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Thermal comfort

Thermal comfort is defined as that condition of mind which expresses satisfaction with the thermal environment and is assessed by subjective evaluation. This psychological state arises when individuals perceive neither excessive heat nor cold, enabling focus on tasks without thermal distraction, and it plays a critical role in occupant , , and in built environments. The perception of thermal comfort is primarily determined by six key factors: two personal—metabolic rate (related to ) and —and four environmental—air temperature, mean radiant temperature, air speed, and . Metabolic rates typically range from 1.0 met for sedentary office work to higher values for manual labor, while is measured in clo units, with 0.5 clo representing light summer attire and 1.0 clo typical business wear. Environmental factors interact dynamically; for instance, higher air speeds can enhance comfort in warmer conditions by promoting convective cooling, and relative between 40% and 70% is generally recommended to avoid discomfort from dryness or stickiness. Additional influences include individual differences such as , , , and , which can widen or narrow acceptable ranges. Standards like establish guidelines to achieve thermal comfort for at least 80% of occupants, using models such as the Predicted Mean Vote (PMV) and Predicted Percentage of Dissatisfied (PPD). The PMV model, developed by P.O. Fanger in the 1970s based on controlled laboratory experiments, predicts average thermal sensation on a seven-point scale (-3 cold to +3 hot) under steady-state conditions in air-conditioned spaces, aiming for a PMV near zero to minimize PPD below 10%. In contrast, the adaptive comfort model, incorporated into since 2004, applies to naturally ventilated buildings and allows broader indoor temperature ranges (up to 2.5–5°C wider than PMV predictions) by relating comfort to prevailing outdoor conditions, drawing from global field studies of over 21,000 occupant responses. These approaches balance human physiology with , informing HVAC systems, strategies, and efforts worldwide.

Definition and Importance

Definition

Thermal comfort is defined as that condition of mind which expresses satisfaction with the thermal environment, assessed through subjective evaluation. This standard definition, established in ISO 7730, emphasizes the psychological aspect of thermal perception rather than purely physiological responses. The standard was last revised in 2025 to refine evaluation methods for moderate thermal environments. The concept originated in P.O. Fanger's seminal 1970 work, which analyzed thermal sensation based on empirical studies and introduced a framework identifying six primary factors influencing comfort: two personal factors—metabolic rate and —and four environmental factors—air temperature, mean radiant temperature, air speed, and relative humidity. Fanger's analysis derived from heat balance principles, aiming to predict conditions where the achieves steady-state without discomfort. Thermal comfort differs from thermal neutrality, where an individual experiences no sensation of warmth or coolness (a neutral vote on sensation scales), as satisfaction can occur even with slight deviations from neutrality if they align with personal preferences. Thermal equilibrium underlies this, representing the balance between the body's internal heat production and its loss to the environment through mechanisms including convection (heat transfer via air movement), radiation (infrared exchange with surfaces), evaporation (sweat vaporization), respiration (moisture and heat loss from lungs), and conduction (direct contact with solids). In comfort conditions, this balance maintains core body temperature around 37°C without excessive physiological strain.

Significance

Thermal comfort plays a pivotal role in enhancing occupant , , and overall satisfaction across diverse environments, including buildings, vehicles, and outdoor spaces. In indoor settings, optimal thermal conditions have been shown to improve cognitive and reduce , leading to higher work and employee . For instance, studies indicate that each Celsius deviation from optimal temperatures (around 22°C) can decrease by approximately 2% in office environments. In vehicles, maintaining thermal balance is crucial for driver alertness and passenger well-being, as poor cabin conditions contribute to drowsiness and reduced reaction times, potentially increasing accident risks. Outdoors, comfortable microclimates encourage greater use of public spaces, promoting and benefits while mitigating effects. Economically, thermal comfort significantly influences global demands, particularly through (HVAC) systems in , which account for a substantial portion of consumption. represent approximately 30% of global final use, with HVAC operations contributing heavily to this figure and associated emissions. Achieving thermal comfort efficiently can reduce operational costs for building owners and lower utility bills for occupants, while poor management leads to inefficiencies that exacerbate in vulnerable populations. In vehicles and outdoor designs, energy-efficient comfort strategies, such as advanced or , further minimize or use without compromising . From a perspective, inadequate thermal comfort is linked to various adverse effects, including (SBS), which manifests as headaches, fatigue, and irritation in poorly ventilated or thermally inconsistent spaces. Poor indoor conditions can also aggravate respiratory issues by promoting growth or circulation due to suboptimal control. In extreme climates, thermal stress from heat or cold exposure heightens risks of cardiovascular strain, , and heat-related illnesses, disproportionately affecting outdoor workers and the elderly. These health impacts underscore the need for comfort standards to prevent morbidity and support recovery from conditions. Societally, thermal comfort highlights challenges, as access to cooling and heating technologies remains uneven, particularly in low-income and developing regions where amplifies vulnerabilities. Marginalized communities often face higher exposure to due to inadequate , leading to disparities in health outcomes and . Integration of thermal comfort considerations into initiatives, such as the Union's Green Deal and its Energy Performance of Buildings Directive (revised 2024), emphasizes net-zero standards that balance efficiency with occupant well-being, promoting inclusive designs for resilient urban environments.

Influencing Factors

Metabolic Rate

Metabolic rate refers to the rate at which the produces through metabolic processes, converting from food into and mechanical work per unit of . In thermal comfort assessments, it is quantified in "met" units, where 1 met corresponds to approximately 58 W/m², representing the heat generation of a seated person at rest. The primary factor influencing metabolic rate is the level of , which directly modulates expenditure. For instance, sleeping typically generates about 0.7 met, while light walking at around 3.2 km/h produces approximately 2.0 met. Other contributors include , such as higher muscle mass leading to elevated rates due to greater demands, and health conditions like , which can increase basal heat production through accelerated cellular metabolism. Metabolic rate is commonly calculated using indirect , a method that measures oxygen consumption and production to estimate expenditure with an accuracy of ±5% under controlled conditions. Alternatively, standardized tables in Standard 55 provide estimated values for typical activities, allowing quick application in without direct measurement. The overall production, denoted as M in W/m², is fundamentally influenced by the (BMR), which represents the minimum required for vital functions at complete rest. BMR can be estimated using the revised Harris-Benedict equation, derived from empirical data on over 200 healthy adults to predict resting needs adjusted for , , , and : For males: \text{BMR} = 88.362 + (13.397 \times \text{weight in kg}) + (4.799 \times \text{height in cm}) - (5.677 \times \text{age in years}) For females: \text{BMR} = 447.593 + (9.247 \times \text{weight in kg}) + (3.098 \times \text{height in cm}) - (4.330 \times \text{age in years}) This equation, validated against direct calorimetry measurements, forms the basis for scaling metabolic rate by activity multipliers (e.g., 1.2 for light office work) to obtain total M.

