Disclosure focus
This disclosure asks an organisation to explain the approach it uses to measure its greenhouse gas emissions, including the main inputs and assumptions behind those measurements. In practice, the focus is on showing how the numbers were built: what data was used, what estimation methods were applied, and where judgement or assumptions were needed to fill gaps or convert activity data into emissions figures.
The practical point is to make the measurement basis understandable and comparable, not just to present a final emissions total. An organisation should be clear about the scope of the approach across its operations, and whether the same method is used consistently or only for certain sites, business units or emission sources. The aim is to help users judge how robust and complete the reported emissions information is.
This LRA educational guidance supports disclosure preparation. For the exact requirements, always refer to the official IFRS source.
Before you start
A quick mental checklist before you prepare this disclosure — tick each as you settle it.
Preparation
Key information to prepare
＋ Show s2-29-a-iii sub-elements (LRA working checklist)
Explain how this year’s figure differs from the previous year’s.
State the boundary method used to decide what is included in the reporting group or operating perimeter.
Identify the emission factors applied.
Set out the key inputs and assumptions used in the calculation.
Describe why the figures changed, where there is a change.
Add any data-quality comments for Scope 3, if they are relevant.
How to prepare it
1Set the reporting boundary first. Confirm which entities, operations, and activities sit inside the calculation perimeter, and record the approach you used to draw that line so the same basis can be applied consistently.
2Define what will count in the calculation. Agree the data items, methods, and any ordinary-language assumptions that will feed the result, including the emission factors you intend to use.
3Gather the supporting evidence for each input. Keep source records for activity data, factor selections, assumptions, and any quality notes needed where supply-chain information is less robust.
4Build the reported figures or narrative from the evidence. Make sure the final output reflects the chosen boundary, the selected factors, and the assumptions actually used in the calculation.
5Explain any year-on-year movement. Note what changed compared with the previous period, why it changed, and whether the change affects the way the numbers should be read.
6Check the draft against the source material before sign-off. Confirm the boundary approach, factor choices, assumptions, change explanations, and any relevant quality comments are all complete and consistent with the underlying records.
Request the data
Request the emissions calculation pack from the carbon accounting owner
Translate the disclosure into an internal business question — then adapt it to your organisation's own language.
What calculation approach, inputs, assumptions, and year-on-year changes were used to produce the greenhouse gas figures for this reporting period?
Use your organisation’s own names for the team, systems, and calculation packs first, then map them to the reporting disclosure. Keep the ask in everyday internal language rather than framework wording, and check the source material before sign-off.
Weak request
Please provide the IFRS S2 GHG measurement approach, inputs and assumptions evidence for S2-29(a)(iii).
Why it fails: It uses framework language that many operational teams will not recognise, so the owner may not know which files or calculations to send. It also does not point to the practical artefacts needed to explain the numbers, such as the boundary, factors, assumptions, and year-on-year changes.
Better request
Please send the latest emissions calculation pack for [reporting period], including the boundary used, the source file or system extract, the factor set and version, the main inputs and assumptions, any changes since [prior period], and the reason for those changes. If you track indirect-emissions data quality, include those notes too.
Industry examples
Draft your disclosure
Notes that turn data into a disclosure
LRA training templates — adapt them to your organisation, and check the official source before sign-off.
Method note
Explain the basis used to prepare the figures, including how the reporting boundary was defined, which inputs and assumptions were applied, and what conversion factors were used.
Context note
Describe what the numbers represent in practice, including the effect of the chosen boundary, the main calculation inputs, and any quality limits that shape how the figures should be read.
Fluctuation statement
Set out the main reasons the figures changed from the previous year, distinguishing between real operational movement, changes in the reporting boundary, and updates to data or assumptions.
Content index entry
s2-29-a-iii GHG measurement approach, inputs and assumptions — [location / page] / [notes]
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Preparation tools & forms
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Assurance readiness
For each claim, check the evidence
Evidence pack to prepare
Common reporting gaps
The information is presented without a date or as-at point.The scope or boundary of the statement is left undefined.Key terms are used inconsistently across the report.Material changes since the previous period are not disclosed.Assertions are made without supporting detail or a source record.Boilerplate is used that does not actually answer what is asked.
