Investigating the impacts of shaded outdoor spaces on thermal adaptation and cognitive performance of university students in classroom environments.

Shading strategies are effective means to reduce urban risk factors such as the Urban Heat Island (UHI) effect. The influence of shaded outdoor spaces on university students' thermal adaptability and cognitive performance is limited researched. The study aims at evaluating the effect of shaded outdoor spaces upon thermal comfort; and, linking such results upon university students' cognitive performance in a classroom environment with natural ventilation. A case study was conducted with students the ages of 19-22 at Bilkent University in Ankara, during the mid-season in October.The quantitative microclimatic conditions of the university campus's unshaded/shaded areas and indoor studios were obtained through Physiologically Equivalent Temperature (PET) index. The qualitative evaluation was undertaken by the adaptive model and thermal comfort survey. D2 test of attention was conducted to measure cognitive performance of students.This study revealed that the shade may increase thermal adaptation with the lowest mean PET of 18.7°C, while the highest mean PET of 33.2°C was obtained in sun-exposed space. Also, experiencing shaded outdoor space contributed to an improvement in concentration performance (CP) of students resulting in the mean CP score of 182.8, while those with sun-exposed outdoor space experience had the mean CP score of 167.6 within studios.

Urban heat island data by local weather types in Lisbon metropolitan area based on Copernicus climate variables dataset for European cities.

Here we provide Urban Heat Island (UHI) by local weather types (LWT) maps for the Lisbon Metropolitan Area (LMA). These maps were produced from the Copernicus Land Monitoring Service climate variables dataset that contains hourly air temperature raster data for 100 European cities (2008-2017), namely Lisbon and part of its metropolitan area. Over 61000 maps (2008-2014) were extracted in NetCDF format and processed in geographic-information-systems (GIS). An urban mask was created from the recently updated Local Climate Zones (LCZ) classification for this area and a cell of the LCZ class "Low Plants" (non-urban) was chosen to calculate the temperature difference. UHI intensity was estimated using an R script. The outputs of this process were divided by thermal seasons and LWT. Ultimately, average UHI intensity by LWT was estimated. Average UHI according to meteorological conditions is available in GeoTIFF raster format (Appendix 1), with a spatial resolution of 100 × 100m pixels, as well as hourly average UHI for each LWT (Appendix 2 to 16). This data may provide valuable information for urban planners, designers and architects in the process of pinpointing recurrent hot and cool spots/neighborhoods in the city and its heating/cooling degrees. Moreover, these maps may contribute to a construction of an early warning system that anticipates which weather conditions we might expect an significant increase in thermal discomfort on those critical areas in the city.