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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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

There is a growing need for accurate and interpretable machine learning models of thermal comfort in buildings. Physics-informed machine learning could address this need by adding physical consistency to such models. This paper presents metamodeling of thermal comfort in non-air-conditioned buildings using physics-informed machine learning. The studied metamodel incorporated knowledge of both quasi-steady-state heat transfer and dynamic simulation results. Adaptive thermal comfort in an office located in cold and hot European climates was studied with the number of overheating hours as index. A one-at-a-time method was used to gain knowledge from dynamic simulation with TRNSYS software. This knowledge was used to filter the training data and to choose probability distributions for metamodel forms alternative to polynomial. The response of the dynamic model was positively skewed; and thus, the symmetric logistic and hyperbolic secant distributions were inappropriate and outperformed by positively skewed distributions. Incorporating physical knowledge into the metamodel was much more effective than doubling the size of the training sample. The highly flexible Kumaraswamy distribution provided the best performance with R2 equal to 0.9994 for the cold climate and 0.9975 for the hot climate. Physics-informed machine learning could combine the strength of both physics and machine learning models, and could therefore support building design with flexible, accurate and interpretable metamodels. [ABSTRACT FROM AUTHOR]

The Mandya district of Karnataka, India, houses a unique Jain settlement constructed about 1000 years ago. Recent excavations by the Archaeological Survey of India (ASI) indicate a high degree of engineering skills among the builders of this settlement. Adapting to heat-stresses in a region where the Monsoons often failed was and is still a matter of concern. Ingenious methods were adopted to modulate bioclimatic responses to maintain thermal comfort indices. The Aretippurians used composite building fabrics which modulated heat transfer to the interiors. Indeed, the thermal transmittances for these composite fabrics were low to moderate for both the temple complexes as well as the dormitories; these were 0.27 Wm−1K−1 and 0.23 Wm−1K−1, respectively. A site visit revealed that a unique and engineered micro-climate was also made to prevail on this hilltop settlement housing several hundred Jain settlers. A granite skirted reservoir was indeed the pièce-de-résistance promoting hydraulic air-conditioning for eight months of the year around the premises with copious winds blowing over a large and exposed rain-fed reservoir. This fanned chilled air across the open plan temples, courtyards, and lived-in areas. This paper explores bioclimatic responses for around 120 residents to the prevailing indoor settings modulated by an engineered microclimate. This was possible because of the staggered layout, unique building forms, use of mixed building fabric, and carefully chosen glazing ratios which yielded salubrious settings. Clearly, this entailed a complex interplay between the intercepted solar insolation, structure-driven turbulence, and the transfer of heat across the original composite walls within and around the complex, requiring a systematic experimental as well as modelling study. The experimental part of the project involved the calculation of the thermal transmittivity across the walls made up of fired bricks, granite, and limestone, and the theoretical part involved the use of appropriate software to reconstruct air flow and heat distribution across floors, walls, and ceilings to proxy the original flow pattern yielding the comfortable PMV (predicted mean vote) and PET (physiological equivalent temperature) values within these premises. This exercise may well lead to further explorations on indoor comfort adaptations in tropical settings with the use of many edifying vernacular idioms in ancient settlements which prevail even in modern layouts. [ABSTRACT FROM AUTHOR]

Since indoor clothing insulation is a key element in thermal comfort models, the aim of the present study is proposing an approach for predicting it, which could assist the occupants of a building in terms of recommendations regarding their ensemble. For that, a systematic analysis of input variables is exposed, and 13 regression and 12 classification machine learning algorithms were developed and compared. The results are based on data from 3352 questionnaires and 21 input variables from a field study in mixed-mode office buildings in Spain. Outdoor temperature at 6 a.m., indoor air temperature, indoor relative humidity, comfort temperature and gender were the most relevant features for predicting clothing insulation. When comparing machine learning algorithms, decision tree-based algorithms with Boosting techniques achieved the best performance. The proposed model provides an efficient method for forecasting the clothing insulation level and its application would entail optimising thermal comfort and energy efficiency. [ABSTRACT FROM AUTHOR]

