Comfortable Thermal Environment Research Articles

Effects of electrochromic glass window on energy efficiency, thermal and visual performances under tropical climate

This study investigated the thermal, visual environments of real-life climate chambers installed with a full-scale dark gray electrochromic glass window (ECW) under tropical climate in Singapore. Two large-scale climate chambers were built and installed with electrochromic windows or 6 mm single clear glass for comparison, and their thermal and visual performances and effects on the efficiency of air-conditioning were real-time measured and analyzed in detail. Compared to the chamber installed with 6 mm glass, the coefficient of performance (COP) of the air conditioner can be enhanced by 29.64 % and 45.40 % if replaced by bleached and tinted ECWs, respectively. Our study shows that ECW can efficiently reduce around 80 % of the heat flux passing through the indoor under both states, and provide a cooler and more comfortable thermal environment. In contrast, the bleached ECW showed the best performance with 39 % of the daytime spent with a comfortable visual environment without glare. With a 4 % solar heat gain coefficient and a 0.1 % visible light transmission, the fully tinted ECW could reduce the mean radiant temperature and operative temperature by up to 4.7 °C and 11.6 °C, respectively, when compared to the 6 mm glass. The operative temperature of the chamber with fully tinted ECW was even 0.6 °C lower than that of the bleached state. In conclusion, the fully gray tinted ECW showed superior thermal performance with high energy efficiency, and the bleached state gave better visual environment comfortably and economically.

Coupling Computational Fluid Dynamics and EnergyPlus to Optimize Energy Consumption and Comfort in Air Column Ventilation at a Tall High-Speed Rail Station

With the rapid development of railways, the air distribution and thermal comfort within waiting halls of high-speed railway stations receive significant attention. In this research, the EnergyPlus and CFD simulation coupling method was employed to investigate three ventilation schemes (column attached ventilation (CAV), side jet ventilation (SJV), column attached with side jet ventilation (CASJV)) for the waiting hall of a high-speed railway station in Guangzhou. The research focused on analyzing the airflow characteristics, thermal comfort, and cooling energy consumption associated with each ventilation method. The results show that thermal stratification phenomena are obvious in summer waiting halls. Most of the predicted mean vote (PMV) values in the research are from −0.5 to 0.5, indicating a comfortable thermal environment. In certain areas of both the CAV and SJV, the LPD1 > 40%, which may lead to a strong sensation of a cold draft for passengers. Compared with the SJV, the CAV and CASJV save 11.89% and 9.25% in cooling energy consumption, respectively. Therefore, the CASJV is more suitable for applications in high-speed railway station waiting halls. The results of this study aim to support the application of this combination of attached ventilation and an “air column” air supply in high-speed railway stations.

Machine learning applications for a better demand controlled ventilation system experience in buildings: a review

PurposeAt the beginning of the Corona Virus Disease 2019 (COVID-19) pandemic, a digitalized construction environments surfaced in the heating, ventilation and air conditioning (HVAC) systems in the form of a modern delivery system called demand controlled ventilation (DCV). Demand controlled ventilation has the potential to solve the building ventilation's biggest problem of managing indoor air quality (IAQ) for controlling COVID-19 transmission in indoor environments. However, the improper evaluation and information management of infection prevention on dense crowd activities such as measurement errors and volatile organic compound (VOC) generation failure rates, is fragmented so the aim of this research is to integrate this and explore potentials with machine learning algorithms (MLAs).Design/methodology/approachThe method used is a thorough systematic literature review (SLR) approach. The results of this research consist of a detailed description of the DCV system and digitalized construction process of its IAQ elements.FindingsThe discussion revealed that DCV has a potential for being further integrated by perceiving it as a MLAs and hereby enabling the management of IAQ level from the perspective of health risk function mechanism (i.e. VOC and CO2) for maintaining a comfortable thermal environment and save energy of public and private buildings (PPBs). The appropriate MLA can also be selected in different occupancy patterns for seasonal variations, ventilation behavior, building type and locations, as well as current indoor air pollution control strategies. Furthermore, the conceptual framework showed that MLA application such as algorithm design/Model Predictive Control (MPC) integration can alleviate the high spread limitation of COVID-19 in the indoor environment.Originality/valueFinally, the research concludes that a large unexploited potential within integration and innovation is recognized in the DCV system and MLAs which can be improved to optimize level of IAQ from the perspective of health throughout the building sector DCV process systems. The requirements of CO2 based DCV along with VOC concentrations monitoring practice should be taken into consideration through further research and experience with adaption and implementation from the ventilation control initial stage of the DCV process.