Clothing Insulation

Clothing insulation refers to the thermal resistance provided by a clothing ensemble to transfer from the body, serving as a key personal factor that modifies loss and influences thermal comfort. This resistance is quantified using the clo unit, introduced in 1941, where 1 clo equals 0.155 m²·K/W, corresponding to the insulation required for comfort by a resting person in a 21°C (70°F) environment with minimal air movement. The unit accounts for both the fabric and the air layers trapped within and around the garments, which together impede convective and radiative exchange. Standard clothing ensembles exhibit characteristic clo values that reflect typical daily attire. For instance, business attire, such as a , , and , provides approximately 1.0 clo of , while lighter summer clothing like a short-sleeve and offers about 0.5 clo. Heavier , including a and multiple layers, can reach 1.5 clo, though standards like limit applicability to ensembles below this threshold to ensure reliable comfort predictions. Several factors influence the effective of clothing beyond basic composition. Fabric type and thickness determine inherent thermal resistance, with thicker or denser materials like providing higher clo values than thin synthetics. garments additively increases by incorporating additional air pockets, though occur due to of inner layers. Fit affects by altering trapped air volume; loose enhances resistance, while tight fits reduce it through decreased air. from sweat or external sources significantly degrades , as wet fabrics conduct more readily and eliminate air layer benefits, potentially halving effective clo values in humid conditions. The total clothing insulation I_{cl} for an ensemble is calculated as the sum of individual garment insulations, with values derived from standardized tables that adjust for the effective covered by each piece to account for partial exposure of . This summation yields I_{cl} in clo units, which can be converted to thermal resistance R using the relation: R = 0.155 \times I_{cl} \quad (\mathrm{m}^2 \cdot \mathrm{K/W}) This conversion facilitates integration into broader heat balance equations for thermal comfort assessment.

Air Temperature

Air , denoted as t_a, refers to the of the air in the occupied space and acts as the dominant factor in convective , which governs the exchange of between the human body surface and the surrounding . This convective process directly influences thermal sensation: elevated air temperatures diminish the body's cooling rate, promoting warmer perceptions, while lower temperatures accelerate cooling, which may induce chill if excessive. In thermal balance models, such as the Predicted Mean Vote (PMV) framework, air temperature is a input , with its effect scaled by factors like metabolic rate and to predict overall comfort. To capture the combined influence of convection and radiation on thermal sensation, air temperature is integrated into the operative temperature (t_{op}), a composite index representing the uniform temperature of an enclosure that would yield equivalent heat transfer to the actual nonuniform environment. The operative temperature is defined by the equation: t_{op} = \frac{h_c t_a + h_r t_r}{h_c + h_r} where h_c is the convective heat transfer coefficient (typically 2-8 W/m²·K, depending on air speed), h_r is the radiative heat transfer coefficient (approximately 4.7 W/m²·K for typical indoor conditions), t_a is air temperature, and t_r is mean radiant temperature. At low air speeds below 0.2 m/s, where h_c approximates h_r, this simplifies to: t_{op} = \frac{t_a + t_r}{2} This approximation is widely applied in standards for moderate thermal environments, emphasizing air temperature's convective role while accounting for radiative contributions. For typical indoor settings involving sedentary office work and light clothing (around 0.5-1 clo insulation), comfort is generally achieved when air temperature aligns with operative temperatures of 20-24°C, corresponding to PMV values near neutral (0 ± 0.5) and predicted percentage dissatisfied below 10%. Vertical air temperature gradients exceeding 2.5-3°C between ankle and head height can cause local discomfort, such as cold feet, even within overall acceptable ranges. Air temperature also interacts with relative humidity, as elevated levels at higher temperatures reduce evaporative heat loss, intensifying discomfort in warm conditions.

Mean Radiant Temperature

The mean radiant temperature (), denoted as t_r, represents the uniform temperature of an imaginary black enclosure in which the radiant between a and its surroundings equals that in the actual nonuniform environment. This parameter quantifies the radiative component of thermal exchange, distinct from convective or conductive effects, and is essential for assessing overall thermal balance in built environments. MRT is calculated as the fourth root of the weighted of the fourth powers of surrounding surface temperatures, where weights are the view factors (also called angle factors) representing the fraction of leaving the body that reaches each surface. The view factor F_{p-i} between the person (p) and surface i accounts for , , and relative , with \sum F_{p-i} = 1. The , derived from the Stefan-Boltzmann of (q = \epsilon \sigma (T^4 - T_{\text{surr}}^4), where \sigma = 5.67 \times 10^{-8} W/m²K⁴ is the Stefan-Boltzmann constant and \epsilon is , typically 0.97 for and clothing), equates the net radiative in a nonuniform setting to an equivalent uniform one. To arrive at the solution, start with the net long-wave radiative heat loss from the body: H_r = f_{cl} \epsilon_{cl} A_p \sigma (T_{cl}^4 - \sum_{i=1}^n F_{p-i} T_i^4 ), where f_{cl} is the area factor, \epsilon_{cl} is emissivity, A_p is , T_{cl} is clothing surface temperature, and T_i are surface temperatures in . For equivalence to a uniform enclosure at MRT (t_r + 273), set T_{cl}^4 - (t_r + 273)^4 = \sum_{i=1}^n F_{p-i} (T_{cl}^4 - T_i^4), which simplifies (since \sum F_{p-i} = 1) to (t_r + 273)^4 = \sum_{i=1}^n F_{p-i} T_i^4. Thus, t_r = \left[ \sum_{i=1}^n F_{p-i} T_i^4 \right]^{1/4} - 273 where t_r is in °C and T_i in K. For example, in a simple room with four walls at temperatures 20°C, 18°C, 22°C, and 19°C, each with equal view factor 0.25 (ignoring floor/ceiling for illustration), convert to K (293, 291, 295, 292), compute \sum 0.25 \times T_i^4 \approx 7.346 \times 10^9, take fourth root ≈ 292.8 K, then t_r \approx 19.8^\circC (close to the arithmetic mean of 19.75°C for small variations). View factors for complex geometries, such as a seated person, are tabulated in standards (e.g., 0.22 for floor, 0.60 for walls combined). (Note: ASHRAE 55 references the equation per Fanger's formulation) Measurement of MRT typically involves indirect methods due to the complexity of direct computation. The black globe thermometer, a 150 mm diameter black-painted hollow with a , provides an approximation by integrating and : t_r = \left[ (t_g + 273)^4 + 0.4 \times 10^8 v_a^{0.6} (t_g - t_a) \right]^{1/4} - 273, where t_g is globe , t_a is air , and v_a is air speed in m/s (valid for 0.15–3.0 m/s). Alternatively, captures surface temperatures T_i across the field of view, followed by of view factors using software or predefined body postures. These methods ensure accuracy within ±1°C in controlled indoor settings. In indoor environments, significantly influences thermal comfort, often accounting for about half of total heat exchange under typical conditions, as dominates over when air speeds are low. Large asymmetries, such as exterior in winter-heated spaces (e.g., at 10°C versus air at 22°C), can depress by 3–5°C below air , inducing radiant cooling sensations and discomfort despite neutral air conditions; studies show such discrepancies increase predicted dissatisfaction by up to 20% per 5 asymmetry. This effect is pronounced in buildings with high or poor , highlighting 's role in for uniform surface .

