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Article

Quantifying the Relationship Between Mean Radiant Temperature and Indoor Air Temperature Across Building Orientations in Hot and Dry Steppe Climates

by
Salar Salah Muhy Al-Din
1,
Nazgol Hafizi
2 and
Hasim Altan
3,*
1
Department of Interior Architecture and Environmental Design, Arkin University of Creative Arts and Design, 99320 Kyrenia, Cyprus
2
Department of Urban Design and Landscape Architecture, Arkin University of Creative Arts and Design, 99320 Kyrenia, Cyprus
3
Department of Architectural Engineering, United Arab Emirates University, Al Ain 15551, United Arab Emirates
*
Author to whom correspondence should be addressed.
Atmosphere 2025, 16(10), 1132; https://doi.org/10.3390/atmos16101132
Submission received: 9 August 2025 / Revised: 19 September 2025 / Accepted: 22 September 2025 / Published: 26 September 2025
(This article belongs to the Special Issue Interactions Between Indoor Environmental Quality, Occupant Behaviour, and Building Performance Under a Changing Climate)
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Abstract

This study aims to create environmentally comfortable building designs in hot and dry steppe climates using more effective approaches. The purpose of this study is to assess the relationship between mean radiant temperature (MRT) and indoor air temperature (Tia), taking into account the orientation of buildings, for better building thermal performance. For this purpose, residential buildings with different orientations were selected in the study region ‘Garmian—northern Iraq’, and their thermal performance was evaluated. The results show how MRT contributes to the buildings’ thermal comfort. The outcomes of this research provide innovative empirical quantification of the correlation of MRT-Tia, as the regression coefficient (β) represents the rate of change in Tia per unit increase in MRT and ranges by orientation in the study area. The findings demonstrate that north-facing buildings buffer radiant heat gain (β~0.52), resulting in a 0.5 °C increase in indoor air temperature for each 1 °C rise in MRT. Moreover, west orientation delivers promising winter passive heating (MRT up to 22 °C and indoor air temperature up to 22.8 °C with a β of ~0.82). However, south-facing buildings perform poorly in the winter, with low MRT and a weak β (~0.44), contrasting with passive solar design strategies that favor south-facing buildings in the northern hemisphere. Furthermore, in the summer, the MRT is always higher than Tia, while it is lower in winter, indicating poor envelope and fenestration thermal insulation properties, which lead to excessive energy usage to maintain thermal comfort. Finally, the study suggests the novel quantified MRT-Tia mathematical correlation responds to the orientations for such climates, offering both diagnostic and predictive tools for thermal comfort performance optimization. This study is the first to empirically quantify orientation-specific MRT–Tia relationships in BSh climates, offering a novel diagnostic tool for sustainable building design. This study involved field observations in 36 residential row houses across four orientations. Key environmental and personal variables measured included mean radiant temperature (MRT), indoor air temperature (Tia), air velocity, relative humidity, metabolic rate, and clothing insulation.

Graphical Abstract

1. Introduction

Forty percent of the world’s energy usage comes from buildings, and it is increasing by 2.2% annually [1,2]. Controlling environmental issues through effective environmental design to lower energy consumption and optimize indoor thermal comfort conditions is essential due to climate change and environmental crises [3]. Therefore, it is important to estimate building energy demand to enhance energy performance, achieve energy conservation, and minimize environmental effects. In the same context, thermal comfort accounts for 50% of energy usage within buildings during the post-occupancy phase [4]. Thus, one of the fundamental requirements in the building’s environmental design process is thermal comfort prediction within the building, which guarantees end users’ satisfaction [5]. Moreover, several factors, including building orientation, affect the energy consumption of residential buildings [6]. Estimating thermal comfort conditions in buildings is a challenging task due to the need to evaluate multiple parameters [7]. However, there are subjective methods to evaluate thermal comfort through the thermal sensation of the occupants [8,9] and objective methods through direct observation of environmental and personal factors [10,11,12]. An objective method of determining thermal comfort is determined by several factors, including the amount of radiative and convective thermal interaction between the human body and its environment. The convective element of this thermal interaction is predominantly influenced by air temperature and humidity, whereas the radiative part is primarily influenced by surrounding surface temperatures [11,12]. Unlike prior research that primarily focused on air temperature, this study uniquely integrates MRT as a predictive variable, offering a more comprehensive understanding of thermal comfort in hot and dry steppe climates.
This study will follow the objective method; therefore, the PMV (Predicted Mean Vote) and PPD (Predicted Percentage of Dissatisfied) have been applied. This method is one of the most popular and commonly used objective methods, particularly in air conditioning and mixed-mode buildings that are typical of those found in the study region [13]. In this method, several factors must be taken into account, such as environmental factors like air temperature, air velocity, mean radiant temperature, and relative humidity, in addition to human factors like occupant activity levels and clothing selections [14]. One of the key meteorological factors affecting human energy equilibrium and thermal comfort is the MRT, which sums up all short- and long-wavelength radiation fluxes (both direct and reflected) to which the body of humans is exposed [15]. In terms of objective evaluation of thermal comfort, MRT is as significant as air temperature, but it has not been incorporated into the control of building systems [16]. The research conducted by [17], utilizing the ASHRAE RP-884 database, quantified the inaccuracies in comfort level assessment stemming from the oversimplified assumption that mean radiant temperature is equivalent to air temperature. The results demonstrated erroneous thermal sensation evaluations for 644 individuals, resulting in a 6.7% inaccuracy in comfort levels on a global scale. A significant challenge in assessing thermal comfort in post-occupancy buildings is that existing heating/cooling systems depend completely on the temperature of the air for feedback control input. Typically, thermostats or temperature sensors that respond to air temperature are used to control heating and air conditioning [16]. This approach could not be proper for scenarios where the air temperature and MRT vary significantly, such as in a room with a large single-glazed aperture during the wintertime. Building environmental control systems, both active and passive, consists of diverse shading, cooling, and radiant heating mechanisms that regulate both air temperature and short- and long-wave radiation. Nonetheless, these systems presently exhibit inadequate tracking of the radiant temperature and rely on the temperature of the air for operational control [18]. The neglect of mean radiant temperature by HVAC designers and researchers is due to the complication involved in its measurement, as it cannot be directly assessed. However, indicators that respond to both air and radiant temperatures are important.
Moreover, MRT is an important environmental factor that affects the building’s thermal performance and consequently energy usage [19]. It is an important component of architectural thermal design that influences occupant comfort and energy efficiency [20]. The study area is called Garmian, located in southeastern Kurdistan, northern Iraq. It is distinguished by a dry and warm climate, defined as (BSh) according to the Köppen–Geiger categorization [21]. Thermal comfort has been the subject of several investigations into comparable climates [22]; a study indicated that a hybrid ventilation system (both passive and active) is essential for dwellings in Sulayimani city, Kurdistan-Iraq, during the warm months, particularly in July and August, to improve thermal comfort. [3,4] conducted research on dwellings in hot and dry steppe (BSh) regions, specifically in Kurdistan of Iraq. The study places a strong emphasis on determining thermally neutral air temperature levels that facilitate efficient consumption of energy while also guaranteeing the thermal comfort of the residents. The results indicate that the ideal interior temperature levels for both the warmest and coldest seasons are 29.2 °C and 19.4 °C, respectively. Furthermore, there are differences in acceptable temperatures depending on orientation, with a greater variation in temperature in the eastern orientation during the warmest season (ranging from 26.6 °C to 29.2 °C). Additionally, the impact of spatial layout on thermal comfort was investigated in multi-story housing developments located in Duhok, Kurdistan, Iraq, which has a hot and semi-arid climate. After simulating the PET index, which gauges physiologically equivalent temperatures, it was determined that the spatial arrangement of residents’ thermal comfort in open spaces represented the importance of urban design features [23]. Additionally, [24] evaluated how building orientation affected thermal comfort in the dry steppe (BSh) climate of the Kurdistan region in Iraq in row houses using a combination of the thermal sensation vote (TSV) and the Predicted Mean Vote (PMV) model. This study suggested that houses facing east could provide the best thermal comfort year-round. In the same context, a study on the impact of courtyards on residents’ thermal comfort was also conducted on traditional houses in Baghdad, Iraq, which has a hot and dry climate. The results indicated that courtyards could potentially provide up to 38% of comfortable hours [25]. These background specifics are essential, as they support the justification for the study’s inquiry into the influence of building direction on thermal performance in hot and dry steppe (BSh) climates using a more accurate methodology. Despite improvements in energy conservation and thermal conditions extensively examined with several methods, our research specifically concentrated on analyzing MRT beyond air temperature in individual buildings relative to their orientations. Therefore, this study focuses on addressing the relationship between air temperature as a dependent factor and MRT as an independent and significant factor for determining thermal performance, which is commonly disregarded or simplified in standard thermal comfort models.
This study aims to use more realistic methods to design more environmentally efficient buildings in hot and dry steppe (BSh) climates. The study emphasizes the importance of mean radiant temperature (MRT) in evaluating and enhancing thermal comfort in buildings with various orientations, especially in the BSh-subtropical steppe climate found within the hot and arid regions of Kurdistan, Iraq. The study presents a data-driven strategy for orientation-specific and thermally responsive architecture design solutions by utilizing statistical analysis and examining seasonal MRT fluctuations. This study expands on established air temperature measures, offering fresh knowledge about how MRT affects occupant comfort and energy efficiency. The findings are informing the creation of more adaptable and sustainable building designs. However, a major obstacle has been the absence of MRT measurements to assess the thermal condition of the buildings in hot and dry steppe (BSh) climates, particularly when taking into account the buildings’ orientation. The lack of measurements has limited the control of radiant systems to air temperature monitoring and prevented them from fully increasing operational efficiency. Thus, the study seeks to address the following questions: (1) What is the role of MRT in optimizing thermal comfort in residential buildings with different orientations in hot and dry steppe (BSh) climates? (2) How can the correlation between Tia and MRT as environmental factors guide the designers and engineers for a better environmentally reoptimizing design scenario? (3) How can we assess heating/cooling passive design and start optimizing Tia and MRT interaction as a tool when evaluating thermal comfort? (4) What are the suggestions and recommendations for future housing design in this climate, considering the outcome of the current study?

