4th International Conference on Countermeasures to Urban Heat Island, 30-31 May and 1 June 2016, National University of Singapore, Singapore
Influence of urban design in formation of Heat islands in Samambaia-DF, Brazil Raquel Dias Guedes1, Ana Paula Ribeiro2 and Caio Frederico e Silva.3 1 Raquel Dias Guedes, University of Brasilia, raqueldguedes@gmail.com 2 Ana Paula Ribeiro, University of Brasilia, anaonze@gmail.com 3 Caio Frederico e Silva, University of Brasilia, caiosilva@unb.br
ABSTRACT This article analyses one region of the Federal District of Brazil. Samambaia was chosen out of 30 different Administrative Regions (ARs) because its urban design has unique characteristics and replicates many principles of the modern movement, such as the open spaces between buildings, major roads and residual areas in the inflexion of the grid. This research discusses the relationship between thermal performance and urban design. One can identify three repeating patterns of blocks, which differ in orientation, size of lots and blocks, and arrangement of green spaces. This diversity of typologies causes solar reflection variation on the surface interfering with the air temperature and different scattering directions of the winds. The latter may be associated to air renewals and variety of shades, factors that influence the thermal comfort in the pedestrian level. These three urban patterns of blocks were modeled in the ENVI-MET software. The simulation examined the air temperature, the humidity and the dispersion of winds. From the simulation software, it can be observed that urban scenario thermal performance are significantly different from each other. The conclusion is that the urban design influences the behaviour of air masses in the city. It also suggests which situations of urban design must be avoided and which are beneficial to the thermic performance. Key Words: pattern blocks, simulation, Envi-Met, thermal performance, thermal comfort 1. INTRODUCTION The research shows how urban design can contribute to the formation of heat islands. According to Lombard (1985), it appears as a phenomenon that associates derivatives conditions of human activities on the urban environment in terms of use the ground and the constraints of the physical environment and its geological attributes. The variety of human activities in different spaces, such as parks, streets, houses, industries and the physical configuration of the city, contribute to temperature, humidity and air renewal variations. When higher temperatures are found in urban area, compared to the closest rural areas, the area is a heat island. Several factors influence the formation of this phenomenon such as the extent and density of built area, the shade conditions in streets and parking lots, the distribution of green areas, the relationship between building area and open spaces (LOMBARDO). This paper is meant to study relationship between urban design and its thermal performance, considering the building area and the open spaces of three areas of the same administrative region of the Federal District of Brazil, named Samambaia. This article will present a critical analysis using an example of peripheral modern urbanism. Samambaia is the Brazilian Federal District’s RA XII (Administrative Region 12). There lives 220,000 inhabitants and it is 30 km far from Brasilia. Its urban design reflects Brasilia’s architectural and urbanistic style, planned in 1957 by Lucio Costa and built following the Charter of 1
Athens principles of modern urbanism, written in 1933. It is a linear garden city with large green areas between housing, major roads and residual areas in the inflexion of the grid. Three parameters were considered for climate change analysis in each scenario bounded in the city: the air temperature, wind speed and dissipation and the relative humidity. The air temperature is the main factor considered in the presence of heat islands. As the speed and dissipation of the winds can mitigate these temperatures, leading to a lower thermal sensation, it is also considered important parameters for climate change. The relative humidity influence the masses of air and climate stability. In a city like Samambaia, which has two distinct seasons - rainy summer and dry winter -, the humidity is important for climate condition and its study. These chosen parameters were specified in Envi-met to obtain the simulations of each city scenario. The Envi-met is a three-dimensional simulation software of urban climate developed by Michael Bruse in Germany. According Bruse and Fleer, Envi-met Envi-met allows to analyze the effects of small scale changes in urban design on microclimate under different mesoscale conditions such as solar radiation, wind direction and humidity. According to Nogueira (2011), Chatzidimitriou et al. (2006) conducted a study in the city of Thessaloniki (Greece), observing air temperatures and surfaces, wind speed and relative humidity using the envi-met software for simulations and field research. The surface temperature difference was around 15%, which was attributed to the shadow caused by the surroundings. Romero et al. (2010) used the Envi-met to evaluate the influence of vegetation in urban microclimate of the superblock model in Brasilia (108 South), analyzed that, even without certainty of the material that the software specifies under the shade of trees, the data collected were very similar to field research. The field measuring tool associated with the simulations of these studies confirm the consistency of the data extracted from the software. 2. METHODOLOGY 2.1. Urban area of study According to Romero and Burgos (2010), the climate of Brasilia is marked by two distinct periods or two defined seasons: The hot-wet period, characterized by rainy summers from October to April. From the spring, a mass of hot air from the Amazon, acts on the Midwest and brings moisture to the Federal District, covering the city of clouds and generating strong rain showers. The apex of this mass action occurs in the months of December and January. The hot-dry season, characterized by dry winters from May to September. The hot mass and tropical dry air coming from the Paraguayan Pantanal extension reaches the Midwest, preventing the entry of cold fronts from Argentina and Uruguay. Due to insufficient of water vapor in the atmosphere, the sky is cloudless and the drought sets in. According to Romero (2001) Brasilia has conditions similar to those of humid tropical climate during the rainy season and the dry tropical climate during the dry season. Due to the continental size influence and its high altitude, the daily high temperature range are considerable, especially in the dry season. For this region, the occupation of the space should be dense and shaded. The form must be compact and offer the lowest possible surface for exposure to solar radiation. The streets should be narrow and short with changes in direction contained to reduce and prevent undesirable wind laden with suspended dust. (2013) The Federal District, shown in Figure 1, according to the INMET (National Meteorological Institute), is located at 1159.54 meters above sea level; the wind speed in the region is 1.4 m / s and they are prevalent in the east; the relative humidity varies between 35% and 95% throughout the year, reaching up to 15% in the dry season. The minimum and maximum temperatures range between approximately 12ºC and 30ºC throughout the year. The climate data used in the characterization of Samambaia climate were collected in Brasilia station. Samambaia is distant 30km southwest of the capital, as shown in Figure 2, and is home to 220,000 inhabitants in an area of 102 km². Three patterns of repetitive scenario of this city were identified and analyzed. They differ in orientation of the blocks, size of the lots and blocks, and organization of green spaces. 2
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Figure 1: Location of the Federal District and Samambaia in Brazil. Adapted Wikimedia commons, 2007
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Figure 2: Location Samambaia regarding capital Brasilia and Brazil. Adapted Google Maps, 2015
The scenarios analyzed are aerial views in Figure 3 below. These blocks are repeated in the urban area, have different ways of directions and approximate dimensions, therefore they were chosen as templates. The orientation of the north of the scenarios is almost the same, however, the blocks acquire different orientations. Scenario 1 has 345mx335m size, 17 blocks of singlefamily housing units and seven public green areas with a predominance of grass and few trees. Scenario 2 has 216mx310m size, has 12 blocks of single-family housing units and 1 block of 4 floors multifamily housing. It has a central zone of integrated green areas with predominance of lawns. The Scenario 3 has 312mx295m dimension 17 blocks of single-family residential and small green areas distributed throughout the block, the ground has grass and trees.
