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Emission Factor Matching Algorithm

Updated this week

The Emission Factor Matching Algorithm is being gradually implemented. The rollout for all customers is in progress and your Customer Success Manager will approach you with more details soon.

Accurately calculating carbon emissions is essential for businesses striving to measure and reduce their environmental impact. The accuracy of emission factors used in calculations is key to determine the accuracy of the emissions associated with your different business activities.

Best practices take many criteria into account, such as:

  • The reliability of the creator of the emission factor

  • The technical correlation between the activity related to the emission factor and your activity

  • The temporal correlation between the activity related to the emission factor and your activity

  • The geographical correlation between the activity related to the emission factor and your activity

  • The representativeness of the sample studied to create the emission factor

  • Other diverse criteria (the global warming potential version used, source consistency, granularity of emissions across gases…)

Deciding which trade off is optimal can be a complex task, which is why our carbon accounting platform uses a robust emission factor algorithm and selection logic to ensure we are offering credible emissions calculations.

In some cases, there may be complex trade-offs between the available factors. Our proprietary algorithm however is designed to balance these variables, ensuring that each assessment applies the most relevant and credible emission factors available.

1. Emission factor matching algorithm overview

The algorithm is split into 3 stages:

  • Filtering: pre-selecting emission factors that are compatible with the log entry

  • Scoring: each of the eligible emission factor is given a score that reflects its closeness to the specificities of the log entry

  • Tie-breaking: if 2 or more emission factors are tied with the highest score, we apply deterministic criteria to ensure the traceability and auditability of the selection

2. Details per stage

2.1 Filtering

Ensuring all emission factors scored are a viable choice for the log entry.

We select in our database all the emission factors which are compatible with your entry:

Filter

Description

Example

Representativity

The emission factor reflects the activity assessed.

If this log entry assesses the cradle-to-gate emissions of steel, we get all generic emission factors for steel.

Availability

If your suppliers provided emission factors for this activity, we fetch them.

We enable supplier engagement by automatically pulling in your suppliers’ emission factors.

Unit compatibility

The unit of the emission factor is compatible with the unit of the log entry.

If the log entry is in kg, we’ll fetch the emission factors whose units we’re able to convert to kg.

Validity

The emission factor has not been disabled.

We stay on top of database updates, to ensure you get the most up-to-date emission factors.

2.2 Scoring

While we always prioritize an emission factor that reflects the assessed activity accurately, there may not be one available. In these cases, we manage the trade-off we need to make through a scoring system.

The score takes into account the following criteria:

  • The geographical match: how close the emission factor’s region is to the log entry’s region

  • The temporal match: how close the emission factor’s validity period is to the log entry’s time period

  • The reliability of the source that provided the emission factor: not all sources follow the same practices for transparency, and we prioritize the most reliable sources

  • The specificity of the emission factor: if it is provided directly by your suppliers, we increase the score to reflect the precise knowledge of the product obtained through supply chain engagement.

2.3 Tie-Breaking

In most cases, one emission factor has the highest score, and is selected. Sometimes, a few emission factors obtain the same score. This can be caused by an exact trade-off (e.g. one emission factor is closer to the log entry geographically, while the other is closer in time)

In those cases, we apply tiebreakers to ensure we can keep track of why an emission factor is chosen over another, even if they seem like a similar fit.

These tiebreakers include:

  • Selecting the emission factor using the Global Warming Potential from the most recent IPCC assessment report

  • If applicable, selecting the emission factor that avoids using unit conversions

  • If that has not determined a specific emission factor, we take the worst case scenario, which takes the highest emission factor among the remaining ones

  • If the emission factors have the same value, we take the one that was last added.

Carbon accounting and the use of emission factors are continually evolving as new data sources, scientific methodologies, and regulatory frameworks emerge. At Cozero we are committed to continuous improvement, regularly refining our methodology to incorporate the latest research, regulatory updates, and best practices.

This dedication ensures our customers always benefit from the most accurate and transparent emissions data, empowering them to make informed sustainability decisions with confidence.

Please contact your Climate Success Manager if you have any questions.

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