反照率(炼金术)
环境科学
城市热岛
大气科学
城市气候
亚热带
平流
中尺度气象学
城市气候学
热舒适性
气象学
气候学
城市规划
地理
土木工程
地质学
渔业
表演艺术
艺术
工程类
物理
热力学
生物
艺术史
作者
Afifa Mohammed,Ansar Khan,M. Santamouris
标识
DOI:10.1016/j.buildenv.2021.108276
摘要
Extreme urban heat alongside higher ambient temperatures in urban areas causes serious energy, comfort, health and environmental problems. The implementation of urban heat mitigation techniques can significantly reduce urban temperatures and counterbalance the impact of extreme urban heat. This study assesses the potential cooling ability of modified urban albedo strategies through the implementation of reflective and super reflective materials, as well as the global climatic impacts on a subtropical desert urban environment in Dubai, UAE. Three scenarios using low, average and high albedo modifications are designed and evaluated in parallel to a reference scenario. A physically-based mesoscale urban modeling system is used to assess the thermal and meteorological impacts of the albedo modifications during both the summer and winter seasons at a city scale. The reduction of ambient temperature during the peak of a summer day (14:00 LT) is shown to be 0.6 °C, 1.4 °C and 2.6 °C when urban albedo is increased by 0.20, 0.45 and 0.60 respectively. The winter cooling penalty ranges between 0.6 °C and 1.1 °C for the different albedo scenarios. The increase of the urban albedo also significantly reduces the planetary boundary layer (PBL) depth due to the loss of sensible heat and decreases the intensity of the convective mixing and advection flows from the desert to the city, improving the mitigation potential of the reflective materials; however this increases the risk of a higher pollutants concentration. A much higher mitigation potential is observed for the high-density parts of the city when compared to that of the low-density parts of the city. Irrespective of linear function in the drop of ambient temperature and changing fraction of global albedo, our results reported that the cooling potential of reflective materials is highly influenced by the climate, landscape, and urban characteristics of the cities.
科研通智能强力驱动
Strongly Powered by AbleSci AI