Thermal Comfort Improvement Strategies for Outdoor Spaces in Traditional Villages Based on ENVI-Met: Shimengao Village in Chizhou City

The thermal comfort of outdoor spaces in traditional villages must be improved because high building density combined with complex and narrow spaces leads to a poor thermal environment. In traditional villages, outdoor spaces are the most frequently used places by local residents and tourists. In this study, the Shimengao Village in Tangxi Town, Chizhou City, a typical mountainous area in the southern Anhui Province, was selected as the research object, and Depthmap software was used to identify the most frequently used outdoor spaces. The spatial layout and three different outdoor spaces of the traditional village were measured and validated using ENVI-met software. In addition, the distribution of thermal comfort in the core area of the village and influencing factors were analyzed. Our results demonstrated that during summer, PET reached its highest value at 15:00, exhibiting a poor thermal environment in the core area of traditional village integration. From 15:00 to 21:00, PET values declined, resulting in improved thermal comfort levels. Open spaces had better thermal comfort ratings throughout the day. The thermal comfort distribution of three different types of outdoor space in traditional villages was also analyzed. The courtyard space had the worst thermal comfort, followed by the street space, whereas the square space had the best thermal comfort environment. This was correlated with the spatial layout of traditional villages, external facilities of buildings, microlandscapes (plants, water availability, etc.), and outdoor ground materials. Hence, we propose that optimizing the overall spatial layout of a traditional village, increasing the external facilities of buildings, creating “micro landscapes,” and optimizing the materials of outdoor spaces are important for improving the thermal comfort of the outdoor spaces of traditional villages.

Influence of space properties of enclosed patio on thermal performance in hot-humid areas of China

Patio plays an important role in climate adaptation and microclimate adjustment of buildings. This study aims to explore enclosed patio design guidelines, which are essential for both architectural design methodology and practical projects for providing better thermally comfortable indoor and outdoor spaces. A combined qualitative and quantitative methodological approach was used to clarify how the passive design strategies of the enclosed patio affect the thermal environment of houses around the patio. The findings reveal the spacial characteristics and thermal adjustment of enclosed patios. The results of simulation indicate that appropriate design parameters of enclosed patio can achieve a better indoor and outdoor thermal comfort environment for its users, which includes similar dimension in width and depth, increased number of windows in a high ratio of width to depth, semi-open auxiliary space, 3-4 floor height, upper-lower double windows of four-sided enclosed patio and south opening direction of three-sided enclosed patio.

Evaluating the Impact of Transition spaces on the Indoor comfort conditions of a Naturally Ventilated Institution Building

Transition spaces connect between the interior space and the exterior environment and it acts as an intermediate or a third space. A well-designed transition space acts as a microclimate modifier for the interior spaces. The current study focuses on the role of transition spaces in creating a comfortable thermal environment in classrooms of an educational institute, located in a region with hot humid climate. The aim of the study is to investigate the impact of transition spaces upon the creation of indoor thermal comfort. For this study, the quantitative data was collected through field measurements in terms of air temperature on a typical summer day. Further, the field data was also collected from different orientations and various classrooms within the campus of the institution. Adaptive thermal comfort metrics was used to compare the performance on the built geometry. The spatial distribution of adaptive thermal comfort was simulated using IESVE software. Further, new scenarios were proposed and developed for the built geometry by altering the built parameters like aspect ratio and the depth of the transition space. The indoor thermal comfort performance of the proposed scenarios was compared with the existing conditions so as to establish a relationship between the built parameters and comfort conditions. A significant improvement was evident in the comfort level of indoor spaces, which suggest that the transition spaces optimize the indoor space comfort levels by reducing the indoor temperature by about 0.5°C to 2°C. Thus, the study proves that the changes in the aspect ratio and corridor width significantly impacts the indoor comfort. The current study outcomes can further help the designers to understand that the best efficient transition space has a positive impact upon a healthy learning space.

