Green-cloud scheduling: Minimizing Energy use in Multi-Cloud Operations within SLAs

Operational carbon footprint of the U.S. water and wastewater sector’s energy consumption

The relationship between operational energy demand and embodied energy in Dutch residential buildings

Energy use is an indicator of economic growth. However, high energy intensity has two main disadvantages. First, low energy efficiency increases a country’s dependence on other countries, especially when the country lacks energy sources. Second, if the country’s energy needs are met using traditional fossil fuels, this increases its CO2 emissions and reduces its air quality. Improving energy efficiency and reducing energy intensity are essential to reach the sustainability targets. This paper investigates the determinants of energy use in Turkiye for the period 1991–2019 by taking a dual approach. First, utilizing the Tapio decoupling factor, the decoupling factor analysis is not only being done for total energy use and real GDP, but also for industrial energy use and industrial income. Second, the factors determining the country’s total energy use are also examined, followed by an investigation of the indicators of energy use in the industry sector, which is highly energy intensive. For the industrial sector, two different decomposition analyses are performed and results are compared. The refined Laspeyres index method is adopted, and for each analysis, three main factors are considered. The empirical findings demonstrate that the income effect and population effect increased Turkiye’s total energy use, whereas the energy intensity effect decreased it. The first decomposition analysis for the industrial energy use reveals partly contrasting results with the previously published articles. For the industry sector, the second analysis show that productivity and employment increased Turkiye’s sectoral energy use; however, the sector’s energy intensity reduced it. Turkiye achieved some success in terms of reducing energy intensity at the sectoral and aggregate levels; however, as the findings of the present study demonstrate, further efforts are needed to lessen the country’s energy dependence and also to achieve future environmental sustainability targets. Trends relating to the determining factors in total and sectoral energy use are also compared in this paper, and some policy implications are presented.

Buildings are at the locus of three trends driving China's increased energy use and emissions: urbanization, growing personal consumption, and surging heavy industrial production. Migration to cities and urban growth create demand for new building construction. Higher levels of per-capita income and consumption drive building operational energy use with demand for higher intensity lighting, thermal comfort, and plug-load power. Demand for new buildings, infrastructure, and electricity requires heavy industrial production. In order to quantify the implications of China's ongoing urbanization, rising personal consumption, and booming heavy industrial sector, this study presents a lifecycle assessment (LCA) of the energy use and carbon emissions related to residential and commercial buildings. The purpose of the LCA model is to quantify the impact of a given building and identify policy linkages to mitigate energy demand and emissions growth related to China's new building construction. As efficiency has become a higher priority with growing energy demand, policy and academic attention to buildings has focused primarily on operational energy use. Existing studies estimate that building operational energy consumption accounts for approximately 25% of total primary energy use in China. However, buildings also require energy for mining, extracting, processing, manufacturing, and transporting materials, as well as energy for construction, maintenance, and decommissioning. Building and supporting infrastructure construction is a major driver of industry consumption--in 2008 industry accounted for 72% of total Chinese energy use. The magnitude of new building construction is large in China--in 2007, for example, total built floor area reached 58 billion square meters. During the construction boom in 2007 and 2008, more than two billion m{sup 2} of building space were added annually; China's recent construction is estimated to account for half of global construction. Lawrence Berkeley National Laboratory (LBNL) developed an integrated LCA model to capture the energy and emissions implications of all aspects of new buildings from material mining through construction, operations, and decommissioning. Over the following four sections, this report describes related existing research, the LBNL building LCA model structure and results, policy linkages of this lifecycle assessment, and conclusions and recommendations for follow-on work. The LBNL model is a first-order approach to gathering local data and applying lifecycle assessment to buildings in the Beijing area--it represents one effort among a range of established, predominantly American and European, LCA models. This report identifies the benefits, limitations, and policy applications of lifecycle assessment modeling for quantifying the energy and emissions impacts of specific residential and commercial buildings.

Urban residential energy switching in China between 1980 and 2014 prevents 2.2 million premature deaths

As quantum computers increase in size, the total energy used by a quantum data center, including the cooling, will become a greater concern. The cooling requirements of quantum computers, which operate at temperatures near absolute zero, are determined by computing system parameters, including the number and type of physical qubits, the packaging efficiency of the system, and the split between circuits operating at cryogenic temperatures and those operating at room temperature. When combined with thermal system parameters such as cooling efficiency and cryostat heat transfer, the total energy use can be determined using a first-principles energy model. These models show that cooling of quantum computers differs in two fundamental ways from conventional data centers: (1) the energy required for cooling is much greater than the energy required for computation, and (2) the cooling loads are sensitive to the computational architecture. The temperature requirements for different qubit types can change energy requirements by orders of magnitude. Power use and computational power, as quantified by quantum volume, are analytically correlated. Approaches are identified for minimizing energy use in integrated quantum systems relative to computational power. Designing a sustainable quantum computer will require both efficient cooling and system design that minimizes cooling requirements.

