• Energy Research
• 2025-2025close
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• 11. Sustainability close

Creating and delivering products and services that promote sustainability is increasingly important in today’s economy. Novel services based on digital technologies and infrastructure can significantly contribute to sustainable development, as demonstrated by digitally enabled car-sharing services where increased asset utilization reduces production-related greenhouse gas emissions. However, there is still limited knowledge on how digital service innovation can purposefully be applied to promote sustainability. To address this gap, we conduct a systematic literature review and perform a qualitative inductive analysis of 50 articles on the impact of digital service innovation on social, environmental, and economic sustainability. We provide a comprehensive overview of real-world applications and identify five underlying mechanisms through which innovation with digital services can drive sustainable development. In doing so, we aim to pave the way to purposefully conceive, design, and implement digital services for sustainability.

The adoption of electric vehicles (EVs), including electric taxis and buses, as a mode of transportation, is rapidly increasing in cities. In addition to providing economic and environmental benefits, these fleets can potentially participate in the energy arbitrage market by leveraging their mobile energy storage capabilities. This presents an opportunity for EV owners to contribute to a more sustainable and efficient energy system while also reducing their operational costs. The present study introduces deterministic and single-stage stochastic optimization frameworks that aim to maximize revenue by optimizing the charging, discharging, and travel of a fleet of electric vehicles in the context of uncertainty surrounding both spatial and temporal energy prices. The simulations are performed on a fleet of electric delivery trucks, which have to make deliveries to certain locations on specific dates. The findings indicate the promising potential of bidirectional electric vehicle charging as a mobile grid asset. However, it is important to note that significant revenue is only realized in scenarios where there is substantial variation in prices between different areas, and when these price variations can be accurately forecasted with a high level of confidence.

By providing various services, such as Demand Response (DR), buildings can play a crucial role in the energy market due to their significant energy consumption. However, effectively commissioning buildings for such desired functionalities requires significant expert knowledge and design effort, considering the variations in building dynamics and intended use. In this study, we introduce an adaptive data-driven prediction scheme based on Willems' Fundamental Lemma within the building control hierarchy. This scheme offers a versatile, flexible, and user-friendly interface for diverse prediction and control objectives. We provide an easy-to-use tuning process and an adaptive update pipeline for the scheme, both validated through extensive prediction tests. We evaluate the proposed scheme by coordinating a building and an energy storage system to provide Secondary Frequency Control (SFC) in a Swiss DR program. Specifically, we integrate the scheme into a three-layer hierarchical SFC control framework, and each layer of this hierarchy is designed to achieve distinct operational goals. Apart from its flexibility, our approach significantly improves cost efficiency, resulting in a 28.74% reduction in operating costs compared to a conventional control scheme, as demonstrated by a 52-day experiment in an actual building. Our findings emphasize the potential of the proposed scheme to reduce the commissioning costs of advanced building control strategies and to facilitate the adoption of new techniques in building control.

Le carbone noir est une petite particule d'aérosol (ou aérienne) de courte durée de vie liée au réchauffement climatique et aux effets nocifs sur la santé. Il est rejeté par la combustion incomplète de carburants à base de carbone (c.-à-d. les combustibles fossiles, les biocarburants ou le bois) sous la forme de matière particulaire très fine. Le carbone noir n'est pas rejeté seul, mais en tant que composante d'une matière particulaire d'un diamètre inférieur ou égal à 2,5 micromètres (PM2,5). En tant que membre du Conseil de l'Arctique, le Canada est engagé à produire un inventaire annuel des émissions de carbone noir. Ces données serviront à informer les Canadiens au sujet des émissions de carbone noir et à fournir des renseignements inestimables pour l'élaboration de stratégies de gestion de la qualité de l'air. Les données utilisées pour la compilation du rapport proviennent des sections de l'Inventaire des émissions de polluants atmosphériques (IEPA) en particulier pour les émissions de matières particulaires fines (PM2,5) provenant de sources liées à la combustion Renseignements supplémentaires Pour un complément d'information sur l'Inventaire des émissions de carbone noir du Canada, consulter : https://Canada.ca/carbone-noir Pour les émissions canadiennes d'autres polluants atmosphériques, se reporter à l'Inventaire des émissions de polluants atmosphériques : https://www.canada.ca/fr/environnement-changement-climatique/services/polluants/inventaire-emissions-atmospheriques-apercu.html Outil d'interrogation interactif de l'IEPA et carbone noir : https://pollution-waste.canada.ca/air-emission-inventory/?GoCTemplateCulture=fr-CA Soutien aux projets : Inventaire des émissions de carbone noir au Canada 2013-2023 Black carbon is a short-lived, small aerosol (or airborne) particle linked to both climate warming and adverse health effects. It is emitted from incomplete combustion of carbon-based fuels (i.e., fossil fuels, biofuels, wood) in the form of very fine particulate matter. Black carbon is not emitted on its own, but as a component of particulate matter less than or equal to 2.5 micrometres in diameter (PM2.5). As a member of the Arctic Council, Canada has committed to producing an annual inventory of black carbon emissions. This data will serve to inform Canadians about black carbon emissions and provide valuable information for the development of air quality management strategies. The data used to compile the report originate from sections of the Air Pollutant Emission Inventory (APEI) specifically fine particulate matter (PM2.5) emissions from combustion-related sources. Supplemental Information For more information on Canada's Black Carbon Inventory, please visit: https://Canada.ca/black-carbon For Canada's emissions of other air pollutants, please reference the Air Pollutant Emission Inventory: https://Canada.ca/APEI APEI and Black Carbon Interactive Query Tool: https://pollution-waste.canada.ca/air-emission-inventory Supporting Projects: Canada's Black Carbon Inventory for 2013-2023