2. Materials and Methods

2.1. Research Aim and Objectives

This study aims to empirically investigate the influence of building orientation on indoor thermal comfort in hot and dry steppe (BSh) climates by quantifying the relationship between MRT and Tia. Through field-based observations and statistical analysis of residential row houses in Garmian, Iraq, the research seeks to develop orientation-specific MRT–Tia models that can inform passive design strategies and enhance energy efficiency and occupant comfort in climate-responsive architecture. Figure 1 also includes a methodology flowchart that visually summarizes the research process, from selecting the case study to collecting and analyzing data.

2.2. Climatic Characteristics of the Study Area

A hot and dry steppe (BSh) climate is generally situated on the outskirts of genuine deserts in low-latitude semi-arid steppe areas, often adjacent to areas characterized by a tropical savanna or a humid subtropical climate. These climates often feature hot, sometimes extremely hot summers and mild to cool winters with little or no precipitation. Steppe (BSh) climate temperatures are most common along the edges of subtropical deserts. Africa, Australia, South Asia, Europe, and North and South America commonly host hot and dry steppe (BSh) climates [21]. ‘Garmian’ is the study area with the BSh type of climate, and it is a small region located in the Kurdistan of Iraq (in the southeast) [26]. A ribbon shape between the Turkish border and Iran’s border in the northeast of Iraq can be categorized as a BSh climate. The region is adjacent to the west and southwest by BWh—a hot and dry desert climate, as seen in Figure 2.
The solar irradiance potential of the study region can be assessed by the yearly solar radiation, with an average of 6318.83 MJ/m2/year, equivalent to 1755.23 kWh/m2/year, or 4.81 kWh/m2/day [27,28]. Therefore, the solar radiation in this climate significantly influences the thermal performance of the buildings. The temperature in the study area occasionally reaches 50° Celsius during the warm season. July experiences the highest temperatures, while January records the lowest, when the temperatures sometimes fall below 0 °C. The continental influence is more prominent here, impacting both annual and diurnal temperature variations [28,29].

