•Three models for predicting thermal comfort distribution were compared.•The accuracies of ordered probability and multinomial logit models were similar.•Linear regression model was less accurate ...than the other two models.
This study compares the linear regression model, ordered probability model, and multinomial logit model for prediction of the individual thermal sensation votes (TSVs) and TSV distributions under given conditions. Two thermal comfort datasets were used to develop and evaluate the models. One dataset was taken from an indoor thermal comfort survey conducted in Pakistan, and the other was taken from an outdoor thermal comfort survey conducted in Tianjin, China. The data were divided into training and validation datasets. The training datasets were used for model development. The developed models were then used to predict new cases in the validation dataset. The predictive capability of the three models were systematically evaluated and compared to examine how well the developed models predicted individual TSVs and TSV distributions for the validation dataset. The results showed that the ordered probability model and the multinomial logit model correctly predicted around 50% of the individual TSVs, whereas the accuracy of the linear regression model was only around 20 to 40%. In addition, the chi-square statistics show that the ordered probability model and the multinomial logit model better predicted the TSV distributions than the linear regression model.
The predicted mean vote (PMV) and predicted percentage of dissatisfied (PPD) are the most widely used thermal comfort indices. Yet, their performance remains a contested topic. The ASHRAE Global ...Thermal Comfort Database II, the largest of its kind, was used to evaluate the prediction accuracy of the PMV/PPD model. We focused on: (i) the accuracy of PMV in predicting both observed thermal sensation (OTS) or observed mean vote (OMV) and (ii) comparing the PMV-PPD relationship with binned OTS – observed percentage of unacceptability (OPU). The accuracy of PMV in predicting OTS was only 34%, meaning that the thermal sensation is incorrectly predicted two out of three times. PMV had a mean absolute error of one unit on the thermal sensation scale and its accuracy decreased towards the ends of the thermal sensation scale. The accuracy of PMV was similarly low for air-conditioned, naturally ventilated and mixed-mode buildings. In addition, the PPD was not able to predict the dissatisfaction rate. If the PMV model would perfectly predict thermal sensation, then PPD accuracy is higher close to neutrality but it would overestimate dissatisfaction by approximately 15–25% outside of it. Furthermore, PMV-PPD accuracy varied strongly between ventilation strategies, building types and climate groups. These findings demonstrate the low prediction accuracy of the PMV–PPD model, indicating the need to develop high prediction accuracy thermal comfort models. For demonstration, we developed a simple thermal prediction model just based on air temperature and its accuracy, for this database, was higher than PMV.
Display omitted
•Assessed PMV-PPD accuracy using the ASHRAE Global Thermal Comfort Database II.•PMV predicted thermal sensation correctly only one out of three times.•PMV had a mean absolute error of one unit on the thermal sensation scale.•PPD was not able to predict the dissatisfaction rate.•PMV-PPD accuracy varied strongly between ventilation, building types and climate.
•1040 valid measurement data and subjective questionnaires were obtained.•Acceptable temperature range of older people in all seasons was assessed.•Existing adaptive thermal comfort models were not ...suitable for older people.•Adaptive thermal comfort models of older people in different seasons were established.•The prediction of winter and summer model were both reliable.
This research focused on adaptive thermal comfort in homes for older people in the hot summer and cold winter climate zone of China. A field study was conducted throughout the four seasons beginning in January 2014 and ending in April 2017 in Shanghai, China. The survey included simultaneous measurements of outdoor and indoor environmental parameters and an assessment of the participants’ sensations using questionnaires. A total of 19 homes for older people and 64 buildings were surveyed; 1040 measured data points and subjective questionnaires were obtained. The sensation ratings were analyzed, and thermal comfort temperature was calculated using regression methods. Results showed that thermal comfort assessments of older people in Shanghai should use –0.2 < TSV < +0.2 as the standard, yielding acceptable temperature ranges for older people of 14.1–19.4 ℃ in winter, 23.8–27.0 ℃ in summer, and 20.6–31.7 ℃ in mid-season. Adaptive thermal comfort models in different seasons showed that, first, the predictions of the winter and summer models were both reliable. Second, the thermal adaptive models of the mid-season intersected with the ASHRAE 55 model at 20.5 ℃ and was within the applicable range of the mid-season model (10–20.8 ℃); under the same outdoor temperature conditions, the neutral temperatures predicted by the EN15251 model and the ASHRAE 55 model were higher than the predicted values of the mid-season thermal adaptive model. Third, the slopes of both the winter and summer thermal adaptive models were slightly lower than those of the GB/T50785-2012 model. These results can be used to assess indoor thermal comfort in homes for older people and help create age-friendly building environments in China.