• The physiological equivalent temperature (PET) and the universal thermal climate index (UTCI) are considered adaptive thermal comfort evaluation indices applicable to transition space. • The strong wind is prone to occur in winter on Huajiang campus. It is important to take precautions against the discomfort caused by a strong wind. • The outdoor thermal comfort condition of Huajiang campus in summer is better than it in winter. • Adjusting the coverage of lawn, marble floor, water surface and landscape trees can effectively regulate the microclimate of the library's inner courtyard space. The inner courtyard is an important transition space for mass exchange and heat transfer between the internal space of courtyard buildings and the external environment. A good layout of courtyard space is conducive to building energy efficiency and human thermal comfort. In the paper, we analyze the impacts of different design schemes of the spatial layout on the microclimate of inner courtyard space using field measurements and numerical simulation methods. The analysis of the measured data presents the main meteorological factors affecting the thermal comfort of the courtyard. The magnitude of the effects is ranked as air temperature, total solar radiation intensity, near-surface air flow rate, and relative humidity. Results of the ENVI-met simulation show that changing the cover of different underlying surface types leads to different microclimate regulation effects in the sense that the temperature and relative humidity in summer drops up to 3.53 °C and 15.59%, respectively and in winter increase up to 3.97 °C and 37.21%, respectively. This paper proposes that lawn ground, marble ground, water surface and landscape tree coverage of 25%, 25%, 50% and 75%, respectively, are suitable design schemes for the inner courtyard space of library. [ABSTRACT FROM AUTHOR]

It has been found in recent years that using setpoint temperatures based on adaptive thermal comfort models is a successful method of energy conservation. Recent studies using adaptive setpoint temperatures incorporate international models from ASHRAE Standard 55 and EN16798-1. This study, however, has instead considered a regional Brazilian adaptive comfort model. This study investigates the energy demand arising from the use of a local Brazilian comfort model in order to assess the energy implications from the use of the worldwide ASHRAE Standard 55 adaptive model and various fixed setpoint temperatures. All of Brazil's climate zones, full air-conditioning, mixed-mode building operating modes, present-day climate change scenarios, and future scenarios—specifically Representative Concentration Pathways (RCP) 2.6, 4.5, and 8.5 for the years 2050 and 2100—have all been taken into account in building energy simulations. The use of adaptive setpoint temperatures based on the Brazilian local model considering mixed-mode has been found to significantly reduce energy consumption when compared to static setpoint temperatures (average energy-saving values ranging from 52% to 58%) and the ASHRAE 55 adaptive model (average values ranging from 15% to 21%). Considering climate change and the mixed-mode Brazilian model, the overall energy demand for the three groups of climatic zones (annual average outdoor temperatures ≤ 21 °C, > 21 and ≤ 25 °C and > 25 °C) ranged between 2% decrease and 5% increase, 4% and 27% increase, and 13% and 45% increase, respectively. It is concluded as a consequence that setting setpoint temperatures based on the Brazilian local adaptive comfort model is a very efficient energy-saving method. [ABSTRACT FROM AUTHOR]

The residential Heating Ventilation and Air-Conditioning (HVAC) system use around 3/5 of the total energy consumption. Connected thermostats optimize the HVAC operation; however, householders have personality traits that lead into behavioral and usability problems toward the thermostat's interface usage. Thus, a serious game applied in the thermostat interface can balance entertainment and education. Therefore, thermostat interfaces must address strategies that reduce energy without losing thermal comfort. This paper proposed an interactive interface type and a predicted interface type based on an HVAC strategy and a Natural Ventilation strategy. These strategies measured the impact of adaptive thermal comfort, energy consumption, and costs. Hence, twelve energy models located in California (Concord, Riverside, Los Angeles, and San Diego) were simulated using EnergyPlus™ through LadybugTools. The first interactive interface included Serious Game elements, so the householder interacted with the date, location, and setpoint. The second interface predicted the energy consumption and thermal comfort during winter and summer in Concord by a two-layer feed-forward Artificial Neural Network structure. The proposed structure decreases the energy consumption by at least 62% without losing thermal comfort.

The present investigation carries out a thermal evaluation of two rooms located in the Royal Hospital of Granada (Rector's Office). This is a heritage building where have been done studies that allow the as-sessment of possible improvements in future interventions that guarantee improvement in en-ergy and regulatory compliance are decisive. This article presents for the first time, through energy simulation, the behavior of two rooms in two temporal periods, thermally extreme (summer and winter) and with opposite orientations. This has allowed the potential benefits to be considered in real climate conditions. The results demonstrate and quantify that considering the location, orientation, arrangement of openings, and inclusion of transition zones between the exterior and the interior, an improvement in thermal comfort is obtained. The southwesterly orientation is favorable in the winter period and the northeasterly orientation in the summer period. It is also confirmed that the arrangement of thick masonry walls responds adequately in climates with high thermal amplitudes, favoring the mitigation of extreme conditions. It is concluded by stating that the orientation and the construction components are the main responsible factors for the thermal capacity in this type of building. In this context, the use of non-destructive study methods offers valuable scientific support through the results obtained. [ABSTRACT FROM AUTHOR]

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.

