92 resultados para energy use


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Collectively small and medium sized enterprises (SMEs) are significant energy users although many are unregulated by existing policies due to their low carbon emissions. Carbon reduction is often not a priority but smart grids may create a new opportunity. A smart grid will give electricity suppliers a picture of real-time energy flows and the opportunity for consumers to receive financial incentives for engaging in demand side management. As well as creating incentives for local carbon reduction, engaging SMEs with smart grids has potential for contributing to wider grid decarbonisation. Modelling of buildings, business activities and technology solutions is needed to identify opportunities for carbon reduction. The diversity of the SME sector complicates strategy development. SMEs are active in almost every business area and occupy the full range of property types. This paper reviews previous modelling work, exposing valuable data on floor space and energy consumption associated with different business activities. Limitations are seen with the age of this data and an inability to distinguish SME energy use. By modelling SME energy use, electrical loads are identified which could be shifted on demand, in a smart network. Initial analysis of consumption, not constrained by existing policies, identifies heating and cooling in retail and commercial offices as having potential for demand response. Hot water in hotel and catering and retail sectors may also be significant because of the energy storage potential. Areas to consider for energy efficiency schemes are also indicated.

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How people live, work, move from place to place, consume and the technologies they use all affect heat emissions in a city which influences urban weather and climate. Here we document changes to a global anthropogenic heat flux (QF) model to enhance its spatial (30′′ × 30′′ to 0.5° × 0.5°) resolution and temporal coverage (historical, current and future). QF is estimated across Europe (1995–2015), considering changes in temperature, population and energy use. While on average QF is small (of the order 1.9–4.6 W m−2 across all the urban areas of Europe), significant spatial variability is documented (maximum 185 W m−2). Changes in energy consumption due to changes in climate are predicted to cause a 13% (11%) increase in QF on summer (winter) weekdays. The largest impact results from changes in temperature conditions which influences building energy use; for winter, with the coldest February on record, the mean flux for urban areas of Europe is 4.56 W m−2 and for summer (warmest July on record) is 2.23 W m−2. Detailed results from London highlight the spatial resolution used to model the QF is critical and must be appropriate for the application at hand, whether scientific understanding or decision making.

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Cities and global climate change are closely linked: cities are where the bulk of greenhouse gas emissions take place through the consumption of fossil fuels; they are where an increasing proportion of the world’s people live; and they also generate their own climate – commonly characterized by the urban heat island. In this way, understanding the way cities affect the cycling of energy, water, and carbon to create an urban climate is a key element of climate mitigation and adaptation strategies, especially in the context of rising global temperatures and deteriorating air quality in many cities. As climate models resolve finer spatial-scales, they will need to represent those areas in which more than 50% of the world’s population already live to provide climate projections that are of greater use to planning and decision-making. Finally, many of the processes that are instrumental in determining urban climate are the same factors leading to global anthropogenic climate change, namely regional-scale land-use changes; increased energy use; and increased emissions of climatically-relevant atmospheric constituents. Cities are therefore both a case study for understanding, and an agent in mitigating, anthropogenic climate change. This chapter reviews and summarizes the current state of understanding of the physical basis of urban climates, as well as our ability to represent these in models. We argue that addressing the challenges of managing urban environments in a changing climate requires understanding the energy, water, and carbon balances for an urban landscape and, importantly, their interactions and feedbacks, together with their links to human behaviour and controls. We conclude with some suggestions for where further research is needed.

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Data on electricity consumption patterns relating to different end uses in domestic houses in Botswana is virtually non-existent, despite the fact that the total electricity consumption patterns are available. This can be attributed to the lack of measured and quantified data and in other instances the lack of modern technology to perform such investigations. This paper presents findings from initial studies that are envisaged to bridge the gap. Electricity consumption patterns of 275 domestic households in Gaborone (the capital city of Botswana) have been studied. This was carried out through a questionnaire survey and electricity measurements. Households were categorized based on the number of people occupying the house. From the study, it was evident that the number of people influences the amount of energy a household use although this cannot be treated as an independent factor when assessing energy use. The study also indicated that heating, cooling and domestic hot water (DHW) account for over 30% of energy used in the home. This is worth considering in energy consumption reduction measures. Due to a small sample size, it would not be wise to draw sweeping conclusions from the analysis of this paper or to make statements that would be aimed at influencing policies. However, the results presented forms a formidable base for further research, which is currently on going.