The understanding of human outdoor thermal comfort demand and thermal adaptation contributes to sustainable urban design as well as city resilience in the context of human health and wellbeing. ...Humans' past thermal experience influence their outdoor thermal comfort. However, the quantitative relationship between the past thermal experience and outdoor thermal comfort is still not clear. This study aims to reveal quantitative relations of the impact of people's past thermal experience on adaptive thermal comfort and to develop a new outdoor adaptive thermal comfort model. A year-long longitudinal questionnaire survey along with a combination of outdoor thermal environment campaigns was carried out in Chongqing, China. It began on August 15, 2020, and finished on August 19, 2021. Through the analysis of 2240 valid responses to the questionnaire survey, the outdoor thermal adaptation characteristic and dynamic thermal comfort evaluation of the respondents were revealed. The results show that the quantified temperature of past outdoor thermal experience is the quadratic correlation with the thermal sensitivity coefficient and deviation constant, and the linear correlated with outdoor thermal demands. Based on the quantitative analysis, a new outdoor adaptive thermal comfort model has been developed as a function of the exponentially weighted sum of historical mean air temperature series (MeanTrm). The outdoor adaptive thermal comfort zones by 80% and 90% satisfactions thereby have been first drawn based on the Universal Thermal Climate Index (UTCI). The study developed a methodology for the evaluation of dynamic outdoor thermal comfort which can be used for different climate regions.
•A year-long longitudinal questionnaire survey with outdoor thermal environment campaigns.•Quantitative evidence of past thermal experiences on outdoor thermal sensation.•Developed a new outdoor adaptive thermal comfort model.•Determined the outdoor adaptive thermal comfort zones.
The growth of cities intensifies the urban heat island effect by obstructing and weakening the incoming wind and thus deteriorates thermal comfort in the pedestrian level. The elevated building ...design is believed to be able to create some localized comfort spots at precinct scale, but no researches on pedestrians' thermal perceptions in the area underneath an elevated building (UEB) have been reported. In this study, simultaneous on-site meteorological measurements and questionnaire surveys of 1107 human subjects were conducted in a university campus in Hong Kong. Three outdoor thermal comfort models, PET, UTCI and UC-Berkeley model, were compared. The survey results indicate that the UEB area is significantly (α = 0.05) more comfortable in hot weather without extra discomfort in cold weather. All three models outputs correlate well with the subjects' mean thermal sensation votes in linear regression (R2 ≈ 0.9). Yet, shifts in neutral indices (6.2 K, 5.8 K and 1.1 respectively for PET, UCTI and UC-Berkeley model) appeared when comparing the correlation results separately for the UEB areas and open areas, indicating that the impacts of solar radiation and wind or the lack of them on pedestrian's thermal comfort perceptions have not been well predicted by the three models. These investigations, on the one hand, characterize the benefits that elevated building designs have on the pedestrian-level microclimate and provide references and inspirations for urban planners to enhance pedestrian thermal comfort by altering building designs; on the other hand, indicate the need to refine the thermal comfort models for better outdoor thermal comfort assessment.
•Underneath-elevated-building and open areas mainly differ in radiation and wind.•Area underneath elevated building is significantly more comfortable in hot weather.•PET, UTCI and UC-Berkeley outputs correlate well with Mean Thermal Sensation Vote.•Extra considerations of radiation and wind are required to improve model predictions.
This article reviews the literature on the Indoor Environment Quality of a built environment. Thermal comfort is a complex concern and the methods studied so far are only approximate. The first part ...of this review deals with the general description of the topic. This was followed by the classification of the literature published in the last fifty years based on the year of publication, methodologies adopted and comfort parameters studied. The main focus remained on a notable number of articles from recent years. In the following sections, the different factors responsible for the IEQ and its effects on the well-being and thermal comfort of the occupants are discussed. The next part deals with the evaluation of thermal comfort using various models and indices of thermal comfort described by the various literature. A range of IEQ-related issues, such as sick body syndrome, cold drafts, hot, and cold radiation are discussed. This study reviews the literature that signifies the importance of IEQ and factors that affect human thermal comfort. It documents how physical, psychological, personal, and environmental factors affect human thermal comfort, and efforts have been made to simplify a rather complex relationship between comfort parameters, occupant well-being, and IEQ. The study would be useful for designers, engineers, and researchers undertaking studies in this area.
•Reviewing Indoor Environmental Quality (IEQ) parameters in different aspects and their importance.•Current procedures to assess indoor thermal comfort at present and limitations.•Discrepancy and importance of various thermal comfort assessment models.•The numerical simulation is mostly used for thermal comfort study, while field experiment is primarily for indoor environment quality which need more attentions.
Outdoor thermal comfort in urban spaces is known as an important contributor to pedestrians' health. The urban microclimate is also important more generally through its influence on urban air quality ...and the energy use of buildings. These issues are likely to become more acute as increased urbanisation and climate change exacerbate the urban heat island effect. Careful urban planning, however, may be able to provide for cooler urban environments. Different urban forms provide different microclimates with different comfort situations for pedestrians. In this paper, singular East–West and North–South, linear East–West and North–South, and a courtyard form were analysed for the hottest day so far in the temperate climate of the Netherlands (19th June 2000 with the maximum 33 °C air temperature). ENVI-met was used for simulating outdoor air temperature, mean radiant temperature, wind speed and relative humidity whereas RayMan was used for converting these data into Physiological Equivalent Temperature (PET). The models with different compactness provided different thermal environments. The results demonstrate that duration of direct sun and mean radiant temperature, which are influenced by urban form, play the most important role in thermal comfort. This paper also shows that the courtyard provides the most comfortable microclimate in the Netherlands in June compared to the other studied urban forms. The results are validated through a field measurement and calibration.
