Thermal Comfort Research Articles

Development of a tailored questionnaire instrument to evaluate thermal sensation of elderly people in India

Purpose India’s growing elderly population necessitates ensuring indoor thermal comfort because of their vulnerability to temperature-related illnesses and reduced capacity to regulate body temperature. Currently, thermal sensation (TS) assessment scales, designed for those between 20 and 60 years of age, may not accurately capture the preferences of elderly adults. To address the gap, this study aims to identify appropriate scaling methods to help the elderly understand the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE-55) seven-point TS scale clearly. Design/methodology/approach Four scaling methods – color, emoji, landscape images and regional images scales – identified from literature were analyzed using quantitative approaches. The differences between two age groups (<60 years and = 60 years) were examined using frequency distribution differences and independent sample t-test methods. Findings Results indicated that both younger/middle-aged (<60 years) and elderly individuals (= 60 years) were adept at identifying color and regional images scale, while emoji and landscape images scale posed challenges for the elderly. Furthermore, a tailored questionnaire instrument was developed to enhance the comprehension of TS questions for the elderly. One sample t-test results indicated that the proposed questionnaire instrument is a better fit to support ASHRAE-55 seven-point TS scale, making it particularly effective for the elderly population. Originality/value This research presents a novel, tailored questionnaire instrument that significantly enhances the elderly population’s comprehension of TS questions, thereby improving the accuracy of thermal comfort assessments and contributing to the creation of better indoor thermal environments for the elderly people.

An analysis of outdoor thermal comfort impact on pedestrian walking patterns at sub-hour timescales with agent-based modelling

PurposeThis study aims to analyse the impact of outdoor climate, building configuration and locations of public amenities on pedestrians’ walking behaviour and their outdoor thermal comfort. As outdoor climate can rapidly change within minutes, this study maintains that outdoor thermal comfort should be analysed at the pedestrian scale and within a short period to understand people’s walking behaviour and how it may affect urban activities.Design/methodology/approachThis research analyses the thermal stresses experienced by pedestrians and their walking patterns within a sub-hour timeframe in Darling Square, Sydney. The simulation incorporates multiple outdoor climate analyses with agent-based modelling (ABM) simulation; it runs on a parametric modelling platform to predict walking patterns according to the agents’ innate properties, goals and environmental constraints as the weather fluctuates.FindingsThis study demonstrates that mapping outdoor thermal comfort within a shorter timescale could reveal emergent walking patterns that inform pedestrians’ preferences of their surrounding environment and their walking behaviour.Practical implicationsThe findings could inform planners and stakeholders on how outdoor climate and building configuration affect pedestrian walking patterns for improving outdoor space quality during the design process or post-occupancy evaluation.Originality/valueThis study integrates ABM that incorporates multiple agents’ goals and innate properties and a micro-climate analysis on diverse context geometries under sub-hour periods, compatible with the pedestrian walking speed and distances at the neighbourhood scale.

A comparison of heating and cooling systems having radiant and ventilation systems regarding thermal comfort

A comparison of heating and cooling systems having radiant and ventilation systems regarding thermal comfort

Optimization of Triple-Layer Glass Thickness for Maximizing Sunlight Incidence in Northern Winter Using Ant Colony Algorithm

Abstract. This study investigates the optimization of multilayer glass thickness to maximize solar heat gain in buildings located in cold northern climates, utilizing the Ant Colony Optimization (ACO) algorithm. The research focuses on enhancing thermal comfort and reducing energy consumption by optimizing the thickness of three glass layers, thereby improving solar energy transmission into indoor spaces. ACO, a metaheuristic inspired by the foraging behavior of ants, is employed due to its robustness in handling complex optimization problems. The study incorporates wavelength-specific considerations into the ACO framework to achieve a sophisticated optimization approach, resulting in improved solar energy transmission. The experimental results demonstrate that the optimized glass configuration significantly increases sunlight transmittance, especially within the target wavelength range, contributing to more energy-efficient and comfortable architectural designs. This research highlights the potential of ACO in optimizing building materials and suggests further refinement of the algorithm for enhanced performance in real-world applications.

