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The ability to discern the content of the view through a window is referred to as view clarity. It is often overlooked in the design process, and the methods of shading daylight can affect window views. We conducted a narrative review of building standards and the scientific literature to better understand how shades can be designed so as to retain the window view. View clarity was characterised by three main dimensions: (1) the shading solution, (2) the view content and (3) the observer. Each dimension and the interactions between them influence view clarity. These interactions make it difficult to predict view clarity for all the situations that can occur in buildings. Nonetheless, we highlighted the effects of different shades on the view clarity. Our insights can help designers consider these impacts within the context of overall window design.

Assessment of integrated personal exposure (PE) to airborne particulate matter (PM) across diverse microenvironments (MEs) over 24 hours under different exposure scenarios is necessary to identify appropriate strategies to improve urban air quality and mitigate the health effects of PM. We carried out a collaborative study in a densely populated city-state (Singapore) to assess the integrated PE to fine particles (PM2.5), ultrafine particles (UFPs) and black carbon (BC) across diverse indoor and outdoor urban MEs, estimate related health risks and make suitable recommendations for healthy living in cities. Two volunteers with different lifestyles participated in the study by tracking their PE to particulate air pollution and the time-activity patterns over 24 hours using portable PM monitoring devices and recording their whereabouts using GPS coordinates. Home, transport and recreation (i.e., food court) MEs represented pollution hotspots of PM2.5 (21.0 μg/m3), BC (3.4 μg/m3) and UFP (33.0 × 103 #/cm3), respectively. Among the different modes of transport used by the participants (walking, cycling, e-scooter, mass rapid transport (MRT), bus, car and taxi), the air pollutants had elevated concentrations while commuting by public transport (bus and MRT) as well as during active modes of transport (walking and cycling). Air-conditioned cars and taxis, equipped with air filtration systems, represented the lowest PE. The health risk assessment revealed that there are potential carcinogenic risks associated with the long-term exposure to elevated levels of PM2.5-bound toxic trace elements. These risks can be mitigated with the introduction of low-carbon and active modes of transport in place of internal combustion engines and the use of indoor air pollution exposure mitigation devices.

Thermal comfort assessment for the built environment has become more available to analysts and researchers due to the proliferation of sensors and subjective feedback methods. These data can be used for modeling comfort behavior to support design and operations towards energy efficiency and well-being. By nature, occupant subjective feedback is imbalanced as indoor conditions are designed for comfort, and responses indicating otherwise are less common. This situation creates a scenario for the machine learning workflow where class balancing as a pre-processing step might be valuable for developing predictive thermal comfort classification models with high-performance. This paper investigates the various thermal comfort dataset class balancing techniques from the literature and proposes a modified conditional Generative Adversarial Network (GAN), comfortGAN, to address this imbalance scenario. These approaches are applied to three publicly available datasets, ranging from 30 and 67 participants to a global collection of thermal comfort datasets, with 1,474; 2,067; and 66,397 data points, respectively. This work finds that a classification model trained on a balanced dataset, comprised of real and generated samples from comfortGAN, has higher performance (increase between 4% and 17% in classification accuracy) than other augmentation methods tested. However, when classes representing discomfort are merged and reduced to three, better imbalanced performance is expected, and the additional increase in performance by comfortGAN shrinks to 1 - 2%. These results illustrate that class balancing for thermal comfort modeling is beneficial using advanced techniques such as GANs, but its value is diminished in certain scenarios. A discussion is provided to assist potential users in determining which scenarios this process is useful and which method works best.

The use of smiley-face polling stations has had a rapid growth as a means of automatically and efficiently collecting user satisfaction verdicts in airports, restrooms, museums, and retail. Their advantages are that they are low cost, efficient for both respondents and analysts, in addition to having higher response rates than other survey types. Their main disadvantage is the lack of control with who is voting, meaning both repeat voters and non-voters may lead to biased results. The aim of this study is to assess the representativeness and functioning of such publicly located satisfaction polling stations (SPSs) in an indoor climate setting, and to evaluate their potential for real-time evaluation of occupant's satisfaction with the indoor climate. We carried out continuous field tests in two office buildings for more than two months where the results of SPSs were compared with 473 survey results collected in 10 rounds during the tests. To assess how sensitive the instrument was to changing conditions, we deliberately changed temperature setpoints on selected days in one of the buildings. We found that the SPSs had a high and variable non-response bias which could result in a low accuracy for benchmarking of building indoor climate satisfaction. Results also showed a high correlation between SPS complaints and complaints recorded in the surveys for the thermal comfort aspect of indoor climate, including thermal comfort induced by temperature interventions. SPSs can provide valuable continuous recordings of the occupant's satisfaction with the indoor climate.