Air Speed

Air speed, or air velocity, refers to the rate of air movement within an occupied indoor environment, expressed in meters per second (m/s). It is a key environmental parameter in thermal comfort assessments, as it directly affects the convective and evaporative heat exchange between the human body and the surrounding air. Air speed is typically measured using anemometers, with hot-wire anemometers being particularly effective for capturing low velocities common in indoor settings due to their sensitivity to small changes in airflow. In standard indoor environments, air speeds generally range from 0.1 to 0.3 m/s to maintain comfort without inducing unwanted sensations. Within this range, air movement provides subtle cooling without exceeding typical requirements. Air speed primarily influences thermal comfort by enhancing convective heat loss from the skin and promoting the of , which together allow occupants to tolerate higher ambient temperatures while maintaining a thermal sensation. Increased air speed accelerates the removal of the warm of air around the body, thereby boosting the overall rate of dry heat loss via and facilitating greater moisture in humid or warm conditions. This effect is particularly beneficial in spaces where mechanical cooling is limited, enabling energy-efficient comfort strategies. Thresholds for air speed are critical in balancing cooling benefits against potential discomfort. In cooling-dominated scenarios, air speeds exceeding 0.2 m/s can introduce a of , where localized convective cooling leads to uneven thermal sensations across the body. Standards recommend keeping average air speeds at or below 0.2 m/s in sedentary activities to minimize this , though higher velocities may be acceptable if uniformly distributed. The impact of air speed on convective heat loss is quantified through the convective h_c, given by the empirical : h_c = 8.3 \, v^{0.6} where h_c is in W/m²·K and v is the relative air speed in m/s, applicable for seated occupants with air movement between 0.2 and 1.0 m/s. This relation, derived from experimental studies on human , is incorporated into the body's overall balance to predict thermal and adjust comfort boundaries for varying airflow conditions.

Relative Humidity

Relative humidity () is defined as the ratio of the actual of in the air to the saturation vapor pressure of at the same , expressed as a . In the context of thermal comfort, RH typically ranges from 30% to 60%, as this interval supports satisfactory evaporative cooling and minimizes sensory irritation for most occupants under standard indoor conditions. High relative humidity impairs the evaporation of sweat from the skin, reducing the body's primary mechanism for dissipating and thereby increasing the perception of warmth, which can lead to thermal discomfort during or in warmer environments. Conversely, low relative humidity below 30% promotes excessive loss from and mucous membranes, causing dryness, , and discomfort in the eyes, nose, and throat. Relative humidity is commonly measured using psychrometers, which compare the temperatures of dry-bulb and wet-bulb thermometers to determine via evaporative cooling principles, or with electronic hygrometers that directly sense moisture content through or changes. These instruments allow for accurate assessment in indoor settings, often integrated into systems for . In thermal comfort models such as Fanger's Predicted Mean Vote (PMV), the role of relative humidity is incorporated through its influence on evaporative heat loss from the skin, which is a key component of the human heat balance equation. The evaporative heat loss due to diffusion, Esk, is given by: E_{sk} = 3.05 \times 10^{-3} \times (P_{sk} - P_a) \times f_{cl} \times h_c where Psk is the saturated water vapor pressure at the skin temperature (typically around 35.7°C for comfort conditions), Pa is the partial water vapor pressure in the ambient air (calculated as RH multiplied by the saturation vapor pressure at air temperature), fcl is the clothing area factor, and hc is the convective heat transfer coefficient (dependent on air speed). This term represents the passive moisture diffusion through the skin and clothing, distinct from active sweating, and decreases as RH rises because Pa approaches Psk, limiting the vapor pressure gradient driving evaporation. To compute Pa and related psychrometric properties, practitioners use psychrometric charts, which plot air temperature against humidity ratio or wet-bulb temperature to visualize the state of moist air; for instance, at 25°C and 50% RH, the chart yields a vapor pressure of approximately 1.58 kPa, illustrating how RH modulates the moisture content available for heat transfer. Regulatory sweating adds a separate term in the full model, but the diffusion component highlights RH's direct impact on baseline evaporative cooling.

Natural Ventilation

Natural ventilation refers to the process of supplying and removing indoor air through intentional building openings by means of wind- and buoyancy-induced pressure differences, without reliance on mechanical systems. This passive airflow leverages natural forces to facilitate thermal exchange, contributing to occupant comfort by moderating indoor temperatures and humidity levels. Key design principles enhance the efficacy of natural ventilation for thermal comfort. The , or buoyancy-driven ventilation, occurs when warmer indoor air rises and exits through higher openings, drawing cooler outdoor air in from lower levels, thereby promoting vertical airflow in multi-story structures. Cross-ventilation, achieved by placing openings on opposite or adjacent building facades, harnesses to create horizontal airflow paths, which can lower indoor air temperatures and increase air movement across occupied zones. These strategies not only reduce —potentially saving 10% to 30% of total building energy in suitable climates by minimizing mechanical cooling needs—but also improve by diluting contaminants and providing fresh air exchange. Despite these advantages, natural ventilation faces significant challenges related to variability and , particularly in diverse climatic conditions. Performance is highly sensitive to fluctuating speeds, directions, and outdoor temperatures, which can lead to inconsistent indoor conditions and failure to maintain thermal comfort during , such as heatwaves exceeding 35°C. In warm climates, single-sided ventilation often underperforms, while even cross-ventilation may not suffice without supplemental measures, complicating precise over to avoid overcooling in winter or pollutant ingress from urban environments. Ventilation effectiveness in natural systems is commonly quantified using (ACH), which measures the number of complete air volume replacements within a over one hour, with typical comfort targets ranging from 4 to 10 ACH depending on building use and climate. Standard 62.1 recommends minimum outdoor airflow rates of 5 to 10 L/s per person for occupied s to ensure acceptable while supporting thermal comfort, though higher rates may be needed in naturally ventilated designs to offset elevated air speeds for cooling.

