Estimation of Mean Radiant Temperature in Urban Canyons Using Google Street View: A Case Study on Seoul

Extreme heat exposure has severe negative impacts on humans, and the issue is exacerbated by climate change. Estimating spatial heat stress such as mean radiant temperature (MRT) is currently difficult to apply at city scale. This study constructed a method for estimating the MRT of street canyons using Google Street View (GSV) images and investigated its large-scale spatial patterns at street level. We used image segmentation using deep learning to calculate the view factor (VF) and project panorama into fisheye images. We calculated sun paths to estimate MRT using panorama images from Google Street View. This paper shows that regression analysis can be used to validate between estimated short-wave, long-wave radiation and the measurement data at seven field measurements in the clear-sky (0.97 and 0.77, respectively). Additionally, we compared the calculated MRT and land surface temperature (LST) from Landsat 8 on a city scale. As a result of investigating spatial patterns of MRT in Seoul, South Korea, we found that a high MRT of street canyons (>59.4 °C) is mainly distributed in open space areas and compact low-rise density buildings where the sky view factor is 0.6–1.0 and the building view factor (BVF) is 0.35–0.5, or west-east oriented street canyons with an SVF of 0.3–0.55. However, high-density buildings (BVF: 0.4–0.6) or high-density tree areas (Tree View Factor, TVF: 0.6–0.99) showed low MRT (<47.6). The mapped MRT results had a similar spatial distribution to the LST; however, the MRT was lower than the LST in low tree density or low-rise high-density building areas. The method proposed in this study is suitable for a complex urban environment consisting of buildings, trees, and streets. This will help decision makers understand spatial patterns of heat stress at the street level.

An IoT measurement solution for continuous indoor environmental quality monitoring for buildings renovation

The measurement of Indoor Environmental Quality (IEQ) requires the acquisition of multiple quantities regarding thermal comfort and indoor air quality. The IEQ monitoring is essential to investigate the building’s performance, especially when renovation is needed to improve energy efficiency and occupants’ well-being. Thus, IEQ data should be acquired for long periods inside occupied buildings, but traditional measurement solutions could not be adequate. This paper presents the development and application of a non-intrusive and scalable IoT sensing solution for continuous IEQ measurement in occupied buildings during the renovation process. The solution is composed of an IR scanner for mean radiant temperature measurement and a desk node with environmental sensors (air temperature, relative humidity, CO2, PMs). The integration with a BIM-based renovation approach was developed to automatically retrieve building’s data required for sensor configuration and KPIs calculation. The system was installed in a nursery located in Poland to support the renovation process. IEQ performance measured before the intervention revealed issues related to radiant temperature and air quality. Using measured data, interventions were realized to improve the envelope insulation and the occupant’s behaviour. Results from post-renovation measurements showed the IEQ improvement achieved, demonstrating the impact of the sensing solution.

The importance of the calculation of angle factors to determine the mean radiant temperature in temperate climate zone: A university office building case

Thermal comfort depends on four environmental (air velocity, relative humidity, air temperature, mean radiant temperature) and two personal (clothing insulation and metabolic rate) parameters. Among all parameters, the mean radiant temperature (tr) is the most problematic variable in thermal comfort studies due to its complexity. Measurement methods, calculation methods and assumptions are mostly used to obtain the tr. Researchers mainly prefer to obtain the tr via measurement methods or assumptions due to their easiness compared to the calculation methods. Besides, some researchers use constant values of angle factors in calculation methods. However, using constant values is not proper for every indoor environment, and it causes wrong estimations in the tr and thus the thermal comfort. This paper gives the importance of calculation of angle factors, with an example of a university office building in temperate climate zone, according to the ISO 7726. The angle factors of the room were calculated for a seated occupant from the centre of gravity in three different locations and compared with the constant angle factors. The results indicate that a significant difference (MAPE of 1.02) was found in the tr values, which were obtained by calculation of constant values of angle factors.

