Marginal Abatement Cost Curves

What a Marginal Abatement Cost Curve Is

A marginal abatement cost curve (MACC) is a decision-support visualisation that ranks a set of emission-reduction measures by their cost-effectiveness. Each measure becomes a rectangular block. The blocks are sorted from cheapest to most expensive per tonne of CO₂e avoided and laid side by side, producing a stepped curve that rises from left to right. The tool originates in energy-system economics and became a mainstream corporate and policy instrument after consultancy and IEA/IPCC modelling work popularised it for climate-mitigation planning.

Unlike a GHG inventory, which measures what an organisation emitted, a MACC is forward-looking: it models what could be avoided, at what price, relative to a defined baseline. It is the analytical bridge between an inventory and a decarbonisation plan — it turns a list of possible actions into a prioritised sequence.

The two axes

Every MACC has the same axes, and understanding them is most of the battle:

The area of each block (width × height) approximates the total net cost — or net saving — of deploying that measure over the appraisal period. Blocks below the zero line represent measures that pay for themselves; blocks above it represent net costs.

Marginal versus average cost

The word “marginal” matters. The height of each block is the cost of the last — or representative — tonne abated by that measure, not the average across the whole programme. This matters because the curve is meant to answer “should we do the next thing?” rather than “what did the whole plan cost on average?” Confusing marginal with average cost is the single most common conceptual error, and it systematically understates the cost of the most ambitious measures on the right of the curve.

Why the “curve” is really a step function

A MACC is not a smooth line — it is a series of discrete steps, one per measure. The smoothness in glossy published versions is a rendering choice, not economics. Treating it as a continuous function invites the false impression that abatement is infinitely divisible at the margin, when in reality each measure is a lumpy, capital-committing decision with a fixed potential.

The Cost Concept: What “Marginal Abatement Cost” Actually Measures

The vertical axis is where MACCs live or die. A cost per tonne is only comparable across measures if every measure’s cost is bounded and discounted the same way. Three decisions define that boundary.

Cost boundary: capex, opex, and avoided costs

The marginal abatement cost of a measure nets three flows over its lifetime: the up-front capital expenditure, the change in operating costs, and any avoided costs — chiefly energy or fuel savings, but also avoided maintenance, avoided carbon-price liability, or avoided regulatory penalties. A heat-pump retrofit, for example, carries high capex, higher electricity opex, but avoided gas cost; whether its net cost per tonne is positive or negative depends entirely on which of those flows the analyst chose to include.

Illustrative composition for a single measure. Whether the net result lands above or below zero on the MACC is decided by which flows enter the boundary — not by the technology itself.

The negative-cost “no-regret” region

Many published MACCs show a block of measures below the zero line — actions that both cut emissions and save money over their life. The classic examples are lighting upgrades, insulation, and efficiency controls. The economic puzzle is obvious: if these measures are genuinely profitable, why has the market not already deployed them?

Levelised versus annualised framing

Costs can be expressed as a levelised cost over the measure’s lifetime or annualised into an equivalent yearly figure. Corporate MACCs almost always annualise, because it lets a five-year controls upgrade sit on the same axis as a twenty-year building fabric retrofit. Annualising requires a capital recovery factor, which is where the discount rate enters — covered in the formula below.

The Core Formula

A MACC is built one measure at a time. For each candidate measure, the analyst computes two numbers — its marginal cost per tonne and its annual abatement potential — then sorts and stacks. Everything else is bookkeeping.

Annualised cost of abatement

The capital recovery factor is the mechanical heart of the calculation and the reason two analysts can produce different curves from identical technology data. A £100,000 measure with a 20-year life costs about £6,700/yr at a 3.5% discount rate but about £11,700/yr at 10% — a 75% swing in annualised cost, and therefore in the height of the block, driven purely by the financing assumption.

Abatement potential per measure

Sorting and cumulative construction

Once every measure has a (MAC, abatement) pair, construction is three steps:

1. Sort all measures by MAC, ascending (most negative first).
2. Place each block on the x-axis starting where the previous block ended — the left edge of block k is the sum of the abatement of blocks 1 through k−1.
3. Draw each block at height = its MAC, width = its abatement. The resulting staircase is the MACC.

Discount Rate, Baseline, and Time Horizon

These three parameters are set once for the whole curve and silently determine its shape. A MACC that does not disclose them is not auditable.

Discount-rate sensitivity

Because the discount rate feeds the capital recovery factor, it reshapes the entire cost axis. Capital-heavy measures (renewables, deep retrofit) are penalised at high discount rates; opex-heavy or fuel-saving measures are relatively favoured. The chart below shows the same illustrative £100,000, 20-year, 500 tCO₂e/yr measure priced at three commonly used rates.

Baseline (business-as-usual) definition

Abatement is always measured against a counterfactual. If the baseline assumes the grid decarbonises on its own, an electrification measure abates less (because the avoided emissions shrink over time). If the baseline freezes today’s grid factor, the same measure appears to abate more. The baseline is not a technical detail — it is the denominator of every abatement figure on the curve, and it should be defined with the same rigour a target baseline is defined under the SBTi Corporate Net-Zero Standard.

