About

Gail Brager, PhD, has been a professor in the Building Science & Sustainability area of the department since 1984 and is also an affiliate faculty member of the Energy and Resources Group. She serves as the director of the Center for Environmental Design Research and as associate director of the Center for the Built Environment, a research collaboration between the university and over 40 industry partners focused on improving the energy performance and environmental quality in buildings, especially in the workplace. Her research and teaching span multiple dimensions of sustainability, with a focus on the design, operation, and assessment of buildings, emphasizing thermal comfort and adaptation, occupant well-being, natural ventilation, and personalized environmental control. Professor Brager specializes in design for high-performance buildings, post-occupancy evaluation, thermal comfort in naturally ventilated and mixed-mode buildings, assessment of energy and indoor environmental quality, and sustainable design in hot climates. She has contributed significantly to the field through her leadership roles, including serving as the founding chair of the Research Committee of the US Green Building Council, and has been recognized with numerous awards such as the Presidential Young Investigator Award from the National Science Foundation and multiple honors from ASHRAE. Her philosophy emphasizes the importance of environmental forces like sun, wind, and light in shaping a building's experiential aesthetic, guiding students to create buildings that are both beautiful and efficient, climate-responsive, environmentally sensitive, and a delight to inhabit.

Research topics

• Computer Science
• Engineering
• Psychology
• Meteorology
• Sociology
• Geography
• Architectural engineering
• Political Science
• Civil engineering
• Applied psychology
• Business
• Process management
• Environmental science
• Knowledge management
• Cognitive psychology

Selected publications

• Temporal resolution matters: Evaluating carbon emission factors for accurate accounting in commercial buildings

  Applied Energy · 2026-03-11 · 1 citations

  articleOpen access

  Accurately quantifying operational carbon emissions from buildings is essential to verify that decarbonization targets are met. Yet many current practices rely on overly simplified yearly average emission factors that overlook the temporal variability of the electrical grid generation. This issue becomes increasingly critical with the rising penetration of renewable energy and the adoption of demand-side strategies in buildings, such as load shifting. Existing literature on net-zero carbon buildings rarely examines how the temporal resolution of emission factors affects accounting accuracy. In this study, we evaluated a range of grid emission factors (annual, seasonal, time-of-day, season-hour, and month-hour) and quantified their impact on carbon emissions accounting accuracy for commercial buildings across 18 U.S. grid regions. These emission factors, derived from publicly available datasets, are applied to measured hourly electricity consumption profiles from over 600 real commercial buildings. By considering hourly emission factors as the benchmark reference, we then quantified the resulting errors and uncertainties due to the reduced temporal resolution of the emission factors. Additionally, we assessed how buildings' on-site solar PV generation affects avoided emissions accounting from grid exports when electricity generation exceeds demand. As a result, we found that annual and seasonal averages are unreliable and should not be used for net-zero target assessments. Instead, we recommend incentivizing the adoption of season-hour and month-hour emission factors, which consistently deliver sufficient accuracy across diverse U.S. grid regions, with median errors typically less than 10%. This is also the case when quantifying the avoided emissions when utility export is available, yet the results are more variable and dependent on the grid generation mix. In particular, when coarse emission factors such as annual or seasonal averages are used, increasing onsite solar capacity can raise the median normalized fractional error to approximately 15% for operational emissions and to more than 100% for avoided emissions. These findings highlight the need for future standards and guidelines to consider at least the use of season-hour or month-hour emission factors' resolution to achieve acceptable emissions accounting accuracy. • Annual average emission factors should not be used for assessing building operational or avoided carbon emissions. • Season-hour and month-hour average emission factors deliver sufficient accuracy with median errors typically below 10%. • The importance of temporal resolution increases significantly in grid regions with higher solar generation. • Coarse-resolution emission factors risk underestimating the true impact of efficiency and flexibility retrofits.

  PublisherDOI

• Whole-life carbon reduction in early building design: Comparing industry perspective in China and the United States

  Building and Environment · 2026-04-08

  articleOpen access
  PublisherDOI

• Demonstrating the reliability of randomized measurement and verification for switchable control retrofits using a large open-source dataset

  Applied Energy · 2026-04-01

  articleOpen accessSenior author

  Conventional measurement and verification (M&V) methods for estimating energy savings rely on comparing pre- and post-retrofit performance. They are often time-consuming and unreliable, especially when non-routine events, such as step changes or more gradual changes in building operation, occur during the M&V process. When those events are unrelated to the retrofit intervention and significantly affect building energy consumption, the results will be confounded when the analyst applies the conventional M&V method. In this study, we demonstrated that switchable interventions, such as most HVAC control retrofits, can benefit from a new M&V method that randomly samples whether to implement the baseline or the intervention strategy at a fixed interval (e.g., daily). We tested this novel randomized M&V method on a large public dataset (hourly energy data over 2 years for 639 buildings) covering various climate zones and commercial building types, using a virtual chilled water supply temperature reset based on outdoor weather as the intervention. The results show that, compared to the conventional method, the randomized method provides more accurate savings estimations with a median of 74% accuracy improvement and is faster (typically 36 weeks instead of 104 weeks, ∼65% reduction in duration). Additionally, we found that when non-routine events are present (e.g., occupancy pattern change), the randomized method estimates savings that are much closer to the ground-truth values than the conventional method, demonstrating significantly improved reliability. We also assessed the impact of normalizing for different weather, starting the M&V at different dates of the year, continuing randomization with a different sampling ratio after satisfying all stopping criteria, and dropping samples affected by carryover effects when switching between strategies. For each scenario, we identified the optimal sampling interval using the large dataset. • Randomized switchback method improved measurement and verification accuracy. • Randomized switchback reduced uncertainty and shortened evaluation time. • Operational drift and non-routine events can strongly affect conventional savings estimates. • Longer sampling intervals reduced carryover effect but increased sampling error. • Favoring intervention in sampling increased error and uncertainty.

