993 resultados para Heat island


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 Putrajaya is a model city planned with concepts of a "city in the garden" and an "intelligent city" in the tropics. This study presents the behaviour of the surface temperature and the heat island effect of Putrajaya. Findings show that heat island intensity is 2 °C on average at nighttime and negligible at daytime. But high surface temperature values were recorded at the main boulevard due to direct solar radiation incident, street orientation in the direction of northeast and southwest and low building height-to-street width ratio. Buildings facing each other had cooling effect on surfaces during the morning and evening hours; conversely, they had a warming effect at noon. Clustered trees along the street are effective in reducing the surface temperature compared to scattered and isolated trees. Surface temperature of built up areas was highest at noon, while walls and sidewalks facing northwest were hottest later in the day. Walls and sidewalks that face northwest were warmer than those that face southeast. The surface temperatures of the horizontal street surfaces and of vertical façades are at acceptable levels relative to the surface temperature of similar surfaces in mature cities in subtropical, temperate and Mediterranean climates. © 2014 Springer-Verlag Wien.

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 Urban Heat Island (UHI) has become a growing concern to the quality of densely built urban environments, particularly in tropical cities. Wind speed has widely been reported to have decreased the intensity of heat island effect in urban areas. The cooling effect of the wind helps to mitigate the adverse effects of heat island on the micro climate and human thermal comfort. This paper investigates the existence of heat island in Muar, one of the fast growing cities in southern part of Malaysia and its possible causes, and then examines the effects of different urban geometry on the wind flow. The results of this study indicate that the chaotic development in Muar has caused reduced ventilation in urban canyons. The heat island intensity in the city center was recorded as 4. °C during the day and 3.2. °C during the night. Investigation of various urban geometry modifications showed that step up configuration was the most effective geometry as it can distribute the wind evenly allowing the wind to reach even the leeward side of each building. © 2014 Elsevier Ltd.

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This work aims to study the urban heat island on North region of Parana state, Brazil and the influence of land use and urban settlements on the intensity and frequency of occurrence of these events. Through atmospheric modeling whith WRF/Chem model two simulations were made with different land and use files, one with the original land use another obtained from a composition of MODIS-Landsat imagery. The simulations showed good skills compared to observed data. Urban areas presented higher temperatures. Landsat land use has represented better urban heat islands (UHI), the gradient between urban and rural areas was well demonstrated and the correlation coefficient was above 0.92. The model underestimated the maximum values and overestimated the minimum compared with observed data in both simulations.

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Nowadays the environmental issues and the climatic change play fundamental roles in the design of urban spaces. Our cities are growing in size, many times only following immediate needs without a long-term vision. Consequently, the sustainable development has become not only an ethical but also a strategic need: we can no longer afford an uncontrolled urban expansion. One serious effect of the territory industrialisation process is the increase of urban air and surfaces temperatures compared to the outlying rural surroundings. This difference in temperature is what constitutes an urban heat island (UHI). The purpose of this study is to provide a clarification on the role of urban surfacing materials in the thermal dynamics of an urban space, resulting in useful indications and advices in mitigating UHI. With this aim, 4 coloured concrete bricks were tested, measuring their emissivity and building up their heat release curves using infrared thermography. Two emissivity evaluation procedures were carried out and subsequently put in comparison. Samples performances were assessed, and the influence of the colour on the thermal behaviour was investigated. In addition, some external pavements were analysed. Albedo and emissivity parameters were evaluated in order to understand their thermal behaviour in different conditions. Surfaces temperatures were recorded in a one-day measurements campaign. ENVI-met software was used to simulate how the tested materials would behave in two typical urban scenarios: a urban canyon and a urban heat basin. Improvements they can carry to the urban microclimate were investigated. Emissivities obtained for the bricks ranged between 0.92 and 0.97, suggesting a limited influence of the colour on this parameter. Nonetheless, white concrete brick showed the best thermal performance, whilst the black one the worst; red and yellow ones performed pretty identical intermediate trends. De facto, colours affected the overall thermal behaviour. Emissivity parameter was measured in the outdoor work, getting (as expected) high values for the asphalts. Albedo measurements, conducted with a sunshine pyranometer, proved the improving effect given by the yellow paint in terms of solar reflection, and the bad influence of haze on the measurement accuracy. ENVI-met simulations gave a demonstration on the effectiveness in thermal improving of some tested materials. In particular, results showed good performances for white bricks and granite in the heat basin scenario, and painted concrete and macadam in the urban canyon scenario. These materials can be considered valuable solutions in UHI mitigation.

