Human Thermal Comfort Indices Research Articles

Effects of large skylights on lighting and thermal environments in underground public transport hubs: A case study in Shenzhen

Large skylights in underground public transport hubs are designed to introduce natural light and reduce the energy consumed by artificial lighting. Although large skylights can improve the lighting environment of underground public transport hubs, they also increase energy consumption due to solar radiation. Therefore, there is an urgent need to balance the improved lighting and energy consumption associated with large skylights and to determine the optimal design scheme. There are few studies on the lighting and thermal environments of underground public transport hubs, and the optimal design scheme for large skylights is unclear. Therefore, in the current study, field tests were conducted to analyze the lighting and thermal environments of two underground public transport hubs located in Shenzhen: Shenzhen North Station and Futian Station. In addition, multiobjective optimization was carried out for the large skylight at Futian Station. The results showed that most passengers were satisfied with the lighting and thermal environment under large skylights, but they were less satisfied in the summer than in the winter. Therefore, appropriate shading measures should be considered to reduce the effect of large skylights on passengers’ thermal comfort in the summer. Furthermore, the results of multiobjective optimization indicated that the large skylight at Futian Station led to a 28.1 % reduction in annual air conditioning-induced energy consumption, a 31.5 % increase in the lighting performance index (UDI), and a 43.8 % increase in the human thermal comfort index (CTR). The results of this study could provide guidance for the design of large skylights in underground public transport hubs.

Substantial increase in human-perceived heatwaves in eastern China in a warmer future

Heatwaves describe prolonged periods of excessive heat. The increasing trend in heatwave frequency, duration, and magnitude in a warmer future has been extensively investigated. However, the vast majority of traditional studies on heatwaves consider only the role of air temperature, which is inadequate as a metric for human heat stress. While reported worsening levels in heat stress with global warming are concerning, the changes in heatwaves may not be directly comparable to the temperature increase. The reliable information on future changes in human-perceived heatwaves is still fairly limited. Given this context, we quantified future changes in human-perceived heatwaves in eastern China, where the population is dense and the summers are often sultry, based on dynamic downscaling climate projections and a human thermal comfort index that combines the effect of temperature and humidity. We demonstrated that under the 3.0 °C of global warming (similar to late-century warming projected based on current mitigation policies), the frequency, duration, and magnitude of human-perceived heatwaves in eastern China would increase approximately 5, 4, and 20 times, respectively, relative to the reference period (1986–2005). Human-perceived heatwaves are projected to increase more rapidly than heatwaves solely based on the temperature definition, implying that the escalating heat risk for humans may have been underestimated by previous studies. Moreover, extra cautions need to be given to low-latitude regions, where the smallest changes in the mean temperature will probably be accompanied by the most pronounced increases in human-perceived heatwaves. Our results suggest the urgent demand of reducing greenhouse gas emissions toward mitigating persistent thermal discomfort in the future. Although here we focused on eastern China, our approach to assessing heatwaves can also be readily generalized to address similar problems worldwide.

Effects of urban street trees on human thermal comfort and physiological indices: a case study in Changchun city, China

Planting trees along urban streets is one of the most important strategies to improve the urban thermal environment. However, the net impacts of urban street trees on human thermal comfort and physiological parameters are still less clear. On three similar east–west orientated streets with different degrees of tree cover—low (13%), medium (35%), and high (75%), urban microclimatic parameters and human physiological indices for six male students were simultaneously measured on three cloudless days in summer 2018. The results show that the differences in tree cover were predominant in influencing urban thermal environment and comfort. The street with the highest tree cover had significantly lower physiological equivalent temperature (PET) and more comfortable than the other two streets. The frequency of strong heat stress (PET > 35 °C) was 64%, 11%, and 0%, respectively, for streets with low, medium, and high tree cover. For the six male university students, human physiological indices varied greatly across the three streets with different tree cover. Systolic blood pressure, diastolic blood pressure, and pulse rate increased with decreasing tree cover. The results also suggest that urban thermal environment and comfort had considerable impact on human physiological parameters. Our study provides reasons for urban planners to plant trees along streets to improve the thermal environment and promote urban sustainability.