Common gaps
Mistakes to avoid when collecting the data
Wrong owner, wrong language
The team asks a technical lead in framework terms instead of the person who actually runs the emissions data, so the answer comes back in the wrong business language and cannot be used cleanly.
Boundary left undefined
People start collecting figures before agreeing which parts of the business sit inside the reporting perimeter, so different teams pull different populations and the dataset cannot be reconciled.
Period basis not fixed
One team uses the latest month available while another uses the reporting year cut-off, so the inputs are built on different timing bases and do not line up.
Counting basis gets mixed
Activity data, estimates and converted values are gathered together without separating how each was counted, which makes the underlying method impossible to trace.
Source labels are stripped out
Original file names, system tags and version markers are lost during collection, so no one can tell which extract or calculation the numbers came from.
Populations merged too early
Data for different business units, sites or asset groups is combined before the collection rules are agreed, even though those groups should stay separate for review.
Evidence details not captured
The team saves the number but not the supporting context, such as where it came from, who produced it and when it was taken, so the trail is incomplete.
No sign-off trail
Draft inputs move through email and spreadsheets without a clear approval record, so there is no reliable record of who checked the data before it was used.
Change reasons not logged
Year-on-year movements are collected without recording what changed in the business or the method, so later reviewers cannot explain the difference.
Quality notes for indirect data missed
Where third-party or estimated data needs a quality note, the collector skips it, leaving no record of known limitations or assumptions.
Where judgement is often needed
Acquisitions and disposals during the year
State whether you bring in or remove emissions from businesses bought or sold part-way through the period, and explain the cut-off date and any restatement used so the year-on-year comparison is understandable.
Different country definitions for the same activity
If local records classify the same fuel, site, or workforce group differently across countries, choose one organisation-wide basis, explain the mapping rule, and note where local data had to be translated.
People or sites close to the reporting line
For assets, teams, or contractors that sit near your chosen boundary, explain the rule used to include or exclude them and why that rule gives the clearest picture of the business you are measuring.
Using estimates where direct readings are missing
Where actual measurements are not available, disclose which figures are estimated, the method used to build them, and how you checked that the estimate is reasonable.
Choosing the timing basis for the period
If activity data, meter reads, invoices, or other source records arrive on different dates, explain the timing rule you applied and keep it consistent unless you can clearly justify a change.
Selecting emission factors and updating them
Explain which factor set you used, why that source was chosen over alternatives, and whether any mid-year update or country-specific factor changed the result.
Rounding and aggregation of small amounts
If you round figures or combine small items before reporting, say how you did it and make sure the rounded totals still reconcile to the underlying figures.
Protecting sensitive supplier or employee data
When detailed source data cannot be shown because of privacy or confidentiality limits, explain the level of aggregation used and how that still supports a fair view of the calculation.
Explaining changes from the prior period
If the current year differs from last year because of a method change, boundary shift, or better source data, describe the reason for the movement and separate it from genuine operational change where possible.
Examples
Illustrative examples
Synthetic, written by LRA — not from a company report, not text from any standard.
Illustrative (synthetic) example — manufacturing
We have kept the same group perimeter as last year, with one small plant added after acquisition and no other boundary changes, so the year-on-year movement is mainly operational rather than structural.
- For the current year, we used the same calculation methods across the group and applied location-based electricity factors from our market data provider, plus supplier-specific factors where we had them for purchased materials and freight.
- The main shift came from higher output at our two largest sites and a fuller set of supplier data for upstream transport; our scope 3 figures remain partly estimate-based for categories where supplier coverage is still incomplete, so those numbers are less precise than our direct emissions data.
This example shows how to explain a stable reporting perimeter, the main drivers of movement, the factor sources used, the assumptions behind the numbers, and where indirect-emissions data still relies on estimates.
Illustrative (synthetic) example — retail
Our reporting boundary stayed unchanged this year and continues to follow the stores, warehouses and central functions we control, with franchise activity left outside the group totals.
