Consumption and withdrawal
Evaporation consumes water. Water withdrawn for use may include returned flows; makeup, blowdown, treatment and source conditions require their own accounting. Annual use cannot establish peak local demand.
Infrastructure / Cooling & resource efficiency
An engineering framework for high-density AI infrastructure: rack cooling, final heat rejection, water, electricity and useful compute. These are Aguasto’s evaluation priorities; no operating efficiency result is claimed.
Direct-to-chip cooling moves heat from selected components into a technology coolant circuit. A coolant distribution unit can transfer that heat across a controlled interface to the facility circuit.
Other components may still require room air cooling. The facility must ultimately reject heat outside; dry, evaporative and hybrid arrangements have different climate, water, electricity, capacity and maintenance implications.
Warm-water architectures can expand suitable operating options where the exact server, coolant, supply-temperature and ambient envelopes support them. They do not remove the need to validate the selected OEM equipment or establish a universal best design.
Follow the heat beyond the closed technology loop.
Evaporation consumes water. Water withdrawn for use may include returned flows; makeup, blowdown, treatment and source conditions require their own accounting. Annual use cannot establish peak local demand.
Reclaimed water may change freshwater demand where permitted and technically suitable. Quality, treatment, transport, availability and local water conditions need documented assessment.
Dry systems can reduce cooling-related local freshwater use while changing electricity, approach temperatures, space, capital and thermal capacity. Hybrid water assistance needs explicit operating conditions.
Site overhead, local water conditions and quality-qualified model output answer different questions. Comparisons require aligned measurement periods, disclosed equipment and operating boundaries, and reproducible workload conditions.
| Metric | What to measure | Required boundary |
|---|---|---|
| PUE | Facility energy divided by IT energy over aligned measurement periods. | Identify the facility, meters, shared services and reporting period. PUE alone is not useful AI work or a water metric. |
| WUE | Defined facility water use per unit of IT energy, with the applicable reporting boundary stated. | Identify units, period, water sources and what the metric includes. Keep withdrawal and consumption visible rather than interchanging them. |
| Local freshwater consumption | Freshwater consumed within the stated on-site boundary. | Separate evaporation and other consumptive uses from withdrawn water that is returned; identify local water conditions. |
| Peak water withdrawal | Water taken from a source over the specified peak interval. | Annual averages do not establish peak demand, utility availability or local environmental suitability. |
| Indirect water | Electricity-related water effects outside the facility boundary. | State generation/location/time assumptions. A site cooling claim is not a complete system-wide water footprint. |
| Cooling electricity | Measured energy for the included pumps, fans, chillers and related systems. | Identify which loops, residual air cooling and heat-rejection equipment are counted under the actual climate/load. |
| Useful compute per kWh | Quality-qualified completed work or tokens per the defined energy denominator. | Specify checkpoint, request/context distribution, quality, latency, concurrency, errors and included equipment. No Aguasto result is available. |
| Facility energy per billable work | Included facility energy per completed commercial workload unit. | Separate a metering definition from token billing rules. Idle energy, overhead and failed work need explicit treatment. |
| Embodied carbon & life cycle | A disclosed lifecycle assessment of included construction, equipment, transport and replacement. | Declare inventory, service-life assumptions and exclusions. Reuse is not automatically lower impact or indefinitely feasible. |
For GPU work and tokens per kWh, pin the checkpoint, runtime, precision, input/output lengths, latency and quality criteria, concurrency, failed work and power metering. Device specifications and token billing are distinct from executed, facility-wide measurements.
Evaluate construction, equipment, transport, replacement and end-of-life together. Suitable reuse and modular adaptation can avoid some work, but condition, safety, interface changes and service life determine actual outcomes. Qualified engineering and technical partners would validate functions beyond Aguasto’s established capabilities.
This framework draws on DOE’s facility energy and water guidance, LBNL’s data-center energy/water accounting and ASHRAE’s liquid-cooling system distinctions. Manufacturer material is attributed as vendor guidance; it does not verify an Aguasto result.
DOE FEMP: data centers and servers · LBNL: 2024 energy and water study · ASHRAE: liquid cooling guidance