Wikipedia

Building science

(Redirected from Indoor environment)

Building Science is the science and technology-driven collection of knowledge to provide better indoor environmental quality (IEQ), energy-efficient built environments, and occupant comfort and satisfaction. Building physics, architectural science, and applied physics are terms used for the knowledge domain that overlaps with building science. In building science, the methods used in natural and hard sciences are widely applied, which may include controlled and quasi-experiments, randomized control, physical measurements, remote sensing, and simulations. On the other hand, methods from social and soft sciences, such as case study, interviews & focus group, observational method, surveys, and experience sampling, are also widely used in building science to understand occupant satisfaction, comfort, and experiences by acquiring qualitative data. One of the recent trends in building science is a combination of the two different methods. For instance, it is widely known that occupants' thermal sensation and comfort may vary depending on their sex, age, emotion, experiences, etc. even in the same indoor environment. Despite the advancement in data extraction and collection technology in building science, objective measurements alone can hardly represent occupants' state of mind such as comfort and preference. Therefore, researchers are trying to measure both physical contexts and understand human responses to figure out complex interrelationships.

Small furnace capable of 600°C and of applying a static load for testing building materials

Building science traditionally includes the study of indoor thermal environment, indoor acoustic environment, indoor light environment, indoor air quality, and building resource use, including energy and building material use.[1] These areas are studied in terms of physical principles, relationship to building occupant health, comfort, and productivity, and how they can be controlled by the building envelope and electrical and mechanical systems.[2] The National Institute of Building Sciences (NIBS) additionally includes the areas of building information modeling, building commissioning, fire protection engineering, seismic design and resilient design within its scope.[3]

One of the applications of building science is to provide predictive capability to optimize the building performance and sustainability of new and existing buildings, understand or prevent building failures, and guide the design of new techniques and technologies.

Applications

edit

During the architectural design process, building science knowledge is used to inform design decisions to optimize building performance. Design decisions can be made based on knowledge of building science principles and established guidelines, such as the NIBS Whole Building Design Guide (WBDG) and the collection of ASHRAE Standards related to building science.

Computational tools can be used during design to simulate building performance based on input information about the designed building envelope, lighting system, and mechanical system. Models can be used to predict operational energy use, solar heat and radiation distribution, air flow, and other physical phenomena within the building.[4] These tools are valuable for evaluating a design and ensuring it will perform within an acceptable range before construction begins. Many of the available computational tools analyze building performance goals and perform design optimization.[5] The accuracy of the models is influenced by the modeler's knowledge of building science principles and by the amount of validation performed for the specific program.[4]

When existing buildings are being evaluated, measurements and computational tools can be used to evaluate performance based on measured existing conditions. An array of in-field testing equipment can be used to measure temperature, moisture, sound levels, air pollutants, or other criteria. Standardized procedures for taking these measurements are provided in the Performance Measurement Protocols for Commercial Buildings.[6] For example, thermal infrared (IR) imaging devices can be used to measure temperatures of building components while the building is in use. These measurements can be used to evaluate how the mechanical system is operating and if there are areas of anomalous heat gain or heat loss through the building envelope.[7]

Measurements of conditions in existing buildings are used as part of post occupancy evaluations. Post occupancy evaluations may also include surveys[8] of building occupants to gather data on occupant satisfaction and well-being and to gather qualitative data on building performance that may not have been captured by measurement devices.

Many aspects of building science are the responsibility of the architect (in Canada, many architectural firms employ an architectural technologist for this purpose), often in collaboration with the engineering disciplines that have evolved to handle 'non-building envelope' building science concerns: Civil engineering, Structural engineering, Earthquake engineering, Geotechnical engineering, Mechanical engineering, Electrical engineering, Acoustic engineering, & fire code engineering. Even the interior designer will inevitably generate a few building science issues.

Topics

edit

Daylighting and visual comfort

edit

Daylighting is the controlled admission of natural light, direct sunlight, and diffused skylight into a building to reduce electric lighting and save energy. A daylighting system consists of daylight apertures, such as skylights and windows, but is also coupled with a daylight-responsive lighting control system. [9] Daylight positively impacts the psychological and physiological health of a human being by stimulating the human circadian rhythm, which can lower depression, improve sleep quality, reduce lethargy, and prevent illness. [10]

