GHG Protocol · ESRS E1 · General

Scope 3 Emissions Estimator
for General

Estimate Scope 3 across the 15 GHG Protocol categories — spend-based to activity-based — with category screening for ESRS E1-6 and a data improvement narrative limited assurance reviewers will accept.

GHG PROTOCOL · LIVEv2026.04ESRS E1 · IFRS S2

Scope 3 emissions, documented.
Not just estimated.

Session
0x252D
Sector
All
Categories
0 / 15
scope3.conf
categories.csv
README.md
01// engagement— GHG Protocol Ch. 3
02entity_name=
03reporting_period=
04currency=
05sector=
08// scope_3_categories— GHG Protocol Table 5.1
09selected=none
★ = typically material for All sectors (median). Missed: cat. 1, 2, 4, 6, 7.
27// materiality_and_exclusions— GHG Ch.6 · ESRS 1.133
Relevance tests performed for each Scope 3 category (GHG Ch.6):
28
29
30
31
32
33
35exclusion.rationale=
Materiality + exclusions (GHG Ch.6 + ESRS 1.133)
38// data_quality_and_sources— GHG Ch.7 · data hierarchy
Data-quality hierarchy applied:
39
40
41
42
43
44
45data_sources.narrative=
Data quality + sources (GHG Ch.7)
48// intensity_metrics— GHG Ch.9 · ESRS E1-5
49revenue_millions_eur=MEUR
50num_employees=FTE
51prior_year_scope3=tCO2e
52scope1_total=tCO2e
53scope2_total=tCO2e
Intensity metrics (GHG Ch.9 / ESRS E1-5)
56// sector_benchmark— CDP 2023 median · tCO2e/M€
Enter revenue (above) to compare against the All sectors (median) sector median (120 tCO2e/M€).
Sector benchmark · CDP 2023 median
60// sensitivity— ±25% total emissions
Enter activity data to see sensitivity analysis.
Sensitivity · ±25% scenarios
65// risk_warnings— ISSA 5000 / ISAE 3410 · rule engine
Enter activity data to run risk analysis.
Risk warnings · rule engine (ISSA 5000)
70// disclosure_and_conclusion— IFRS S2.29 · ESRS E1-6
Tick disclosure items addressed in FS / sustainability report:
71IFRS S2.29(a)(iii) · ESRS E1-6
72ESRS E1-6(58)
73IFRS S2.29(a)(iv) · ESRS E1-6(62)
74ESRS E1-6(63)
75GHG Protocol Ch.6 · ESRS E1-6(57)
76ESRS E1.45
77ESRS E1-6(54)
78ESRS 1.89
79ESRS E1-4
80ESRS E1-1
81ESRS 1.81
82ESRS 1.133
84prepared_by=
85reviewed_by=
99conclusion.narrative=
Disclosure + conclusion · IFRS S2.29 + ESRS E1-6
awaiting input·0 categories · 2 fieldsEUR·ESRS E1 · IFRS S2
previewscope3-wp-2026.pdf
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Scope 3 emissions estimation for General

On most CSRD first-year files we work, Scope 3 is 70%+ of the carbon footprint and the weakest part of the disclosure. Not because the emissions are absent — they sit in supplier spend, freight invoices, employee commuting surveys, and the use phase of sold products. They are absent from the file because category screening happened late, spend-based factors got applied uniformly, and no one documented why this entity has Categories 1, 6 and 7 material rather than Categories 4, 9 and 11. ESRS E1-6 requires the gross Scope 3 number broken out by significant category. ESRS E1-7 requires the reduction plan that connects to it. Limited assurance under ISAE 3410 looks at both, plus the data improvement narrative — and that narrative is what most files miss.

The practical difficulty begins with category screening. Not all 15 categories will be material for every entity. GHG Protocol guidance recommends screening each category for size (estimated share of total Scope 3), influence (the entity's ability to reduce emissions), data availability, and stakeholder interest. Most entities find that two to four categories account for 80% or more of their Scope 3 total. For a services firm, Category 1 (purchased goods and services), Category 6 (business travel), and Category 7 (employee commuting) typically dominate. For a manufacturer, Category 1, Category 4 (upstream transport), Category 9 (downstream transport), and Category 11 (use of sold products) carry the weight. Spending time on immaterial categories wastes effort that should go toward improving data quality on the categories that matter.

A common assurance finding is that entities apply spend-based emission factors uniformly without documenting why they chose spend-based over activity-based methods. Spend-based methods (using economic input-output factors like those from DEFRA, ADEME, or the US EPA's EEIO model) are acceptable as a starting point, but they carry high uncertainty. Activity-based methods (using physical quantities like kWh, kg, or tonne-km paired with process-level emission factors) produce far more reliable estimates. Assurance providers under ISAE 3410 expect entities to demonstrate a data improvement plan, showing progression from spend-based to activity-based methods over reporting cycles. Another frequent finding is double counting between Scope 1 or Scope 2 and Scope 3 Category 3 (fuel and energy related activities not included in Scope 1 or 2). Entities that do not reconcile these boundaries produce inflated totals that do not survive limited assurance procedures.

When applying this estimator, start by listing your entity's five largest spend categories and mapping them to GHG Protocol categories. Run the screening criteria on each category, document your materiality rationale, then select the estimation method that matches available data. For spend-based estimates, use the most jurisdiction-appropriate emission factors (DEFRA for UK entities, ADEME for French, GEMIS for German). Record the factor source, vintage year, and any assumptions about currency conversion or inflation adjustment. Where supplier-specific data exists (energy bills, transport manifests, waste transfer notes), switch to activity-based calculation for those line items. This hybrid approach gives you defensible numbers that improve as your data collection matures.

Frequently asked questions: General

Which Scope 3 categories should a first-time CSRD reporter prioritise?
Start with Category 1 (purchased goods and services), which is almost always the largest category for any entity. Then screen Category 4 (upstream transport), Category 6 (business travel), and Category 11 (use of sold products) based on your business model. GHG Protocol Technical Guidance recommends screening all 15 categories for size and influence, but focusing estimation effort on the categories that represent 80% or more of your expected Scope 3 total.
Can we use spend-based emission factors for CSRD compliance?
Yes, ESRS E1 does not prescribe a specific calculation method, and spend-based factors are accepted as a starting point. DEFRA, ADEME, and the US EPA EEIO model all publish spend-based factors. However, assurance providers under ISAE 3410 will expect you to document the limitations of spend-based approaches and show a plan for transitioning to activity-based data where categories are material. The uncertainty range on spend-based factors can exceed plus or minus 50%.
How do we avoid double counting between Scope 2 and Scope 3 Category 3?
Category 3 covers upstream emissions from fuel and energy that are not already captured in Scope 1 (direct combustion) or Scope 2 (purchased electricity, heat, steam). This includes transmission and distribution losses for purchased electricity, upstream extraction and refining of fuels you burn on site, and upstream emissions from electricity that enters the grid. Map each fuel and energy line item to the correct scope boundary first, then calculate Category 3 as the residual upstream component only.
What documentation do assurance providers expect for Scope 3 estimates?
At a minimum, document your category screening rationale (why each category is or is not material), the estimation method chosen per category, the emission factor source and vintage year, all assumptions about allocation and data gaps, and a data quality improvement plan. ISAE 3410 paragraph 12 requires the practitioner to assess whether the quantification methods are suitable. If you cannot explain why you chose a particular factor or method, the assurance provider will raise it as a finding.

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