Global greenhouse gas emissions from the tech sector are on par or larger than the aviation industry, at around 3% for ICT and 2% for aviation respectively. Within ICT, data centres are responsible for around 1% of greenhouse gas emissions and global electricity usage. Currently, most cloud providers do not disclose energy or carbon emissions from cloud usage to their customers (at an aggregate or individual level), which can be a challenge for organisations who want to baseline and reduce their carbon footprint. Cloud Carbon Footprint (CCF) is a starting point to enable organisations to have greater visibility into their emissions across multiple cloud providers.
There are currently no guidelines for reporting Scope 3 emissions as part of the Greenhouse Gas (GHG) Protocol, which cloud provider usage would fall under. However, we hope more and more organisations report on both location-based and market-based emissions from cloud usage. To that end, this application’s focus is on providing a location-based cloud emissions estimate, and we welcome contributions that could aid with market-based reporting to include energy attributes such as RECs or power purchasing agreements.
CCF calculate CO2e estimates with this formula:
Total CO2e = operational emissions + embodied Emissions
Where: Operational emissions = (Cloud provider service usage) x (Cloud energy conversion factors [kWh]) x (Cloud provider Power Usage Effectiveness (PUE)) x (grid emissions factors [metric tons CO2e])
And: Embodied Emissions = estimated metric tons CO2e emissions from the manufacturing of datacenter servers, for compute usage
The approach builds upon Etsy’s Cloud Jewels (cloud energy conversion factors) for estimating CO2e emissions for cloud compute and storage services, with the addition of networking and memory usage.
For a detailed breakdown of the methodology see the Longer Version of the CCF Methodology.
In order to estimate energy used by cloud providers we are leveraging the methodology that Etsy created called “Cloud Jewels” to determine energy coefficients (kWh) for cloud service compute and storage usage. In addition, they have added energy estimation for networking and memory usage.
After estimating the kilowatt hours for compute, storage and networking, we need to multiply this by the cloud provider Power Usage Effectiveness (PUE). PUE is a score of how energy efficient a data center is, with the lowest possible score of 1 meaning all energy consumed goes directly to powering the servers and none is being wasted on cooling. This is based on publicly available information provided by the cloud providers. In the case of GCP, they publish their PUE. In the case of AWS, we have made a conservative guess based on public information. Microsoft's Sustainability team have provided a statement [1] as to the PUE for the Azure data centers.