- Compared with the prior period, the rise in our footprint was driven mainly by more customer deliveries and a larger electricity load in distribution centres; we used the same grid factors as last year, together with supplier data for leased vehicles where available.
- For indirect categories, we relied on spend-based estimates for a few upstream items and on activity data for logistics and waste; those areas are the least mature in our dataset, so we flag them as lower-quality inputs and expect future revisions as supplier coverage improves.
This example shows how to describe an unchanged boundary, explain the main reasons for movement, identify the factor set and input types used, and note where indirect-emissions data is still less robust.
How companies report S2-29-a-iii in practice
Examples of full and partial reporting practice. These are evidence-led reviews, not exact disclosure templates to copy.
SITC International Holdings Company Limited
Water Transportation · Hong Kong · 2025
SITC International Holdings Company Limited’s 2025 Environmental, Social and Governance Report covers its consolidation operational boundary approach for emissions, specifying an operational control methodology for Scope 1 emissions on page 76. The report also provides information on changes to measurement approaches, inputs, and assumptions during the reporting period on page 196. However, the report lacks clear disclosures on changes versus the prior year, reasons for changes, and scope 3 data quality notes, with emission factors discussed only unclearly on page 196.
ANZ Group Holdings
None · Australia · 2025
ANZ Group Holdings’ 2025 Climate Report provides clear coverage of its consolidation operational boundary approach, stating on page 65 that where data is unavailable, the operational control approach is used for in-scope lending and capital markets. The report also details the use of the most current emission factors for reporting, as noted on page 79. However, disclosures on changes versus the prior year (p.54), inputs and assumptions, reasons for changes, and scope 3 data quality notes (p.57) are either unclear or not found in the report.
Aditya Birla Fashion and Retail Limited
Retailing · India · 2025
Aditya Birla Fashion and Retail Limited’s Integrated Annual Report 2024-25 provides coverage on changes made to the measurement approach, inputs, and assumptions during the reporting period, including some reasons for those changes (p.112). However, the report does not clearly disclose changes versus the prior year or reasons for changes in detail, and there is no clear information on the consolidation operational boundary approach or scope 3 data quality notes. Additionally, emission factors are mentioned with related context but lack a clear, explicit disclosure (p.111).
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Scenarios to work through
A group has changed from using a market-based electricity factor to a location-based one for part of its footprint, and the emissions team also updated the boundary to include a newly controlled subsidiary from 1 July. The draft note currently says the numbers moved because of 'method updates' but does not separate the effects.
QHow should the team decide what to explain so a reader can see what changed in the current period and why the figures moved?
Reveal model answer →Hide answer ↑They should spell out the main measurement changes in plain language, including what was altered in the boundary treatment and what was altered in the calculation inputs, then link each change to its effect on the current-year numbers. A brief label such as 'method updates' is too vague if it hides whether the movement came from a boundary shift, a factor update, or both. The explanation should let a user understand the year-on-year movement without guessing.
Why this matters · Separate the measurement change from the reason for the movement, so the reader can trace what drove the difference from the prior period.
A preparer has used a mix of supplier-specific activity data, spend-based estimates, and default factors for purchased goods and freight. The working papers are complete, but the draft disclosure only lists the final tonnes and does not explain the main data sources or the assumptions behind the estimates.
QWhat should be included in the narrative so the basis of the calculation is understandable to a reader?
Reveal model answer →Hide answer ↑The note should describe the main data inputs and the assumptions used to turn those inputs into emissions, in enough detail for a reader to understand the basis of the estimate. That means explaining where the activity data came from, where estimates were needed, and what simplifying assumptions or proxies were applied. The aim is not to reproduce every worksheet line, but to make the calculation approach transparent.
Why this matters · Explain the key inputs and assumptions that sit behind the emissions figure, not just the final total.
A company has changed its emissions factor set during the year because it moved to a newer database for stationary fuel and refrigerants. The draft note mentions the new database name, but it does not say whether the change affected the current-year result or whether the prior-year figure was restated.
