Center for the Built Environment

Causal thinking emphasizes the understanding of asymmetric causal relationships between variables, requiring us to specify which variable is the cause (independent variable) and which is the effect (dependent variable). Reversing the causal relationship direction can lead to profoundly different assumptions and interpretations. We demonstrate this by comparing two linear regression approaches used in thermal comfort research: Approach (a), which regresses thermal sensation votes (y-axis) on indoor temperature (x-axis); Approach (b), which does the reverse, regressing indoor temperature (y-axis) on thermal sensation votes (x-axis). From a correlational perspective, they may appear interchangeable, but causal thinking reveals substantial and practical differences between them. Approach (a) represents occupants’ thermal sensations as responses to indoor temperature. In contrast, Approach (b), rooted in adaptive comfort theory, suggests that thermal sensations can trigger behavioral changes, which in turn alter indoor temperature. Using the same data, we found that two approaches lead to different neutral temperatures and comfort zones. Approach (b) leads to what we call a ‘preferred zone’, which is 10 °C narrower than the conventionally derived comfort zone using Approach (a). We hypothesize that the ‘preferred zone’ might be interpreted as thermal conditions that occupants are likely to choose when they have significant control over their personal and environmental thermal settings. This finding has important implications for occupant comfort and building energy efficiency. We highlight the importance of integrating causal thinking into correlation-based statistical methods, which have been prevalent in building science research, especially given the increasing volume of data in the built environment.

Desk fans allow individual thermal adjustment in shared spaces which increases occupants’ thermal satisfaction. When associated with the increase of room conditioning system setpoint temperature, they can also reduce energy use. In comparison to other Personal Comfort Systems (PCS), low-power desk fans can be very efficient for cooling. Nevertheless, previous studies identify some barriers to their implementation and show no clear guidelines on how to overcome them. Therefore, this study presents the results of a field implementation of desk fans in an open office in Brazil. The intervention consisted of providing one desk fan for each occupant and progressively increasing the setpoint temperature. Indoor thermal conditions were recorded simultaneously with occupants’ thermal perception using sensors and surveys. Results show fans increased thermal satisfaction by 20 %. And, when fans were available, the preferred indoor air temperature increased by 1 °C. However, many constraints affect the results. Based on this experience, we propose guidelines for future implementation. We emphasize the need to understand the HVAC system, engage building operators, and apply gradual temperature modification. As occupants’ expectations had a great impact on the potential temperature extension, we suggest a way to limit temperature extension in future implementations.

We evaluate the heat transfer from radiant ceilings that have suspended acoustical panels present for noise reduction. An upward-directed ceiling fan is added to offset the reduction of heat exchange due to the acoustical panels. We systematically simulate the indoor thermal environment and the changes to heat transfer coefficients caused by the interaction between radiant ceiling panels, acoustical panels, and ceiling fan under four influencing factors: (1) coverage ratio of acoustical panels, (2) fan rotational speed, (3) radiation panel temperature and (4) room height. The simulation method is validated with experimental data. Numerical results show that the augmented air speed increases convective and total heat transfer for radiant panel. Simulated temperature non-uniformity, air and operative temperature in the occupied part of the room is reduced with increased fan speed, and with decreased acoustical panel coverage ratio. The PMV increased with increased acoustical panel coverage ratio and radiant surface temperature, and also with reduced fan speed. When using fans, the radiant surface temperature can be raised 2 ℃ while maintaining equivalent thermal comfort, allowing higher water supply temperatures. The radiation heat transfer coefficient of the bare ceiling is decreased 25% by adding 63% acoustical panel coverage. The total heat transfer coefficient of radiant ceiling increases with fan speed up to 106.2% over a no-fan base case, and decreases with increased acoustical panel coverage ratio. The study indicates that an upward-directed ceiling fan is a worthwhile method to enable raised radiant surface temperatures, save cooling energy, and reduce surface condensation risk.

Small conference rooms are often used for either face-to-face communication or for virtual meetings involving an electroacoustical link between a talker and a listener. The intelligibility of speech in such environments depends on a number of factors, one of which is the nature of the reverberant sound within the space. Treating such a room with sound-absorbing materials helps reduce the so-called “cognitive load” for people who are spaced some distance away from a talker or who are listening to monaural speech reproduced by a loudspeaker. This study describes an acoustical retrofit of a small conference room to attain the reverberation time criterion found in LEED version 4.1 ID+C. Several mathematical models were used to predict the reverberation time before and after adding soundabsorbing treatment. In addition, measurements were conducted to quantify the before and after room reverberation characteristics. We found that speech was always intelligible both before and after the retrofit; however, one’s cognitive load is noticeably reduced when listening to speech after installation of the treatment.

The purpose of this paper is to evaluate the performance of a novel office temperature control system. To make occupants more comfortable with less energy, we have been developing a new system that uses an inexpensive infrared camera to evaluate occupants’ thermal sensation and optimize room temperature. The system (1) detects the positions of a person’s face, nose, and hands in a thermal image taken by an infrared camera and measures temperatures in those areas; (2) predicts thermal sensation using measured skin temperatures; and (3) adjusts an HVAC set-point temperature based on the predicted sensation to optimize occupant thermal comfort. We compared the comfort and energy performance of the new system to conventional control using a fixed setpoint of 72.0 °F (22.2 °C) in a small conference room. The results indicate that the conventional control often overcooled the occupants, whereas our system reduced cooling energy consumption and made the occupants more thermally neutral and comfortable than the conventional control.