A Relationship between Micro-Meteorological and Personal Variables of Outdoor Thermal Comfort: A Case Study in Kitakyushu, Japan

Outdoor thermal comfort is an important indicator to create a quality and livable environment. This study examines a relationship between micro-meteorological and personal variables of outdoor thermal comfort conditions in an urban park. The data collection of outdoor thermal comfort is carried out using two methods in combination: micro-meteorological measurement and questionnaire survey. This finding shows that most of the respondents were comfortable with the thermal, wind, and humidity condition. The acceptability and satisfaction level of thermal comfort were positive. The most significant micro-meteorological variable for the physiologically equivalent temperature (PET) value is mean radiant temperature (Tmrt). As the Tmrt value is influenced by how much shading is produced from the presence of vegetation or buildings around the measurement location, this finding shows that the shadow was very important to the thermal comfort conditions in the Green Park Kitakyushu. The most influential micro-meteorological variable for the three different personal variables (TSV, WFSV, and HSV) is air temperature. The strongest relationship among the four variables is between TSV and PET. The findings will be the basis for the city authorities in preparing regional development plans, especially those related to the planning of city parks or tourist attractions.

Analysis of ceiling type to produce energy efficient residential buildings: case study on housing design of puskim pu-bandung city

Many houses that exist on this earth. Therefore, it is necessary to have tactical and intelligent thinking in designing a home. Many things are rarely considered related to the effects of the design of building elements when related to the temperature or the energy produced. Existing background regarding efforts to reach a comfortable temperature can not only be solved in terms of mechanical systems, but the architectural approach can help and provide a comfortable effect for its inhabitants. This research was conducted to determine the level of thermal comfort or temperature in the room of a residential design that would be related to the size of energy consumption by applying several alternative designs or ceiling forms. This type of research is research using simulation methods through a computer model. The results showed the use of ceiling type Vaulted Ceiling was able to increase the Surface Inside Temperature value by 3 ° C when compared to the type of drop ceiling. The Mean Radiant Temperature value when using the ceiling vault type rises 0.6 ° C and on the acquisition of Operative, Temperature rises 0.3 ° C. The use of insulation material on the roof can significantly reduce Mean Radiant Temperature and Operative Temperature at 1.7 ° C at Mean Radiant Temperature and 0.8 ° C at Operative Temperature. Seeing the results of the simulation in this study, the recommended ceiling type is to use the drop ceiling type because it is quite capable of keeping the temperature in the room not too high so that thermal comfort can be achieved. However, if you want to apply a ceiling design with a model or type of drop ceiling, it is better to use additional insulation material so that the heat transmission temperature is not too high in the room.

Experimental Investigation of Adaptive Thermal Comfort in French Healthcare Buildings

The thermal comfort requirements of disabled people in healthcare buildings are an important research topic that concerns a specific population with medical conditions impacted by the indoor environment. This paper experimentally investigated adaptive thermal comfort in buildings belonging to the Association of Parents of Disabled Children, located in the city of Troyes, France, during the winter season. Thermal comfort was evaluated using subjective measurements and objective physical parameters. The thermal sensations of respondents were determined by questionnaires adapted to their disability. Indoor environmental parameters such as relative humidity, mean radiant temperature, air temperature, and air velocity were measured using a thermal microclimate station during winter in February and March 2020. The main results indicated a strong correlation between operative temperature, predicted mean vote, and adaptive predicted mean vote, with the adaptive temperature estimated at around 21.65 °C. These findings highlighted the need to propose an adaptive thermal comfort strategy. Thus, a new adaptive model of the predicted mean vote was proposed and discussed, with a focus on the relationship between patient sensations and the thermal environment.