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Present research is framed within the project MODIFICA (MODelo predictivo - edIFIcios - Isla de Calor urbanA) aimed at developing a predictive model for dwelling energy performance under the urban heat island effect in order to implement it in the evaluation of real energy demand and consumption of dwellings as well as in the selection of energy retrofitting strategies. It is funded by Programa de I+D+i orientada a los retos de la sociedad 'Retos Investigación' 2013. Despite great advances on building energy performance have been achieved during the last years, available climate data is derived from weather stations placed in the outskirts of the city. Hence, urban heat island effect is not considered in energy simulations, which implies an important lack of accuracy. Since 1980's several international studies have been conducted on the urban heat island (UHI) phenomena, which modifies the atmospheric conditions of the urban centres due to urban agglomeration [1][2][3][4]. In the particular case of Madrid, multiple maps haven been generated using different methodologies during the last two decades [5][6][7]. These maps allow us to study the UHI phenomena from a wide perspective, offering however an static representation of it. Consequently a dynamic model for Madrid UHI is proposed, in order to evaluate it in a continuous way, and to be able to integrate it in building energy simulations.

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Present research is framed within the project MODIFICA (MODelo predictivo - edIFIcios - Isla de Calor Urbana) aimed at developing a predictive model for dwelling energy performance under the urban heat island effect in order to implement it in the evaluation of real energy demand and consumption of dwellings as well as in the selection of energy retrofitting strategies. It is funded by Programa de I+D+i orientada a los retos de la sociedad 'Retos Investigación' 2013. The scope of our predictive model is defined by the heat island effect (UHI) of urban structures that compose the city of Madrid. In particular, we focus on the homogeneous areas for urban structures with the same urban and building characteristics. Data sources for the definition of such homogeneous areas were provided by previous research on the UHI of Madrid. The objective is to establish a critical analysis of climate records used for energy simulation tools, which data come from weather stations placed in decontextualized areas from the usual urban reality, where the thermal conditions differs by up to 6ºC. In this way, we intend to develop a new predictive model for the consumption and demand in buildings depending on their location, the urban structure and the associated UHI, improving the future energy rehabilitation interventions

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Esta investigación se enmarca dentro del proyecto MODIFICA (modelo predictivo - Edificios - Isla de Calor Urbano), financiado por el Programa de I + D + i Orientada a los Retos de la sociedad 'Retos Investigación' de 2013. Está dirigido a desarrollar un modelo predictivo de eficiencia energética para viviendas, bajo el efecto de isla de calor urbano (AUS) con el fin de ponerla en práctica en la evaluación de la demanda de energía real y el consumo en las viviendas. A pesar de los grandes avances que se han logrado durante los últimos años en el rendimiento energético de edificios, los archivos de tiempo utilizados en la construcción de simulaciones de energía se derivan generalmente de estaciones meteorológicas situadas en las afueras de la ciudad. Por lo tanto, el efecto de la Isla de Calor Urbano (ICU) no se considera en estos cálculos, lo que implica una importante falta de precisión. Centrado en explorar cómo incluir los fenómenos ICU, el presente trabajo recopila y analiza la dinámica por hora de la temperatura en diferentes lugares dentro de la ciudad de Madrid. Abstract This research is framed within the project MODIFICA (Predictive model - Buildings - Urban Heat Island), funded by Programa de I+D+i orientada a los retos de la sociedad 'Retos Investigación' 2013. It is aimed at developing a predictive model for dwelling energy performance under the Urban Heat Island (UHI) effect in order to implement it in the evaluation of real energy demand and consumption in dwellings. Despite great advances on building energy performance have been achieved during the last years, weather files used in building energy simulations are usually derived from weather stations placed in the outskirts of the city. Hence, Urban Heat Island (UHI) effect is not considered in this calculations, which implies an important lack of accuracy. Focused on exploring how to include the UHI phenomena, the present paper compiles and analyses the hourly dynamics of temperature in different locations within the city of Madrid.

