Search

School learning environments play a crucial role in both student and faculty outcomes; however, the limited funding allocated to public school facilities can result in poor environmental conditions which can hinder occupant health and performance. Existing school facilities must then explore affordable retrofit strategies that can effectively improve health and performance outcomes. The emerging field of biophilic design offers significant potential for improving existing school environments with benefits for both the students and faculty. Through case study research, this study proposes a toolkit of 42 biophilic retrofits for existing K-12 schools in a set of stakeholder cards that illustrate precedents, known impacts, and their relevance to high-performance schools. Additionally, a stakeholder card sorting study was conducted to establish the perceived viability and impact of each strategy. The findings reveal that biophilic retrofit design strategies are perceived by school community stakeholders to be impactful with varying levels of affordability. These findings further demonstrate that a toolkit of biophilic interventions for K-12 schools will offer invaluable insights to improve student and faculty conditions.

Outlier detection plays a critical role in building operation optimization and data quality maintenance. However, existing methods often struggle with the complexity and variability of building energy data, leading to poorly generalized and explainable results. To address the gap, this study introduces a novel Vision-based Outlier Detection (VOD) approach, leveraging computer vision models to spot outliers in the building energy records. The models are trained to identify outliers by analyzing the load shapes in 2D time series plots derived from the energy data. The VOD approach is tested on four years of workday time-series electricity consumption data from 290 commercial buildings in the United States. Two distinct models are developed for different usage purposes, namely a classification model for broad-level outlier detection and an object detection model for the demands of precise pinpointing of outliers. The classification model is also interpreted via Grad-CAM to enhance its usage reliability. The classification model achieves an F1 score of 0.88, and the object detection model achieves an Average Precision (AP) of 0.84. VOD is a very efficient path to identifying energy consumption outliers in building operations, paving the way for the enhancement of building energy data quality, operation efficiency, and energy savings.

Buildings account for 40% of the energy consumption and 31% of the CO2 emissions in the United States. Energy retrofits of existing buildings provide an effective means to reduce building consumption and carbon footprints. A key step in retrofit planning is to predict the effect of various potential retrofits on energy consumption. Decision-makers currently look to simulation-based tools for detailed assessments of a large range of retrofit options. However, simulations often require detailed building characteristic inputs, high expertise, and extensive computational power, presenting challenges for considering portfolios of buildings or evaluating large-scale policy proposals. Data-driven methods offer an alternative approach to retrofit analysis that could be more easily applied to portfolio-wide retrofit plans. However, current applications focus heavily on evaluating past retrofits, providing little decision support for future retrofits. This paper uses data from a portfolio of 550 federal buildings and demonstrates a data-driven approach to generalizing the heterogeneous treatment effect of past retrofits to predict future savings potential for assisting retrofit planning. The main findings include the following: (1) There is high variation in the predicted savings across retrofitted buildings, (2) GSALink, a dashboard tool and fault detection system, commissioning, and HVAC investments had the highest average savings among the six actions analyzed; and (3) by targeting high savers, there is a 110–300 billion Btu improvement potential for the portfolio in site energy savings (the equivalent of 12–32% of the portfolio-total site energy consumption).

Objective: Panic attacks are an impairing mental health problem that affects 11% of adults every year. Current criteria describe them as occurring without warning, despite evidence suggesting individuals can often identify attack triggers. We aimed to prospectively explore qualitative and quantitative factors associated with the onset of panic attacks. Results: Of 87 participants, 95% retrospectively identified a trigger for their panic attacks. Worse individually reported mood and state-level mood, as indicated by Twitter ratings, were related to greater likelihood of next-day panic attack. In a subsample of participants who uploaded their wearable sensor data (n = 32), louder ambient noise and higher resting heart rate were related to greater likelihood of next-day panic attack. Conclusions: These promising results suggest that individuals who experience panic attacks may be able to anticipate their next attack which could be used to inform future prevention and intervention efforts.

This study proposes a generalized building energy and carbon emissions benchmarking approach. Leveraging eleven years of real-world data from twelve U.S. cities, an advanced ensemble learning model is employed to predict building site, source energy, and carbon emissions. The generalizability is validated across seven climate zones, yielding R2 values ranging from 0.3 to 0.9. Additionally, a post-prediction analysis method is proposed that categorizes actual and predicted values into well-estimated, underestimated, and overestimated groups by an [−15%, 15%] acceptance interval (AI). This approach allows for assessing predictions related to energy, building types, and climate zones. The findings indicate the feasibility of a reliable generalized benchmarking tool. It’s been observed that energy in most underestimated groups tends to be higher than that of their overestimated counterparts. Over 63% of buildings' predictions perform within the well-estimated group by [−15%, 15%] AI.

