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Carbon-aware computing adjusts when, where, or how much flexible computing work runs in response to the carbon intensity of the electricity it uses. Software can defer a task until electricity is lower carbon, run it in a suitable region with a lower-carbon electricity signal, or reduce optional work when carbon intensity is high.
What carbon-aware computing means
The Green Software Foundation’s Software Carbon Intensity (SCI) specification defines carbon-aware behavior as software or hardware adjusting its behavior in response to the carbon intensity of the energy it consumes. In plain terms, a system considers the emissions associated with its electricity and uses that information to make operational decisions.
Carbon intensity describes the greenhouse-gas emissions associated with electricity generation, commonly expressed as grams of carbon dioxide equivalent per kilowatt-hour (gCO₂e/kWh). It can vary by time and by grid region as the mix of electricity generation changes. The figure is meaningful only with its location, time period, data source, and calculation method understood. Green Software Foundation: Carbon-aware computing
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How carbon-aware computing works
A system uses carbon-intensity information alongside workload requirements to decide whether to run work now, later, elsewhere, or at a reduced level. These are different scheduling choices, and a workload may use more than one.
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Shift work to a lower-carbon time
Temporal shifting delays flexible work until a time when the electricity is expected to have lower carbon intensity. This can suit tasks such as software updates or batch processing that do not need to finish immediately. The schedule still has to meet the task’s deadline and any service requirements.
Shift work to a lower-carbon location
Spatial shifting runs eligible work in a physical location or grid region with a lower-carbon electricity signal. The workload must be able to run there, and the comparison must use emissions data that is meaningful for each location. Data freshness and geographic coverage matter: a region comparison based on incomplete or mismatched data can mislead.
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Shape or reduce demand
Demand shaping changes the amount or timing of work as carbon intensity changes. For example, a system might pause or reduce optional processing during a high-intensity period. This is not necessarily a shift to another time or region; it can simply mean doing less work for a while.
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Energy efficiency means using less electricity to provide the same function. Hardware efficiency means using fewer physical resources to provide that function. Carbon awareness instead changes behavior in response to the carbon intensity of consumed energy—for example, by shifting a task to a cleaner time or region. The approaches can complement one another, but they describe different actions. A system can be energy-efficient without scheduling around grid carbon intensity, or carbon-aware while still having opportunities to improve its efficiency. Green Software Foundation: Software Carbon Intensity specification
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Which computing work can be scheduled this way?
Carbon-aware scheduling requires flexibility. Work that can wait, move, or scale down is a better candidate than work that must respond immediately. The decision should account for the workload’s deadline, latency needs, service quality, and technical ability to run in another location. There is no universal latency or quality threshold that makes a workload carbon-aware; those constraints depend on the service.
- More flexible: tasks with a deadline window, such as some batch jobs or software updates.
- Less flexible: work that must run immediately or meet strict response-time requirements.
- Location-dependent: work that can run in more than one region without violating technical, operational, or service constraints.
- Potentially reducible: optional work that can be paused or scaled down without compromising essential service.
How to assess an emissions impact
A scheduling change alone does not prove that emissions fell. To assess an impact, define what software and infrastructure are included, what amount of useful work is being compared, and how electricity use and carbon intensity are measured or estimated.
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The SCI method calls for a defined system boundary and functional unit, along with disclosure of the calculation method. Its process includes bounding the system, choosing a functional unit, selecting measurement or estimation methods for relevant components, quantifying component rates, and reporting the result and method. The specification describes electricity carbon intensity in gCO₂e/kWh and, for its consequential approach, calls for location-based marginal emissions factors. That approach should not be confused with every other way of reporting electricity emissions. Green Software Foundation: Software Carbon Intensity specification
A useful comparison therefore identifies the baseline and the proposed schedule, then records the time window, candidate region, workload amount, deadlines or service constraints, emissions-data source and coverage, system boundary, functional unit, and measurement method. A result from one workload, location, and period should not be presented as a general reduction rate.
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What a carbon-aware software tool can—and cannot—do
The Green Software Foundation’s Carbon Aware SDK offers emissions data through a Web API and command-line interface (CLI) for developers building software that considers when or where work runs. Its documentation describes examples such as choosing lower-carbon times for software updates and selecting cloud regions. The project documentation also identifies the SDK as a graduated project and notes that its stage can change; check its current status, configuration, and data-source availability before relying on it. Carbon Aware SDK documentation
The SDK documentation names WattTime and Electricity Maps among data sources in the project’s ecosystem. A tool can provide data or support a scheduling decision, but its use does not establish that a particular deployment reduced emissions. That conclusion still depends on the workload, baseline, data, boundary, and reporting method.
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