ATLAS SANCTUM
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Simulate the future

Change the variables. Every output below is a stated function of the inputs — no hidden magic, no decorative numbers.

Place
Scenario presets
Variables
System response · Africa
Energy demand
540.9TWh/yr
Modeled · low confidence
vs baseline 0.0
Compute load
3973MW
Modeled · low confidence
vs baseline 0.0
Water demand
80669Mm³/yr
Modeled · low confidence
vs baseline 0.0
Emissions
105MtCO₂e
Modeled · low confidence
Infrastructure gap
$3446B
Modeled · low confidence
Capital requirement
$4351.2B
Modeled · low confidence
People with access
925.7M
Modeled · low confidence
Economic activity
51index
Modeled · low confidence
Resilience40.2
Ecosystem health55.4
RICI44.8
Modeled · confidence Low · provenance

Atlas scenario model v0.4 — deterministic system of equations over population, income, system capacity/demand and scenario variables. Sensitive to assumptions; use for direction, not magnitude. · 2025. Atlas does not present modelled output as observed fact. Where confidence is low, treat the value as a hypothesis to be tested, not a measurement.

What this future requires
  • Generation. ~103 GW of new firm-equivalent capacity at 55% renewable share.
  • Water. 8874 Mm³/yr of new supply or reuse to avoid competing with agriculture.
  • Capital. $4351.2B over the horizon — roughly $290.1B per year.
  • People. 18,275,040 skilled roles across construction, operations and maintenance.
Trade-offs Atlas will not hide
  • Investment below 40% growth leaves the reliability gap unaddressed regardless of new generation.
  • Unknown: local grid topology, land tenure, and the political economy of tariffs are not represented in this model.
Data provenance · scenario outputs11 metrics traced

Observed = direct measurement. Reported = published by the named source. Estimated = Atlas estimate from partial public data. Modeled = model output, not a measurement.

Energy demand · Modeled · low confidence

Annual electricity demand implied by the scenario, TWh/yr.

Method. base = population × GDP/capita ÷ 9000; scaled by energy-demand and population-growth variables, plus a compute-demand term.

Inputs. population · GDP per capita · energy demand % · population growth % · compute demand %

Caveat. Elasticities are constant; no price feedback or efficiency S-curve.

Compute load · Modeled · low confidence

IT load of data-centre capacity implied by the scenario, MW.

Method. compute system capacity × (population scale + 4) × (1 + compute demand %).

Inputs. compute capacity · population · compute demand %

Caveat. Interconnection queues are speculative; most requested load is never built.

Water demand · Modeled · low confidence

Annual water withdrawal implied by the scenario, million m³/yr.

Method. population × 42 m³ × urbanisation factor + compute load × 0.012, discounted by technology adoption.

Inputs. population · urbanisation % · compute load · technology adoption

Caveat. Agricultural withdrawal, by far the largest term in most basins, is held constant.

Emissions · Modeled · low confidence

Operational emissions of the electricity system, MtCO₂e/yr.

Method. energy demand × 0.42 tCO₂e/MWh × (1 − renewable share ÷ 115) − restoration sequestration term.

Inputs. energy demand · renewable penetration % · ecosystem restoration %

Caveat. Embodied and non-energy emissions are excluded.

Infrastructure gap · Modeled · low confidence

Unfunded investment need over the scenario horizon, USD billions.

Method. (energy × 1.7 + water × 0.02 + population × 0.9) × (1 − investment effect × 0.45).

Inputs. energy demand · water demand · population · investment %

Capital requirement · Modeled · low confidence

Total capital needed including compute build-out, USD billions.

Method. infrastructure gap × 1.25 + compute load × 0.011.

Inputs. infrastructure gap · compute load

People with access · Modeled · low confidence

Population with reliable service under the scenario, millions.

Method. population × growth × access indicator adjusted by investment and technology adoption ÷ 100.

Inputs. population · access indicator · investment % · technology adoption

Economic activity · Modeled · low confidence

Relative index (0–140) of economic activity enabled by the infrastructure state.

Method. 45 + investment, technology, compute and population terms, less water-shortfall and climate-pressure penalties.

Inputs. investment % · technology adoption · compute demand · water supply index · climate pressure

Caveat. An index, not a GDP forecast.

  • Atlas Sanctum — Atlas scenario model v0.4 (deterministic) (2025)
Resilience · Modeled · low confidence

Ability of the system to absorb shocks and recover, 0–100.

Method. baseline resilience + investment, renewables, restoration and technology terms − climate pressure, unfunded demand growth and water loss.

Inputs. resilience indicator · investment % · renewable % · restoration % · climate pressure · water availability

Ecosystem health · Modeled · low confidence

Ecological integrity under the scenario, 0–100.

Method. baseline ecological integrity + restoration × 0.42 − urbanisation, climate pressure and energy-demand penalties.

Inputs. ecological integrity · restoration % · urbanisation % · climate pressure

Scenario RICI · Modeled · low confidence

RICI recomputed on the indicator set the scenario produces.

Method. Each indicator adjusted by scenario variables, then the published RICI weighting applied.

Inputs. all ten indicators · all scenario variables

  • Atlas Sanctum — Atlas scenario model v0.4 (deterministic) (2025)