Appendix — figure atlas

Capacity scaling atlas

Every curve below is drawn by evaluating the locked equation register across the full validated capacity window, Q = 0.1 MW → 1 GW, on log–log axes. Nothing is fitted to the picture: the lines are the same functions the workspace calls when it prices a project, so a figure and a scenario result can never disagree. Dashed lines are accepted external benchmarks, never model output.

Solid = model output · dashed = accepted external benchmark · every axis carries its unit and time basis.

Part 1

Economics of scale

Capital intensity, operating cost and output all follow power laws in Q. On log–log axes a power law is a straight line, and its slope is the scale exponent θ — the single number that decides whether a bigger plant is cheaper per kilogram.

Fig 1AInstalled CAPEX
1A Installed CAPEX by technology 10⁻¹ 10⁰ 10¹ 10² 10³ 10⁴ 10⁻¹ 10⁰ 10¹ 10² 10³ C(Q) = a · Q^θ, EUR2024, installed basis.Validity 1–1000 MW;AEL extrapolation flagged above 400 MW. Installed hydrogen-output capacity, Q (MW) Installed CAPEX (M€2024) PEM installed CAPEX (M€) AEL installed CAPEX (M€) SOEC installed CAPEX (M€)

Straight lines with slope θ < 1: doubling capacity costs less than double. SOEC sits highest because its stack is the least mature; AEL is the cheapest per installed kilowatt across the whole window.

C(Q) = a · Q^θ · [M€2024] · θ = scale exponent, dimensionless

Fig 1BSpecific CAPEX
1B Specific CAPEX (€/kW) 0.00 1.9k 3.8k 5.7k 7.6k 10⁻¹ 10⁰ 10¹ 10² 10³ c(Q) = 1000 · C(Q) / QFalling curve = economy of scale. Installed hydrogen-output capacity, Q (MW) Specific CAPEX (€2024/kW) PEM specific CAPEX (€/kW) AEL specific CAPEX (€/kW) SOEC specific CAPEX (€/kW)

The same curves normalised by capacity. This is the figure that answers 'how much cheaper does the next megawatt get?'

c(Q) = 10³ · C(Q)/Q · [€2024/kW]

Fig 1CReference OPEX
1C Reference annual OPEX 10⁻¹ 10⁰ 10¹ 10² 10³ 10⁻¹ 10⁰ 10¹ 10² 10³ O(Q) = a · Q^θ, excludes electricity.Electricity is priced separately per MWh. Installed hydrogen-output capacity, Q (MW) OPEX (M€2024/yr) PEM reference OPEX (M€/yr) AEL reference OPEX (M€/yr) SOEC reference OPEX (M€/yr)

Fixed operation and maintenance only — electricity, water and stack replacements are charged in their own engines so no cost is counted twice.

O(Q) = a · Q^θ · [M€2024/yr]

Fig 1DAnnual hydrogen output
1D Annual production 10¹ 10² 10³ 10⁴ 10⁵ 10⁶ 10⁻¹ 10⁰ 10¹ 10² 10³ m(Q) = Q · 1000 · 7884 h / SECCF = 90 % economic basis Installed hydrogen-output capacity, Q (MW) Output (t H₂/yr) PEM output (t H₂/yr) AEL output (t H₂/yr) SOEC output (t H₂/yr)

Output is exactly linear in Q — slope 1 — so every intensity indicator per kilogram is a pure ratio of the curves above to this one.

ṁ(Q) = Q·10³ · CF · 8760 / SEC · [kg H₂/yr] · SEC in kWh/kg

Fig 1ELCOH anchors
1E Reference LCOH at 100 MW 0.00 1.26 2.53 3.79 5.06PEM reference LCOH at 100 MW 4.00 €/kgAEL reference LCOH at 100 MW 3.50 €/kgSOEC reference LCOH at 100 MW 4.60 €/kg LCOH (€2024/kg H₂)

The three anchor points the engines are validated against. Any scenario that lands far from these at 100 MW indicates an input error, not a discovery.