3D urban landscape optimization: From the perspective of heat flux-microclimate relations

Three-dimensional urban landscapes significantly alter surface energy dynamics and local climates. However, it remains unclear how heat fluxes impact the microclimate at the neighborhood scale in dense megacities. Combined spatial gradient sampling method and multi scenarios simulations based on the ENVI-met model, we aimed to explore the relations between heat fluxes and microclimate in Beijing, China. The results showed that (1) The sensible heat flux/latent heat flux had the largest explanatory power to wind speed at night (39% vs. 39%), followed by air temperature at midday (35% vs. 24%). The explanatory power improved under dual-factor regression analysis, especially for the wind speed at night (67%). (2) As the sensible heat flux/latent heat flux increased by 10 W/m2 at midday, the air temperature increased by 0.024°C and 0.017°C, respectively. (3) As the sensible heat flux/latent heat flux increased by 10 W/m2 at night, the wind speed increased by 0.21 m/s and 0.76 m/s, respectively. For the neighborhoods with high sensible heat flux and low latent heat flux, both decreasing the three-dimensional fractal of buildings and greening the plants can lead to more comfortable thermal environment.

INFLUENCES OF VEGETATION STRUCTURE (VS) ON METEOROLOGICAL PARAMETERS IN BUILT ENVIRONMENT; A FIELDWORK STUDY

Vegetation plays a crucial role in establishing a comfortable thermal environment by regulating temperature, humidity, and wind velocity. It is a well-documented that the Vegetation Structure (VS) variables, including height, density, leaf colour and size, canopy, density can have a significant impact on the microclimate inside and around the plants. However, the correlation between the different vegetation structures around residential buildings and the meteorological conditions inside and outside remains unclear. In this paper, an experimental investigation was carried out to determine the effect of VS on residential buildings’ microclimate. Parameters of meteorological were measured in and around two Case Study (CS1 & CS2) which are single story buildings located in Perak, Malaysia. Five days of meteorological data were collected using a Thermal Microclimate Datalogger (HD32.1 Delta Ohm) and an Indoor Air Quality Datalogger (HD37AB1347 Delta Ohm) to measure temperature (oC), relative humidity (%), and air velocity (m/s). Both case study's VS variables were measured and then thoroughly examined to determine the potential of VS in generating a pleasant thermal environment. This research compares and discusses VS and meteorological parameters measured within and outside of the case study buildings. The results were analyzed in three Quartile: Q1 from 7:30 a.m. to 11:00 a.m., Q2 from 11.15 a.m. to 2:30 p.m., and Q3 from 2:45 p.m. to 6:00 p.m. In Q1, CS1 shows the highest outdoor-indoor temperature difference of 2.31℃ compared to 2.02oC for CS2. In contrast, CS2 recorded the highest ambient temperature differences of 1.35℃ and 2.73oC in Q2 and Q3, respectively compared to CS1; 1.27oC and 1.19℃. Overall, vegetation structure can have a significant impact on meteorological parameters, which can in turn influence indoor and outdoor thermal performance.