However, studies do not always lead to a positive correlation between maximizing daylighting availability and human comfort and health. [11] When larger areas of fenestration exist within the buildings with so much of the sky exposed, it is important to control the quantity and the quality of the visual environment. [12] A lack of attention to visual comfort issues often makes the best daylighting intentions ineffective due to excessive brightness and high contrast luminance ratios within the space which result in glare. Illuminating Engineering Society (IES)’s Lighting Handbook defines glare as the sensation produced by luminance levels in the visual field, sufficiently greater than those that our eyes can adapt to, that causes discomfort or loss in visual performance or visibility. [13] Glare interferes with visual perception caused by an uncomfortably bright light source or reflection, a form of visual noise. If the occupants experience visual discomfort from excessive sunlight penetration through the glazed facades of the buildings, they may wish to close the shading devices that would decrease the daylight availability and increase the electric lighting energy consumption. [14]

Thus, for successful harvesting of daylight and energy savings, it is crucial to fully understand occupants’ visual comfort parameters and use the most suitable daylight and glare metrics to evaluate lighting conditions in daylit spaces.

Indoor environmental quality (IEQ)

edit

Indoor environmental quality (IEQ) refers to the quality of a building's environment in relation to the health and wellbeing of those who occupy space within it. IEQ is determined by many factors, including lighting, air quality, and temperature.[15] Workers are often concerned that they have symptoms or health conditions from exposures to contaminants in the buildings where they work. One reason for this concern is that their symptoms often get better when they are not in the building. While research has shown that some respiratory symptoms and illnesses can be associated with damp buildings,[16] it is still unclear what measurements of indoor contaminants show that workers are at risk for disease. In most instances where a worker and his or her physician suspect that the building environment is causing a specific health condition, the information available from medical tests and tests of the environment is not sufficient to establish which contaminants are responsible. Despite uncertainty about what to measure and how to interpret what is measured, research shows that building-related symptoms are associated with building characteristics, including dampness, cleanliness, and ventilation characteristics.

Indoor environments are highly complex and building occupants may be exposed to a variety of contaminants (in the form of gases and particles) from office machines, cleaning products, construction activities, carpets and furnishings, perfumes, cigarette smoke, water-damaged building materials, microbial growth (fungal, mold, and bacterial), insects, and outdoor pollutants. Other factors such as indoor temperatures, relative humidity, and ventilation levels can also affect how individuals respond to the indoor environment. Understanding the sources of indoor environmental contaminants and controlling them can often help prevent or resolve building-related worker symptoms. Practical guidance for improving and maintaining the indoor environment is available.[17]

Building indoor environment covers the environmental aspects in the design, analysis, and operation of energy-efficient, healthy, and comfortable buildings. Fields of specialization include architecture, HVAC design, thermal comfort, indoor air quality (IAQ), lighting, acoustics, and control systems.

HVAC systems

edit

The mechanical systems, usually a sub-set of the broader Building Services, used to control the temperature, humidity, pressure and other select aspects of the indoor environment are often described as the Heating, Ventilating, and Air-Conditioning (HVAC) systems. These systems have grown in complexity and importance (often consuming around 20% of the total budget in commercial buildings) as occupants demand tighter control of conditions, buildings become larger, and enclosures and passive measures became less important as a means of providing comfort.

Building science includes the analysis of HVAC systems for both physical impacts (heat distribution, air velocities, relative humidities, etc.) and for effect on the comfort of the building's occupants. Because occupants' perceived comfort is dependent on factors such as current weather and the type of climate the building is located in, the needs for HVAC systems to provide comfortable conditions will vary across projects.[18] In addition, various HVAC control strategies have been implemented and studied to better contribute to occupants' comfort. In the U.S., ASHRAE has published standards to help building managers and engineers design and operate the system.[19] In the UK, a similar guideline was published by CIBSE.[20] Apart from industry practice, advanced control strategies are widely discussed in research as well. For example, closed-loop feedback control can compare air temperature set-point with sensor measurements;[21] demand response control can help prevent electric power-grid from having peak load by reducing or shifting their usage based on time-varying rate.[22] With the improvement from computational performance and machine learning algorithms, model prediction on cooling and heating load with optimal control can further improve occupants comfort by pre-operating the HVAC system.[23] It is recognized that advanced control strategies implementation is under the scope of developing Building Automation System (BMS) with integrated smart communication technologies, such as Internet of Things (IoT). However, one of the major obstacles identified by practitioners is the scalability of control logics and building data mapping due to the unique nature of building designs. It was estimated that due to inadequate interoperability, building industry loses $15.8 billion annually in the U.S.[24] Recent research projects like Haystack[25] and Brick[26] intend to address the problem by utilizing metadata schema, which could provide more accurate and convenient ways of capturing data points and connection hierarchies in building mechanical systems. With the support of semantic models, automated configuration can further benefit HVAC control commissioning and software upgrades.[27]