Well-being in the built environment is a topic that features frequently in building standards and certification schemes, in scholarly articles and in the general press. However, despite this surge in attention, there are still many questions on how to effectively design, measure, and nurture well-being in the built environment. Bringing together experts from academia and the building industry, this paper aims to demonstrate that the promotion of well-being requires a departure from conventional agendas. The ten questions and answers have been arranged to offer a range of perspectives on the principles and strategies that can better sustain the consideration of well-being in the design and operation of the built environment. Placing a specific focus on some of the key physical factors (e.g., light, temperature, sound, and air quality) of indoor environmental quality (IEQ) that strongly influence occupant perception of built spaces, attention is also given to the value of multi-sensory variability, to how to monitor and communicate well-being outcomes in support of organizational and operational strategies, and to future research needs and their translation into building practice and standards. Seen as a whole, a new framework emerges, accentuating the integration of diverse new competencies required to support the design and operation of built environments that respond to the multifaceted physical, physiological, and psychological needs of their occupants.

The Center for the Built Environment (CBE) Thermal Comfort Tool is a free online tool for thermal comfort calculations and visualizations that complies with the ASHRAE 55–2017, ISO 7730:2005 and EN 16798–1:2019 Standards. It incorporates the major thermal comfort models, including the Predicted Mean Vote (PMV), Standard Effective Temperature (SET), adaptive models, local discomfort models, SolarCal, and dynamic predictive clothing insulation. Our tool also provides dynamic and interactive visualizations of thermal comfort zones. The CBE Thermal Comfort Tool has several practical applications and each year is used by more than 49,000 users worldwide, including engineers, architects, researchers, educators, facility managers and policymakers.

We developed pythermalcomfort, a Python package that allows users to calculate the most common thermal comfort indices in compliance with the main thermal comfort standards. For example, pythermalcomfort can be used to calculate: whole body thermal comfort indices (e.g., Predicted Mean Vote, adaptive models, Standard Equivalent Temperature), local discomfort, clothing insulation, and psychrometric properties of air. All pythermalcomfort functions have been validated against the reference tables provided in the corresponding thermal comfort standards. We have developed documentation, examples and tutorial videos to guide users on how to use our package. pythermalcomfort allows researchers and professionals to accurately perform complex thermal comfort calculations without the need of re-writing the programming code. With Python being among the most widely utilized programming languages and pythermalcomfort being the only Python library which includes a comprehensive list of thermal comfort functions, we believe that pythermalcomfort will have a significant impact on both the research and industrial communities.

People's subjective response to any thermal environment is commonly investigated by using rating scales describing the degree of thermal sensation, comfort, and acceptability. Subsequent analyses of results collected in this way rely on the assumption that specific distances between verbal anchors placed on the scale exist and that relationships between verbal anchors from different dimensions that are assessed (e.g. thermal sensation and comfort) do not change. Another inherent assumption is that such scales are independent of the context in which they are used (climate zone, season, etc.). Despite their use worldwide, there is indication that contextual differences influence the way the scales are perceived and therefore question the reliability of the scales’ interpretation. To address this issue, a large international collaborative questionnaire study was conducted in 26 countries, using 21 different languages, which led to a dataset of 8225 questionnaires. Results, analysed by means of robust statistical techniques, revealed that only a subset of the responses are in accordance with the mentioned assumptions. Significant differences appeared between groups of participants in their perception of the scales, both in relation to distances of the anchors and relationships between scales. It was also found that respondents’ interpretations of scales changed with contextual factors, such as climate, season, and language. These findings highlight the need to carefully consider context-dependent factors in interpreting and reporting results from thermal comfort studies or post-occupancy evaluations, as well as to revisit the use of rating scales and the analysis methods used in thermal comfort studies to improve their reliability.

Climate models imply that by 2100 atmospheric CO2 levels could exceed 900 ppm. At these levels, subscribing to current ventilation rates would lead to indoor CO2 levels ≥1,400 ppm, possibly impacting our physiology and other responses. We ran a randomized, within-subject study with 15 participants to examine the physiological effects of 2,5 hour exposure to three CO2 levels: 900 ppm, 1450 ppm (reduced ventilation), and 1450 ppm (pure CO2 added, ventilation same as 900 ppm). End-tidal CO2 and respiration rate across the different exposures were not significantly different. Spirometry parameters reduced significantly from the beginning to the end at reduced ventilation exposure compared to the 900 ppm condition (p

