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KeprinGroup

Representative Case Studies

How the work
actually runs.

Five worked assessments across cement and steel under the EU Carbon Border Adjustment Mechanism. Each sets out the data as it arrived, what the audit found in it, the method applied, and the evidence left behind.

The case studies presented on this page are simulated industrial assessments developed using representative plant data. They are intended to demonstrate EcoSetu's methodology, analytical capabilities and approach to CBAM compliance. Plant names, operational datasets and commercial information have been anonymised for privacy.

5 case studiesCement · 3Iron and Steel · 2Practice · EcoSetu
Case Study 01CementIntegrated clinker and cement production
Simulated industrial assessment

Reconstructing a defensible CBAM emissions baseline

A plant that had supplied Europe for years, with production data that had never been kept for carbon.

Production route
Integrated clinker and cement
Plant capacity
2.20 Mt clinker/yr
Clinker production
1,780,000 t
Cement production
2,410,000 t
EU-bound cement exports
164,000 t
Assessment period
2025 baseline, 2026 CBAM preparation

The situation

The plant had been supplying cement to European customers but had never maintained its production data specifically for CBAM. When its EU customer requested embedded-emissions information, the plant supplied a spreadsheet containing annual coal consumption, annual electricity consumption, clinker production, cement production and total cement dispatched.

At first glance the information appeared sufficient. It was not. The initial data review identified inconsistencies between the plant's production, procurement and finance records.

Data as first reported

ParameterPlant-reported figure
Clinker production1,780,000 t
Cement production2,410,000 t
Coal consumption278,600 t
Petcoke consumption36,400 t
Alternative fuel41,800 t
Electricity212 GWh
EU cement exports164,000 t
Reported emissions intensity0.694 tCO₂e/t cement

Data-quality findings

  1. 01Fuel duplicationApproximately 7,600 tonnes of fuel appearing in the monthly procurement ledger had already been included in kiln consumption records.
  2. 02Alternative fuel classificationThe plant had reported all alternative fuel as fossil-derived. The dataset did not distinguish between fossil fraction, biomass fraction and waste-derived material.
  3. 03Electricity allocationOne electricity meter covered clinker production, cement grinding, packing and captive utilities. No allocation methodology existed.
  4. 04Production reconciliationCement dispatch data did not reconcile with the production database.
  5. 05Process emissionsThe original calculation focused heavily on fuel combustion and did not adequately document the plant's process-emissions methodology.

Step 01. Installation boundary

  1. Raw material preparation
  2. Kiln and precalciner
  3. Clinker
  4. Cement grinding
  5. Packing
  6. Dispatch

Reconstruction

  1. 02Fuel reconciliationProcurement records were reconciled against weighbridge records, kiln logs, monthly inventory and laboratory records.
  2. 03Alternative fuel classificationThe alternative-fuel stream was separated into its relevant fractions and treated according to the applicable CBAM methodology.
  3. 04Electricity allocationPlant electricity consumption was separated between the relevant production processes instead of applying the entire electricity bill to cement production.
  4. 05Production reconciliationClinker production, cement production, internal transfers and dispatches were reconciled to establish a consistent production dataset.
  5. 06Emissions calculationThe emissions model was rebuilt using fuel quantities, fuel emission factors, process-emissions data, electricity consumption, production quantities and product allocation.

Final assessment

Plant's original figure
0.694
Reconstructed baseline
0.731

tCO₂e per tonne of cement. The result was higher, not lower. That was intentional. The objective was not to produce a smaller number. It was to produce a defensible one.

Deliverables

  • Installation boundary document
  • Fuel reconciliation
  • Electricity allocation methodology
  • Production reconciliation
  • Emissions calculation workbook
  • Product-level emissions allocation
  • Data-gap register
  • Evidence register
  • CBAM reporting data pack
  • Verification-readiness checklist

Outcome

The plant moved from an unsupported emissions estimate to a structured emissions dataset capable of being taken through the appropriate CBAM verification and reporting process.

A credible CBAM assessment does not make the emissions number smaller. It makes the number traceable.

Case Study 01 · Cement · Simulated industrial assessment. Representative plant data. No client is identified.

Case Study 02CementIntegrated cement plant, Portland and blended products
Simulated industrial assessment

The clinker factor was driving CBAM exposure

One average emissions intensity applied to three products with materially different clinker content.

