Scope 3 Carbon Footprint: The Data You Use Is (Almost Always) Wrong – And Nobody Tells You

Carbon footprint Scope 3 inaffidabile: il dato che usi è (quasi sempre) sbagliato

A recent study published in the Journal of Industrial Ecology – “Shedding Light on the Shadows: Transparency Challenge in Background Life Cycle Inventory Data” (Guo et al., 2025) – has highlighted one of the most underestimated weaknesses in environmental assessments: the lack of transparency and limited reliability of background Life Cycle Inventory (LCI) data.

Why Scope 3 Carbon Footprint Data Is Unreliable

Most Scope 3 emissions are calculated using secondary inventory data, extracted from generic LCI databases that are often aggregated, outdated, and opaque. These are convenient proxies used instead of primary data, but – as demonstrated by Guo et al. (2025) – they have alarmingly low levels of transparency and representativeness.

Here are some key findings from the study and related literature that every company should consider when preparing (or reviewing) its carbon footprint:

• Over 60% of LCI datasets do not clearly disclose their sources, assumptions, or system boundaries.

• More than 70% of data in major databases (e.g., Ecoinvent, GaBi) is aggregated: it’s impossible to trace specific inputs or verify alignment with actual business processes.

• Scope 3 emissions can represent up to 90% of a company’s total carbon footprint in sectors like FMCG, fashion, ICT, or finance – yet are often estimated using generic proxies with high uncertainty.

• Uncertainty in Scope 3 calculations can exceed 80–90%, making even auditor-approved values unreliable.

• Most LCI databases rely on data over 5 years old, collected in different regions or based on outdated technologies.

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Choosing the Right Parameters to Avoid Unreliable Scope 3 Carbon Footprints

These numbers are not technical nuances: they form the foundation for climate strategies, investment decisions, reputation management, compliance, and business positioning.

The issue isn’t just technical – it’s cultural. Many believe that using a certified software or “official” database is enough to produce reliable results. But selecting the right inventory data is never automatic. It requires:

• deep understanding of data sources,

• awareness of representativeness limits (geographical, temporal, technological),

• the ability to validate with internal primary data,

• and a clear view of the analysis objective (disclosure, investments, communication).

Without these competencies, even a “verified” study can produce unreliable – and therefore risky – results.

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How to Avoid Unreliable Scope 3 Carbon Footprint Data

In a world where climate disclosures are under increasing scrutiny, just calculating your emissions is not enough. It must be done properly, with the right level of technical rigor and by those who understand the limits and complexity of LCI data.

Your data’s credibility doesn’t depend on who verifies it, but on who selected it.

That’s why working with professionals experienced in LCA and carbon markets is essential. A carbon footprint is not a box to check – it’s a strategic tool for leading in a climate-conscious economy.