Thermal Sensation and Discomfort

Predicted Mean Vote and Predicted Percentage of Dissatisfied

The Predicted Mean Vote (PMV) and Predicted Percentage of Dissatisfied (PPD) method, developed by P.O. Fanger in 1970, provides a heat balance-based approach to predict overall thermal sensation and dissatisfaction in indoor environments. This model derives from experimental studies involving human subjects in controlled climate chambers, aiming to quantify the thermal load on the body relative to comfort conditions. The PMV index represents the predicted average vote of a large group of occupants on the seven-point thermal sensation scale, ranging from -3 () to +3 (hot), with 0 indicating thermal neutrality. The associated PPD index estimates the proportion of individuals expected to feel thermally dissatisfied, forming a nonlinear relationship with PMV where dissatisfaction rises symmetrically above and below neutrality, reaching a minimum of about 5% at PMV = 0. The PMV calculation integrates six primary factors—metabolic rate, , , mean radiant temperature, air speed, and —into a steady-state balance equation for the . These inputs account for both personal variables, such as metabolic rate (typically 58 W/m² for office work) and (around 0.5 clo for light business attire), and environmental parameters that influence exchange. The core PMV equation is derived by comparing the actual heat balance to an idealized comfort balance, where and sweat rate are fixed at optimal values (approximately 33.5°C and 0.06 g/h·m², respectively) based on empirical from comfort experiments. The full PMV equation is given by: \text{PMV} = (0.303 \, e^{-0.036 M} + 0.028) \times \left[ (M - W) - E - C - R - K - S \right] where M is the metabolic rate (W/m²), W is the external work (typically 0 for sedentary tasks), E is the total evaporative heat loss, C is the convective heat loss, R is the radiative heat loss, K is the conductive heat loss, and S is the rate of heat storage (set to 0 in steady state). Each heat loss term is computed using detailed sub-equations involving the input factors; for instance, E combines diffusive and regulatory evaporation modulated by relative humidity and clothing permeability, while C and R depend on air speed, temperatures, and surface emissivity. The derivation involves iterative solving to match the body's heat production to losses under comfort assumptions, as originally formulated in Fanger's work and later standardized. Once PMV is determined, PPD is calculated as: \text{PPD} = 100 - 95 \exp \left[ - (0.03353 \, \text{PMV}^4 + 0.2179 \, \text{PMV}^2) \right] This equation reflects empirical observations that even at neutrality, a small fraction remains dissatisfied due to individual variability. Practical implementation often relies on software tools, such as the , which automates the computations, handles iterative solutions, and visualizes compliance with standards like by plotting PMV/PPD against environmental conditions. Despite its widespread adoption in standards such as ISO 7730 and , the PMV/PPD model has limitations, including its assumption of steady-state conditions where environmental parameters and activity levels remain constant over time. It is primarily validated for sedentary, office-like indoor settings with air speeds below 0.2 m/s and temperatures between 10–30°C, potentially underperforming in dynamic or non-uniform environments.

Local Discomfort Types

Local thermal discomfort arises when specific body parts experience sensations of cooling or warming that deviate from overall body comfort, often due to uneven environmental exposures. Common types include radiant asymmetry, draughts, floor surface temperatures, and vertical air temperature gradients. These localized issues can lead to complaints even when the overall thermal environment meets general comfort criteria, affecting occupant satisfaction and productivity. Standards such as ISO 7730 and provide assessment limits to minimize the percentage of dissatisfied individuals to below 10%. Radiant temperature asymmetry occurs when there is a significant difference in plane radiant temperature between opposing surfaces, causing uneven radiant heat exchange on the body. Vertical radiant , such as from a ceiling or warm floor, is limited to less than 5 to avoid discomfort, while horizontal asymmetry from side walls is restricted to under 10 per ISO 7730 criteria. This asymmetry can lead to sensations of chill or warmth on exposed , particularly in spaces with large glazed areas or single-sided heating. Draughts, defined as unwanted local cooling from air movement, arise when mean air velocity exceeds 0.15 m/s combined with turbulence intensity greater than 0.05, often from HVAC diffusers or open windows, resulting in convective cooling of the face, neck, or limbs. Floor surface temperature extremes cause discomfort at the feet and ankles due to direct conduction. Operative temperatures below 19 °C induce sensations, prompting behaviors like wearing thicker , while temperatures above 29 °C at ankle level feel uncomfortably warm, especially on bare feet. Vertical air gradients, where head-level air is warmer than at ankle level, contribute to stratified discomfort, with differences exceeding 3 K often leading to head warmth and foot chill. Recent revisions in 2023, applicable through 2025, introduced explicit methods for evaluating ankle-to-head gradients to address this, expanding from prior overall limits. Assessment of local discomfort typically combines subjective surveys, where occupants rate sensations on scales like "cold feet" or "draughty," with objective sensors measuring parameters such as air velocity, turbulence, surface temperatures, and radiant fields. The predicted percentage of dissatisfied (PPD) for local issues is targeted below 10%, aligning with overall comfort thresholds but applied specifically to these factors. Field studies validate these limits by correlating sensor data with survey responses, ensuring design criteria prevent dissatisfaction in diverse indoor settings.

Standard Effective Temperature

The Standard Effective Temperature (SET*) is defined as the of an imaginary standard environment at 50% relative humidity, 0.1 m/s air speed, 0.6 clo , and 1.2 met metabolic rate that would induce the same and skin wettedness in a person as experienced in the actual environment. This index provides a single equivalent metric that integrates the combined effects of , radiative, convective, and evaporative exchanges on human sensation and comfort. Developed by A. P. Gagge, A. P. R. Fobelets, and L. G. Berglund in 1986, SET* builds on the two-node model of human thermoregulation, which divides the into a core compartment and a shell to simulate balance and physiological responses. The model incorporates inputs such as metabolic production, , and environmental factors to predict (Tsk) and wettedness (w), which are then mapped to an equivalent standard condition. This approach extends the earlier (ET*) concept—a psychrometric index based on air , , and —into SET* by standardizing non-thermal parameters while preserving sensitivity to transient physiological states. SET* is calculated as a function of air (Ta), relative humidity (RH), air velocity (v), mean radiant (MRT), , and activity level through iterative psychrometric modeling that solves for the equivalent temperature inducing identical skin heat loss (Hsk) and evaporative efficiency. Specifically, it uses the relation Hsk = h’s(Tsk - SET*) + w h’es(Pssk - 0.5 PsSET*), where h’s and h’es are sensible and evaporative coefficients, and Pssk and PsSET* are skin and standard vapor pressures, adjusted for operative temperature and activity-standardized (e.g., Icl ≈ 1.33/(MET - 0.74) - 0.095 clo). This index finds applications in evaluating outdoor thermal comfort in varied climates, such as deserts or , where it assesses heat stress under non-uniform conditions like solar radiation or . It is also suited for transient comfort analysis, simulating dynamic exposures in environments like vehicles or intermittently ventilated spaces, by modeling time-varying physiological strain. Compared to the Predicted Mean Vote (PMV), SET* offers advantages in accounting for humidity's role in evaporative cooling and transient adaptations, providing a more accurate reflection of discomfort in high- or low-humidity scenarios without overemphasizing operative temperature alone. For instance, PMV may exaggerate discomfort in dry deserts or underestimate it in humid tropics, whereas SET* better captures the enthalpy-driven sensations through its skin wettedness component.