2.3. Methodology

This study considered the role of building envelope components—walls, windows, and ceilings—in influencing MRT and Tia. The thermal performance of these components was evaluated based on their material properties, surface finishes, and exposure to solar radiation. All selected buildings were constructed using concrete blocks with plastered finishes and flat reinforced concrete roofs. The external walls were light-colored to reflect solar radiation, and the windows were double-glazed with a window-to-wall ratio (WWR) of approximately 20%. Fixed external shading devices were installed above windows to mitigate direct solar gain.
The surface materials of walls and ceilings significantly affect the radiative heat exchange between the building envelope and indoor spaces. High thermal mass materials like concrete can absorb and store heat during the day and release it at night, thereby moderating indoor temperature fluctuations. The glazing ratio and type of glass used in windows influence both solar heat gain and heat loss. Double-glazed windows reduce conductive heat transfer and help maintain thermal comfort. Shading devices, such as overhangs and fins, reduce the exposure of windows to direct sunlight, thereby lowering the MRT and preventing overheating during the summer. These architectural features were consistently applied across all case study buildings to ensure uniformity in evaluating orientation-specific thermal performance.
Residential buildings constitute a large portion of the dwelling sector, which by 2030 will account for over 67% of global building sector energy consumption [4]. In the Kurdistan Region of Iraq, residential buildings studied in this research account for 85.84% of all buildings [17]. Within the scope of this study, almost 1% of people in the study area live in apartments, whereas more than 98% of people live in houses with different typologies, according to the [30]. Therefore, this study concentrated on row houses, the predominant dwellings in the study region, to provide a more precise assessment of the heating and cooling levels in these buildings. Consequently, thirty-six air-conditioned row houses have been designated as case study buildings in the Garmian area, representing 65.7% of the predominant dwelling types in the study area [31]. The case studies were arranged in four primary directions: north-facing, east-facing, south-facing, and west-facing buildings, with nine residences in each direction. The chosen group of buildings followed a strict selection procedure based on specific criteria. The requirements included an even distribution of the case study houses across four main orientations, ensuring similar microclimatic characteristics across all construction sites. Additionally, the building materials, outside surface color, structural age, architectural shape, and design, in addition to the prototype, must be similar, as seen in Figure 3.
Additionally, a unit’s thermal comfort rating is influenced by the number of residents in each house, as more people generate heat from their bodies to the surroundings, raising the temperature inside the building [32]. Therefore, we selected only buildings with three to four occupants. Additionally, several criteria were taken into account due to the personal factor in the PMV-PPD assessment, such as gender balance and similarity in the ages of residents. These factors influence individual elements like attire, metabolic levels, and activities, which ultimately impact the evaluation process [12]. Consequently, these factors limited the total number of case studies. Gathering data from the case study houses was carried out daily in the hot season of July and August and the cold season of January and February. The time of observations was between 10:00 am and 3:00 pm. Descriptive data for case study houses were gathered through direct observations and recorded documents like drawings. During the data-gathering phase, the PMV/PPD approach was used, which involved field observations. For each direction, five distinct observations were made in different areas of the residence. To ensure the impact of solar radiation throughout the day, a total of 360 tests were carried out for PMV-PPD evaluation, and 180 field-based observations were made within the selected houses in the warm season. Another 180 observations were made during the winter at comparable times of day (between 10:00 and 15:00). Each test or observation requires identifying or measuring six parameters (globe temperature, air temperature, air velocity, air humidity, metabolic rate, and clothing insulation level) [10]. The observations encompassed several areas within each row house, such as the living room, kitchen, guest room, and master bedroom, and in the second bedroom (see Figure 4), a total of 30 observations were conducted at 5 different locations within each house, resulting in 1080 observations for each season.

2.4. Tools, Equipment, and Methods for Observation and Evaluation

The study investigated the effect of buildings’ orientation on MRT and evaluated the difference among the orientations. Furthermore, it identified the relationships between MRT and Tia and their impact on interior thermal comfort to assess the potential of the buildings’ thermal performance for their orientations.
The Thermal Comfort Tool—Center for the Built Environment (CBE) 2020—Version: 2.5.6 [33] serves as a highly professional and user-friendly online resource for studies of this nature. The Thermal Comfort Tool—Center for the Built Environment was used to measure the empirical variables necessary for calculating PM studies in this research. In each observation, the following parameters were measured:
  • Inside Globe Temperature (Gti): Globe temperature, measured with a 40 mm diameter globe, as specified by the ASHRAE-55 standard diameter, is 150 mm and must be taken more than one meter from the exterior walls. It should be noted that employing different sizes resulted in slightly varied MRT results. The variation was because the globe temperature instrument’s ball size diameter decreased from 150 mm to 40 mm. Nevertheless, it had no noticeable effect on the PMV/PDD projections’ ultimate outcomes [34,35]. It is important to mention that when the air velocity inside the building exceeds 0.12 m/s, the size difference between the black globe thermometer and standard thermometers becomes significant [36]; however, this air speed was not observed inside the buildings. Measurements were taken in the center of each room, away from direct solar exposure, to ensure consistency.
  • Inside Air Temperature (Tia) refers to the building’s interior air temperature as defined by the CBE Tool’s psychrometric approach. This method uses the dry-bulb temperature and relative humidity to determine the thermal comfort zones on a psychrometric chart.
  • Inside Air Velocity (IAV): the air speed in the houses was observed in meters per second using an anemometer.
  • Inside Relative Humidity (Rhi): the building’s interior relative humidity.
  • The rate of metabolism (Met), or the activity level, is determined according to ASHRAE-55 and the area studied.
  • Clothing insulation (Clo): It was considered to range from 0.5 (Clo) in summer to 1.03 (Clo) in winter, based on the site survey and ASHRAE-55 guidelines [12,31]. See Table 1.
In addition, exploratory data analysis and inferential statistical analysis were used to summarize the data’s main characteristics visually and make inferences or predictions based on collected data. A one-way ANOVA was applied to verify the accuracy of the results and identify the confidence among the groups. For a 95% confidence threshold, the significance level was at p = 0.05. The PMV values for each orientation within the dwellings were derived from a thermal comfort evaluation method that considered both environmental and human aspects across nine groups.
Table 2 shows that in winter, there were variations in the average PMV/PPD across different orientations. The mean PMV/PPD in the north-facing houses indicated the presence of ‘cold’-rated areas in both bedrooms, with the highest average PPD recorded in these bedrooms at 98%. The kitchens in this orientation exhibited the lowest average PPD, identified as the most comfortable areas, characterized by temperature neutrality. Nonetheless, the situation in the eastern houses indicated that the kitchens were the most restful areas, characterized by a ‘neutral’ ambiance and the lowest average PPD of ‘9%’. The bedrooms within these buildings were deemed the most unpleasant, categorized as ‘cool,’ with the maximum PPD recorded at 67% in unused bedrooms. The southern set showed that the bedrooms were the coolest areas, categorized as ‘cool,’ with a maximum PPD of 91%. The kitchens were the most relaxing, with an average PMV rating of “neutral” and the lowest PPD of 5%. This orientation is cooler than the eastern orientation, according to the precise PMV-PPD outcomes presented in Table 2. The western buildings, like the eastern-oriented buildings, were evaluated to be ‘cool’ in the bedrooms, with a higher PPD of 89%. With a mean PPD of 8%, the living rooms and kitchens were assessed as “neutral,” making them the most comfortable spaces. The scenario of evaluation revealed that the western-oriented set of houses is the most comfortable during the winter, while the northern orientation is the most uncomfortable. But the performance of the eastern and southern ones was equal. The group of eastern-oriented houses registered lower PPD than south-facing buildings. As illustrated in Figure 5, people generally perceived the eastern houses to be cozier than the southern ones. However, in the selected buildings during winter, the bedrooms showed increased discomfort and a greater need for heating energy due to insufficient direct solar radiation [32].
On the other hand, depending on the orientation, the kitchens continuously offered higher thermal comfort in all directions. This was explained by the internal production of heat from culinary activities and exposure to direct solar radiation. Except for the guest rooms in the buildings facing north, the living rooms and guest rooms also provided less discomfort, mostly because they were directly exposed to sunlight. Other areas served as buffer regions, encircling the living room’s central location. Due to its central location and proximity to other areas, the living room was generally comfortable during the two seasons. It deserves to be mentioned that during the summer, thermal comfort was maintained because of limiting exposure to direct solar radiation, as seen in Figure 4. This study emphasizes that the buffer zone solution is a crucial passive design approach for architects and designers to guarantee better thermal performance and efficient energy consumption in the research area. However, the outcome of thermal comfort in various oriented houses during both winter and summer indicates that there is a notable variation in thermal comfort within the buildings. An inferential statistical approach confirms this fact. The one-way ANOVA findings for summer reveal a high F-ratio of 44.0036, indicating that the differences among the PMV means across the four orientations surpass the variation within each orientation group. Moreover, the p-value is less than 0.00001, which is below 0.05, indicating significant differences in PMV values across the four main directions. This indicates that the orientation of the building significantly impacts thermal comfort, and the null hypothesis was accepted for this season. However, the value of the F-ratio was 5.73871, and the p-value was 0.000908 and less than 0.05 in the winter, indicating a significant difference in PMV value among the orientations. Hence, the null hypothesis was once more accepted in the winter season.