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Leishmaniasis is one of the most important emerging vector-borne diseases in Western Eurasia. Although winter minimum temperatures limit the present geographical distribution of the vector Phlebotomus species, the heat island effect of the cities and the anthropogenic heat emission together may provide the appropriate environment for the overwintering of sand flies. We studied the climate tempering effect of thermal bridges and the heat island effect in Budapest, Hungary. Thermal imaging was used to measure the heat surplus of heat bridges. The winter heat island effect of the city was evaluated by numerical analysis of the measurements of the Aqua sensor of satellite Terra. We found that the surface temperature of thermal bridges can be at least 3-7 °C higher than the surrounding environment. The heat emission of thermal bridges and the urban heat island effect together can cause at least 10 °C higher minimum ambient temperature in winter nights than the minimum temperature of the peri-urban areas. This milder micro-climate of the built environment can enable the potential overwintering of some important European Phlebotomus species. The anthropogenic heat emission of big cities may explain the observed isolated northward populations of Phlebotomus ariasi in Paris and Phlebotomus neglectus in the agglomeration of Budapest.

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Lo scopo di questo studio è la comprensione della dinamica dello strato limite urbano per città dell’Emilia Romagna tramite simulazioni numeriche. In particolare, l’attenzione è posta sull’ effetto isola di calore, ovvero sulla differenza di temperatura dell’aria in prossimità del suolo fra zone rurali e urbane dovuta all’urbanizzazione. Le simulazioni sono state effettuate con il modello alla mesoscala "Weather Research and Forecasting" (WRF), accoppiato con le parametrizzazioni urbane "Building Effect Parametrization" (BEP) e "Building Energy Model" (BEM), che agiscono a vari livelli verticali urbani. Il periodo di studio riguarda sei giorni caldi e senza copertura nuvolosa durante un periodo di heat wave dell’anno 2015. La copertura urbana è stata definita con il "World Urban Databes and Access Portal Tools" (WUDAPT), un metodo che permette di classificare le aree urbane in dieci "urban climate zones" (UCZ), attraverso l’uso combinato di immagini satellitari e "training areas" manualmente definite con il software Google Earth. Sono state svolte diverse simulazioni a domini innestati, con risoluzione per il dominio più piccolo di 500 m, centrato sulla città di Bologna. Le differenze fra le simulazioni riguardano la presenza o l’assenza delle strutture urbane, il metodo di innesto e tipo di vegetazione rurale. Inoltre, è stato valutato l’effetto dovuto alla presenza di pannelli fotovoltaici sopra i tetti di ogni edificio e le variazioni che i pannelli esercitano sullo strato limite urbano. Per verificare la bontà del modello, i dati provenienti dalle simulazioni sono stati confrontati con misure provenienti da 41 stazioni all’interno dell’area di studio. Le variabili confrontate sono: temperatura, umidità relativa, velocità e direzione del vento. Le simulazioni sono in accordo con i dati osservativi e riescono a riprodurre l’effetto isola di calore: la differenza di temperatura fra città e zone rurali circostanti è nulla durante il giorno; al contrario, durante la notte l’isola di calore è presente, e in media raggiunge il massimo valore di 4°C alle 1:00. La presenza dei pannelli fotovoltaici abbassa la temperatura a 2 metri dell’aria al massimo di 0.8°C durante la notte, e l’altezza dello strato limite urbano dell’ordine 200mrispetto al caso senza pannelli. I risultati mostrano come l’uso di pannelli fotovoltaici all’interno del contesto urbano ha molteplici benefici: infatti, i pannelli fotovoltaici riescono a ridurre la temperatura durante un periodo di heat wave, e allo stesso tempo possono parzialmente sopperire all’alto consumo energetico, con una conseguente riduzione del consumo di combustibili fossili.