Comfort Models

Elevated Air Speed Method

The Elevated Air Speed Method, outlined in ASHRAE Standard 55, extends the upper boundary of the thermal comfort zone in warmer environments by incorporating higher air speeds to enhance convective and evaporative heat loss from the human body, thereby offsetting elevated operative temperatures. This approach applies to spaces with metabolic rates of 1.0 to 2.0 met and clothing insulation levels of 0.0 to 1.5 clo, where the average air speed exceeds 0.20 m/s (40 fpm). It builds on the analytical comfort zone method by adjusting operative temperature limits based on the cooling effect of air movement, calculated via the Standard Effective Temperature (SET) model in Appendix D of the standard. To determine the cooling effect (CE), the SET is computed at the elevated air speed and at a reference speed of 0.1 m/s (20 fpm) under identical conditions of air temperature, mean radiant temperature, relative humidity, metabolic rate, and clothing insulation; the difference represents the allowable increase in operative temperature (ΔT = SET_{0.1 m/s} - SET_v). The specifies air speed limits tied to operative : for temperatures above 25.5°C (77.9°F), the maximum average air speed is 0.8 m/s (160 fpm) for light, sedentary activities; between 23.0°C and 25.5°C (73.4°F and 77.9°F), air speed follows contours of equal SET; and below 23.0°C (73.4°F), it is capped at 0.2 m/s (40 fpm) unless exceeds 0.7 clo or metabolic rate surpasses 1.3 met. For instance, at 0.8 m/s, the permits an upper operative offset of up to 2.5°C relative to still-air conditions, enabling air speeds up to 2.0 m/s (400 fpm) in select cases with occupant approval. The cooling effect is determined through SET calculations as described, providing precise values for design purposes. This method supports fan-assisted cooling applications in warm climates, such as offices or residences, by allowing indoor setpoints 2–3°C higher than conventional still-air zones, potentially reducing cooling by 10–20% while achieving 80% occupant acceptability. Limitations include reduced efficacy at relative above 65%, where impaired sweat diminishes the cooling benefit, and requirements for occupant (e.g., one or speed per 6 people or 84 m²) to avoid discomfort from unwanted drafts. Solar radiation must also be controlled per standard guidelines to prevent local overheating.

Adaptive Comfort Model

The adaptive comfort model posits that building occupants' expectations and preferences for thermal conditions are influenced by contextual factors and recent thermal history, allowing for wider indoor temperature ranges in naturally ventilated or free-running buildings compared to air-conditioned spaces. This approach contrasts with static models by recognizing that people actively adjust to their environment through various mechanisms, leading to higher acceptability of temperature variations. Developed primarily from field studies in office buildings across diverse climates, the model enables energy-efficient design by reducing reliance on mechanical heating and cooling systems. The foundational work by de Dear and Brager in analyzed over 21,000 sensation votes from 160 buildings worldwide, deriving an adaptive equation for the neutral or comfort temperature (T_comf) as a function of prevailing outdoor conditions: T_comf = 0.31 T_out + 17.8°C, where T_out is the monthly mean outdoor air temperature. This equation predicts the indoor operative temperature at which 80% of occupants report thermal neutrality, with an acceptability band of ±3.5°C encompassing 80% satisfaction and ±2.5°C for 90% acceptability. The model applies specifically to naturally ventilated buildings where occupants have some control over their thermal environment, such as opening windows, and assumes typical clothing insulation (0.5 clo) and metabolic rates (1.2 met). Adaptive processes underlying the model include three main types: , where expectations shaped by cultural norms and prior experiences alter perceptions of comfort; physiological , involving bodily adjustments like changes in sweat rate or response to sustained exposure to local ; and behavioral adjustments, such as modifying levels, operating fans, or opening windows to mitigate discomfort. These adaptations collectively explain why indoor comfort temperatures correlate positively with outdoor temperatures, with a slope of approximately 0.3–0.4 in empirical data, allowing indoor temperatures to drift seasonally without widespread dissatisfaction. For instance, in temperate s, acceptable indoor ranges might span 18–28°C, promoting natural and reducing energy use by up to 50% compared to fixed-setpoint HVAC systems. In applications to naturally ventilated buildings, the model has been refined in standards like CIBSE TM52 (2013), which uses an exponentially weighted running outdoor (T_rm) to account for short-term fluctuations more responsively than monthly averages. The running is calculated recursively as T_rm = 0.6 T_od-1 + 0.4 T_rm-1, where T_od-1 is the outdoor of the previous day and T_rm-1 is the prior running . Based on this, the comfort for Category II (standard comfort) is T_c = 0.33 T_rm + 18.8°C, with operative limits of ±3°C for 80–90% acceptability; Category I (high comfort) uses ±2°C, and Category III (acceptable deviation) ±4°C. TM52 assesses overheating risk through criteria like hours exceeding upper limits (no more than 25 hours annually for Category II), daily weighted exceedance, and upper limit exceedance, ensuring buildings remain within adaptive bounds during free-running periods. EN 16798-1 (2019) provides adaptive comfort criteria that can be applied to mixed-mode buildings through category adjustments (e.g., Category III for operation), where mechanical systems supplement natural ventilation during extreme conditions. The standard uses the running mean approach but introduces hybrid bands: for mixed-mode, the upper may be raised by 1–2 above free-running values when HVAC is inactive, allowing seamless transitions while maintaining 80% acceptability. This supports energy performance assessments by integrating adaptive criteria with building simulation tools, applicable to categories I–IV based on building type and occupant vulnerability, and has been validated in field studies showing 10–20% energy savings in hybrid offices.

Predicted Heat Strain Model

The Predicted Heat Strain (PHS) model is a rational physiological approach designed to evaluate in hot environments by simulating the human body's heat balance and predicting physiological responses during . Developed through extensive validation on and , it was first formalized in the ISO 7933 in 2004 and subsequently updated in 2023 to refine predictions and incorporate improved algorithms for broader applicability. The model takes as inputs the metabolic rate associated with the activity level (M, in W/m²), environmental parameters including air temperature, mean radiant temperature, relative humidity, and air speed, as well as clothing insulation (I_cl, in clo). These factors determine the required evaporative heat loss (E_req) needed to maintain thermal equilibrium; if the maximum possible evaporation (E_max) is insufficient, excess heat storage leads to rising body temperatures and increased strain. Outputs include time-dependent predictions of rectal (core) temperature (T_re), skin temperature (T_sk), sweat rate (S_w), heart rate, and the heat strain index itself, which quantifies the overall physiological burden. The model assumes no fluid intake by default; with drinking, the dehydration limit can be extended, allowing longer safe exposures. At its core, the PHS model employs a dynamic, iterative simulation performed minute by minute to account for changing physiological states, but a simplified approximation for core temperature rise over time t (assuming constant heat imbalance) can be expressed as: T_{\text{core}}(t) = T_{\text{core}0} + \frac{(M - W - E_{\text{req}}) \times t}{m \times c_p} where T_{\text{core}0} is the initial core temperature (typically 36.8°C), W is external work (often 0 for most tasks), E_req is the required evaporative cooling (W/m²), m is body mass (kg), and c_p is the specific heat capacity of the body (approximately 3.49 kJ/kg·°C). This equation represents heat storage from unbalanced metabolism after accounting for work and required evaporation, divided by the body's thermal capacitance (with consistent units: e.g., M area-normalized, t in seconds); the full model expands this with skin blood flow, evaporation efficiency, and regulatory adjustments for more precise transient predictions. To ensure safety, the PHS model determines the maximum allowable exposure duration (t_max) as the shorter of two limits: the time until core temperature reaches 38.5°C (indicating uncompensable heat stress) or until reaches approximately 3% of body mass (e.g., about 2 loss for a 70 individual, leading to impaired performance and health risks). These thresholds are set to protect 95% of the exposed population, with t_max guiding work-rest cycles in occupational settings; limits are user-adjustable but typically conservative.