Influence of air pollution on human comfort in five typical Chinese cities

It is known that air pollution is harmful to creatures, though until now most of the human thermal comfort indices that existed were calculated only with meteorological conditions. Therefore, a new index - meteorology and environment comfort (MEC) - was given out in this paper that considers both meteorology and air pollution conditions and presents the comprehensive and synergistic effects of meteorological and air pollution. The meteorology and air pollution data were used to establish the influence function of the five air pollutants (PM2.5, PM10, O3, NO2, and SO2) according to Fechner's law; then, we calculated the somatosensory temperature (ST, a class of human thermal comfort indices) and MEC values of five typical cities (Beijing, Xining, Nanjing, Kunming, and Guangzhou). The results showed average improvements of five cities on MEC as a new comprehensive human comfort index to new ST. In spring, the MEC comfort proportion fell by 29.25%. Besides, the extreme heat discomfort ratio in Nanjing and Kunming has increased over 20%. In summer, the comfort proportion fell 12.54%; the extreme heat discomfort proportion of Beijing increased 37.86% and Kunming increased 24.09%. Air pollution significantly raised discomfort stress in Beijing. In fall, the comfort proportion fell by 20.87%; and the extreme heat discomfort of Nanjing increased 23.67% caused by poor air quality. About winter, the comfort ratio decreased 12.72%, and the cold discomfort proportion of Nanjing increased 30.30%, signifying awful air quality in winter. Air pollution levels significantly affect the comfort levels in all seasons, which is more evident with good weather patterns. MEC can offer early warnings of extreme weather events and provide a basis for the better prevention and control of air pollution to protect human health basing on the predictions of meteorological and environmental impact factors.

ERA5‐HEAT: A global gridded historical dataset of human thermal comfort indices from climate reanalysis

AbstractThe mean radiant temperature (MRT) and the Universal Thermal Climate Index (UTCI) are widely used as human biometeorology parameters to assess the linkages between outdoor environment and human well‐being. Historically computed from meteorological station measurements, we here present ERA5‐HEAT (Human thErmAl comforT), the first historical dataset of MRT and UTCI as spatially gridded records at the global scale. Derived using climate variables from ERA5, a quality‐controlled reanalysis produced by the European Centre for Medium‐Range Weather Forecasts (ECMWF) within the Copernicus Climate Change Service (C3S), ERA5‐HEAT consists of hourly gridded maps of MRT and UTCI at 0.25° × 0.25° spatial resolution. It currently spans from 1979 to present, and it will be extended in time as updates of ERA5 are made available. ERA5‐HEAT provides two streams, a consolidated and an intermediate one, that are released at 2 or 3 months and 5 days behind real time, respectively. Data are publicly and freely available for download at the Climate Data Store which has been developed as part of C3S. Being the only existing global historical gridded time series of MRT and UTCI to date, ERA5‐HEAT is aimed at a wide range of end users, from scientists to policymakers, with an interest in environment–health applications at any spatial and temporal scale.

Investigating the Behaviour of Human Thermal Indices under Divergent Atmospheric Conditions: A Sensitivity Analysis Approach

This paper aims to analyse and conclude about the behaviour of the most commonly used human thermal comfort indices under a variety of atmospheric conditions in order to provide further information about their appropriateness. Utilising Generalized Additive Models (GAMs), this article examines the indices’ sensitivity when exposed to diverse classified atmospheric conditions. Concentrated upon analysing commonly used human thermal indices, two Statistical/Algebraic indices (Thermohygrometric Index (THI) and HUMIDEX (HUM)), and four Energy Balance Model indices (Physiologically Equivalent Temperature (PET), modified PET (mPET), Universal Thermal Climate Index (UTCI), and Perceived Temperature (PT)) were selected. The results of the study are twofold, the identification of (1) index sensitivity to parameters’ variation, and change rates, resultant of different atmospheric conditions; and, (2) the overall pertinence of each of the indices for local thermal comfort evaluation. The results indicate that the thermohygrometric indices cannot follow and present the thermal conditions’ variations. On the other hand, UTCI is very sensitive under low radiation condition, and PET/mPET present higher sensitivity when the weather is dominated by high radiation and air temperature. PT index provides the lower sensitive among the human energy balance indices, but this is adequately sensitive to describe the thermal comfort environment.

