Many companies and investors want a simple benchmark to judge whether a greenhouse gas (GHG) inventory is "reliable" or "complete". In practice, quality cannot be guaranteed by citing a single framework or standard. It depends on how thoroughly the methods are applied, how transparent the boundary-setting is, and how credible the underlying data and governance are.
Automated and AI-assisted carbon calculators have made GHG accounting more accessible, but not necessarily more accurate. Many of these tools carry disclaimers such as "AI can make errors; use with caution", a reminder that automation does not replace professional judgement.
Likewise, when companies calculate in-house or through consultants, they often state that the inventory was prepared "with reference to" or "in accordance with" the GHG Protocol. From a professional standpoint, such phrases do not automatically guarantee robustness, nor do they mean the inventory meets the Protocol's full intent.
GreenCo, an ESG advisory firm established in 2016, shares the following professional guidance for assessing the quality of Scope 3 disclosures, at a time when auto-generated numbers risk becoming the norm. Scope 3 reporting is now required or expected under IFRS S2, the HKEX climate requirements and Singapore's climate reporting regime, so its quality matters more than ever.
1) Start with Relevance Screening: Which of the 15 Categories Are Covered?
Scope 3 emissions are divided into 15 categories: 8 upstream and 7 downstream. The GHG Protocol expects companies to screen all categories for relevance, using criteria such as:
- Size – the expected magnitude of emissions
- Influence – the company's ability to affect or reduce those emissions
- Risk – exposure to regulatory, market or reputational risk
- Stakeholder interest
- Data availability and quality
A credible disclosure should clearly explain:
- Which categories are included and which are excluded
- The rationale for each decision
- The screening results, supported by screening logic, thresholds and evidence
- No generic blanket statements such as "excluded because it is immaterial"
Red Flags
- Categories marked "not relevant" despite clear relevance (for example, a retailer excluding Purchased goods and services, or a food and beverage company excluding Waste generated in operations).
- Categories excluded with no documented screening analysis or rationale.
- Double counting or obvious omissions (for example, a fuel company reporting Use of sold products as "N/A").
Acceptable Exclusions, If Justified
It can be reasonable to exclude categories that are demonstrably not relevant to the business model. The key is evidence: a screening showing that the category's estimated emissions are trivial and do not affect decision-making or target-setting.
2) Review Boundary and Scope Definitions
After identifying relevant categories, the next quality indicator is whether organisational and operational boundaries are properly defined and applied. Look for:
- Organisational boundary – whether the inventory follows an equity share, financial control or operational control approach, applied consistently to subsidiaries, joint ventures and franchises.
- Value chain boundary – whether relevant upstream and downstream partners are included in data collection.
- Reporting period and currency consistency – whether activity data match the reporting year, and whether financial data used in spend-based methods are adjusted for exchange rates and inflation.
- Avoided emissions – whether these are kept separate, clearly labelled and not netted against Scope 3 totals.
3) Assess Methodological Robustness, Beyond the Name of the Standard
Citing the GHG Protocol is the beginning, not the end. A professional review should examine how rigorously the methodology has been implemented:
- Data hierarchy – evaluate the share of primary versus secondary data:
- Best: supplier-specific primary data (measured, metered or process-level).
- Good: activity-based secondary data (physical quantity × emission factor).
- Basic: spend-based estimates using sector averages.
- Emission factors – check named sources, version numbers, geographies and publication years (for example, UK DEFRA/DESNZ conversion factors or ecoinvent, with the version stated).
- Allocation rules – for multi-output processes, whether allocation follows consistent, transparent rules (mass, energy or economic value).
- Sampling – if suppliers or sites are sampled, whether the methodology defines sample frames, representativeness, confidence intervals and scaling logic.
- Updates and restatements – if methods or emission factors change, whether prior-year figures are restated with an explanation.
4) Scrutinise Exclusions and Justifications
The quality of a disclosure depends as much on what is excluded as on what is included. When reviewing justifications, consider:
- Relevance screening evidence – has the company documented why categories were deemed not relevant, using GHG Protocol criteria?
- Counter-examples – if obvious activity contradicts an exclusion, raise a red flag.
- Resource limitation claims – assess whether limited resources or data are a temporary technical challenge or a management choice. For financially strong companies, repeated use of "resource limitation" may indicate a lack of prioritisation rather than a real constraint.
- Confidentiality claims – rarely valid except in national security or highly sensitive trade contexts; aggregated or anonymised disclosure is usually still possible.
5) Industry-Specific Quality Signals
Each sector has its own Scope 3 risk profile. Watch for sectoral alignment, for example:
- Apparel and retail – Category 1 (Purchased goods and services) usually dominates; credible inventories include supplier-specific data and material-processing impacts.
- Food and beverage – agricultural emissions (land-use change, enteric fermentation) and upstream logistics are key; treatment of biogenic CO₂ and CH₄ should be clearly disclosed.
- Technology hardware – capital goods and upstream manufacturing are often major sources; check regional electricity factors and the treatment of yield and scrap.
- Oil, gas and energy – downstream Use of sold products is typically material; exclusions require very strong justification.
- Financial institutions – financed emissions (Category 15, investments) are usually the most significant; look for PCAF-based methods and data quality scores.
6) Human Oversight in the Age of Automation
AI and automation can help with data collection and estimation, but they cannot replace professional judgement. Companies using automated tools should demonstrate:
- Human verification of AI outputs
- Error-checking procedures
- Documentation of assumptions and decision logic
Automation without oversight risks producing numbers that look precise but are methodologically weak.
Conclusion
High-quality Scope 3 reporting is not about perfection, nor about citing a standard. It is about transparency, credibility and continuous improvement. A company earns trust when it can clearly explain what is covered, how relevance was determined, which data sources were used and how it plans to improve over time.
Starting with partial coverage (for example, selected sites or supplier samples) is acceptable only with a clear plan, milestones and visible year-on-year improvement. Done well, Scope 3 disclosure is not just a compliance task but a strategic management tool that links supply chain, investment and innovation decisions with climate strategy.
Appendix: Standard Questions to Ask Companies
- Which categories are excluded and why? Please share your quantitative screening.
- For Category 1, what percentage of spend or volume is covered by supplier-specific data?
- What are your primary emission factor sources and versions?
- How do you allocate emissions for multi-output processes?
- Have methods or factors changed since last year? What was restated?
- What controls and quality assurance steps do you use? Is any part externally assured?
- How are automation and AI outputs reviewed by people?
- What is your two-year plan to increase primary data coverage and supplier participation?
Related reading: Climate Risk Disclosure and GHG Calculation · GHG Emissions Calculation Services
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