Static versus dynamic MACCs

Measure Interactions and Ordering Effects

The clean assumption behind a static MACC — that each measure’s cost and abatement are independent of every other measure — is almost always false. Two interaction problems dominate.

Overlap and double-counting

If you both insulate a building and install a heat pump, the heat pump abates less than it would in an uninsulated building, because there is less heat demand to decarbonise. Counting each measure’s abatement in isolation double-counts the overlapping tonnes and overstates the total. Rigorous MACCs compute each measure’s abatement conditional on the measures ranked ahead of it, which changes both its width and its position.

Sequencing dependence

Because abatement is conditional, a measure’s marginal cost can change depending on what precedes it. Insulation-first versus heat-pump-first can produce different curves from the same measure set. This is why the ordering is not a cosmetic sort applied at the end — in a properly constructed dynamic MACC, the ranking and the costing are solved together.

MACC Variants

“MACC” covers several methodologically distinct constructions. Choosing the wrong variant for the decision at hand is a common failure.

Reading a MACC for Decisions

A MACC answers different questions depending on the horizontal line you overlay on it. Three decision lenses cover almost every use.

The carbon-price lens connects the MACC directly to internal carbon pricing: the marginal cost of the last tonne needed to hit a target is, in effect, the shadow price that target justifies. It also connects to carbon-tax liability and offset pricing — any tonne whose abatement cost exceeds the offset price is a candidate for offsetting rather than in-house abatement, subject to the usual hierarchy of abating before offsetting.

Worked Example: A Corporate MACC

A fictional single-site manufacturer screens six measures against a common cost boundary, a 7% discount rate, and a fixed baseline year. All figures below are illustrative and fixed for the worked example — real MACCs use site-specific appraisals, not reference values.

Sorting by MAC and building the cumulative curve gives the deployment order and the shape below. The x-position of each block is the running total of abatement to its left.

Block width ∝ annual abatement; label shows marginal cost. The two negative-cost measures (LED, controls) sit at the far left as the no-regret starting point; battery storage on the right is the most expensive tonne in the set. Total interaction-unadjusted potential: 1,240 tCO₂e/yr.

Carbon-Price Benchmarks for the Cost Axis

The most decision-relevant overlay on a MACC is a carbon price. Two reference families are worth anchoring against: a market compliance price and a scenario-consistent shadow price. Both are surfaced live from the GreenCalculus MasterBrain.

The EU Emissions Trading System average allowance price gives a real, observed compliance benchmark. The current live reference for the EU ETS average annual EUA price is 64.76 €/tCO₂ [GreenCalculus reporting.eu_ets.price.eua_average_eur_per_t.2024 · EU ETS EEA EU ETS Report 2025/06 §1.2 · v2026.284] (secondary-market annual average, source EU ETS). Any measure on the worked-example curve with a marginal cost below this line is cheaper than surrendering an allowance for the same tonne.

For forward-looking planning, NGFS scenario shadow prices give a carbon-price trajectory consistent with a defined transition pathway. Under the NGFS Phase 5 Net Zero 2050 scenario, the MESSAGEix-GLOBIOM model puts the 2030 shadow carbon price at 256.835 US$/tCO₂ [GreenCalculus reporting.ngfs.carbon_price.messageix_globiom.net_zero_2050.world.2030 · NGFS 2024] (real 2010 USD, weighted-global, source NGFS Phase 5). Model choice moves this materially — the GCAM model gives a lower figure for the same scenario and year — so the model must be stated whenever an NGFS price is used as a MACC overlay.

Governance, Integrity, and Common Failure Modes

A MACC is a persuasive object — a single chart that appears to settle the whole prioritisation question. That persuasiveness is exactly why its assumptions must be governed. The checklist below is the pre-flight for any MACC presented to a board, an investor, or an auditor.

A MACC that discloses its cost boundary, discount rate, baseline, and interaction treatment is an audit-grade decision tool. One that hides them is a marketing chart with error bars the width of the page.

Where the MACC Sits in the Workflow

The MACC is the decision layer between the inventory and the plan. Upstream, it depends on a completed GHG inventory to define the baseline and the emission factors. Downstream, it feeds three workflows:

• Target delivery. The curve identifies the least-cost bundle that reaches a reduction target and the marginal cost of the last required tonne, informing the trajectory in a net-zero pathway and the ambition set under the SBTi Corporate Net-Zero Standard.
• Internal carbon pricing. The implied marginal cost of hitting a target is a natural anchor for a shadow price used in capital appraisal — see internal carbon pricing.
• Abate-versus-offset decisions. Measures whose marginal cost exceeds the prevailing offset price or carbon-tax liability are candidates for offsetting the residual — within a mitigation hierarchy that abates first. Specific measure classes, such as switching to lower-carbon inputs, are appraised in the material substitution methodology.

Frequently Asked Questions