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As the world population continues to grow past seven billion people and global challenges continue to persist including resource availability, biodiversity loss, climate change and human well-being, a new science is required that can address the integrated nature of these challenges and the multiple scales on which they are manifest. Sustainability science has emerged to fill this role. In the fifteen years since it was first called for in the pages of Science, it has rapidly matured, however its place in the history of science and the way it is practiced today must be continually evaluated. In Part I, two chapters address this theoretical and practical grounding. Part II transitions to the applied practice of sustainability science in addressing the urban heat island (UHI) challenge wherein the climate of urban areas are warmer than their surrounding rural environs. The UHI has become increasingly important within the study of earth sciences given the increased focus on climate change and as the balance of humans now live in urban areas.

In Chapter 2 a novel contribution to the historical context of sustainability is argued. Sustainability as a concept characterizing the relationship between humans and nature emerged in the mid to late 20th century as a response to findings used to also characterize the Anthropocene. Emerging from the human-nature relationships that came before it, evidence is provided that suggests Sustainability was enabled by technology and a reorientation of world-view and is unique in its global boundary, systematic approach and ambition for both well being and the continued availability of resources and Earth system function. Sustainability is further an ambition that has wide appeal, making it one of the first normative concepts of the Anthropocene.

Despite its widespread emergence and adoption, sustainability science continues to suffer from definitional ambiguity within the academe. In Chapter 3, a review of efforts to provide direction and structure to the science reveals a continuum of approaches anchored at either end by differing visions of how the science interfaces with practice (solutions). At one end, basic science of societally defined problems informs decisions about possible solutions and their application. At the other end, applied research directly affects the options available to decision makers. While clear from the literature, survey data further suggests that the dichotomy does not appear to be as apparent in the minds of practitioners.

In Chapter 4, the UHI is first addressed at the synoptic, mesoscale. Urban climate is the most immediate manifestation of the warming global climate for the majority of people on earth. Nearly half of those people live in small to medium sized cities, an understudied scale in urban climate research. Widespread characterization would be useful to decision makers in planning and design. Using a multi-method approach, the mesoscale UHI in the study region is characterized and the secular trend over the last sixty years evaluated. Under isolated ideal conditions the findings indicate a UHI of 5.3 ± 0.97 °C to be present in the study area, the magnitude of which is growing over time.

Although urban heat islands (UHI) are well studied, there remain no panaceas for local scale mitigation and adaptation methods, therefore continued attention to characterization of the phenomenon in urban centers of different scales around the globe is required. In Chapter 5, a local scale analysis of the canopy layer and surface UHI in a medium sized city in North Carolina, USA is conducted using multiple methods including stationary urban sensors, mobile transects and remote sensing. Focusing on the ideal conditions for UHI development during an anticyclonic summer heat event, the study observes a range of UHI intensity depending on the method of observation: 8.7 °C from the stationary urban sensors; 6.9 °C from mobile transects; and, 2.2 °C from remote sensing. Additional attention is paid to the diurnal dynamics of the UHI and its correlation with vegetation indices, dewpoint and albedo. Evapotranspiration is shown to drive dynamics in the study region.

