based on average impact characterization results calculated according to LCA methodology, it considers a bonus-malus point system depending on the origin or private certification standards, among others. Although the method is publicly available, it has not been peer-reviewed yet.
The mentioned limitations make results of LCA incomparable and increases confusion for consumers. For instance, only about half of European consumers trust producers’ claims about environmental performance28.
In order to deal with these weaknesses, additional research on developing normalizing and weighting for a range of environmental impact categories is required in order to obtaining a single index which could suggest unequivocal results29.
According to the standard on LCA19, normalization is defined as “calculating the magnitude of category indicator results relative to reference information” and weighting as “converting and possibly aggregating indicator results across impact categories using numerical factors based on value-choices”. On the one hand, normalization can be used to compare the results with a reference situation that is external to or independent from the case studies, which may facilitate the interpretation and communication of the impact results30. On the other hand, weighting can facilitate decision-making in situations where trade-offs between impact category results do not allow choosing one preferable solution among the alternatives. The weights applied are supposed to represent an evaluation of the relative importance of impacts, according to specific value choices, reflecting preferences of, e.g., people, experts, or organizations, e.g. regarding time (present versus future impacts), geography (local versus global), urgency, political agendas or cost31,32,33.
This is the case of the Single Score34 developed by the European Commission (EC) in the framework of the Product Environmental Footprint (PEF) methodology35, where a set of normalization and weighting factors were put forward to calculate an aggregated final punctuation. In this case, the reference framework for the normalization values is based on the environmental impact of all goods and services of the European Union, considering both food and non-food. Within this broad universe of commodities, the relative environmental impact of a given food product is not well reflected, due to the noise caused by other non-food commodities, hindering between and within food products’ benchmarking possibilities.
Therefore, the goal of the current study is to develop new normalization and weighting factors to create a single index capable to reflect the relative environmental impact of food and drink products. Additionally, to facilitate the interpretation of the results by non-experts, cut-off values have been defined to create a 5-scale score. The ultimate ambition is that both methods, the aggregated index, and the 5-scale score, should be capable to demonstrate the relative environmental impact of their food choices in order to motivate them towards more sustainable consumption patterns and, simultaneously, to entice agri-food business to reduce the generation of environmental impacts throughout the supply chain.
In the next sections, we outline how the index, and the score were developed. First, we developed normalization factors (NF) using the environmental impacts characterization of the European Food Basket as a reference situation. Based on these new NF, we identified most recent and suitable weighting factors to create the single index for the Environmental Footprint of European Food and Drink products (EFSI) (section Development of European Environmental Footprint Single Index for Food and Drink Products). Afterwards, we verified that the EFSI addressed the capability to capture variability between different food products and within products (section Relative validation of the European Food Environmental Footprint Single Index). Finally, we established and verified threshold values to translate the EFSI index into an easy-to-understand 5-scale score (section Development and validation of the threshold values).