By: Johannes Fiegenbaum on 5/26/25, 10:05 AM · Last updated September 5, 2026
Marginal abatement cost curves (MACCs) have evolved from static planning tools into dynamic instruments for strategic decarbonisation. With falling technology costs, integration with internal carbon pricing, and application across supply chains, MACCs help companies prioritise emissions reductions whilst optimising ESG investments.
A marginal abatement cost curve (MACC) visualises the cost-effectiveness of different technologies and measures to reduce carbon emissions. Each bar represents a specific abatement measure, with bar height indicating marginal cost per tonne of CO₂ equivalent (€/tCO₂e) and bar width showing emissions reduction potential. The curve arranges measures from lowest cost to highest cost, left to right, giving decision-makers an immediate view of where to invest first and where to plan for the long term.
You will encounter the same tool under several names, and they all refer to the same thing. MACC, MAC curve, marginal abatement curve and plain abatement cost curve are used interchangeably in corporate practice, consultancy reports and academic literature. Where a distinction is drawn at all, MAC curve tends to describe the underlying cost function, while MACC refers to the stepped bar chart most companies actually build. For practical purposes, treat them as the same instrument. Costs are quoted per tonne of CO₂ equivalent, written as €/tCO₂e or $/tCO₂e depending on the reporting currency; this guide uses euros, but the method is identical in dollars or any other currency.
Measures below the horizontal axis generate net savings (negative abatement costs), whilst those above require net investment. This structure makes MACCs the most intuitive tool available for identifying where to start on a decarbonisation journey, and for building investment cases that finance teams can immediately understand and benchmark against capital allocation frameworks.
MACCs matter strategically because they translate complex climate science into financial language. Rather than framing decarbonisation as a cost burden, a well-constructed MACC reveals the economic logic of each intervention, separating quick wins from longer-term bets and allowing organisations to sequence action rationally across time horizons.
According to the World Bank, approximately 50% of emission reductions in core sectors can be achieved at zero or negative net cost, which makes early identification of these opportunities a strategic priority for any organisation developing a transition plan under CSRD or pursuing science-based targets.
Reading a marginal abatement cost curve requires understanding three dimensions:
Bar Height: Represents abatement cost in €/tCO₂e. Positive values indicate additional costs; negative values signal net savings from reduced energy or operational costs.
Bar Width: Shows annual CO₂e reduction potential. Wider bars represent measures with greater emissions reduction capacity.
Bar Area: Height multiplied by width equals total annual cost or saving, enabling direct financial comparison across measures.
Many established measures, renewable energy, efficiency upgrades, and heat pumps, now sit on the left side of the curve with significantly lower marginal costs than a decade ago. Solar PV costs alone have fallen more than 80% since 2010. This creates substantial opportunities to achieve near-term reductions that simultaneously cut operational costs, making the business case for early action stronger than at any previous point in the energy transition.
The three structural elements of any MACC determine how useful it is as a decision tool:
X-Axis (cumulative abatement potential): Running left to right, the x-axis represents cumulative CO₂e reductions achievable as each successive measure is implemented. It shows how far along the decarbonisation pathway a given portfolio of measures takes the organisation, critical for understanding whether current plans are sufficient to meet a science-based or regulatory target.
Y-Axis (marginal abatement cost): The vertical axis expresses the net cost or saving per tonne of CO₂e abated. An internal carbon price overlaid as a horizontal line separates "no-regret" investments (below the line) from measures requiring additional strategic justification (above it). Aligning this threshold with EU ETS price projections helps finance teams apply a consistent and defensible investment hurdle rate.
Bar Width (reduction potential): Each bar's width quantifies the specific emissions reduction achievable from a measure annually, expressed in tCO₂e. Wider bars signal higher-impact interventions, useful for identifying which measures move the needle most on absolute targets, and for prioritising supplier engagement when Scope 3 abatement options are included in the analysis.
Sector-level benchmarks allow organisations to sense-check cost estimates, identify outliers, and build investment cases that can withstand scrutiny from finance committees and ESG auditors. The figures below draw on published project data and European market cost studies. Treat them as directional guidance and validate against project-specific quotes before making capital allocation decisions.
| Measure | Sector | Cost (€/tCO₂e) | Reduction Potential | Notes |
|---|---|---|---|---|
| Energy efficiency (LED, insulation) | Manufacturing | -80 to -20 | Medium | Negative cost = net saving |
| On-site solar PV | Manufacturing / Retail | -40 to 0 | Medium-High | Depends on roof area and irradiation |
| Fleet electrification | Transport / Logistics | 0 to 80 | High | Total cost of ownership improving rapidly |
| Heat pump installation | Buildings | -30 to 40 | Medium | Economics sensitive to gas price |
| Process electrification | Heavy Industry | 50 to 200 | High | High capex, long payback |
| Green hydrogen | Heavy Industry | 150 to 400 | High | Costs falling; not yet commercially mainstream |
Negative-cost measures should almost always be implemented first, they pay organisations to decarbonise, and the savings generated can directly subsidise higher-cost interventions later in the roadmap. Sequencing your investment programme to harvest these savings early, then reinvesting them into higher-cost abatement, is the core financial logic behind any credible multi-year transition plan.
