A low-order canyon model to estimate the influence of canyon shape on the maximum urban heat island effect

2012 ◽  
Vol 33 (4) ◽  
pp. 371-385 ◽  
Author(s):  
GJ Levermore ◽  
HKW Cheung

A simple mathematical model of an urban canyon is developed. The canyon model consists of horizontal and vertical slabs providing thermal storage for heat and absorption of and shielding from solar radiation and long wave radiation to the sky. The model is compared to a horizontal slab in a rural location to examine the effect of the canyon shape. The results show the same trend as measurements by others, with increasing urban heat island (UHI) effect with increasing canyon aspect ratio. The model is then used to determine the maximum UHI effect by producing a simple algebraic equation. This compares well with measurements in Greater Manchester of canyon and rural temperatures although some empirical adjustments are required. The strong influence of cloud cover is shown by the model and measurements as are the canyon shape and the ground temperature. Practical applications: The model is simple and developed in terms applicable to building services engineers, using ventilation rates through the canyon. It also does not require more than the standard weather data available in a CIBSE Test Reference Year or a Design Summer Year. From this model, the UHI effect can be developed to adjust the data from a rural site to that of an urban and city centre site. This is useful for building designers to take account of the UHI effect which they cannot do at present. This would also be useful for UKCP09 data which have been released.

2019 ◽  
Vol 40 (3) ◽  
pp. 290-295 ◽  
Author(s):  
Geoff Levermore ◽  
John Parkinson

On top of climate change and its consequent temperature rises, urban areas have the added burden of the urban heat island (the urban area being warmer than the rural area especially at night under calm, cloud-free conditions). The urban heat island intensity (the difference between the rural air temperature and that in the city centre) can be as large as 10K for the major cities such as London. The urban heat island intensity, consequently, can have a significant effect on the sizing of heating, ventilating and air-conditioning plant and its energy consumption. At present, designers have access to empirical factors for design days only in June, July and August from the Chartered Institution of Building Services Engineers Guide. Or they can use the latest Design Summer Year which implicitly includes the urban heat island intensity. However, the empirical model discussed in this paper allows the designer to add on the hourly urban heat island intensity for central London to any recent year’s hourly weather data set from London Heathrow or Bracknell, a more rural site. The model is similar to one for Manchester, suggesting that the model may well be of application to other UK cities. Practical applications: Most buildings that building services engineers and other building designers are involved with are in urban or city centres. However, the weather data for their designs are based on near-rural weather data, which does not include the urban heat island effect. This paper describes the urban heat island effects that a designer needs to consider and the adjustments that can be made, related to London.


2016 ◽  
Vol 38 (1) ◽  
pp. 21-31 ◽  
Author(s):  
Geoffrey J Levermore ◽  
John B Parkinson

The urban heat island intensity is the difference in temperature between a site close to the centre of a city and a site close to but outside the city (the rural site). The urban heat island intensity varies continuously throughout the day and is strongly dependent on the weather conditions at the time. The most important weather parameters are the wind speed, the cloud cover and the solar radiation. We have developed an empirical model for the urban heat island intensity and applied it to a site near the centre of Manchester and a rural site at Rostherne, approximately 17 km away. Weather data from the Met Office station at Rostherne are available from the British Atmospheric Data Centre. Our model uses the measured wind speed, the measured cloud cover and the measured solar radiation from Rostherne. The parameters of the model are adjusted to give a best fit to the measured urban heat island intensity for the year 2014. The model is then used to predict the hourly urban heat island intensity for the first six months of 2015, obtaining good results especially as the values of the parameters are not changed throughout the year and the model does not make use of the temperatures at either site. The accuracy of the model is such that if used for a basic heating and cooling load calculations the accuracy of the annual demand is high. Practical applications: Many buildings that building services engineers and other building designers design are in urban or city centres. However, the weather data for their designs are based on near-rural weather data which do not include the urban heat island effect. This paper describes a method to ascertain the urban heat island effect in the centre of Manchester. A designer could apply this for Manchester and as an initial indication to other similar urban areas. This will allow the rural weather data to be adjusted on an hourly basis for the urban heat island effect throughout the year.


2019 ◽  
Vol 11 (24) ◽  
pp. 6905 ◽  
Author(s):  
Lindita Bande ◽  
Adalberto Guerra Cabrera ◽  
Young Ki Kim ◽  
Afshin Afshari ◽  
Mario Favalli Ragusini ◽  
...  