Toward Utilizing IoT Open Data Set to Identify the Room Thermal Comfort

Building sectors are responsible for 33% of global energy consumption and a one-third of CO2 emission as buildings are expected to experience high performance in order to mee occupnt requirments such as lightng, coling, heting, and ventiltion systm. Internet of Things (IoT) as one of the leading developments in digital technologies led to the establishment of devices for improving the living style of the occupants. To date, stdies on intgrating the mechnisms of IoT to identify room thrmal cmfort are very sarce. Therefore, this study discussed the room thermal comfort with respect to room temperature and relative humidity. Three activities i.e. read, write, and sit were adopted. The value of air sped, metablic rate, and clohing inslation was assumed constant. The anlysis was condcted according to Fanger method and ASHRAE standard 55. Center for the Built Environment (CBE) Thermal Comfort Tool was usd to calculate the Predicted Mean Vote (PMV) vales. Results showed the average PMV values of each activity were -2.3 (read), -2.0 (write), and -1.4 (sit). Compared to the room climate data set, sitting performed the closest thermal comfort scale to the neutral. It means light activities with lower metabolic rate should be conducted in the room with higher room temperature and relative humidity.

Combined Effects of the Thermal-Acoustic Environment on Subjective Evaluations in Urban Park Based on Sensory-Walking

Studying the impact of various factors on environmental perception is crucial because humans live in an environment where these factors interact and blend. The thermal-acoustic environment is the major factor that affects the overall perception of urban parks. This study focuses on urban parks in the subtropical region, with Xihu Park in Fuzhou, China, as the research area. Through measurements and questionnaires, this study explores the effects of the thermal-acoustic environment in urban parks on subjective evaluation (thermal assessment, acoustic assessment, and overall environmental assessment). The results reveal that: (1) a higher temperature significantly increases the sensation of heat and lowers thermal comfort, heat acceptance, and overall thermal environment evaluation scores. The type of sound source has a significant positive impact on thermal assessment, and the higher the ranking of the sound source type, the greater its positive impact on thermal assessment. (2) Regarding acoustic evaluation, higher sound pressure level is associated with more negative subjective ratings of loudness, harshness, intensity, and excitement. In contrast, positive sound sources can enhance comfort, preference, disorder, coordination, and overall soundscape evaluation. Additionally, temperature increases tend to result in more negative harshness, intensity, and coordination ratings. The interaction between temperature and sound pressure level also significantly affects subjective loudness, harshness, and intensity. (3) Overall environmental evaluation is also affected by temperature, with increasing temperatures leading to decreased comfort and satisfaction while increasing irritation. High sound pressure environments result in worse overall irritation ratings, while positive sound sources can significantly enhance overall comfort, irritation, and satisfaction ratings. Furthermore, the interaction between temperature and sound pressure level significantly impacts overall irritation and satisfaction ratings. These findings are significant for managing and improving the park’s thermal environment and soundscape, providing a practical framework for landscape architects.

CFDを用いた食品小売店舗のエネルギー・室内温熱環境評価（その3）：対策導入によるSC・空調負荷削減と熱的快適性の改善効果に関する評価

In this report, some energy-saving and thermal comfort improving strategies adopted in a grocery store were estimated by using the store environment analysis CFD model. As results, by replacing the frozen multi-deck display cases with frozen reach-in cases, total energy consumption of cases and air conditioners decreased to 3/4 both in summer and winter, meanwhile it led to a more comfortable thermal environment. In winter, exhausting from the lower part of display cases resulted in 3% decreasing in the total energy consumption, while elongating a supermarket shelf near entrance hardly influenced thermal comfort and energy consumption.

室間移動および暖房方式を考慮した女性冷え性者の足部温冷感に関する被験者実験

In Japan, intermittent air conditioning in living rooms is a common occurrence, and the thermal environment in other rooms is generally cold. Thus, it is necessary to provide a comfortable thermal environment for “Hiesho”. This study aimed to clarify the effects of the heating system on the physiological and psychological responses of “Hiesho” when moving between rooms. The physiological and psychological responses were examined by conducting experiments under five different conditions. The results thus obtained showed that even “Hiesho” feel less cold when floor heating is running in the living room and foot heating is running in other rooms.

