RELATIONSHIP BETWEEN MEAN RADIANT TEM- PERATURE AND SOLAR ANGLE FOR PEDESTRIANS

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1 M. A. Schnabel (ed.), Cutting Edge: 47 th International Conference of the Architectural Science Association, pp , The Architectural Science Association (ANZAScA), Australia RELATIONSHIP BETWEEN MEAN RADIANT TEM- PERATURE AND SOLAR ANGLE FOR PEDESTRIANS QUN DAI and MARC AUREL SCHNABEL School of Architecture, The Chinese University of Hong Kong, Hong Kong. {daiqun, 1. Introduction Abstract. Outdoor thermal comfort for pedestrians has become an important issue in urban planning affecting everyone s daily life. Mean Radiant Temperature (T mrt ) is one of the most important parameters in micro climate. In this study, we built a computerised model with idealized buildings in different months. Then a radiation model SOLWEIG was used to simulate T mrt spatial variations on pavements. We analysed and discussed the simulation results by comparing impact from different solar angles. Our finding can act as a reference for architects and planners to make design decisions on quantifying the thermal comfort in specific urban environments and their buildings. Keywords. T mrt ; SOLWEIG; solar angle; pedestrians. The topics surrounding outdoor and micro climate are becoming increasingly popular issues and generate new collaboration between different fields of research. However, urban design knowledge on outdoor thermal comfort for pedestrians conditional on the solar angle remains limited. Different months bring different solar angles and thus can be used as a proxy for revealing the impact from the angle. In presenting thermal comfort distributions, the average value or the centre point value of thermal comfort can t truthfully represent all the thermal comfort information, as there is meaningful difference between the centre zone and two pavements. The spatial variations of T mrt in different months for three street zones were simulated and analysed. Several studies have shown the relationship between thermal comfort and other factors in micro urban street scale. Ali-Toudert et al (2005), Ali- Toudert and Mayer (2006), Johansson (2006), and Johansson and Emmanuel (2006) focused on what role the geometry of urban canyons plays on the thermal comfort for people. Krüger et al (2011) focused on h/w, time zone

2 252 Q. DAI AND M. A. SCHNABEL and orientation impact while Shashua-Bar et al (2010) considered h/w, orientation, ground coverage, and distance from sea for urban morphology. Bourbia and Awbi (2004) discussed the consequences of orientations and shading. Bourbia and Awbi (2004) did analysis on buildings with six orientations but on shading instead of human thermal comfort index. Herrmann and Matzarakis (2012) conducted an analysis on T mrt in idealized urban canyons using RayMan (Matzarakis et al, 2007), and considered the street orientation impact; however they simulated the T mrt along the centre line of the street only. Typically however, people are staying on the pedestrian-zones which are usually located at the street side. Hence the mean or centre point s simulation result can t differentiate the T mrt values between different zones of a street in detail. Thorsson et al (2011) applied SOLWEIG model to show the spatial variations of T mrt with four types of urban forms; yet they did not analyse the hourly variations of T mrt. To quantify the thermal comfort of the environment people have found useful indices as indicators of the human energy balance. The T mrt is one of the most important thermo-physiologically relevant assessment indexes. Several European studies showed that in summer days with a weak wind velocity there is a strong relationship between T mrt and the perceived temperature, such as the thermal comfort index called PET (Gulyás et al, 2006; Matzarakis et al, 1999). Further studies claimed that the perceived temperature during hot summer days directly relates to T mrt (Mayer et al, 2008). In medium-sized western European cities, such as cities in the Netherlands or Germany, wind speed is low during typical heat wave events. Thus T mrt becomes an important thermo-physiological indicator in these regions. T mrt includes all short-wave radiation fluxes (direct, diffuse and reflected) as well as long-wave radiation flux emitted from the sky, walls and floors (Matzarakis et al, 2007). It represents the human radiation exposure to all short and long wave radiation fluxes by weighting the directional components in all six directions (front, back, left, right, top and bottom) to obtain the radiation load on a standardized human being (Matzarakis et al, 2007). We simulate T mrt in an idealized urban environment using the SOL-WEIG model. The similar methodology has been applied before to derive related results in the previous work of the authors. Dai and Schnabel (2013a) considered the impact of orientation on T mrt while Dai and Schnabel (2013b) studied the impact of building type on T mrt. The impact from the height to width ratio and from the combined configurations of both the height to width ratio and orientations were examined in Dai et al (2012a) and Dai et al (2012b) respectively. In this study, built upon the previous work, we would investigate the influence of the solar angle along different months of the year so that the T mrt impact factor investigation becomes even more complete.