Correction to: A comparative sensitivity analysis of human thermal comfort indices with generalized additive models

Correction to: A comparative sensitivity analysis of human thermal comfort indices with generalized additive models

A comparative sensitivity analysis of human thermal comfort indices with generalized additive models

This paper presents a comparative sensitivity analysis of six of the widely used human thermal comfort indices. The analysis consists of the evaluation of the effect of indices ‘input parameters’ variation and change rate on the output of human energy balance and simple thermohygrometric indices. For the implementation of the sensitivity analysis, the generalized additive model’s methodology is applied on a long period and high temporal resolution dataset from Athens, Greece. The results indicate that the proposed methodology of generalized additive models is adequate for such an analysis. Moreover, this research revealed the differences in index behaviour. The thermohygrometric indices (i.e. Thermohygrometric Index and HUMIDEX) exhibit a clearly deferent sensitivity pattern in comparison to the human energy balance indices (i.e. physiologically equivalent temperature (PET), perceived temperature (PT), modified physiologically equivalent temperature (mPET) and Universal Thermal Comfort Index (UTCI)), and they are incapable to handle the complexity of the atmospheric stimuli on human thermal perception. On the other hand, human energy balance indices can follow the input parameters fluctuations but with different grades of sensitivity. PET and mPET present a moderate and gradual sensitivity both in terms of the input variation and input change rate. PT is the less sensitive index among the human energy balance investigated, but it is able to follow efficiently the input parameters variation during the measurements period. Moreover, UTCI is the most sensitive among all the selected indices for low values (and low change rate) of the input parameters but for high input parameter values (except the wind speed), UTCI exhibits a low sensitivity in comparison to the other human energy balance indices. In terms of sensitivity, the most influential input parameter is global radiation, and the less influential is vapour pressure.

Excess of children's outpatient consultations due to asthma and bronchitis and the association between meteorological variables in Canoas City, Southern Brazil.

The southern Brazilian city of Canoas, situated in the metropolitan region of Porto Alegre, is subject to several annual meteorological phenomena, such as cold fronts and squall lines. Here, we assess the relationship between meteorological conditions and outpatient consultations for asthma or bronchitis in children from Canoas City. Data from outpatient consultations of children (below 9years), between January/2005 and September/2008, were combined with daily meteorological data from 12UTC (morning) and 18UTC (afternoon). We identified 42days with an excess of outpatient consultations (peaks). Consultations were negatively correlated with temperature and human thermal comfort index (HTCI) from the 3 previous days based on consultation data at 12 and 18UTC, and positively correlated with atmospheric pressure. A positive correlation with relative humidity was significant only at 12UTC. The highest correlations occurred on the day of consultation (12UTC) with temperature, relative humidity, and atmospheric pressure, as well as 2days previous to the HTCI. The sensation of cold was associated with about 55% of the days of the period at 12UTC: considering only the peaks of consultations, this association exceeds 90% of days. The highest frequencies of respiratory complications (June, July, and August) were associated with negative temperature anomalies, wind speed and direction, and positive anomalies in relative humidity and atmospheric pressure. Nearly half (45%) of the air masses associated with respiratory complications arrived at Canoas from a SW direction, 19% from the south and 14% from the west. In summary, observed increases in respiratory complications were mainly associated with the presence of cold and humid air (and/or falling temperature with increasing humidity) in the morning.

Association between human and animal thermal comfort indices and physiological heat stress indicators in dairy calves

Warm summer episodes have a significant effect on the overall health and well-being of young cattle; however, it is not known which temperature measure should be used for estimating heat stress in dairy calves. In this study, generalized linear mixed-effects models were used to estimate the relationships between thermal comfort indices and animal-based heat stress indicators in sixteen Holstein bull calves that were housed in individual calf hutches. Data were collected under continental weather characteristics over a 5-day period: day 1 (lower-temperature day), days 2 and 3 (heat stress days), and a 2-day post-stress period. Relative humidity, ambient temperature, the heat index, the humidex and five different temperature–humidity indices (THI) were used as thermal indices. Physiological variables monitored included respiratory rate, rectal temperature, ear skin temperature and heart rate. The heat index and the humidex measuring human thermal comfort were more closely associated with physiological measures than were the ambient temperature or the THIs (in case of heat index: R2 = 0.87 for respiratory rate, R2 = 0.63 for rectal temperature, R2 = 0.70 for ear skin temperature, and R2 = 0.78 for heart rate, respectively; in case of humidex: R2 = 0.85 for respiratory rate, R2 = 0.60 for rectal temperature, R2 = 0.68 for ear skin temperature, and R2 = 0.75 for heart rate, respectively). Based on our results, parameters of human outdoor comfort seem better to estimate heat stress in dairy calves in a continental region than those of THIs or ambient temperature.