Occupancy and Thermal Preference-Based HVAC Control Strategy Using Multisensor Network

Human-in-the-loop Heating, Ventilation and Air Conditioning (HVAC) control-based methodologies have gained much attention due to continual discomfort compliance of occupants in residential and commercial buildings; spawning thermal comfort research interest in leveraging emerging advanced technologies to address the prolonged problem of discomfort and energy efficiency. In the past, thermal comfort studies have been conducted to determine the thermal sensation, preference and comfort based on the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) Global Thermal Comfort Database II and customized dataset through machine learning. The ASHRAE Database II is an open-source database that includes sets of objective indoor climatic observations with corresponding subjective evaluations by the building occupants who were used as subjects in experiments. Environmental parameters and occupants’ skin temperature have been used to develop machine learning algorithms to predict thermal comfort indices in both indoor and outdoor settings. However, none of these studies have investigated merging environmental parameters and thermal images to predict thermal comfort indices of occupants. In this study, the holistic understanding of individuals thermal comfort environment was considered by fusing analog environmental sensors and thermal images captured at the time of the subjective measurement. Wavelet scattering features were obtained from the occupants’ thermal image surroundings and joined to the environmental parameters. This research developed different machine learning models, processing methods and evaluated the results based on the fused dataset. The results show the possibility of real time prediction of occupancy and thermal preference through classical machine learning, and stacked models with high accuracy. The proposed framework achieved an estimated 45% mean energy savings during a ten-day energy analysis.

STUDY ON THERMAL COMFORT FACTORS IN CONVERSION-ADAPTIVE BUILDING, CASE STUDY IN SURAKARTA INDISCHE HOUSE

Traditional buildings are one type of structure that can adapt to a dynamic environment. Some functions of the building’s spaces have been changed to the new requirements, but the building's overall shape has been preserved. The purpose of this study was to examine and determine the differences in perceived thermal comfort values ​​between occupants and visitors inside the building. Using the observation method and analyzing the data through PMV-PPD and correlating with the Adaptive method in the Center for the Built Environment (CBE) Thermal Comfort Tool Website, it shows that there are differences caused by the environmental climate that do not match the PMV standard from ASHRAE. This study also has shown a difference of 18% between the PMV value of visitors to occupants, where there are past factors that influence this difference, and also a difference of 0.58 between the PMV value of Fanger and Sugini theory (comparison between general theory that is often used with the local theory that has been researched), because of Indonesians' heat tolerance. In this study, it was found that there are variables that are not needed in the adaptive method approach of naturally ventilated buildings, namely the humidity in buildings that are in tropical and humid areas. The reason for this is that the effect of moisture on the thermal sensation is insignificant, and it can be neglected.

Decision-Refillable-Based Shared Feature-Guided Fuzzy Classification for Personal Thermal Comfort

Different types of buildings in different climate zones have their own design specifications and specific user populations. Generally speaking, these populations have similar sensory feedbacks in their perception of environmental thermal comfort. Existing thermal comfort models do not incorporate personal thermal comfort models for specific populations. In terms of an algorithm, the existing work constructs machine learning models based on an established human thermal comfort database with variables such as indoor temperature, clothing insulation, et al., and has achieved satisfactory classification results. More importantly, such thermal comfort models often lack scientific interpretability. Therefore, this study selected a specific population as the research object, adopted the 0-order Takagi–Sugeno–Kang (TSK) fuzzy classifier as the base training unit, and constructed a shared feature-guided new TSK fuzzy classification algorithm with extra feature compensation (SFG-TFC) to explore the perception features of the population in the thermal environment of buildings and to improve the classification performance and interpretability of the model. First, the shared features of subdatasets collected in different time periods were extracted. Second, the extra features of each subdataset were independently trained, and the rule outputs corresponding to the key shared features were reprojected into the corresponding fuzzy classifiers. This strategy not only highlights the guiding role of shared features but also considers the important compensation effect of extra features; thereby, improving the classification performance of the entire classification model. Finally, the least learning machine (LLM) was used to solve the parameters of the “then” part of each basic training unit, and these output weights were integrated to enhance the generalization performance of the model. The experimental results demonstrate that SFG-TFC has better classification performance and interpretability than the classic nonfuzzy algorithms support vector machine (SVM) and deep belief network (DBN), the 0-order TSK, and the multilevel optimization and fuzzy approximation algorithm QI-TSK.

