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IFRS S2: Climate-related Disclosures·Paragraphs 29–a–iii
GHG measurement approach, inputs and assumptions
Guide pratique pour préparer cette information. Utilisez cette fiche pour identifier les données à préparer, vérifier les affirmations et organiser les preuves. Pour les exigences exactes, reportez-vous toujours à la source officielle IFRS.
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Utilisez-la avec la source officielle IFRS tant que cette révision est en cours.
Norme
IFRS S2: Climate-related Disclosures
Paragraphs 29–a–iii · 2024
Dernière révision
—
Support pédagogique LRA · Non publié ni approuvé par IFRS
Pour préparer cette information
Objet de l’information
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.
Ce support pédagogique LRA aide à préparer l’information. Pour les exigences exactes, reportez-vous toujours à la source officielle IFRS.
Avant de commencer
Avant de commencer
Une courte liste de contrôle avant de préparer cette information — cochez chaque point une fois réglé.
Préparation
Informations clés à préparer
| Champ à préparer | Ce qu’il faut recueillir | Indice de preuve | Responsable |
|---|---|---|---|
| Year-on-year changes | A clear note of what changed in the reported figure compared with the previous reporting year, including which parts of the calculation or coverage were updated. | Prior-year submission, current-year working papers, and a change log showing the revised basis. | Sustainability reporting / Finance |
| Boundary and consolidation basis | The rule used to decide which entities, sites, or activities are included in the reported total, and how that inclusion rule is applied in practice. | Group reporting policy, consolidation memo, organisational chart, and boundary mapping to the source data. | Finance / Sustainability reporting |
| Calculation factors used | The conversion or calculation factors applied to turn activity data into the reported result, including the source and version of each factor set. | Factor library, supplier or database extracts, calculation workbook, and version control records. | Sustainability reporting / Data analytics |
| Key inputs and assumptions | The main source inputs, estimates, and judgement calls used in the calculation, with enough detail to show what was measured, estimated, or assumed. | Source extracts, estimation notes, assumptions register, and calculation workbook comments. | Sustainability reporting / Operational data owners |
| Drivers of change | The specific operational or methodological reasons why the reported figure moved from the prior year, separated into real activity changes and calculation changes. | Variance analysis, management commentary, and supporting operational records for the main drivers. | Finance / Sustainability reporting |
| Scope 3 quality notes | Any short note on the reliability of the value chain data where it matters, including known gaps, estimates, or weak source data that affect confidence in the result. | Supplier data quality review, estimation log, gap analysis, and source-data assessment. | Sustainability reporting / Supply chain |
＋ Afficher les sous-éléments de s2-29-a-iii (liste de travail LRA)
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.
Comment le préparer
Set 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.
Define 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.
Gather 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.
Build 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.
Explain 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.
Check 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.
Demander les données
Request the emissions calculation pack from the carbon accounting owner
Traduisez l’information en une question métier interne, puis adaptez-la au vocabulaire de votre organisation.
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.
Demande faible
Please provide the IFRS S2 GHG measurement approach, inputs and assumptions evidence for S2-29(a)(iii).
Pourquoi elle échoue : 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.
Meilleure demande
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.
Modèle d’e-mail formel
Subject: Request for the emissions calculation pack for [reporting period]\n\nHi [name/team],\n\nWe are preparing the sustainability reporting pack and need the calculation support behind the greenhouse gas figures for [reporting period].\n\nPlease send the latest version of your emissions calculation pack, including:\n- the boundary used for the inventory and any exclusions\n- the source file or system extract used to calculate the figures\n- the emission factor set and version/date\n- the main inputs and assumptions used in the calculations\n- any changes made since [prior period]\n- the reason for those changes\n- any notes on data quality for indirect emissions, where relevant\n\nIf it is easier, you can return this in your usual template or workbook. Please also include the period covered, the owner of the file, and the date it was last updated.\n\nThis is a possible LRA training template only; please adapt it to your organisation’s own terms and check the source material before sign-off.\n\nThanks,\n[preparer name]
Version courte pour Teams / Slack
Hi [name/team] — could you share the latest emissions calculation pack for [reporting period]? Please include the boundary, source file/system, factor set/version, key inputs and assumptions, any changes since [prior period], the reason for those changes, and any data-quality notes for indirect emissions if relevant. Use your usual format if easier. Thanks.
Exemples sectoriels
Manufacturing
Contexte. A plant-based group with fuel, electricity, refrigerants, and freight data held across site logs and a carbon workbook.
Demande adaptée. Please share the latest carbon workbook for [reporting period] covering the plant boundary, site list, fuel and power inputs, refrigerant assumptions, freight estimates, factor library version, and any changes since [prior period]. Include the reason for any restatements or methodology updates.
Exemple de réponse. Attached: carbon workbook v4.2; boundary note; site list; factor library v2025.1; assumptions tab; change log showing one new warehouse added and one freight proxy replaced; reason: improved meter coverage and updated logistics data.
Financial services
Contexte. A services group with office energy, business travel, purchased goods, and supplier estimates managed by sustainability and finance.
Demande adaptée. Please send the emissions calculation pack for [reporting period] used for the office and travel inventory, including the group boundary, source extracts, factor set, assumptions for supplier and travel estimates, and any changes from [prior period]. Add notes on any indirect-emissions data gaps or proxies.
Exemple de réponse. Attached: inventory model; boundary memo; travel extract; office energy file; factor register v3; assumptions log; change note showing a switch from estimated to booked travel data for one region; data-quality note: supplier spend-based estimates still used for one category.
Rédigez votre information
Des notes qui transforment les données en information publiée
Modèles pédagogiques LRA — adaptez-les à votre organisation et vérifiez la source officielle avant validation.
