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There is no defensible universal answer to “Which cloud provider is greenest?” Compare providers using the same workload, region, utilization, data volume, and reporting period, and report both location-based and market-based emissions. Then check what each provider counts, how it allocates shared infrastructure, how current its grid data is, and whether the result is independently assured. Without those controls, differences in reported totals may reflect accounting choices rather than a meaningful difference in the climate impact of running your workload.
Why can’t I rank cloud providers by one emissions total?
A provider-wide total combines many regions, services, customers, and accounting choices. It does not tell you how much emissions a particular workload causes, and providers may draw different boundaries around what they report. A smaller total could reflect a smaller business, a narrower boundary, a different allocation method, or lower emissions—not necessarily a more efficient option for your application.
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The useful question is narrower: what emissions are associated with delivering the same result, under comparable operating conditions? That could mean kilograms of CO2e per 1,000 requests, per machine-hour at a stated utilization, per terabyte-month stored, or per completed analytics job. State the unit, workload, region, and period alongside the result. If those differ, the figures are not a like-for-like comparison.
What should I match before comparing providers?
Set the comparison up as a controlled workload test. Keep the service outcome constant and record the operating conditions that influence energy use and emissions.
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1. Define the work and functional unit
Choose a unit that captures the result the cloud service delivers, rather than relying only on an account-level total. Examples include kilograms CO2e per 1,000 requests, per completed analytics job, per terabyte-month stored, or per machine-hour at a stated utilization. Report the observation period as well as the unit; a monthly value and an annual value should not be compared as though they were the same measurement.
2. Match workload and utilization
Run the same application behavior, data volume, software architecture, and utilization profile in each comparison. Record utilization explicitly: a machine-hour with low utilization is not equivalent to one running near capacity. If the architectures or service configurations differ, describe that difference rather than presenting the result as a clean provider-only comparison.
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Identify the cloud region and time period. Electricity carbon intensity can change by both place and hour, so a global average can hide conditions relevant to your workload. If the providers’ data only supports different time granularity, preserve that distinction in the report rather than implying an hourly comparison when one side uses annual factors.
4. State the boundary and allocation
Write down which facilities and lifecycle sources are included, and how shared infrastructure is assigned to the service or customer. The boundary and allocation method can change a result as much as the underlying energy measurement. Do not treat omitted sources as zero emissions.
What is the difference between location-based and market-based emissions?
Location-based emissions estimate the impact of electricity using the grid mix associated with the data-center location. Market-based emissions reflect qualifying contractual clean-energy purchases. Both views are useful, but they answer different questions: one describes the grid associated with the facility; the other incorporates procurement claims.
Ask providers to report both figures for the same workload, period, and boundary. A lower market-based result does not mean the physical grid mix serving the data center has changed. For example, Google Cloud’s methodology uses hourly grid factors for its location-based calculations and annual factors for market-based calculations that account for its clean-energy purchases. Comparing those figures without naming the accounting view and time resolution would obscure what the numbers mean.
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Do not substitute a renewable-energy claim for an operational emissions figure. Record the provider’s market-based result separately from the location-based result, and make the method and grid-factor source visible. If a provider gives only one view, label it accurately and avoid comparing it directly with the other provider’s different view.
Which emissions sources and facilities are included?
Check the system boundary before interpreting any carbon number. It may include provider-operated data-center infrastructure and selected Scope 1, Scope 2, and Scope 3 sources, while leaving out other facilities or lifecycle stages. In particular, operational electricity alone does not capture embodied emissions from equipment and buildings.
- Operational sources: identify whether direct fuel use and purchased electricity are included, and whether electricity-related fuel and transmission losses are counted.
- Embodied sources: check whether emissions from manufacturing IT hardware, buildings, and non-IT equipment are included.
- Locations: ask about data centers, edge locations, offices, warehouses, manufacturing facilities, and customer-premises deployments. Inclusion of one type of site does not imply inclusion of all the others.
- Lifecycle endpoints: record whether end-of-life impacts are covered.
- Scopes: note which Scope 1, Scope 2, and Scope 3 sources are included, rather than assuming a scope label covers every source within that category.
