Emission Factor Data for AASB S2 Climate Disclosures: Four Things That Matter

Most companies spend months preparing their first AASB S2 report. They clean spend data. They categorise every invoice. They document every assumption.

Then they multiply all of it by a number from a spreadsheet of unknown vintage. And never look at it twice.

That number is the emission factor. It is the variable that converts spend into an emissions figure — the core output of any emission data API or emission factors database. It determines whether your Scope 3 number is right or wrong. Under AASB S2, getting it wrong is no longer just a methodology issue. Directors sign off on climate disclosures. ASIC enforces them.

Would you use UK education system data to choose an Australian university? The same logic applies to emission factors data.

The question being asked more often now — by assurance providers, by consultants who know what is coming, and by finance directors who have started paying attention — is simple: is your emission factor data fit for purpose for Australian AASB S2 reporting?

There are four tests. Here is what they are and why each one matters.

Why emission factors data is the variable everyone overlooks

A Scope 3 calculation is a multiplication. Spend data times an emission factor equals an emissions figure. Most of the effort goes into the spend data side. The emission factors data is treated as given.

That assumption is being stress-tested. A 2024 update to major EEIO databases shifted median emission factors 10 to 20 percent across industries. Companies that had not updated their emission factors data in two or three years were, by definition, reporting the wrong number.

Harvard Business School reviewed S&P 500 sustainability reports from 2010 to 2020. 74 percent of companies revised their emissions data at least once. More than 135 million tonnes had been underreported in original disclosures. Emission factors data quality is one of the contributing variables to that revision rate.

Under AASB S2, a restatement is not just a reputational issue. It is a financial disclosure issue.

The four tests for emission factor data fitness

Test 1: Is it Australian emission factors data?

Spend-based emission factors data is built from input-output tables that model how money flows through an economy. An Australian company's spending reflects Australian supply chains and energy intensity. Factors built from the UK or US economy do not accurately represent that.

The GHG Protocol's data pedigree specifications include geographic fit: the emission factors data should reflect the economy where the spend occurred. For Australian AASB S2 reporting, that means Australian national data.

FootprintLab's emission factors data is built from the Australian Bureau of Statistics input-output tables and the National Greenhouse Gas Inventory. The same dataset is used by the Australian Government's Climate Active program and NSW and QLD Government reporting.

Test 2: Is your emission factors data current?

The GHG Protocol specifies recency as a data pedigree criterion: the most recent available emission factors data should be used. For annual AASB S2 reporting, that means factors updated at least annually, aligned to the most recent national statistics release.

FootprintLab updates its Australian emission factors data annually, in time for EOFY reporting. Historical versions are available so year-on-year comparisons remain consistent.

Test 3: Has your emission factors data been CPI-adjusted?

Spend-based emission factors data is benchmarked to a specific price year. Applying a 2021 factor to 2025 spend without inflation adjustment introduces a growing error. Over three to four years, cumulative inaccuracy can reach 30 to 40 percent. Most free emission factors data is not CPI-adjusted.

FootprintLab adjusts its emission factors data for CPI annually and provides CPI adjustment guides for clients who need to apply adjustments within their own workflows.

Test 4: Has your emission factors data been peer-reviewed?

AASB S2 requires external assurance. Assurance providers ask about the methodology behind Scope 3 numbers — including whether the underlying emission factors data has been independently validated.

FootprintLab's emission factors data methodology is published in Economic Systems Research and Science of The Total Environment. It was selected by the United Nations to monitor SDG 8.4.1 and is used by the IMF and OECD.

Get it right the first time

A carbon inventory is only as reliable as the emission factors data it is built on. Get it right from the start and you have a number that is defensible, comparable year on year, and unlikely to surprise you when an assurance provider looks closely.

Over-reporting emissions carries its own risks. Overstating your Scope 3 footprint misrepresents your actual impact and distorts decisions made on that data. Under-reporting is the more obvious risk: a number that looks good until it does not, and a restatement that is harder to explain the longer it has been in print.

Group 2 reporting starts in July 2026. The time to check your emission factors data is now.

The questions to ask your provider or platform

• Is this Australian emission factors data, built from Australian national input-output tables?

• What is the base year of the emission factors data, and when was it last updated?

• Has the emission factors data been adjusted for CPI?

• Has the underlying methodology been peer-reviewed and where is that published?