Enclosure (envelope) systems

edit

The building enclosure is the part of the building that separates the indoors from the outdoors. This includes the wall, roof, windows, slabs on grade, and joints between all of these. The comfort, productivity, and even health of building occupants in areas near the building enclosure (i.e., perimeter zones) are affected by outdoor influences such as noise, temperature, and solar radiation, and by their ability to control these influences. As part of its function, the enclosure must control (not necessarily block or stop) the flow of moisture, heat, air, vapor, solar radiation, insects, or noise, while resisting the loads imposed on the structure (wind, seismic). Daylight transmittance through glazed components of the facade can be analyzed to evaluate the reduced need for electric lighting.[28]

Building sustainability

edit

Part of building science involves designing buildings with consideration for the future resources and environmental realities. This field, often referred to as sustainable design, integrates strategies to lower building environmental impacts, including lowering both operational carbon, which is the emissions from energy use during a building's life, and embodied carbon, which accounts for the emissions from material production and construction.[29]

Buildings are responsible for approximately 40% of global energy consumption[30] and 13% carbon emissions[31], primarily related to building HVAC systems operation. Reducing operational carbon is critical to mitigate climate change. To address these emissions, renewable energy sources, such as solar and wind energy, are adopted by the building industry to support electricity generation. However, the electricity demand profile shows imbalance between supply and demand, which is known as the 'duck curve'. This could impact on maintaining grid system stability.[32] Therefore, other strategies such as thermal energy storage systems are developed to achieve higher levels of sustainability by reducing grid peak power.[23]

A push towards zero-energy building also known as Net-Zero Energy Building has been present in the Building Science field. The qualifications for Net Zero Energy Building Certification can be found on the Living Building Challenge website.

Embodied Carbon and Decarbonization

edit

Embodied carbon refers to the total carbon emissions associated with the entire life cycle of a building material (i.e. material extraction, manufacturing and production, transportation, construction, and end of life).[29] As building performance research has decreased operational carbon, there has been an increase in embodied carbon within the building sector, partly due to the higher material demands of energy-efficient designs.[33] This shift has underscored the need to address embodied carbon alongside operational emissions to achieve holistic decarbonization.

A significant portion of decarbonization focuses on building structural materials. For example, steel and concrete have significant embodied carbon content.[34] Strategies to reduce embodied carbon have included material substitution, recycling and reuse, and low-carbon manufacturing. Building decarbonization can occur within all facets of the building design process, however, the most significant reduction impacts are through early-stage design.[35]

Challenges in addressing embodied carbon include insufficient data, standardization issues, cost considerations, and regulatory barriers. Reliable databases are limited in availability and are region-specific. Existing standards are often voluntary and vary in scope, making comparisons and benchmarking difficult.[33]

Addressing embodied carbon is a growing aspect of building science, becoming critical for advancing building sustainability efforts and reducing the environmental impact of the built environment.

Post-Occupancy Evaluation (POE)

edit

POE is a survey-based method to measure the building performance after the built environment was occupied. The occupant responses were collected through structured or open inquiries. Statistical methods and data visualization were often used to suggest which aspects(features) of the building were supportive or problematic to the occupants. The results may become design knowledge for architects to design new buildings or provide a data-basis to improve the current environment.

Certification

edit

Although there are no direct or integrated professional architecture or engineering certifications for building science, there are independent professional credentials associated with the disciplines. Building science is typically a specialization within the broad areas of architecture or engineering practice. However, there are professional organizations offering individual professional credentials in specialized areas. Some of the most prominent green building rating systems are:

There are other building sustainability accreditation and certification institutions as well. Also in the US, contractors certified by the Building Performance Institute, an independent organization, advertise that they operate businesses as Building Scientists. This is questionable due to their lack of scientific background and credentials. On the other hand, more formal building science experience is true in Canada for most of the Certified Energy Advisors. Many of these trades and technologists require and receive some training in very specific areas of building science (e.g., air tightness, or thermal insulation).

