Norwegian Study Proposes Environmental Scoring Framework for Food

Researchers from the Norwegian research project NewTools have developed and evaluated a multi-indicator framework designed to score the environmental sustainability of food products. Published in Environmental and Sustainability Indicators in December 2026, the study presents a method tailored to Norwegian conditions that adapts the European Commission’s Environmental Footprint (EF) 3.1 methodology. The primary objective was to create a transparent, policy-relevant tool that aggregates complex life cycle assessment data into a simplified, five-level rating scale ranging from A to E. This approach aims to assist consumers, producers, and policymakers in making more sustainable choices by providing a clear and scientifically robust assessment of food products’ environmental impacts.

The framework addresses significant limitations in existing environmental scoring systems, which often struggle to balance scientific accuracy with user-friendliness. Current life cycle assessment tools provide detailed data across multiple impact categories, such as climate change, eutrophication, and biodiversity loss, but translating these results into single scores can obscure important nuances. The NewTools framework seeks to overcome this by selecting key impact categories that remain relevant and meaningful for food systems while reducing complexity. It is part of a broader multidimensional framework that also includes separate nutritional and social scoring systems, offering a comprehensive perspective on food sustainability from a Nordic viewpoint.

To ensure the framework’s relevance, the researchers conducted extensive stakeholder consultations involving representatives from academia, industry, government, and civil society. These discussions helped identify environmental issues that are insufficiently represented in standard indicator sets but are critical for assessing Norwegian food systems. Stakeholders suggested the inclusion of terrestrial and marine biodiversity loss, as well as circularity. While terrestrial biodiversity was incorporated into the final indicator set, marine biodiversity approaches were tested but require further development. Circularity was not included in the present assessment because no sufficiently established and consistently applicable set of indicators with adequate product-level data was identified.

The study analyzed a dataset of 60 food products representing the Norwegian diet, categorized into twelve food groups based on national per capita consumption data. Life cycle processes were modeled from cradle to farm gate, a stage that accounts for the majority of environmental impacts in food production. Although the defined system boundaries extend through retail, data limitations restricted the empirical analysis to earlier stages. The consumer stage, including household food waste and energy use, was excluded due to the high variability and limited availability of reliable product-specific data, which would introduce substantial uncertainty into the scoring.

Statistical analyses were employed to evaluate the robustness of product rankings and to identify redundancies among impact categories. The researchers compared rankings generated using the EF 3.1 method with those from alternative weighting and endpoint methods, including ReCiPe 2016, IMPACT World+, and Ecological Scarcity. The results showed a very high level of agreement among these methods, with a Kendall’s coefficient of concordance of 0.915. This consistency supports the use of EF 3.1 as the methodological basis for the framework, indicating that the product rankings are stable across different analytical approaches.

Principal Component Analysis and hierarchical clustering were used to examine correlations among the midpoint impact categories. These analyses revealed strong correlations between several categories, such as climate change and acidification, suggesting shared variation across products. Based on these statistical patterns and stakeholder input, the researchers selected eight impact categories for inclusion in the NewTools scoring method. These categories are climate change, freshwater ecotoxicity, freshwater eutrophication, terrestrial eutrophication, fossil resource use, water use, land occupation (cropland), and biodiversity loss. This reduction in indicators aims to retain essential environmental information while making the system more manageable and easier to communicate.

The weighting factors for the selected impact categories were adapted from the original EF 3.1 set to reflect the specific relevance of each category to food systems. Because the total weight is distributed across fewer categories, the relative weights of retained categories, such as climate change, are higher in the adapted set. Land occupation and terrestrial biodiversity were each assigned a weight of 0.128, reflecting their close interdependency and the importance of land management. A sensitivity analysis was conducted to assess the robustness of the framework by varying the weighting factor for climate change by 25%. The results indicated that only a small proportion of products, between 5% and 8%, changed their scores under these variations, demonstrating limited sensitivity to weighting choices.

Threshold values for the A–E rating scale were defined through a structured expert judgment process, informed by existing literature, benchmarks, and score distributions. For climate change, the threshold for the highest score was derived from a target of 1.4 kg CO2 equivalent per day per consumer in 2050. For other categories where planetary boundaries were not directly available, thresholds were set based on the distribution of scores across the 60 products and expert judgment. This approach ensures that the ratings reflect meaningful differences in performance rather than just relative standing within a specific dataset, enhancing comparability across different studies and contexts.

The framework acknowledges several limitations, including the use of a mass-based functional unit, which does not account for the nutritional value of the food. While this may favor products with low environmental impact per kilogram even if their nutritional contribution is limited, the NewTools project assesses nutritional performance separately. Additionally, the statistical analyses were based on a specific set of 60 products representing conventional agricultural systems, which may not fully capture the environmental profiles of novel production methods. The researchers emphasize the need for periodic reassessment and adaptation of the indicator set as production systems and data availability evolve.