Individual and Contextual Variations

Individual Differences

Individual differences in thermal comfort arise from variations in physiological and psychological traits, influencing how people perceive and respond to thermal environments. (BMI) plays a notable role, with individuals with higher BMI often exhibiting a for cooler temperatures (typically 0.4–0.7°C lower neutral temperatures) compared to those with lower BMI, as observed in field studies of office occupants. Similarly, fitness level affects thermal preferences; higher muscle mass, indicative of greater , correlates with a preference for cooler conditions, while lower muscle mass is associated with warmer preferences, based on experimental assessments of and thermal votes. Thermal history, encompassing both short-term exposure (e.g., recent outdoor conditions) and long-term to local climates, further modulates comfort responses; for instance, individuals with recent exposure to warmer environments report adjusted neutral temperatures, demonstrating adaptive shifts in thermal perception. Thermal sensitivity varies significantly among individuals, with some exhibiting heightened responsiveness to temperature changes. Research using high-density thermal mapping on the indicates that the most sensitive individuals have approximately 1.5 times the thermal sensitivity of the average, while the least sensitive show about 50% lower sensitivity, highlighting substantial interpersonal variability in detecting thermal stimuli. These differences can stem from physiological factors like blood flow and sweat gland density, leading to divergent comfort thresholds even in identical environments. Field studies consistently reveal spreads in individual thermal preferences of 2-3°C within groups exposed to the same conditions. For example, in office and laboratory settings, surveys of hundreds of occupants showed neutral or preferred temperatures varying by up to 3°C across individuals, underscoring the challenge of uniform environmental controls and the need for personalized approaches. These variations emphasize that standard models often overlook the breadth of personal comfort zones derived from real-world data. A 2024 genome-wide association study (GWAS) on cold hypersensitivity in Japanese women identified suggestive single nucleotide polymorphisms (SNPs) near genes such as KCNK2 and TRPM2 associated with cold sensory responses, indicating potential heritable components in thermal sensitivity. Recent studies as of 2025 have explored thermal comfort during exercise, revealing a drift toward warmer neutral sensations (e.g., +0.7 on the thermal sensation scale) in active individuals.

Biological Sex and Age Differences

Biological sex influences thermal comfort primarily through physiological differences in , , and perceptual sensitivity. Females typically prefer indoor temperatures 0.5–1°C warmer than males, as evidenced by field studies showing female neutral temperatures around 25.3–26.9°C compared to 25.1–26.5°C for males under similar conditions. This preference stems from lower metabolic rates in females, which reduce internal heat production, particularly post-menopause when estrogen decline further lowers basal by up to 5–10% compared to pre-menopausal levels. Hormonal factors also affect sweating responses; females generally exhibit lower sweat rates than males (typically 20–50% less) during heat stress due to differences in sensitivity influenced by sex hormones, leading to greater reliance on for cooling and heightened discomfort in cooler environments. A of over 20 studies indicates that sex accounts for approximately 15% of variance in predicted dissatisfied (PPD), with females 1.74 times more likely to report thermal dissatisfaction than males, especially below 22°C. Age-related changes alter thermal comfort through shifts in metabolic rate, skin blood flow, and sensory acuity, often requiring adjusted environmental setpoints. The elderly (over 65 years) experience reduced and sensitivity, resulting in a preference for warmer conditions—typically 1–2.3°C higher than younger adults—to maintain comfort, with neutral temperatures around 24.9°C in winter settings. This vulnerability arises from age-induced declines in and heat dissipation efficiency, increasing the risk of in standard comfort zones. In contrast, children exhibit higher metabolic rates (up to 64 W/m² for ages 9–11, compared to 58 W/m² for adults), generating more internal but possessing limited behavioral control over their , such as adjusting or activity, which can lead to overheating in warm spaces despite their physiological tolerance for cooler conditions. These differences build on broader individual sensitivities, where demographic factors like and explain up to 20% of thermal sensation variability in controlled studies. Standards like ANSI/ASHRAE Standard 55 recommend segmented comfort zones to accommodate such variations, advising designers to incorporate metabolic rate adjustments (e.g., 1.0–1.2 met for elderly vs. 1.3–1.4 met for children) and wider operative ranges (e.g., 20–26°C for mixed-age groups) to minimize dissatisfaction across demographics.

Regional and Cultural Differences

Thermal comfort preferences exhibit significant regional variations influenced by climatic conditions, with populations in tropical regions generally tolerating and preferring higher neutral temperatures compared to those in temperate zones. For instance, field studies in , a tropical country, have identified neutral operative temperatures around 26–29°C in naturally ventilated buildings, reflecting to warmer outdoor environments. In contrast, temperate climates show lower neutral temperatures, typically 22–24°C, as evidenced by winter indoor studies across multiple countries where neutral sensations align with cooler baselines. These differences highlight how long-term exposure to local climates shapes thermal expectations, with tropical residents showing a 3–4°C higher neutral temperature threshold than temperate counterparts. Cultural factors further modulate these preferences through behavioral norms, such as clothing choices and activity patterns, which vary by societal conventions and environmental history. In hot-dry climates like those in the or , cultural acceptance of higher warmth is common, with residents exhibiting elevated upper limits of thermal acceptability—often up to 28–30°C—due to traditional loose-fitting garments that facilitate heat dissipation and norms favoring outdoor activities despite heat. Similarly, in regions with strong cultural emphasis on modest attire, such as parts of , clothing insulation remains relatively constant across seasons, leading to broader acceptance of warmer indoor conditions without frequent adjustments. These behavioral adaptations underscore how cultural practices can extend comfort zones beyond physiological limits alone. Adaptive comfort models address these regional and cultural influences by incorporating local running mean outdoor temperatures to predict acceptable indoor ranges, allowing for geographically tailored comfort bands. Extensions of the original adaptive model, such as those in Standard 55, use the exponentially weighted running mean of outdoor air temperature over the past 30 days to adjust neutral temperatures, enabling wider acceptability in warmer climates like India's (up to 35°C upper limit) compared to Europe's narrower bands (around 18–28°C). This approach accounts for psychological to local patterns, improving model applicability across diverse regions. Large-scale analyses, including the Global Thermal Comfort Database II (updated through 2021 with over 100,000 observations), confirm these patterns by revealing 3–4°C shifts in neutral temperatures between climate zones, with tropical datasets showing higher satisfaction at elevated temperatures than temperate ones. The database, aggregating field studies from over 100 locations worldwide, demonstrates that regional data clusters indicate systematic biases in global models if local variations are ignored, emphasizing the need for climate-specific calibrations.

