Intensity and Spatial Influence of Urban Parks: A case study in Sao Paulo, Brazil

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1 600 Intensity and Spatial Influence of Urban Parks: A case study in Sao Paulo, Brazil Paula Shinzato PhD Student at Faculty of Architecture University of São Paulo Brazil paulashinzato@yahoo. com Denise H. S. Duarte Professor at Faculty of Architecture University of São Paulo Brazil dhduarte@terra.com.br Fernanda C. Barros, graduate student at FAU-USP, Brazil, fernanda.camargobarros@gmail.com Denise C. Moreira, graduate student at FAU-USP, Brazil, denise.moreira@usp.br Summary The main purpose of this ongoing research is to assess the cooling effects of vegetation in urban microclimate. Considering the influence of Leaf Area Index LAI, this study will quantify the intensity and spatial distribution of the microclimate effects in border regions for urban parks, such as Trianon Park, located at Paulista Avenue in downtown São Paulo/ Brazil. Considering Trianon park as a large mass of vegetation with few sparse areas, an average leaf area index for the entire park was estimated based on two indirect gap-fraction method, the LAI-2000 plant canopy analyser (LI-COR) and a camera system with eyefish lens (Nikon Coolpix 4500). The hemispheric photographs were analysed using can-eye software. Microclimatic meteorological data was obtained in two areas of the park during four consecutive days of measurements, beginning on 28 th October This database was important to adjust the ENVI-met model to local conditions before starting the parametric studies. Parametric simulations on ENVI-met were developed to investigate the effect of the park on its surroundings, indicating the influence of LAI measured previously. Results indicated that, concerning the intensity of the effect, the average difference between air temperatures inside the green areas (LAI=2.5) and the surrounding streets is about 2ºC at 2 p.m. and the extension of the effect can reach 10 m from the park. Keywords: urban vegetation, urban microclimate, leaf area index, ENVI-met. 1. Introduction Vegetation plays an important role in moderation of urban climate. It varies according to the mesoscale circumstances, but in any case vegetation can give a significant contribution to the climatic conditions [1]. Areas covered by plants have some common properties by which they differ from build-up and hard surface unplanted areas. Leaves of plants absorb most of solar radiation which impinges upon them. A small part of of the radiant energy is transformed by photosynthesis into chemical energy and in this way reduce the rate of heating of the urban space [2]. Previous studies have shown the vegetation benefits in urban environment, which include: microclimate modifications [3,4,5], removal of air pollutants [6,7], tree shading as passive cooling for buildings façades [8,9], influence in human health and aesthetic value of green areas [10,11,12]. Considering the microclimate, vegetation is important due to its properties on energy balance. According to Penman-Monteith method [13], the equation for evapotranspiration rate by plants is direct related to the quantity of stomata in the surface of leaves. In this sense, the density of leaves,

2 601 which can be represented by the leaf area index LAI, is an indicator of gas exchange (oxygen and carbon dioxide) as well as the water vapor loss in transpiration. LAI is a dimensionless variable and is defined as one-half the total green leaf area per unit of ground surface area [14] drives the within and the below canopy microclimate, determines canopy water interception, radiation extinction, and water and carbon gas exchange. LAI is a key parameter in models describing the exchange of fluxes of energy, mass (e.g. water and CO 2 ), and momentum between the surface and the planetary boundary layer [15]. This study is part of an ongoing research about the impact of vegetation on urban microclimates, using predective models such as ENVI-met. This computational model considers the density of leaves to simulate the micro scale interations of surface-vegetation- atmosphere. 2. Methodology 2.1 Area of Study São Paulo is located in the Southeast region of Brazil. It is a sprawling megacity which metropolitan area houses almost 19 million inhabitants, distributed in an area of 8051km 2. Nowadays, São Paulo is characterised by a heterogeneous urban structure, which has been caused by the rapid growth of the city during the last century. One of the effects of this growth is the social conflict of high-rise office towers close to poor informal settlements. For decades, downtown has suffered a continuous degradation process and has gradually been abandoned by its residents. The city's plan distribution is very uneven, the metropolitan area of São Paulo experiences simultaneously massive urban sprawl in its peripheries and population decrease in its central parts Now the average density in the city centre is approximately only 64 inhab/ha [16] in spite of a high built density. Today, 48% of the territory of São Paulo is significantly lacking in plant cover of any type. Although the Environmental Atlas of São Paulo [17] indicates adequate arborization with more than 7m 2 of green area per habitant, some other neighbourhood in downtown area has almost zero (Sé, Republica). The highest temperatures were found in the central area without green areas and the lowest in urban parks. The municipal district of São Paulo has 35 urban parks distributed throughout the city, with a total area of 1,579 hectares, corresponding to 1.12% of the total area of the municipal district. In the downtown area, there are seven urban parks and this study focuses on Tenente Siqueira Campos Park (or Trianon Park), situated on Paulista Avenue. 2.2 Field Measurement at Trianon Park LAI Measurements There are two main forms to obtain the LAI values: the direct and the indirect methods. The first one can be accessed directly by using harvesting methods such as destructive sampling or by non-harvesting litter traps during autumn leaf fall period in deciduous forests [18]. The indirect methods consist in measurements of light transmission through the tree canopy. It can be calculated by Beer-Lambert law, which defines the empiric relation between radiation intercepted by the canopy and the total incident solar radiation. For this study, two methods were applied based on gap fraction distribution: using the instrument LAI-2000 Plant Canopy Analyzer (LI-COR) and the technique via hemispherical canopy photography [19], between August and September of Although the park is crossed by Alameda Santos Street, it has a pedestrian bridge to connect the two separated parts. During planning process, a grid of 20x20m was created over the site plan of

