Assessing Internet energy intensity: A review of methods and results

• Published in: Environmental impact assessment review Vol. 45; pp. 63 - 68
• Main Authors: Coroama, Vlad C., Hilty, Lorenz M.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Inc 01.02.2014; Elsevier
• Subjects: Animal, plant and microbial ecology; Applied ecology; Biological and medical sciences; Conservation, protection and management of environment and wildlife; DATA TRANSMISSION; DATA TRANSMISSION SYSTEMS; Dematerialization; ELECTRONIC EQUIPMENT; ENERGY CONSUMPTION; ENERGY EFFICIENCY; ENERGY PLANNING, POLICY AND ECONOMY; Environmental impact; ENVIRONMENTAL IMPACTS; ENVIRONMENTAL SCIENCES; Fundamental and applied biological sciences. Psychology; General aspects; Industrial ecology; Information and communication technologies (ICT); INTERNET; Parks, reserves, wildlife conservation. Endangered species: population survey and restocking; PERSONAL COMPUTERS; REVIEWS; Data transmission; Industrial ecology; Dematerialization; Energy efficiency; Information and communication technologies (ICT); Environmental impact; Transmission; Method; Energy intensity; Energetic efficiency; Technology; Environment impact; Communication
• ISSN: 0195-9255; 1873-6432; 1873-6432
• DOI: 10.1016/j.eiar.2013.12.004

Assessing the average energy intensity of Internet transmissions is a complex task that has been a controversial subject of discussion. Estimates published over the last decade diverge by up to four orders of magnitude — from 0.0064kilowatt-hours per gigabyte (kWh/GB) to 136kWh/GB. This article presents a review of the methodological approaches used so far in such assessments: i) top–down analyses based on estimates of the overall Internet energy consumption and the overall Internet traffic, whereby average energy intensity is calculated by dividing energy by traffic for a given period of time, ii) model-based approaches that model all components needed to sustain an amount of Internet traffic, and iii) bottom–up approaches based on case studies and generalization of the results. Our analysis of the existing studies shows that the large spread of results is mainly caused by two factors: a) the year of reference of the analysis, which has significant influence due to efficiency gains in electronic equipment, and b) whether end devices such as personal computers or servers are included within the system boundary or not. For an overall assessment of the energy needed to perform a specific task involving the Internet, it is necessary to account for the types of end devices needed for the task, while the energy needed for data transmission can be added based on a generic estimate of Internet energy intensity for a given year. Separating the Internet as a data transmission system from the end devices leads to more accurate models and to results that are more informative for decision makers, because end devices and the networking equipment of the Internet usually belong to different spheres of control. •Assessments of the energy intensity of the Internet differ by a factor of 20,000.•We review top–down, model-based, and bottom–up estimates from literature.•Main divergence factors are the year studied and the inclusion of end devices.•We argue against extending the Internet system boundary beyond data transmission.•Decision-makers need data that differentiates between end devices and transmission.