Carbon Footprint

Google Cloud operates the cleanest cloud in the industry in order to help customers achieve their own sustainability goals. With the newly available Carbon Footprint data, you can now accurately measure your gross carbon footprint and track the emissions profile of your cloud usage to improve your carbon footprint. Detailed calculation methodology is published so that reviewers and reporting teams can verify that their emissions data meets GHG Protocol.

Looker takes this available data to the next level, giving you powerful visual insights into your expenditure, allowing you to easily analyze your impact, expose disclosure reporting and act on reducing the gross emissions of your cloud applications and infrastructure.

• Explore the data to determine where the biggest contributors to your green impact exist, segmenting by service, project, region, and month for the selected billing account over all available months.
• Initiate alerts based on substantial increases or shifts in service, project or regional impact.
• Schedule deliveries of dashboards to your team so they can proactively manage and identify where opportunities for investigation exist.
• Navigate directly from your dashboard to your console to make updates or changes to your projects and services used.

Configure and manage your data export

Carbon Footprint data is exported via the BigQuery Data Transfer Service. The data will be exported to the BigQuery table of your choice on the schedule you specify. Each export will overwrite the entire table with the most recent data available. Each month's data is added to the export on the 15th day of the following month. Initiate and manage the export using this documentation, and review the schema. For further reading, please see the Carbon Footprint tool available directly from your console.

Customizations

In order to fit the LookML files to your chosen connection, schema and table names, you will need to update the manifest file.

• Navigate to the manifest file, manifest.lkml, and replace the values for connection_name, schema_name and table_name to your appropriate values.

You may also associate your Carbon Footprint data with your billing dataset.

• To get started, export your billing data to BigQuery or download the GCP Billing Block by Datatonic
• Add the following join parameter to your billing Explore in order to associate Carbon emmissions at the location, service, project and month level:

join: carbon {
  type: left_outer
  relationship: many_to_one
  sql_on:   ${carbon.location} = ${your_gcp_billing_export.location__location} AND
            ${carbon.service_id} = ${your_gcp_billing_export.service__id} AND
            ${carbon.service_name} = ${your_gcp_billing_export.service__description} AND
            ${carbon.usage_month} = ${your_gcp_billing_export.usage_end_month} AND
            ${carbon.project_number} = ${your_gcp_billing_export.project__number};;
        }

Just make sure to replace the reference to the view name your_gcp_billing_export with your own view name

Notes and Other Known Issues

• Limited coverage of Google Cloud services - Carbon Footprint does not cover all Google Cloud services, see the list of covered services.
• Only gross carbon emissions from electricity are reported - As captured in the methodology behind Carbon Footprint, the data reported only includes gross greenhouse gas emissions from electricity associated with the usage of covered Google Cloud services for the selected billing account. It does not include direct emissions or indirect emissions related to the value chain (respectively Google's Scope 1 and Scope 3 in the Greenhouse Gas (GHG) Protocol carbon reporting standards).
• Only location-based emissions are reported - Net emissions, after including Google's purchase of clean energy (market-based methodology) are not yet available.