Assessing anthropogenic heat flux of public cloud data centers: current and future trends

Abstract

Global average temperature had been significantly increasing during the past century, mainly due to the growing rates of greenhouse gas (GHG) emissions, leading to a global warming problem. Many research works indicated other causes of this problem, such as the anthropogenic heat flux (AHF). Cloud computing (CC) data centers (DCs), for example, perform massive computational tasks for end users, leading to emit huge amounts of waste heat towards the surrounding (local) atmosphere in the form of AHF. Out of the total power consumption of a public cloud DC, nearly 10% is wasted in the form of heat. In this paper, we quantitatively and qualitatively analyze the current state of AHF emissions of the top three cloud service providers (i.e., Google, Azure and Amazon) according to their average energy consumption and the global distribution of their DCs. In this study, we found that Microsoft Azure DCs emit the highest amounts of AHF, followed by Amazon and Google, respectively. We also found that Europe is the most negatively affected by AHF of public DCs, due to its small area relative to other continents and the large number of cloud DCs within. Accordingly, we present mean estimations of continental AHF density per square meter. Following our results, we found that the top three clouds (with waste heat at a rate of 1,720.512 MW) contribute an average of more than 2.8% out of averaged continental AHF emissions. Using this percentage, we provide future trends estimations of AHF densities in the period [2020–2100]. In one of the presented scenarios, our estimations predict that by 2100, AHF of public clouds DCs will reach 0.01 Wm−2.

Analysis of Anthropogenic Waste Heat Emission from an Academic Data Center

“…In addition to the value of recovering waste heat as a resource, there may be value in not releasing the waste heat to the ambient environment. This is particularly true if the data center is located in an urban setting where surface heating contributes to the urban heat island effect or disturbance of the ambient environment is a concern in cold areas [9]. For urban environments, use of a waste heat data set in a broader analysis of the environmental impact of anthropogenic heat emitted by industrial and residential buildings would be beneficial.…”

“…In 2020, the average PUE value for typical data centers in the US was 1.6 [8]. In comparison, the best hyper-scale data centers run by Google, Microsoft, and Amazon achieved PUE values of 1.1 [2,5,9], 1.25 [9], and 1.14 [9]. Large-scale data centers in the private sector following LEED design concepts reported an average PUE value of 1.38 in 2022 [8].…”

Use of semantic segmentation for mapping Sargassum on beaches

“…Maps are a fundamental tool for the study and visualization of phenomena with some spatial component; that is why they are applied in various areas of knowledge ( Baniata, Mahmood & Kertesz, 2021 ; Ma, Zhang & Huang, 2021 ). Concerning the study of Sargassum , there are studies ( Arellano-Verdejo & Lazcano-Hernandez, 2020 ; Arellano-Verdejo & Lazcano-Hernández, 2021 ), that present an approach to the generation of Sargassum maps on the beach.…”