Successful applicants of the 2017-2019 Solar for Community Buildings Program, that enables eligible community groups and organizations to generate solar photovoltaic (PV) electricity on their roofs or properties

L'objectif de cette page est de décrire l'organisation du rapport d'inventaire des gaz à effet de serre et d'indiquer où trouver le matériel en ligne. Pour en savoir plus sur l'inventaire officiel des gaz à effet de serre du Canada, visitez la page principale : https://www.canada.ca/inventaire-ges Contactez-nous : https://www.canada.ca/fr/environnement-changement-climatique/services/changements-climatiques/emissions-gaz-effet-serre/coordonnees-equipe.html Documents disponibles en ligne : Le Rapport d'inventaire national (RIN) comprend trois parties. La Partie 1 du RIN comprend le Sommaire et les Chapitres 1 à 8. La Partie 2 comprend les Annexes 1 à 7. La Partie 3 comprend les Annexes 8 à 13. Le rapport complet se trouve à l'adresse suivante : https://publications.gc.ca/site/fra/9.506002/publication.html. Les fichiers de données des Partie 2 et Partie 3 sont accessibles en cliquant sur le bouton « Explorer », puis « Aller à la ressource » ci-dessous. Description du contenu de chaque répertoire: A-Secteur du GIEC : Contient divers fichiers d'émissions de gaz à effet de serre (GES) par secteur du Groupe d'experts intergouvernemental sur l'évolution du climat (GIEC) et par gaz, pour toutes les années, pour le Canada et pour les provinces et territoires. B-Secteur économique : Contient divers fichiers d'émissions de GES par secteurs économiques, pour toutes les années pour le Canada et pour la dernière année pour les provinces et les territoires. Dans le fichier FR_GES_Econ_Canada, un onglet contenant la relation entre les secteurs du GIEC et les secteurs économiques est également inclus. Les émissions sont également présentées par gaz pour le Canada et pour les provinces et territoires. C-Tableaux Électricité Canada Provinces Territoires : Contient un sommaire et des tableaux sur l'intensité des GES pour l'électricité au Canada. D-Coefficients d'émission : Contient des fichiers comprenant des informations sur les coefficients d'émission. E-ATCATF : contient des estimations de séries chronologiques pour le secteur de l'affectation des terres, du changement d'affectation des terres et foresterie (ATCATF), des fichiers géomatiques contenant des estimations attribuées à des unités spatiales, et un plan pluriannuel d'amélioration de la foresterie. F-Agriculture : Contient des estimations de séries chronologiques pour le secteur de l'agriculture et des fichiers géomatiques contenant des estimations attribuées à des unités spatiales. G-Annexes supplémentaires du RIN : Contient l'Annexe 1 (catégories clés), l'Annexe 2 (incertitude), l'Annexe 3 (méthodologies), l'Annexe 4 (approches sectorielles et de référence, et bilan énergétique national), l'Annexe 5 (exhaustivité), l'Annexe 7 (ozone et précurseurs d'aérosols) et l'Annexe 8 (protocole d'arrondissement) du Rapport d'inventaire national (RIN). The purpose of this page is to describe the organization of the greenhouse gas inventory report and to indicate where to find the online material. To learn more about Canada's official greenhouse gas inventory, visit the Main page: https://www.canada.ca/ghg-inventory Contact us: https://www.canada.ca/en/environment-climate-change/services/climate-change/greenhouse-gas-emissions/contact-team.html Documents available online: The National Inventory Report (NIR) comprises three parts. Part 1 of the NIR includes the Executive Summary and Chapters 1 to 8. Part 2 consists of Annexes 1 to 7. Part 3 includes Annexes 8 to 13. The full report can be found at the following address: https://publications.gc.ca/site/eng/9.506002/publication.html. Part 2 and Part 3 data files can be accessed by clicking on the "Explore" button below, then "Go to resource". Description of the content of each folder: A-IPCC Sector: Contains various greenhouse gas (GHG) emissions files by Intergovernmental Panel on Climate Change (IPCC) sector and by gas, for all years, for Canada and for provinces and territories. B-Economic Sector: Contains various GHG emissions files by Economic sectors, for all years for Canada and for the latest year for provinces and territories. In the EN_GHG_Econ_Canada file, a tab containing the relationship between IPCC sector and Economic sector is also provided. Emissions are also presented by gas for Canada and for the provinces and territories. C-Tables Electricity Canada Provinces Territories: Contains summary and GHG intensity tables for Electricity in Canada. D-Emission Factors: Contains files with information on emission factors. E-LULUCF: Contains time-series estimates for the Land Use, Land-Use Change and Forestry (LULUCF) sector, geomatics files containing estimates attributed to spatial units, and a multi-year forestry improvement plan. F-Agriculture: Contains time-series estimates for the Agriculture sector and geomatics files containing estimates attributed to spatial units. G-Additional NIR Annexes: Contains Annex 1 (key categories), Annex 2 (uncertainty), Annex 3 (methodologies), Annex 4 (sectoral and reference approaches, and national energy balance), Annex 5 (completeness), Annex 7 (ozone and aerosol precursors) and Annex 8 (rounding protocol) of the National Inventory Report (NIR).

