There is no established, universally lowest-carbon choice among AWS, Azure, and Google Cloud for every workload. Compare the emissions of the services and regions you could actually use, keep location-based and market-based figures separate, and check what each provider includes in its calculations. Then factor in residency, latency, resilience, price, and how efficiently your workload uses cloud resources.
Start with the regions and services your workload can actually use
A region’s electricity mix is relevant, but it is only useful if that region can meet your requirements. First identify the services your application needs and the locations allowed by law, contracts, or internal data-residency rules. Then narrow the options by latency, redundancy, and price. Google’s guidance on carbon-free energy for Google Cloud regions explicitly treats these placement constraints as part of the decision.
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Do this before comparing emissions figures. A region that looks favorable on a carbon-intensity signal is not a practical alternative if it cannot host the required service or meet your workload’s operational and legal needs.
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Understand what the emissions numbers measure
Location-based figures describe the electricity mix where power is consumed
Location-based scope 2 accounting reflects the grid electricity mix associated with the place where electricity is used. It helps answer: “What emissions are associated with power consumption in this location?” Google’s Carbon Footprint methodology says its location-based figures do not include Google’s carbon-free electricity purchases.
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Market-based figures account for qualifying contractual electricity claims
Market-based accounting applies the relevant contractual instruments and method under the GHG Protocol. Google’s market-based figures account for its carbon-free electricity purchases under that method. This answers a different question from the location-based view; neither should be substituted for the other or treated as a complete description of every environmental impact.
When both figures are available, retain both in your evaluation and label them clearly. If a provider reports only one, record that limitation rather than treating the figure as directly comparable to another provider’s different accounting view.
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Compare provider reporting before comparing providers
Provider dashboards are useful inputs, not automatically comparable measurements. Their granularity, included services, system boundaries, estimation methods, reporting periods, and export options may differ. Record those differences alongside any emissions value.
| Provider | Available reporting described in the cited material | Boundary or comparability detail |
|---|---|---|
| Google Cloud | Carbon Footprint presents location-based and market-based emissions for covered Google Cloud usage, with views by project, product, and region. | Google publishes its calculation approach in its methodology documentation. The cited material does not establish a harmonized, like-for-like workload result against AWS or Azure. |
| Microsoft Azure | Microsoft’s Emissions Impact Dashboard describes estimated emissions and emissions saved associated with Azure and Microsoft 365. Microsoft’s cloud strategy guidance also identifies greenhouse gas emissions, carbon-footprint data, water use, and energy consumption as possible sustainability metrics. | The cited dashboard description does not establish a matched AWS/Azure/Google comparison for the same workload, service, region, utilization, and accounting boundary. For facility-efficiency disclosures, Microsoft says its FY24 dataset covers data centers it fully owns and controls that operated for 12 months in the calculation period, July 1, 2023 through June 30, 2024; see Measuring energy and water efficiency. |
| AWS | AWS’s sustainability methodology documents scope 2 estimates using both market-based and location-based calculations. | AWS describes an operational-control system boundary. Read its system boundary documentation before comparing its estimates with another provider’s reporting. |
These descriptions do not establish equal service coverage, regional granularity, update cadence, or audit and export options across all three providers. Check each provider’s current documentation for the particular dashboard and services you plan to use.
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Use a matched, workload-specific comparison
- Define the workload. Record the required service class, expected utilization, data volume and movement, and the measurement period. Use the same assumptions for each candidate.
- Make a feasible shortlist. Filter provider regions by data residency, service availability, latency, redundancy, and price before considering their carbon signals.
- Collect emissions data for each feasible combination. Note provider, service, region, period, scope, accounting method, granularity, and whether figures are estimated or reported for covered usage. Keep location-based and market-based values in separate fields.
- Read the reporting boundary and method. Check which facilities and services are included, how owned and third-party facilities are treated, which emissions scopes are covered, and how often data is updated. Note whether you can export the information or use it in your organization’s inventory.
- Assess the workload as well as the data center. Identify idle or oversized resources, scaling opportunities, and avoidable data movement. Compare the feasible options using the same workload assumptions, and state where provider data is not comparable.
If the available figures do not line up on service, region, time period, utilization, and accounting boundary, they do not support a defensible provider ranking. Treat the result as an unresolved comparison and seek workload-specific assessment rather than declaring a winner.
Do not confuse facility efficiency with workload emissions
Power usage effectiveness (PUE) measures facility energy efficiency: it compares total data-center energy with the energy used by IT equipment. It does not, by itself, show the carbon intensity of a specific region or the emissions attributable to a particular customer workload. Google reports a 2025 fleet-wide average PUE of 1.09; this is Google’s provider-reported fleet average, not a region-specific or independently comparable carbon result. See Google’s operating-sustainably information.
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Use fleet-wide efficiency figures as context, not as proof that a particular provider-region-service combination has the lowest emissions. A customer’s workload utilization and design also affect the result.
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Reduce the workload’s avoidable resource use
Choosing a region is only one lever. Microsoft’s sustainable workloads guidance recommends right-sizing, autoscaling, and removing idle or redundant resources. These practices can reduce resources provisioned for work that is unnecessary or not currently happening. Evaluate them alongside location choices, while preserving the availability, performance, and resilience the application requires.
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Recheck the evidence on your reporting cycle
Region signals, dashboard coverage, calculation methods, and facility disclosures can change. As of October 4, 2026, the provider materials cited here offer different kinds of evidence, not a controlled head-to-head test. Save the reporting period and methodology used in each decision, then refresh the comparison when your workload or provider data changes.
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