AWS documents a boundary that includes AWS-operated infrastructure; location-based and market-based Scope 2; selected fuel- and energy-related Scope 3; and embodied emissions for IT hardware, buildings, and non-IT equipment. Its stated exclusions include AWS offices, warehouses, manufacturing facilities, and customer-operated sites such as Outposts. This is a defined boundary, not a complete inventory of every place or device involved in a customer’s technology stack.
Google Cloud Carbon Footprint reports selected Scope 1, Scope 2, and Scope 3 sources. The available methodology summary does not establish that its boundary is identical to AWS’s, so do not infer equivalence from the scope labels alone. Obtain the detailed boundary documentation for each provider before treating totals as directly comparable.
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Cloud infrastructure is shared. A provider must attribute facility energy and emissions through a chain of shared resources before it can report a service-, project-, or customer-level figure. That chain may involve machines, internal services, SKUs, products, regions, and customers.
Google describes allocating measured and modeled energy from machines to internal services, SKUs, products, projects, regions, and customers. When comparing its output with another provider’s, ask what is measured directly and what is modeled, and what allocator is used at each step. Possible approaches include measured machine energy, modeled coefficients, revenue, or usage volume; these are examples of methods to verify, not assumptions about any provider’s approach.
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Allocation matters because a customer-level result is not simply a meter reading from a dedicated server. If the provider uses a model, changes its model, or revises underlying data sources, a reported customer result can change even when the customer’s workload has not. Compare the allocation descriptions and revision policies, not just the final decimal value.
How should I use PUE, CUE, and WUE?
PUE, CUE, and WUE add context about facility overhead, carbon intensity, and water intensity. They can support a cloud comparison, but they do not replace a workload-normalized emissions result or resolve differences in boundaries and allocation.
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- PUE is a measure of facility overhead. A lower value is not, by itself, proof that a particular customer workload has lower total emissions.
- CUE can express carbon intensity; check the unit, time period, and emissions view used.
- WUE can express water intensity; check its definition and data source before comparing values.
Cloud Carbon Footprint’s methodology page uses PUE inputs of 1.135 for AWS, 1.1 for Google Cloud, and 1.185 for Azure. These are inputs to that open methodology, not a universal ranking of providers or a substitute for matched workload measurements. The page cautions that provider methods differ, making precise comparison difficult. Treat the figures as methodology inputs and verify their applicability before using them in a calculation.
The Green Software Foundation specification recommends reporting annual and monthly location-based intensity, market-based intensity, CUE, and WUE, with stated data sources. Using a consistent reporting format makes it easier to see which values are comparable and which need further explanation.
How do AWS and Google Cloud differ in the evidence described here?
The available provider details support a comparison of methodology and assurance, not a verdict about which service emits less for a specific workload. A like-for-like result still requires matched workload data and compatible boundaries.
| Comparison point | AWS | Google Cloud |
|---|---|---|
| Customer-level energy allocation | Detailed allocation chain not established in the methodology summary described here. | Measured and modeled energy is allocated from machines to internal services, SKUs, products, projects, regions, and customers. |
| Electricity accounting | Boundary includes market-based and location-based Scope 2. | Location-based calculations use hourly grid factors; market-based calculations account for clean-energy purchases and use annual factors. |
| Embodied emissions | Includes embodied emissions for IT hardware, buildings, and non-IT equipment. | The cited methodology summary establishes selected Scope 1, Scope 2, and Scope 3 coverage but does not establish an identical embodied-emissions boundary. |
| Assurance of customer-specific output | AWS says its impact-estimate methodologies are based on industry standards and verified by an independent third party. | Google says its customer-specific Carbon Footprint data has not been third-party verified or assured. |
| Revisions | AWS says it updates methodology over time and recalculates historical data after methodology changes. | Google says methodology or data-source changes may adjust current and historical results. |
These statements describe the providers’ published methodologies and assurance claims; they are not an independent validation of a particular customer’s reported number. AWS says its company methodology has independent third-party verification. Google distinguishes its customer-specific report, which is not third-party assured, from its company-wide inventory, which receives assurance.
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What should a comparison table contain?