Impact of Urban Surfaces on Microclimatic Conditions and Thermal Comfort in Burdur, Türkiye

Rapid urbanization worldwide offers numerous benefits but also introduces challenges, particularly concerning urban climate comfort, which affects the physical and social well-being in cities. This study examined the microclimatic characteristics of the Burç neighborhood in the historical core of Burdur city, using ENVI-Met models with temperature, relative humidity, wind and PET data collected over a 33,665 m2 area at 06:00, 09:00, 12:00, 15:00, 18:00 and 21:00 on 15 August 2023. The analysis revealed that thermal comfort decreases significantly from 09:00 onwards, especially on hard surfaces like asphalt, concrete and parquet, which lack vegetation and intensify heat retention. By contrast, green areas were found to enhance bioclimatic comfort by reducing perceived temperatures by up to 20% in shaded and vegetated zones. Based on these findings, it is recommended that urban areas reduce heat-absorbing materials, such as asphalt and concrete and prioritize green spaces in landscape planning to improve thermal comfort and create more sustainable urban environments.

Effects of cryo-facial mask on running performance in amateur middle-distance runners

The excess heat accumulated during exercise can lead to stress-induced fatigue, possibly impairing athletic performance. Various precooling techniques have been applied to enhance thermal comfort, reduce perception of effort, and improve endurance. In this randomized crossover study, twelve male amateur middle-distance runners (age: 33.69 ± 5.9 years; body mass: 71.9 ± 4.4 kg; height: 178.4 ± 5.6 cm; V˙O2 peak: 63.3 ± 5.6 mL min−1·kg−1) wore a facial cooling mask before a time-to-exhaustion (TTE) test on a treadmill, under cryostimulation or control conditions. The running performance comprised also two constant load trials, one conducted before and another after wearing the mask, both performed at the velocity of the first ventilatory threshold. Under cryostimulation condition, the TTE was 13 % higher than the control condition (p = 0.0049; d = −0.19) with a significant main effect of time for both ratings of perceived exertion (F1, 22 = 50.10; p < 0.0001; η2p = 0.69) and heart rate (F1, 22 = 31.53; p < 0.0001; η2p = 0.59). A significant interaction “condition × time” was found for facial skin temperature (F2, 44 = 36.93; p < 0.0001; η2p = 0.63) and for heart rate during the constant load trial after wearing the mask (F1, 22 = 5.90; p = 0.0238; η2p = 0.21). The localized cryostimulation provided by the mask lowered the skin temperature on the face, potentially mitigating the negative effects of heat stress during running. Incorporating the cryo-facial mask as part of a pre-exercise routine for runners may offer a practical and convenient method to optimize performance and enhance overall training outcomes.

Use of pneumatic waste in thermal insulation systems in arid áreas

Recent decades have seen a major global concern to protect the environment from non-biodegradable waste as little as possible. On the other hand, the problem of energy saving has emerged. Builders in arid areas and particularly in the Algerian Sahara are always faced with a very difficult choice: “build with traditional and local materials promoting a certain thermal comfort or build with modern materials offering more convenience, aesthetics and space but with less or no thermal comfort and very high consumption of air conditioning energy. The appearance of new materials and the innovation of waste in construction have not only improved the mechanical properties of materials but also energy saving through insulation, waterproofing and even the appearance of the construction. In the present work, an investigation was undertaken in order to respond to the problem of thermal comfort of construction while getting rid of tires which, through their long life, occupy large environmental spaces and through their incineration contribute to environmental pollution. Numerous tests have been carried out on reduced or real models representing either the floors or the partition walls which represent the two elements which are the main players in the heat transfer of the building. In comparison with the usual materials used in thermal insulation, the innovation of pneumatic waste has shown technical performances and thermal insulation properties superior to those existing on the market, which has the effect of increasing the energy efficiency of the buildings thus generating great economic interest. It is necessary to point out that only the plastic part of the tires was used while the metal part constituting the structural hoops of the tires has a wide use as a reinforcement system.