List of principal building science journals

edit
  • Building and Environment: This international journal publishes original research papers and review articles related to building science, urban physics, and human interaction with the indoor and outdoor built environment. The journal's most cited articles cover topics such as occupant behavior in buildings,[39] green building certification systems,[40] and tunnel ventilation systems.[41] Publisher: Elsevier. Impact Factor (2019): 4.971[42]
  • Energy and Buildings: This international journal publishes articles with explicit links to energy use in buildings. The aim is to present new research results, and new proven practice aimed at reducing the energy needs of a building and improving indoor air quality. The journal's most cited articles cover topics such as prediction models for building energy consumption,[43] optimization models of HVAC systems,[44] and life cycle assessment.[45] Publisher: Elsevier. Impact Factor (2019): 4.867[46]
  • Indoor Air: This international journal publishes papers reflecting the broad categories of interest in the field of indoor environment of non-industrial buildings, including health effects, thermal comfort, monitoring and modelling, source characterization, and ventilation (architecture) and other environmental control techniques. The journal's most cited articles cover topics such as the impact of indoor air pollutants and thermal conditions on occupant performance,[47] the movement of droplets in indoor environments,[48] and the effects of ventilation rates on occupant health.[49] Publisher: John Wiley & Sons. Impact Factor (2019): 4.739[50]
  • Architectural Science Review: Founded at the University of Sydney, Australia in 1958, this journal aims to promote the development, accumulation, and application of scientific knowledge on a wide range of environmental topics. According to the journal description, the topics may include but not limited to building science and technology, environmental sustainability, structures and materials, audio and acoustics, illumination, thermal systems, building physics, building services, building climatology, building economics, ergonomics, history and theory of architectural science, the social sciences of architecture. Publisher: Taylor & Francis Group
  • Building Research and Information: This journal focuses on buildings, building stocks and their supporting systems. Unique to BRI is a holistic and transdisciplinary approach to buildings, which acknowledges the complexity of the built environment and other systems over their life. Published articles utilize conceptual and evidence-based approaches which reflect the complexity and linkages between culture, environment, economy, society, organizations, quality of life, health, well-being, design and engineering of the built environment. The journal's most cited articles cover topics such as the gap between performance and actual energy consumption,[51] barriers and drivers for sustainable building,[52] and the politics of resilient cities.[53] Publisher: Taylor & Francis Group. Impact Factor (2019): 3.887[54]
  • Journal of Building Performance Simulation: This international, peer-reviewed journal publishes high quality research and state of the art “integrated” papers to promote scientifically thorough advancement of all the areas of non-structural performance of a building and particularly in heat transfer, air, moisture transfer. The journal's most cited articles cover topics such as co-simulation of building energy and control systems,[55] the Buildings library,[56] and the impact of occupant's behavior on building energy demand.[57] Publisher: Taylor & Francis Group. Impact Factor (2019): 3.458[58]
  • LEUKOS: This journal publishes engineering developments, scientific discoveries, and experimental results related to light applications. Topics of interest include optical radiation, light generation, light control, light measurement, lighting design, daylighting, energy management, energy economics, and sustainability. The journal's most cited articles cover topics such as lighting design metrics,[59] psychological processes influencing lighting quality,[60] and the effects of lighting quality and energy-efficiency on task performance, mood, health, satisfaction, and comfort.[61] Publisher: Taylor & Francis Group. Impact Factor (2019): 2.667[62]
  • Building Simulation: This international journal publishes original, high quality, peer-reviewed research papers and review articles dealing with modeling and simulation of buildings including their systems. The goal is to promote the field of building science and technology to such a level that modeling will eventually be used in every aspect of building construction as a routine instead of an exception. Of particular interest are papers that reflect recent developments and applications of modeling tools and their impact on advances of building science and technology. Publisher: Springer Nature. Impact Factor (2019): 2.472[63]
  • Applied Acoustics: This journal covers research findings related to practical applications of acoustics in engineering and science. The journal's most cited articles related to building science cover topics such as the prediction of the sound absorption of natural materials,[64] the implementation of low-cost urban acoustic monitoring devices,[65] and sound absorption of natural kenaf fibers.[66] Publisher: Elsevier. Impact Factor (2019): 2.440[67]
  • Lighting Research & Technology: This journal covers all aspects of light and lighting, including the human response to light, light generation, light control, light measurement, lighting design equipment, daylighting, energy efficiency of lighting design, and sustainability. The journal's most cited articles cover topics such as light as a circadian stimulus for architectural lighting,[68] human perceptions of color rendition,[69] and the influence of color gamut size and shape on color preference.[70] Publisher: SAGE Publishing. Impact Factor (2019): 2.226[71]