3 MEAN RADIANT TEMPERATURE AND SOLAR ANGLE 253 The solar angle is also intrinsically related to the urban form factors in shaping thermal comfort, so the former studies on urban form factors also provide necessary context for this new development. We focus on the spatialtemporal T mrt distributions of three zones of a street with different months in an idealized urban environment for a year. The results demonstrate that T mrt strongly depends on solar angle, h/w, and orientation, on a computerized and idealized urban model consisting of a centre area for cars and the adjacent pedestrian zones and bicycles. The study also quantifies the effect of solar angles in Rotterdam. The findings of better urban form for thermal comfort can be used in urban planning. 2. Simulation Software Regarding the simulation tools for micro-scale models, most of the architectural modelling and visualization software cannot be used to derive T mrt. Currently there are five commonplace simulation models for T mrt easily available, namely the ENVI-met Model (Bruse and Fleer, 1998) developed by Michael Bruse Ozkeresteci, the point simulation model called RayMan (Matzarakis, 2009; Matzarakis et al, 2007), SkyHelios for calculating sky view factor and sunshine durations (Matzarakis and Matuschek, 2011), TownScope for building energy calculation (Teller and Azar, 2001), and the SOLWEIG model developed by the Göteborg Urban Climate Group (Lindberg and Grimmond, 2010; Lindberg et al, 2008; Lindberg and Thorsson, 2009). The Rayman model is a human thermal energy balance model. SOLWEIG is a 3D radiation balance model which calculates radiation load on a human body in a complex 3D environment. SOLWEIG models both thermal and shortwave radiation components, with a limitation that it cannot simulate overhanging roofs. However, Thorsson et al (2011) showed that SOLWEIG presents reasonable T mrt simulation results for the urban canyon microclimates in Goteborg, Sweden in Goteborg has a similar climate with the Netherlands, according to updated Köppen-Geiger climate classification (Kottek et al, 2006). In order to get a better overview of spatial distribution of T mrt within a given street and orientation, we also chose SOLWEIG for this study to simulate the spatial variations of T mrt and 3D fluxes of longand short-wave radiation in complex urban settings. In this paper, we compared real survey data with the SOLWEIG simulation results to test the suitability for urban areas of Rotterdam with the configured albedo value (0.15), surface emissivity (0.95) and buildings emissivity (0.90), the same setting as Thorsson et al (2011) used. Measured T mrt values in Rotterdam were taken from the mobile-equipment survey conducted by the Meteorology and Air Quality Research Group at Wageningen Uni-

4 254 Q. DAI AND M. A. SCHNABEL versity on 6th August, 2009 (Heusinkveld et al, 2010). Meanwhile, Digital Elevation Model (DEM) data of Rotterdam were employed to simulate T mrt by running SOLWEIG. We found that there is significant correlation (0.84) between the simulation and real survey data (Dai et al, 2012a). Subsequently we consider SOLWEIG as suitable for simulating T mrt in Rotterdam. 3. Building Model The Digital Elevation Model (DEM) is used for the building input in ESRI ArcGIS 10. The typical height of buildings in Rotterdam is around 15 meters, and the typical width of streets is generally around 25 meters in reality, varying between 5 and 45 meters. The typical h/w is therefore around 0.6. In the modelling we take 15 meters to be the height of buildings (h), and consider each street to be 300 meters in length (Figure 1). The width (w) of the street varies in incremental steps of 5 meters from 5 to 45 meters, same as the model employed by Herrmann and Matzarakis (Herrmann and Matzarakis, 2012). In the one-day simulation, we rotate the urban canyon in 90 steps, namely 0 and 90. To overcome the influence of boundary conditions, we only consider the 100-meter area in the middle of the streets in the simulations. For each street three separate zones are distinguished and differentiated, that is, the centre zone and the two side zones (left pavement and right pavement). The definition of these zones here is to consider the central 3/5 part of the street as the centre zone and the rest 2/5 as the two side pavement zones. For example, in the left panel of Figure 1 the actual width of the centre zone pointed out is 9 meters, while the side zone is 3 meters in width. Figure 1. Plans of the idealized urban streets scenario: showing study area in the middle of the streets, and the center-/side-zones of each street

5 MEAN RADIANT TEMPERATURE AND SOLAR ANGLE Methodology In this paper we are concerned with the impact on T mrt from the three different street zones, as well as different orientations, and different months. Regarding the impact of different months, there is one complexity that the difference comes in two ways: the change in the solar angle, and the variation of meteorological factors, e.g., humidity, air temperature, global radiation, etc. The meteorological factors could be accessed via SOLWEIG. To isolate the effects of solar angle difference for our study, we therefore take the following approach to exclude impact from meteorological factors. The meteorological conditions of July 16th are used to represent the average meteorological environment across all the five months, since this date lies in the middle of the five-month duration. This representative meteorological setup is then combined with the different solar angles on the 16 th of May through September as model input to simulate the impact of different months in terms of solar angles. The T mrt at different hours of the day are then averaged over the set of chosen h/w values to reduce possible bias and error. 5. Results Figure 2 to Figure 11 plot the evolution of T mrt during the day for the three street zones, conditional on different solar angles and orientations. As the software produces unsmooth output at four a.m. and seven p.m., we focus on the time between five a.m. and 7 p.m. Figure 2 & 3. T mrt evolution in the three street zones on in North-South orientation & T mrt evolution in the three street zones on in East-West orientation