Standards and Applications

Key Standards and Guidelines

The (ISO) 7730:2025 standard, "Ergonomics of the thermal environment — Analytical determination and interpretation of thermal comfort using calculation of the PMV and PPD indices and local thermal comfort criteria," provides a framework for evaluating moderate thermal environments, primarily for sedentary or light activities indoors. It uses the predicted mean vote (PMV) index, where comfort is defined as a PMV range of -0.5 to +0.5, corresponding to a predicted of dissatisfied (PPD) below 10% for at least 90% among occupants. This standard emphasizes analytical methods to specify environmental parameters like air temperature, mean radiant temperature, air speed, and to achieve these conditions. The core PMV range remains unchanged from previous editions. The American Society of Heating, Refrigerating and Air-Conditioning Engineers () Standard 55, "Thermal Environmental Conditions for Human Occupancy," outlines methods for assessing thermal comfort in occupied spaces, incorporating both analytical approaches based on PMV/PPD and adaptive models that account for occupants' behavioral adjustments in naturally ventilated buildings. The 2023 edition includes updates to support personal comfort systems, such as wearable devices for individualized control, and expands provisions for elevated air speeds to extend comfort zones without increasing energy use. It applies to indoor environments with air speeds up to 0.8 m/s and operative temperatures typically between 20°C and 27°C, depending on and activity levels. Recent editions, including ASHRAE 55-2023, incorporate provisions for and personal comfort systems to address evolving environmental challenges. In , EN 16798-1:2019, "Energy performance of buildings - - Part 1: ," integrates thermal comfort criteria into building energy performance evaluations, classifying environments into three categories based on PMV ranges: Category I (-0.2 to +0.2 for sensitive occupants), Category II (-0.5 to +0.5 for normal expectations), and Category III (-0.7 to +0.7 for acceptable minimum). This standard supports both PMV-based analysis for mechanically conditioned spaces and adaptive models for naturally conditioned ones, with operative temperature limits varying by external climate, such as 20–24°C for heating and 23–26°C for cooling in Category II in temperate zones. Recent editions, including EN 16798-1:2019, incorporate provisions for and personal comfort systems to address evolving environmental challenges. For occupational settings, the American Conference of Governmental Industrial Hygienists (ACGIH) Threshold Limit Values (TLVs), as per the 2025 edition, establish guidelines to prevent heat stress, using (WBGT) as the primary metric, with limits such as 26–30°C WBGT depending on work intensity and rest cycles to maintain core body temperature below 38°C for acclimatized workers. These TLVs focus on physiological strain rather than subjective comfort, recommending action levels at 50% of TLVs for and interventions. Key standards differ in their comfort bands, reflecting variations in acceptability thresholds and environmental assumptions. The following table summarizes representative operative temperature ranges for office-like settings (sedentary activity, 0.5 clo , 50% relative humidity) achieving at least 80% acceptability:
StandardCategory/LevelOperative Temperature Range (°C)PMV RangeAcceptability (%)
ISO 7730:2025Recommended20–26-0.5 to +0.590
Standard20–26 (analytical); 18–28 (adaptive)-0.5 to +0.580–90
EN 16798-1Category II20–26 (approx., varying by season/climate)-0.5 to +0.580–90
ACGIH TLVsAction LimitWBGT <28 (light work)N/APrevents strain (95% safe)

Applications in Built Environments

In , thermal zoning divides spaces into distinct areas served by independent HVAC controls, allowing tailored regulation to match patterns and reduce waste while maintaining comfort. This approach uses dampers and multiple thermostats to direct conditioned air precisely, preventing overcooling or overheating in unused zones and improving overall thermal uniformity. systems, such as hydronic panels embedded in floors, walls, or ceilings, provide heating and cooling by directly exchanging heat with occupants via and , achieving thermal comfort at lower air temperatures compared to all-air systems and potentially reducing use by up to 30%. These systems enhance comfort by minimizing air movement and drafts, particularly in settings where uniform surface temperatures stabilize the indoor environment. controls, including IoT-enabled thermostats, integrate sensors for real-time monitoring of , , and , optimizing HVAC operation to balance comfort and ; for instance, adaptive algorithms can achieve 10-20% savings in cooling by adjusting setpoints based on predictive data. In , automotive HVAC systems maintain comfort through distributed air vents and zones that account for varying passenger positions and loads, ensuring rapid equalization of temperatures. heating and cooling technologies, often using thermoelectric modules or ventilated fabrics, target localized discomfort by directly warming or cooling contact surfaces, which can reduce overall HVAC load by 4% and improve in conventional by 2.8%. These systems are particularly effective in electric , where they preserve by minimizing reliance on high-energy heating, achieving thermal neutrality for occupants in under 5 minutes during starts. Mixed-mode strategies combine mechanical HVAC with natural ventilation to leverage outdoor air when conditions permit, extending comfort ranges and cutting mechanical cooling demands by 20-50% in temperate climates without compromising indoor thermal satisfaction. Automated controls switch modes based on external temperature, wind, and indoor sensors, fostering adaptability that aligns with occupant preferences for fresh air while adhering to standards like 55. This hybrid approach briefly incorporates operable windows for natural airflow, enhancing perceived comfort through increased air quality and reduced reliance on full mechanical conditioning. A notable case is office building in , which employs adaptive facades with automated shading and glazing to modulate , combined with zoned radiant floors and IoT-driven HVAC, resulting in 94% occupant satisfaction for thermal comfort and a 70% reduction in use compared to conventional offices. The building's south-facing walls and sensor network enable dynamic responses to weather, maintaining neutral temperatures year-round and demonstrating scalable integration of these strategies in high-performance green architecture.

Personal Comfort Systems

Personal comfort systems (PCS) are individualized devices designed to provide targeted thermal conditioning to occupants, allowing for personalized control over microenvironments without relying on centralized building HVAC systems. These systems enhance thermal comfort by delivering localized heating, cooling, or ventilation directly to the body, accommodating variations in individual preferences and enabling wider ambient temperature setpoints in buildings. Common types of PCS include wearable fans, which provide convective cooling through airflow to the upper body; heated or cooled seats that use conduction or to warm or chill seated areas; and desk fans that direct air movement toward the occupant for evaporative or convective relief. Personal environmental control systems (PECS), a related category, encompass integrated setups like adjustable desk-mounted units combining fans, radiant panels, and sensors for more comprehensive local control. These devices typically operate at low power levels, often under 50 watts, making them efficient alternatives to space heaters or full-room air conditioners. PCS offer significant benefits, including an effective temperature offset of 2-3°C in cooling scenarios through mechanisms like increased air speed or localized conditioning, which can maintain occupant satisfaction even in environments up to 28°C. For heating, offsets can reach 7-10°C with conductive elements like heated chairs. Energy savings arise from relaxing HVAC setpoints by 2-4°C, potentially reducing total building HVAC consumption by up to 40% in mixed climates, as the low-energy PCS compensate for the broader while preserving comfort levels above 80% satisfaction. Research from the in the 2020s has focused on chair-based PCS, featuring integrated heating, cooling, and ventilation elements controlled via armrest interfaces. Field studies with these systems in settings demonstrated the ability to maintain predicted percentage dissatisfied (PPD) below 5% across ambient temperatures from 16°C to 29°C, significantly outperforming standard HVAC alone by addressing individual discomfort hotspots like the lower body. These investigations used thermal manikins and occupant surveys to validate performance, confirming enhanced productivity alongside comfort gains. Integration of with enables adaptive user feedback loops, where IoT sensors collect real-time data on occupant adjustments and physiological responses to train personal comfort models. These AI-driven systems predict individual preferences and automate PCS operation, such as adjusting fan speeds or seat temperatures based on wearable inputs, further optimizing use and satisfaction in dynamic environments.

