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L'Énergie représente l'un des principaux postes de dépense pour un centre de données, dont la majeure partie est attribuée au système de refroidissement, ainsi qu'aux nombreuses parties sous-jacentes, comme les équipements réseau et au grand nombre de machines utilisées. Ces infrastructures sont très énergivores, et leur nombre ne cesse d'augmenter à travers le monde, notamment grâce à la popularité croissante du Cloud Computing. De nombreux logiciels sont nécessaires au bon fonctionnement de ces infrastructures, notamment pour la gestion du réseau, du stockage de données, de l'ordonnancement des tâches ainsi que de la supervison de l'ensemble du matériel et des logiciels. Tous ces logiciels consomment une quantité significative d'énergie, mais ne sont pourtant pas pris en compte dans les calculs de l'efficience énergétique des infrastructures. La communauté scientifique ainsi que les opérateurs de centres de données ont développé de nombreuses approches afin d'évaluer et d'optimiser globalement la consommation énergétique, mais la question du coût en énergie des infrastructures logicielles reste peu étudiée. L'objectif de cette thèse est de proposer des méthodes permettant d'analyser de bout en bout l'efficacité énergétique logicielle des infrastructures de traitement de données. Pour cela, nous proposons des approches et outils permettant d'estimer fidèlement la consommation énergétique des logiciels éxécutés sur une infrastructure distribuée, ainsi qu'un indicateur permettant de calculer leur efficience énergétique. Dans un premier temps, nous proposons SmartWatts, un wattmètre logiciel permettant d'estimer la consommation énergétique des conteneurs logiciels déployés sur une machine. Ensuite, nous proposons SelfWatts, un contrôleur permettant d'automatiser la configuration des wattmètres logiciels afin de faciliter leur déploiement dans des infrastructures hétérogènes. Et enfin, nous proposons le xPUE, un indicateur permettant de calculer l'efficience énergétique des logiciels et du matériel en temps réel aux différents niveaux d'une infrastructure. À travers ces différentes contributions, nous visons à faire évoluer la connaissance dans le domaine de la consommation énergétique des logiciels, et permettre de mesurer avec précision la consommation énergétique des logiciels déployés aux différents niveaux des infrastructures. Cela permet aux opérateurs de ces infrastructures, mais également aux développeurs et utilisateurs de logiciels d'observer et d'analyser en détails la consommation énergétique et ainsi d'assister dans l'optimisation de celle-ci. Energy is one of the biggest expenses for a data center, most of which is attributed to the cooling system, as well as the many underlying parts, such as network equipment and the large number of machines used. These infrastructures are very energy-intensive, and their number is constantly increasing around the world, especially due to the growing popularity of the Cloud Computing.A lot of software is needed to run these infrastructures, especially for network management, data storage, task scheduling and the supervision of all hardware and software. All these software consume a significant amount of energy, but are not taken into account in the calculation of the energy efficiency of the infrastructures. The scientific community as well as data center operators have developed many approaches to evaluate and optimize energy consumption globally, but the question of the energy cost of software infrastructures remains rarely studied. The objective of this thesis is to propose methods to analyze the end-to-end software energy efficiency of data processing infrastructures. To do so, we propose approaches and tools to accurately estimate the energy consumption of software running on a distributed infrastructure, as well as an indicator to calculate their energy efficiency. Firstly, we introduce SmartWatts, a software power meter to estimate the energy consumption of software containers deployed on a machine. Secondly, we propose SelfWatts, a controller to automate the configuration of software power meters to facilitate their deployment in heterogeneous infrastructures. And finally, we propose xPUE, a metric to calculate the energy efficiency of software and hardware in real time at different levels of an infrastructure. Through these contributions, we aim to advance the knowledge in the field of software energy consumption, and allow to accurately measure the energy consumption of software deployed at different levels of the infrastructure. This allows infrastructure operators, but also software developers and users to observe and analyze in detail the energy consumption and thus assist in its optimization.

This report provides an overview of the United Nations Framework Convention on Climate Change (UNFCCC) reporting process for national greenhouse gas (GHG) inventories with particular focus on the methodology used for estimating direct nitrous oxide (N2O) emissions from mineral fertiliser. Examples are given of several schemes for sub-national or project- level approaches to monitor and estimate the impact of fertiliser best management practice (BMP) on direct N2O emission reductions. The extent to which these approaches align with those of the national inventory is evaluated and conclusions drawn on actions needed to close any gaps. Collectively, 63% of world fertiliser consumed is reported at the higher Tier 2 and Tier 3 levels. However, countries reporting at the Tier 1 level for direct N2O emissions from fertilisers still predominate, accounting for 180 of the total 191 reporting countries. Case studies of fertiliser BMP were generally found to align well with national inventory methods, mainly through the use of modifiers to Tier 1 & 2 emission factors (EFs). Good quality activity data (AD) is a main challenge to full alignment of project and national inventory-based estimates of fertiliser-induced emissions and emission reductions. Lack of quality AD also limits the extent to which national inventories can capture mitigation impacts. Given the early stage of developing accounting processes for agricultural GHGs, an opportunity now exists to design national GHG inventory processes to reflect emissions savings achieved through mitigation actions such as implementing fertiliser BMPs. To achieve this, it is necessary to strengthen the alignment among different policy instruments, inventory compilation processes and national data providers. In this respect, we should seize opportunities made available from instruments such as the Nationally Determined Contributions that would support development of project-specific, nationally consistent and inventory-aligned measurement, reporting and verification (MRV) ...

