6 common data entry mistakes in carbon accounting

1. Misclassifying primary and secondary data

One of the biggest carbon accounting mistakes is misidentifying primary and secondary data. This impacts the accuracy of emissions calculations, especially in Scope 3 reporting.

Understanding the difference

• Primary data: Comes directly from your operations or suppliers. Examples include on-site fuel consumption logs, electricity invoices, and supplier-specific emission factors.
• Secondary data: Derived from industry averages, government reports, or emissions databases like DEFRA, Ecoinvent, and Exiobase. It provides broad coverage but lacks company-specific accuracy.

Why this matters

Using the wrong data type can inflate or understate emissions. For example, a steel manufacturer may source raw materials from two suppliers—one using 100% renewable energy and another relying on coal-based power. If both are assigned the same industry-average emission factor, the results will be inaccurate.

How to avoid this mistake

✔ Prioritize primary data for Scope 1 and Scope 2 where possible.
✔ For Scope 3, disclose what percentage of emissions are calculated using secondary data (per ESRS E1-6 recommendations).
✔ Clearly document data sources and justifications in reports.
✔ Download our comprehensive go-to list of Carbon accounting data types

2. Overestimating data precision

Many businesses assume their emissions data is highly precise. However, this is rarely the case—especially when relying on secondary data or broad emission factors.

Where overestimation happens

• Industry averages hide abnormalities – A factory in Sweden (powered by hydroelectricity) will have a vastly different footprint than one in Germany (coal-based grid), even if both belong to the same sector.
• Scope 3 emission factors can be misleading – Many purchased goods and services use global average factors or spend-based factors, which fail to reflect supplier-specific sustainability efforts.

How to fix it

✔ Use supplier-specific data where feasible.
✔ When using secondary data, state limitations clearly in disclosures.
✔ Implement quality checks to validate outliers or unusual trends.

3. Failing to engage suppliers for Scope 3 data

Scope 3 emissions account for the majority of most companies’ footprints. Yet, they are the hardest to measure due to the reliance on supplier-provided data.

Why supplier data matters

• Purchased goods, logistics, and business travel emissions vary widely depending on suppliers.
• Relying solely on secondary data reduces credibility in regulatory filings.

How to engage suppliers effectively

✔ Establish supplier engagement programs that provide incentives for accurate emissions data.
✔ Standardize reporting templates to ensure consistency.
✔ Use automated tools to collect real-time supplier emissions data.

4. Using inconsistent emission factors

Emission factors convert activity data into CO₂ equivalents. However, different databases (e.g., IPCC, DEFRA, Ecoinvent) use varying methodologies, leading to discrepancies.

Why emission factors vary

Different organizations maintain databases of emission factors, but their methodologies and assumptions differ, leading to potential discrepancies. Some of the most widely used sources include:

• Intergovernmental Panel on Climate Change (IPCC) – Offers global emission factors based on scientific research, often used for regulatory compliance.
• UK Department for Environment, Food & Rural Affairs (DEFRA) – Provides emission factors tailored for UK and international organisations.
• US Environmental Protection Agency (EPA) – Publishes industry-specific factors for emissions reporting in the US.
• Ecoinvent, Exiobase, and other life cycle databases – These contain product-specific emission factors often used in Scope 3 calculations.

Since each source collects, updates, and averages data differently, using multiple sources without standardization can distort emissions reporting.

Common mistakes with emission factors

1. Mixing regional and global factors – A company operating in Norway (where grid electricity is mostly renewable) should not use global-average grid emissions, which might be skewed by coal-heavy regions.
2. Using outdated data – Emission factors are updated annually in databases like DEFRA and EPA. Applying an old dataset may result in inaccurate emissions estimates.
3. Selecting general instead of process-specific factors – Some industries require detailed emission factors based on specific production processes. Using a general industry-average factor may over- or underestimate real emissions.

How to ensure accuracy

✔ Standardize emission factors across reporting cycles to ensure consistency.
✔ Use the latest version of official datasets to reflect current energy mixes and industry trends.
✔ Prioritize regional and supplier-specific emission factors when available, instead of relying solely on global averages.
✔ Document the sources of emission factors used in sustainability reports for transparency.

5. Ignoring location vs. market-based Scope 2 reporting

Scope 2 emissions are calculated using both location-based or market-based methods:

• Location-based: Uses grid-average emissions (e.g., EU electricity mix).
• Market-based: Uses supplier-specific contracts (e.g., renewable energy purchase agreements).

Why this matters

Many companies mistakenly report only one method instead of both. This leads to discrepancies, especially for companies buying renewable electricity.

How to correct it

✔ Report both location and market-based emissions per GHG Protocol Scope 2 guidance.
✔ Ensure purchased renewable energy meets contractual quality standards.

6. Not validating data regularly

Many carbon accounting errors come from poor data validation. Even automated systems require manual checks.

Top mistakes in validation

• Relying on single-source data without cross-verification.
• Ignoring audit trails for high-impact emission sources.
• Failing to update methodologies in line with evolving reporting standards.

Best practices

✔ Conduct quarterly data reviews with finance and sustainability teams.
✔ Use third-party verification for key emissions data points.
✔ Automate data consistency checks in reporting software.

“Position Green gives us reliable, quality data that we can share with our stakeholders”.

Ida Ljungkvist – Group Sustainability Director at Scandi Standard

Conclusion

Avoiding these common carbon accounting mistakes improves the credibility, accuracy, and audit-readiness of your sustainability reporting.

1. Prioritize primary data for high-impact categories.
2. Engage suppliers for Scope 3 transparency.
3. Validate and standardize data sources regularly.

Want to streamline your carbon accounting? Chat with us about our dedicated Carbon Accounting solution to learn how you can shore up data-collection accuracy, and ensure you’re always calculating your emissions factors efficiently.