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In the field investigation of rural dwellings, it was found that thermal feelings are significantly different with varied envelopes even under the same indoor air temperature, and this paper explores the phenomenon in simulation. Based on building thermal investigations in several villages of North China, a typical energy and environment simulation model for rural residences was developed using DeST, and the hourly parameters of temperature and humidity were used to calculate the adaptive thermal comfort (APMV) of the rooms. The results show that the main reason for the different thermal comfort at the same air temperature is the large difference in the inner surface temperature. By adjusting the insulation thickness of the envelope structure, the relationship between it and the APMV value is obtained. By adjusting the insulation thickness of the enclosure structure and getting the correlation between it and the APMV value, it is obtained that when the heat transfer coefficient of the enclosure structure meets 0.5 W/(m2·K), the indoors can be in thermal comfort. This paper considers that the indoor air temperature cannot represent the APMV to evaluate the indoor thermal comfort, and the APMV value should be used to evaluate the thermal comfort of the renovated building and calculate the corresponding energy saving rate.

Ecuador is a country with several climate zones. However, their behaviour is similar throughout the year, with no peaks of extreme temperatures in the various seasons. This paper is a first approach to study the adaptive comfort behaviour in several areas and populations of the country. Considering the ASHRAE 55-2020 model, energy simulation programmes are applied not just to the current climate scenario but also to the climate change scenarios of 2050 and 2100. The results of locations are analysed and compared to determine their performance. Thanks to their climate characteristics, adaptive comfort models could be applied as a passive strategy, using natural ventilation for building indoor comfort improvement, particularly social dwellings. According to previous studies, some prototypes have not considered the climate determinants in each region. Given the geographic situation of the study areas, the adaptive comfort model could be applied in all cases. Percentages of application of natural ventilation and heating and cooling degree hours have similar behaviours according to the climatic region, with a variation greater than 30% among them.

Thermal comfort has an important role in human life, considering that people spend most of their lives in indoor environments. However, the necessity of ensuring the thermal comfort of these people presents an important problem, calculating the thermal comfort accurately. The assessment of thermal comfort has always been problematic, from past to present, and the studies conducted in this field have indicated that there is a gap between thermal comfort and thermal sensation. Although recent studies have shown an effort to take human psychology into account more extensively, these studies just focused on the physiological responses of the human body under psychological disturbances. On the other hand, the mood state of people is one of the most significant parameters of human psychology. Thus, this paper investigated the effect of occupants’ mood states on thermal sensation; furthermore, it introduced a novel “Mood State Correction Factor” (MSCF) to the existing thermal comfort model. To this aim, experiments were conducted at a mixed-mode building in a university between 15 August 2021 and 15 August 2022. Actual Mean Vote (AMV) and Profile of Mood States (POMS) were used to examine the effect of mood state on thermal sensation. The outcomes of this study showed that in the mood states of very pessimistic and very optimistic, the occupants felt warmer than the calculated one and the MSCFs are calculated as −0.125 and −0.114 for the very pessimistic and very optimistic mood states, respectively. It is worth our time to note that the experiments in this study were conducted during the COVID-19 Global Pandemic and the results of this study could differ in different cultural backgrounds.

This paper investigates adaptive thermal comfort during summer in medical residences that are located in the French city of Troyes and managed by the Association of Parents of Disabled Children (APEI). Thermal comfort in these buildings is evaluated using subjective measurements and objective physical parameters. The thermal sensations of respondents were determined by questionnaires, while thermal comfort was estimated using the predicted mean vote (PMV) model. Indoor environmental parameters (relative humidity, mean radiant temperature, air temperature, and air velocity) were measured using a thermal environment sensor during the summer period in July and August 2018. A good correlation was found between operative temperature, mean radiant temperature, and PMV. The neutral temperature was determined by linear regression analysis of the operative temperature and Fanger’s PMV model. The obtained neutral temperature is 23.7 °C. Based on the datasets and questionnaires, the adaptive coefficient α representing patients’ capacity to adapt to heat was found to be 1.261. A strong correlation was also observed between the sequential thermal index n(t) and the adaptive temperature. Finally, a new empirical model of adaptive temperature was developed using the data collected from a longitudinal survey in four residential buildings of APEI in summer, and the obtained adaptive temperature is 25.0 °C with upper and lower limits of 24.7 °C and 25.4 °C.

Retrofitting heritage buildings for energy efficiency is not always easy where cultural values are highly concerned, which requires an integrated approach. This paper aims to assess the potential of applying passive retrofitting scenarios to enhance indoor thermal comfort of heritage buildings in North Africa, as a hot climate, a little attention has been paid to retrofit built heritage in that climate. A mixed-mode ventilation residential building in Cairo, Egypt, was selected as a case study. The study combines field measurements and observations with energy simulations. A simulation model was created and calibrated on the basis of monitored data in the reference building, and the thermal comfort range was evaluated. Sets of passive retrofitting scenarios were proposed. The results (based on the ASHRAE-55-2020 adaptive comfort model at 90% acceptability limits) showed that the annual thermal comfort in the reference building is very low, i.e., 31.4%. The application of hybrid passive retrofitting scenarios significantly impacts indoor thermal comfort in the reference building, where annual comfort hours of up to 66% can be achieved. The originality of this work lies in identifying the most effective energy measures to improve indoor thermal comfort that are optimal from a conservation point of view. The findings contribute to set a comprehensive retrofitting tool that avoids potential risks for the conservation of residential heritage buildings in hot climates.

Heating, ventilation and air-conditioning (HVAC) systems play a key role in shaping the built environment. However, centralized HVAC systems cannot guarantee the provision of a comfortable thermal environment for everyone. Therefore, a personalized HVAC system that aims to adapt thermal preferences has drawn much more attention. Meanwhile, occupant-related factors like skin temperature have not had standardized measurement methods. Therefore, this paper proposes to use infrared thermography to develop individual thermal models to predict thermal sensations using three different feature sets with the random forest (RF) and support vector machine (SVM). The results have shown the correlation coefficients between clothing surface temperature and thermal sensation are 11% and 3% higher than those between skin temperature and thermal sensation of two subjects, respectively. With cross-validation, SVM with a linear kernel and penalty number of 1, as well as RF with 50 trees and the maximum tree depth of 3 were selected as the model configurations. As a result, the model trained with the feature set, consisting of indoor air temperature, relative humidity, skin temperature and clothing surface temperature, and with linear kernel SVM has achieved 100% recall score on test data of female subjects and 95% recall score on that of male subjects.

This paper focuses on thermal environmental conditions in the stone dwellings of a Tibetan village in Danba County, Sichuan, China, in winter. During the study, field measurements and subjective survey studies were collected, simultaneously, to provide a comprehensive understanding of the thermal comfort conditions that were experienced by residents in cold rural areas of Sichuan. Subjective surveys involved questions about thermal comfort perceptions and acceptability in cold conditions. The status of thermal comfort and characteristics of indoor environmental qualities were investigated in the study. The majority of survey participants (47% and 74%) voted as “slightly cool” for temperature, and “slightly dry” for humidity in the studied typical winter days, respectively. The available adaptive opportunities for the residents were investigated through the survey studies. Adjusting clothing, drinking hot beverages, blocking air infiltration through windows, and changing activities were the most common adaptive measures. An adaptive coefficient ( λ ) was determined based on adaptive predicted mean votes (aPMV) models using least square methods to assess the different adaptation measures in the region. Findings of this study provided a valuable reference for thermal comfort adaptations in cold climates, where limited adaptive opportunities were available due to the low standard of living.