LCOH = (CRF·CAPEX + OPEX + electricity + water) / annual kg · [€/kg]

Fig 1FSpecific CAPEX anchors
1F Specific CAPEX at 100 MW 0.00 631 1.3k 1.9k 2.5kPEM specific CAPEX at 100 MW 1.2k €/kWAEL specific CAPEX at 100 MW 720 €/kWSOEC specific CAPEX at 100 MW 2.3k €/kW €2024/kW

Point values read off Figure 1B at the reference capacity, for quick comparison against vendor quotations.

c(100 MW) = 10³ · C(100)/100 · [€/kW]

Part 2

Climate, water, land and biodiversity

Environmental loads are annualised at the environmental capacity factor and reported per year, not per kilogram, so that a 1 GW project and a 1 MW pilot can be compared on the same axis without hiding four orders of magnitude in a ratio.

Fig 2AClimate-change impact
2A Annual GWP100 by production route 10¹ 10² 10³ 10⁴ 10⁵ 10⁶ 10⁷ 10⁻¹ 10⁰ 10¹ 10² 10³ CF = 85 %; EU-27 2024 grid proxy.Slope 1: impact is linear in Q, intensity is scale-free. Installed hydrogen-output capacity, Q (MW) GWP100 (t CO₂e/yr) SMR (w = 25 %) — 2585 t CO₂e/(MW·yr) SMR + CCS, 90 % capture — 866.4 t CO₂e/(MW·yr) Methane pyrolysis, electric heat — 1258 t CO₂e/(MW·yr) PEM electrolysis, EU-27 mix — 2692 t CO₂e/(MW·yr) Unified 4-route portfolio

All four routes are straight lines of slope 1 — the carbon intensity per kilogram does not improve with size, only with cleaner electricity. That is the single most important message in this atlas.

GWP100 = Σ_g m_g · CF_g · [t CO₂e/yr] · CF_g = characterisation factor

Fig 2BWater consumption
2B Annual water consumption 10² 10³ 10⁴ 10⁵ 10⁶ 10⁷ 10⁸ 10⁻¹ 10⁰ 10¹ 10² 10³ Central curve W(Q) = 2.73e+4 · QDashed lines are per-kg benchmarks, not fits. Installed hydrogen-output capacity, Q (MW) Water (m³/yr) Lifecycle water consumption (m³/yr) Process-water floor 9 L/kg Grid electrolysis 130 L/kg

The lifecycle curve sits far above the 9 L/kg stoichiometric-plus-treatment floor because it includes the water embedded in the electricity supply.

W(Q) = w · Q · [m³/yr] · per-kg basis = W/ṁ [L/kg]

Fig 2CLand footprint
2C Land occupation and rights exposure 10⁻⁴ 10⁻³ 10⁻² 10⁻¹ 10⁰ 10¹ 10² 10³ 10⁴ 10⁵ 10⁻¹ 10⁰ 10¹ 10² 10³ Attributed land = 13.14 ha/MWExposure area is a screening proxy forownership and participation review, not a rights violation. Installed hydrogen-output capacity, Q (MW) Land (ha, and km² for exposure curves) Renewable-attributed land (ha) AWE + West-Europe PV exposure (km²) SMR total land benchmark (km²)

Land is dominated by the renewable generation attributed to the plant, not by the electrolyser hall. The SMR benchmark is roughly twenty times smaller because its energy arrives as a pipeline, not as a field.

