Carbon Footprint reporting methodology

To give customers a report tailored to their specific carbon footprint, Google looks at the gross carbon emissions produced by the computing infrastructure supporting its internal services. Google apportions those gross emissions to each Google Cloud product, and allocates the emissions to a customer based on the customer's usage of those Google Cloud products.

The Google Cloud customer-specific gross greenhouse gas emissions data provided by the Carbon Footprint report has not been third-party verified or assured. Any updates to our methodology or the data sources might result in material changes to our calculations and might result in the current and previous Google Cloud customer-specific gross greenhouse gas emissions data provided by the Carbon Footprint report to be adjusted.

Carbon Footprint uses the GHGP's location-based reporting method for its primary reports and dashboards. This means these footprints represent "gross emissions" arising from all electricity generation sources in use at a given location. The location-based footprints do not take into account Google's renewable power purchase agreements or other contracts for carbon-free electricity.

Disaggregating Google Cloud's electricity use and its resulting gross carbon footprint to specific products and customers presents a technical conundrum. Determining a customer's footprint is very complex due to the layers of shared resources called upon to serve customer compute needs. Developing new apportionment methodologies and assumptions (as discussed in detail below) enables Google Cloud to present customer footprint reports that are appropriate and representative of each customer's cloud computing use and product choices.

Carbon Footprint first calculates energy use as a function of compute usage and data center resource requirements. Then, Carbon Footprint calculates location-based carbon emissions from electricity use, and allocates those emissions across customers and further across each customer's purchased products. The carbon emissions from electricity per customer and product are then augmented with proportional allocations of emissions arising from the non-electricity sources.

In order to apportion the total machine energy usage to internal services, Google separately evaluates the energy used when running a workload ("dynamic power") against the energy used when machines are idle ("idle power"). Each machine's hourly dynamic power is allocated to the internal services it supported that hour, based on relative internal service CPU usage. Machine idle power is allocated to each internal service based on its resource allocation (CPU, RAM, SDD, HDD) in the data center.

Overhead energy use–power systems, cooling and lights–is allocated hourly to every machine, and its users, based on the machine's total energy use that hour.

Google's shared infrastructure services track the usage of other internal services that call them. This enables the shared infrastructure services' energy usage to be reapportioned to those internal services based on their relative usage. For some internal services that do not have sufficient usage data, Google uses internal costs to reallocate the shared infrastructure's energy consumption.

When these calculations and allocations are complete, we have hourly power use allocated to each internal service in each data center.

To calculate emissions, Google multiplies the hourly energy use for each internal service at each location by the appropriate carbon emission intensity factor for that hour and location to determine the internal service's location-based electricity carbon footprint per hour and location.

SKU = Stock-Keeping Unit

Carbon Footprint uses data streams for these non-electricity sources that originate with Google company-wide measurement systems. As such, emissions from non-electricity sources are calculated and added to the Google Cloud footprint on a less dynamic and less granular basis than emissions from electricity: though we measure electricity use and its location-based footprint on an hourly basis, emissions from other sources are established on either a monthly or annual basis, and are not available with any geographic specificity. Note that the Google company-wide data for embedded emissions of data center equipment and data center facilities has not been assured.

Embedded emissions of data center equipment: This emission source encompasses the activities necessary to extract, refine, and transport materials to equipment manufacturing locations, and the emissions associated with the manufacturing processes. Using lifecycle analysis, Google has established a per-piece embedded emissions footprint for data center equipment. This footprint is then amortized over a 4-year timeframe (chosen to match our financial accounting standards though we see significantly longer lifetimes for our equipment in practice) to create an annual emissions burden for each piece of equipment.