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Countless cities are rapidly developing across the globe, pressing the need for clear urban planning and design recommendations geared towards sustainability. This article examines the intersections of Jane Jacobs’ four conditions for diversity with low-carbon and low-energy use urban systems in four cities around the world: Lyon (France), Chicago (United-States), Kolkata (India), and Singapore (Singapore). After reviewing Jacobs’ four conditions for diversity, we introduce the four cities and describe their historical development context. We then present a framework to study the cities along three dimensions: population and density, infrastructure development/use, and climate and landscape. These cities differ in many respects and their analysis is instructive for many other cities around the globe. Jacobs’ conditions are present in all of them, manifested in different ways and to varying degrees. Overall we find that the adoption of Jacobs' conditions seems to align well with concepts of low-carbon urban systems, with their focus on walkability, transit-oriented design, and more efficient land use (i.e., smaller unit sizes). Transportation sector emissions seems to demonstrate a stronger influence from the presence of Jacobs' conditions, while the link was less pronounced in the building sector. Kolkata, a low-income, developing world city, seems to possess many of Jacobs' conditions, while exhibiting low per capita emissions - maintaining both of these during its economic expansion will take careful consideration. Greenhouse gas mitigation, however, is inherently an in situ problem and the first task must therefore be to gain local knowledge of an area before developing strategies to lower its carbon footprint.

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One of the most significant sources of greenhouse gas (GHG) emissions in Canada is the buildings sector, with over 30% of national energy end-use occurring in buildings. Energy use must be addressed to reduce emissions from the buildings sector, as nearly 70% of all Canada’s energy used in the residential sector comes from fossil sources. An analysis of GHG emissions from the existing residential building stock for the year 2010 has been conducted for six Canadian cities with different climates and development histories: Vancouver, Edmonton, Winnipeg, Toronto, Montreal, and Halifax. Variation across these cities is seen in their 2010 GHG emissions, due to climate, characteristics of the building stock, and energy conversion technologies, with Halifax having the highest per capita emissions at 5.55 tCO2e/capita and Montreal having the lowest at 0.32 tCO2e/capita. The importance of the provincial electricity grid’s carbon intensity is emphasized, along with era of construction, occupancy, floor area, and climate. Approaches to achieving deep emissions reductions include innovative retrofit financing and city level residential energy conservation by-laws; each region should seek location-appropriate measures to reduce energy demand within its residential housing stock, as well as associated GHG emissions.

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Over the last decade we have seen the growth and development of low carbon lifestyle movement organisations, which seek to encourage members of the public to reduce their personal energy use and carbon emissions. As a first step to assess the transformational potential of such organisations, this paper examines the ways in which they frame their activities. This reveals an important challenge they face: in addressing the broader public, do they promote ‘transformative’ behaviours or do they limit themselves to encouraging ‘easy changes’ to maintain their appeal? We find evidence that many organisations within this movement avoid ‘transformative’ frames. The main reasons for this are organisers’ perceptions that transformational frames lack resonance with broader audiences, as well as wider cultural contexts that caution against behavioural intervention. The analysis draws on interviews with key actors in the low carbon lifestyle movement and combines insights from the literatures on collective action framing and lifestyle movements.

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Fire-centred studies have recently been highlighted as powerful avenues for investigation of energy flows and relations between humans, materials, environments and other species. The aim in this paper is to evaluate this potential first by reviewing the diverse theories and methods that can be applied to investigate the ecological and social significance of anthropogenic fire, and second by applying these to new and existing data sets in archaeology. This paper examines how fire-centred approaches can inform on one of the most significant step-changes in human lifeways and inter-relations with environment and other species – the transition from mobile hunting-gathering to more sedentary agriculture in a key heartland of change, the Zagros region of Iraq and Iran, c. 12,000–8,000 BP. In the review and case studies multiple links are investigated between human fire use and environment, ecology, energy use, technology, the built environment, health, social roles and relations, cultural practices and catastrophic events

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This paper describe a simulation program, which uses Trengenza’s average room illuminance method in conjunction with hourly solar irradiance and luminous efficacy, to predict the potential lighting energy saving for a side-lit room. Two lighting control algorithms of photoelectric switching (on/off) and photoelectric dimming (top-up) have been coded in the program. A simulation for a typical UK office room has been conducted and the results show that energy saving due to the sunlight dependent on the various factors such as orientation, control methods, building depth, glazing area and shading types, etc. This simple tool can be used for estimating the potential lighting energy saving of the windows with various shading devices at the early design stage.

