Why has the Emissions Factor (EF) changed?

Emissions factors are estimates that translate your activity data, like kWh of electricity, litres of fuel, dollars spent, kilometres travelled, into greenhouse gas emissions. They are not fixed constants. They change because the underlying evidence, methods, and system conditions change over time.

Below are the most common reasons, explained in plain language, plus what to do if you spot something that looks wrong.

1) New or improved underlying data

• What changes

  • New national statistics are published (for fuels, electricity generation, industrial processes, waste treatment, agriculture, and more)

  • Suppliers and industry bodies release more complete datasets

  • Data gaps get filled or updated after audits and corrections

• Why it matters

  • Factors are only as good as the input data behind them

  • When the data improves, the factor becomes a better reflection of real world emissions

• Typical impact on your results

  • Often small year to year changes

  • Larger shifts where earlier data was incomplete or later revised

2) Methodology improvements

• What changes

  • The calculation approach is refined to better match science and standards

  • Boundaries are adjusted (what is included or excluded) to align with guidance

  • Treatment of co products, recycling, waste, or upstream emissions may be updated

  • Global warming potentials or gas coverage may be updated if a dataset refreshes its basis

• Why it matters

  • The aim is to reduce bias and improve comparability across organisations

  • Over time, methods tend to become more precise and consistent

• Typical impact on your results

  • Some categories can move noticeably, especially where the method shift is meaningful

  • Changes may affect the split between Scope 1, Scope 2, and Scope 3, depending on the dataset

3) Real world system changes (the best type of change!)

Even if the method stays the same, the real world changes.

• Electricity grids change

  • The generation mix shifts year to year (more renewables, gas, coal changes, interconnectors, etc.)

  • This alters grid emissions intensity and can meaningfully change electricity factors

• Supply chains change

  • Production routes evolve (for example more recycled content, process efficiency improvements, new technology)

  • Transport modes and logistics patterns can shift over time

• Policies and market changes

  • Regulations, carbon prices, and reporting rules can affect data quality and availability

  • National inventory updates can cascade into factor updates

4) Better geography, sector, or product specificity

• What changes

  • Factors become more tailored (country specific, region specific, sector specific, or product level rather than broad averages)

• Why it matters

  • A generic average can be directionally right but wrong for your actual context

  • Increased granularity improves decision usefulness and reporting quality

• Typical impact on your results

  • Some lines may change because they are now matched to a more accurate factor

  • This can be especially relevant for spend based factors and complex procurement categories

5) Reclassification and mapping improvements

Sometimes what changes is not the factor itself, but how it is applied.

• What changes

  • A category mapping is refined (for example, a supplier or expense code is routed to a more appropriate emissions factor category)

  • Product and service definitions are clarified

• Why it matters

  • Better mapping reduces misallocation and improves comparability over time

• Typical impact on your results

  • Shifts between categories (for example travel vs accommodation) without changing total emissions much

  • Occasionally, changes in both category and total emissions if the new mapping points to a materially different factor

6) Corrections and misstatements do occasionally happen

Emissions factor datasets are produced by humans and systems, and even reputable sources can occasionally include mistakes or misstatements.

• Examples of what this can look like

  • A factor published with an incorrect unit or scaling

  • A category definition that is later clarified or corrected

  • A transcription or formatting issue in a release file

  • A factor that is revised after publication due to an upstream data correction

• How Trace approaches this

  • We version control factor releases so changes are traceable

  • We apply sanity checks and review material movements when datasets update

  • Where a trusted source issues a correction, we update the platform accordingly

If something looks off in your results, it is worth flagging. The fastest path is to share the category, source activity, and what changed so we can confirm whether it is a data update, a mapping improvement, or a genuine issue.

What you should expect when factors update

• Your activity data has not changed

• The calculated emissions may change because the conversion rate has changed

• Increases or decreases are both normal

• The goal is a more accurate and defensible inventory

When to contact us

Please contact our support (support@our-trace.com) team if:

• A category has moved significantly and you want help interpreting why

• You suspect a unit issue or a misstatement in a factor

• You want to lock a reporting year to a specific factor version for consistency

• You need to understand implications for assurance or comparative reporting

We will help you understand the change and confirm the correct treatment.

External resources explaining changes in detail

1. DEFRA 2025 factor changes https://www.dcceew.gov.au/sites/default/files/documents/national-greenhouse-account-factors-2025.pdf 

Trace process for maintaining and updating Emissions Factors

Our process and principles for updating EFs can be found here.

Our list of EF sources can be found here.