Villas are a very common building typology in Abu Dhabi. Due to its preponderance in residential areas, studying how to effectively reduce energy demand for this type of building is critical for Abu Dhabi, and many similar cities in the region. This study aims to show the impact of proposed energy efficiency measures on a villa using a calibrated model and to demonstrate that to be accurate, the model must be driven using urban weather data instead of rural weather data due to the significance of the urban heat island effect. Available data for this case study includes construction properties, on-site (urban) weather data, occupancy-related loads and schedules and rural weather data. Four main steps were followed, weather data customisation combining urban and rural weather variables, model calibration using a genetic algorithm-based tool and simulating retrofit strategies. We created a calibrated model for electricity demand during 2016–2017 with a 4% normalized mean bias error and an 11% coefficient of variation of the mean square error. Changing from none to all retrofit strategies results in a 34% reduction in annual energy consumption. According to the calibrated model, increased urban temperatures cause a 7.1% increase in total energy consumption.


2019 ◽  
Vol 46 (11) ◽  
pp. 1032-1042 ◽  
Author(s):  
Isabeau Vandemeulebroucke ◽  
Klaas Calle ◽  
Steven Caluwaerts ◽  
Tim De Kock ◽  
Nathan Van Den Bossche

Renovating historical buildings with valuable facades often includes interior retrofitting, perhaps entailing an increased durability risk. However, the urban heat island effect and the ongoing climate change might mitigate the severity of frost action and mould growth. By means of heat air moisture (HAM) simulations in Delphin, this study evaluates interior retrofitting of solid masonry on three scales. First, the sensitivity to the intra-urban climatic differences of the freeze–thaw cycles in Ghent is analysed. Secondly, the spatial pattern of freeze–thaw behaviour across Europe is assessed. Finally, the influence of observed climate change on the European freeze–thaw pattern is investigated. A decreasing number of critical freeze–thaw cycles is found when comparing the rural area with the city centre of Ghent. Furthermore, due to climate change, the number of freeze–thaw cycles across Europe generally decreases as well, except at northern latitudes exposed to increased wind-driven rain loads.


Author(s):  
Stephen Burt ◽  
Tim Burt

This chapter deals with the growth of Oxford since 1767 and assessment of the potential influence of the expanding urban area on the temperature record from the Radcliffe Observatory, using long-period data from a semi-rural site at Rothamsted (Hertfordshire) and a more recent 3-year comparison with records from nearby Wallingford to assess the extent of, and changes in, Oxford’s urban heat island. The urban heat island effect remains small but is shown to have increased in magnitude in recent decades, and is likely to affect the homogeneity of the Oxford temperature record. In addition, the chapter provides a comparison of the data from the Radcliffe Observatory with that from the Central England Temperature series.


2021 ◽  
Vol 13 (3) ◽  
pp. 1099
Author(s):  
Yuhe Ma ◽  
Mudan Zhao ◽  
Jianbo Li ◽  
Jian Wang ◽  
Lifa Hu

One of the climate problems caused by rapid urbanization is the urban heat island effect, which directly threatens the human survival environment. In general, some land cover types, such as vegetation and water, are generally considered to alleviate the urban heat island effect, because these landscapes can significantly reduce the temperature of the surrounding environment, known as the cold island effect. However, this phenomenon varies over different geographical locations, climates, and other environmental factors. Therefore, how to reasonably configure these land cover types with the cooling effect from the perspective of urban planning is a great challenge, and it is necessary to find the regularity of this effect by designing experiments in more cities. In this study, land cover (LC) classification and land surface temperature (LST) of Xi’an, Xianyang and its surrounding areas were obtained by Landsat-8 images. The land types with cooling effect were identified and their ideal configuration was discussed through grid analysis, distance analysis, landscape index analysis and correlation analysis. The results showed that an obvious cooling effect occurred in both woodland and water at different spatial scales. The cooling distance of woodland is 330 m, much more than that of water (180 m), but the land surface temperature around water decreased more than that around the woodland within the cooling distance. In the specific urban planning cases, woodland can be designed with a complex shape, high tree planting density and large planting areas while water bodies with large patch areas to cool the densely built-up areas. The results of this study have utility for researchers, urban planners and urban designers seeking how to efficiently and reasonably rearrange landscapes with cooling effect and in urban land design, which is of great significance to improve urban heat island problem.


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