Development and application of artificial neural network models to estimate values of a complex human thermal comfort index associated with urban heat and cool island patterns using air temperature data from a standard meteorological station.

The present study deals with the development and application of artificial neural network models (ANNs) to estimate the values of a complex human thermal comfort-discomfort index associated with urban heat and cool island conditions inside various urban clusters using as only inputs air temperature data from a standard meteorological station. The index used in the study is the Physiologically Equivalent Temperature (PET) index which requires as inputs, among others, air temperature, relative humidity, wind speed, and radiation (short- and long-wave components). For the estimation of PET hourly values, ANN models were developed, appropriately trained, and tested. Model results are compared to values calculated by the PET index based on field monitoring data for various urban clusters (street, square, park, courtyard, and gallery) in the city of Athens (Greece) during an extreme hot weather summer period. For the evaluation of the predictive ability of the developed ANN models, several statistical evaluation indices were applied: the mean bias error, the root mean square error, the index of agreement, the coefficient of determination, the true predictive rate, the false alarm rate, and the Success Index. According to the results, it seems that ANNs present a remarkable ability to estimate hourly PET values within various urban clusters using only hourly values of air temperature. This is very important in cases where the human thermal comfort-discomfort conditions have to be analyzed and the only available parameter is air temperature.

Development of the VTUF-3D v1.0 urban micro-climate model to support assessment of urban vegetation influences on human thermal comfort

With urban areas facing longer duration heat-waves and temperature extremes from climate change and growing urban development, adaptation strategies are needed to protect city residents. Examining the role that increased tree cover and water availability can have on human thermal comfort (HTC) is needed to help guide the development of thermally comfortable cities. To inform planning, modelling tools are needed that provide sufficient resolution to resolve urban influences on HTC and the ability to model important physiological processes of vegetation. To achieve this, a new micro-scale model, VTUF-3D (Vegetated Temperatures of Urban Facets) has been developed. In it, offline modelling of individual items of vegetation is performed using the MAESPA process-based tree model (Duursma and Medlyn, 2012) (a model that can model individual trees, vegetation, and soil components), and integrated into the TUF-3D (Krayenhoff and Voogt, 2007) urban micro-climate surface energy balance (SEB) model. This innovative approach allows the new model to account for important vegetative physiological processes and shading effects, using configurable templates to allow representation of any type of vegetation or water sensitive design feature. This work enables detailed calculations of surface temperatures (Tsfc), mean radiant temperature (Tmrt), and a HTC index, the universal thermal climate index (UTCI), across urban canyons. This study presents an overview of VTUF-3D. Also presented are two evaluations of VTUF-3D. The first evaluation compares modelled surface energy balance fluxes to observations in Preston, Australia (Coutts et al., 2007). The second evaluation compares spatial and temporal predictions of Tmrt and UTCI to two observed street canyons in the City of Melbourne (Coutts et al., 2015b). The VTUF-3D model is shown to perform well and is suitable for use to examine critical questions relating to the role of vegetation and water in the urban environment in support of HTC.

Urban Finescale Forecasting Reveals Weather Conditions with Unprecedented Detail

Abstract Urban landscapes impact the lives of urban dwellers by influencing local weather conditions. However, weather forecasting down to the street and neighborhood scale has been beyond the capabilities of numerical weather prediction (NWP) despite the fact that observational systems are now able to monitor urban climate at these scales. In this study, weather forecasts at intra-urban scales were achieved by exploiting recent advances in topographic element mapping and aerial photography as well as looking at detailed mappings of soil characteristics and urban morphological properties, which were subsequently incorporated into a specifically adapted Weather Research and Forecasting (WRF) Model. The urban weather forecasting system (UFS) was applied to the Amsterdam, Netherlands, metropolitan area during the summer of 2015, where it produced forecasts for the city down to the neighborhood level (a few hundred meters). Comparing these forecasts to the dense network of urban weather station observations within the Amsterdam metropolitan region showed that the forecasting system successfully determined the impact of urban morphological characteristics and urban spatial structure on local temperatures, including the cooling effect of large water bodies on local urban temperatures. The forecasting system has important practical applications for end users such as public health agencies, local governments, and energy companies. It appears that the forecasting system enables forecasts of events on a neighborhood level where human thermal comfort indices exceeded risk thresholds during warm weather episodes. These results prove that worldwide urban weather forecasting is within reach of NWP, provided that appropriate data and computing resources become available to ensure timely and efficient forecasts.