Because the ranking depends on prices that move, it is worth re-checking the carbon price assumption behind the curve before every capital round. Current EU ETS prices, green bond volumes and reporting benchmarks are maintained in the Fiegenbaum Atlas and updated automatically.
Constructing a corporate MACC requires systematic data, a structured measure inventory, and consistent cost calculations. The following condensed framework is applicable to organisations of any size.
Document all greenhouse gas emissions across Scope 1 (direct), Scope 2 (purchased energy), and material Scope 3 categories using the GHG Protocol Corporate Standard. Choose a baseline year representative of normal operations, avoid years distorted by shutdowns, acquisitions, or exceptional production cycles. The accuracy of your MACC depends entirely on the quality of this foundation.
Generate a longlist of at least 10 bis 15 technically feasible measures per scope. For each, calculate capital costs (procurement, installation), operating costs or savings (energy, maintenance), and opportunity costs (capital foregone from alternative investments). Convert all figures to net present value using a consistent discount rate, then express as €/tCO₂e. Obtain at least two supplier quotes per measure to avoid single-source bias. Also quantify co-benefits such as improved air quality or reduced energy price exposure, as excluding them systematically overstates the true cost of action.
Arrange measures in ascending cost order from left to right. Plot each as a bar, height = €/tCO₂e, width = tCO₂e/year. Overlay your internal carbon price as a horizontal threshold. Colour-code by scope or business unit for stakeholder presentations. Use the prioritised view to sequence implementation and build investment cases. Update the curve every two years, or immediately after significant changes in energy prices, carbon policy, or organisational structure.
Three errors consistently undermine MACC quality and the decisions based on them:
Using an unrepresentative baseline year: A baseline distorted by the COVID-19 pandemic, a major acquisition, or an unusual production cycle will skew all subsequent cost and reduction calculations, making future targets look either too easy or too difficult. Under CSRD, baseline data is subject to external assurance, so credibility matters from the outset. Where a single year is unrepresentative, use a multi-year average or restate the baseline after significant structural changes and document the rationale transparently.
Applying static pricing assumptions: Building a MACC using today's energy and carbon prices without modelling how inputs may evolve produces a curve accurate only at the moment of analysis. Solar PV costs fell by more than 90% between 2010 and 2024. Run at least two or three price scenarios and flag which measures are robust across all of them versus those whose attractiveness depends on a specific assumption.
Restricting analysis to Scope 1 and 2: For companies with complex supply chains, Scope 3 typically represents 70 bis 90% of total emissions. Excluding it can cause the MACC to miss the highest-impact abatement opportunities available. Supply chain switching and material substitution may appear expensive in isolation on a Scope 1/2 curve, but represent decisive levers when viewed as a share of total footprint. Including Scope 3 also future-proofs the analysis against tightening regulatory expectations: CSRD already requires material Scope 3 disclosures, and science-based target methodologies increasingly demand supply chain engagement as a condition of approval.
MACCs serve multiple strategic functions beyond regulatory compliance. When integrated with internal carbon pricing, they create a clear financial threshold: measures below the internal price qualify as no-regret investments, whilst those above require strategic justification aligned with EU ETS trajectories and science-based targets. The expansion of EU ETS 2 to buildings and transport from 2028 further extends this market mechanism, increasing the financial relevance of MACC analysis for organisations in those sectors.
For CSRD transition plan disclosures, MACCs provide the analytical backbone for demonstrating that emissions reduction targets reflect thorough, costed analysis. The European Sustainability Reporting Standards (ESRS) require disclosure of capital expenditure for climate transition, MACCs quantify those investment needs measure by measure, giving sustainability and finance teams a shared language for capital allocation discussions. Dynamic, scenario-based MACCs further allow companies to demonstrate how their abatement portfolio performs under different carbon price trajectories, which CSRD mandates when assessing strategy resilience.
A McKinsey study found that implementing approximately 500 decarbonisation measures could achieve 50% emission reductions by 2030, with average costs of just 1% of total revenue, reinforcing that the financial case for systematic MACC-based planning is strong and that the perceived cost barrier to climate action is far lower than most organisations assume.
