Study of Urban Heat Islands Using Different Urban Canopy Models and Identification Methods

Climate data for building simulations with urban heat island effects and nature-based solutions

As cities face a changing climate, buildings will be subjected to increasing energy demand, heat stress, thermal comfort issues, and decreased service life. Therefore, evaluating building performance under climate change is essential for maintaining sustainable and resilient communities. To better prepare building simulation climate data with urban effects, a computationally efficient approach is used to generate "urbanized" data, where the city's unique signature is obtained through the dynamic Weather Research and Forecasting model for the Ottawa, Canada region. We demonstrate this process using existing climate data and extend it to prepare projections for scenarios where nature-based solutions, such as increased greenery and albedo, were implemented. The data consists of several 31-year time series of climate variables such as temperature, humidity, wind speed and direction, pressure, cloud cover, and precipitation over different global warming thresholds. Such a dataset allows building practitioners to evaluate building performance under both historical and future climate conditions, as well as to evaluate the impacts of nature-based solutions to mitigate future climate change risks.

Identification of SUHI in Urban Areas by Remote Sensing Data and Mitigation Hypothesis through Solar Reflective Materials

The urban heat island (UHI) is an increasingly widespread phenomenon of concern to the wellbeing and the health of populations living in urban environments. The SUHI (Surface UHI) is directly related to UHI and influences its extension and intensity. Satellite images in the thermal infrared spectral region can be used to identify and study the SUHI. In this work, Landsat 8 TIR images were acquired to study the SUHI of a medium-sized municipality of the Po valley in the northern part of Italy. An additional Worldview 3 satellite image was used to classify the study area and retrieve the surface albedo of building roofs. Using the Local Climate Zone approach, existing roof materials were virtually replaced by solar reflective materials, and the mitigation potential of the SUHI and the UHI was quantified. This virtual scenario shows a decrease in the overheating of building roofs with respect to the ambient temperature of up to 33% compared to the current situation in the industrial areas. Focusing on UHI intensity, the air temperature decrease could be up to 0.5 °C.

Benefit Evaluation Model of Prefabricated Buildings in Seasonally Frozen Regions

In order to effectively develop the benefit evaluation model of prefabricated houses in seasonal frozen soil areas, and improve the comprehensive benefits of prefabricated buildings, this paper proposes a life cycle benefit evaluation model for prefabricated buildings in seasonally frozen regions. According to the climatic characteristics of the area, the impact of the seasonally frozen regions is listed as an evaluation index in the construction stage for comprehensive analysis. The 16 indicators that affect the comprehensive benefits of prefabricated buildings are grouped by the nearest neighbor element analysis method. Fuzzy cluster analysis and analytic hierarchy process are used to filter out the most influential index group to calculate the index weight. Then the model proposed in this paper is compared with the existing model to test the validity of the model. The research results show that research and development costs weight is 0.23, design cost weight is 0.10, construction cost weight is 0.22, resource consumption weight is 0.25, building demolition cost weight is 0.04, and seasonal freezing effect weight is 0.16. The calculation result passed the consistency test and the expert scoring result conformed to the normal distribution, which proved the accuracy of the conclusion. It is proposed that the calculation result of the comprehensive benefit score of the model is 1.8% lower than the previous results, which proves the validity of the model. The model can speed up the efficiency of comprehensive benefit evaluation of prefabricated buildings thereby improving the development level of prefabricated buildings.