School buildings performance evaluation method (SC-BPE Method)

Assessing the condition of school buildings is essential to ensure a quality learning environment for users. Therefore, the objective of this article is to propose a Method for Evaluating the Performance of School Buildings. In this work, design science research was the method used to create the artifact, which consists of 4 stages. A literature review of academic works and national and international standards and guidelines were carried out to identify the criteria that should be considered in assessing the performance of school buildings. 71 subcriteria were identified, grouped into 12 criteria according to their correlations: facilities, finishes, fire safety, thermal, acoustic and visual comfort, infrastructure, sustainability, habitability, safety (of the school and the student), external factors and environments. The 12 criteria were further divided into 2 dimensions. The weighting of these criteria was performed using the Delphi method. For this stage, 6 experts from four different cities with experience in design, conservation and maintenance of school infrastructure were selected. Subsequently, a method of evaluating the criteria and measuring performance was proposed, which consists of the weighted sum of the evaluations of each criterion, based on a visual inspection and completion of the established protocols. The School Building Performance Evaluation Method encompasses all aspects of the building and is a viable form of evaluation, without requiring sophisticated equipment.

The Prediction of the Leakage Airflow Rate Using the Supply and Return Airflow Rate in a Variable Air Volume System

Pressure differences in the envelope of a building result in leakage airflow (i.e., the unintended flow of air). This can lead to increased building heating and cooling energy, decreased thermal comfort for occupants, and the spread of moisture. To address this problem, it is necessary to know the leakage airflow in a building. Generally, the leakage airflow in a building is calculated by determining the leakage function through fan pressurization methods, such as the blower door test, and substituting the pressure difference measured by the pressure sensor. However, it is difficult to install continuous pressure sensors in an operating building. Therefore, this study proposes a method to utilize the supply and return airflow of an air conditioning system to predict the variation in the leakage airflow with changing indoor and outdoor airflow, and the efficacy of this approach was verified through experiments. The experiment measured the indoor and outdoor pressure difference of the building with a change in the speed of the supply and return fans and the opening rate of the variable air volume (VAV) damper. As a result of the experiment, the indoor–outdoor pressure difference is proportional to the difference between the indoor supply airflow and the ventilation airflow. In addition, the relationship between the pressure difference and the leakage airflow was derived through the pressurization/decompression method using an air handler, and the leakage airflow from the pressure difference generated by the operation of the air conditioning system was calculated. Lastly, the relationship between the supply and return airflow difference and the leakage airflow was derived based on the experimental results, and the leakage airflow was predicted based on the relationship.

Thermal Comfort and Green Spaces: The Role of Temperature-Regulating Elements in Neighborhood Parks

According to current studies, the thermal effects of global warming will affect urban areas more intensely. In the face of this situation, strategies for the improvement and management of urban green spaces are becoming increasingly important in sustainable landscape design. These strategies promote social sustainability by positively affecting individuals’ physical and psychological well-being, taking into consideration ecological sustainability. Projections regarding global warming emphasize that the density of hardscapes and green spaces, the selection of plant species, and the distribution of plants considered within the scope of this study should be taken into account. This research was conducted in the Görükle neighborhood of Bursa, focusing on the role of temperature-regulating elements in 14 neighborhood parks. Systematic temperature measurements were carried out in the research area on the 10th, 20th, and 30th of July and August, specifically between 12:00 and 13:00, during peak temperature hours. The presence of parks that are close to each other and relatively far away from each other in the study area was seen as advantageous to filter the effects of plant differences in similar conditions. Furthermore, evaluating these various factors together highlights the multifaceted nature of thermal comfort. Designated temperature measurement points included three points (hard surfaces and hard surfaces surrounded by vegetation and planted green spaces) in each park. An analysis utilizing SPSS and the RayMan program revealed that parks with a softscape to hardscape ratio of approximately two to one experienced temperature reductions of 2.5 to 3 °C. Furthermore, the findings indicate that coniferous trees have a more significant impact on thermal comfort compared to deciduous trees. The significant differences identified in this study underscore essential considerations for urban design processes aimed at achieving sustainability.

