89 resultados para Energy consumption in buildings


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The objective of this article is to review the scientific literature on airflow distribution systems and ventilation effectiveness to identify and assess the most suitable room air distribution methods for various spaces. In this study, different ventilation systems are classified according to specific requirements and assessment procedures. This study shows that eight ventilation methods have been employed in the built environment for different purposes and tasks. The investigation shows that numerous studies have been carried out on ventilation effectiveness but few studies have been done regarding other aspects of air distribution. Amongst existing types of ventilation systems, the performance of each ventilation methods varies from one case to another due to different usages of the ventilation system in a room and the different assessment indices used. This review shows that the assessment of ventilation effectiveness or efficiency should be determined according to each task of the ventilation system, such as removal of heat, removal of pollutant, supply fresh air to the breathing zone or protecting the occupant from cross infection. The analysis results form a basic framework regarding the application of airflow distribution for the benefit of designers, architects, engineers, installers and building owners.

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Methods of data collection are unavoidably rooted in some sort of theoretical paradigm, and are inextricably tied to an implicit agenda or broad problem framing. These prior orientations are not always explicit, but they matter for what data is collected and how it is used. They also structure opportunities for asking new questions, for linking or bridging between existing data sets and they matter even more when data is re-purposed for uses not initially anticipated. In this paper we provide an historical and comparative review of the changing categories used in organising and collecting data on mobility/travel and time use as part of ongoing work to understand, conceptualise and describe the changing patterns of domestic and mobility related energy demand within UK society. This exercise reveals systematic differences of method and approach, for instance in units of measurement, in how issues of time/duration and periodicity are handled, and how these strategies relate to the questions such data is routinely used to address. It also points to more fundamental differences in how traditions of research into mobility, domestic energy and time use have developed. We end with a discussion of the practical implications of these diverse histories for understanding and analysing changing patterns of energy/mobility demand at different scales.

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Data are presented for a nighttime ion heating event observed by the EISCAT radar on 16 December 1988. In the experiment, the aspect angle between the radar beam and the geomagnetic field was fixed at 54.7°, which avoids any ambiguity in derived ion temperature caused by anisotropy in the ion velocity distribution function. The data were analyzed with an algorithm which takes account of the non-Maxwellian line-of-sight ion velocity distribution. During the heating event, the derived spectral distortion parameter (D∗) indicated that the distribution function was highly distorted from a Maxwellian form when the ion drift increased to 4 km s−1. The true three-dimensional ion temperature was used in the simplified ion balance equation to compute the ion mass during the heating event. The ion composition was found to change from predominantly O4 to mainly molecular ions. A theoretical analysis of the ion composition, using the MSIS86 model and published values of the chemical rate coefficients, accounts for the order-of-magnitude increase in the atomic/molecular ion ratio during the event, but does not successfully explain the very high proportion of molecular ions that was observed.

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We have investigated methane (CH4) dissociative chemisorption on the Ni{100} surface by first-principles molecular dynamics (MD) simulations. Our results show that this reaction is mode-specific, with the n1 state being the most strongly coupled to efficient energy flow into the reaction coordinate when the molecule reaches the transition state. By performing MD simulations for two different transition state (TS) structures we provide evidence of TS structure-specific energy redistribution in methane chemisorption. Our results are compared with recently reported state-resolved measurement of methane adsorption probability on nickel surfaces, and we find that a strong correlation exists between the highest vibrational efficacy measured on Ni{100} for the n1 state and the calculated highest fractional vibrational energy content in this mode.

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We have investigated the chemisorption of CH3D and CD3H on Pt{11 0}-(1 2) by performing first-principles molecular dynamics simulations of the recombinative desorption of CH3D (from adsorbed methyl and deuterium) and of CD3H (from adsorbed trideuteromethyl and hydrogen). Vibrational analysis of the symmetry adapted internal coordinates of the desorbing molecules shows that excitation of the single C– D (C–H) bond in the parent molecule is strongly correlated with energy excess in the reaction coordinate. The results of the molecular dynamics simulations are consistent with observed mode- and bond-specific reactivity measurements for chemisorption of methane and its isotopomers on platinum and nickel surfaces.