AbstractThe summer of 2018 was characterized by prolonged heatwaves over Northern Europe, associated with persistent atmospheric blocking, and an unusually northward jet stream location over Scandinavia. Whilst event attribution studies tend to focus on the change in probability or magnitude of the extreme temperatures themselves, we provide context to these studies by examining whether there are human induced trends in the atmospheric circulation that might affect the likelihood of similar extreme circulation patterns and associated heat waves occurring in the future. We examine trends and variability in summer jet latitude, blocking frequency and overall circulation pattern over the Scandinavian sector in a variety of reanalyses and climate model ensembles. Both the number of blocked days, and the average jet location for summer 2018 were unprecedented in the reanalyses, and rare in climate model simulations. We found no robust evidence of past or future externally forced changes in summer blocking frequency over Scandinavia in model simulations, whilst trends in circulation analogs were also largely insignificant. Trends in jet latitude were dependent on the time period examined, models included and other analysis choices. Overall, we found no robust evidence for systematic trends in average or extreme years toward Summer 2018‐like conditions for any of the three indices, nor in the frequency of co‐occurring extreme northward jet latitude and high blocking frequency. We conclude that Summer 2018s circulation can likely be explained by internal atmospheric variability.

(IF 3.90; Q1) ; International audience ; Coastal ecosystems are subjected to an increasing number of anthropogenic drivers, including marine renewable energies and climate change (CC). These drivers can interact in complex ways, which may lead to cumulative effects (CEs) whose potential consequences on the ecosystems need to be addressed. We used a holistic approach—ecological network analysis (ENA)—coupled with a two-dimensional food web model—Ecospace—to conduct an ecosystem study of the CEs of CC plus the operation of an offshore wind farm on ecosystem functioning in the extended Bay of Seine (English Channel). Mapped ENA indices showed that CEs were not restricted to the wind farm area, i.e. where anthropogenic drivers are concomitant. CEs varied both in space and among ecosystem properties, displaying that ENA indices can distinguish between different cumulative pathways that modify ecosystem functioning in multiple ways. Moreover, the effects seemed to be tied to the structuring role of CC, and differed under the 2050 and 2100 conditions. Such changes resulted in stronger loss of ecosystem resilience under the 2100 conditions despite the benefits of the reef and reserve effects of the wind farm.

The new GHG calculator named SECTOR (Source-selective and Emission-adjusted GHG CalculaTOR for Cropland) is based on the IPCC Tier 2 approach for rice as well as other crops. The new features of SECTOR facilitate high flexibility in terms of entering newly obtained emission factors, easy data transfer from crop statistics for entering activity data and detailed specifications of GHG scenarios. A new procedure of entering frequency-based data on current water management practices was also developed. Moreover, the tool allows deviating from the 2006 IPCC Guidelines by considering field records with high background levels of N₂O emissions in the overall assessment of GHG emissions. This article assesses different applications of the tool, namely as add-ons to field measurements, for GHG calculation at national/sectorial scale and within measurement, reporting and verification of development projects. SECTOR is downloadable in the form of templates that can be used to develop custom versions with varying levels of disaggregated data entries at different scales. A case study for rice production in one Vietnamese province demonstrates the potential to display GHG results in combination with GIS. SECTOR can easily be adjusted to incorporate new emission factors and calculation procedures expected in forthcoming revisions of the IPCC Guidelines.

Abstract During the course of a severe accident in a Pressurized Water Reactor, pressurization of the containment occurs and hydrogen can be produced by the reactor core oxidation and distributed in the containment according to natural, mixed and forced convection flows induced by break flow, wall condensation and spray systems used in some reactors' containment to prevent overpressure. Because of these phenomena, water can be collected in the sump containment, inducing further heat and mass exchanges between the sump surface and the atmosphere. Considering the large volume of the reactor containment, LP (0D) codes are preferred to CFD calculations, which still remain a very challenging task to compute. The French IRSN has tested different tools for containment studies with lumped-parameter codes and the reference code is now ASTEC/CPA, so that mainly results of this code will be presented here. This paper focuses mainly on several IRSN tests especially developed for containment studies and the above mentioned thermal-hydraulical phenomena. The objective of this paper is to present the validations performed with LP codes on these different experimental tests. Experiments on the TOSQAN facility are considered.

Se destaca la importancia de recuperar el equilibrio humano-no humano en el ecosistema del mundo frente al cambio climático, para el efecto se esboza la necesidad de una articulación de saberes partiendo del realismo especulativo. Se gira del enfoque de ciudad al de territorio, tomando como caso el DM de Quito y sugiere hacer de esta práctica una fuente de formación.

Glaciers are retreating globally, and the resulting ice-free areas provide an experimental system for understanding species colonization patterns, community formation, and dynamics. The last several years have seen crucial advances in our understanding of biotic colonization after glacier retreats, resulting from the integration of methodological innovations and ecological theories. Recent empirical studies have demonstrated how multiple factors can speed up or slow down the velocity of colonization and have helped scientists develop theoretical models that describe spatiotemporalchanges in community structure. There is a growing awareness of how different processes (e.g., time since glacier retreat, onset or interruption of surface processes, abiotic factors, dispersal, biotic interactions) interact to shape community formation and, ultimately, their functional structure through succession. Here, we examine how these studies address key theoretical questions about community dynamics and show how classical approaches are increasingly being combined with environmental DNA metabarcoding and functional trait analysis to document the formation of multitrophic communities, revolutionizing our understanding of the biotic processes that occur following glacier retreat.