See also

edit

References

edit
  1. ^ V., Szokolay, S. (2014-04-11). Introduction to architectural science: the basis of sustainable design (Third ed.). Abingdon, Oxon. ISBN 9781317918592. OCLC 876592619.{{cite book}}: CS1 maint: location missing publisher (link) CS1 maint: multiple names: authors list (link)
  2. ^ Norbert, Lechner (2014-09-23). Heating, cooling, lighting: sustainable design methods for architects (Fourth ed.). Hoboken, New Jersey. ISBN 9781118849453. OCLC 867852750.{{cite book}}: CS1 maint: location missing publisher (link)
  3. ^ "About NIBS | National Institute of Building Sciences". www.nibs.org. Retrieved 2021-08-24.
  4. ^ a b Building performance simulation for design and operation. Hensen, Jan., Lamberts, Roberto. Abingdon, Oxon: Spon Press. 2011. ISBN 9780415474146. OCLC 244063540.{{cite book}}: CS1 maint: others (link)
  5. ^ Nguyen, Anh-Tuan; Reiter, Sigrid; Rigo, Philippe (2014-01-01). "A review on simulation-based optimization methods applied to building performance analysis". Applied Energy. 113: 1043–1058. doi:10.1016/j.apenergy.2013.08.061. hdl:2268/155988. ISSN 0306-2619.
  6. ^ Performance measurement protocols for commercial buildings. American Society of Heating, Refrigerating and Air-Conditioning Engineers., U.S. Green Building Council., Chartered Institution of Building Services Engineers. Atlanta: American Society of Heating, Refrigerating, and Air-Conditioning Engineers. 2010. ISBN 9781461918226. OCLC 826659791.{{cite book}}: CS1 maint: others (link)
  7. ^ Balaras, C.A.; Argiriou, A.A. (2002-02-01). "Infrared thermography for building diagnostics". Energy and Buildings. 34 (2): 171–183. doi:10.1016/s0378-7788(01)00105-0. ISSN 0378-7788.
  8. ^ "Occupant Satisfaction Survey". Archived from the original on 2004-02-22.
  9. ^ “Daylighting | WBDG - Whole Building Design Guide.” n.d. Accessed November 15, 2024. https://www.wbdg.org/resources/daylighting.
  10. ^ Edwards, L.; Torcellini, P. (2002). "A literature review of the effects of natural light on building occupants" (PDF). National Renewable Energy Laboratory.
  11. ^ Elzeyadi, I; Abboushi, B. (2017). "Dynamic daylight: measuring the impacts of high performance daylighting systems on occupant's health, satisfaction, and productivity.". IES Annual Conference 2017. Portland, OR, USA: Illuminating Engineering Society.
  12. ^ Boubekri, M. (2014-09-29). Daylighting Design: Planning Strategies and Best Practice Solutions (1 ed.). ISBN 978-3764377281.
  13. ^ Dilaura, David L.; Houser, KW; Mistrick, RG; Steffy, GR. (2011-01-11). IES lighting handbook: reference and application (10th ed.). ISBN 978-0879952419.
  14. ^ Suk, JY (2019). "Luminance and vertical eye illuminance thresholds for occupants' visual comfort in daylit office environments". Building and Environment. 148: 107–115. doi:10.1016/j.buildenv.2018.10.058.
  15. ^ Kent, Michael; Parkinson, Thomas; Kim, Jungsoo; Schiavon, Stefano (2021). "A data-driven analysis of occupant workspace dissatisfaction". Building and Environment. 205: 108270. doi:10.1016/j.buildenv.2021.108270.
  16. ^ Fisk, W. J.; Lei-Gomez, Q.; Mendell, M. J. (2007-07-25). "Meta-analyses of the associations of respiratory health effects with dampness and mold in homes". Indoor Air. 17 (4): 284–296. doi:10.1111/j.1600-0668.2007.00475.x. ISSN 0905-6947. PMID 17661925. S2CID 21733433.
  17. ^ "Indoor Environmental Quality | NIOSH | CDC". www.cdc.gov. 2021-07-29. Retrieved 2021-08-24.
  18. ^ Brager, Gail S.; de Dear, Richard J. (1998-02-01). "Thermal adaptation in the built environment: a literature review". Energy and Buildings. 27 (1): 83–96. doi:10.1016/s0378-7788(97)00053-4. ISSN 0378-7788. S2CID 114893272.
  19. ^ ASHRAE (2019). ANSI/ASHRAE/IES Standard 90.1-2019 Energy Standard for Buildings Except Low-Rise Residential Buildings (Report).
  20. ^ CIBSE (2016). Guide B0: Applications and activities: HVAC strategies (Report).