Influence of Subjective Factors on Window Use in Maternity Hospitals in Spring

Poor indoor air quality in maternity hospitals can spread respiratory diseases; however, limited research exists on modifiable factors like occupant behavior. This study explores subjective drivers of window-opening in maternity wards, using surveys and on-site measurements. Results show 71.4% of respondents stay less than 14 days, leading to dynamic and irregular window behavior. Comfort, particularly thermal comfort, air quality, and circulation, is the main driver for window operations. Especially at low temperatures, pregnant women’s comfort plays a critical role, while other factors increase in importance as temperatures rise. The results show that environmental factors drive window-opening, while indoor comfort drives closing. Occupants are more tolerant to humidity than thermal discomfort, but window adjustments are random. Moreover, respondents prioritize others’ needs in closing windows, where outdoor noise often serves as a key factor. The time also had a greater impact on both window opening and closing decisions, while field measurements confirm that time influences window-opening more than closing. A Multivariate Analysis of Variance (MANOVA) analysis of the questionnaire data for ‘comfortable sensation’ showed that only ‘air circulation’ and ‘air humidity’ were correlated with comfort, whilst ‘heat sensation’ was the least correlated. The possible reason is that the questionnaire was conducted in the spring, when temperatures were within the comfort range, and therefore, occupants were more concerned with other factors. Window operations in maternity wards are a collective strategy for natural ventilation. This study shows that the factors affecting window use in maternity hospitals are different from other buildings, providing useful ideas for improving maternity ward design.

Machine learning-based assessment of thermal comfort for the elderly in warm environments: Combining the XGBoost algorithm and human body exergy analysis

Many elderly people rarely own or use air conditioners because of low income and economising habits, causing them to live in warm thermal environments when heat waves and hot weather occur. Living in warm conditions worsens thermal discomfort and poses health risks this group. To investigate the thermal comfort and adaptation of the elderly, a total of 38 participants were recruited for two parts of experiments in a climate chamber: Part A collected thermal sensation vote (TSV) and physiological parameters for 30 min at 28, 30, and 32 °C, and Part B presented a 20-min cooling with fans (air velocities of 0.6 and 1.4 m/s) at the same temperature. Furthermore, we constructed a thermal comfort model for the elderly based on human body exergy analysis and the GBDT, AdaBoost, and XGBoost machine-learning algorithms. The results showed that the predicted mean vote considerably overestimated the actual TSV. The TSV and mean skin temperature were decreased by 0.1–0.5 scores and 0.4–0.5 °C by the behavioural adaptation of fan cooling. The predictive results showed that the XGBoost model performed better, with R2 score, mean absolute error (MAE), and mean squared error (MSE) of 81 %, 0.10, and 0.01. Exergy transfer from evaporation (Ex-Esk), mean skin temperature (mtsk), air velocity (va), and convective exergy transfer (Ex-C) contributed more to the feature importance in the SHAP value analysis. The current study has implications for investigating physiological comfort and age-friendly environmental designs for the elderly, providing new perspectives for thermal comfort evaluations.

Optimizing Outdoor Thermal Comfort for Educational Buildings: Case Study in the City of Riyadh

In hot, arid climates, educational buildings often face the challenge of limited outdoor space usage. This research, through comprehensive simulation, aims to propose practical solutions to enhance outdoor thermal comfort, particularly during school break times and student dismissal periods, thereby fostering more comfortable and functional outdoor school environments. That will happen through achieving the main objective of the study, which is evaluating the suggested passive strategies. Riyadh was selected as the case study, and four representative schools were analyzed through simulation and optimization processes to identify key areas for improvement. The research leveraged simulation tools such as Ladybug and Grasshopper in Rhino, highlighting the practicality and impact of this approach. Simulations were performed to assess the existing outdoor thermal conditions using the universal thermal climate index (UTCI) and to pinpoint regions with elevated thermal discomfort. Passive design interventions, such as shading devices and vegetation, were explored and optimized using the Galapagos in Grasshopper. This methodology supports the originality of this research in its integration of simulation tools, such as Ladybug and Grasshopper, with optimization techniques using the Galapagos plugin, specifically applied to the unique site-specific context of educational outdoor environments in a hot, dry climate in Riyadh. Additionally, insights for urban planners and architects demonstrate the possibility of integrating passive design principles to improve the usability and sustainability of outdoor spaces. The findings indicated that fewer apertures in shade devices combined with greater tree canopies might double the effectivity in lowering UTCI values, thereby enhancing thermal comfort, especially during peak summer months.

