This paper presents a methodology for allocating energy consumption to multiple users of shared data center machines, infrastructure, and software. Google uses this methodology to provide carbon reporting data for enterprise customers of multiple Google products, including Google Cloud and Workspace. The approach documented here advances the state-of-the-art of large scale Cloud carbon reporting systems. It uses detailed, granular measurement data on machine energy consumption. In addition, it uses physical factors for allocating energy consumption and carbon emissions--preferred by the Greenhouse Gas Protocol's Scope 3 Reporting Standard. Specifically, the approach described here allocates machine energy consumption based on a combination of data center resource reservations and hourly measured resource usage. It also accounts for Google's own internal use of shared software services, reallocating energy use to the users of those shared services. Finally, it uses hourly, location-specific estimates of carbon intensity to precisely measure carbon emissions of users in a global fleet of data centers.

翻译：本文提出了一种将能耗分配给共享数据中心设备、基础设施及软件的多用户的方法论。谷歌采用此方法为包括谷歌云和Workspace在内的多个谷歌产品的企业客户提供碳排放报告数据。本文记录的方法推动了大规模云碳排放报告系统的最新技术发展。该方法利用机器能耗的详细细粒度测量数据，并采用温室气体核算体系范围三报告标准所推荐的物理因子来分配能耗与碳排放。具体而言，该方法基于数据中心资源预留量与每小时实测资源使用量的组合来分配机器能耗，同时核算谷歌内部对共享软件服务的使用情况，并将能耗重新分配给这些共享服务的用户。最后，该方法采用每小时、特定地点的碳强度估算值，精确测量全球数据中心集群中用户的碳排放量。