Green-building certification systems aim at improving the design and operation of buildings. However, few detailed studies have investigated whether a green rating leads to higher occupant satisfaction with indoor environmental quality (IEQ). This research builds on previous work to address this. Based on the analysis of a subset of the Center for the Built Environment Occupant Indoor Environmental Quality survey database featuring 11,243 responses from 93 Leadership in Energy and Environmental Design (LEED)-rated office buildings, this study explores the relationships between the points earned in the IEQ category and the satisfaction expressed by occupants with the qualities of their indoor environment. It was found that the achievement of a specific IEQ credit did not substantively increase satisfaction with the corresponding IEQ factor, while the rating level, and the product and version under which certification had been awarded, did not affect workplace satisfaction. There could be several reasons for this, some of which are outside the control of designers and beyond the scope of rating systems based primarily on design intent. The challenges and priorities facing building professionals, researchers and green building certification systems are discussed for the creation of more comfortable, higher performing and healthier green-rated buildings.

Replicating scientific findings is a fundamental aspect of research. However, in studies of discomfort due to glare, it is difficult to make comparisons between the results of different experiments since the statistical tests usuallyreported do not allow independent findings to be directly compared to each other. Here we present an alternative Bayesian approach that can address this problem. To show how this approach works, we performed a laboratory test with 55 participants to validate the effect of order bias previously detected in a similar study evaluating discomfort due to glare but, this time, under a large luminous source. Using the luminance adjustment procedure, the glare source was varied to meet four sensations of discomfort due to glare. Adjustments were performed under three different order sequences: ascending, descending, and randomised. Test participants provided glare settings using a newly proposed evaluation scale. The effect of order bias detected in the original study was compared to the data obtained with the same methodological procedure in the new experiment using Bayesian inferential tests. The results showed a close replication, highlighting that the order bias effect found in the original study was also present in the new experiment. The wide application of Bayesian methods in thedesign and analysis of experimental studies may improve the accuracy and validity of glare models.

This paper presents preliminary analysis of occupant satisfaction with indoor environmental quality in BREEAM (Building Research Establishment Environmental Assessment Method) and non-BREEAM certified offices in the UK. Results from cross-sectional questionnaires (N = 121) showed that BREEAM certification per se did not seem to substantively influence building and workspace satisfaction. Conversely, occupants of BREEAM offices tended to be less satisfied with air quality and visual privacy than users of non-BREEAM buildings. Lower satisfaction was also detected in BREEAM offices for occupants having spent over 24 months in their building, and for users working in open-plan spaces. To interpret these findings, a methodology for data analysis was adopted whereas responses to point-in-time surveys (N = 82) were paired with environmental measurements. Broadening the perspective for appraising occupants’ perceptions, these combined techniques led to conclude that certification schemes should balance criteria addressing energy performance with design solutions considerate of issues of privacy, proxemics and perceived control over the qualities of the indoor environment.

© 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd Draft is unwanted local convective cooling. The draft risk model of Fanger et al. (Energy and Buildings 12, 21-39, 1988) estimates the percentage of people dissatisfied with air movement due to overcooling at the neck. There is no model for predicting draft at ankles, which is more relevant to stratified air distribution systems such as underfloor air distribution (UFAD) and displacement ventilation (DV). We developed a model for predicted percentage dissatisfied with ankle draft (PPDAD) based on laboratory experiments with 110 college students. We assessed the effect on ankle draft of various combinations of air speed (nominal range: 0.1-0.6 m/s), temperature (nominal range: 16.5-22.5°C), turbulence intensity (at ankles), sex, and clothing insulation (

Radiant chilled ceilings with displacement ventilation represent a promising system that combines the energy efficiency of both subsystems with the opportunity for improved ventilation performance. Laboratory experiments were conducted for an interior zone office with a very high cooling load (91.0 W/m2) and with two different heat source heights to investigate their influence on thermal stratification and air change effectiveness. The results showed that displacement ventilation with a chilled ceiling is able to provide a stable thermal stratification and improved ventilation effectiveness compared to mixing ventilation for a wide range of configurations. Stratification and air change effectiveness decreases when a larger portion of the cooling load is removed by the chilled ceiling. For every degree decrement of the surface temperature of the radiant ceiling, the stratification decreases by 0.13 K and the air change effectiveness by 0.13. Moving the computer processing units (representing 51% of the total room heat gain) from the floor level to 1.5 m height markedly increased the room median stratification and the median air change effectiveness (from 1.15 to 2.90). Therefore, increasing the height of heat sources has the potential to reduce energy use and improve indoor air quality.

This report documents the UFAD module specifications for EnergyPlus v3.1 and higher. We have conducted extensive validation of the interior zone model for Price swirl and York MIT1 variable area (VA) diffusers. These correlations should not be considered to be applicable to other diffuser types. (See below for user procedures to support other diffuser brands and types.)