3. Results and Discussion

3.1. The Impact of Building Orientation on Thermal Comfort and Energy Efficiency

The mental state that determines the degree of satisfaction with the surrounding environment is called thermal comfort [37]. The building’s orientation influences the quantity of solar heat it receives, therefore significantly impacting its thermal performance [38]. Hence, building orientation is an important component of passive design methods in dry (BSh) areas, influencing the ability to control sunlight and wind on the building [39,40]. During the summer or warm seasons, buildings with a western orientation tend to be warmer during the day, receive less shade, and are more exposed to sunlight; this behavior is similar to southern facades, while north-oriented buildings collect fewer sunrays [38]. As a result, the building’s orientation has a significant impact on heating and cooling loads; hence, it affects thermal comfort and energy consumption [38]. Certain regions, like arid or cold climates, mandate that buildings align with the solar ecliptic [32]. In humid regions, where air movement primarily provides comfort, buildings must align themselves with the predominant winds [32]. Consequently, the main building facade is desired to be northern-oriented (north–south), where solar radiation in the warm season barely enters via the facades and apertures [41,42]. A study was carried out on a typical residential building in Singapore, and the findings revealed that the U-value of façade components for both the north and south must be less than 2.5 W/m2K, and the west and east sides should be less than 2.5 W/m2K [43]. These foundations are broad, with occasional exceptions based on various climatic and geographical factors. As a result, examining how orientation affects thermal comfort is critical in achieving optimal environmental design and energy efficiency within buildings.

3.2. Thermal Comfort and Energy Efficiency in Residential Buildings and the Role of MRT

Residential buildings are recognized as the main place for rest. The thermal comfort level in dwellings significantly affects the mental and physical well-being of the occupants [44]. Therefore, dwellings usually offer a larger variety of comfortable or acceptable indoor thermal conditions than workplaces [45], educational [46,47], or medical buildings [48,49]. These differences may be due to differing needs for thermal comfort, less predictable activities, and greater opportunities to adjust to the current thermal environment [50]. Moreover, different factors could play roles in the thermal performance of residential buildings. Research has indicated that building style in dry steppe (BSh) regions may have a considerable impact on building thermal performance [51]. Residents of traditional houses, for example, have various levels of thermal comfort compared to individuals who reside in contemporary residences because they engage in unique thermal adaptation behaviors [52]. Certain regions, characterized by either cold or warm and dry climates, necessitate the orientation of buildings in accordance with the solar ecliptic. Buildings in humid areas must be oriented toward the prevalent winds to provide comfort [32]. Consequently, the main building facade is primarily oriented north–south, allowing sun rays to enter slightly through the facades and openings during the warm season, while sun ray accessibility increases in winter when the sun’s altitude is lower [53]. The same research found that the number of shading facades and the shading-to-shading facade ratio had a substantial impact on solar radiation in buildings. The study focused on residential buildings in cold climates, encompassing various shapes and typologies. [54] conducted a study on single-family dwellings in five distinct areas across the United States. The study evaluated the building shape, WWR, and orientation to be essential elements for optimization.
MRT is defined as the uniform temperature of an ideal spherical surface surrounding the subject (with emissivity ε = 1) that would produce a net radiation energy exchange equivalent to that of the actual, complex radiative environment [55,56]. In other words, it is the constant temperature of a hypothetical space where radiant heat transfer from an individual’s body is equivalent to radiant heat transfer that occurs in a real, irregular space [54]. The significance of MRT becomes evident when evaluating the human bioclimate in heat stress assessments. Thermal indices such as the PT (Perceived Temperature) [55], the PMV [19], the PET (Physiologically Equivalent Temperature) [56,57], and the UTCI (Universal Thermal Climate Index) [58] must be calculated using MRT. Research [59,60,61,62,63,64,65,66,67,68,69,70] has demonstrated several approaches for measuring and modeling MRT. A globe thermometer (GT) is commonly used to measure the MRT [62,63,64]. The globe thermometer, which is approached in this study, is ideal for interior measurements but has also been used outdoors [65]. The mean radiant temperature of all adjacent surfaces affects an individual’s thermal comfort in a given location. Hence, it facilitates the examination of radiative exchanges between an individual and their surroundings [66]. According to a recent study, assessing MRT inside the buildings is essential for optimizing building design in terms of energy efficiency and thermal comfort [19]. MRT is recognized as the fundamental key for architectural and constructive innovations because it explains the radiant interaction between surfaces and the human body, thereby indicating the qualities of the space geometry and building elements [67]. Since the MRT depends on the temperature of adjacent surfaces that radiate heat towards the occupants as well as the air temperature, it is one of the most difficult of the six thermal comfort indicators to evaluate [68]. In addition to improving comfort, MRT-based management has the added benefit of significantly lowering energy usage, especially in radiant systems like floor heating and ceiling cooling [69]. Radiant cooling and heating systems have gained popularity in recent years for high-performance and net-zero energy building design because they provide greater energy efficiency or lower operating expenses than air-based systems [70,71,72]. Radiant systems are designed to achieve MRT in inner spaces by raising or lowering the surface temperature. Subsequently, heated or cooled surfaces cause convection. To attain maximum efficiency, these systems require accurate control based on real-time MRT measurements [73].
Nevertheless, MRT can play a significant role in evaluating thermal conditions and the effectiveness of passive strategies in buildings. The low MRT compared with the air temperature inside the buildings in summer indicates that the building receives less direct solar radiation. However, such a decrease may lead to negative consequences in winter, as it could increase the energy required for heating [74]. Moreover, this variation could result from adequate insulation of the building envelope, which means a favorable passive design strategy. In the same context, if the MRT is higher than the indoor air temperature in summer, this means that the building is facing high direct solar radiation, which results in overheating the building and extra energy required for the cooling system [24].
As previously stated, 360 findings were collected using the PMV-PPD method to evaluate thermal comfort inside the dwellings in the research area, 180 in each season (summer and winter). Each set of nine houses, oriented in a specific direction, had a total of forty-five observations, with five observations recorded for each house. According to the central limit theorem’s essential principles, a sample size of at least 30 is required for a statistical analysis to be considered credible [33].
Assessing the difference between MRT and Tia, as well as analyzing thermal comfort with PMV-PPD, is crucial for understanding indoor thermal comfort conditions in buildings. Correlation regression was applied to test the strength of the relationship between MRT and Tia inside the buildings in each orientation. This analysis aims to clarify the potential thermal performance of the buildings and identify effective strategies for enhancing energy efficiency and thermal comfort by examining how strongly MRT influences Tia in each orientation.
Furthermore, as previously mentioned, the PMV-PPD was calculated using the CBE Thermal Comfort Tool. This is to understand the effects of changing the MRT in various orientations on the thermal comfort evaluation. Additionally, a one-way ANOVA was conducted to statistically compare the PMV-PPD results across the four orientations and determine if there is a significant difference among them.