This paper explores the role of international partnerships to facilitate low-energy building design, construction, and operations. We present the strategic approach, joint research and development outcomes, and implementation activities of a unique U.S.-India program on buildings energy efficiency, the Center for Building Energy Research and Development. We discuss the collaboration successes in both countries despite their dissimilar building contexts, implementation challenges and opportunities. We highlight a range of R&D outcomes, such as novel tools and technologies developed and tested by the joint teams, with their technical energy savings potential, as well as results of capacity building and technology demonstrations. A deep-dive into key new scientific methods around building energy monitoring and benchmarking that could have a significant impact on high-performanceof buildings in both countries is also provided. Finally, in addition to joint R&D successes, pathways to deployment, and lessons learned are discussed as key takeaways.

In response to a burgeoning pediatric mental health epidemic, recent guidelines have instructed pediatricians to regularly screen their patients for mental health disorders with consistency and standardization. Yet, gold-standard screening surveys to evaluate mental health problems in children typically rely solely on reports given by caregivers, who tend to unintentionally under-report, and in some cases over-report, child symptomology. Digital phenotype screening tools (DPSTs), currently being developed in research settings, may help overcome reporting bias by providing objective measures of physiology and behavior to supplement child mental health screening. Prior to their implementation in pediatric practice, however, the ethical dimensions of DPSTs should be explored. Herein, we consider some promises and challenges of DPSTs under three broad categories: accuracy and bias, privacy, and accessibility and implementation. We find that DPSTs have demonstrated accuracy, may eliminate concerns regarding under- and over-reporting, and may be more accessible than gold-standard surveys. However, we also find that if DPSTs are not responsibly developed and deployed, they may be biased, raise privacy concerns, and be cost-prohibitive. To counteract these potential shortcomings, we identify ways to support the responsible and ethical development of DPSTs for clinical practice to improve mental health screening in children.

Buildings account for 40% of the energy consumption and 31% of the CO2 emissions in the United States. Energy retrofits of existing buildings provide an effective means to reduce building consumption and carbon footprints. A key step in retrofit planning is to predict the effect of various potential retrofits on energy consumption. Decision-makers currently look to simulation-based tools for detailed assessments of a large range of retrofit options. However, simulations often require detailed building characteristic inputs, high expertise, and extensive computational power, presenting challenges for considering portfolios of buildings or evaluating large-scale policy proposals. Data-driven methods offer an alternative approach to retrofit analysis that could be more easily applied to portfolio-wide retrofit plans. However, current applications focus heavily on evaluating past retrofits, providing little decision support for future retrofits. This paper uses data from a portfolio of 550 federal buildings and demonstrates a data-driven approach to generalizing the heterogeneous treatment effect of past retrofits to predict future savings potential for assisting retrofit planning. The main findings include the following: (1) There is high variation in the predicted savings across retrofitted buildings, (2) GSALink, a dashboard tool and fault detection system, commissioning, and HVAC investments had the highest average savings among the six actions analyzed; and (3) by targeting high savers, there is a 110–300 billion Btu improvement potential for the portfolio in site energy savings (the equivalent of 12–32% of the portfolio-total site energy consumption).

This paper explores the role of international partnerships to facilitate low-energy building design, construction, and operations. We present the strategic approach, joint research and development outcomes, and implementation activities of a unique U.S.-India program on buildings energy efficiency, the Center for Building Energy Research and Development. We discuss the collaboration successes in both countries despite their dissimilar building contexts, implementation challenges and opportunities. We highlight a range of R&D outcomes, such as novel tools and technologies developed and tested by the joint teams, with their technical energy savings potential, as well as results of capacity building and technology demonstrations. A deep-dive into key new scientific methods around building energy monitoring and benchmarking that could have a significant impact on high-performanceof buildings in both countries is also provided. Finally, in addition to joint R&D successes, pathways to deployment, and lessons learned are discussed as key takeaways.