  21. ^ Tashtoush, Bourhan; Molhim, M.; Al-Rousan, M. (2005-07-01). "Dynamic model of an HVAC system for control analysis". Energy. 30 (10): 1729–1745. doi:10.1016/j.energy.2004.10.004. ISSN 0360-5442.
  22. ^ Yoon, Ji Hoon; Baldick, Ross; Novoselac, Atila (2016-08-17). "Demand response control of residential HVAC loads based on dynamic electricity prices and economic analysis". Science and Technology for the Built Environment. 22 (6): 705–719. doi:10.1080/23744731.2016.1195659. ISSN 2374-4731. S2CID 157771793.
  23. ^ a b Ma, Yudong; Kelman, Anthony; Daly, Allan; Borrelli, Francesco (2012). "Predictive Control for Energy Efficient Buildings with Thermal Storage: Modeling, Stimulation, and Experiments". IEEE Control Systems Magazine. 32 (1): 44–64. doi:10.1109/MCS.2011.2172532. ISSN 1941-000X. S2CID 18462462.
  24. ^ Gallaher, Michael P.; O'Connor, Alan C.; Dettbarn, John L. Jr.; Gilday, Linda T. (2004). "Cost Analysis of Inadequate Interoperability in the U.S. Capital Facilities Industry". National Institute of Standards and Technology. doi:10.6028/nist.gcr.04-867.
  25. ^ "Home – Project Haystack". project-haystack.org. Retrieved 2022-11-14.
  26. ^ Balaji, Bharathan; Bhattacharya, Arka; Fierro, Gabriel; Gao, Jingkun; Gluck, Joshua; Hong, Dezhi; Johansen, Aslak; Koh, Jason; Ploennigs, Joern; Agarwal, Yuvraj; Berges, Mario; Culler, David; Gupta, Rajesh; Kjærgaard, Mikkel Baun; Srivastava, Mani (2016-11-16). "Brick". Proceedings of the 3rd ACM International Conference on Systems for Energy-Efficient Built Environments. BuildSys '16. New York, NY, USA: Association for Computing Machinery. pp. 41–50. doi:10.1145/2993422.2993577. ISBN 978-1-4503-4264-3. S2CID 207243610.
  27. ^ Amir, Roth; Michael, Wetter; Kyle, Benne; David, Blum; Yan, Chen; Gabriel, Fierro; Marco, Pritoni; Avijit, Saha; Draguna, Vrabie (2022-08-01). "Towards Digital and Performance-Based Supervisory HVAC Control Delivery". doi:10.20357/b70g62. {{cite journal}}: Cite journal requires |journal= (help)
  28. ^ Leslie, R.P. (2003-02-01). "Capturing the daylight dividend in buildings: why and how?". Building and Environment. 38 (2): 381–385. doi:10.1016/s0360-1323(02)00118-x. ISSN 0360-1323.
  29. ^ a b Hammond, G. P.; Jones, C. I. (May 2008). "Embodied energy and carbon in construction materials". Proceedings of the Institution of Civil Engineers - Energy. 161 (2): 87–98. doi:10.1680/ener.2008.161.2.87. ISSN 1751-4223.
  30. ^ Conti, John; Holtberg, Paul; Diefenderfer, Jim; LaRose, Angelina; Turnure, James T.; Westfall, Lynn (2016-05-01). "International Energy Outlook 2016 With Projections to 2040". doi:10.2172/1296780. OSTI 1296780. {{cite journal}}: Cite journal requires |journal= (help)
  31. ^ IEA (2021). Key World Energy Statistics 2021 (Report). Paris: IEA.
  32. ^ Denholm, Paul; O'Connell, Matthew; Brinkman, Gregory; Jorgenson, Jennie (2015). Overgeneration from Solar Energy in California. A Field Guide to the Duck Chart (Report). doi:10.2172/1226167.
  33. ^ a b Röck, Martin; Saade, Marcella Ruschi Mendes; Balouktsi, Maria; Rasmussen, Freja Nygaard; Birgisdottir, Harpa; Frischknecht, Rolf; Habert, Guillaume; Lützkendorf, Thomas; Passer, Alexander (January 2020). "Embodied GHG emissions of buildings – The hidden challenge for effective climate change mitigation". Applied Energy. 258: 114107. doi:10.1016/j.apenergy.2019.114107.
  34. ^ Guggemos, Angela Acree; Horvath, Arpad (June 2005). "Comparison of Environmental Effects of Steel- and Concrete-Framed Buildings". Journal of Infrastructure Systems. 11 (2): 93–101. doi:10.1061/(ASCE)1076-0342(2005)11:2(93). ISSN 1076-0342.
  35. ^ Fang, Demi; Brown, Nathan; De Wolf, Catherine; Mueller, Caitlin (October 2023). "Reducing embodied carbon in structural systems: A review of early-stage design strategies". Journal of Building Engineering. 76: 107054. doi:10.1016/j.jobe.2023.107054.
  36. ^ "LEED professional credentials | USGBC". new.usgbc.org. Retrieved 2019-04-06.