A(Q) = a_land · Q · [ha] · exposure in km², A = π r²

Fig 2DBiodiversity endpoint
2D Annualised biodiversity loss 10⁻¹⁰ 10⁻⁹ 10⁻⁸ 10⁻⁷ 10⁻⁶ 10⁻⁵ 10⁻¹ 10⁰ 10¹ 10² 10³ PDF·yr/kg source endpoint, LC-IMPACT / GLAMcoefficient 1.812e-9 per MW Installed hydrogen-output capacity, Q (MW) PDF·yr / year Biodiversity endpoint (PDF·yr/yr)

Potentially disappeared fraction of species, integrated over a year. Reported on the source endpoint basis; production boundary only, storage and transport excluded.

B(Q) = b · Q · [PDF·yr/yr]

Part 3

Noise, annoyance and health burden

The noise chain is the one place where an impact genuinely switches on at a threshold. Below Q ≈ 3.86 MW the 55 dB(A) contour never reaches a receptor, so annoyance and DALYs are exactly zero — not small, zero. Above it the dose–response curve takes over.

Fig 3ABoundary and receptor noise level
3A Plant-boundary / receptor noise level 0.00 20 39 59 79 10⁻¹ 10⁰ 10¹ 10² 10³ 70 dB(A) hearing-loss prevention 55 dB(A) outdoor day 40 dB(A) WHO night Lp(Q,r) = 90.6 + 10·β·log₁₀(Q) − 20·log₁₀(r) − ILβ = 0.75, r in metres, IL = insertion lossdB values are not linearly addable. Installed hydrogen-output capacity, Q (MW) Noise level, dB(A) Plant-boundary level at 100 m, dB(A) At 300 m receptor, dB(A) With 10 dB barrier at 100 m

A logarithmic axis in dB would be a logarithm of a logarithm, so the level is plotted linearly against log Q — the straight line is the 7.5 dB per decade slope of the source law.

Lp(Q,r) = 90.6 + 10·β·log₁₀Q − 20·log₁₀r − IL · [dB(A)]

Fig 3BNoise benchmark ladder
3B Accepted noise benchmarks 0.00 25 50 75 100WHO night residential 40 dBEPA indoor residential / school 45 dBOil & gas residential night 50 dBEPA / WHO outdoor day 55 dBCompressor stations <300 m, night 60 dBCompressor stations <300 m, day 61 dBEPA hearing-loss prevention 70 dBElectrolysis source term, 1 m 91 dB Noise level, dB(A)

Regulatory and literature reference levels the boundary curve is judged against. These are inputs to the assessment, never outputs of it.

Benchmark set — WHO, EPA, oil & gas practice, measured electrolysis source term

Fig 3CImpacted contour area
3C Area inside the 55 dB(A) contour 10⁻³ 10⁻² 10⁻¹ 10⁰ 10¹ 10⁻¹ 10⁰ 10¹ 10² 10³ A₅₅(Q) = 1.141e-2 · Q^0.75 km²Derived by solving the source law for the55 dB(A) radius, then A = π r². Installed hydrogen-output capacity, Q (MW) Contour area (km²) ≥55 dB(A) contour area (km²)

Area grows with the three-quarter power of capacity, because sound pressure falls with the square of distance while the source term grows with Q^0.75.

A₅₅(Q) = π · r₅₅(Q)² · [km²]

Fig 3DContour area anchors
3D Contour area at reference capacities 10⁻² 10⁻¹ 10⁰ 10¹≥55 dB(A), Q = 1 MW 0.01 km²≥55 dB(A), Q = 10 MW 0.06 km²300 m exposure circle 0.28 km²≥55 dB(A), Q = 100 MW 0.36 km²≥55 dB(A), Q = 1000 MW 2.03 km² Area (km², log scale)

Point values from Figure 3C, plus the 300 m field-exposure circle used as a screening comparator.

A = π r² · [km²]

Fig 3EPersons highly annoyed
3E Noise annoyance 10⁻² 10⁻¹ 10⁰ 10¹ 10² 10⁻¹ 10⁰ 10¹ 10² 10³ Threshold Q = 3.861 MW; below it, exactly zero.P_HA = 0.1107 · (Q − Q₀)^0.8982ρ = 175 persons/km², 55 dB(A) contour. Installed hydrogen-output capacity, Q (MW) Persons highly annoyed / year Persons highly annoyed (persons/yr)

The vertical wall at 3.86 MW is physical, not numerical: it is the capacity at which the 55 dB(A) contour first extends past the plant boundary.