The regulatory effect of the asymmetrical dress style on people’s thermal comfort and heat loss

The regulatory effect of the asymmetrical dress style on people’s thermal comfort and heat loss

Plasma Proteome Alterations of Laying Hens Subjected to Heat Stress and Fed a Diet Supplemented with Pequi Oil (Caryocar brasiliense Camb.): New Insights in the Identification of Heat Stress Biomarkers

Heat stress can disrupt the balance between the heat poultry release into the environment and the heat they generate. Pequi oil has antioxidant properties, which may mitigate the heat stress effects. This study aimed to investigate the response of laying hens to pequi oil supplementation under heat stress using a proteomic approach. A total of 96 Lohmann White laying hens with 26 weeks old were housed in a completely randomized design with a 2 × 2 factorial arrangement. They were housed in two climate chambers, thermal comfort temperature ± 24.04 °C with the relative humidity ± 66.35 and heat stress (HS) ± 31.26 °C with the relative humidity ± 60.62. They were fed two diets: a control diet (CON), basal diet (BD) without additives, and with Pequi oil (PO), BD + 0.6% PO. After 84 days, plasma samples were analyzed using Shotgun and LC-MS/MS. Proteins related to anti-inflammation, transport, and the immune system were differentially expressed in hens fed PO and CON under heat stress compared to those in thermoneutral environments. This helps protect against oxidative stress and may support the body’s ability to manage heat-induced damage, stabilizing protein expression under stress conditions. The ovotransferrin proteins, fibrinogen isoforms, apolipoprotein A-I, Proteasome activator subunit 4, Transthyretin, and the enzyme serine Peptidase Inhibitor_Kazal Type 5, which presented Upregulated (Up) equal to 1, present characteristics that may be crucial for enhancing the adaptive responses of hens to thermal stress, thereby increasing their tolerance and minimizing the negative effects of heat on egg production. The data presented in this manuscript provides new insights into the plasma proteome alterations of laying hens fed a diet supplemented with pequi oil during heat stress challenges.

Characteristics of air temperature and thermal comfort in the grey and green spaces of an urban heat island

Characteristics of air temperature and thermal comfort in the grey and green spaces of an urban heat island

Polyamide 6-Al2O3 nanoparticle composite nanofiber membranes with high solar reflectivity and human radiation transmittance for passive human body cooling

Passive radiant heat management is an energy-saving thermal radiation management technology that can improve the temperature regulation of conventional clothing in high-temperature environments. However, existing materials are either complex in structure, difficult to fabricate, or unsuitable for human application. In this study, a novel nanofiber membrane was developed that exhibits high solar reflectance and infrared transparency to human radiation, thus having an excellent radiative cooling effect. The nanofiber membrane was prepared by electrospinning polyamide (PA) 6 containing Al2O3 nanoparticles. It exhibits an average solar radiation reflectance of about 88 %, a maximum reflectance of more than 95 %, and transmittance to the human body infrared of more than 95 % and provides a cooling effect of 4–6.4 °C for outdoor objects (with convection), which results from the coaction of PA6 nanofibers and Al2O3 nanoparticles. The implementation of nanofiber membranes in clothing could not only protect wearers from high outdoor temperatures but also improve air and moisture permeability. We hope that this unique nanofiber membrane will be useful for managing thermal comfort and energy efficiency in various applications ranging from architectural materials to personal cooling solutions.