3 602 the park to define points for measurements (figure 1). The Area 1 was located close to the main entrance of the park from Paulista Avenue, which has low-density trees with 6 points for LAI measurements. The Area 2 is in the middle of the second block of the park and it has a very dense group of trees (points 10-22). Fig. 1: Location of 22 points for LAI measurents at Trianon Park Fig. 2: LAI-2000 Plant Canopy Analyser Source: LI-COR The LAI 2000 (figure 2) is a portable instrument that calculates Leaf Area Index (LAI) and other canopy attributes from light measurements made with a fish-eye optical sensor (148 field-ofview). Measurements made above and below the canopy are used to calculate canopy light interception at five zenith angles (7 º, 23 º, 38 º, 53 º, 68 º), from which LAI is computed using a model of radiative transfer in vegetative canopies Moreover there is an in-built optical filter that rejects incoming radiation with wavelengths below 490nm in order to minimize the radiation scattered by the canopy [20]. To reduce the margin of error in the results, there is an option to use 5 different view restricting caps, which serves to limit the azimuthal field of view of the optical sensor in circumstances that it is necessary or desirable to block part of the view. For the conditions of Trianon Park view restricting caps were used to remove the operator from the sensor s view and to reduce the required clearing size for above-canopy readings in this dense urban park. Pre-sensitivity tests of the equipment LAI-2000 were conducted in the surrounding of the Faculty of Architecture and Urbanism of the University of Sao Paulo/ USP. The estimate value for LAI with the LAI-2000 was made using the single sensor method to collect readings outside and below the canopy. These tests were made in two days on July/ 2012 with different sky conditions and using 90 º and 180 º view caps. According to the best results obtained during pre-tests at USP, the same conditions were considered at Trianon Park. The single sensor method was used for measurements with 90 view cap and under a very uniform overcast sky conditions. This helped to avoid sun glare or sun flecks during field measurements. To obtain the LAI values for each point in the park, 4 measurements were performed below the canopy (figure 3a) and 1 external to the canopy (figure 3b). (a) (b) Fig. 3: Internal points with the cover of 90 (a) and external point with the cover of 90 (b). The results of LAI values in all points varied from 1.46 to 3.86, and are shown in Figure 4. The average value of LAI in the 22 measured points was 2.52.

4 603 Fig. 4: LAI values measured at Trianon Park (22 points). Hemispherical canopy photography is a technique for studying plant canopies using photographs acquired through a hemispherical (fisheye) lens from beneath the canopy (oriented towards zenith) or placed above the canopy for downward looking. Furthermore, the use of fish-eye lens allows the gap fraction to be evaluated in all viewing directions, which increases the accuracy of the derived biophysical variables (LAI) and there is a potential to characterize the azimuthal distribution of the foliage and the departure to non-random leaf arrangement. In addition, it is also possible to derive estimates of the leaf area index for canopies growing on sloppy terrains [21]. For Trianon Park, a coupled system based on a fish-eye lens (Nikon FC-E8) and a digital camera (Nikon FC-E8) were used under overcast sky conditions. The hemispherical photographs were taken on August 15 of 2012, from12h to 15h. The analysis of all photographs were done using Can-Eye model. Firstly, the camera and lens were calibrated to define optical center and projection function. Then, each image was pre-processed in the model. The pixel brightness values for the blue band are extracted from each RGB image to achieve maximum contrast between leaf and sky, because absorption of leafy materials is maximal and sky scattering tends to be highest in that band [22, 23]. Thresholding procedures were applied in order to identify the optimal brightness threshold and distinguish vegetation from sky. Fig. 5: Results of hemisferical photographs (1-6) taken at Trianon Park Fig. 6: Color classification and image preprocessing using Can-Eye model