Structural, geographic, and social factors in urban building energy use: Analysis of aggregated account-level consumption data in a megacity

Detached accessory dwelling units are a building typology that, when built to passive design standards, can help reduce GHG emissions while addressing the socioeconomic pressures facing many housing markets. Energy performance metrics like those used in passive design standards are based on per unit of floor area and lead to a size-bias against smaller housing typologies. A life cycle assessment of cost-optimal passive house sizes ranging from 230 m² (2,500 ft²) to 30 m² (300 ft²) is performed to understand their total life cycle energy use and GHG emissions implications. Additionally, an analysis using BEopt examines operational energy use for 10 cost-optimal passive house sizes ranging from 230 m² (2,500 ft²) to 30 m² (300 ft²) across all 17 climate zones and examines how cost-optimal passive design changes with house size. The results show that per-occupant energy use and GHG emissions are similar or better for small house sizes and that cost-optimal passive design does not change significantly with house size.

Sustainable High-rises

As the population increases, the growing demand for residential housing escalates construction activities, significantly impacting global warming by contributing 42% of primary energy use and 39% of global greenhouse gas (GHG) emissions. This study addresses a gap in research on lifecycle assessment (LCA) for Indian residential buildings by evaluating the full cradle-to-grave carbon footprint of a typical single-family house in Northern India. A BIM-based LCA framework was applied to a 110 m2 single-family dwelling over a 60-year life span. Operational use performance and climate analysis was evaluated via cove tool. The total carbon footprint over a 60-year lifespan was approximately 5884 kg CO2e, with operational energy use accounting for about 87% and embodied carbon approximately 11%. Additional impacts came from maintenance and replacements. Energy usage was calculated as 71.76 kWh/m2/year and water usage as 232.2 m3/year. Energy consumption was the biggest driver of emissions, but substantial impacts also stemmed from material production. Cement-based components and steel were the largest embodied carbon contributors. Under the business-as-usual (BAU) scenario, the operational emissions reach approximately 668,000 kg CO2e with HVAC and 482,000 kg CO2e without HVAC. The findings highlight the necessity of integrating embodied carbon considerations alongside operational energy efficiency in India’s building codes, emphasizing reductions in energy consumption and the adoption of low-carbon materials to mitigate the environmental impact of residential buildings. Future work should focus on the dynamic modeling of electricity decarbonization, improved regional datasets, and scenario-based LCA to better support India’s transition to net-zero emissions by 2070.

CO2 emissions are reduced by cutting fossil energy use.Matters on carbon emission efficiency or low carbon education can be delivered through educational processes.This study aims to describe articles in terms of total publications, citations, authors, countries, journals, publishers, and co-authorship network using most frequently used keywords and determine what is to be researched in the future.Bibliometrics was used to review articles in the Scopus database .The PRISMA model was used for data collection, and VOSviewer and Harzing's Publish or Perish were employed for data analysis.A total of 917 articles were identified, and 456 were selected.The results of the study showed that there has been an increase in the number of publications.Most of the studies were conducted in China, the USA, and the UK.Journal of Cleaner Production and Elsevier Ltd have been the most productive journal and publisher.The most frequently used keywords in research was "carbon".Within the period, several keywords such as "low carbon", "higher education", and "education" have been unrelated and understudied.It was found that the "low-carbon" policy has been implemented in the forms of energy policy, engineering education, and energy efficiency.Monitoring of "carbon emissions" has been conducted in the form of carbon footprint, strengthened by controls such as controls of "energy use", "energy efficiency", "energy consumption", and "carbon footprint"."Emissions control" needs to be linked with "education".Based on the findings, further studies on "energy efficiency" and "carbon footprint" combined with "education" are needed.

Building energy use in China: Ceiling and scenario

Climate target fulfilment in scenarios for a sustainable Swedish built environment beyond growth

Predicating Energy Demand and Carbon Emissions of the Yellow River Delta High-efficiency Eco-economic Zone

AimThe frequency of different body sizes in an ecological community (the individual size distribution, or ISD) is a key link between the number of individual organisms present in a community and community function—total biomass or total energy use. If the ISD changes over time, the dynamics of community function may become decoupled from trends in abundance. Understanding how, and how often, the ISD modulates the relationship between abundance, biomass and energy use is of critical importance to understand biodiversity trends in the Anthropocene. Here, we conduct the first macroecological‐scale analysis of this type for avian communities.LocationNorth America, north of Mexico.Time Period1989–2018.Major Taxa StudiedBreeding birds.MethodsWe used species' traits to generate annual ISDs for bird communities in the North American Breeding Bird Survey. We compared the long‐term trends in total biomass and energy use to the trends generated from a null model of an unchanging ISD.ResultsTrends in biomass have been evenly split between increases and decreases, but the trends predicted by the null model were dominated by decreases. A substantial number of communities have undergone a shift in the ISD favouring larger bodied species, resulting in a less negative trend in biomass than would be expected had the ISD remained static. Trends in energy use more closely paralleled the null model.Main ConclusionsTaking changes in the ISD into account qualitatively changes the continental‐scale picture of how biomass and energy use have changed over the past 30 years. For North American breeding birds, shifts in species composition favouring larger bodied species may have partially offset declines in standing biomass driven by losses of individuals over the past 30 years.