Note méthodologique
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.
Note de contexte
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.
Déclaration sur les variations
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.
Entrée de l’index de contenu
s2-29-a-iii GHG measurement approach, inputs and assumptions — [location / page] / [notes]Centre de téléchargement
Outils et formulaires de préparation
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Préparation à l’assurance
Pour chaque affirmation, vérifiez les preuves
| Affirmation | Risque | Preuves à vérifier |
|---|---|---|
| We kept the coverage figure on the same basis as last year, and where we changed the basis we explained the effect clearly. | Assurer may test whether the year-on-year comparison is genuinely like-for-like, or whether a basis change has been hidden in the narrative. | Prior-year calculation file; current-year methodology note; reconciliation showing the effect of any basis change; draft-to-final review comments; sign-off confirming the comparison basis used. |
| We set out the practical method we used to build the figure, including the boundary we applied to the disclosed operations. | Assurer may probe whether the reported perimeter matches the entity’s chosen reporting boundary and whether any exclusions were deliberate and consistent. | Boundary memo; consolidation or operational control papers; list of included and excluded entities/sites; methodology paper; management approval of the boundary choice. |
| We explained why we used this approach, rather than another available method, for the disclosed figure. | Assurer may challenge whether the chosen approach was selected for convenience or to improve the result, rather than because it was the most suitable basis. | Method selection paper; options appraisal; internal emails or committee papers showing the rationale; approval records; consistency check against prior reporting decisions. |
| We described the data inputs and assumptions that fed into the calculation, so the reader can see what drove the result. | Assurer may look for missing assumptions, undocumented estimates, or inputs that were applied inconsistently across parts of the calculation. | Calculation workbook; assumption log; source data extracts; data dictionary; review notes showing each key input was traced and approved. |
| Where we changed the calculation basis, we explained what changed and why the update was made. | Assurer may test whether the explanation is complete, whether the change was intentional, and whether it has been applied consistently across the reporting period. | Change log; version history; revised methodology note; approval of the revised basis; comparison of old and new outputs showing the impact of the change. |
| For the supply-chain part of the figure, we noted the quality of the underlying data and how much came from detailed activity records or independently checked sources. | Assurer may question whether lower-quality estimates were presented as stronger evidence, or whether the mix of data types was properly disclosed. | Supplier data pack; activity-based input schedule; third-party verification statements where available; data quality assessment; summary of estimated versus directly sourced inputs. |
Dossier de preuves à préparer
Lacunes fréquentes dans les rapports
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.
Lacunes fréquentes
Erreurs à éviter lors de la collecte des données
Wrong owner, wrong languageThe 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 undefinedPeople 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 fixedOne 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 mixedActivity 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 outOriginal 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 earlyData 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 capturedThe 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 trailDraft 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 loggedYear-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 missedWhere third-party or estimated data needs a quality note, the collector skips it, leaving no record of known limitations or assumptions.
Là où un jugement professionnel est souvent nécessaire
Acquisitions and disposals during the yearState 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 activityIf 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 lineFor 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 missingWhere 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 periodIf 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 themExplain 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 amountsIf 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 dataWhen 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 periodIf 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.
Exemples
Exemples illustratifs
Synthétiques, rédigés par LRA — ils ne proviennent ni d’un rapport d’entreprise ni du texte d’une norme.
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.
Rapports d’entreprises
Comment les entreprises publient S2-29-a-iii en pratique
Exemples de pratiques de publication complètes et partielles. Ce sont des analyses fondées sur des preuves, non des modèles à recopier.
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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Essayez
Comment préparer s2-29-a-iii ?
Quelles données dois-je collecter ?
Où voir un exemple issu d’un rapport réel ?
Quelles erreurs éviter ?
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Vérifiez votre compréhension
Scénarios à travailler
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?
Afficher la réponse type →Masquer la réponse ↑
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.
Pourquoi c’est important · 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?
Afficher la réponse type →Masquer la réponse ↑
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.
Pourquoi c’est important · 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?
Afficher la réponse type →Masquer la réponse ↑
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.
Pourquoi c’est important · 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?
Afficher la réponse type →Masquer la réponse ↑
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.
Pourquoi c’est important · Where indirect-emissions data quality matters, describe the main strengths and weaknesses of the data used, not a vague overall label.
Références au référentiel
Exigences IFRS / ISSB applicables et informations connexes
Références disponibles du référentiel et informations voisines utiles à la préparation de cette exigence.
IFRS / ISSB
s2-29-a-iii
au sein de IFRS S2 : Climate-related Disclosures
Connexes et exploration
Climate-related risks and opportunities → FicheIdentification inputs and industry topics → FicheObjective →Business model and value chain impact → FicheStrategy response and transition plan → Fiche
Parcourir toutes les informations →
Plus dans IFRS S2 → Parcourir le catalogue complet → Accueil de la Bibliothèque des informations → Rechercher dans toutes les informations →
FAQ
Questions auxquelles cette page répond
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.
Autres questions auxquelles cette page peut aider
s2-29-a-iii disclosure checklist for sustainability managers2-29-a-iii year-on-year changes what evidence do I needs2-29-a-iii boundary and consolidation basis how to documents2-29-a-iii calculation factors and assumptions examples2-29-a-iii who should own the data and sign-offs2-29-a-iii assurance claims evidence pack what to includes2-29-a-iii common reporting gaps and mistakes to avoids2-29-a-iii workbook download how to use prep and assurance files2-29-a-iii printable library card pdf what is it fors2-29-a-iii synthetic example disclosure table narrative starters2-29-a-iii content index line how to drafts2-29-a-iii ESRS E1 data reuse for climate disclosure
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