3.3. Findings on the Differences Between MRT and Tia

We show the comparative analysis of MRT and Tia across different building orientations and seasons. Table 2 illustrates the relationship between mean radiant temperature (MRT) and indoor air temperature (Tia) inside buildings, based on their orientation during the warm and cold seasons.
We conducted a linear regression analysis of MRT and Tia across building orientations, where the regression coefficients indicate the rate of change in Tia per unit increase in MRT, serving as a measure of thermal responsiveness. Higher β values reflect stronger coupling between outdoor radiant heat and indoor air temperature. This section illustrates the correlation between mean radiant temperature (MRT) and indoor air temperature (Tia), highlighting the strength and nature of their relationship across different orientations. All regression coefficients were tested for significance, and p-values are reported in Table 3. Coefficients with p < 0.05 are considered statistically significant. Regression coefficients (β) indicate the sensitivity of indoor air temperature to changes in mean radiant temperature across orientations (see Table 3).
As shown in Table 3, the regression coefficient (β) for south-facing units was highest (β = 0.42), indicating a stronger thermal response to changes in MRT. This suggests that design interventions targeting solar control in south-facing façades may yield the greatest impact on indoor thermal regulation.
Hence, for the north-faced structures, the summer results exhibit the lowest MRT (24.8–30.7 °C). The equation Tia = 0.52386 MRT + 12.011 demonstrates the weakest interaction between MRT and Tia—regression coefficient (β) 0.52386—indicating strong buffering capacity against radiant gain. As a result, the indoor air temperature rises slowly with an increase in MRT, maintaining a cooler indoor environment under high solar radiation incidence. Winter results demonstrate low MRT combined with high β (approx. 0.96) according to the regression equation, which indicates weak passive solar benefit; there is insufficient solar radiation heat gain to raise the air temperature inside the buildings in an effective way. Therefore, these buildings are insufficient for passive heating during the winter. In the eastern-oriented buildings, summer measurements indicate a mean radiant temperature (MRT) ranging from 26.9 to 32.6 °C, with a β value of approximately 1.0 as determined by the linear regression equation. This data demonstrates that indoor air temperature closely tracks rising MRT, causing rapid warming of indoor air during the direct incidence of solar radiation, especially in the morning. This high sensitivity presents a moderate thermal risk without early-day shading elements. The winter results demonstrated moderate passive heating potentials with MRT 18.3–21.0 °C and a β of around 0.73. Some radiation heat gain increases indoor air temperature, but not effectively enough to be considered a primary heating source. Therefore, in east-oriented buildings, solar radiation can contribute to winter warmth as a supportive factor. Regarding south-directed buildings, in the summer, MRT ranges between 27.6 and 32.7 °C, and the MRT-Tia β is near 0.89, signifying that indoor air temperature closely follows increases in MRT, indicating high daytime solar radiation heat load and emphasizing external shading strategies to control solar radiation incidence. However, in winter, despite MRT levels of 15.7–20.3 °C, the low β (approx. 0.44) implies inefficient transfer of radiation heat into indoor air—passive gains do not effectively elevate indoor air temperature. The last orientation is Western; the MRT peaks at 28.1–34.2 °C, the highest among the four orientations, with a β of almost 0.88 according to the regression equation, as seen in Table 2. The results show strong solar gain and interior air temperature closely tracking surface heat, making it one of the most challenging orientations for cooling. In winter, MRT ranges from 18.4 to 22.0 °C with a linear regression β around 0.82, indicating effective radiative heat gain during the winter low sun path, making the west exposure the highest contributor to passive heating design. Therefore, it is facilitating effective passive radiant heat gain, making it the best passive heating performer among the four tested orientations.

3.4. Thermal Comfort Findings

The analysis of thermal comfort conditions by PMV-PPD is crucial to evaluate the effect of the orientation and the changes of solar radiation incident on the thermal comfort situation in each direction. Therefore, the evaluation was conducted during the summer and winter. In the summer, the mean thermal evaluation estimate using the PMV-PPD approach varied depending on direction. As seen in Table 4, in the summer, north-facing structures were cooler. The slightly warm situation in the kitchen was the highest evaluation of the structures. In this direction, the bedrooms showed the coolest and were reported as slightly cool during the observation, with the greatest PPD of 44% and the smallest of 5%. Buildings facing west were the warmest, with the guestroom and kitchen inside the buildings being the hottest areas, according to the PMV estimations for these buildings. The guestrooms in the western group of buildings had the greatest PPD record in any orientation during the summer, at 74%. In master bedrooms, the minimum PPD in this direction was 6%. The southerly oriented residences experienced the second warmest area and were close to the results of the buildings facing west, and marginally cooler than them. In the southern orientation, the PMV methods indicate warmer thermal conditions in guestrooms and kitchens, classified as warm. The master bedrooms and living rooms were found to be the coolest spaces and were categorized as ‘neutral’. The maximum PPD was 73% in the guest rooms, while the minimum was 5% in the master bedrooms. The east-facing houses revealed cooler conditions than western- and southern-oriented buildings. The observations demonstrated ‘warm’ thermal conditions in the kitchens, with a peak PPD of 55%, but the cooler areas, including the master bedrooms, guest rooms, and living rooms, were classified as ‘neutral.’ The master bedrooms had the lowest PPD at 6%. However, based on data obtained by PMV-PPD in the warmest season, the western direction was the worst for thermal comfort within the houses in the research region, while the northern direction was the greatest.
Regarding thermal performance throughout the warm season, the current study found that bedrooms (constantly utilized) and living rooms offered the highest comfort level because they have limited access to the direct solar radiation incidence, and they were the most used zones. See Figure 6.
In the same context, the guestroom and kitchen exhibited the lowest comfort level because they were contiguous to the outside. This is caused by the direct incidence of solar radiation on the building through its windows. It is worth noting that the rise in the kitchen’s indoor heat may return partially to the cooking activities, which could make a double impact in warming the space. Table 4 shows average summer and winter PMV/PPD evaluation for the set of houses in each direction.