Wearable sensors facilitate the evaluation of gait and balance impairment in the free-living environment, often with observation periods spanning weeks, months, and even years. Data supporting the minimal duration of sensor wear, which is necessary to capture representative variability in impairment measures, are needed to balance patient burden, data quality, and study cost. Prior investigations have examined the duration required for resolving a variety of movement variables (e.g., gait speed, sit-to-stand tests), but these studies use differing methodologies and have only examined a small subset of potential measures of gait and balance impairment. Notably, postural sway measures have not yet been considered in these analyses. Here, we propose a three-level framework for examining this problem. Difference testing and intra-class correlations (ICC) are used to examine the agreement in features computed from potential wear durations (levels one and two). The association between features and established patient reported outcomes at each wear duration is also considered (level three) for determining the necessary wear duration. Utilizing wearable accelerometer data continuously collected from 22 persons with multiple sclerosis (PwMS) for 6 weeks, this framework suggests that 2 to 3 days of monitoring may be sufficient to capture most of the variability in gait and sway; however, longer periods (e.g., 3 to 6 days) may be needed to establish strong correlations to patient-reported clinical measures. Regression analysis indicates that the required wear duration depends on both the observation frequency and variability of the measure being considered. This approach provides a framework for evaluating wear duration as one aspect of the comprehensive assessment, which is necessary to ensure that wearable sensor-based methods for capturing gait and balance impairment in the free-living environment are fit for purpose.

Indoor acoustic quality is one of the critical indicators for occupants’ health, comfort, and productivity in contemporary office environments. Post-occupancy evaluation (POE) is usually employed to examine in situ acoustic measurements to ensure indoor acoustic quality. However, prevailing acoustic performance evaluation does not often consider the technical attributes of building systems (TABS) to holistically investigate the significant correlations between objective acoustic field measurements and subjective POE. As such, this study proposes to cross-examine in situ and perceived acoustic quality indices with TABS to quantify critical factors leading to enhanced occupant satisfaction. Statistical analyses suggest that technical building attributes can significantly influence occupants’ acoustic satisfaction compared to sound levels recorded in contemporary offices. For instance, lowering the distributed noise level from above 40% to 2% can lead to an average 21% increase in occupant satisfaction. Ultimately, incorporating environmental measurements with physical building attributes from an occupant-centric perspective can uncover applicable design guidelines for achieving optimal acoustic quality with the highest occupant satisfaction.

Buildings account for 40% of the energy consumption and 31% of the CO2 emissions in the United States. Energy retrofits of existing buildings provide an effective means to reduce building consumption and carbon footprints. A key step in retrofit planning is to predict the effect of various potential retrofits on energy consumption. Decision-makers currently look to simulation-based tools for detailed assessments of a large range of retrofit options. However, simulations often require detailed building characteristic inputs, high expertise, and extensive computational power, presenting challenges for considering portfolios of buildings or evaluating large-scale policy proposals. Data-driven methods offer an alternative approach to retrofit analysis that could be more easily applied to portfolio-wide retrofit plans. However, current applications focus heavily on evaluating past retrofits, providing little decision support for future retrofits. This paper uses data from a portfolio of 550 federal buildings and demonstrates a data-driven approach to generalizing the heterogeneous treatment effect of past retrofits to predict future savings potential for assisting retrofit planning. The main findings include the following: (1) There is high variation in the predicted savings across retrofitted buildings, (2) GSALink, a dashboard tool and fault detection system, commissioning, and HVAC investments had the highest average savings among the six actions analyzed; and (3) by targeting high savers, there is a 110–300 billion Btu improvement potential for the portfolio in site energy savings (the equivalent of 12–32% of the portfolio-total site energy consumption).

Biophilic design is one of a number of trending design practices that rely on nature-based systems, engineering principles and design cues to improve environmental quality, health, and efficiency. Biophilic design integrates but does not appropriate the contributions of other nature-based design techniques precisely because it can act as a platform or “interstitial tissue,” providing a connective language/practice/ethos that can unite disparate practices in the built environment more broadly. This paper provides an illustrative compilation of how biophilic design practices can directly support resilience in human health and the built environment on behalf of the International Living Future Institute's Biophilic Design Advisory Board. We strongly advocate the use of metrics related to climate change mitigation as a dimension of performance analysis for biophilic design practices as a demonstration of professional mindfulness and responsibility.