P_HA(Q) = ρ · ∫ %HA(L(Q,r)) dA · [persons/yr]

Fig 3FHealth burden
3F Noise-related DALY burden 10⁻⁴ 10⁻³ 10⁻² 10⁻¹ 10⁰ 10¹ 10⁻¹ 10⁰ 10¹ 10² 10³ DALY = DW · P_HA, central DW = 0.02Band spans DW = 0.01 – 0.03.Base curve excludes storage and transport. Installed hydrogen-output capacity, Q (MW) DALY / year Noise health burden (DALY/yr) Upper disability-weight band DW = 0.03 Lower disability-weight band DW = 0.01

Disability-adjusted life years from chronic high annoyance. The band is the disability-weight uncertainty, which dominates every other source of error in this indicator.

DALY(Q) = DW · P_HA(Q) · [DALY/yr] · DW dimensionless

Fig 3GDALY anchors
3G Central DALY at reference capacities 10⁻² 10⁻¹ 10⁰ 10¹Q = 10 MW central 0.01Q = 100 MW central 0.13Q = 1000 MW central 1.09 DALY/year, log scale

Even a gigawatt plant carries under one DALY per year at the central disability weight — small, but not zero, and it must be disclosed.

DALY = DW · P_HA · [DALY/yr]

Part 4

Employment, skills, safety and value added

Social indicators are reported on the project lifetime where the source defines them that way — employment in job-years, not headcount — because a headcount without a duration is not an indicator.

Fig 4AProject-lifetime employment
4A Employment, green and blue routes 10⁰ 10¹ 10² 10³ 10⁴ 10⁵ 10⁻¹ 10⁰ 10¹ 10² 10³ Direct = on-site and supply chain.Net = direct + indirect − displaced.Job-years, not simultaneous headcount. Installed hydrogen-output capacity, Q (MW) Employment (job-years / project) Green direct (job-years) Green net (job-years) Blue direct (job-years) Blue net (job-years)

The green route carries more employment per megawatt than blue at every scale, and the net curve exceeds direct because indirect activity outweighs displacement in the source studies.

J(Q) = j · Q · [job-years/project]

Fig 4BTraining and skills demand
4B Education / skills demand 10⁻¹ 10⁰ 10¹ 10² 10³ 10⁴ 10⁻¹ 10⁰ 10¹ 10² 10³ Scenario only: H_training = h_worker · job-yearsh_worker = 40 h/job-year shown for demonstration. Installed hydrogen-output capacity, Q (MW) Training demand (thousand hours / project) Green training demand (thousand h) Blue training demand (thousand h)

A scenario layer, not a measured indicator: it inherits all the uncertainty of the employment curve and adds an assumed hours-per-worker figure the user should override with local data.

H(Q) = h_worker · J(Q) · [thousand h/project]

Fig 4COccupational safety exposure
4C Fatal-accident exposure basis 10¹ 10² 10³ 10⁴ 10⁵ 10⁶ 10⁷ 10⁸ 10⁻¹ 10⁰ 10¹ 10² 10³ Not expected deaths.Expected fatalities F = r_h · worker-hours / 1e6r_h = local fatal rate per million hours. Installed hydrogen-output capacity, Q (MW) Worker-hours / project On-site S-LCA route (worker-hours) Off-site incl. storage / transport (worker-hours)

This figure deliberately stops at exposure hours. Converting to fatalities requires a jurisdiction-specific rate, and the platform refuses to invent one.