• Provided a platform to test various residential building control systems. • Used probability of occupancy to determine setback temperature when unoccupied. • Integrated optimizer with adaptive and occupancy control. • Generated dynamic electricity tariff based on wholesale electricity pricing. • Evaluated the peak load shaving potential with dynamic pricing and optimization. Energy consumption in buildings continues to rise with increased deployment of energy-consuming equipment such as Heating, Ventilation, and Air Conditioning (HVAC) amid a growing world economy. Renewable energy is projected to comprise a majority of the future electricity supply, but the intermittent nature of renewables means that consumption must respond to dynamic supply for optimal utilization. This paper proposes a novel HVAC control strategy for residential buildings using the adaptive comfort model, considering occupancy through probability and real-time information, and optimizing the HVAC schedule to reduce cost, maintain thermal comfort, and respond to the dynamic availability of renewable energy while being generalizable to different situations. To validate this approach, the Universal CPS Environment for Federation (UCEF) co-simulation platform is used to connect advanced building controls with the building energy simulation software EnergyPlus. Simulations are performed for a residential building in Sacramento, CA during a typical summer week. Economic impacts, energy consumption, and thermal comfort are analyzed for traditional, adaptive, and occupancy-based control strategies under demand-based, tiered, and fixed electric tariff systems. Simulation results show that occupancy consideration, adaptive thermal comfort, and optimization can reduce cost by 50.1 %, electricity consumption by 52.9 %, and discomfort by 56.2 % compared to traditional fixed setpoints. The ability of the proposed HVAC control strategy to shift energy consumption away from peak times under a demand-based tariff system is qualitatively analyzed and findings suggest that maximum load-shifting on a grid-scale is attained using occupancy consideration with optimized control and demand-based pricing. For individual residential buildings, similar economic benefits can be gained using the less-complex adaptive HVAC control strategy with existing tiered or simple electric tariff systems. [ABSTRACT FROM AUTHOR]

Semi-Transparent Photovoltaic (STPV) windows have the potential of active energy-saving and have attracted more attention in recent years. Due to the selective absorption effect of solar cells on solar radiation, the indoor thermal environment and human thermal comfort of buildings integrated with STPV windows are considerably different from that with clear glass windows, and there are few studies on this. In this paper, the indoor human thermal comfort of buildings integrated with STPV window was investigated. Firstly, experiments and subjective questionnaires for the indoor environment were conducted in STPV and clear glass window buildings respectively. Secondly, the influence of illuminance on thermal sensation was statistically analyzed, with the consideration of visual effect, non-visual effect, as well as visual and non-visual coupling effect respectively. On this basis, an innovative thermal comfort evaluation method was provided. The thermo-physiological effect, light-physiological effect and light-psychological effect were comprehensively considered in this method. Finally, the reliability was verified by comparing with TSV. According to tests and questionnaires, it was found that the indoor thermal environment of the STPV window was an uneven thermal environment, and the subjective thermal sensation was more inclined to be slightly warm. When investigating the effect of illuminance on thermal sensation considering visual and non-visual coupling effect, it was found that illuminance had a significant influence on thermal sensation in different illuminance ranges. Meanwhile, it indicated the coupled effect of thermal environment and daylight environment on the thermal comfort of human. • The thermal environment and human thermal sensation for buildings integrated with STPV window are studied. • The influence of illuminance on human thermal comfort through visual effect and non-visual effect is investigated. • An adaptive thermal comfort evaluation method for buildings integrated with STPV window is proposed. [ABSTRACT FROM AUTHOR]

• A study on housing stock improvement potential in Mediterranean areas is presented. • Three typical case studies were chosen from the stock of a southern Spanish city. • Monitoring on environmental and electricity data and tests logged real performance. • Energy models were built and adjusted based on real occupancy conditions. • The considered building retrofits raise indoor temperature and reduce discomfort. Renovating buildings is one of the major targets within the current European goals toward decarbonized cities in 2050. The residential stock offers extensive opportunities to achieve current energy horizons, since more than 75% of the existing buildings in the European Union are energy deficient, with poorly insulated thermal envelopes which drive indoor conditions far from current comfort standards. This paper aims to provide a protocol for forecasting the upgrading potential of this housing stock in southern Europe, particularly in Mediterranean areas, identifying the level of obsolescence and possibilities for improvement, especially in winter indoor thermal conditions, offered by standard passive strategies. Following an architectural, constructive, and energy analysis of common patterns throughout the urban stock of the southern Spanish city of Córdoba, three case studies built-in 1951–1980 – pre-dating the first Spanish regulations on thermal conditioning in buildings – were selected for the assessment. Long-term monitoring and in situ tests (i.e., infrared thermography, airtightness) recorded the performance of these buildings under real occupancy conditions, subsequently incorporating them into the calibration of simulation energy models, aiming to predict the potential improvements after implementing standard passive strategies in these buildings. Results show that building retrofits not only improve the quality of indoor thermal conditions by increasing indoor temperatures by 3–4 °C but also almost eliminate occupied hours outside the comfort range. [ABSTRACT FROM AUTHOR]