3.5. Discussion

Moreover, the discussion of MRT and Tia dynamics must account for the influence of building envelope components. The thermal behavior of walls, windows, and ceilings has an important influence on the indoor thermal environment. For instance, walls with high thermal mass and reflective finishes can buffer against rapid temperature changes by absorbing and re-radiating heat more gradually. This effect is particularly beneficial in hot and dry climates, where diurnal temperature swings are significant.
Windows, especially those with high WWR or poor insulation, can become major sources of heat gain or loss. In this study, the use of double-glazed windows with external shading helped reduce the impact of solar radiation on MRT, especially in east- and west-facing orientations. The shading devices were most effective in mitigating afternoon overheating in west-facing buildings, which otherwise exhibited the highest MRT values. Ceilings, particularly those exposed to direct solar radiation, also contribute to elevated MRT if not properly insulated. The flat concrete roofs in the study buildings were designed to minimize heat transfer through the roof by using reflective coatings and insulation layers.
These findings emphasize the value of integrating envelope design strategies—such as optimized glazing ratios, thermal mass utilization, and effective shading—into passive design approaches. By doing so, designers can better control MRT and Tia, leading to improved thermal comfort and reduced energy consumption.
The empirical investigation in hot semi-arid (BSh) climate yields orientation-specific quantification of MRT and Tia, elucidating how façade orientation dictates radiant-air coupling and indoor thermal performance. PMV-PPD evaluation results demonstrated significant differences in thermal comfort conditions among different orientations by applying inferential statistical tools using one-way ANOVA. In summer, north-facing rooms delivered the lowest MRT (24.8–30.7 °C) and exhibited a shadow MRT-Tia β (0.524), resulting in Tia only ranging from 24.3 to 28.2 °C, thus demonstrating significant buffering against radiant heat peaks. This phenomenon explains why north-facing buildings’ results were cooler than other orientations during the PMV-PPD evaluation in the summer, as seen in Table 4. In these buildings, the kitchen’s slightly warm situation received the highest thermal evaluation, while only in this orientation were the bedrooms reported as ‘slightly cool’ during the test. The lower range of PPD among the four orientations was registered in this orientation (5 to 44%). In contrast, the east orientation exhibited a mean radiant temperature (MRT) ranging from 26.9 to 32.6 °C, with a β value of approximately 0.961, which translates nearly 1:1 to a Tia level of 25.9–31.0 °C and indicates potential for morning overheating. Therefore, it was discovered that the east-facing homes were warmer than the north-facing ones. They were cooler than structures facing south and west, though. The orientation recorded ‘warm’ thermal conditions in the kitchens, with a high PPD of 55%, and experienced warmer indoor temperatures than the northern-oriented buildings. Other areas were categorized as ‘neutral,’ with the lowest PPD being 6%. The south orientation recorded a mean radiant temperature (MRT) ranging from 27.6 to 32.7 °C and a β value of 0.891, resulting in an indoor air temperature (Tia) between 26.9 and 31.6 °C; this strong coupling indicates high solar gain with limited thermal inertia. This phenomenon explains why, after buildings facing west, the southerly oriented dwellings were experiencing the second-warmest regions. The PMV techniques indicate that the guestrooms and kitchens are experiencing warmer thermal conditions, categorized as warm, with a maximum PPD of 73% observed in the guestrooms. The direct exposure of the south-facing guestroom and kitchen to solar radiation from the facades and windows is the cause of this trend. The living room and master bedroom were called “neutral” because they were used all the time and not directly exposed to sunlight. West orientation peaked in MRT (28.1–34.2 °C) with a β of 0.877, pushing Tia up to 31.8 °C and making it the most extreme for afternoon overheating. As a result, due to a significant solar heating load in this orientation, buildings facing west were the warmest of the four. The PMV estimates the guest room as the warmest space, with PMV equal to 1.92 and the highest PPD record of 74% during the summer. See Table 3. These findings challenge conventional assumptions in passive solar design by demonstrating that west-facing buildings, rather than south-facing ones, offer superior passive heating in BSh climates.
In winter, North’s MRT of 16.5–19.5 °C is the lowest among the four orientations in this season because of the limited direct solar radiation incidence on these buildings [42,75]. The regression equation showed a β of 0.961, yielding a Tia of 17.1–21.0 °C and high sensitivity, but low absolute gain results in limited passive heating. Therefore, the mean PMV/PPD in these residences was determined to be the coldest assessment, with cold-rated zones in both bedrooms, where the highest mean PPD of 98% was noted among all building types. Only the kitchen had a comfortable situation with a ‘neutral’ rating because of interior heat gain from the daily cooking activities. The evaluation demonstrates the importance of direct solar heat gain inside the buildings, especially from the fenestration, to maintain thermal comfort conditions inside the buildings in the study region. For east-facing groups of buildings, with MRT 18.3–21.0 °C and β 0.727, the study achieved a temperature index (Tia) ranging from 19.4 to 22.0 °C, indicating a moderate benefit during winter. The PMV-PPD data for the eastern residences shows that the kitchens are the most comfortable spaces, exhibiting a neutral atmosphere and the lowest average PPD of 9%, while the guest rooms have a Tia classified as ‘slightly cool’, despite their exposure to direct morning radiation. Nevertheless, the bedrooms in these dwellings were considered the least comfortable, classified as ‘cold,’ with the PPD fluctuating between 65% and 67% due to the limited entrance of direct solar radiation into the rooms. South had an MRT of 15.7–20.3 °C, which is lower than the MRT of eastern-oriented buildings, but the lowest β (approx. 0.443), giving Tia 19.8–22.3 °C; inefficient translation of radiant gains undermines passive heating. The low β of 0.443, indicative of the relationship between indoor air temperature and MRT according to the MRT-Tia correlation presented in Table 3, suggests that ineffective conversion of radiant gains compromises passive heating. Because of this, the PMV-PPD precise results for this season indicate that the southern direction is cooler than the eastern orientation. With ‘cool,’ the southern set showed that bedrooms were the coolest spaces, with a maximum PMD of 91%. An average PMV grade of ‘neutral’ and the lowest PPD of 5% indicated that the kitchens were the most tranquil. Next came the guest room, which had a 0.56 PMV and 12% PPD, which was very close to the “neutral” rating even though it was described as ‘slightly cool’. This configuration results in suboptimal winter performance relative to conventional passive solar design expectations that prioritize south-oriented buildings in the Northern Hemisphere [30,32,41,42,75]. Finally, west-facing buildings in winter exhibited MRT values ranging from 18.4 to 22.0 °C, which were the highest among all orientations, and had a relatively strong β of 0.816, resulting in the highest indoor air temperatures between 19.9 and 22.8 °C. This position offers the best winter warming in the dataset. These quantified relationships confirm that high β and elevated MRT correlate with strong indoor air temperature rises, while low β buffers radiant exchange, which is critical information for designers and architects. Therefore, houses in this orientation are the most comfortable during the winter, with more ‘neutral’ spaces (kitchen and living room) than other orientations. See Table 3.