A multi-mode cellulose acetate/MXene Janus film with structure enhanced self-reflection, selective emission and absorption for cooling and heating

Passive radiative thermal management has been recognized as one of the most promising energy-saving technologies to provide thermal comfortable environment. However, static function and complex production process limit its application. Herein, we propose a simple strategy to achieve the integration of radiative cooling, radiative heating, and active electro-thermal heating. It is worth stressing that the radiative cooling is only based on the self-reflective structure and self-emissive molecular property of cellulose acetate electrospun membrane. In cooling mode, the average temperature of Janus film outdoor is 9.4 °C lower than commercial cotton fabric. Meanwhile, radiative heating and active heating stem from the photothermal and electrothermal performance of MXene. In heating mode, the average temperature of Janus film is 40 °C higher than cotton fabric. Flipping the Janus film allows for dynamic thermal management. In short, the scalable and universal strategy paves the way for the development of dynamic thermal-regulating technology.

Physiological responses and data-driven thermal comfort models with personal conditioning devices (PCD)

Thermal comfort in uniform environments created by HVAC systems have been investigated for decades. However, the case in nonuniform microenvironments created by the personal conditioning device (PCD) is different because of the local thermal stimuli on occupants. This study used PCD to provide localized cooling for users based on their individual thermal preferences. We collected PCD users' wrist temperatures and heart rate variabilities (HRV), as well as thermal sensation/comfort questionnaires. Because of the nonuniform thermal stimuli, the physiological responses triggered by the PCD show unclear patterns, which are incompatible with traditional thermal comfort models developed for the uniform environment. Therefore, we utilized machine learning methods to model PCD users’ thermal comfort. By using SVM with RBF kernel based on multiple HRV indices in addition to wrist temperatures, the F1 score is improved by more than four times when compared to the model only based on wrist temperatures. This indicates the importance of HRV as physiological indices for the thermal comfort with nonuniform thermal stimuli. The best performances of our models are higher than 0.90 for both thermal sensation and comfort, which can provide a reliable solution in predicting the thermal sensation and comfort in nonuniform environments with the PCD.

Optimization of the Thermal Environment of Large-Scale Open Space with Subzone-Based Temperature Setting Using BEM and CFD Coupling Simulation

A cruise ship, which has large-scale open spaces, has an uneven cabin thermal environment in the cruise public space, leading to overcooling or poor cooling issues. Therefore, optimizing the thermal environment of public spaces during a cruise should be the priority. According to the space functions of the cruise ship, the large public space is divided into three subzones: the entertainment area (Subzone I), the round-table dining area (Subzone II), and the square-table dining area (Subzone III). To create a uniform, stable, and comfortable thermal environment, this study proposes a subzone-based temperature setting approach to independently adjust the thermal environment of each subzone. Coupling simulation of building energy modeling (BEM) and computational fluid dynamics (CFD) was adopted in this study to determine proper temperature setpoints of the subzones under different occupancy rates. The results indicate that, compared with a single-temperature setpoint for the entire public space, the subzone-based temperature setpoints could achieve a uniform thermal environment. The average temperature difference among the three subzones was 0.68 °C. Moreover, the airflow between two adjacent subzones considerably affected the BEM results of energy consumption of the air-conditioning system.