Research Directions

Medical and Healthcare Settings

In medical and healthcare settings, thermal comfort is particularly critical due to the vulnerability of patients and the need to balance environmental control with clinical requirements. Vulnerable populations, such as neonates, require warmer ambient temperatures to maintain neutral thermal environments and prevent ; guidelines recommend room temperatures of 24–26°C for neonatal intensive care units to support in preterm or low-birth-weight infants. In contrast, surgical operating rooms prioritize infection control and staff performance, typically maintaining cooler conditions of 18–22°C to minimize bacterial proliferation and ensure precise handling of instruments, though this can challenge patient comfort during procedures. Key challenges in these environments arise from the tension between thermal comfort and infection prevention measures. High airflow rates for , essential to reduce airborne pathogens, often create drafts in recovery rooms, leading to discomfort and potential for postoperative patients who may experience or delayed warming. Similarly, lower levels (often 40–60%) in sterile areas help curb microbial growth but can dry mucous membranes, exacerbating discomfort for patients with respiratory issues or those recovering from . These conflicts necessitate tailored HVAC designs that integrate systems without compromising overall thermal satisfaction. International guidelines provide frameworks for optimizing these conditions. The (WHO) recommends minimum indoor temperatures of 18°C in healthcare facilities during cold periods, with adjustments to 20–21°C for elderly or vulnerable patients to support recovery and prevent -related health risks. Complementing this, the Chartered Institution of Building Services Engineers (CIBSE) Guide A outlines criteria for hospitals, advocating operative temperatures of 21–24°C in general wards (Category II comfort level) and emphasizing adaptive controls to account for patient metabolic variations while adhering to standards for air quality. Recent research underscores the clinical benefits of optimized thermal environments. A 2024 study on in wards found that maintaining stable comfort conditions reduced recovery time by up to 15% in surgical cases, attributing this to decreased and improved quality. Broader literature reviews confirm that such interventions not only enhance satisfaction but also accelerate processes by mitigating physiological strain from suboptimal temperatures.

Impacts of Climate Change

Climate change is projected to significantly alter comfort conditions worldwide, with urban areas facing heightened risks of heat stress. Studies project that a global rise of 1.5°C above pre-industrial levels could double the number of large cities experiencing extreme heat stress by 2050, compared to current conditions, thereby increasing the frequency and intensity of days where thermal discomfort impairs and . This escalation is particularly acute in densely populated urban environments, where heat stress is expected to reduce labor capacity by an additional 10% during hot months by mid-century, compounding existing vulnerabilities. The urban heat island (UHI) effect further intensifies these challenges by amplifying local temperatures through impervious surfaces, reduced vegetation, and anthropogenic heat, leading to greater thermal discomfort under warming scenarios. Studies indicate that UHIs can elevate nighttime temperatures by several degrees, prolonging exposure to uncomfortable conditions and increasing the proportion of the population experiencing to over 90% in affected cities. In response, adaptive urban designs—such as enhanced and reflective materials—are essential to mitigate UHI-driven discomfort and align built environments with evolving climate realities. Equity concerns are pronounced, as climate-induced thermal discomfort disproportionately burdens populations in the Global South, where socioeconomic constraints limit and infrastructure resilience. Research highlights a north-south disparity, with tropical regions in the Global South projected to see a sharper decline in comfortable outdoor days—up to 50% fewer under high-emission scenarios—exacerbating health risks and economic inequalities compared to temperate northern areas. These impacts widen existing divides, as low-income communities in urbanizing southern cities face higher exposure to extreme heat without adequate cooling resources. To address these projections, resilient standards are emerging through updated adaptive thermal comfort models tailored to +2°C warming scenarios, which incorporate future data to redefine acceptable indoor and outdoor ranges. For instance, revisions to models like those in and EN 16798-1 evaluate comfort under projected Mediterranean and similar climates, enabling energy-efficient building designs that maintain habitability while reducing reliance on mechanical cooling. Such models promote proactive standards that enhance thermal resilience across diverse regions.

Emerging Technologies

Artificial intelligence (AI) and (ML) are revolutionizing thermal comfort prediction by enabling personalized models that integrate data from wearable devices. These models analyze physiological signals such as , , and activity levels to forecast individual thermal sensations in , surpassing traditional static standards like PMV by accounting for personal variability. For instance, algorithms, including neural networks, map environmental and biometric data to adjust HVAC systems proactively, reducing discomfort episodes by up to 20% while optimizing use. Wearable sensors facilitate non-intrusive monitoring, allowing AI to predict comfort levels with accuracies exceeding 85% in diverse indoor settings. Smart home integrations, such as those with thermostats, further enhance these predictive capabilities by combining wearable data with home environmental sensors and weather forecasts. The employs to adapt setpoints based on patterns, , and modeled home characteristics, achieving up to 15% savings without compromising comfort. When linked to wearables via platforms, this setup enables dynamic adjustments that align ambient conditions with user-specific predictions, promoting scalable implementation in residential and commercial spaces. Advanced materials like phase-change materials (PCMs) embedded in building walls offer passive solutions for stabilizing indoor temperatures and enhancing thermal comfort across varying climates. PCMs absorb and release during phase transitions, maintaining operative temperatures within the 20-26°C comfort range for extended periods and reducing peak loads by 20-30% in hot-humid regions. Recent reviews highlight their integration into wallboards, where microencapsulated organic PCMs prevent overheating, improving occupant satisfaction by minimizing temperature fluctuations without active energy input. In contrasting climate zones, PCM-enhanced envelopes have demonstrated up to 25% better thermal inertia compared to conventional insulation. Electrochromic windows represent another breakthrough in dynamic building envelopes, automatically tinting to modulate heat gain and glare while preserving daylight. These windows reduce through facades by approximately 80%, lowering mean radiant temperatures by up to 4.7°C and operative temperatures by 11.6°C in tropical climates, thereby elevating thermal comfort indices. By optimizing visible transmittance—down to 0.1% in tinted states—they also enhance visual comfort, increasing glare-free daytime hours by 39% relative to clear glass. This technology cuts cooling energy demands by 14-29%, making it ideal for energy-efficient retrofits. Digital twins are emerging as powerful simulation tools for personalized thermal comfort in smart cities, creating virtual replicas of urban environments to test and optimize HVAC strategies. These models integrate from sensors and algorithms, such as mixture-of-experts architectures with LSTM networks, to predict individual comfort with 96% accuracy and low (0.3156). In smart building applications, digital twins enable energy-efficient operations by simulating occupant responses, achieving 15-20% reductions in HVAC consumption while ensuring comfort across diverse zones. For urban scales, they visualize thermal distributions in 3D platforms, supporting city-wide planning to mitigate heat islands. Recent developments in 2025 include advanced cooling vests incorporating phase-change materials, which provide targeted relief by reducing skin temperatures by 3-4°C for up to 120 minutes in hot conditions. These vests, often with integrated feedback mechanisms for user adjustment, lower perceived thermal strain and enhance comfort during prolonged exposure, as evidenced in field tests for high-heat environments. Such innovations extend beyond personal devices, influencing scalable wearable tech for broader .