To make the methodology concrete, here is a stylised MACC for a typical mid-cap Maschinenbau-site (500 bis 2.000 employees, 50.000 tCO₂/yr Scope 1+2 baseline) under 2025/26 German conditions. Energy prices reflect post-2024 spreads, the EU-ETS price band sits at 70 bis 110 €/tCO₂, and all paybacks are calculated after BEG-EM grants (up to 40 % for energy-efficient manufacturing, up to 55 % for process-heat decarbonisation) and the 30 % Wachstumsbooster super-deduction introduced by the Growth Booster Act on 11 July 2025.
The measures are grouped into three decision buckets, a structure popular in German Mittelstand decarbonisation playbooks because it maps cleanly onto board-level capital-allocation decisions:
| Bucket | Measure | €/tCO₂ | tCO₂/yr saved | Cumulative | Source |
|---|---|---|---|---|---|
| A | IE4 motors + VFD retrofit | -80 | 2,000 | 2,000 | Fraunhofer ISI 2022, Agora Industry 2024 |
| A | Heat recovery on process exhaust | -60 | 4,500 | 6,500 | Agora Industry 2024, dena 2024 |
| A | Building envelope: LED, HVAC, insulation | -50 | 1,250 | 7,750 | Agora Energiewende 2023, Fraunhofer ISE |
| B | Rooftop PV (self-consumption) | +0 | 2,500 | 10,250 | Fraunhofer ISE 2024, BMWK PV-Strategie |
| B | Light-duty EV fleet | +60 | 1,000 | 11,250 | Fraunhofer ISI 2024 |
| B | Low-temp industrial heat pump (60 bis 120 °C) | +80 | 2,500 | 13,750 | Agora Industry 2024, Fraunhofer IEG 2024 |
| B | Biogas / biomass fuel switching | +100 | 4,000 | 17,750 | UBA, Fraunhofer ISI |
| B | High-temp industrial heat pump (120 bis 200 °C) | +130 | 1,250 | 19,000 | Fraunhofer IEG 2024, IEA |
| C | Green H₂ for high-temp process heat (>500 °C) | +250 | 5,000 | 24,000 | Fraunhofer ISI 2024, BMWK Klimaschutzverträge |
| C | Carbon capture (post-combustion, residual) | +300 | 10,000 | 34,000 | Agora Industry, Klimaschutzverträge 2026 |
Reading this MACC: the first three measures alone (Bucket A) abate roughly 7.750 tCO₂/yr at negative cost, i.e. they generate net cash flow after fuel-cost savings, BEG-EM grants and the Wachstumsbooster super-deduction. Bucket B extends abatement to ~19.000 tCO₂/yr (38 % of baseline) at 0 bis 150 €/tCO₂, comfortably below the projected 2030 EU-ETS price corridor. Bucket C, green hydrogen for high-temp process heat and post-combustion CCS, covers the remaining 15.000 tCO₂/yr but at 250 bis 300 €/tCO₂, which only pencils out under Germany's 15-year Klimaschutzverträge (carbon contracts for difference) launched for the 2026 funding round.
Compared with McKinsey's 2020 Costs and potentials of GHG abatement in Germany, the 2025/26 picture differs in three important ways: (1) negative-cost measures expand significantly because higher gas and CO₂ prices increase the savings side; (2) industrial heat pumps shifted from "post-2030" technologies into the 0 bis 150 €/tCO₂ band thanks to the EnEfG framework and 55 %-subsidies for process-heat decarbonisation; (3) green hydrogen and CCS remain meaningfully more expensive than McKinsey-2020 modelled, because electrolyser costs and CO₂ logistics have fallen more slowly than expected. Always rebuild your MACC on real load profiles and current Förderkulisse, the curve shifts every 12 bis 18 months as energy prices and subsidy schemes evolve.
Use the same weighted average cost of capital the company applies to any other investment, and apply one rate to every lever on the curve. A separate, lower rate for climate projects makes them look cheap by construction and breaks comparability with the rest of the capital budget.
Annualise capital expenditure over the technical lifetime of each measure rather than over a uniform period, because a long-lived heat pump and a short-lived lighting retrofit carry very different annual charges. State the rate next to the chart, and where it is contested internally, run the curve at two rates and report which measures change bucket.
Match the horizon to the target the curve has to serve, usually the interim target year of the science-based pathway rather than the net-zero date, because a horizon running to net zero pushes every hard lever into a distant band where no one has to decide anything.
Use the current financial year as the start year, not the emissions baseline year. The two are deliberately different: the baseline year fixes the emissions denominator, the start year fixes when capital is spent and which energy and carbon prices apply. Mixing them is the most common reason a curve cannot be reconciled with the finance plan. Measures whose technical life runs past the horizon are still annualised over that full life.
Both, for different purposes, and never for the same tonne. The carbon cost the company already pays belongs inside the cost function: for an installation covered by the EU ETS, allowances no longer surrendered are a cash saving in exactly the way avoided gas is.
