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A comfortable thermal environment is extremely important for the enjoyment of outdoor spaces. The relationship among microclimate, thermal sensation, and human behavior is expected to provide guidelines and implications for outdoor space design and planning practice. Given that, this study aimed at a better understanding of outdoor thermal comfort and activities in the residential community in a humid subtropical area of China. This study counted the number of people staying at the outdoor space, recorded physical measurements, and collected questionnaire surveys to determine the thermal comfort and activities of the outdoor space. Analysis results confirmed that the thermal experience and expectation existed and changed people’s perceptions about the outdoor thermal environment in different seasons. The 90% acceptable physiologically equivalent temperature (PET) range affected by the local climate and thermal adaptation was 18.1–31.1 °C. The residents adapted to the outdoor spaces through adjustment of clothing, activity spaces and activity times in different seasons. These findings shed light on the optimal design of outdoor spaces for increasing the utilization rate. Sunny and shady subspaces should be considered to provide residents with more opportunities to interact with the environment for different seasons, thus improving their thermal comfort and the usage rate. [ABSTRACT FROM AUTHOR]

[Display omitted] • An architect-friendly rapid evaluation for the adaptive facades (AFs) is presented. • The method eliminates uncertainty in AFs selection during the early design stage. • Optimal hourly values are obtained via co-simulation with EnergyPlus and Python. • AFs strategy is characterized by climate and optimal values using a white-box model. • U-value strategy reduces consumption by up to 6.6%, SHGC&τ v strategy by 17.0%. Adaptive façades (AFs) are technologies with great potential to reduce energy consumption by changing their properties to adapt to variable climatic conditions. This paper proposes an architect-friendly computational approach for the exploration of strategies for the selection of the thermal parameters of AFs based on co-simulation and white-box models in the early design stage. In the case study, the proposed approach is applied to obtain strategies with variable U -values and variable SHGC& τ v values for high-rise office buildings in seven cities. The energy consumption analysis of five scenarios is carried out to investigate the energy-saving potential of the AFs and to propose design strategies for transparent façades, and the accuracy of the approach is verified. It is concluded that the highest match of the variable U- value strategy with the optimal hourly U- values is 85.3%, while that between the variable SHGC& τ v strategy and the optimal hourly SHGC& τ v values is only 71.0%. Regarding the energy-saving potential, the highest energy-saving rate is 6.6% for the variable U- value strategy. However, for the variable SHGC& τ v strategy, the highest energy-saving rate is greater than 10.8% in seven cities. The difference between the energy-saving rates of the proposed strategy and the optimal hourly strategy is less than 0.4%, and it is 0.8% for the AFs with variable U- values and variable SHGC& τ v values, respectively. This architect-friendly approach represents a widely used design strategy for AFs that can directly provide recommended thermal parameters based on climatic conditions, and is an effective way to demonstrate the potential application of AFs in the early design stage. [ABSTRACT FROM AUTHOR]

Highlights • An equation for estimating the daily UHII max is evaluated with a dataset of 658 days. • Robust and satisfactory estimation of the UHII max under various weather conditions. • A method to apply the equation to building energy simulation is developed and validated. • Implying that the equation and the method have the potential to be applicable to other cities. Abstract The reliable estimation of the urban heat island intensity (UHII) within an urban canopy will benefit a number of fields of research such as urban design, public health, and building energy performance. A diagnostic equation for estimating the daily maximum UHII (UHII max), which is based on routine meteorological data and basic urban properties, was extensively tested with the long-term observations from the metropolis of Nanjing, China. The field measurement has been carried out based on the Local Climate Zone (LCZ) scheme, which is a standardized classification protocol for urban temperature studies. The temperature data set of 658 days collected from six different LCZ classes was used for testing. The results show that the diagnostic equation produced a robust and satisfactory estimation of the daily UHII max under various weather conditions. The overall performance of the equation for Nanjing, that has a root mean squared error (RMSE) of 0.95°C and a median absolute error (MEAE) of 0.60°C, closely approximates its performance for the 14 cities in northwestern Europe (RMSE = 0.91°C, MEAE = 0.58°C). The results also imply that the equation has the potential to be applicable to other cities. Another attempt in this study was to develop a method to apply the diagnostic equation to building energy simulations (BES). The hourly heat island intensities were derived from the estimated UHII max based on the typical diurnal pattern of UHII evolution. An apartment was modeled with the BES program EnergyPlus to examine the validity of the proposed method. Using the modeled and measured temperature data as the inputs in the EnergyPlus simulations, the annual, monthly, and hourly energy demands for cooling and heating were investigated and compared. For all the six LCZ sites except the large low-rise case (LCZ 8), the impacts of the heat island effects at the neighborhood scale on building energy performance were reasonably evaluated with the method. The limitations and perspectives of the equation and its application to BES have also been discussed. [ABSTRACT FROM AUTHOR]

Monitoring buildings' heat loss and quickly discovering high energy-consuming buildings in a certain area is of great significance for urban management departments to propose urban governance and management measures from the perspective of global optimization. Developing a 3D-infrared (3D-IR) model of a building or a complex created with infrared thermograph (IRT) obtained by unmanned aerial vehicle (UAV) technologies would greatly contribute to a comprehensive observation on the thermal performance of a study objective. In this paper, a procedure for high energy-consuming building screen based on the 3D infrared (IR) models of multiple buildings is proposed and demonstrated as an effective approach for regional evaluation comparing with measured heating energy data provided by the local municipal department. Firstly, the 3D-IR model of multiple buildings is established, where the single building models are built based on UAV-IRT technology respectively, and the modelling condition as well as the temperature-color mapping relationship of each building is unified. Secondly, the measuring schemes and the evaluation method of the building thermal performance based on the 3D-IR model is proposed. Thirdly, the energy-consuming performance of five buildings in Jining, a city in northern China, is measured and analyzed by using the above-mentioned methods. Finally, the proposed evaluation method of the building performance is applied to evaluate the tested buildings. By referencing to measured heat energy data, the proposed method can be taken as an efficient and reasonably accurate screen method. [ABSTRACT FROM AUTHOR]