People usually experience transient thermal environments when entering or leaving a conditioned indoor environment. This has been previously explored but there is little knowledge on the impact of temperature step-changes on thermal comfort in a radiantly cooled environment. We aim to investigate human comfort and underlying physiological mechanism in such conditions. We assessed thermal comfort, sick building syndromes (SBS) symptoms, and physiological responses. Twenty healthy participants were exposed to three temperature step-change conditions with three outdoor air temperatures (29 ℃, 33 ℃ and 36 ℃) and one indoor air temperature of 26 ℃. Subjective evaluation was collected through a questionnaire. Blood oxygen saturation (SpO2), skin temperature, and electrocardiograph (ECG) were measured. As expected, the overall thermal sensation, comfort, acceptability, preference, and subjective air freshness changed significantly before and after temperature step-changes. Perceived sweat and chest tightness were also affected by the temperature step-changes. Skin temperature, heart rate, time-domain, and nonlinear heart rate variability were affected significantly under temperature step-changes. We observed the overshoot phenomenon with thermal sensation and subjective air freshness under temperature down-step. Thermal sensation had a faster stabilization time than the measured physiological parameters (i.e., skin temperature, heart rate and heart rate variability) under temperature step-changes. The stabilization time before starting a thermal comfort experiment should be at least 30 minutes. Thermal sensation and skin temperature had an asymmetry effect on temperature step-changes.

Providing indoor environmental quality (IEQ) that satisfies building occupants is an essential component for sustainable and healthy buildings. Existing studies mainly analyse the importance of environmental factors on occupant satisfaction but often overlook the influence of personal factors. Here, we aim to explore the impact of personal factors like life satisfaction, job satisfaction, the Big Five personality traits, sex, and age on occupant IEQ satisfaction. We conducted a cross-sectional assessment in nine air-conditioned commercial buildings in Singapore and surveyed 1162 individuals on their satisfaction with 18 IEQ parameters. Using proportional odds ordinal logistic regression, we found that occupants with higher job and life satisfactions were, respectively, 1.3 – 2.3 and 1.3 – 2 times more likely satisfied with the 18 IEQ parameters. The odds ratios (OR) for overall environment satisfaction and job and life satisfaction were 2.1 (95% CI: 1.8 – 2.6) and 1.9 (95% CI: 1.6 – 2.3). We speculate that occupants’ satisfaction with their job and the overall environment are entwined, meaning that a better workspace could improve job satisfaction and vice versa. We observed some associations between the Big Five personality traits and some IEQ parameters, but the corresponding effects were small. Due to the substantial relationship between job and overall workspace satisfaction observed in this study, we recommend including job satisfaction questions in future post occupancy evaluations (POEs).

Thermal comfort in buildings is typically assessed through occupant surveys, especially for short-term thermal comfort. For long-term thermal comfort, thermal comfort standards and recent research suggest continuous physical monitoring of temperature is sufficient. However, a lack of formal rules for data representation in building automation systems and the high costs of analytical application development for buildings impede predicting long-term thermal comfort at scale. This paper demonstrates portable and reproducible application development techniques for evaluating long-term thermal comfort with the Brick metadata schema and Mortar data testbed. We take advantage of the relatively large Mortar dataset containing over 25 buildings to improve the generalizability of long-term thermal comfort evaluation. Previous research often performs analysis on limited datasets.The design of Mortar enables running the same software applications across many heterogeneous buildings, simplifying building analytics application development, and acting as a vehicle for reproducible evaluations in building science. To assess the efficacy of this workflow, we identify six air temperature- based long-term thermal comfort evaluation metrics from the literature and implement them in software. The six indices are temperature mean index, temperature variance index, degree hours index, range outlier index, daily range outlier index, and combined outlier index. During the application development, we find that the calculation of threshold in the daily range outlier index is arbitrary, and the months belonging to cooling and heating seasons with different comfortable temperature ranges are unclear. Also, all long-term thermal comfort indices fail to differentiate between tool hot and too cold. To address this, we develop two new metrics to calculate overheating and overcooling separately. We evaluate our software across all the buildings available in the Mortar testbed. The result shows that 25 buildings with 1953 thermal zones have qualified air temperature sensor data during building occupancy. Based on this building dataset, we analyze Pearson correlation among long-term thermal comfort indices. The range outlier index has a 0.19 Pearson correlation coefficient with the daily range outlier index, compared with the Pearson correlation coefficient of-0.35 at a randomly selected building in Mortar. The opposite result indicates that a small building dataset is not capable of long-term thermal comfort indices development, generating misleading results. With the help of the uniform Brick metadata schema, we also investigate disaggregating the results by buildings, floors, zones, and equipment. We summarize them as a means of identifying problem areas and equipment.