Production route
Integrated cement plant
Cement production
2.65 Mt/yr
Clinker production
1.92 Mt/yr
EU exports
218,000 t
Products
Portland and blended cement

The situation

The plant initially treated all cement shipped to Europe identically. Its internal calculation effectively multiplied total cement shipped by an average plant emissions intensity. This ignored a critical difference between its products.

The plant sold high-clinker Portland cement, medium-clinker blended cement and low-clinker blended cement. The product mix therefore mattered.

Product portfolio

ProductEU volumeClinker content
Portland Cement96,000 t91.0%
Blended Cement A74,000 t68.0%
Blended Cement B48,000 t52.0%

The plant's original CBAM spreadsheet used one average emissions intensity for all three.

Product-level mapping

  1. CN code
  2. Product
  3. Production route
  4. Clinker content
  5. Relevant emissions
  6. Specific embedded emissions

The major finding

The plant's highest-carbon product was also the product representing the largest share of its EU commercial exposure.

The question was therefore not how much CO₂ the plant emits. It was which products are creating the greatest CBAM exposure.

Layer one. Operational decarbonisation

  • Kiln thermal efficiency
  • Alternative-fuel substitution
  • Raw-meal optimisation
  • Process control
  • Reduction of fossil fuel dependency

Layer two. Product optimisation

  • Increase appropriate supplementary materials
  • Optimise clinker factor
  • Develop lower-carbon cement formulations
  • Map each product separately for CBAM purposes

After product-level allocation

ProductIndicative emissions intensity
Portland Cement0.784 tCO₂e/t
Blended Cement A0.584 tCO₂e/t
Blended Cement B0.466 tCO₂e/t

The plant average of 0.716 tCO₂e/t cement was not representative of any single product. These are simulated plant values, not official EU default values.

Deliverables

  • Product-level CBAM matrix
  • Clinker-factor analysis
  • Product emissions model
  • CBAM exposure dashboard
  • Product optimisation roadmap
  • Data requirements for future verification

Outcome

The plant gained the ability to rank its exposure by product: Portland cement highest, Blended Cement A medium, Blended Cement B lowest.

This allowed management to connect CBAM to product mix, production strategy and commercial strategy as a single chain rather than four separate conversations.

Carbon compliance is not only an emissions problem. It is also a product-mix problem.

Case Study 02 · Cement · Simulated industrial assessment. Representative plant data. No client is identified.

Case Study 03CementIntegrated cement plant
Simulated industrial assessment

The kiln was not the only problem

Management wanted to start with an electricity project. The hotspot analysis said otherwise.

Clinker production
1,460,000 t
Cement production
1,980,000 t
EU exports
132,000 t
Reported intensity
0.758 tCO₂e/t

The situation

Management believed the plant's CBAM problem was straightforward: kiln emissions are high, so reduce coal. A preliminary assessment confirmed the kiln was indeed carbon intensive. The data then revealed several additional problems.

Data as first reported

ParameterReported
Coal221,500 t
Petcoke28,200 t
Alternative fuel19,600 t
Electricity176 GWh
Clinker1,460,000 t
Cement1,980,000 t
Reported intensity0.758 tCO₂e/t

Data audit

  1. 01Fuel NCV inconsistencyCoal consumption was being converted using a single assumed calorific value. Laboratory records showed significant monthly variation.
  2. 02Alternative fuelThe plant was reporting quantity but not consistently maintaining the supporting characteristics required for emissions calculations.
  3. 03Kiln downtimeFuel consumption during startup and shutdown periods had not been separated from normal production.
  4. 04ElectricityGrinding electricity represented a much larger proportion of total electricity associated with cement than management had assumed.
  5. 05Clinker factorThe plant had several cement products with materially different clinker contents.

Approach

  1. 01Correct the dataEstablish a baseline before proposing any capital expenditure.
  2. 02Identify emissions hotspotsAttribute emissions to source rather than to assumption.
  3. 03Rank reduction opportunitiesOrder interventions by verified impact, not by visibility.
  4. 04Calculate implicationsTranslate each intervention into financial and CBAM terms.

Hotspot analysis

SourceContribution to emissions
Process emissions54%
Kiln fossil fuels38%
Electricity6%
Other2%

Management had been considering a major electricity optimisation project first. Electricity accounted for 6 per cent. The priority was reversed.

