Product Carbon Footprints for Your Full Portfolio

A Product Carbon Footprint (PCF) measures the total greenhouse gas emissions associated with a specific product across its life cycle, from raw material production and ingredient processing to manufacturing, packaging, and distribution.
FoodFacts calculates PCFs by combining product-specific activity data (ingredient quantities, packaging specifications, energy use, and transport distances) with scientifically established greenhouse gas emission factors. Emissions are calculated across relevant life cycle stages and aggregated into a single result expressed as kilograms of CO₂ equivalents (kg CO₂e) per kg of product.
Greenhouse gas emissions are converted into CO₂ equivalents using IPCC Global Warming Potential values over a 100-year time horizon (GWP100), enabling different greenhouse gases to be compared based on their climate impact.

FoodFacts follows a standards-aligned LCA methodology based on ISO 14040, ISO 14044, and ISO 14067, the GHG Protocol Product Standard, and FLAG guidance, as well as the industry methodology from Svensk Dagligvaruhandel and Livsmedelsföretagen.

Yes. FoodFacts supports integration of supplier-specific data for ingredients, packaging, and production inputs such as energy use and electricity mix. This increases accuracy and reduces reliance on generic emission factors.

A Product Carbon Footprint (PCF) measures the greenhouse gas emissions of an individual product, while Scope 3 reporting measures emissions across a company's entire value chain. Rather than being an alternative to Scope 3 reporting, PCFs provide the product-level data that can significantly improve its accuracy.
Compared with traditional carbon accounting approaches, such as spend-based calculations, PCFs provide a much more granular view of emissions at the product, ingredient, and supplier level. This enables companies to replace generic estimates with product-specific data where available, leading to more accurate and actionable Scope 3 reporting.
PCFs are particularly valuable for calculating emissions from Scope 3 Category 3.1 (Purchased Goods and Services), as well as contributing to Category 3.4 (Upstream Transportation and Distribution) and Category 3.12 (End-of-Life Treatment of Sold Products).
This level of detail is especially important for food companies, where Scope 3 emissions typically account for the majority of total greenhouse gas emissions.

PCFs are updated automatically whenever underlying product data changes, such as ingredient composition, recipe changes, packaging updates, or supplier inputs.

Getting started with FoodFacts is simple. Product data can be imported through GS1, Excel, or API integrations with your existing PLM/ERP systems. FoodFacts structures and enriches the data to enable automated PCFs across your product portfolio.
For example, if the origin of an ingredient is unknown, FoodFacts automatically uses proxy data from third-party industry databases. In this case, it applies the most representative sourcing origin for that ingredient in the product's market.

PCF quality depends on the quality, granularity, and transparency of the underlying data and methodology. FoodFacts provides full transparency into data sources, assumptions, and calculation methods, allowing users to assess confidence levels and identify opportunities to improve data quality over time.
FoodFacts PCFs are designed to continuously improve as more detailed product-specific data becomes available. Calculations can start from high-quality secondary data based on industry averages and evolve towards more precise assessments using primary data from suppliers and companies, such as ingredient specifications, packaging materials, energy use, and electricity mix. The more granular the input data, the higher the potential accuracy of the PCF.
Secondary data is sourced from recognised LCA databases such as Agri-footprint® and SAFAD. FoodFacts also accounts for processing steps throughout the value chain, adjusting climate impacts for processed ingredients to reflect the full production chain, including concentration effects where relevant

FoodFacts PCFs are calculated using the FoodFacts methodology, which is based on established LCA principles and relevant standards. The calculations are automatically quality-checked within the FoodFacts platform to ensure consistency and data quality.
For companies requiring independent assurance, FoodFacts also offers the option of third-party verification through its network of Sustainability Expert Partners. This provides an independent review of the PCF calculation and methodology application.

FoodFacts combines multiple scientific third-party databases and industry data sources to provide broad coverage while maintaining methodological consistency across PCF calculations.
Key data sources include for example Agri-footprint®, SAFAD, Blonk LUC Database. You can read more about our databases and our PCF methodology here.
FoodFacts prioritizes datasets that are transparent, scientifically robust, geographically representative, and aligned with internationally recognized carbon footprint methodologies. This approach enables consistent calculations while allowing PCFs to become more accurate as more product-specific data becomes available.

FoodFacts applies a cradle-to-distribution system boundary for Product Carbon Footprints (PCFs), covering the major emission sources associated with food products and beverages from raw material production through distribution to the point where products reach the market.

The calculation includes the following life cycle stages:

• Agricultural production and extraction of raw materials
• Land use change
• Processing and refinement of ingredients
• Food manufacturing
• Packaging production
• Transportation and distribution
• Food losses occurring within the supply chain
• End-of-life treatment of packaging

By covering emissions across the value chain, FoodFacts provides a comprehensive view of the main contributors to a product's climate impact and helps identify opportunities for improvement.

FoodFacts calculates PCFs at the product level, typically linked to a specific SKU/GTIN. The accuracy and level of detail of a PCF depend on the granularity of the underlying product data. FoodFacts calculations can incorporate increasingly specific information, such as ingredient composition, supplier-specific data, production processes, packaging details, energy use, and transport information. As more primary data becomes available, the PCF becomes more representative of the actual product and its value chain.
For retailers and producers, FoodFacts enables consistent PCF calculations across large product portfolios by combining available product data with scientifically robust secondary data where primary data is not yet available.