The Brazilian World Cup: too hot for soccer?

The main objective of this research was to analyze the climate data for the host cities of the soccer World Cup held in Brazil in June and July 2014. A great deal of criticism was expressed about the Brazilian climate in the national and international press and media in the run-up to the competition, suggesting that the air temperature and relative air humidity would be the main adversaries of the soccer teams, especially those from Europe, during the competition. An analysis of the weather was done at the places and times of each of the 64 matches held. A human thermal comfort index was calculated (discomfort index (DI)) for each of the matches in order to discover the real climatic conditions in the host cities during the 2014 World Cup and their potential influence on the teams and human comfort in general. During the 2014 World Cup, only two matches were played at temperatures above 30°C, representing a negligible percentage of the total number of matches. The air temperature for over half the matches (53%) was 20-25°C. The results showed the air temperature and relative humidity data analyzed here both individually and in the form of an index indicate that the World Cup held in Brazil in 2014 did not put any of the players at risk due to extreme heat.

Implementation of human thermal comfort information in Köppen-Geiger climate classification-the example of China.

Köppen-Geiger climate classification (KGC) is accepted and applied worldwide. The climatic parameters utilised in KGC, however, cannot indicate human thermal comfort (HTC) conditions or air humidity (AH) conditions directly, because they are originally based on climatic effects on vegetation, instead of that on human body directly. In addition, HTC is driven by meteorological parameters together. Thus, the objective of this study is to preliminarily implement the HTC information and the AH information in KGC. Physiologically equivalent temperature (PET) has been chosen as the HTC index, and vapour pressure (VP) is for the quantification of AH conditions. In this preliminary study, 12 Chinese cities in total have been taken into account as the assumed representatives of 11 climate types. Basic meteorological data of each city with 3-h resolution in 2000-2012 has been analysed. RayMan model has been applied to calculate PET within the same time period. Each climate type has been described by frequencies of PET and frequencies of VP. For example, the Aw (Sanya) has the most frequent occurrence of thermally stressful conditions compared to other climate types: PET in 22% points in time of the year was above 35°C. The driest AH conditions existed in Dwc (Lhasa) and Dfb (Urumqi) with VP rarely above 18hPa in the wettest month. Implementation of the HTC information and the additional AH information in each climate type of KGC can be helpful for the topics of human health, energy consumption, tourism, as well as urban planning.

Indoor Human Thermal Comfort Optimal Control with Desiccant Wheel Cooling System

Human thermal comfort is an important concern in the energy management of commercial buildings. Human thermal comfort research focuses mostly on the temperature control or the humidity control while based on human thermal comfort index control is ignored. In this paper, an optimal human thermal comfort control model (OHTCM) for a desiccant wheel cooling system is presented for the dehumidification and cooling of a commercial building in summer seasons. The OHTCM has two objectives. The first objective of the OHTCM is to minimize the predicted percentage of dissatisfied (PPD) which is the human thermal comfort index, and the second objective is to minimize the power consumption of the desiccant wheel cooling system. Model predictive control (MPC) strategy has the ability to handle constraints, being able to use simple models and to change controls dynamically in terms of temperature, humidity and air velocity changes, which makes it very practical to use in indoor human thermal comfort control problem. Therefore, MPC strategy is applied to implement the optimal operation of the desiccant wheel cooling system during working hours of the commercial building. To illustrate the practical applications of the MPC strategy, the optimization of the desiccant wheel cooling system in a commercial building of South Africa is studied.