3.6. Limitations

While this study offers novel insights into the relationship between mean radiant temperature (MRT) and indoor air temperature (Tia) across building orientations in hot and dry steppe (BSh) climates, several limitations should be acknowledged. First, the sample size—36 residential row houses—though methodologically justified, may limit broader generalizability across different building typologies or urban contexts. Second, the seasonal scope was restricted to peak summer and winter months, which may not capture transitional seasonal dynamics or year-round thermal behavior. Third, the study focused on a specific geographic region (Garmian, Kurdistan-Iraq), and findings may not be directly transferable to other BSh climates with differing urban morphology, cultural practices, or construction standards. Finally, while the regression analysis provides valuable correlational insights, causal relationships between MRT and Tia require further investigation through controlled experiments or longitudinal studies. Future research should expand the temporal and spatial scope, incorporate additional building types, and explore the integration of MRT into dynamic thermal control systems.

4. Conclusions

These findings challenge the conventional assumption in passive solar design that southern orientation is universally optimal. While traditionally favored in Mediterranean and European climates for maximizing solar gain, our results demonstrate that in hot and dry steppe (BSh) climates, south-facing buildings may underperform in winter due to low mean radiant temperatures and weak thermal gains. This illustrates the importance of climate-specific orientation strategies. Architects are encouraged to reconsider the default preference for southern orientation in such climates and instead adopt adaptive design solutions—such as enhanced thermal mass, improved insulation, and dynamic shading systems—for southern facades to optimize thermal comfort and energy efficiency.
Solar radiation has a significant impact in all climates, but it plays a particularly important function in hot, dry regions. The study examined how the orientation of row houses affects thermal comfort in hot, dry steppe (BSh) conditions. To determine how solar radiation affects thermal performance depending on orientation, the connection between MRT and Tia is tested in each orientation. Therefore, the PMV-PPD method has been applied to evaluate the four primary directions for thermal comfort: north, east, south, and west in summer and winter. Field observations were part of the PMV/PPD technique employed during the data collection phase. Five separate observations were taken in various locations within each home for each direction. A total of 360 tests were conducted for PMV-PPD evaluation, and 180 on-site observations were made within the chosen dwellings during the summer to guarantee the impact of solar radiation throughout the day. During the winter, 180 more observations were made at similar times of day (from 9:00 to 15:00). It is necessary to identify or measure each test or observation. Using six criteria, 30 observations were made in five locations within each house, for a total of 1080 observations per season.
The study’s findings regarding the MRT and Tia inside the buildings indicate significant differences in both MRT and Tia as the building orientation changes in the study area. This illustrates the importance of building orientation in determining the thermal potential of the structure. The results indicate that the indoor air temperature was lower than the MRT inside the buildings in all the orientations during the summer and vice versa for the winter. In the summer, the MRT is always higher because the surrounding surfaces absorb and radiate the solar irradiance, raising it. However, in the winter, the MRT is lower than the indoor air temperature because the cold surfaces of walls, slabs, and windows conduct outdoor chill inward. These surfaces stay cooler than the indoor air temperature, lowering the MRT compared with the Inside Air Temperature. As a result, the occupants radiate heat toward these surfaces to achieve thermal equilibrium, which makes them feel cooler than the actual air temperature. This phenomenon will result in increased energy consumption to achieve thermal comfort conditions within the buildings, as additional energy is required to establish a thermal balance between the human body and the surrounding environment [76,77,78,79,80]. For summer, the weak thermal insulation properties of the envelope and fenestrations can cause higher MRT than air temperature, because the weak thermal mass lets the surfaces of the building be affected by the conducted heat inside from the hot outside ambiance [81,82,83,84]. In the same context, in the winter, weak thermal mass will allow the conduction through cooler surfaces to go inward and reduce the MRT compared to the Inside Air Temperature [32].
The results demonstrate the role of MRT in thermal comfort optimization. Orientation-specific regression models in this study reveal that MRT strongly influences indoor air temperature in the study area. For instance, east-oriented buildings in summer record MRT of 26.9–32.6 °C with a β of ~0.961, increasing Tia up to 31.0 °C, which implies a PMV value well above +1 and PPD significantly higher than acceptable levels. In contrast, north facades exhibited a maximum MRT of 30.7 °C and a weak correlation (β~0.524), resulting in indoor air temperatures ranging from 24.3 to 28.2 °C, which align with neutral PMV ranges and PPD values below 10%. These results confirm that MRT is the dominant thermal driver in the study area, and its orientation-specific behavior must be considered to optimize comfort. Furthermore, divergence in β values demonstrates which orientations convert solar heat gain and contribute to passive heating. In winter, west-oriented buildings achieve a mean radiant temperature (MRT) of up to 22.0 °C and an indoor air temperature (Tia) of up to 22.8 °C (β~0.82), which confirms their effectiveness in passive heating. In contrast, southern winter βs (~0.443) yield a Tia capped near 22.3 °C, exposing inefficiency despite MRT similar to the West. This clear distinction between MRT and Tia dynamics enables accurate evaluation of passive design strategies. Moreover, the results of this study indicate that eastern-oriented buildings perform inadequately in winter, especially when compared to traditional passive solar design expectations that favor south-oriented buildings in the Northern Hemisphere. As a result, the passive heating and cooling design solutions need to be reevaluated. Hence, coupling β and MRT ranges provide actionable thresholds: North orientations support summer thermal stability; East demands early shading; South offers poor winter efficiency unless the envelope optimizes thermal mass; and West, while efficient in winter, requires strong summer mitigation. Furthermore, these empirical MRT-Tia regressions equip designers with orientation-centered metrics—regression βs and MRT/Tia ranges aid in selecting glazing area, shading geometry, thermal mass deployment (U-Value), and HVAC strategies tailored to each orientation. Finally, based on empirical outcomes, the design suggestions recommend prioritizing north-side glazing for summer and implementing external shading on eastern and western facades to reduce MRT and PMV; additionally, it suggests redesigning south facades by enhancing the thermophysical properties of the envelope and increasing glazing areas to improve passive heating. The design suggestions recommend prioritizing north-side glazing for summer and implementing external shading on eastern and western facades to reduce MRT and PMV; additionally, it suggests redesigning south facades by enhancing the thermophysical properties of the envelope and increasing glazing areas to improve passive heating. The study comes out with the MRT-aware framework, which aligns with the international standards.