5 604 Comparing the final results from both LAI measuring systems, it can be seen that the average LAI values had few differences, varying between 2.14 (hemispheric photographs) and 2.52 (LAI-2000), calculate from 22 defined points at Trianon Park. Each system has its specific measuring details and the choice has to consider the local conditions for the studies. In this sense, the Trianon Park has a dense arrangement of trees distribution with few spots among them. For these characteristics, the technique using hemispherical images had a better application comparing with LAI-2000 instrument as it evaluate an average LAI for a determined area, but not for a single tree. Overestimated values can be found using LAI-2000 as it considers not only leaves but other elements such as branches and trunk. 3. Preliminary ENVI-met Simulations 3.1 ENVI-met Model The micro scale model ENVI-met [24] was chosen for this study due to its advanced approach on plant-atmosphere interactions in cities. The numerical model simulates aerodynamics, thermodynamics and the radiation balance in complex urban structures with resolutions between 0.5m and 10m according to the position of the sun, urban geometry, vegetation, soil and various construction materials by solving thermodynamic and plant physiological equations. The model calculates the energy balance for long and short waves, considering total radiation, air fluxes, air temperature, humidity, local turbulence, reflection from buildings and vegetation. Based on the studies of Deardorff [25] and Jacobs [26], it also implemented a numerical model to calculate the main variables related to plant physiological behaviour: transpiration, evaporation, latent heat flux, water exchange, stomata resistance, leaf temperature and energy balance for soilvegetation system [27]. To adjust the model, previous climate monitoring was carried out from September 28 th to October 1 st of 2012 at the park. With this database as a starting point, preliminary studies were done for the initial simulations in ENVI-met. These parametric studies were important to adjust the model main variables and to verify the influence for each parameter in the input data. Before inserting the green areas, it was fundamental to adjust the output values to the measured climatic conditions of the city of Sao Paulo. 3.2 ENVI-met Parametric Simulations ENVI-met model, instead of using LAI, considers the parameter Leaf Area Density LAD to calculate plants physiology. According to the ENVI-met plant database, there are 11 types of vegetation, which have specific characteristics according to the following aspects: CO 2 fixation (C 3 or C 4 plants), minimum stomata resistance, short-wave albedo, height of the plant, total depth of the root, Root Area Density - RAD and Leaf Area Density LAD. LAD is a parameter defined as the total one-sided leaf area (m²) per unit layer volume (m³) in each horizontal layer of the tree crown. The LAD profile was calculated by integrating LAI values [28]. For this study, a vegetation data basis was created based on the previous data survey mentioned before that pointed out the main tree species used in the city of Sao Paulo and their canopy characteristics quantified by Leaf Area Density LAD. Based on LAI measurements results, the ENVI-met simulations consider a medium canopy with LAI value of 2,5. The tree is 20m high and its leaf density started 4m above the ground to avoid obstruction for wind flux at the pedestrians level. The parametric tree model had ellipsoid leaf area distributions with maximum LAD located in the middle height of the crown (Figure 7). The input data for the simulations are presented in Table 1, based on previous parametric studies carried out to adjust the model. The input area domain was created with information from the park and its surroundings. Two receptors were considered for simulations: one in the middle of the park and another one in the sidewalk without vegetation to give specific information for each point.

6 605 Fig. 7: LAD (Leaf Area density) (m2/m3) in 10 layers of the tree model (LAI=2.5) Fig. 8: The input area domain for ENVI-met simulations Table 1: Input configuration data applied in the ENVI-met simulations. Start Simulation at day Wind Speed in 10m ab. Ground [m/s] 0.1 Wind Direction (0:N/ 90:E/ 180:S/ 270:W) 200 Initial Temperature Atmosphere [K] 283 Specific Humidity in 2500m [g Water/ kg air] 9.5 Relative Humidity in 2m [%] 79 Initial Temperature Upper Layer (0-20cm) [K] Analysis of Results From the results of simulations, the receptor located in green areas of the park showed a reduction up to 2.0ºC compared to air temperature in the sidewalk. Over paved areas the simulations showed an average air temperature of 26.5ºC at 14h, while 24ºC under the canopies. The results for superficial temperature indicated that trees have a significant impact by lowering the surface temperature by up to 29ºC. The tree canopy blocks part of the direct solar radiation and avoid the rapidly surface warming up. In the street, the superficial temperature varies from 41ºC to 45ºC, while in the green areas, it goes between 26ºC and 27.5ºC. Concerning the intensity of the effect, the average difference among air temperatures inside the green areas and the surrounding streets is about 2.0ºC. For surface temperatures, the dense tree shading (LAI=2.5) has shown average differences of 17ºC under the canopy. In that sense, green areas can be an important strategy to mitigate the warming up effect in cities due to the shading and evapotranspiration process. Regarding the spacial distribution of vegetation, results show that the effect is very local, and the influence of green areas doesn t go very far from the green borders at pedestrian level. Measurements at Trianon Park showed that the effect for air temperature can be felt under the canopy and approximately 10m away from the canopy. As an indicator to urban planning, green areas should be better distributed in small groups of trees than a large park. The effect of tree canopy shadow has also a great potential to ameliorate the microclimate and mitigate heat stress in a hot humid climate. On the other hand the shade efficiency of trees will depend on the type of plants and the amount of leaf density. Because of this parameters such as Leaf Area Index and Leaf Area Density are fundamental to improve the positive impact of vegetation, considering the plant local influence.