F = r_h · WH / 10⁶ · [expected fatalities] · WH in worker-hours

Fig 4DPeople affected
4D People served versus people exposed 10⁻² 10⁻¹ 10⁰ 10¹ 10² 10³ 10⁴ 10⁵ 10⁶ 10⁷ 10⁻¹ 10⁰ 10¹ 10² 10³ Energy access is a proxy:replace 3500 kWh/person-yr with localdemand or displacement data where available. Installed hydrogen-output capacity, Q (MW) Persons Energy-equivalent persons served / yr Noise-exposed persons >55 dB(A)

The benefit curve and the burden curve on one axis. Four to five orders of magnitude separate them, which is the honest framing of the social trade-off.

Persons served = LHV·ṁ / 3500 kWh · exposed = P_HA(Q)

Fig 4EMonetary socioeconomic value
4E Gross value added and labour compensation 10⁻² 10⁻¹ 10⁰ 10¹ 10² 10³ 10⁴ 10⁻¹ 10⁰ 10¹ 10² 10³ Source basis is GBP; EUR2024 conversion pendinga frozen coefficient.Do not stack GVA + labour compensation:the economic boundaries overlap. Installed hydrogen-output capacity, Q (MW) Source-basis GBP million / project Green GVA (GBP million) Blue GVA (GBP million) Green labour compensation (GBP million) Blue labour compensation (GBP million)

Kept deliberately in its source currency until a single frozen GBP→EUR2024 coefficient is adopted, so that no silent conversion error propagates into the decision file.

GVA(Q) = g · Q · [GBP million/project] · labour compensation ⊂ GVA

Part 5

Storage economics, degradation and the CAPEX envelope

Three families of curve that do not run on capacity Q at all. Storage prices run on stored mass M, degradation runs on operating time, and the CAPEX envelope is a band rather than a line — because a single number for capital cost would be a false precision.

Fig 5AUnit storage cost
5A Unit storage cost by medium 10¹ 10² 10³ 10¹ 10² 10³ Geological media scale; engineered media do not.Tank and pipe are flat in M by construction. Stored mass, M (tonnes H₂) — technology-agnostic Unit storage cost (€/kg, EUR2024) Salt cavern — 850·M^−0.456 (R²=0.991) Pooled multi-source — 1350·M^−0.537 (R²=0.948) Lined rock cavern — 983·M^−0.377 (R²=0.977) Compressed tank — 0.346·P + 286 at 350 bar Underground pipe — flat 607 €/kg (niche)

Cavern cost falls with the roughly minus-one-half power of stored mass, so a large cavern is cheap per kilogram and a small one is not worth excavating. Tanks are modular: the price per kilogram is the same at one tonne and at one thousand.

p(M) = a·M^−b · [€/kg] · tank p = 0.346·P + 286, pipe p = 607

Fig 5BTotal storage CAPEX
5B Total storage CAPEX by medium 10⁰ 10¹ 10² 10³ 10⁴ 10¹ 10² 10³ cavern feasibility ≥ 100 t 1) pick stored mass M 2) read CAPEX on your curve3) below 100 t, tank or pipe only4) M(Q) = (1000/SEC)·24·Q for a 24 h inventory Stored mass, M (tonnes H₂) — technology-agnostic Total storage CAPEX (M€, EUR2024) Salt cavern — C = 0.850·M^0.544 Lined rock — C = 0.983·M^0.623 Compressed tank — C = 0.407·M (modular, any mass) Underground pipe — C = 0.607·M

The same laws integrated to a capital number. Below one hundred tonnes the cavern curves are drawn but not offered: the geology, cushion gas and deliverability requirements make them infeasible, not merely expensive.