Use one row per decision-critical field and fill it only with provider values that share the same definition and period. A useful procurement worksheet is below. “Not stated” means the figure or method has not been established by the documentation being compared; it must not be interpreted as zero or as proof that the provider does not measure it.
| Field | What to record |
|---|---|
| Functional unit | For example, kgCO2e per 1,000 requests, per machine-hour at stated utilization, per terabyte-month, or per completed job. |
| Workload and utilization | Work performed, data volume, software architecture, utilization profile, and configuration. |
| Region and reporting period | Named region and start/end dates or reporting interval. |
| Location-based emissions | kgCO2e for the functional unit, plus grid-factor source and time resolution. |
| Market-based emissions | kgCO2e for the same functional unit, plus procurement method and factor period. |
| Scopes and embodied sources | Included Scope 1, Scope 2, and Scope 3 sources; hardware, building, and other embodied impacts. |
| Allocation | Measured versus modeled energy and the method used to assign it to services and customers. |
| Efficiency and water metrics | PUE, CUE, and WUE, with definitions, units, period, and data sources. |
| Site coverage | Provider-operated facilities, edge locations, offices, warehouses, manufacturing, and customer-premises sites. |
| Assurance and revisions | What output is independently verified or assured, and how historical results are treated after methodology changes. |
| Reduction controls | Provider or customer controls available to reduce emissions, with evidence of their effect on the matched workload. |
How do I calculate and report my cloud footprint?
Start with the provider’s workload- or customer-level emissions data where available, but preserve its method and accounting view. A single account total is useful for tracking a defined account over time; it is not automatically suitable for comparing platforms or workloads.
- Choose the outcome unit. Select a unit aligned to the work your system delivers and record utilization, data volume, architecture, region, and observation period.
- Collect both emissions views. Record location-based and market-based kgCO2e separately. Keep each figure attached to its factor source and time resolution.
- Document boundaries and allocation. Capture included scopes, embodied sources, site coverage, and the method by which shared energy is assigned to your service.
- Record supporting metrics. Add PUE, CUE, and WUE only with their definitions, periods, and sources; do not use a facility metric as a substitute for the workload result.
- Compare like with like. If a provider cannot supply a comparable field, mark it “not stated” and identify the provider documentation used. Do not fill missing data with zero or silently substitute a company-wide number.
- Preserve the version and assurance context. Note the date of the methodology, whether the customer-specific figure is assured, and whether revisions may alter historical results.
For ongoing measurement, keep the same functional unit and operating profile across reporting periods. If the provider changes its methodology or data sources, annotate the break in the series rather than treating a revised historical number as evidence that the workload itself changed.
Which cloud region has the lowest emissions?
There is no region that can be named as lowest for every workload and hour based on the provider details described here. Grid intensity varies by region and time, and the available methodologies do not establish a single synchronized region-by-region comparison across providers.
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How much confidence should I place in the reported number?
Assurance, methodology transparency, and revision practices determine how confidently you can use a figure in procurement or disclosure. A customer-specific estimate without third-party assurance is not equivalent to an independently verified methodology or to an assured company-wide inventory.
AWS says the methodologies used to calculate its impact estimates are based on industry standards and have been verified by an independent third party. It also says the methodology changes over time and that historical results are recalculated after changes. Google Cloud states that customer-specific Carbon Footprint reports are not third-party verified or assured, while its company-wide inventory receives assurance; it also warns that methodology or data-source changes may adjust current and historical results.
When using either provider’s figures, retain the report period, calculation method, boundary, and revision context. For a disclosure, state what the assurance applies to: the company inventory, the calculation methodology, or the customer-level result. Those are not interchangeable statements.
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Can I compare cloud emissions figures from different years?
Only if the provider can explain whether its methodology and underlying data stayed consistent or provide a recalculated historical series. A methodology revision can alter past values, so an apparent year-over-year change may not represent a change in the workload.
Should I use a cloud provider’s company-wide emissions total for procurement?
Use it as context about the provider’s overall inventory, not as a proxy for the emissions of your application. Procurement comparisons need figures tied to a matched service outcome, boundary, region, and period.
Can a market-based result show that a data center uses a cleaner local grid?
No. It reflects qualifying contractual clean-energy purchases, whereas the location-based view uses the grid mix associated with the facility. Keep the two accounting views distinct when explaining a result.
What does independent verification actually tell me?
First check what was verified: the calculation methodology, a company-wide inventory, or the customer-specific figure you plan to use. Assurance of one does not establish assurance of the others.
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