Recommended roadmap, in order

  • Alternative-fuel substitution
  • Kiln thermal efficiency
  • Process optimisation
  • Clinker-factor optimisation
  • Electricity optimisation

Illustrative reduction scenario

Baseline
0.758
Modelled target
0.682

tCO₂e per tonne of cement, a reduction of 0.076. At 1.98 Mt cement production that represents an illustrative reduction potential of approximately 150,500 tCO₂e per year. This is a scenario model, not a claimed achieved reduction.

Deliverables

  • Corrected emissions baseline
  • Hotspot analysis
  • Ranked reduction opportunities
  • Quantified decarbonisation roadmap
  • CBAM exposure linkage

Outcome

The plant received a quantified decarbonisation roadmap rather than a generic instruction to become more sustainable.

The roadmap linked technical intervention to emissions reduction, CBAM exposure, commercial value and future compliance readiness.

The right decarbonisation project is the one that attacks the largest verified emissions source first.

Case Study 03 · Cement · Simulated industrial assessment. Representative plant data. No client is identified.

Case Study 04Iron and SteelElectric arc furnace, casting and rolling
Simulated industrial assessment

Reconstructing a broken production boundary

Four departments, four datasets, and a billet figure lower than finished steel.

Production route
EAF, continuous casting, rolling
Finished steel
620,000 t/yr
EU exports
86,000 t

The situation

The environmental department reported 0.418 tCO₂e per tonne of finished steel. The finance department reported a completely different production volume. The rolling department maintained its own electricity records. The EAF department maintained another spreadsheet. Nobody had created a single production-flow model.

Billet production was lower than finished steel. This was not physically impossible, because the plant also purchased external billets. But those purchased billets had not been separated from internally produced billets.

Data as first reported

ParameterReported
Scrap purchased671,000 t
Liquid steel601,000 t
Billet produced575,000 t
Finished steel620,000 t
Electricity468 GWh
Natural gas21.8 million Nm³
Electrodes1,540 t

Stream A. Internal production

  1. Scrap
  2. EAF
  3. Liquid steel
  4. Casting
  5. Billet

Stream B. Purchased precursor

  1. Purchased billet
  2. Rolling
  3. Finished steel

The critical finding

The plant had been combining EAF production and purchased billet rolling into a single emissions denominator. This distorted its product-level emissions calculation.

The correction was structural rather than arithmetic: the installation had to be resolved into three reporting layers before any figure could be calculated.

Three reporting layers established

  • Installation 1. EAF and steelmaking
  • Installation 2. Continuous casting
  • Installation 3. Rolling

Data reconciliation

MetricOriginalCorrected
Finished steel620,000 t617,400 t
Internal billet575,000 t572,800 t
Purchased billetNot separated44,600 t
Electricity468 GWh452 GWh
Natural gas21.8m Nm³20.9m Nm³

Revised working intensity

Original unsupported figure
0.418
Reconstructed baseline
0.447

tCO₂e per tonne of finished steel. Again the number became higher. That was not a failure. It meant the plant finally had a number it could explain.

Deliverables

  • Installation boundary map
  • Material balance
  • Energy balance
  • Product mapping
  • CBAM emissions model
  • Purchased precursor mapping
  • EU shipment reconciliation
  • Evidence register
  • Data-gap report
  • Verification preparation pack

Outcome

The plant moved from a spreadsheet-based carbon estimate to an installation-level emissions accounting system.

The resulting dataset could be provided to the EU customer as part of the producer's CBAM information package, subject to the applicable verification requirements. CBAM records for actual emissions must be sufficiently detailed to allow verification and regulatory review.

Before calculating carbon, establish exactly what was produced, where it was produced, and which emissions belong to it.

Case Study 04 · Iron and Steel · Simulated industrial assessment. Representative plant data. No client is identified.

Case Study 05Iron and SteelElectric arc furnace
Simulated industrial assessment

From a number with no file behind it to a CBAM-ready system

The producer said 0.52. The importer asked where 0.52 came from. There was no answer.

Production route
Electric arc furnace
Steel production
890,000 t/yr
EU exports
118,000 t

The situation

The plant's EU customer had requested actual emissions data. The producer responded that its steel emissions were approximately 0.52 tCO₂e per tonne. No calculation file was available. No installation boundary was documented. No evidence register existed. No production-route mapping had been prepared.

