Microclimate in the built environment is known as a local phenomenon that affects the well-being of people and can also be an index for urban liveability. It was proven that outdoor comfort conditions in cities and public spaces are a driver for how frequently people use and occupy public spaces [1]. Public spaces with optimum comfort levels enhance the quality of cities by encouraging cycling and walking, attracting a higher number of people to public spaces and providing opportunities for business and tourism, which can promote the economic sustainability of cities [2],[3]. Microclimate studies are one of the domains where physical, spatial and temporal fields merge to define design concepts that address climate change, resource availability, environmental degradation and energy consumption issues [4]. The complexity of urban contexts demands advanced techniques and methodologies. Microclimate studies are often performed with the aid of computational modelling, digital tools and simulation techniques [5].
However, the human dimension is generally underestimated in such studies. To bridge this gap, a methodology named
‘Climatewalks’ was developed at TU Munich. This is a Human- Cantered approach to understand local microclimate at a pedestrian level as a way to facilitate design interventions to increase comfort levels and to prefigure how to mitigate extreme climatic conditions. From this perspective, Climatewalks focus on humans as a source of information that is captured by methods including measurements, simulations, and data mining [6],[7].
CLIMATE WALKS TO EVALUATE
Figure 4
Mobile micro-meteorological sensors collecting data in Malaga, Photo by Loredana Bruma
CLIMATEWALKS IN MALAGA
During a workshop in Malaga in Autumn 2018, students gathered measurements by mobile micro-meteorological sensors (Figure 4) that were selected for the measuring of relevant environmental parameters to investigate thermal comfort, including wind speed, air temperature, humidity, globe temperature and solar radiation to calculate the universal thermal climate index (UTCI) [8]. A thermal comfort questionnaire within a designed app was also used for collecting data about subjective perceptions and thermal sensations. A measurement backpack was carried while walking through outdoor spaces to collect data for all of the selected routes. The routes were pre-selected so that the measurements could be completed within 90 minutes. Another factor was the skin temperature of people, which was measured with an infrared thermal camera, which was adapted to the cell phone’s camera (Figure 5).
Data visualization done by using Rhinoceros, Grasshopper and the plugin of Ladybug Tools, allowed for importing maps for each route, and a series of scripts in Python code were developed in order to combine data from CSV (Comma Separated Values) files.
Overlaying all collected data (wind speed, relative humidity, air temperature, global temperature and UTCI) with the actual routes on a two-dimensional plane (2d) ,as in Figure 6, which shows the path.
Figure 5
The framework of the Climate Walks method to monitor environmental, psychological and physiological parameters with the aid of a georeferenced system.
Tskin UTCI TS Polin. (Tskin) Polin. (UTCI) Polin. (TS) 32
31 30 29 28 27 26 25 24 23 22
1.5
1
0.5
16:45:00 16:55:00 17:05:00 17:15:00 17:25:00 17:35:00 17:45:00 17:55:00 18:05:00 18:05:00 0
PE (MWh‧1/y) gas - fired boiler
heat pump gas - fired boiler heat pump gas - fired boiler heat pump gas - fired boiler heat pump gas - fired boiler heat pump
CR_2CR_1GR_2GR_1existing
summer winter
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
+1%
-9%
≈0%
-6%
-8%
-10%
-3%
-7%
PE (MWh‧1/y)
summer winter
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
+1%
-9%
≈0%
-6%
-8%
-10%
-3%
-7%
16:30 17:45
16:45
17:00
17:15 17:30
°C
UTCI 36 34 32 30 28 26 24 22 20
In order to investigate the temporal and spatial effects of outdoor comfort on people, the data is segmented into 15 minutes intervals as shown in Figure 6. The results show a continuous increase of UTCI over the walk due to increase in solar radiation (changing from the overcast sky to sunny) and by shifting from densified and shaded areas to open areas where solar radiation is not filtered. This increasing trend from 23 °C to 31 °C within 1.5 hours corresponds to the thermal sensation votes measured by the apps, which moved from Neutral to Warm sensation for the subjects. This trend also validates the UTCI results, in which a temperature above 26 °C is categorized as ‘moderate heat stress’
as shown in Figure 6.
The skin temperatures values (Tskin) in Figure 7 follow an increasing trend within the first 15 minutes of the experiment up to 30 degrees, but they drop later for the next 30 minutes. This trend ascends with the increase of UTCI relatively. Choi and Loftness [9] argued that skin temperature is a suitable indicator of an individual’s thermal sensation in a thermally uniform environment.
However, in this study, temperature of the forehead was recorded at each point of the walking route, but this measurement may not be representative of human physiological response to the thermal environment.
As a summary, the Climatewalks experiment setup for outdoor comfort studies has the potential to find answers to the challenges of thermal comfort perception in more complex outdoor environments and to formulate indications for designers, city planners and policy makers in high resolution and on a micro scale.
Figure 6
An example of a Climate Walk performed in Malaga. UTCI map indicating every 15 minutes over the walking route. The variable UTCI shows how to open areas are more exposed to direct solar radiation, while shaded densified areas are protected, thus positively influencing the UTCI.
Green areas offer comfort when compared to the densified areas, where cars and concrete characterise the landscape
Figure 7
Graphical correlation of UTCI, skin temperature (Tskin) and thermal sensation (TS). The continuous polylines average the point in time values to offer more clarity of interpretation of patterns
REFERENCES
[1] D. Santucci, A. Chokhachian, T. Auer, Impact of environmental quality in outdoor spaces:
dependency study between outdoor comfort and people´s presence., S.ARCH 2017, Get It Published Verlag, Hong Kong, 2017, pp. 511.1-511.10.
[2] A. Chokhachian, D. Santucci, T. Auer, A Human-Centered Approach to Enhance Urban Resilience, Implications and Application to Improve Outdoor Comfort in Dense Urban Spaces, Buildings 7(4) (2017) 113.
[3] M. Nikolopoulou, N. Baker, K. Steemers, Thermal comfort in outdoor urban spaces:
understanding the human parameter, Solar Energy 70(3) (2001) 227-235.
[4] N. Gaitani, M. Santamouris, C. Cartalis, I. Pappas, F. Xyrafi, E. Mastrapostoli, P. Karahaliou, C. Efthymiou, Microclimatic analysis as a prerequisite for sustainable urbanisation:
Application for an urban regeneration project for a medium-size city in the greater urban agglomeration of Athens, Greece, Sustainable Cities and Society 13 (2014) 230-236.
[5] K. Perini, A. Chokhachian, S. Dong, T. Auer, Modeling and simulating urban outdoor comfort:
Coupling ENVI-Met and TRNSYS by grasshopper, Energy and Buildings 152 (2017) 373-384.
[6] A. Chokhachian, K. Ka-Lun Lau, K. Perini, T. Auer, Sensing transient outdoor comfort: A georeferenced method to monitor and map microclimate, Journal of Building Engineering 20 (2018) 94-104.
[7] A.S. Nouman, A. Chokhachian, D. Santucci, T. Auer, Prototyping of Environmental Kit for Georeferenced Transient Outdoor Comfort Assessment, ISPRS International Journal of Geo-Information 8(2) (2019) 76.
[8] G. Jendritzky, R. de Dear, G. Havenith, UTCI—Why another thermal index?, International Journal of Biometeorology 56(3) (2012) 421-428.
[9] J.-H. Choi, V. Loftness, Investigation of human body skin temperatures as a bio-signal to indicate overall thermal sensations, Building and Environment 58 (2012) 258-269.