The outdoor thermal environment is an important factor when measuring the livability of a city. Residents will avoid intense heat by reducing their outdoor activities, which decreases the vitality of a city and increases the energy consumed for air conditioning. Outdoor thermal comfort has a great impact on outdoor activities; therefore, we need to evaluate and design the urban outdoor thermal environments in cold regions to improve the outdoor thermal comfort level. In this study, we conducted a questionnaire survey to assess the outdoor thermal comfort and adaptive thermal comfort in four different urban forms in Xi'an during July 2019, and measuring meteorological parameters, such as the temperature, relative humidity, wind speed, and black bulb temperature. The results are showed as follows. (1) In the cold study area, urban residents generally perceived the outdoor climate as relatively hot during the summer. (2) The participants exhibited psychological and physical adaptations in terms of their thermal comfort. In particular, when the PET was 30 °C, the MTCV was about 1.25 points higher in the later summer period than the early summer period. (3) The neutral PET differs among regions, and it is affected by the climate zone and latitude. Comparisons of our results with thermal comfort studies in different regions such as Singapore and Umeå in north Sweden showed that the thermal comfort is correlated with the regional climate and latitude. The neutral PET is higher in tropical regions. Our findings support the theoretical understanding of adaptive thermal comfort in cold regions and they provide a reference for formulating policies related to adaptive thermal comfort. [ABSTRACT FROM AUTHOR]

Evaporative cooling systems (ECS) in buildings, which are driven by cleaner and more sustainable energy, had been widely applied in recent years especially for the dry hot regions in summer. In this study, an investigation was conducted for office buildings by using ECS in Urumqi (China) from July to August 2021. Through subjective survey and objective measurements, 577 initial questionnaires and measured data were obtained. Outcomes showed that the indoor expectative temperature (Te) was received by 26.6 °C, 0.7 °C lower than neutral temperature (Tn). And the acceptable intervals for the 90% and 80% level were obtained at 27.1–28.9 °C and 26.4–30.3 °C, respectively. It appeared to possess a wider scope than that calculated by PMV algorithm, which further indicted that subjects have adapted to the local climate. Furthermore, the adjustment PMV models (ePMV, APMV) were found to have an effectively narrow gap comparing to the actual thermal sensation vote (TSV). The appropriate usage intervals of ePMV and APMV were quantified by Top < 27.6 °C/Top > 29.8 °C, 27.6 °C < Top < 29.8 °C, respectively. These findings may provide reference values for the revision of local energy-saving standard to some extent. [ABSTRACT FROM AUTHOR]

Due to its excessive energy consumption, the building sector contributes significantly to greenhouse gas (GHG) emissions. The type of thermal comfort models used to maintain the comfort of occupants has a direct influence on forecasting heating and cooling demands and plays a critical role in reducing actual energy usage in the buildings. In this research, a typical residential building was simulated to compare the heating and cooling loads in four different Jordanian climates when using an adaptive thermal model versus the constant setting of temperature limits for air-conditioning systems (19–24 °C). The air-conditioning system with constant temperature settings worked to sustain thermal comfort inside the building, resulting in a significantly increased cooling and heating load. By contrast, significant energy savings were achieved using the temperature limits of an adaptive thermal model. These energy savings equated to 1533, 6276, 3951, and 3353 kWh, which represented 29.3%, 80.5%, 48.5%, and 67.5% of the total energy used for heating and cooling for zones one, two, three, and four, respectively. [ABSTRACT FROM AUTHOR]