The increasingly collaborative nature of knowledge-based work requires workplaces to support both dynamic interactions and concentrated work, both of which are critical for collaboration performance. Given the prevalence of open-plan settings, this requirement has created new challenges for workplace design. Therefore, an understanding of the relationship between the spatial characteristics of workplace settings and the support for collaboration that is perceived by office workers is valuable and timely. Based on a study of 308 office workers in 27 office spaces, this article examines the relationship between a series of workplace spatial characteristics and the support that is perceived by the occupants for collaborations. The spatial characteristics that were examined included individual workstation characteristics that were derived from the literature and a new set of floor-plan layout variables that highlighted shared spaces that are critical for a variety of formal and informal collaboration activities at work. The key characteristics of workplace spatial settings that were associated with the support that the occupants perceived for collaboration were the distance from workstation to meeting space, the distance from workstation to shared service area, the distance from workstation to kitchen/coffee area, and the percentage of floor space that was dedicated to shared services and amenities. (Contains 6 tables and 1 figure.)

The indoor environmental quality (IEQ) of buildings can have a strong influence on occupants’ comfort, productivity, and health. Post-occupancy evaluation (POE) is necessary in assessing the IEQ of the built environment, and it typically relies on the subjective surveys of thermal quality, air quality, visual quality, and acoustic quality. In this research, we expanded POE to include both objective IEQ measurements and the technical attributes of building systems (TABS) that may affect indoor environment and user satisfaction. The suite of three tools, including user satisfaction survey, workstation IEQ measurements, and TABS in the National Environmental Assessment Toolkit (NEAT) has been deployed in 1601 workstations in 64 office buildings, generating a rich database for statistical evaluation of possible correlations between the physical attributes of workstations, environmental conditions, and user satisfaction. Multivariate regression and multiple correlation coefficient statistical analysis revealed the relationship between measured and perceived IEQ indices, interdependencies between IEQ indices, and other satisfaction variables of significance. The results showed that overall, 55% of occupants responded as “satisfied„ or “neutral„, and 45% reported being “dissatisfied„ in their thermal quality. Given the dataset, air temperature in work area, size of thermal zone, window quality, level of temperature control, and radiant temperature asymmetry with façade are the critical factors for thermal quality satisfaction in the field. As a result, the outcome of this research contributes to identifying correlations between occupant satisfaction, measured data, and technical attributes of building systems. The presented integrated IEQ assessment method can further afford robust predictions of building performance against metrics and guidelines for IEQ standards to capture revised IEQ thresholds that impact building occupants’ satisfaction.

Thermal comfort standards such as ASHRAE 55-2013 defines comfort boundaries which are based on the experimental results conducted in climatic chambers and field studies. The current comfort standards do not reflect the cultural and climatic diversity of India. A thermal comfort field study was conducted in 32 naturally ventilated buildings, collecting a total of 2610 samples spread over a total period of four years, covering all seasons, wide age groups, clothing types, and building types. In the present study, ASHRAE comfort boundaries at three different air speeds - still air (up to 0.2 m/s), natural air flow (0.2 m/s–0.5 m/s) and forced air flow with ceiling fan assist (0.5 m/s–1.5 m/s) are investigated. The method of calculation suggested by the ASHRAE 55-2013 and ISO-7730 were followed to determine extended acceptable temperature ranges for comfort at elevated air speed. Comfort boundaries are defined based on climate specific adaptations, the role of air speed and thermal preferences. Results from this study indicate that subjects in naturally ventilated buildings of this region are comfortable at temperatures different from those suggested by ASHRAE 55 and ISO-7730 standards. New extended boundaries of comfort zones are proposed considering various adaptations specific to this region, including the role of air speed to offset the temperature. The proposed comfort zones show that subjects are comfortable up to 32 °C at still air condition (0 m/s–0.2 m/s) and up to 35 °C at higher speed (up to 1.5 m/s) in naturally ventilated buildings in the composite climate of India. [ABSTRACT FROM AUTHOR]