Figure 3: Urban patterns in Samambaia-DF. Adapted Google Earth, 2014
2.2.Simulation After determining the areas of study, it was inserted into the input data in the program. The image of each scenario was imported in .bmp format for Envi-met. The program has a grid for the 3
location of the elements, which varies according to the size of the urban area to be modeled. In this study was used a 2x2x2 grid with pixels, which equals the resolution area of 180x180 m / pixel to the size of the scenarios studied. The determination of surface coverage was grass, tree, asphalt and buildings 4m and 12m high. Each pixel of the grid was marked with one of these and, after finishing the grid, were added to the simulation data for the month of September: Wind speed in 10m ab. Ground (m/s): 1,4 Wind direction (0:N..90:E..180:S..270:W..): 90 Roughness Length z0 at reference point: 1 Initial Temperature atmosphere (K): 311 Specific humidity in 2500m (g water/kg air): 5,05 Relative humidity in 2m (%): 17 After these specifications, the simulations were imported into the Leonardo application and the maps shown in Figures 4, 5 and 6 were generated. The parameters used were potential temperature, wind speed and relative humidity.
Figure 4: potential temperature simulation held at Envi-met
Figure 5: wind speed simulation held at Envi-met
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Figure 6: relative humidity simulation relative held at Envi-met
From the maps, using AutoCAD (Autodesk) software, it was calculated the ratio of minimum and maximum value for each parameter. The Envi-met exports maps that can be precisely calculated the area of each color on the map. In Table 1, there are the percentage of built-up area, permeable areas and paved areas of each scenario. The pink and blue colors of figures above represent the most extreme values for each performance parameter, blue being the lowest value and pink the highest. In Table 2, these maximum and minimum values are associated with potential temperature, wind speed and relative humidity Table 1 Physical Aspects Physical aspects
Built up area
Permeable areas
Paved areas
Scenario 1 Scenario 2 Scenario 3
51% 48% 66%
12% 17% 2%
37% 35% 32%
Table 2 Simulation Pot temperature Simulation Scenario 1 Scenario 2 Scenario 3
Maximum 12% 14% 9%
Minimum 3% 1% 10%
Wind speed Maximum 7% 1% 9%
Minimum 10% 12% 3%
Relative humidity Maximum 1% 0% 6%
Minimum 23% 14% 17%
3. RESULTS AND DISCUSSION The three scenarios studied behave differently in each parameter. Scenario 1 showed values in the physical aspects, with the exception of the paved area, which had a higher percentage. The design of the blocks influenced the behavior of winds. The wind speed increases in the roads and decreases in the green areas. This factor was considered positive because the relative humidity from the green areas was carried by winds to the built environment and can be observed in the upper region of Figures 5 and 6. Scenario 2 has the largest green area and smaller built area compared to other scenarios. It was expected that the performance would be better, however, this scenario showed greater area of high temperatures, lower wind speeds and low relative humidity.
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Scenario 3 had the highest built-up area and lower green area and paved area. It got the best thermal performance with increased wind speed, higher humidity and lower percentage of high temperatures. The scenario 1 and 3 gained more shadows because of the different orientations of the blocks (Figure 7), which reduces the air temperature. Scenario 2 has large green areas without trees exposed to the sun all day, and this causes the highest temperature observed in Figure 1 and Table 2. For the three scenarios studied, the most suitable urban design to the local climate (hot-dry) was the scenario 3. The compact blocks with varying orientation and distributed green areas are favorable for the region. They decrease the formation of heat islands because they avoid high temperatures, increase the renewal of air masses and increase the relative humidity in the drier season.
Figure 7: Three-dimensional model of the scenarios for the preview projection of shadows at 9:00 at the winter solstice (June 22)
This study showed that urban design influences the main parameters on urban thermal performance, which are: air temperature, wind speed and relative humidity. It was observed that the urban project of Samambaia did not consider the weather of the region. The use of simulation as a design tool can positively contribute to the thermal performance of the city, which is as important as the urban aspects. The thermal performance of each region is unique and urban design must be appropriate for each climate.
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