  PublisherDOI

• Envelope-Driven Comfort Risk in Residential Demand Response

  SSRN Electronic Journal · 2026-01-01

  preprintOpen access
  PublisherDOI

• Demonstrating the Reliability of Randomized Measurement and Verification for Switchable Control Retrofits Using a Large Open-Source Dataset

  SSRN Electronic Journal · 2025-01-01

  preprintOpen accessSenior author
  PublisherDOI

• Usability of Lighting and Shading Controls: Influence of Interface Position and Information on User Preferences and Acceptance

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access
  PublisherDOI

• Causal effects estimation: Using natural experiments in observational field studies in building science

  Indoor Environments · 2025-02-24 · 6 citations

  articleOpen access

  Correlational analysis, such as linear regression, does not imply causation. This paper introduces and applies a causal inference framework and a specific method, regression discontinuity, to thermal comfort field studies. The method utilizes policy thresholds in China, where the winter district heating policy is based on cities' geographical locations relative to the Huai River. The approximate latitude of the Huai River can be considered as a natural, geographical threshold, where cities near the threshold are quite similar, except for the availability of district heating in cities north of the threshold, creating a situation similar to a randomized experiment. Using the regression discontinuity method, we quantify the causal effects of the experiment treatment (district heating) on the physical indoor environments and subjective responses of building occupants. We found that mean indoor operative temperatures were 4.3 °C higher, and mean thermal sensation votes were 0.6 warmer due to the district heating. In contrast, using conventional correlational analysis, we demonstrate that the correlation between indoor operative temperature and thermal sensation votes does not accurately reflect the causal relationship between the two. We also show that the indoor operative temperature could be either positively or negatively correlated with occupants’ thermal satisfaction. However, we cannot conclude that increasing the indoor operative temperature in these circumstances will necessarily lead to higher or lower thermal satisfaction. This highlights the importance of causal inference methods in thermal comfort field studies and other observational studies in building science, where the regression discontinuity method might apply. • Correlations in observational studies do not accurately reflect causal relationships. • Natural experiments at the Huai River in China enable causal effect estimation. • District heating causes a 4.3 °C higher indoor operative temperature. • District heating causes a 0.6 warmer thermal sensation vote. • Correlations could be spurious and even misleading.

  PublisherDOI

• Commercial Building HVAC Functional Performance Test Automation Using Brick Metadata Schema

  Lecture notes in civil engineering · 2025-11-22

  book-chapterSenior author
  PublisherDOI

• Ten questions concerning the application of adaptive thermal comfort in mixed-mode buildings

  Building and Environment · 2025-07-28 · 7 citations

  articleOpen access

  • Applying adaptive thermal comfort (ATC) in mixed-mode (MM) buildings was discussed. • Successful MM design requires balancing automated controls with manual controls. • MM strategies are viable in both new constructions and existing buildings. • International thermal comfort standards should allow ATC use for MM buildings. • Integrating ATC with MM offers a compelling way to achieve sustainable buildings. The recently completed IEA Annex 69 ( Strategy and Practice of Adaptive Thermal Comfort in Low Energy Buildings ) identified mixed-mode (MM) building design and operation as key strategies for the buildings sector in its transition towards a low-carbon mode. Mixed-mode is short-hand for naturally ventilated designs with supplemental air-conditioning that can be called upon whenever and wherever external climatic loads and/or internal loads dictate. Success of the MM strategy requires shifting the sector’s concept of thermal comfort away from a static comfort zone towards an adaptive approach in which the indoor comfort zone drifts in the same direction as external weather and seasonal trends. The potential for mixed-mode design arises from its applicability in both new construction and existing building stock. The objective of this paper is to elevate awareness of the mixed-mode design concept within the building sector and related research communities. Furthermore, it aspires to influence international thermal comfort standards and guidelines, advocating for a more explicit endorsement of adaptive thermal comfort in mixed-mode applications. Towards this end, we address ten critical questions concerning the application of adaptive thermal comfort in mixed-mode buildings. The questions elucidate the fundamental aspects of MM buildings, the role of adaptive thermal comfort, and the broader implications for building design and operation.

  PublisherDOI

• Assessing Overheating Risk and Energy Impacts in California's Residential Buildings

  2025-05-30 · 1 citations

  articleSenior author
  PublisherDOI

Frequent coauthors

• Richard de Dear

  University of Sydney

  22 shared

• Edward Arens

  University of California, Berkeley

  19 shared

• Stefano Schiavon

  University of California, Berkeley

  16 shared

• Katie Ackerly

  University of California, Berkeley

  9 shared

• Sahar Abbaszadeh Fard

  University of California, Berkeley

  8 shared

• Leah Zagreus

  Berkeley College

  8 shared

• Charlie Huizenga

  University of California, Berkeley

  8 shared

• Paul Raftery

  8 shared

Education

• M.S. and Ph.D., Mechanical Enginerring

  University of California, Berkeley

  1984

Awards & honors

• Presidential Young Investigator Award from National Science…
• Progressive Architecture Research Award
• AIA Education Honors Honorable Mention
• Places/EDRA award for Place-based research
• ASHRAE Fellow