Here we present a field study examining the impact of elevated room temperature and air movement on thermal comfort and self-reported productivity. This experiment was performed in three environmental conditions (one with a set-point of 23 °C—a typical set-point used in Singapore—and two elevated (up to 28 °C) room temperature conditions). Occupants had shared control of ceiling fans. The results show that the most comfortable thermal condition, with thermal sensation closest to neutral, is achieved at a room temperature of 26 °C with operating fans. Increasing the temperature set-point from 23 °C to 26 °C resulted in a significant increase in thermal acceptability (from 59% to 91%), and a 44 kWh/m2yr savings in electrical energy used for comfort cooling. We found that a room’s set-point temperature can be increased up to 27 °C without creating a negative impact when controllable air movement is provided compared to an environment with a set-point of 23 °C. Thermal satisfaction is significantly higher in spaces of 26 °C with operating fans, than when the room’s temperature is set at the typical 23 °C. Moreover, the relative humidity in the office is decreased from 62% (when the temperature was 23 °C) to 50% when the temperature was 27 °C. Occupant’s self-reported ability to concentrate, be alert, and ability to be productive was comparably high in all conditions. The results indicate that work performance is poorly correlated with room temperature, but increases with greater individual thermal satisfaction.

Globally 39% of adults are overweight, 13% are obese, and 9% are underweight. Current thermal comfort standards, catering to the normal weight occupant, may hence be ignoring nearly 60% of the population. This could have significant comfort, productivity and energy implications. We performed a climate chamber study of the thermal response of 76 subjects in all the body mass index (BMI) categories, from 17 and 37 kg/m2. Every participant underwent the same four sessions at average operative temperatures of 19.9, 22.4, 25.3, and 28.2 °C. We obtained subjective feedback from participants on their thermal sensation and preference, humidity sensation and preference, thermal comfort rating, and air quality perception. We also measured skin temperature, blood pressure, pulse rate, blood glucose level, weight, height, waist and hip circumferences and body composition. Overall, we did not find significant impact of BMI on the thermal sensation. However, the overweight and obese participants preferred lower temperature compared to normal weight and underweight participants which may indicate practical implication for control strategies.

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.

Comfort cooling by ceiling fans is cost-effective and energy-efficient compared to compressor-based cooling and fans are commonly used in tropical and subtropical countries. There are however limited data and design tools supporting the design of fan systems, especially for situations where there are multiple fans. In this paper, we investigate airflow profiles induced by a single fan and multiple fans using high spatial resolution air speed measurements (5,760 and 20,160 measuring points for the two cases respectively) in a climatic chamber. To authors' knowledge, this is the first time that interaction between multiple fans has been reported. We developed typical airflow patterns from the measurements and further validated them via smoke visualization. The singlefan results are consistent with previous studies of this configuration, providing additional refinements. For the multiple-fan case, both the difference of fan speed levels and the distance between the fans affect the interacting airflow profiles of the fans in complex ways. When fans are close enough, the combined air speed profile cannot be extrapolated from the profile of a single fan. All the measurement results are open sourced: raw data is included in the supplementary materials and can be visualized via an online platform (single fan, multiple fans). The data and the tool can be used to validate CFD models and inform fan layout design.

Elevated air movement produced by fans can offset air-conditioning energy requirements by allowing temperature setpoints to be raised without compromising thermal comfort. These advantages are even greater in hot and humid climates that inherently have large and sustained indoor cooling requirements. Few studies have assessed the in-situ benefits of fans in actual buildings. We installed ceiling and desk fans into a Zero Energy office building (675 m2) in Singapore. Across an 11-week period, 35 occupants alternated between two conditions (no fan vs. fan): 24 °C setpoint with fans off, and 26.5 °C setpoint with fans on. When the temperature setpoint was raised and elevated air movement was provided, a 32% energy reduction was obtained. The energy savings accrued without any negative impacts occurring on thermal satisfaction. Overcooling caused by thermal preference to slightly warmer and warmer conditions was substantially reduced from 33 to 9%. No changes in perceived air-staleness or self-reported alertness and ability to concentrate occurred either, indicating parity across the no fan and fan conditions. Although occupants primarily relied on ceiling fans at the 26.5 °C setpoint, they were by default on at the beginning of each day, giving less incentive to use the desk fans. Our study took place in a high-performance Zero Energy building, whereby thermal dissatisfaction was already low (7%). Therefore, notable changes did not occur, but significant improvements to thermal comfort could still occur in buildings that are unable to maintain high levels of thermal satisfaction.

This paper introduces a database of 34 field-measured building occupant behavior datasets collected from 15 countries and 39 institutions across 10 climatic zones covering various building types in both commercial and residential sectors. This is a comprehensive global database about building occupant behavior. The database includes occupancy patterns (i.e., presence and people count) and occupant behaviors (i.e., interactions with devices, equipment, and technical systems in buildings). Brick schema models were developed to represent sensor and room metadata information. The database is publicly available, and a website was created for the public to access, query, and download specific datasets or the whole database interactively. The database can help to advance the knowledge and understanding of realistic occupancy patterns and human-building interactions with building systems (e.g., light switching, set-point changes on thermostats, fans on/off, etc.) and envelopes (e.g., window opening/closing). With these more realistic inputs of occupants' schedules and their interactions with buildings and systems, building designers, energy modelers, and consultants can improve the accuracy of building energy simulation and building load forecasting.