6 256 Q. DAI AND M. A. SCHNABEL Figure 4 & 5. T mrt evolution in the three street zones on in North-South orientation & T mrt evolution in the three street zones on in East-West orientation Figure 6 & 7. T mrt evolution in the three street zones on in North-South orientation & T mrt evolution in the three street zones on in East-West orientation Figure 8 & 9. T mrt evolution in the three street zones on in North-South orientation & T mrt evolution in the three street zones on in East-West orientation

7 MEAN RADIANT TEMPERATURE AND SOLAR ANGLE 257 Figure 10 & 11. T mrt evolution in the three street zones on in North-South orientation & T mrt evolution in the three street zones on in East-West orientation Regarding the impact of the solar angle, which achieves a highest value in June and is mostly declining in the period concerned, in both orientations we can notice that the T mrt in general is going in a downward trend as we move from May to September, consistent with the decreasing solar angle. Therefore it is evidence that larger solar angle is correlated with higher T mrt. The three different street zones also have different T mrt profiles as shown in the curves. Especially for the zero-degree orientation, the right pavement is significantly cooler than the other two street zones. This is caused by the sun shade in this orientation and demonstrates that dividing the street into three zones provides genuinely more insight into the actual thermal comfort of pedestrians. Cross-comparing the results for zero-degree and ninety-degree orientations, we can see that the T mrt for the latter case is consistently higher than the former, especially for the right pavement. It is caused by the reduced effectiveness of the sun shade. 6. Conclusion We simulated the T mrt along the day of three different street zones under two orientations in five months from May to September of a year for typical setting of Rotterdam. The effect of variations in meteorological factors is removed by using the same representative meteorological conditions across all different days for simulation input. T mrt results averaged over different h/w configurations reveal influence from all the factors considered. The street zones and the orientation together influence the sun shading effect, which is modulated by the difference in solar angles across the time duration studied. Only by accounting for all these factors collectively in an integrative manner could the thermal comfort be accurately evaluated and measures and subsequently be taken to improve the thermal environment for human beings.

8 258 Q. DAI AND M. A. SCHNABEL With the solar angle factor added in we can see more clearly the underlying reasons for T mrt distributions and come up with suggestions for thermal comfort considerations. Based on the simulation results, we learn that in the period considered during which the solar angle is mostly high and the climate is mostly hot, the thermal comfort is significantly affected by the street orientations a lot for specific street zones, which is due to the sun shadows as confirmed by the variation of T mrt values with the solar angle. What is important in planning and design would then be to provide the best shading for the most important area. This discovery by using more dimensions of parameters to reveal underlying structure between other parameters is a useful direction to explore in future investigations too. With regard to the architecture domain specifically, the implications of this study can be detailed on both the individual building and the congregate building group level. For each individual building, the influence on the surrounding thermal comfort has to be taken into consideration in the design and the actual solar angle distribution at the building site is necessary input from the beginning phase. For a group of buildings as a whole, the results about the building sun shade on the pedestrian zones can be extrapolated to the sun shade on other buildings as well and it would be interesting to consider and investigate the interactions between the buildings. The solar angle and shade from other buildings would impact the natural heating of both the exterior and interior of the buildings, affecting the thermal comfort of pedestrians and building residents as well. Careful simulations and concerns have to be involved to improve the thermal comfort in the urban context for all the related people from the architectural point of view. References Ali-Toudert, F., Djenane, M., Bensalem, R. and Mayer, H.: 2005, Outdoor thermal comfort in the old desert city of Beni-Isguen, Algeria, Climate Research, 28(3), Ali-Toudert, F. and Mayer, H.: 2006, Numerical study on the effects of aspect ratio and orientation of an urban street canyon on outdoor thermal comfort in hot and dry climate, Building and Environment, 41(2), Bourbia, F. and Awbi, H. B.: 2004, Building cluster and shading in urban canyon for hot dry climate: Part 2: Shading simulations, Renewable Energy, 29(2), Bruse, M. and Fleer, H.: 1998, Simulating surface plant air interactions inside urban environments with a three dimensional numerical model, Environmental Modelling & Software, 13(3 4), Dai, Q. and Schnabel, M. A.: 2013a, Pedestrian Thermal Comfort in Relation to Street Pedestrian Zones with Different Orientations, in R. Stouffs, P. H. T. Janssen, S. Roudavski and B. Tunçer (eds.), Open Systems: Proceedings of the 18th International Conference of the Association of Computer-Aided Architectural Design Research in Asia, CAADRIA 2013, 10pgs.

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