•Outdoor thermal comfort of singular, linear and courtyard forms are studied in a summer day.•The Singular shape receives the longest and the courtyard the shortest direct sun.•Averages of Ta and Tmr are the lowest for the courtyard.•The courtyard provides 81% comfortable hours while the others less than 38%.
A personal comfort model is a new approach to thermal comfort modeling that predicts an individual's thermal comfort response, instead of the average response of a large population. It leverages the ...Internet of Things and machine learning to learn individuals' comfort requirements directly from the data collected in their everyday environment. Its results could be aggregated to predict comfort of a population. To provide guidance on future efforts in this emerging research area, this paper presents a unified framework for personal comfort models. We first define the problem by providing a brief discussion of existing thermal comfort models and their limitations for real-world applications, and then review the current state of research on personal comfort models including a summary of key advances and gaps. We then describe a modeling framework to establish fundamental concepts and methodologies for developing and evaluating personal comfort models, followed by a discussion of how such models can be integrated into indoor environmental controls. Lastly, we discuss the challenges and opportunities for applications of personal comfort models for building design, control, standards, and future research.
•Framework for personal comfort models to predict individuals' thermal comfort.•Literature review on personal comfort models.•Methodologies that leverage the Internet of Things and machine learning.•System architecture for integrating personal comfort models in indoor environmental controls.•Challenges and opportunities for model applications in design, control, standards, and future research.
In recent years, walkability is increasingly integrated into sustainability strategies, considering its many health and environmental benefits. Besides, thermal comfort also has been progressively ...promoted as a critical measure for pedestrian comfort and wellbeing. Despite the relevance of the two concepts, few studies combined them in a comprehensive model. This study considers thermal comfort in assessing walkability by developing a new measurement tool, the Street Walkability and Thermal Comfort Index (SWTCI), which focuses on comfort facilities and Physiological Equivalent Temperature (PET), at the street scale. The applied point system method requires combining a questionnaire survey, observations, and in situ measurements (air temperature, wind velocity, and relative humidity). The questionnaire survey (330 responders) measured 21 street design indicators' importance, using a five-point Likert scale ranging from 1 (least important) to 5 (very important). The observation technique seeks to evaluate every pedestrian comfort indicator score (Sis). The in situ measurements permit Envi-met's calibrated data validation and getting the mean radian temperature (Tmrt). Those were considered in the PET's calculation using Rayman software. Three distinct streets have been chosen in Annaba city, Algeria, within the Mediterranean climate (Csa). The results show that the SWTCI achieves its highest score on the three streets when the thermal perception is neutral (20 < PET <26), and its lowest score, with a warm thermal sensation (28 < PET < 31). Despite the divergence in PET values, the highest score of SWTCI was 33%, reflecting a low comfort quality and minimal pedestrian facilities. Applying the SWTCI method can transform uncomfortable streets into an ideal walkable and pleasant path by finding the problems and proposing improvements.
Display omitted
•SWTCI tool combines walkability and thermal comfort at the street scale.•Exploration of PET and pedestrian comfort facilities became a systematic method.•PET assessment is based on the calibration process in the Mediterranean climate.•PET comfort range has a considerable effect on the SWTCI average.•Applying this method can transform uncomfortable streets into ideal walkable paths.
India is witnessing unprecedented growth trends in building construction, particularly office spaces. Indian offices are designed to operate at 22.5 ± 1 °C all year round to meet the stringent “Class ...A” specifications outlined by international standards in the absence of an India-specific comfort standard. This paper proposes an India Model for Adaptive Comfort – IMAC – based on the field surveys administered in 16 buildings in three seasons and five cities, representative of five Indian climate zones. A total of 6330 responses were gathered from naturally ventilated, mixed mode and air-conditioned office buildings using instantaneous thermal comfort surveys.
Occupants in naturally ventilated Indian offices were found to be more adaptive than the prevailing ASHRAE and EN models would suggest. According to the IMAC model, neutral temperature in naturally ventilated buildings varies from 19.6 to 28.5 °C for 30-day outdoor running mean air temperatures ranging from 12.5 to 31 °C. This is the first instance where a study proposes a single adaptive model for mixed mode buildings asserting its validity for both naturally ventilated and air-conditioned modes of operation in the building, with neutral temperature varying from 21.5 to 28.7 °C for 13–38.5 °C range of outdoor temperatures. For air-conditioned buildings, Fanger's static PMV model was found to consistently over-predict the sensation on the warmer side of the 7-point sensation scale.
•A single adaptive model is proposed for NV and AC modes of operation.•Indian office occupants are more adaptive than predicted by ASHRAE-55 and EN15251 models.•International comfort standards are not appropriate for Indian office buildings.•Occupants in MM offices are more adaptive than those in AC and less adaptive than those in NV offices.•Fan and window operation, change in clothing are significant adaptive measures in NV offices.
PDF
