Methodology To model the energy and greenhouse gas emissions of electronic software distributions

A new electronic software distribution (ESD) life cycle analysis (LCA)methodology and model structure were constructed to calculate energy consumption and greenhouse gas (GHG) emissions. In order to counteract the use of high level, top-down modeling efforts, and to increase result accuracy, a focus upon device details and data routes was taken. In order to compare ESD to a relevant physical distribution alternative,physical model boundaries and variables were described. The methodology was compiled from the analysis and operational data of a major online store which provides ESD and physical distribution options. The ESD method included the calculation of power consumption of data center server and networking devices. An in-depth method to calculate server efficiency and utilization was also included to account for virtualization and server efficiency features. Internet transfer power consumption was analyzed taking into account the number of data hops and networking devices used. The power consumed by online browsing and downloading was also factored into the model. The embedded CO2e of server and networking devices was proportioned to each ESD process. Three U.K.-based ESD scenarios were analyzed using the model which revealed potential CO2e savings of 83% when ESD was used over physical distribution. Results also highlighted the importance of server efficiency and utilization methods.

A methodology to measure the environmental impact of ICT operating systems across different device platforms

Abstract: A new methodology was created to measure the energy consumption and related green house gas (GHG) emissions of a computer operating system (OS) across different device platforms. The methodology involved the direct power measurement of devices under different activity states. In order to include all aspects of an OS, the methodology included measurements in various OS modes, whilst uniquely, also incorporating measurements when running an array of defined software activities, so as to include OS application management features. The methodology was demonstrated on a laptop and phone that could each run multiple OSs, results confirmed that OS can significantly impact the energy consumption of devices. In particular, the new versions of the Microsoft Windows OS were tested and highlighted significant differences between the OS versions on the same hardware. The developed methodology could enable a greater awareness of energy consumption, during both the software development and software marketing processes.