Outdoor thermal comfort rehabilitation for different LCZ classes in an arid city

M. BELÉN SOSA; M. FLORENCIA COLLI; ÉRICA N. CORREA; M. ANGÉLICA RUIZ

Santiago

Conferencia; PLEA 2022 SANTIAGO: Will Cities Survive?; 2022

PLEA Association (Passive and Low Energy Architecture)

1. INTRODUCTION Urban populations are exposed to an increasing frequency and intensity of weather extremes due to both regional and global climate changes and urban climate alteration [1]. This tends to be exacerbated in arid cities during the summer months. For this reason, it is important to understand how cities perform climatically in order to be able to propose an urban design according to the natural resources and the particular features of the cities [2]. The application of easy-to-use tools in the pre-design stage, would help urban planners to improve the microclimatic conditions of cities. This work was carried on in Mendoza Metropolitan Area (MMA) in central western Argentina, Andes region (32°53′ S, 68°51′ W, 750 m.a.s.l.). The climate classification according to the Koppen-Greiger corresponds to BWh or BWk. The landscape classification system [3] comprises the categorization of LCZ or uniform regions in land cover, structure, materials and human activities. Based on this background, the objective of this work is to analyze the urban rehabilitation possibilities of the MMA, focusing of improving the daytime outdoor thermal performance and comfort by applying two easy-to-use tools. 2. DATA AND METHODS2.1 LCZ distribution and thermal behavior monitoringTo define the LCZ of the MMA, the WUDAPT tool has been used [4]. For thermal behavior monitoring a set of points in each LCZ class were selected. The thermal behaviors were monitored with HOBO® data-loggers (H08-003-02) set up every 15 minutes. They were installed regarding the recommendations of [5]. Microclimatic data were captured during a 20-day measuring campaign (12/21/2018 to 01/09/2019). December 23th was selected as the study day as the meteorological conditions were typical of a summer day in an arid region.2.2 Urban rehabilitation design toolsIn order to analyze the MMA thermal rehabilitation possibilities, two previous developed easy-to-use design tools were used [2; 6]. These tools are statistical models that allow urban planners to predict in a pre-design stage the following outdoor performances: DTair=29.18 - 6.2 0 * T/m - 0.05 * MBH - 0.13 * UCW - 6.97 * HA + 0.28 * DTwall (1)Tcomfort= -491.59 - 12.90*SP - 4.86 * NT + 313.23 * SVF + 20.89 * DTwall (2)where DTair - daytime thermal behavior (◦C); T/m - trees per meter; MBH - mean building height (m); UCW - urban canyon width (m);HA - horizontal albedo;DTwall - daytime surface temperature of walls (◦C);Tcomfort - thermal comfort (W/m2); SP - solar permeabilityNT - number of treesSVF - sky view factor3. RESULTS3.1 Urban design tool adjustmentThe thermal behavior of three points was used for testing the adjustment of the pre-design tools. This MMA points made a representative sample of the most common LCZ classes: “LCZ 3b-Low-rise compact”, “LCZ 6b-Open-rise compact” and “LCZ 8-Large-low construction” which represents the 21.4%, 27.5% and 22.7% respectively of the total area. Figure 1 shows the thermal behavior of the selected day (12/23/2018), and Table 1 shows the difference in ºC between the monitored and the estimated by using the DTair pre-design tool performances. Figure 1. Thermal behavior measured on 12/23/18.Table 1. Adjustment of the DTair tool.MonitoredEstimatedDifferenceLCZ 335.7ºC36.0ºC+0.3ºCLCZ 635.8ºC35.5ºC-0.2ºCLCZ 836.7ºC35.8ºC-0.8ºCBy analyzing the thermal behavior, we can see that the LCZ 8 point it’s the hottest, and the LCZ 3 and 6 points remains cooler and with similar behaviors. Regarding the adjustment by using the pre-design tool we can notice that in all cases the thermal predictive difference is minor than 1ºC. Taking into account that the data-loggers used accuracy is ±0.7°C, these predictive results found to be reliable.3.2 Urban scenarios proposedIn order to use the pre-design tools to search planning recommendations, a set of twelve urban scenarios were tested (six forested and the other six non-forested). Each of the urban scenarios respect the validity ranges of the tools [2] and the values of geometric and surface cover properties for LCZ [3]. Table 2 shows the variables used, it is important to clarify that some variables are fixed and others varies.The results in terms of DTair shows that:The best scenario corresponds to LCZ 3b (31.2ºC). This scenario has 15 m building height, SVF=0.48, forested, with a horizontal albedo of 0.54. The worst scenario corresponds to LCZ 8b (34.4ºC). This scenario has 3m building height, SVF 0.86, non-forested, with a horizontal albedo of 0.38. The results in terms of Tcomfort shows that:None scenario reaches an outdoor thermal comfort sensation, regarding the COMFA index (-50 > Would prefer no change < +50 W/m2).The best scenario corresponds to LCZ 3b (327 W/m2). The worst scenario corresponds to LCZ 8b (572 W/m2). For each LCZ the results are coincident with the best scenario in terms of DTair.Table 2. Urban scenarios variables values.VariableValueMBH (m)3 - 9 - 15UCW (m)20H/W0.20 - 0.50 - 0.80T/m *0.24HA0.38 - 0.54Dtwall (ºC)38SVFBetween 0.48 - 0.86NT (u) 0 - 25SP Morus alba0.314*2º magnitude trees implanted at 8 m - street length of 100 m4. CONCLUSIONRegarding to provided urban planning rehabilitation strategies for the MMA we can found that for “LCZ 3b-Low-rise compact”, “LCZ 6b-Open-rise compact” and “LCZ 8-Large-low construction” (which represent 71.6 % in total), is recommended to keep the street forestation homogeneaus and increase the horizontal albedo values. Taking into account the relationship between DTair and Tcomfort responses with the H/W and SVF indicators, to greater SVF values DTair is hotter but Tcomfort sensation is better, and to greater H/W values Tcomfort sensation tends to be better. REFERENCES 1. Mandelmilch, M., F. Michal, M. Noa and P. Oded, (2020). Urban Spatial Patterns and Heat Exposure in the Mediterranean City of Tel Aviv. Atmosphere, 11: p. 963.2. Ruiz, M. A., M. B. Sosa, E. Correa and M. A. Canton, (2017). Design tool to improve daytime thermal comfort and nighttime cooling of urban canyons. Landscape and Urban Planning, 167: p. 249–2563. Stewart, I. D. and Oke, T. R. (2012). Local climate zones for urban temperature studies. Bulletin of the American Meteorological Society 12: p. 1879-1900.4. Colli, M. F., E. N. Correa y C. F. Martinez (2020). Aplicación del método WUDAPT en la ciudad De Mendoza-Argentina para definir Zonas Climáticas Locales. Revista Urbano 42: p. 18-31. 5. Oke, T. R. (2004). IOM Report No. 81, WMO/TD No. 1250: Initial guidance to obtain re presentative meteorological observations at urban sitesGeneva: WMO.6. Ruiz, M. A., & Correa Cantaloube, E. N. (2015). Adaptive model for outdoor thermal comfort assessment in an Oasis city of arid climate. Building and Environment, 85, 40–51. http://dx.doi.org/10.1016/j.buildenv.2014.11.018.