Author Contributions

Conceptualization, S.S.M.A.-D., N.H., and H.A.; methodology, S.S.M.A.-D., N.H. and H.A.; software, S.S.M.A.-D., N.H., and H.A.; validation, S.S.M.A.-D., N.H., and H.A.; formal analysis, S.S.M.A.-D. and N.H.; investigation, S.S.M.A.-D. and N.H.; resources, S.S.M.A.-D., N.H., and H.A.; data curation, S.S.M.A.-D. and N.H.; writing—original draft preparation, S.S.M.A.-D. and N.H.; writing—review and editing, H.A.; visualization, S.S.M.A.-D., N.H., and H.A.; supervision, S.S.M.A.-D., N.H., and H.A. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

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Atmosphere 16 01132 g001
Figure 1. Methodology flowchart summarizing the research process from case study selection to data collection and analysis.
Figure 1. Methodology flowchart summarizing the research process from case study selection to data collection and analysis.
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Figure 2. Global distribution of hot and dry steppe (BSh) climates based on the Köppen–Geiger classification [21], highlighting the study area location in southeastern Iraq.
Figure 2. Global distribution of hot and dry steppe (BSh) climates based on the Köppen–Geiger classification [21], highlighting the study area location in southeastern Iraq.
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Figure 3. The external elements and appearance of the buildings: (a) the elevation of the row houses; (b) the outside shape of the existing houses.
Figure 3. The external elements and appearance of the buildings: (a) the elevation of the row houses; (b) the outside shape of the existing houses.
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Figure 4. The plan of the selected row house, a one-floor building with a construction area equal to 109 m2, showing the zone and spaces within the selected row houses.
Figure 4. The plan of the selected row house, a one-floor building with a construction area equal to 109 m2, showing the zone and spaces within the selected row houses.
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Figure 5. Assessment of thermal comfort within each building group across the four orientations with PMV-PPD, informed by site observations conducted during winter.
Figure 5. Assessment of thermal comfort within each building group across the four orientations with PMV-PPD, informed by site observations conducted during winter.
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Figure 6. The evaluation of thermal comfort for each group of buildings across the four orientations, based on PMV-PPD measurements from site observations conducted during the summer.
Figure 6. The evaluation of thermal comfort for each group of buildings across the four orientations, based on PMV-PPD measurements from site observations conducted during the summer.
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Table 1. Environmental and individual variables.
Table 1. Environmental and individual variables.
(a) Environmental Variables
No.EquipmentParameterLocation
1EXTECH-H30 (Extech Electronics Co., Taiwan) globe thermometer (40 mm globe) Inside Globe Temperature (Gti) Indoor
2HAMA (Monheim, Germany) electronic metrological stationInside Air Temperature (Tia) Indoor
3Pack life DA02 anemometer model (Tacklife, Shenzhen, China) Inside Air Velocity (IAV) Indoor
4HAMA (Monheim, Germany) electronic metrological station Inside Relative Humidity (Rhi) Indoor
(b) Individual Variables
RoomActivity Level (Met)Clothing Insulation (Clo)Clo Value
Kitchen1.60.51.03
Living Room1.00.51.03
Master Bedroom0.80.51.03
Second Bedroom0.80.51.03
Guest Room1.00.51.03
Table 2. Relationship between MRT and Tia by orientation and season.
Table 2. Relationship between MRT and Tia by orientation and season.
(a) Summer
OrientationMRT Min (°C)MRT Max (°C)Tia Min (°C)Tia Max (°C)Regression Equation
North24.830.724.328.2Tia = 0.52386 MRT + 12.011
East26.932.625.931.0Tia = 0.96133 MRT + 0.29491
South27.632.726.931.6Tia = 0.89142 MRT + 2.53725
West28.134.226.531.8Tia = 0.87704 MRT + 2.45374
(b) Winter
OrientationMRT Min (°C)MRT Max (°C)Tia Min (°C)Tia Max (°C)Regression Equation
North16.519.517.120.0Tia = 0.96132 MRT + 1.29778
East18.321.019.422.0Tia = 0.7268 MRT + 6.35881
South15.720.319.822.3Tia = 0.4427 MRT + 12.43516
West18.422.019.922.8Tia = 0.81624 MRT + 5.0074
Table 3. Sensitivity of Indoor Air Temperature to MRT.
Table 3. Sensitivity of Indoor Air Temperature to MRT.
OrientationRegression Coefficient (β)R2 ValueInterpretation
North0.280.62Moderate thermal responsiveness; partial shielding from direct solar gain.
East0.350.68Increased morning exposure; moderate thermal coupling.
South0.420.74Strongest thermal coupling due to high solar exposure and limited shading.
West0.310.65Afternoon solar gain contributes to moderate responsiveness.
Note: Regression coefficients (β) quantify the change in indoor air temperature (Tia) per 1 °C increase in mean radiant temperature (MRT). These values reflect the degree of thermal responsiveness associated with each building orientation. Coefficients with p < 0.05 are considered statistically significant.
Table 4. PMV/PPD evaluation by orientation and season.
Table 4. PMV/PPD evaluation by orientation and season.
(a) Summer
RoomNorth PMVNorth SensationNorth PPDEast PMVEast SensationEast PPDSouth PMVSouth SensationSouth PPDWest PMVWest SensationWest PPD
Guest Room −0.45Neutral10%0.32Neutral9%1.92Warm73%1.94Warm74%
Kitchen 0.74Slightly Warm17%1.57Warm55%1.61Warm57%1.65Warm59%
Living Room 0.08Neutral5%0.44Neutral10%0.44Neutral9%0.47Neutral10%
Master Bedroom −1.37Slightly Cool44%0.11Neutral6%0.01Neutral5%0.14Neutral6%
Second Bedroom −0.95Slightly Cool26%1.14Slightly Warm33%1.35Slightly Warm43%1.23Slightly Warm38%
(b) Winter
RoomNorth PMVNorth SensationNorth PPDEast PMVEast SensationEast PPDSouth PMVSouth SensationSouth PPDWest PMVWest SensationWest PPD
Guest Room−1.64Cool59%−0.84Slightly Cool20%−0.56Slightly Cool12%−0.61Slightly Cool13%
Kitchen 0.19Neutral6%0.42Neutral9%0.05Neutral5%0.44Neutral9%
Living Room −1.62Cool58%−1.05Slightly Cool29%−1.16Slightly Cool33%−0.37Neutral8%
Master Bedroom−2.86Cold98%−1.76Cool65%−2.4Cool91%−2.1Cool81%
Second Bedroom −2.87Cold98%−1.8Cool67%−2.39Cool91%−2.3Cool89%
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Muhy Al-Din, S.S.; Hafizi, N.; Altan, H. Quantifying the Relationship Between Mean Radiant Temperature and Indoor Air Temperature Across Building Orientations in Hot and Dry Steppe Climates. Atmosphere 2025, 16, 1132. https://doi.org/10.3390/atmos16101132

AMA Style

Muhy Al-Din SS, Hafizi N, Altan H. Quantifying the Relationship Between Mean Radiant Temperature and Indoor Air Temperature Across Building Orientations in Hot and Dry Steppe Climates. Atmosphere. 2025; 16(10):1132. https://doi.org/10.3390/atmos16101132

Chicago/Turabian Style

Muhy Al-Din, Salar Salah, Nazgol Hafizi, and Hasim Altan. 2025. "Quantifying the Relationship Between Mean Radiant Temperature and Indoor Air Temperature Across Building Orientations in Hot and Dry Steppe Climates" Atmosphere 16, no. 10: 1132. https://doi.org/10.3390/atmos16101132

APA Style

Muhy Al-Din, S. S., Hafizi, N., & Altan, H. (2025). Quantifying the Relationship Between Mean Radiant Temperature and Indoor Air Temperature Across Building Orientations in Hot and Dry Steppe Climates. Atmosphere, 16(10), 1132. https://doi.org/10.3390/atmos16101132

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