The price not yet paid belongs on a horizontal reference line, either as an internal carbon price or as a forward assumption for a sector entering the system later. The line answers which measures clear the hurdle; the cost function answers what a measure actually costs. Counting the same tonne in both places is double counting and it flatters the middle of the curve, so label which bars carry a carbon cost inside them.
Set that reference line against projected EU ETS developments and review it as prices rise and technology costs fall: measures below it are no-regret investments, measures above it need a justification grounded in regulatory risk or long-term competitiveness.
No. The curve ranks abatement, offsets compensate for what is left, and putting both on one axis lets a cheap certificate outrank a real reduction. Keep offsets and unbundled renewable energy certificates off the bars.
If their price matters to the decision, draw it as a second reference line, after the curve rather than inside it. That ordering also matches how a transition plan is read: reduction first, compensation for the remainder. The distinction is set out in more detail in the guide to CO₂ reduction versus compensation.
Physically yes; on paper it depends on which Scope 2 convention the curve is built on. Under market-based accounting a fully renewable tariff already reports the electricity footprint at or near zero, so an efficiency measure shows almost no reduction and falls off the curve. Under location-based accounting the same measure still abates at the grid emission factor.
Build the curve on the location-based figure and note the market-based effect separately. Otherwise the supply contract quietly deletes the whole negative-cost block, which is the part of the curve that funds everything to the right of it.
In practice there is none: both describe the same instrument for ranking abatement measures by cost per tonne of CO₂ equivalent. Where authors do distinguish, MAC curve refers to the underlying marginal cost function and MACC to the stepped bar chart built from it, with bar height showing cost and bar width showing abatement potential. Abatement cost curve and marginal abatement curve are further variants of the same term.
MACC analysis is the process of building and interpreting a marginal abatement cost curve to prioritise carbon reduction measures. You plot each measure by its cost per tonne of CO₂e (bar height) and its reduction potential (bar width), ordered from cheapest to most expensive. The analysis shows which measures pay for themselves, where cost-effective abatement runs out, and how much total reduction is achievable at a given carbon price. It turns a long list of decarbonisation options into a ranked, budget-aware investment plan.
Marginal abatement cost is the net cost of reducing one additional tonne of CO₂e with a given measure. The simple formula is: marginal abatement cost = (annualised cost of the measure minus annual energy or operating savings) divided by annual tonnes of CO₂e avoided. A negative result means the measure saves money while cutting emissions, a no-regret move that sits below the zero line on the MACC.
A MACC model is the underlying calculation, usually a spreadsheet, that holds one row per abatement measure with its investment cost, operating cost, expected lifetime, annual savings and annual abatement volume. The chart is only the output. Because the ranking depends entirely on the assumptions in that model, discount rate, energy price path and measure lifetime should be documented alongside the curve.
Yes, and those measures are the most important part of the chart. Bars below the zero line represent measures with a negative marginal abatement cost, typically efficiency improvements whose energy savings exceed their annualised cost. They reduce emissions and improve the bottom line, which makes them the obvious starting point. If your curve shows no negative bars at all, the model is probably ignoring avoided energy costs.
Extend the MACC beyond direct operations by developing collaborative analyses with key suppliers. Progressive companies work with vendors to identify cost-effective abatement opportunities throughout the value chain, shifting focus from purely technical measures to business model innovations, material substitution, supplier development programmes, and contract structures that incentivise low-carbon production. For detailed guidance, see the Scope 3 accounting guide.
Review and update at least every two years, or immediately following a significant change in energy prices, carbon policy, technology costs, or organisational structure. The value of a MACC lies not in a one-time analysis but in a structured process that improves with each iteration. Organisations that revisit their curves regularly develop a progressively more accurate and strategically useful tool.
Marginal abatement cost curves provide the analytical foundation for credible, costed decarbonisation planning. By revealing which measures save money, which require investment, and which deliver the greatest emissions impact, MACCs transform climate strategy from aspiration into actionable roadmap. The most effective MACC programmes are treated as living tools, updated as energy prices shift, technology costs fall, and regulatory requirements evolve, rather than one-time studies that gather dust after the initial workshop.
As CSRD requirements intensify, EU ETS prices rise, and stakeholders demand ever more transparent transition plans, organisations with robust MACC programmes will be better positioned to allocate capital efficiently, engage investors and customers credibly, and achieve science-based targets on time. The companies that start building and iterating on their MACCs now will have a material competitive advantage when deeper decarbonisation commitments become unavoidable across every sector.
Ready to build your own MACC or integrate carbon pricing into your climate strategy? Contact Fiegenbaum Solutions to get started.
ESG and sustainability consultant based in Hamburg, specialised in VSME reporting and climate risk analysis. Has supported 300+ projects for companies and financial institutions, from mid-sized manufacturers to major banks and insurers.
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