Pulse Brain · Growing Health Evidence Index
Tier 3 — Observational / field trialPeer-reviewed

Estimating the environmental impacts of 57,000 food products

Michael Clark, Marco Springmann, Mike Rayner, Peter Scarborough, Jason Hill, David Tilman, Jennie I. Macdiarmid, Jessica Fanzo, Lauren Bandy, Richard Harrington

Proceedings of the National Academy of Sciences · 2022

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Summary

This study develops and applies a novel computational approach to estimate the environmental footprint of individual packaged food products by inferring ingredient composition from ingredient lists and pairing these with environmental databases. Analysis of 57,000 United Kingdom and Ireland products reveals substantial variation in environmental impact within food categories, with meat, fish, and cheese typically showing high impacts whilst sugary beverages, fruits, and breads show low impacts. The work demonstrates that more nutritious products are often more environmentally sustainable, though important exceptions exist, and highlights that foods consumers perceive as substitutable may have markedly different environmental profiles.

UK applicability

The study was conducted on United Kingdom and Ireland products, making findings directly applicable to UK food policy, retail labelling, and consumer guidance. The methodology and findings can inform current and future UK environmental labelling schemes and support retailers and policymakers in communicating product-level environmental impacts to consumers.

Key measures

Greenhouse gas emissions, land use, water stress, eutrophication potential; NutriScore nutritional rating

Outcomes reported

The study quantified environmental impacts across four indicators (greenhouse gas emissions, land use, water stress, and eutrophication potential) for 57,000 food products in the United Kingdom and Ireland. It examined correlations between environmental sustainability and nutritional quality using NutriScore.

Theme
Measurement & metrics
Subject
Measurement methods & nutrient profiling
Study type
Research
Study design
Computational modelling study
Source type
Peer-reviewed study
Status
Published
Geography
United Kingdom
System type
Food supply chain
DOI
10.1073/pnas.2120584119
Catalogue ID
BFmor3ggd1-axh0sm

Topic tags

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