Energy consumption in Indian building sector is increasing at high rate. The National Building Code of India specifies a narrow comfort temperature range between 21 °C and 26 °C for all types of buildings and for all seasons. A thermal comfort field study was conducted in 32 naturally ventilated buildings, collecting a total of 2610 samples spread over a total period of four years, covering multiple seasons, age groups, clothing types and building types. Questionnaires were administered to building occupants to record sensations and preferences for air temperature, relative humidity and air velocity on ASHRAE seven point and five point scales. The objective of the study was to evaluate thermal comfort of occupants and study the methods of thermal adaptation such as adjusting clothing, window opening, and use of air circulation fans. Griffith's method was used to determine thermal neutrality. The comfort temperature for summer and winter season was found to be 30.6 °C and 25.2 °C, respectively. Preferred clothing level for summer was found to be 0.30 clo, whereas in winter it was 0.80 clo. Preferred air velocity was observed as 0.62 m/s in summer season and 0.27 m/s in winter. Controlling air velocity has been found to be preferred method of thermal adaptation over adjusting clothing and window opening. [ABSTRACT FROM AUTHOR]

An interview with Vivian Loftness, professor at School of Architecture at Carnegie Mellon University in Pittsburgh, Pennsylvania, is presented. Topics include bottom line in building industry, government incentive to good quality buildings and triple bottom line calculations for buildings. Other topics include maintenance of substandard building and high quality buildings' benefit to the society are mentioned.

Abstract: Buildings consume a significant amount of energy to maintain the indoor thermal comfort. One way to reduce the energy consumption in buildings is to improve the overall energy efficiency through integrated advanced controls. It is undoubted that incorporating a model and utilizing future information in real-time building operation offers great energy saving potentials. However, there are many barriers preventing this from happening. Building systems are nonlinear and multiple-input-multiple-output (MIMO) in nature. Conventional approach with a global search solver and a detailed model simulator or direct nonlinear model predictive control (MPC) incurs prohibitive computational cost. This paper proposes a multi-structural fast nonlinear model predictive control (MPC) for handling nonlinear building systems and applied it on a hydronic heating system. The methodology remains the advantages of linear classical MPC and solves the nonlinearity issues involved in thermal comfort and energy conservation oriented control. The simulation shows that the controllers can achieve the optimal solutions in less than five minutes for five days simulation in a full look-ahead scenario with a Duo T6400 2.0 GHz computer. The fastest scenario takes only thirty more seconds to accomplish, which makes the approach feasible for online implementation. The techniques of using MPC for achieving smooth day-night switch, band control, dynamic constraints, and dynamic weighting are discussed. The energy saving potential of applying the proposed MPCs is found to be between six to forty two percent. In addition, the techniques decouple the building system from the mechanical system and are applicable to other space conditioning systems as well. [Copyright &y& Elsevier]

Abstract: This study investigates the possibility of the use of human body skin temperature to assess thermal sensation, by studying skin temperatures from ten body segments and analyzing the correlation between the physiological data: skin temperature and overall thermal sensation. Since the human body regulates skin temperature to balance the heat gain and heat loss, the use of skin temperature has significant potential as an index to the thermal sensation. Therefore, this research has relied on experiments using human subjects in an environmental chamber to investigate and determine how skin temperatures change, depending on the ambient thermal conditions, and to identify which data type and body segment generate the most significant physiological information that will represent the overall thermal sensation. For this study, the experiments were conducted with 26 volunteers in an experimental chamber for about 2h each, while the indoor temperature was changed from 20°C to 30°C. Results of this study revealed that skin temperature change rates (gradients) were more consistent with the thermal comfort condition than with the actual levels of skin temperatures of participants, and that the measured skin temperatures at their wrists provided more interpretable data than that of any other body segments. Therefore, the research findings have shown the potential of skin temperature as a thermal sensation index to reliably represent an individual’s thermal sensation in a thermally uniformed environment. [Copyright &y& Elsevier]

Abstract: According to the current thermal comfort theory, metabolic rate and clothing insulation are critical human factors that affect thermal sensation. Since heart rate is significantly correlated with human metabolic rate, it may undoubtedly be a potential parameter that directly (or indirectly) impacts the principle of thermal comfort. In addition, even though a few researchers have identified an insignificant relationship between heart rate and thermal conditions, many have reported heart rate variability at different thermal sensation levels based on the principle of thermoregulation. However, in spite of its potential as a thermal sensation effector, as well as an indicator, current thermal comfort models have focused mainly on several local body skin temperatures and the core body temperature without considering heart rate. Therefore, this research has relied on experiments with human subjects in two environmental chambers (each with a different thermal condition) to investigate and determine whether and how the heart rate during the same activity level is affected by warm and cold conditions. It also sought to determine how heart rate is related to thermal sensation, and whether the effect would vary depending on gender and body mass index. Results of this study revealed that the heart rate and the changes in rates that occurred between different activity levels showed a significant increase during warm conditions, with a 2.5 metabolic rate, especially in males and in body mass index groups higher than 22. A decent increase in the change rates was also found at 1.0 Met, as compared with 0.8 Met. [Copyright &y& Elsevier]