Human-Biometeorological Assessment of Urban Structures in Extreme Climate Conditions: The Example of Birobidzhan, Russian Far East

The study shows the effect of urban structures on human thermal comfort indices in the extreme climate region of the Russian Far East, with an annual temperature range of . The study examines different urban zones in Birobidzhan, the capital city of the Jewish Autonomous Region (JAR). The climate of this region can be characterized as continental monsoon climate. The difference of thermal values for three zones with different vegetation and build-up density shows the influence of urban planning on the local microclimate. The moderating effect of dense build-up and inner city vegetation on extreme thermal conditions becomes clear when comparing all zones. Through the analysis of daily and monthly timelines it was possible to determine preferable times of the day for inner city outdoor activities. From the results derived from PET with a total of 170 days per year with PET values below Birobidzhan can be considered a region of extreme cold stress. This means that an adaptation based solely on behaviour and clothing is not sufficient, but an adaptation of the urban surroundings and therefore the identification and choice of preferable urban structures is necessary.

Effect of thermal environment on the temporal, spatial and seasonal occurrence of measles in Ondo state, Nigeria

We investigated the temporal and spatial dynamics, as well as the seasonal occurrence of measles in Ondo state, Nigeria, to better understand the role of the thermal environment in the occurrence of the childhood killer disease measles, which ranks among the top ten leading causes of child deaths worldwide. The linkages between measles and atmospheric environmental factors were examined by correlating human-biometeorological parameters in the study area with reported clinical cases of measles for the period 1998-2008. We also applied stepwise regression analysis in order to determine the human-biometeorological parameters that lead to statistical changes in reported clinical cases of measles. We found that high reported cases of measles are associated with the least populated areas, where rearing and cohabitation of livestock/domestic animals within human communities are common. There was a significant correlation (P < 0.01) between monthly cases of measles and human-biometeorological parameters except wind speed and vapour pressure. High transmission of measles occurred in the months of January to May during the dry season when human thermal comfort indices are very high. This highlights the importance of the thermal environment in disease demographics since it accounted for more than 40% variation in measles transmission within the study period.

A distributed sensor network for measurement of human thermal comfort feelings

Previous research suggested that real-time measurement of human thermal comfort feelings could enhance the operation of an air-conditioning system. However, there is no such measurement system in the market. The reason is the difficulty in obtaining the real-time values of predicted mean vote (PMV), a well-recognized human thermal comfort index. In this paper, a distributed sensor network was employed to conduct real-time PMV measurement in office environments. Smart sensors were installed at different locations and were connected on the network. They measured the thermal data around an occupant and processed them in order to derive important information. This information was then transferred over the network to facilitate the measurement of PMV values. A laboratory experiment was performed to evaluate the technical feasibility of the approach, in which the prototype of the newly proposed measurement system was tested. An accuracy of ±0.5 deviating from the actual PMV value was found. A case study was then conducted to evaluate the economic impact of the system in an office using computer simulation. The new measurement system was first modeled to compute PMV values in the office. Advanced control algorithms were employed to issue control actions to maintain the thermal environment by using the PMV values from the measurement system. Much better performance in terms of human comfort and energy consumption was achieved. In conclusion, practical real-time PMV measurement was made feasible by using a distributed sensor network, which yielded a better air-conditioning control.

Neighborhood microclimates and vulnerability to heat stress

Human exposure to excessively warm weather, especially in cities, is an increasingly important public health problem. This study examined heat-related health inequalities within one city in order to understand the relationships between the microclimates of urban neighborhoods, population characteristics, thermal environments that regulate microclimates, and the resources people possess to cope with climatic conditions. A simulation model was used to estimate an outdoor human thermal comfort index (HTCI) as a function of local climate variables collected in 8 diverse city neighborhoods during the summer of 2003 in Phoenix, USA. HTCI is an indicator of heat stress, a condition that can cause illness and death. There were statistically significant differences in temperatures and HTCI between the neighborhoods during the entire summer, which increased during a heat wave period. Lower socioeconomic and ethnic minority groups were more likely to live in warmer neighborhoods with greater exposure to heat stress. High settlement density, sparse vegetation, and having no open space in the neighborhood were significantly correlated with higher temperatures and HTCI. People in warmer neighborhoods were more vulnerable to heat exposure because they had fewer social and material resources to cope with extreme heat. Urban heat island reduction policies should specifically target vulnerable residential areas and take into account equitable distribution and preservation of environmental resources.