C(M) = p(M)·M / 1000 · [M€2024] · M in tonnes H₂

Fig 5CPEM degradation profile
5C PEM degradation over a 25-year life 0.0 2.0 4.1 6.1 8.2 10 0 5 10 15 20 25 D̄ = 3.3% Operating time (years) Degradation (% loss / OPEX escalation) stack (efficiency, convex) · life 7.6 yr → 3 replacements BoP (maintenance, raised cosine) · reset 20 yr system (0.75·stack + 0.25·BoP)

Each stack replacement resets the efficiency loss to zero; the balance of plant keeps ageing until its own twenty-year overhaul. The mean of the system curve, 3.3 %, is exactly the δ̄ that divides mean annual output in the lifecycle LCOH — nothing here is decorative.

g_sys(t) = 0.75·g_stack(t mod t_stack) + 0.25·g_BoP(t mod 20) · δ_max = 10 %

Fig 5DAEL degradation profile
5D AEL degradation over a 25-year life 0.0 2.0 4.1 6.1 8.2 10 0 5 10 15 20 25 D̄ = 3.2% Operating time (years) Degradation (% loss / OPEX escalation) stack (efficiency, convex) · life 10.1 yr → 2 replacements BoP (maintenance, raised cosine) · reset 20 yr system (0.75·stack + 0.25·BoP)

Each stack replacement resets the efficiency loss to zero; the balance of plant keeps ageing until its own twenty-year overhaul. The mean of the system curve, 3.2 %, is exactly the δ̄ that divides mean annual output in the lifecycle LCOH — nothing here is decorative.

g_sys(t) = 0.75·g_stack(t mod t_stack) + 0.25·g_BoP(t mod 20) · δ_max = 10 %

Fig 5ESOEC degradation profile
5E SOEC degradation over a 25-year life 0.0 2.0 4.1 6.1 8.2 10 0 5 10 15 20 25 D̄ = 3.5% Operating time (years) Degradation (% loss / OPEX escalation) stack (efficiency, convex) · life 2.5 yr → 9 replacements BoP (maintenance, raised cosine) · reset 20 yr system (0.75·stack + 0.25·BoP)

Each stack replacement resets the efficiency loss to zero; the balance of plant keeps ageing until its own twenty-year overhaul. The mean of the system curve, 3.5 %, is exactly the δ̄ that divides mean annual output in the lifecycle LCOH — nothing here is decorative.

g_sys(t) = 0.75·g_stack(t mod t_stack) + 0.25·g_BoP(t mod 20) · δ_max = 10 %

Fig 5FCAPEX envelope and validity domain
5F Installed CAPEX with screening envelope 10⁻¹ 10⁰ 10¹ 10² 10³ 10⁴ 10⁻¹ 10⁰ 10¹ 10² 10³ validity 1 MW 1 000 MW Shaded = screening envelope, not a confidence interval.Outside 1–1 000 MW the law is extrapolated and flagged.AEL carries extra caution above 400 MW. Installed hydrogen-output capacity, Q (MW) Total CAPEX (M€, EUR2024) PEM — ±35% envelope · 1210 €/kW at 100 MW AEL — ±45% envelope · 720 €/kW at 100 MW SOEC — ±55% envelope · 2295 €/kW at 100 MW

The band is the honest answer to 'what will it cost'. A point estimate inside a ±35 to ±55 percent envelope is a reading aid, not a quotation, and the platform flags every evaluation that falls outside the calibrated interval instead of silently extrapolating.

C(Q) = A·Q^β ± envelope % · [M€2024] · validity 1–1 000 MW

How to read these figures

Slope is the physics

On log–log axes the slope of a line is the exponent θ in y = a·Q^θ. Slope 1 means strictly proportional; slope below 1 means economy of scale; a bend means a regime change.

Dashed is external

Solid lines are model output. Dashed and dotted lines are published benchmarks or regulatory limits, drawn so the model can be judged, never fitted to.

Units are on the axis

Every y-axis carries its unit and its time basis. Annual quantities are per year at the stated capacity factor; lifetime quantities say so explicitly.

Thresholds are real

Where a curve starts abruptly, an exposure threshold has been crossed. The platform never smooths a threshold to make a chart look continuous.