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

Read source ↗ All evidence

Summary

Clark et al. developed an approach to estimate the environmental footprint of individual food products by inferring ingredient composition from food labels and matching these against environmental life-cycle assessment databases. Applied to 57,000 products in the United Kingdom and Ireland, the analysis demonstrates substantial variation in environmental impact across food types and reveals that, whilst more nutritious products tend to be more environmentally sustainable, important exceptions exist and substitutable foods can have markedly different impacts. The methodology is robust to uncertainty in ingredient composition and sourcing, providing a foundation for more informed decision-making by consumers, retailers and policymakers.

UK applicability

The study was directly conducted on UK and Irish food products, making findings directly applicable to the UK food retail environment and consumer choices. Results could inform UK food labelling policy and retail sustainability initiatives, though sourcing decisions and supply chain geography may limit direct applicability to other regions.

Key measures

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

Outcomes reported

The study developed and applied a novel methodology to estimate environmental impacts (greenhouse gas emissions, land use, water stress, and eutrophication potential) across 57,000 food products in the United Kingdom and Ireland by inferring ingredient composition from food labels and pairing with environmental databases. It found that product-level environmental impacts vary widely by food type, with sugary beverages, fruits and breads showing low impacts, whilst meat, fish and cheese products showed high impacts.

Theme
Measurement & metrics
Subject
Measurement methods & nutrient profiling
Study type
Research
Study design
Methodological development and application to large-scale dataset
Source type
Peer-reviewed study
Status
Published
Geography
United Kingdom
System type
Food supply chain
DOI
10.1073/pnas.2120584119
Catalogue ID
BFmou2mlyw-2ym00b

Topic tags

Pulse AI · ask about this record

Dig deeper with Pulse AI.

Pulse AI has read the whole catalogue. Ask about this record, its theme, or how the findings apply to UK farming and policy — every answer cites the underlying studies.