The EU importer therefore faced a basic question: where did the 0.52 figure come from?

Records requested

  • Scrap purchase records
  • DRI and HBI records
  • Electricity bills and production meters
  • EAF logs
  • Natural gas records
  • Electrode consumption
  • Oxygen consumption
  • Casting records
  • Rolling records
  • Production reports
  • EU shipment records

Data findings

  1. 01Invoice-based electricityElectricity consumption had been calculated from invoices rather than production meters.
  2. 02Non-production loadThe electricity dataset contained an estimated 6.8 per cent non-production consumption.
  3. 03Combined loadsEAF electricity and rolling electricity were combined.
  4. 04Unmapped precursorPurchased DRI and HBI was not consistently mapped to the finished products.
  5. 05Departmental mismatchProduction data from the rolling department did not reconcile with the casting department.
  6. 06Premature roundingThe original emissions intensity had been rounded to two decimal places before product allocation.

Reconstructed dataset

ParameterCorrected value
Steel production884,600 t
Electricity612 GWh
Natural gas16.7 million Nm³
Scrap input702,000 t
DRI and HBI126,000 t
Electrodes2,180 t
EU exports118,000 t

Revised working intensity

Management estimate
0.520
Reconstructed baseline
0.563

tCO₂e per tonne. The increase came from corrected electricity allocation, inclusion of previously omitted production-related energy, improved material-flow allocation and a corrected production denominator.

Decarbonisation roadmap

  • Electricity optimisation: furnace optimisation, reduced idle time, improved charge mix, operational control
  • Renewable electricity, evaluated against CBAM requirements and evidence criteria
  • Material optimisation of the scrap and DRI mix against quality, energy, cost and emissions
  • Production efficiency: heat losses, idle furnace time, yield losses, unnecessary reheating

Illustrative scenario

Baseline
0.563
Potential target
0.475

tCO₂e per tonne, a reduction of 0.088. At 884,600 tonnes annual production that is approximately 77,800 tCO₂e per year. This represents a modelled reduction scenario, not an achieved project result.

Deliverables

  • 01. Installation profile: production route, boundaries and responsible personnel
  • 02. Production flow: raw materials, EAF, casting, rolling, finished products
  • 03. Energy inventory: electricity, natural gas and relevant energy streams
  • 04. Emissions calculation: direct and applicable indirect emissions
  • 05. Product allocation: specific embedded emissions by relevant product
  • 06. Evidence register: source documents supporting each major input
  • 07. Data gap register: missing information and corrective actions
  • 08. Verification preparation: documentation structured for the subsequent process

Outcome

The plant moved from saying it estimated its emissions at 0.52 tonnes, to being able to present its installation, its production route, its source data, its methodology, its calculation, its product allocation and the evidence supporting each major input.

That is the difference between an emissions estimate and a CBAM-ready emissions system.

An emissions number without a file behind it is not data. It is an opinion with a decimal point.

Case Study 05 · Iron and Steel · Simulated industrial assessment. Representative plant data. No client is identified.

EcoSetu’s Approach

The same seven steps, on every assessment.

The plants differ. The sequence does not. It is what makes the output reproducible rather than a matter of opinion.

01

Understand the installation

Production route, boundaries, products and processes.

02

Reconstruct the data

Fuel, electricity, raw materials, production and dispatch.

03

Identify the gaps

Missing data, inconsistent records, incorrect allocations and unsupported assumptions.

04

Calculate

Direct emissions, applicable indirect emissions, product allocation and specific embedded emissions.

05

Benchmark

Compare the plant's position against applicable CBAM reference and default values, and identify exposure.

06

Improve

Identify the highest-impact operational and product-level decarbonisation opportunities.

07

Prepare the evidence

Create the documentation required to support the CBAM data through the appropriate reporting and verification process.

Representative Case Studies

The case studies presented on this page are simulated industrial assessments developed using representative plant data. They are intended to demonstrate EcoSetu's methodology, analytical capabilities and approach to CBAM compliance. Plant names, operational datasets and commercial information have been anonymised for privacy.

Your installation will not match any of these exactly.

It rarely does. Tell us what you are actually facing and we will tell you honestly whether it is work we should take.

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