7 Acknowledgments This research was supported by Fundação de Amparo à Pesquisa do Estado de São Paulo FA- PESP and Conselho Nacional de Desenvolvimento Científico e Tecnológico - CNPq. The authors are grateful to Labaut staff for their assistance in the field measurements. 6. References [1] WILMERS F. Effect of Vegetation on Urban Climates and Buildings. Energy and Buildings, No.15, [2] GIVONI B. Impact of Planted Areas on Urban Environmental Quality- A review. Atmospheric Environment. Vol 25, No. 3, 1991, pp [3] YU, C.; HIEN, W. N. Thermal benefits of city parks. Energy and Buildings, Lausanne, v.38, p , [4] EMMANUEL M.R. An Urban Approach to Climate-Sensitive Design Strategies for the Tropics. Spon Press, [5] YU C., HIEN W.N. Thermal benefits of city parks. Energy and Buildings, Vol. 38, 2006, pp [6] DIMOUNDI A., NIKOLOPOULOU M. Vegetation in the Urban Environment: Microclimatic Analysis and Benefits. Energy and Buildings, Vol. 35, No.1, [7] NOWAK, D. J.; MCHALE, P. J.; IBARRA, M.; CRANE, D.; STEVENS, J. C.; LULEY, C. J Modeling the effects of urban vegetation on air pollution. In: Gryning, Sven-Erik; Chaumerliac, Nadine, eds. Air pollution modeling and its application XII. New York; Plenum Press: [8] HEISLER, G.M., Effects of individual trees on the solar radiation climate of small buildings. Urban Ecol. 9, , [9] SANTAMOURIS M. Energy and Climate in the Built Environment. James and James, London, [10] ULRICH, R. S. The therapeutic role of greenspace, paper presented at the Greenspace and Healthy Living National Conference, Manchester, [11] ULRICH, R. S. View through window may influence recovery from surgery, Science 224 pp , [12] ULRICH, R. S. Influences of passive experiences with plants on individual wellbeing and health, in Relf, D. (ed) The Role of Horticulture in Human Well-Being and Social Development: A National Symposium. Timber Press, Portland, Oregon pp , [13] MONTEITH, J.L. Evaporation and environment. pp In G.E. Fogg (ed.) Symposium of the Society for Experimental Biology, The State and Movement of Water in Living Organisms, Vol. 19, Academic Press, Inc., NY, [14] CHEN, J. M.,BLACK, T. A. Foliage area and architecture of clumped plant canopies from sunfleck size distributions. Agricultural and Forest Meteorology, 60: p , [15] LI, Z., GUO, G. A suitable vegetation index for quantifying temporal variations of LAI in semi-arid mixed grassland. Canadian Journal of Remote Sensing. 36(6): , [16] Meyer R.M.P et al., Sao Paulo Metrópole. Sao Paulo. Editor University of Sao Paulo, [17] SVMA, Atlas ambiental de Sao Paulo, [18] ONG, B. L. Green Plot Ratio: An Ecological Measure for Architecture and Urban Planning. Landscape and Urban Planning, vol.63, p , [19] WEISS, M., BARET, F. CAN-EYE V6.1 User Manual. EMMAH laboratory (Mediterranean environmentand agro-hydro system modelisation). French National Institute of Agricultural Research (INRA), [20] JONCKHEERE, I.et al. Review of methods for in situ leaf area index determination Part I. Theories, sensors and hemispherical photography. Agricultural and Forest Meteorology 121: 19 35, 2004 [21] JONCKHEERE, I. G. C., MUYS, B., COPPIN, P. R. Derivative Analysis for In Situ High Dynamic RangeHemispherical Photography and Its Application in Forest Stands. IEEE Geoscience and Remote Sensing Letter, 2, , 2005b.

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