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 datapoints 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 explain that our current-year figures cover the same group of operations as last year, using the same control-based boundary unless a site has been bought or sold. For the year, we updated several conversion rates and activity inputs, which changed the reported total; the main driver was a switch to more recent supplier-specific factors for purchased electricity and freight, while a small part of the movement came from revised fuel-use estimates. - Our scope 3 figures are still partly estimate-based for a few upstream categories, so we flag those areas as lower confidence and note where primary supplier data is not yet available. - The numbers below are prepared on a like-for-like basis, and the year-on-year movement reflects both the revised factors and the updated assumptions used in the calculation model.
This example shows how to describe the reporting boundary, the main calculation inputs, the reason the current year differs from the prior year, and any quality caveats for indirect value-chain data without using a tabular format.
Illustrative (synthetic) example — Retail
We report on the basis of the stores, warehouses and central functions we control during the year, so the comparison with the prior period excludes locations that were franchised out mid-year. The increase in the current period mainly reflects higher customer delivery activity and a fuller set of supplier data, while the calculation also uses updated grid factors and refreshed travel assumptions. - For indirect value-chain emissions, we still rely on spend-based estimates for some categories where supplier activity data is incomplete, and we mark those areas as less precise than the rest of the inventory. - Overall, the movement from last year is explained by the changed operating footprint, the revised factors used in the model, and the better coverage of data from logistics partners.
This example shows a different reporter describing the same kind of information in plain language: what is included in the boundary, what changed from the prior year, which factors and assumptions were used, why the figures moved, and where value-chain data remains less robust.
How companies report s2-29-a-iii
Real reports where this topic is disclosed. These are report practice, 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 provides a clear disclosure of its consolidation operational boundary approach based on operational control, with specific emissions data for Scope 1 reported on page 76. The report also includes information on inputs and assumptions used in data processes on page 196. However, the report does not clearly disclose changes versus prior years (A iii changes vs prior year) or scope 3 data quality notes, and the reasons for changes and emission factors are only partially addressed with unclear context on pages 195 and 81 respectively.
Enel Chile S.A.
Electric Utilities / IPP / Energy Traders · Chile · 2025
Enel Chile S.A.'s 2025 Integrated Annual Report references the use of the Science Based Targets initiative (SBTi) models, specifically the Sectoral Decarbonization Approach (SDA) and Absolute Contraction Approach (ACA), both certified for a 1.5°C pathway (pp. 189, 191). The report provides a quantitative figure for greenhouse gas emissions associated with energy supplies, stating 3,548,316 tons CO2 equivalent, though detailed data quality notes for scope 3 emissions are unclear (p. 352). However, the report lacks explicit disclosures on changes versus the prior year, operational boundary consolidation, emission factors, inputs and assumptions, and reasons for changes, limiting clarity on methodological specifics.
Empresas CMPC S.A.
Forest and Paper Products · Chile · 2024
Empresas CMPC S.A.'s Integrated Report 2024 provides some related context on scope 3 data quality notes on page 235, though it does not clearly disclose this datapoint. The report includes various sections on governance, material topics, and ESG indicators (pp. 236, 238), but no explicit information is found regarding changes versus prior year, consolidation operational boundary approach, emission factors, or reasons for changes. Inputs and assumptions are also not clearly disclosed, indicating gaps in detailed methodological transparency for this disclosure.
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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
Related framework references
How this disclosure maps across the major reporting frameworks.
Primary
Related & explore
FAQ
Questions this page answers
How do I prepare disclosure s2-29-a-iii using the page’s step-by-step guidance?+−
Use the page’s plain-language explainer and step-by-step preparation section to turn the disclosure into a working plan. It points you to the datapoints to gather, the evidence pack to build, and the draft-output section so you can move from source data to a first draft.
What data do I need for s2-29-a-iii before I start drafting?+−
The page says to prepare year-on-year changes, the boundary and consolidation basis, calculation factors, key inputs and assumptions, drivers of change, and any quality notes on Scope 3 data. Those are the core inputs it expects you to assemble before drafting.
How should I set the boundary and consolidation basis for s2-29-a-iii?+−
The page flags boundary and consolidation basis as one of the datapoints to prepare, so you should document the scope used for the disclosure and keep that explanation with the supporting evidence. The page does not give a fixed method, so use the approach described in your own reporting process and evidence pack.
What calculation factors and assumptions should I capture for s2-29-a-iii?+−
The page specifically asks for calculation factors used, key inputs, and assumptions. In practice, that means recording what sits behind the numbers so the draft can be traced back to source data and reviewed during assurance.
Who should own the data for s2-29-a-iii in my team?+−
The page does not assign roles, but it is designed for sustainability/ESG managers, HR or data owners, and assurance reviewers to use together. A practical approach is to have the relevant data owner prepare the inputs, with the ESG lead coordinating the draft and the reviewer checking the evidence pack.
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 keep the claim, the risk, and the supporting evidence together so a reviewer can follow the trail from draft to source.
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 meant to help you spot weak or missing parts before sign-off. Use it as a pre-submission check against your draft, evidence pack, and assumptions.
How do I use the workbook and printable library card for s2-29-a-iii?+−
The Download Centre provides a Prep & Assurance workbook in .xlsx format and a printable Library Card in .pdf format. Use the workbook to organise the preparation and assurance steps, and the PDF as a quick reference while drafting or reviewing the disclosure.
Can I use the synthetic example disclosure on the s2-29-a-iii page as a draft template?+−
Yes, as a synthetic illustration only. The page includes example disclosures, including a quantitative table, to show how the disclosure can be presented and how the narrative starters and content-index line can be used in a draft.
How can I turn the s2-29-a-iii data into a first draft narrative?+−
The page’s draft-output section gives visualisation ideas, narrative starters, and a content-index line. Use those to convert your prepared data and notes into a readable draft, then check it against the evidence pack and the common gaps list.
Is the data I prepare for s2-29-a-iii reusable for ESRS E1 (Climate Change)?+−
The page says ESRS E1 (Climate Change) is the closest correspondence, so there is a cross-framework link to consider. It does not say the requirements are identical, but it does indicate that some of the data you prepare may be reusable across reporting needs.
More questions this page can help with
s2-29-a-iii disclosure checklist for ESG managers2-29-a-iii what evidence do I need for assurances2-29-a-iii workbook download how to uses2-29-a-iii boundary and consolidation basis explaineds2-29-a-iii calculation factors and assumptions templates2-29-a-iii scope 3 quality notes what to includes2-29-a-iii year-on-year changes how to drafts2-29-a-iii common reporting gaps and mistakess2-29-a-iii evidence pack items for reviews2-29-a-iii narrative starters and content index lines2-29-a-iii from company reports exampless2-29-a-iii ESRS E1 data reuse
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