The climate crisis is the biggest threat to the health, development, and wellbeing of the current and future generations. While there is extensive evidence on the direct impacts of climate change on human livelihood, there is little evidence on how children and young people are affected, and even less discussion and evidence on how the climate crisis could affect violence against children.In this commentary, we review selected research to assess the links between the climate crisis and violence against children.We employ a social-ecological perspective as an overarching framework to organize findings from the literature and call attention to increased violence against children as a specific, yet under-examined, direct and indirect consequence of the climate crisis.Using such a perspective, we examine how the climate crisis exacerbates the risk of violence against children at the continually intersecting and interacting levels of society, community, family, and the individual levels. We propose increased risk of armed conflict, forced displacement, poverty, income inequality, disruptions in critical health and social services, and mental health problems as key mechanisms linking the climate crisis and heightened risk of violence against children. Furthermore, we posit that the climate crisis serves as a threat multiplier, compounding existing vulnerabilities and inequities within populations and having harsher consequences in settings, communities, households, and for children already experiencing adversities.We conclude with a call for urgent efforts from researchers, practitioners, and policymakers to further investigate the specific empirical links between the climate crisis and violence against children and to design, test, implement, fund, and scale evidence-based, rights-based, and child friendly prevention, support, and response strategies to address violence against children.

Global climate challenge is demanding urgent actions for decarbonization, while electric power systems take the major roles in clean energy transition. Due to the existence of spatially and temporally dispersed renewable energy resources and the uneven distribution of carbon emission intensity throughout the grid, it is worth investigating future load planning and demand management to offset those generations with higher carbon emission rates. Such techniques include inter-region utilization of geographically shiftable resources and stochastic renewable energy. For instance, data center is considered to be a major carbon emission producer in the future due to increasing information load, while it holds the capability of geographical load balancing. In this paper, we propose a novel planning and operation model minimizing the system-level carbon emissions via sitting and operating geographically shiftable resources. This model decides the optimal locations for shiftable resources expansion along with power dispatch schedule. To accommodate future system operation patterns and a wide range of operating conditions, we incorporate 20-year fine-grained load and renewables scenarios for grid simulations of realistic sizes (e.g., up to 1888 buses). To tackle the computational challenges coming from the combinatorial nature of such large-scale planning problem, we develop a customized Monte Carlo Tree Search (MCTS) method, which can find reasonable solutions satisfying solution time limits. Besides, MCTS enables flexible time window settings and offline solution adjustments. Extensive simulations validate that our planning model can reduce more than 10\% carbon emission across all setups. Compared to off-the-shelf optimization solvers such as Gurobi, our method achieves up to 8.1X acceleration while the solution gaps are less than 1.5\% in large-scale cases. Accepted at IEEE Transactions on Power Systems

In order to solve the problem of excessive burden of electricity and energy consumption in urban landscape buildings clusters, the study combined data mining algorithms to establish a prediction model for energy-saving renovation of urban landscape building clusters. Firstly, the energy demand and energy consumption of theurban landscape buildings complex were analysed, a mathematical model was established to predict the energy consumption of the building complex. Then, the prediction model of energy-saving retrofitting of building clusters was constructed by combining data mining techniques. The experimental results show that the change trend of total energy consumption is different under different single influencing factors of energy consumption. Among them, the lighting power density factor has the greatest influence on energy consumption, and its annual energy consumption change rate can reach about 0.35. Applying the prediction model to the energy consumption prediction of 15 urban single buildings, it was found that the total energy consumption of the buildings before the retrofit was much higher than that after the retrofit, and the energy-saving rate of the whole observed sample building group was as high as 18.5%, meanwhile, the highest energy-saving rate of the single buildings reached 30.1%.