Costs#

Implementation status: Production economics block Partial (fuel and removal costs). CASCADE’s Cost page is additionally implemented in full — all 22 governing equations, including the effective cost per MJ \(\hat{C}\), the relative-cost decomposition \(\tilde{C}\) for all five strategies, marginal abatement cost \(MAC_{stype}\), and the per-payload-distance costs \(\Delta C^{mass}/\Delta C^{pax}\) on the engine’s own RTK/RPK denominators from payload.ts — standalone under DL-134; the production path still emits the legacy absolute series. CASCADE states no currency year for its cost inputs (COST_CURRENCY_NOTE). Source: src/engine/cascade.ts:computeLCA (economics block), src/engine/removals.ts:offsetBlend (removal costs), src/engine/fuel-costs.ts (Workstream-B 2050 stacks), src/engine/cost-model.ts (full CASCADE cost model, DL-134), src/engine/cost-series.ts Test evidence: tests/fuel-costs.spec.ts, tests/removal-capacity.spec.ts, tests/suite-h-cost-context.spec.ts, tests/sbatch-cost.spec.ts

Fuel costs and breakeven oil price#

Jet-A1 cost per tonne is crude plus crack spread, with a carbon adder:

\[C_{jet} = (p_{oil} + 12) \times 7.74, \qquad C_{jet,tot} = C_{jet} + p_{CO_2} \times 3.16\]

($/bbl → $/t via 7.74 bbl/t; 3.16 tCO₂ per tonne of fuel at the displayed rate convention; defaults oil $85/bbl, CO₂ $30/t). The LH₂ energy-equivalent cost uses the LHV ratio (120 / 43.2 MJ/kg):

\[C_{LH_2} = \frac{p_{H_2}\,[\$/\mathrm{kg}] \times 1000}{120 / 43.2}, \qquad C_{LH_2,carbon} = p_{CO_2} \times 3.16 \times \frac{CI_{LH_2,del}}{CI_{JetA1,WTW}}\]

and the breakeven oil price solves for cost parity including the CI-scaled carbon adder:

\[p^{*}_{oil} = \frac{C_{LH_2} + C_{LH_2,carbon} - C_{jet,carbon}}{7.74} - 12\]

A five-bucket ASK cost comparison (oil $60–200/bbl) evaluates per-ASK costs for Jet-A1, Jet-A1+CO₂, SAF, LH₂ and LH₂+SC (superconducting discount 0.8 %/pt of SC gain) — used to read off the first year LH₂ beats Jet-A1.

Removal costs and MACC-like output#

Removal costs follow the learning curves on Carbon Offsets & Removals (\(C_k(y)\)), and the engine reports the capacity-constrained total spend ($B/yr) and the weighted-average $/tCO₂. HyFlux does not construct a full marginal abatement cost curve (MACC); the per-pathway cost/capacity pairs and the blended average are the MACC-like output currently surfaced.

Workstream B — 2050 fuel-cost stacks#

fuel-costs.ts (DL-033) reconstructs 2050 component cost stacks per fuel in 2024 US$/GJ (LHV), each component a triangular {low, central, high} range. Percentile combination sums component percentiles — the documented fully-correlated approximation (the dominant component of every e-fuel is the same electricity price; this honours the required correlation within each fuel and yields the widest, conservative spread). Three metrics per fuel:

\[C_{GJ} = \sum_i c_i, \qquad C_{JGE} = C_{GJ} \times 0.131354\ \mathrm{GJ/JGE}, \qquad C_{shaft} = \frac{C_{GJ}}{\eta_{prop}}\]

with \(\eta_{prop} = 0.40\) (turbine) or 0.55 (fuel-cell + superconducting LH₂ chain). The shaft renormalisation is the point of the workstream: per-gallon comparisons ignore conversion efficiency. Verified finding (§19 Q5): per jet-gallon-equivalent, e-methane ($4.83) beats LH₂ ($5.40) at p50, but per unit of propulsive output the ranking inverts — LH₂ FC+SC ($74.7/GJ shaft) beats e-methane turbine ($91.9). Disclosed Boeing 2050 anchors (Jet-A $0.89–3.72/gal, bio-CH₄ ≤ $5.44/gal, e-SAF ≤ $19.96/gal; currency year unstated by Boeing) are bracketed by the model envelopes.

Known deviations / limitations#

  • The full CASCADE cost model (22/22 equations incl. MAC and cost per tonne-km / seat-km) exists standalone (cost-model.ts, DL-134) but is not wired into computeLCA — the production output remains the legacy absolute series. Aircraft acquisition learning curves and NPV are not CASCADE-published equations and remain out of scope.

  • Electricity price inputs are triangular literature ranges ($20/40/80 per MWh), not market forecasts.

  • The percentile-sum method is the full-correlation limit (an upper bound on spread). The §7.3 prerequisite is now satisfied: the gated Monte Carlo engine (monte-carlo.ts, DL-039) draws one shared electricity-price sample per iteration to correlate the e-fuel chain (electricity ↔ H₂ ↔ e-CH₄ ↔ e-SAF), all other components independent (documented assumption), deterministic seeded PRNG; MC spreads ≤ the percentile-sum interim is asserted as a cross-method check (tests/mc-scthermal.spec.ts).

  • Carbon price is a flat user input with no trajectory.