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Tier 1 — Meta-analysis / systematic reviewGrey literature

Full Excel model: Life-cycle environmental impacts of food & drink products

Joseph Poore

Oxford University Research Archive (ORA) (University of Oxford) · 2018

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Summary

This study presents a comprehensive life-cycle assessment (LCA) model developed at Oxford University, as suggested by the 2018 publication date and archival status. The Excel-based tool quantifies environmental impacts—including greenhouse gases, land use, water consumption, and nutrient pollution—across diverse food and drink products and supply chain stages. The model is designed to enable systematic comparison of environmental footprints across product categories, supporting evidence-based assessment of food system sustainability.

UK applicability

The model provides a transferable methodology and dataset relevant to UK food policy and environmental impact assessment, though product-specific results will reflect global supply chains and production practices. UK-specific applications would require localisation of production, transport, and retail assumptions to reflect domestic farming systems and supply networks.

Key measures

Life-cycle environmental impact indicators including greenhouse gas emissions (kg CO₂-eq), land use (m² per kg product), freshwater use (L per kg), eutrophication potential, and acidification potential across food and drink categories

Outcomes reported

The study presents a comprehensive Excel-based model quantifying life-cycle environmental impacts (greenhouse gas emissions, land use, water use, eutrophication, acidification) across a broad range of food and drink products. The model enables comparison of environmental footprints across product categories and supply chain stages.

Theme
Measurement & metrics
Subject
Measurement methods & nutrient profiling
Study type
Research
Study design
Meta-analysis
Source type
Grey literature
Status
Published
Geography
Global
System type
Food supply chain
DOI
10.5287/bodleian:0z9mybmyz
Catalogue ID
BFmovi28q3-7zqfbz

Topic tags

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