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Summary 1. Agent-based models (ABMs) are widely used to predict how populations respond to changing environments. As the availability of food varies in space and time, individuals should have their own energy budgets, but there is no consensus as to how these should be modelled. Here, we use knowledge of physiological ecology to identify major issues confronting the modeller and to make recommendations about how energy budgets for use in ABMs should be constructed. 2. Our proposal is that modelled animals forage as necessary to supply their energy needs for maintenance, growth and reproduction. If there is sufficient energy intake, an animal allocates the energy obtained in the order: maintenance, growth, reproduction, energy storage, until its energy stores reach an optimal level. If there is a shortfall, the priorities for maintenance and growth/reproduction remain the same until reserves fall to a critical threshold below which all are allocated to maintenance. Rates of ingestion and allocation depend on body mass and temperature. We make suggestions for how each of these processes should be modelled mathematically. 3. Mortality rates vary with body mass and temperature according to known relationships, and these can be used to obtain estimates of background mortality rate. 4. If parameter values cannot be obtained directly, then values may provisionally be obtained by parameter borrowing, pattern-oriented modelling, artificial evolution or from allometric equations. 5. The development of ABMs incorporating individual energy budgets is essential for realistic modelling of populations affected by food availability. Such ABMs are already being used to guide conservation planning of nature reserves and shell fisheries, to assess environmental impacts of building proposals including wind farms and highways and to assess the effects on nontarget organisms of chemicals for the control of agricultural pests. Keywords: bioenergetics; energy budget; individual-based models; population dynamics.

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The ground surface net solar radiation is the energy that drives physical and chemical processes at the ground surface. In this paper, multi-spectral data from the Landsat-5 TM, topographic data from a gridded digital elevation model, field measurements, and the atmosphere model LOWTRAN 7 are used to estimate surface net solar radiation over the FIFE site. Firstly an improved method is presented and used for calculating total surface incoming radiation. Then, surface albedo is integrated from surface reflectance factors derived from remotely sensed data from Landsat-5 TM. Finally, surface net solar radiation is calculated by subtracting surface upwelling radiation from the total surface incoming radiation.

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Targeted observations are generally taken in regions of high baroclinicity, but often show little impact. One plausible explanation is that important dynamical information, such as upshear tilt, is not extracted from the targeted observations by the data assimilation scheme and used to correct initial condition error. This is investigated by generating pseudo targeted observations which contain a singular vector (SV) structure that is not present in the background field or routine observations, i.e. assuming that the background has an initial condition error with tilted growing structure. Experiments were performed for a single case-study with varying numbers of pseudo targeted observations. These were assimilated by the Met Office four-dimensional variational (4D-Var) data assimilation scheme, which uses a 6 h window for observations and background-error covariances calculated using the National Meteorological Centre (NMC) method. The forecasts were run using the operational Met Office Unified Model on a 24 km grid. The results presented clearly demonstrate that a 6 h window 4D-Var system is capable of extracting baroclinic information from a limited set of observations and using it to correct initial condition error. To capture the SV structure well (projection of 0.72 in total energy), 50 sondes over an area of 1×106 km2 were required. When the SV was represented by only eight sondes along an example targeting flight track covering a smaller area, the projection onto the SV structure was lower; the resulting forecast perturbations showed an SV structure with increased tilt and reduced initial energy. The total energy contained in the perturbations decreased as the SV structure was less well described by the set of observations (i.e. as fewer pseudo observations were assimilated). The assimilated perturbation had lower energy than the SV unless the pseudo observations were assimilated with the dropsonde observation errors halved from operational values. Copyright © 2010 Royal Meteorological Society

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We report the results of variational calculations of the rovibrational energy levels of HCN for J = 0, 1 and 2, where we reproduce all the ca. 100 observed vibrational states for all observed isotopic species, with energies up to 18000 cm$^{-1}$, to about $\pm $1 cm$^{-1}$, and the corresponding rotational constants to about $\pm $0.001 cm$^{-1}$. We use a hamiltonian expressed in internal coordinates r$_{1}$, r$_{2}$ and $\theta $, using the exact expression for the kinetic energy operator T obtained by direct transformation from the cartesian representation. The potential energy V is expressed as a polynomial expansion in the Morse coordinates y$_{i}$ for the bond stretches and the interbond angle $\theta $. The basis functions are built as products of appropriately scaled Morse functions in the bond-stretches and Legendre or associated Legendre polynomials of cos $\theta $ in the angle bend, and we evaluate matrix elements by Gauss quadrature. The hamiltonian matripx is factorized using the full rovibrational symmetry, and the basis is contracted to an optimized form; the dimensions of the final hamiltonian matrix vary from 240 $\times $ 240 to 1000 $\times $ 1000.We believe that our calculation is converged to better than 1 cm$^{-1}$ at 18 000 cm$^{-1}$. Our potential surface is expressed in terms of 31 parameters, about half of which have been refined by least squares to optimize the fit to the experimental data. The advantages and disadvantages and the future potential of calculations of this type are discussed.