QHow should the team handle the explanation of the factor change and its effect on comparability?
Reveal model answer →Hide answer ↑They should identify the factor change, explain why it was made, and state whether it affected the current-period result, the prior-period figure, or both. If the change altered comparability, the note should make that clear in straightforward terms. A reader should be able to tell whether the movement is due to a real operational change or simply a different calculation basis.
Why this matters · When a factor set changes, explain both the reason for the switch and its effect on the numbers people compare year to year.
For Scope 3, the team has estimated several categories using secondary data because supplier data were incomplete. The draft disclosure says only that 'data quality is acceptable', even though some categories rely on broad industry averages and others on more specific shipment records.
QWhat judgement should the preparer make about the level of detail to give on data quality for these indirect emissions estimates?
Reveal model answer →Hide answer ↑If the quality of the indirect-emissions data is relevant to understanding the estimate, the note should say so and describe the main limitations and strengths in the data used. That could include where the team relied on broad averages, where more specific records were available, and how those differences affect confidence in the result. A generic statement that the data are 'acceptable' does not help a reader assess the reliability of the estimate.
Why this matters · Where indirect-emissions data quality matters, describe the main strengths and weaknesses of the data used, not a vague overall label.
Framework references
Relevant IFRS / ISSB requirements and related disclosures
Available framework references and nearby disclosures relevant to preparing this requirement.
Primary
Related & explore
FAQ
Questions this page answers
How do I prepare disclosure s2-29-a-iii in practice using this page?+−
Start with the plain-language explainer, then work through the step-by-step preparation section and the datapoints list. The page is set up to help you move from source data to a draft disclosure and an assurance-ready evidence pack.
What data do I need to collect for s2-29-a-iii before I draft the disclosure?+−
The page points you to year-on-year changes, the boundary and consolidation basis, calculation factors, key inputs and assumptions, drivers of change, and any Scope 3 quality notes. Use those as your minimum data checklist before drafting.
How should I set the boundary and consolidation basis for s2-29-a-iii?+−
The page flags boundary and consolidation basis as a required datapoint to prepare, so you should document the scope you are using and keep that consistent through the draft and evidence pack. The workbook is there to help you capture that information in a structured way.
What methodology details should I record for s2-29-a-iii calculations?+−
The page tells you to capture calculation factors used, key inputs and assumptions, and the drivers of change. That gives reviewers enough context to understand how the numbers were built and what changed year on year.
Who should own the data for s2-29-a-iii in my organisation?+−
The page does not assign roles, but it is designed for sustainability/ESG managers, HR or data owners, and assurance reviewers to use together. In practice, ownership should sit with the people who can explain the source data, assumptions, and evidence behind the disclosure.
What should go into the evidence pack for s2-29-a-iii assurance readiness?+−
The page includes an evidence pack with five items to support assurance readiness, alongside six assurance claims to verify. Use those materials to show the claim, the risk, and the evidence trail for each point you are relying on.
What are the common mistakes to avoid when drafting s2-29-a-iii?+−
The page has a section on common reporting gaps and mistakes, so it is worth checking your draft against that before sign-off. A practical way to use it is to compare your numbers, boundary, assumptions, and narrative against the page’s preparation checklist.
How do I use the workbook and printable library card for s2-29-a-iii?+−
The Download Centre includes a Prep & Assurance workbook in .xlsx format and a printable Library Card in .pdf format. Use the workbook to organise the disclosure inputs and evidence, and the library card as a quick reference while drafting or reviewing.
Can I use the synthetic example on the s2-29-a-iii page as a template for my own disclosure?+−
Yes, but only as a synthetic illustration of how a draft can be structured. The example is there to show the style of narrative, the kind of table that may be useful, and how the content-index line can be written.
How does the ESRS E1 correspondence help me with s2-29-a-iii?+−
The page notes ESRS E1 (Climate Change) as the closest correspondence, which can help you think about reuse of data and supporting material. It does not say the requirements are identical, so treat it as a cross-reference rather than a one-to-one mapping.
More questions this page can help with
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