Adaptive thermal comfort is a model which considers behavioral and psychological adjustments apart from Fanger's Predicted Mean Vote (PMV)/Percentage of Dissatisfied (PPD) method. In the literature, the differences between the PMV/PPD method and adaptive thermal comfort were mainly considered in aspects of behavioral adjustments in an environment. Conversely, limited studies related to psychological adjustments were considered in detail for thermal comfort. This study purposes to investigate the effects of current mood state subscales on thermal sensation of the occupants for the first time in the literature. To this aim, the Profile of Mood States (POMS) questionnaire is used to determine the mood state of the occupants with six different subscales: Anger, Confusion, Vigor, Tension, Depression, and Fatigue. The experiments were conducted in a university study hall in Ankara, Turkey, which is in warm‐summer Mediterranean climate (Csb) according to Köppen–Geiger Climate Classification. The distributions of each subscale were examined via Anderson Darling and Shapiro–Wilk tests accordingly given responses from the occupants. The sensitivity analysis was applied to the six subscales of the POMS with Monte Carlo simulation method by considering the distributions of each subscale. The results revealed that the current mood state has a crucial effect on the thermal sensation of the occupants. The subscales of the Depression and Vigor were found as the most vital ones among the six subscales. Only the pure effects of the Vigor and Depression would change the thermal sensation of the occupants 0.31 and 0.30, respectively. The Confusion was determined as the least effective subscale to the thermal sensation of the occupants. Moreover, with the combination of all the six subscales, the thermal sensation might change up to 1.32. Findings in this study would help researchers to develop the personalized thermal comfort systems. [ABSTRACT FROM AUTHOR]

Thermal comfort is fundamental to indoor environmental design and operation as well as indoor thermal environment evaluation. This paper has reviewed the historic evolution of thermal comfort research during the last century using a systematic approach and a particular focus on adaptive thermal comfort studies. A large number of published articles as well as standards and guides were collected and screened based on a rigorous search method to ensure the literature database was both focused and complete. A further evaluation of representative prediction models has been conducted by applying the models to a large database and comparing the differences in their performance. Based on the review analysis, three representative thermal environment assessment approaches were classified as the heat balance approach, the adaptive regression-based approach and the adaptive heat balance approach. The strengths and constraints of each approach were analyzed. Comparisons of different models in the adaptive heat balance approach were conducted using the ASHRAE databases I&II. Thermal comfort theory and approaches have been developed which underpin standards and guidelines in building and engineering system design, operation and evaluation though there are pros and cons of different methods. The heat balance approach features the detailed parameters of design criteria of indoor thermal environments. The adaptive regression-based approach played an important role in raising awareness of adaptive capacities and paved the way towards first implementations into standardization. The adaptive heat balance approach combines the heat balance and the adaptive regression approaches and leads towards future improvements in adaptive comfort modelling. It demonstrates very good performance and its inclusive approach offers potential for further breakthroughs in reducing the limitations of the existing methods. • Comprehensive literature review of the development progress of thermal comfort research. • Three representative thermal environment assessment approaches were classified. • They are the heat balance, the adaptive regression-based, and the adaptive heat balance approaches. • The adaptive heat balance approach bridges the gap of the heat balance and the adaptive regression approaches. [ABSTRACT FROM AUTHOR]

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.

Temperatures in Mediterranean cities are rising due to the effects of climate change, with a consequent increase in the heat waves frequency. Recent research has shown the tempering potential of semi-outdoor spaces such as courtyards, which are semi-enclosed spaces that are widely used by the users of buildings in Mediterranean cities. International standards addressing thermal comfort parameters provide technical guidelines for indoor spaces only. Expanding this concept, this paper focuses on the potential to extend and interpret the existing calculation models for indoor thermal comfort, EN 16798 and ASHRAE 55, to determine thermal comfort, monitoring two different courtyards in Cordoba, Spain, during both typical summer and heat wave periods. The results show that during the typical summer, the monitored courtyards can reach temperatures up to 8.4 °C cooler than outside. Subsequently can be considered to be in thermal comfort on average for 88% of the time according to EN 16798, and 75% according to ASHRAE 55, which drop to 71% and 52% respectively during heat wave (HW) periods, in spite of increasing thermal gap (TG) up to 13.9 °C. The results are also compared with the PET indicator used for evaluation of outdoor thermal comfort, which provides comparable figures: 81% summer and 73% HW. Implications of implementing passive shading strategies to increase comfort in these transition spaces are also evaluated. The research highlights the thermal potential and usefulness of courtyards in warm climates, so they can ultimately be included in the building analysis as a potentially comfortable and habitable space. • Courtyard was included in the building analysis as a comfortable and habitable space. • Comfort adaptive assessment according to EN 16798, ASHRAE 55 and PET were confronted. • Courtyard tempering achieves a TG up to 8.4 °C in summer and 13.9 °C in a heatwave. • In warm locations, courtyards can be under comfort more than 75% of the day. • Shadow quantification proves to be a major strategy regarding extreme temperatures. [ABSTRACT FROM AUTHOR]