Live Instrument
GTF Fleet Exposure Calculator
Enter any fleet size and replacement scenario. Get the same exposure methodology used in the SMBC/JSA and Spirit briefs, generated live - CO2, CO2e, and certified non-CO2 pollutant deltas, each labeled by how solid the underlying number is.
Methodology
Two layers, kept deliberately separate.
Layer 1 - CO2 & CO2e
Annualized, fleet-wide. A fuel-burn penalty (16-20%, from published OEM/industry range) applied to each aircraft's estimated annual baseline fuel burn, then converted to CO2 via IATA's 3.16 kg CO2/kg fuel factor. CO2e applies published non-CO2 multipliers on top - an approximation of total climate effect, not a regulatory figure.
Layer 2 - Certified pollutants
Per-aircraft, per-landing-takeoff-cycle deltas taken directly from the ICAO Engine Emissions Databank (v32), comparing the grounded neo engine against two certified ceo alternatives. Scaled by an estimated annual cycle count. No fleet-wide assumption beyond that scaling - this is what the certificates say, multiplied by how often a cycle happens.
Why kept apart: Layer 1 estimates a climate-cost number a lessor or insurer prices risk on. Layer 2 is a local air-quality effect (NOx, HC, CO, soot) at airport level - a different exposure category, with different regulation, and it stays in absolute mass rather than being folded into CO2e. Certified numbers are never blended with estimated ones into a single unlabeled figure.
Field correction
This model's core assumption doesn't hold in every portfolio.
What this calculator assumes: that grounded capacity gets backfilled with older ceo-generation aircraft, producing a fuel-burn and emissions penalty.
What at least one credit risk practitioner reports actually happened: in one portfolio affected by the Spirit Chapter 11 process, no ceo backfill occurred. Instead, a tripartite agreement between the airline, Pratt & Whitney, and Spirit's estate allowed engine "green time" to be used, secured priority restoration slots for 2026-2027, and saw affected aircraft either re-leased to other operators (where the engine wasn't powder-metal affected) or torn down. Freed-up capacity was absorbed directly by market demand rather than replaced with older, less efficient airframes. The credit impact in that case came from a different mechanism entirely: some aircraft returned below book value, a direct accounting loss unrelated to the fuel-burn/emissions pathway modeled here.
Teardown has also occurred earlier than usual in some cases, driven by spare-engine lease demand rather than airframe economics: with demand for spare GTF engines high, some airframes have been stripped, parted out or sold, with the engines leased separately at a value exceeding the aircraft itself. Not the common outcome, and highly case-by-case, but a real pattern alongside re-leasing and restoration.
This doesn't invalidate the ceo-backfill scenario as one possible outcome across a fleet this size - it means the calculator's default assumption should be treated as one scenario among several, not the confirmed mechanism. Whether ceo-backfill, re-leasing, or teardown dominates likely depends on engine type, spare part availability, and each lessor's specific negotiating position - not a single global pattern.
02. Layer 1 - CO2 & CO2e exposure
Annualized climate-cost exposure for the selected fleet.
CO2, tonnes/year (physical)
CO2e, tonnes/year (mid-case CO2 × published non-CO2 multiplier)
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×1.23 · Johansson et al. 2025
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×1.63 · Lee et al. 2020/21
Baseline fuel burn per aircraft: estimated, pending independent validation
03. Layer 2 - Certified pollutant deltas
Fleet-scaled NOx, HC, CO and nvPM, per scenario.