Despite these limitations, the study demonstrates the methodological applicability of the proposed framework to a representative set of food products. The high consistency of rankings across different weighting methods and the transparent selection of indicators provide a strong foundation for further development. The framework is intended as a basis for various applications, including front-of-pack labelling, public procurement, and retail decision support. Further validation and testing across a broader range of products and user contexts are required before operational implementation, but the NewTools framework offers a promising step towards more sustainable food choices in Norway and potentially other regions.

The NewTools framework operates within the broader context of the European Commission’s Farm to Fork strategy, which emphasizes the need for sustainable food production and the use of sustainability labelling to guide consumer choices. The Environmental Footprint methodology, specifically version 3.1, serves as the primary basis for the framework, providing a harmonised, policy-oriented approach to impact assessment. This method enables comparisons between food products by aggregating results across multiple impact categories, such as climate change, eutrophication, and toxicity, into a single score. However, the researchers noted that existing frameworks often face limitations, including the omission of specific agricultural practices and difficulties in understanding weighting choices. By adapting the EF 3.1 approach, the NewTools team aimed to improve transparency and ensure the tool is practically useful for a diverse range of stakeholders, from small-scale producers to policymakers, while maintaining scientific robustness.

A key methodological challenge addressed in the study was the data comparability between domestically produced and imported foods. While detailed and representative data are often available for Norwegian production, equivalent data for imported products from diverse countries of origin can be limited or unavailable. To achieve a consistent level of data quality, the researchers utilized established life cycle inventory databases, prioritizing ecoinvent v3.11 where suitable datasets were available and using Agri-footprint otherwise. For domestic products, life cycle inventories were modeled based on specific Norwegian production conditions. This approach required methodological compromises to ensure that the scoring system could consistently evaluate the entire product range, despite the inherent differences in data availability between local and international supply chains.

The selection of impact categories was further refined by examining the structural and biophysical characteristics of the Norwegian food system. Unlike many EU countries with extensive arable land, Norway’s livestock production relies heavily on forage, pasture, and imported feed. This distinction is critical because shifting consumption from red meat to poultry to reduce greenhouse gas emissions could reduce the use of grasslands while increasing reliance on imported feed, thereby intensifying competition between feed and food resources. The framework was designed to account for these specific Nordic constraints, ensuring that the resulting environmental scores reflect the unique production realities of the region. This tailored approach allows the tool to identify sustainability trade-offs that might be obscured by a generic, one-size-fits-all European model.

Marine biodiversity was assessed using the STECF method, which evaluates the status of targeted fish stocks and the seabed impact of fishing gears. Fishing pressure was determined by assessing stock status and fishing mortality over a six-year period, while seabed impact was calculated based on the potential impact of gear types and habitat sensitivity. To ensure equal importance between these two indicators, the framework applied the average of their respective scores as the final marine biodiversity score. This specific operationalization addresses the gap in the standard PEF method, which does not currently account for these critical aspects of wild-caught fish sustainability. The inclusion of these metrics provides a more comprehensive view of the environmental footprint of seafood products within the Norwegian diet.

The study also explored the concept of circularity as a dimension of environmental sustainability, which stakeholders identified as important for food systems. Circularity involves the efficient use and recirculation of resources to minimize waste and reduce dependence on virgin materials. However, the researchers found that no sufficiently established and consistently applicable set of circularity indicators was available for the range of products included in the framework. Consequently, circularity was not included as a separate dimension in the present assessment. The authors emphasized that while the relevance of circularity is clear, its integration into the scoring system should be considered in future development as methods and product-level data availability improve. This decision reflects a commitment to methodological rigor, avoiding the inclusion of indicators that cannot be reliably quantified across the entire product set.

Validation of the framework involved a stepwise assessment to identify sources of uncertainty and bias. The researchers compared their selected impact categories with recommendations from previous studies, such as those by Ran et al. and Karlsson Potter and Röös, finding a close alignment in the most relevant indicators for food-system assessment. The final indicator set represents a compromise between environmental coverage and the need for a manageable scoring framework. For instance, categories like acidification and particulate matter were excluded due to their strong correlations with retained categories, while freshwater eutrophication was kept despite its lower contribution because it represents a distinct environmental pressure. This careful balance ensures that the framework remains both scientifically sound and operationally feasible for widespread use.

Subject of Research: Development and evaluation of a multi-indicator environmental scoring framework for food products in Norway

Article Title: A multi-indicator framework for environmental scoring of food products

Article References: Møller, H., Svanes, E., Woodhouse, A., Danielsen, R., & Olsen, H. F. (2026). A multi-indicator framework for environmental scoring of food products. Environmental and Sustainability Indicators, 32, Article 101606. https://doi.org/10.1016/j.indic.2026.101606

Image Credits: AI Generated

DOI: 10.1016/j.indic.2026.101606

Keywords: Environmental Sustainability, Food Scoring, Life Cycle Assessment, Norway, Environmental Footprint, Biodiversity, Climate Change, Sustainable Food, Policy Framework, multi-indicator, framework, environmental