Evaluation of thermal environment and human thermal comfort in 8 types of public places from 2019 to 2021

Objective: To evaluate the thermal environment of different types of public places and the thermal comfort of employees, so as to provide scientific basis for the establishment of microclimate standards and health supervision requirements. Methods: From June 2019 to December 2021, 50 public places (178 times) of 8 categories in Wuxi were selected, including hotels, swimming pools (gymnasiums), bathing places, shopping malls (supermarkets), barber shops, beauty shops, waiting rooms (bus station) and gyms. In summer and winter, microclimate indicators such as temperature and wind speed were measured in all kinds of places, combined with the work attire and physical activity of employees in the places. Fanger thermal comfort equation and center for the built environment (CBE) thermal comfort calculation tool were used to evaluate the predicted mean vote (PMV), predicted percent dissatisfied (PPD) and standard effective temperature (SET) according to the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) 55-2020. The modification effects of seasonal and temperature control conditions on thermal comfort were analyzed. The consistency of GB 37488-2019 "Hygienic Indicators and Limits in Public Places" and ASHRAE 55-2020 evaluation results on thermal environment was compared. Results: The thermal sensation of hotel, barber shop staff and the gym front-desk staff were moderate, while the thermal sensation of swimming place lifeguard, bathing place cleaning staff and gym trainer were slightly warm in summer and winter. Waiting room (bus station) cleaning and working staff, shopping mall staff felt slightly warm in summer and moderate in winter. Service staff in bathing places felt slightly warm in winter, while staff in beauty salons felt slightly cool in winter. The thermal comfort compliance of hotel cleaning staff and shopping mall staff in summer was lower than that in winter (χ(2)=7.01, 7.22, P=0.008, 0.007). The thermal comfort compliance of shopping mall staff in the condition of air conditioning off was higher than that in the condition of air conditioning on (χ(2)=7.01, P=0.008). The SET values of front-desk staff in hotels with different health supervision levels were significantly different (F=3.30, P=0.024). The PPD value and SET value of the front-desk staff, and the PPD value of cleaning staff of hotels above three stars were lower than those of hotels below three stars (P<0.05). The thermal comfort compliance of front-desk staff and cleaning staff in hotels above three stars was higher than that in hotels below three stars (χ(2)=8.33, 8.09, P=0.016, 0.018). The consistency of the two criteria was highest among waiting room (bus station) staff (100.0%, 1/1) and lowest among gym front-desk staff (0%, 0/2) and waiting room (bus station) cleaning staff (0%, 0/1) . Conclusion: There are different degrees of thermal discomfort in different seasons, under the condition of air conditioning and health supervision, and the microclimate indicators can not fully reflect the thermal comfort of human body. The health supervision of microclimate should be strengthened, the applicability of health standard limit value should be evaluated in many aspects, and the thermal comfort of occupational group should be improved.

Comparative Analysis of Comfort Temperature of School Children and Their Teachers

Thermal comfort in learning environments influences the student’s focus and learning productivity. This study aims to evaluate and compare the adaptive thermal comfort of schoolchildren and their teachers in naturally ventilated primary schools in some selected cities in Imo State Nigeria. To achieve these objectives, the study analyzed the data collected from 330 pupils and 44 teachers in six surveyed classrooms in two types of classroom buildings. The recorded data in the surveyed classrooms consisted of four environmental factors and two personal factors. At the same time, the subjects filled out the questionnaires asking them about thermal sensation and thermal preferences against the classrooms’ thermal requirements. The results of the measurements showed that the indoor mean air temperature, relative humidity, and air velocity were 29.1°C, 71.2%, and 0.19m/s, respectively. The mean thermal sensation votes of the children were +0.16 while that of their teachers was +0.58. The preferred temperatures were 27.4°C and 29.4°C for the schoolchildren and the teachers, respectively. Furthermore, the comfort range of the students was between 25.8°C - 31.6°C, and that of the teachers was between 28.0°C - 29.9°C. Based on the results of this study conducted in primary school buildings located in warm and humid climates, the thermal comfort perception of children and adults differ. This information will serve as a guide to professionals in the built environment, especially architects when designing primary school buildings in the warm and humid climates.