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Improved nutrient utilization efficiency is strongly related to enhanced economic performance and reduced environmental footprint of dairy farms. Pasture-based systems are widely used for dairy production in certain areas of the world, but prediction equations of fresh grass nutritive value (nutrient digestibility and energy concentrations) are limited. Equations to predict digestible energy (DE) and metabolizable energy (ME) used for grazing cattle have been either developed with cattle fed conserved forage and concentrate diets or sheep fed previously frozen grass, and the majority of them require measurements less commonly available to producers, such as nutrient digestibility. The aim of the present study was therefore to develop prediction equations more suitable to grazing cattle for nutrient digestibility and energy concentrations, which are routinely available at farm level by using grass nutrient contents as predictors. A study with 33 nonpregnant, nonlactating cows fed solely fresh-cut grass at maintenance energy level for 50 wk was carried out over 3 consecutive grazing seasons. Freshly harvested grass of 3 cuts (primary growth and first and second regrowth), 9 fertilizer input levels, and contrasting stage of maturity (3 to 9 wk after harvest) was used, thus ensuring a wide representation of nutritional quality. As a result, a large variation existed in digestibility of dry matter (0.642-0.900) and digestible organic matter in dry matter (0.636-0.851) and in concentrations of DE (11.8-16.7 MJ/kg of dry matter) and ME (9.0-14.1 MJ/kg of dry matter). Nutrient digestibilities and DE and ME concentrations were negatively related to grass neutral detergent fiber (NDF) and acid detergent fiber (ADF) contents but positively related to nitrogen (N), gross energy, and ether extract (EE) contents. For each predicted variable (nutrient digestibilities or energy concentrations), different combinations of predictors (grass chemical composition) were found to be significant and increase the explained variation. For example, relatively higher R(2) values were found for prediction of N digestibility using N and EE as predictors; gross-energy digestibility using EE, NDF, ADF, and ash; NDF, ADF, and organic matter digestibilities using N, water-soluble carbohydrates, EE, and NDF; digestible organic matter in dry matter using water-soluble carbohydrates, EE, NDF, and ADF; DE concentration using gross energy, EE, NDF, ADF, and ash; and ME concentration using N, EE, ADF, and ash. Equations presented may allow a relatively quick and easy prediction of grass quality and, hence, better grazing utilization on commercial and research farms, where nutrient composition falls within the range assessed in the current study.

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Ruminant production is a vital part of food industry but it raises environmental concerns, partly due to the associated methane outputs. Efficient methane mitigation and estimation of emissions from ruminants requires accurate prediction tools. Equations recommended by international organizations or scientific studies have been developed with animals fed conserved forages and concentrates and may be used with caution for grazing cattle. The aim of the current study was to develop prediction equations with animals fed fresh grass in order to be more suitable to pasture-based systems and for animals at lower feeding levels. A study with 25 nonpregnant nonlactating cows fed solely fresh-cut grass at maintenance energy level was performed over two consecutive grazing seasons. Grass of broad feeding quality, due to contrasting harvest dates, maturity, fertilisation and grass varieties, from eight swards was offered. Cows were offered the experimental diets for at least 2 weeks before housed in calorimetric chambers over 3 consecutive days with feed intake measurements and total urine and faeces collections performed daily. Methane emissions were measured over the last 2 days. Prediction models were developed from 100 3-day averaged records. Internal validation of these equations, and those recommended in literature, was performed. The existing in greenhouse gas inventories models under-estimated methane emissions from animals fed fresh-cut grass at maintenance while the new models, using the same predictors, improved prediction accuracy. Error in methane outputs prediction was decreased when grass nutrient, metabolisable energy and digestible organic matter concentrations were added as predictors to equations already containing dry matter or energy intakes, possibly because they explain feed digestibility and the type of energy-supplying nutrients more efficiently. Predictions based on readily available farm-level data, such as liveweight and grass nutrient concentrations were also generated and performed satisfactorily. New models may be recommended for predictions of methane emissions from grazing cattle at maintenance or low feeding levels.

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This paper draws from work conducted under the NERC-funded project 'Understanding energy governance at local and community levels'(Project Reference: NE/H013598/1). This project was a 24 month study carried out in collaboration with the UK Energy Research Council which began in April 2010. The particular workpackage from which these interviews were drawn specifically explores the role of local authorities in emerging energy and environmental responsibilities, paying particular attention to current institutional structures and how external forces and actors influence local authorities on their decision making and practices. It is concluded that whilst the role of local authorities has been changing in response to energy and environmental ‘landscape’ issues, their influence on the design and implementation of energy policy in the UK will correspondingly remain as an emerging process for the foreseeable future, with the more progressive local authorities continuing to exert political, social/cultural and technological influence over ways of designing, articulating, and engaging with energy governance at the local level.

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A body of research suggests that the provision of energy feedback information to building users can elicit significant energy reductions through behaviour change. However, most studies have focused on energy use in homes and the assessment of interventions and technologies, to the neglect of the non-domestic context and broader issues arising from the introduction of feedback technologies. To address this gap, a non-domestic case study explores the delivery of personalized energy feedback to office workers through a novel system utilizing wireless technologies. The research demonstrates advantages of monitoring occupancy and quantifying energy use from specific behaviours as a basis for effective energy feedback; this is particularly important where there are highly disaggregated forms of energy use and a range of locations for that activity to take place. Quantitative and qualitative data show that personalized feedback can help individuals identify energy reduction opportunities. However, the analysis also highlights important contextual barriers and issues that need to be addressed when utilizing feedback technologies in the workplace. If neglected, these issues may limit the effective take-up of feedback interventions.

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Demand for good indoor air quality is increasing as people recorgnise the risks to their health and productivity from indoor pollutants. There is a tendency to reduce ventilation rates to ensure energy conservation in buildings; in this instance schools. However, evidence reviewed shows that this can be detrimental to health and wellbeing in schools because of the learner density within a small area (1.8 - 2.4m2/person); eventually indicating that carbon dioxide (CO2) levels can rise to very high levels in classroom occupancy periods. A preliminary study to investigate the impact of indoor environmental parameters has been performed in a secondary school classroom in Pretoria, South Africa. Factors monitored include temperature, relative humidity, lighting, air velocities and CO2 concentrations. From the results low air velocities are recorded (i.e. 0.1-0.3m/s) impacting on the retention of CO2 build-up in the classroom. Results presented in this paper are the initial findings of ongoing research.