  37. ^ "Become a WELL AP". International WELL Building Institute. 2017-02-11. Retrieved 2019-04-06.
  38. ^ "Passivhaus Institut". passivehouse.com. Retrieved 2024-11-18.
  39. ^ Hong, Tianzhen; Yan, Da; D'Oca, Simona; Chen, Chien-fei (March 2017). "Ten questions concerning occupant behavior in buildings: The big picture". Building and Environment. 114: 518–530. doi:10.1016/j.buildenv.2016.12.006.
  40. ^ Doan, Dat Tien; Ghaffarianhoseini, Ali; Naismith, Nicola; Zhang, Tongrui; Ghaffarianhoseini, Amirhosein; Tookey, John (October 2017). "A critical comparison of green building rating systems". Building and Environment. 123: 243–260. doi:10.1016/j.buildenv.2016.12.006.
  41. ^ Liu, Qiang; Nie, Wen; Hua, Yun; Peng, Huitian; Liu, Changqi; Wei, Cunhou (January 2019). "Research on tunnel ventilation systems: Dust Diffusion and Pollution Behaviour by air curtains based on CFD technology and field measurement". Building and Environment. 147: 444–460. doi:10.1016/j.buildenv.2018.08.061. S2CID 117267043. Retrieved November 20, 2020.
  42. ^ 2019 Journal Impact Factor, Journal Citation Reports (Report). Clarivate Analytics. 2020.
  43. ^ Ahmad, Muhammad Waseem; Mourshed, Monjur; Rezgui, Yacine (15 July 2017). "Trees vs Neurons: Comparison between random forest and ANN for high-resolution prediction of building energy consumption". Energy and Buildings. 147: 77–89. doi:10.1016/j.enbuild.2017.04.038.
  44. ^ Afram, Abdul; Janabi-Sharifi, Farrokh; Fung, Alan; Raahemifar, Kaamran (15 April 2017). "Artificial neural network (ANN) based model predictive control (MPC) and optimization of HVAC systems: A state of the art review and case study of a residential HVAC system". Energy and Buildings. 141: 96–113. doi:10.1016/j.enbuild.2017.02.012.
  45. ^ Vilches, Alberto; Garcia-Martinez, Antonio; Sanchez-Montañes, Benito (2017). "Life cycle assessment (LCA) of building refurbishment: A literature review". Energy and Buildings. 135: 286–301. doi:10.1016/j.enbuild.2016.11.042.
  46. ^ 2019 Journal Impact Factor, Journal Citation Reports (Report). Clarivate Analytics. 2020.
  47. ^ Mendell, Mark J.; Heath, Garvin A. (23 November 2004). "Do indoor pollutants and thermal conditions in schools influence student performance? A critical review of the literature". Indoor Air. 15 (1): 27–52. doi:10.1111/j.1600-0668.2004.00320.x. PMID 15660567. S2CID 21132223. Retrieved November 20, 2020.
  48. ^ Xie, Xiaochen; Li, Yuguo; Chwang, Allen T.Y.; Ho, Pak-Leung; Seto, Wing Hong (29 May 2007). "How far droplets can move in indoor environments – revisiting the Wells evaporation–falling curve". Indoor Air. 17 (3): 211–225. doi:10.1111/j.1600-0668.2007.00469.x. PMID 17542834. Retrieved November 20, 2020.
  49. ^ Sundell, Jan; Levin, Hal; Nazaroff, William W.; Cain, William S.; Fisk, William J.; Grimsrud, David T.; Gyntelberg, Finn; Persily, Andrew K.; Pickering, Anthony C.; Samet, Jonathan M.; Spengler, John D.; Taylor, Steven; Weschler, Charles J. (7 December 2010). "Ventilation rates and health: multidisciplinary review of the scientific literature". Indoor Air. 21 (3): 191–204. doi:10.1111/j.1600-0668.2010.00703.x. PMID 21204989. Retrieved November 20, 2020.
  50. ^ 2019 Journal Impact Factor, Journal Citation Reports (Report). Clarivate Analytics. 2020.
  51. ^ Sunikka-Blank, Minna; Galvin, Ray (1 June 2012). "Introducing the prebound effect: the gap between performance and actual energy consumption". Building Research and Information. 4 (3): 260–273. doi:10.1080/09613218.2012.690952. S2CID 111136278. Retrieved November 20, 2020.
  52. ^ Häkkinen, Tarja; Belloni, Kaisa (11 April 2011). "Barriers and drivers for sustainable building". Building Research and Information. 39 (3): 239–255. doi:10.1080/09613218.2011.561948. S2CID 110423146. Retrieved November 20, 2020.
  53. ^ Vale, Lawrence J. (7 December 2013). "The politics of resilient cities: whose resilience and whose city?". Building Research and Information. 42 (2): 191–201. doi:10.1080/09613218.2014.850602. S2CID 110758538. Retrieved November 20, 2020.