Finally, recognizing that a bridge must be established between the physical science community studying the Urban Heat Island (UHI) effect, and the planning community and decision makers implementing urban form and development policies, Chapter 6 evaluates multiple urban form characterization methods. Methods evaluated include local climate zones (LCZ), national land cover database (NCLD) classes and urban cluster analysis (UCA) to determine their utility in describing the distribution of the UHI based on three standard observation types 1) fixed urban temperature sensors, 2) mobile transects and, 3) remote sensing. Bivariate, regression and ANOVA tests are used to conduct the analyses. Findings indicate that the NLCD classes are best correlated to the UHI intensity and distribution in the study area. Further, while the UCA method is not useful directly, the variables included in the method are predictive based on regression analysis so the potential for better model design exists. Land cover variables including albedo, impervious surface fraction and pervious surface fraction are found to dominate the distribution of the UHI in the study area regardless of observation method.

Chapter 7 provides a summary of findings, and offers a brief analysis of their implications for both the scientific discourse generally, and the study area specifically. In general, the work undertaken does not achieve the full ambition of sustainability science, additional work is required to translate findings to practice and more fully evaluate adoption. The implications for planning and development in the local region are addressed in the context of a major light-rail infrastructure project including several systems level considerations like human health and development. Finally, several avenues for future work are outlined. Within the theoretical development of sustainability science, these pathways include more robust evaluations of the theoretical and actual practice. Within the UHI context, these include development of an integrated urban form characterization model, application of study methodology in other geographic areas and at different scales, and use of novel experimental methods including distributed sensor networks and citizen science.

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Background: Extreme heat is a leading weather-related cause of illness and death in many locations across the globe, including subtropical Australia. The possibility of increasingly frequent and severe heat waves warrants continued efforts to reduce this health burden, which could be accomplished by targeting intervention measures toward the most vulnerable communities. Objectives: We sought to quantify spatial variability in heat-related morbidity in Brisbane, Australia, to highlight regions of the city with the greatest risk. We also aimed to find area-level social and environmental determinants of high risk within Brisbane. Methods: We used a series of hierarchical Bayesian models to examine city-wide and intracity associations between temperature and morbidity using a 2007–2011 time series of geographically referenced hospital admissions data. The models accounted for long-term time trends, seasonality, and day of week and holiday effects. Results: On average, a 10°C increase in daily maximum temperature during the summer was associated with a 7.2% increase in hospital admissions (95% CI: 4.7, 9.8%) on the following day. Positive statistically significant relationships between admissions and temperature were found for 16 of the city’s 158 areas; negative relationships were found for 5 areas. High-risk areas were associated with a lack of high income earners and higher population density. Conclusions: Geographically targeted public health strategies for extreme heat may be effective in Brisbane, because morbidity risk was found to be spatially variable. Emergency responders, health officials, and city planners could focus on short- and long-term intervention measures that reach communities in the city with lower incomes and higher population densities, including reduction of urban heat island effects.

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Surface energy processes has an essential role in urban weather, climate and hydrosphere cycles, as well in urban heat redistribution. The research was undertaken to analyze the potential of Landsat and MODIS data in retrieving biophysical parameters in estimating land surface temperature & heat fluxes diurnally in summer and winter seasons of years 2000 and 2010 and understanding its effect on anthropogenic heat disturbance over Delhi and surrounding region. Results show that during years 2000-2010, settlement and industrial area increased from 5.66 to 11.74% and 4.92 to 11.87% respectively which in turn has direct effect on land surface temperature (LST) and heat fluxes including anthropogenic heat flux. Based on the energy balance model for land surface, a method to estimate the increase in anthropogenic heat flux (Has) has been proposed. The settlement and industrial areas has higher amounts of energy consumed and has high values of Has in all seasons. The comparison of satellite derived LST with that of field measured values show that Landsat estimated values are in close agreement within error of 2 degrees C than MODIS with an error of 3 degrees C. It was observed that, during 2000 and 2010, the average change in surface temperature using Landsat over settlement & industrial areas of both seasons is 1.4 degrees C & for MODIS data is 3.7 degrees C. The seasonal average change in anthropogenic heat flux (Has) estimated using Landsat & MODIS is up by around 38 W/m(2) and 62 W/m(2) respectively while higher change is observed over settlement and concrete structures. The study reveals that the dynamic range of Has values has increased in the 10 year period due to the strong anthropogenic influence over the area. The study showed that anthropogenic heat flux is an indicator of the strength of urban heat island effect, and can be used to quantify the magnitude of the urban heat island effect. (C) 2013 Elsevier Ltd. All rights reserved.