An investigation on the radiant heat balance for different urban tissues in Mediterranean climate: a case study

The outdoor radiant field is a key aspect to determine outdoor comfort conditions for humans, especially in urban areas. In order to unveil the dependence of the radiant field on the features of the urban fabrics, this study analyses the space distribution of the Mean Radiant Temperature (TMRT) and the radiant field in various urban tissues of the city of Catania (Italy) in a typical Mediterranean climate. The study is based on simulations through the Solar and LongWave Environmental Irradiance Geometry model (SOLWEIG) implemented in UMEP. Results show that the worst conditions occur in areas with moderately deep urban canyons, abundant impervious surfaces and lack of vegetation: here, the TMRT can easily reach 78 °C while in more than 80% of the area it exceeds 60 °C. By modelling the time trends of the shortwave and longwave radiant heat fluxes perceived by a pedestrian, it has been possible to observe that the highest contribution to the outdoor radiant field comes from the downward solar irradiance. However, the downward and upward longwave radiant flux closely follows: this suggests the importance of providing shading rather than using highly reflective surfaces that can exacerbate heat stress by means of the increased reflected shortwave radiation.

Simplified Model for Analyzing Shortwave Solar Effects on Indoor Thermal Comfort

Shortwave solar irradiance through building windows may have significant impacts on indoor thermal comfort, especially in near-window zones. Such effects change with intensity and spectral variations of the solar irradiance incident on building windows, which is related to the day of the year, time of day, orientation and dimension of the window, and atmospheric conditions. To assess the effects on thermal comfort, we derived a variable - mean radiant temperature delta based on a proposed spectrally-resolved method to represent the quantity of shortwave solar irradiance incident on occupants and be incorporated into PMV (predicted mean votes)-based thermal comfort models. By characterizing the variations of the calculated PMV values under different solar conditions, the influencing factors to indoor thermal comfort by shortwave solar irradiance were obtained and analyzed. Last, upon a series of parametric settings and numerical analysis, simplified statistical regression models were also established to directly predict spectrally-resolved mean radiant temperature delta and PMV values. This could be convenient and extensively to estimate the solar effects on indoor thermal comfort within the near-window zones.

Modelling mean radiant temperature in outdoor environments: contrasting the approaches of different simulation tools

Global warming and increasing urbanization are expected to threaten public health in cities, by increasing the heat stress perceived by the inhabitants. Outdoor thermal comfort conditions are influenced by the material and the geometric features of the surrounding urban fabric at both the urban and building scales. In built environments, performance-aware design choices related to street paving or building façade can enhance outdoor thermal comfort in their surroundings. Reliable estimations of outdoor thermal comfort conditions are required to evaluate and control the micro-bioclimatic influences of different design choices. The mean radiant temperature is the physical variable that has the greatest influence on outdoor thermal comfort conditions during summertime. Since its calculation is complex, the available simulation tools employ different approaches and assumptions to estimate it, and potential users need to be aware of their capabilities and simplifications. This research compares the calculation procedures and assumptions of different performance simulation tools (i.e. ENVI-met, TRNSYS, Ladybug/Honeybee, CitySim, and SOLENE-microclimat) to predict the mean radiant temperature in outdoor spaces, based on the available information in the scientific literature. Their ability to account for different radiative components in both the longwave and shortwave spectra is summarized, and practical information regarding the degree of interoperability with the modelling environments and the level of geometrical detail of the virtual model supported by the tools is provided. This work aims to help potential users in the selection of the most appropriate performance tool, based on the requirement of their projects.

Development and initial tests of an urban comfort monitoring system

The paper presents a newly developed low-cost measurement system for outdoor comfort monitoring. The solution is based on IoT (Internet of Things) technologies and is cloud-connected. The system is able to collect physical environment data, and includes a movable GPS monitoring station as well as the subjective thermal sensation of pedestrians via a devoted app. The cloud interface promptly elaborates the received data to calculate outdoor thermal comfort indices such as UTCI (Universal Thermal Climate Index), MRT (mean radiant temperature), and ET (effective temperature). The system is conceived for supporting both fixed and traveling measurements, and to support correlation studies between monitored environmental variables and personal comfort sensations to promote the local adaptation of comfort indices. Results from early testing are also reported.