Abstract: This paper investigates the effects of occupant gender and age on thermal satisfaction in office environments. The data used for the analyses was collected from 40-sampled occupants and their workstations on 38 floors in 20 office buildings in the U.S. with support from the U.S. General Services Administration. The field measurements include data collection for air temperature, radiant temperature, temperature stratification, relative humidity and air velocity of the sampled workstations. Occupant satisfaction surveys were distributed to each occupant in the workstations measured, and the thermal attributes of building systems were recorded. The objective and subjective data sets support statistical correlation analysis between environmental qualities and user satisfactions. The statistical analysis of air temperatures, occupant thermal satisfaction, age and gender revealed that females are more dissatisfied with their thermal environments than males especially in the summer season with high significance, and occupants over 40 years old are more satisfied than under 40 in the cooling season with marginal significance. [Copyright &y& Elsevier]

Experiencing nature provides a multitude of health benefits. Biophilic design has emerged as a design approach that aims to reconnect occupants with the natural environment. We evaluated the impact of a multisensory biophilic environment on occupants' cognitive performance, stress, productivity, mood, connectedness to nature, and attention. Thirty-seven participants in three cohorts were exposed to three biophilic design interventions (visual, auditory, and a combination (multisensory)) and a baseline condition, with weekly variations over eight weeks. A wrist-worn stress sensor, daily surveys, and scheduled executive function tasks were administered. Cognitive performance improved in all biophilic conditions compared to baseline. Most satisfaction with workplace appearance, and visual privacy was reported in visual and multisensory conditions, and stress ratings were lower in the multisensory condition compared to baseline. The results demonstrate that immersive biophilic environments can improve occupants' satisfaction and cognitive performance, while reducing stress. The findings highlight the need to consider non-visual factors in biophilic design. • Biophilic design aims to reconnect occupants with the natural environment • Living Labs can be used to assess sustained exposure to biophilic elements indoors • Immersive biophilic environments can improve cognitive performance and reduce stress • Immersive biophilic environments can increase occupants' perceived productivity • Introducing multisensory biophilic features is recommended in an office setting [ABSTRACT FROM AUTHOR]

For visual quality, the traditional focus on illuminance for paper-based tasks and brightness contrast for visual acuity is becoming less relevant in modern offices with backlit computer screens and sporadic use of paper. This research aims to investigate critical correlations between user satisfaction, workstation lighting conditions, and the physical attributes of the work area. The statistical analyses were conducted to identify applicable recommendations leading to improved visual quality in today's work environment while maintaining optimal user satisfaction. Findings from post-occupancy evaluation on 1,232 workstations in 64 office buildings revealed that satisfaction level would increase by 20% on average when the occupants have a view to the outside in their seated workstations. Upgrading the ceiling light fixture with an indirect lens type increases visual satisfaction. Workstations with an indirect lens type had higher satisfaction (62%), while a prismatic ceiling lens type showed the lowest user satisfaction (34%). The analysis further identified that a combination of indirect light fixtures with task lights increases user satisfaction by 21%. Lastly, utilizing window shading devices revealed greater satisfaction with glare management. The occupants with external and internal shading devices in their work areas showed the highest satisfaction with their overall lighting. In addition to the recommendations mentioned above, an illuminance level of 406 lux for the work surface achieves maximum satisfaction in contemporary office environments. • Presents an occupant-centric assessment method for capturing indoor visual quality. • Identifies critical correlations between user satisfaction and lighting conditions. • Applicable design strategies for optimal visual quality with maximum satisfaction. • Reveals the critical thresholds for illuminance levels in the office environments. [ABSTRACT FROM AUTHOR]