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We investigate the role of the anthropogenic heat flux on the urban heat island of London. To do this, the time-varying anthropogenic heat flux is added to an urban surface-energy balance parametrization, the Met Office–Reading Urban Surface Exchange Scheme (MORUSES), implemented in a 1 km resolution version of the UK Met Office Unified Model. The anthropogenic heat flux is derived from energy-demand data for London and is specified on the model's 1 km grid; it includes variations on diurnal and seasonal time-scales. We contrast a spring case with a winter case, to illustrate the effects of the larger anthropogenic heat flux in winter and the different roles played by thermodynamics in the different seasons. The surface-energy balance channels the anthropogenic heat into heating the urban surface, which warms slowly because of the large heat capacity of the urban surface. About one third of this additional warming goes into increasing the outgoing long-wave radiation and only about two thirds goes into increasing the sensible heat flux that warms the atmosphere. The anthropogenic heat flux has a larger effect on screen-level temperatures in the winter case, partly because the anthropogenic flux is larger then and partly because the boundary layer is shallower in winter. For the specific winter case studied here, the anthropogenic heat flux maintains a well-mixed boundary layer through the whole night over London, whereas the surrounding rural boundary layer becomes strongly stably stratified. This finding is likely to have important implications for air quality in winter. On the whole, inclusion of the anthropogenic heat flux improves the comparison between model simulations and measurements of screen-level temperature slightly and indicates that the anthropogenic heat flux is beginning to be an important factor in the London urban heat island.

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The urban heat island (UHI) phenomenon has been studied extensively, but there are relatively fewer reports on the so-called urban cool island (UCI) phenomenon. We reveal here that the UCI phenomenon exists in Hong Kong during the day, and is associated with the UHI at night under all wind and cloud conditions. The possible mechanisms for the UCI phenomenon in such a high-rise compact city have been discovered using a lumped urban air temperature model. A new concept of urban cool island degree hours (UCIdh) to measure the UCI intensity and duration is proposed. Our analyses reveal that when anthropogenic heat is small or absent, a high-rise and high-density city experiences a significant daytime UCI effect. This is explained by an intensified heat storage capacity and the reduced solar radiation gain of urban surfaces. However, if anthropogenic heat in the urban area increases further, the UCI phenomenon still exists, yet UCIdh decrease dramatically in a high-rise compact city. In a low-rise, low-density city, the UCI phenomenon also occurs when there is no anthropogenic heat, but easily disappears when there is little anthropogenic heat, and the UHI phenomenon dominates. This probably explains why the UHI phenomenon is often observed, but the UCI phenomenon is rarely observed. The co-existence of urban heat/cool island phenomena implies reduction of the daily temperature range (DTR) in such cities, and its dependence on urban morphology also implies that urban morphology can be used to control the urban thermal environment.

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This study proposes the development of thermal and energy consumption maps to generate useful planning information. A residential neighbourhood in a medium-sized city was selected as the study area. In this area, 40 points were taken as urban reference points where air temperatures at the pedestrian level were collected. At the same time, rural temperatures made available by the city meteorological station were registered. Data of electrical energy consumption of the building units (houses and apartments) were collected through a household survey that was also designed to identify the users' income levels. Then, maps were developed so that the configuration of urban heat islands and electrical energy consumption could be visualised, compared and analysed. The results showed that the income level was the most important variable influencing electrical energy consumption. However, a strong relationship of the consumption with the thermal environment was also observed.