  54. ^ 2019 Journal Impact Factor, Journal Citation Reports (Report). Clarivate Analytics. 2020.
  55. ^ Wetter, Michael (22 August 2010). "Co-simulation of building energy and control systems with the Building Controls Virtual Test Bed". Journal of Building Performance Simulation. 4 (3): 185–203. doi:10.1080/19401493.2010.518631. S2CID 6403867. Retrieved November 20, 2020.
  56. ^ Wetter, Michael; Zuo, Wangda; Nouidui, Thierry S.; Pang, Xiufeng (13 March 2013). "Modelica Buildings library". Journal of Building Performance Simulation. 7 (4): 253–270. doi:10.1080/19401493.2013.765506. S2CID 62538895. Retrieved November 20, 2020.
  57. ^ Haldi, Frédéric; Robinson, Darren (4 May 2011). "The impact of occupants' behaviour on building energy demand". Journal of Building Performance Simulation. 4 (4): 323–338. doi:10.1080/19401493.2011.558213. S2CID 111315955. Retrieved November 20, 2020.
  58. ^ 2019 Journal Impact Factor, Journal Citation Reports (Report). Clarivate Analytics. 2020.
  59. ^ Van Den Wymelenberg, Kevin; Inanici, Mehlika (20 February 2014). "A Critical Investigation of Common Lighting Design Metrics for Predicting Human Visual Comfort in Offices with Daylight". LEUKOS. 10 (3): 145–164. doi:10.1080/15502724.2014.881720. S2CID 109233278. Retrieved November 23, 2020.
  60. ^ Veitch, Jennifer A. (2001). "Psychological Processes Influencing Lighting Quality". LEUKOS. 30 (1): 124–140. doi:10.1080/00994480.2001.10748341. Retrieved November 23, 2020.
  61. ^ Veitch, Jennifer A.; Newsham, Guy R. (1998). "Lighting Quality and Energy-Efficiency Effects on Task Performance, Mood, Health, Satisfaction, and Comfort". LEUKOS. 27 (1): 107–129. Retrieved November 23, 2020.
  62. ^ 2019 Journal Impact Factor, Journal Citation Reports (Report). Clarivate Analytics. 2020.
  63. ^ 2019 Journal Impact Factor, Journal Citation Reports (Report). Clarivate Analytics. 2020.
  64. ^ Berardi, Umberto; Iannace, Gino (1 January 2017). "Predicting the sound absorption of natural materials: Best-fit inverse laws for the acoustic impedance and the propagation constant". Applied Acoustics. 115: 131–138. doi:10.1016/j.apacoust.2016.08.012. S2CID 114303375. Retrieved November 23, 2020.
  65. ^ Mydlarz, Charlie; Salamon, Justin; Bello, Juan Pablo (1 February 2017). "The implementation of low-cost urban acoustic monitoring devices". Applied Acoustics. 117: 207–218. arXiv:1605.08450. doi:10.1016/j.apacoust.2016.06.010. S2CID 13961321. Retrieved November 23, 2020.
  66. ^ Lim, Z.Y.; Putra, Azma; Nor, Mohd Jailani Mohd; Yaakob, Mohd Yuhazri (15 January 2018). "Sound absorption performance of natural kenaf fibres". Applied Acoustics. 130: 107–114. doi:10.1016/j.apacoust.2017.09.012. Retrieved November 23, 2020.
  67. ^ 2019 Journal Impact Factor, Journal Citation Reports (Report). Clarivate Analytics. 2020.
  68. ^ Rea, Mark S.; Figueiro, Mariana G. (6 December 2016). "Light as a circadian stimulus for architectural lighting". Lighting Research & Technology. 50 (4): 497–510. doi:10.1177/1477153516682368. S2CID 114410985. Retrieved November 23, 2020.
  69. ^ Royer, Michael R.; Wilkerson, Andrea; Wei, Minchen; Houser, Kevin; Davis, Robert (10 August 2016). "Human perceptions of colour rendition vary with average fidelity, average gamut, and gamut shape". Lighting Research & Technology. 49 (8): 966–991. doi:10.1177/1477153516663615. S2CID 113506736. Retrieved November 23, 2020.
  70. ^ Wei, Minchen; Houser, Kevin; David, Aurelien; Krames, Mike R. (13 August 2016). "Colour gamut size and shape influence colour preference". Lighting Research & Technology. 49 (8): 992–1014. doi:10.1177/1477153516651472. S2CID 125131197. Retrieved November 23, 2020.
  71. ^ 2019 Journal Impact Factor, Journal Citation Reports (Report). Clarivate Analytics. 2020.
Retrieved from "https://en.wikipedia.org/w/index.php?title=Building_science&oldid=1258339938"