Windows provide access to daylight and view, both of which have been linked to positive outcomes for occupants, including improved satisfaction, well-being, and performance. However, window access can also cause discomfort and eyestrain from glare. This controlled crossover study tested the occupant impacts of two modern shading systems designed to provide daylight and view while minimizing glare: windows with manually-controlled motorized mesh shades (Mesh Shades) and windows with automatic tinting (Dynamic Tint). Ten participants spent fourteen weeks working in a living lab in which three conditions were non-consecutively repeated for two-week periods: Mesh Shades, Dynamic Tint, and a baseline condition lacking daylight and view (Blackout Shades). Participants' cognitive function performance, satisfaction, and eyestrain in the baseline Blackout Shades condition were compared to the same measures in the Mesh Shades and Dynamic Tint conditions. Two aspects of cognitive function performance—Working Memory and Inhibition—improved in both the Mesh Shades and Dynamic Tint conditions. Satisfaction with light as well as with the overall environment improved in both the Mesh Shades and Dynamic Tint conditions. Eyestrain symptoms were reduced in both the Mesh Shades and Dynamic Tint conditions. There were no statistical differences between settings with Dynamic Tint and motorized Mesh Shades on measures of cognitive function performance, satisfaction, or eyestrain symptoms. This research demonstrates that providing access to daylight and view in an office environment using modern shading methods can improve occupants' cognitive performance and satisfaction while reducing eyestrain. • Modern shading methods can provide daylight and view while limiting glare. • Controlled crossover study tested occupant impacts of two shading methods in office. • Participants worked in living lab for 14 weeks while three conditions were repeated. • Outcomes in two shading conditions compared to baseline lacking daylight or view. • Cognitive performance, satisfaction, and eyestrain improved in shading conditions. [ABSTRACT FROM AUTHOR]

Indoor Air Quality (IAQ) of the workplace is highly linked with occupants' health, comfort and satisfaction. To maintain the good IAQ of buildings, Post-Occupancy Evaluation (POE) is often combined with environmental measurements to holistically examine existing performance conditions in relation to occupants' satisfaction. The Center for Building Performance and Diagnostics (CPBD) at Carnegie Mellon University conducted post occupancy evaluations for over 1600 workstations in 64 buildings using the National Environment Assessment Toolkit (NEAT)—a suite of three tools for workstation IEQ measurements, Technical Attributes of Building Systems (TABS) and occupant satisfaction surveys. The rich dataset generated by NEAT was employed in this study to perform multivariate regression and multiple correlation coefficient analyses on IAQ. We examine the relationship between measured and perceived IAQ indices, as well as interdependencies between IAQ indices and occupant satisfaction variables of significance. Among measured IAQ indices, CO 2 and particulates are identified as critical factors for user satisfaction. In particular, the analyses revealed that the CO 2 threshold of 582 ppm is the highest occupant satisfaction in office buildings. To ensure good air quality in office buildings, our findings recommend "Operable window", "Dedicated exhaust", "Individual return air diffuser density" and "Low/medium partition height" as applicable design guidelines. Through this study, we demonstrate the effectiveness of integrating POE with environmental measurements to systematically develop a rich database leading to critical thresholds and design guidelines for highest occupant satisfaction. • Provides practical IAQ assessment methods and procedures centered on the occupants' perspective. • Reveals air quality features in the office environment, and defines correlations between occupant perception on air quality and measured data. • Prioritizes critical features on IAQ evaluation in the field to enhance occupant satisfaction. • Proposes metrics and guidelines for IAQ standards that capture new thresholds that impact building occupants' satisfaction on air quality. • Provides design guidelines and maintenance and operation protocols for designers, building owners and facility managers. [ABSTRACT FROM AUTHOR]

Cob is an earthen building material that offers a minimally processed, low carbon, and locally available alternative to conventional building materials and methods. This paper provides a framework for a comparative Life Cycle Assessment (LCA) from an embodied perspective of energy and air emissions, using cob earthen wall construction as well as benchmark wall assemblies of concrete masonry and wood frame. The results of the study show that cob production requires only 18–38% energy and reduces 75–82% of global climate change impacts when compared to conventional materials. Significantly, the embodied environmental impacts of cob were shown to be lower than conventional materials in all aspects. Further, sensitivity analysis shows that impacts can be further reduced by maximizing the use of local materials. Image 1 • Cob production required 75% less energy than conventional wall systems • Cob reduces up to 80% of global climate change impacts as opposed to compared systems • The environmental impacts of cob depend mostly on wall thickness • The local availability of materials highly affect the environmental benefits of cob [ABSTRACT FROM AUTHOR]