We use Product Carbon Footprints (PCFs) to improve the accuracy of upstream emissions calculations. To ensure transparency and consistency, we evaluate the quality of PCF sources before import. This guide outlines the steps and criteria we use to assess PCF quality.
Guide to evaluating PCF quality
We have a framework for evaluating a PCF source and giving it a 1-5 score for quality. This guide explains what the framework covers and how it is used for scoring.
Introduction to PACT PCFs
Our approach to PCFs is aligned with the Partnership for Carbon Transparency (PACT). PACT has developed methodologies for calculating consistent PCFs, and being able to share them in a standardised way.
In terms of data quality, the PACT approach introduces:
Methodological consistency
Metrics for scoring data quality and primary data usage
Directions for third party assurance
💡 Given the above, we therefore accept any PCF receive in PACT format as at least meeting our minimum quality criteria.
Building on PACT and data source quality
The PACT methodology and data model tracks certain information relating to datasource quality. This includes methodology, primary data share, and assurance status. We use the data available in the PACT data model as the foundation for our datasource quality framework.
We then build on this by asking for further information that gives deeper insight into source quality. This leads us to ask additional information on:
Methodology note - technical documentation on the PCF methodology. This gives full transparency of the calculation approach.
PCF source - the organisation that calculated the PCF. This highlights the experience and reliability of the calculating organisation
Input data - what type of business data was used to calculate the PCF, e.g. product-specific activity data or proxy estimates. This demonstrates the accuracy of calculations.
Allocation rules - a description of the approach used to allocate emissions amongst multiple products. This demonstrates what level of the PACT hierarchy for allocation approaches was used.
Lifecycle emissions - GHG emission values for the contributing emission processes in the PCF. More granular information here makes it easier to validate emission values and the methodological approach.
This additional information feeds directly into the data quality indicators we assess in our quality framework below.
💡 We therefore built a scoring framework that builds upon the PACT approach to assess emission datasource quality
Data quality framework for PCF sources
We score the quality of a PCF source on a 1-5 scale. This is done by assessing three categories:
Source reliability - how trusted the PCF data source is
Source methodology - how transparent and aligned with best practice the methodology used to calculate the PCF is
Source data - how high quality the type of data used in the PCF calculation is
Each individual category is also scored 1-5 and weighted equally in the overall quality score.
Source reliability
Reliability assesses the assurance status of the PCF, and the type of organisation that originally calculated the PCF.