Time length of adaptation phase for subjective thermal environment evaluation based on thermal stability time

The adaptation phase is the primary process of subjective thermal comfort evaluations. The time length of the adaptation phase in existing studies disperses largely, which either risks low evaluation reliability or high time and economic costs. This study proposes to determine the time length of the adaptation phase for reliable subjective thermal environment evaluation and to avoid unnecessarily large time and economic costs. First, the variation and distribution of the initial thermal status of the adaptation phase are inferred from a steady bioheat model with ASHRAE (American Society of Heating, Refrigerating and Air-conditioning Engineers) Thermal Comfort Database II. Second, with the initial thermal status, the variation and distribution of the thermal stability time are inferred from the dynamic bioheat model. Third, the time length of the adaptation phase is quantified from the distribution of the thermal stability time according to the targeted reliability level. Results show that under the summer scenario, the time length of the adaptation phase increases from 16.9 – 31.2 min to 25.2 – 38.9 min when the reliability level increases from 90.0 % to 97.5 %. The time length of the adaptation phase of the winter scenario increases by 5.3 – 9.7 min relative to that of the summer scenario. A strategy of shifting the adaptation phase from thermal neutrality to slight warmth is proposed to effectively shorten the time length of the adaptation phase by 5.6 % – 19.4 % and 7.8 % – 23.9 % in the summer and winter scenarios respectively. These results are tabulated for practical convenience.

A framework for assessing the current and future capability of mechanical night ventilation in the context of climate change

Night ventilation is a technique in which the indoor air and the building’s thermal mass is cooled down during nighttime to provide a heat sink available during the next day to help mitigating overheating and reducing the daytime space cooling demand. This paper proposes a framework on evaluating the use of mechanical night ventilation today and in the future. It considers analysis of the ventilative cooling system, including mechanical night ventilation, by means of key performance indicators that involve thermal comfort, energy use and resiliency criteria as suggested by IEA Annex 80. It, additionally, introduces an economic parameter in form of diurnal and nocturnal price ratio of electricity as economic trade-off between nighttime fan- and daytime fan and chiller use in terms of electricity. A historic office building in north-central Sweden is presented as a detailed case as to illustrate the use of the framework. The investigation was done using a validated model of the building in IDA-ICE building simulation program at both current climate and future climate in 2050s. It was revealed that an upgraded ventilative cooling system with three times larger capacity is required to fulfill thermal comfort. Even though mechanical night ventilation could result in the annual cooling source electricity saving intensity up to 0.9 kWh/(m²∙a) at extreme current climate (2018), it could just insignificantly reduce the total electricity use for space cooling (up to 2 %) and only at some night ventilation rates at all mentioned climates. Mechanical night ventilation, however, could be applied in an economically beneficial way if the electricity network has different nocturnal and diurnal electricity prices. A unitless index of maximum nighttime over daytime electricity price ratio was proposed representing the maximum tolerable price for nighttime electricity, given a daytime electricity price, based on night- and daytime ventilation electricity demand. For economically justified application of mechanical night ventilation, lower nighttime over daytime electricity price ratios were required for higher night ventilation rates. For the typical future climate with night ventilation rates larger than 2.6 ACH, it will be necessary to have nighttime prices that are lower than daytime if mechanical night ventilation is to be economical. The approach used in the framework can be applied to future research and practice, regardless of the case-specific parameters such as building type, climate zone, location, etc.

Prediction of building HVAC energy consumption based on least squares support vector machines

Air conditioning, as an essential appliance in daily life, has the function of ensuring comfortable room temperature, but it is also accompanied by a large amount of power consumption. Consequently, the study suggests an energy consumption prediction model based on improved genetic algorithm—least squares support vector machine—to accurately predict the energy consumption of building heating, ventilation, and air conditioning. This model uses the improved genetic algorithm for regularization parameter and kernel parameter optimization to prevent overfitting and underfitting issues. According to the testing results, the least squares support vector machine, an upgraded genetic algorithm, may accomplish convergence faster than other algorithms, taking only 0.2 milliseconds to finish. In addition, the average relative error of the improved genetic algorithm- least squares support vector machine did not exceed 0.6%. In the energy consumption prediction for the whole year of 2022, the average error of the improved genetic algorithm-least squares support vector machine was only 2.0 × 106 kWh, and the prediction accuracy could reach up to 97.2%. The above outcomes revealed that the energy consumption prediction model can accurately predict the air conditioning energy consumption, which provides a strong support for the control and optimization of the air conditioning system.