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A Meta-Synthesis Review of Occupant Comfort Assessment in Buildings (2002–2022)

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  • Amir Faraji

    (Construction Project Management Department, Faculty of Architecture, KHATAM University, Tehran 1991633357, Iran
    School of Engineering, Design and Built Environment, Western Sydney University, Penrith, NSW 2751, Australia)

  • Maria Rashidi

    (School of Engineering, Design and Built Environment, Western Sydney University, Penrith, NSW 2751, Australia)

  • Fatemeh Rezaei

    (Faculty of Architecture, KHATAM University, Tehran 1991633357, Iran)

  • Payam Rahnamayiezekavat

    (School of Engineering, Design and Built Environment, Western Sydney University, Penrith, NSW 2751, Australia)

Abstract

Occupant comfort in buildings is one of the most crucial considerations in designing a building. Accordingly, there is a growing interest in this area. Aspects of comfort include thermal comfort, visual comfort, acoustic comfort, and indoor air quality (IAQ) satisfaction. The objective of this state-of-the-art review was to provide a comprehensive, explicit, and up-to-date literature review on occupant comfort in buildings, since this issue has a great impact on the lifestyle, health, and productivity of occupants. A meta-synthesis method was also used for an analytical-interpretive review of previous studies. In this research, scientific research studies related to the subject of indoor occupant comfort in the period 2002–2022 were reviewed. Previous reviews have often covered the fundamental concepts and principles related to indoor occupant comfort. Although innumerable studies have focused on thermal comfort, other aspects of occupant comfort have not been considered. The review is analyzed and discussed in reference to type of study, case study geographical locations and climate zones, case study building types, decision-making models, assessment criteria, data-collection tools, and data analysis strategies. Finally, future research recommendations are presented. Through the review, we find that the comfort models used in research are mostly based on comfort perception votes collected from experimental studies, which may not reflect the preferences of users well. In addition, only the influence of environmental factors on the models has been investigated, and other personal factors have been ignored. This study presents a useful guide for researchers to determine their outlines for future research in this field.

Suggested Citation

  • Amir Faraji & Maria Rashidi & Fatemeh Rezaei & Payam Rahnamayiezekavat, 2023. "A Meta-Synthesis Review of Occupant Comfort Assessment in Buildings (2002–2022)," Sustainability, MDPI, vol. 15(5), pages 1-36, February.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:5:p:4303-:d:1083164
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    References listed on IDEAS

    as
    1. Sukjoon Oh & Suwon Song, 2021. "Detailed Analysis of Thermal Comfort and Indoor Air Quality Using Real-Time Multiple Environmental Monitoring Data for a Childcare Center," Energies, MDPI, vol. 14(3), pages 1-16, January.
    2. Nundy, Srijita & Ghosh, Aritra, 2020. "Thermal and visual comfort analysis of adaptive vacuum integrated switchable suspended particle device window for temperate climate," Renewable Energy, Elsevier, vol. 156(C), pages 1361-1372.
    3. Wang, Ran & Lu, Shilei & Feng, Wei, 2020. "A three-stage optimization methodology for envelope design of passive house considering energy demand, thermal comfort and cost," Energy, Elsevier, vol. 192(C).
    4. Zomorodian, Zahra S. & Tahsildoost, Mohammad, 2019. "Assessing the effectiveness of dynamic metrics in predicting daylight availability and visual comfort in classrooms," Renewable Energy, Elsevier, vol. 134(C), pages 669-680.
    5. Guofeng Ma & Xuhui Pan, 2021. "Research on a Visual Comfort Model Based on Individual Preference in China through Machine Learning Algorithm," Sustainability, MDPI, vol. 13(14), pages 1-23, July.
    6. Steemers, Koen, 1994. "Daylighting design: Enhancing energy efficiency and visual quality," Renewable Energy, Elsevier, vol. 5(5), pages 950-958.
    7. Leonidas Bourikas & Stephanie Gauthier & Nicholas Khor Song En & Peiyao Xiong, 2021. "Effect of Thermal, Acoustic and Air Quality Perception Interactions on the Comfort and Satisfaction of People in Office Buildings," Energies, MDPI, vol. 14(2), pages 1-18, January.
    8. Carlucci, Salvatore & Causone, Francesco & De Rosa, Francesco & Pagliano, Lorenzo, 2015. "A review of indices for assessing visual comfort with a view to their use in optimization processes to support building integrated design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 1016-1033.
    9. Dietz, Annelore & Vera, Sergio & Bustamante, Waldo & Flamant, Gilles, 2020. "Multi-objective optimization to balance thermal comfort and energy use in a mining camp located in the Andes Mountains at high altitude," Energy, Elsevier, vol. 199(C).
    10. Ebrahimi-Moghadam, Amir & Ildarabadi, Paria & Aliakbari, Karim & Fadaee, Faramarz, 2020. "Sensitivity analysis and multi-objective optimization of energy consumption and thermal comfort by using interior light shelves in residential buildings," Renewable Energy, Elsevier, vol. 159(C), pages 736-755.
    11. Yonggang Zhang & Yongwei Zhong & Yingda Gong & Lirong Zheng, 2018. "The Optimization of Visual Comfort and Energy Consumption Induced by Natural Light Based on PSO," Sustainability, MDPI, vol. 11(1), pages 1-11, December.
    12. Isabel Montiel & Asunción M. Mayoral & Jose Navarro Pedreño & Silvia Maiques, 2019. "Acoustic Comfort in Learning Spaces: Moving Towards Sustainable Development Goals," Sustainability, MDPI, vol. 11(13), pages 1-18, June.
    13. Ma, Nan & Aviv, Dorit & Guo, Hongshan & Braham, William W., 2021. "Measuring the right factors: A review of variables and models for thermal comfort and indoor air quality," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    14. Ilaria Ballarini & Giovanna De Luca & Argun Paragamyan & Anna Pellegrino & Vincenzo Corrado, 2019. "Transformation of an Office Building into a Nearly Zero Energy Building (nZEB): Implications for Thermal and Visual Comfort and Energy Performance," Energies, MDPI, vol. 12(5), pages 1-18, March.
    15. Zhang, Sheng & Cheng, Yong & Fang, Zhaosong & Huan, Chao & Lin, Zhang, 2017. "Optimization of room air temperature in stratum-ventilated rooms for both thermal comfort and energy saving," Applied Energy, Elsevier, vol. 204(C), pages 420-431.
    16. Kim, Jimin & Hong, Taehoon & Jeong, Jaemin & Koo, Choongwan & Jeong, Kwangbok, 2016. "An optimization model for selecting the optimal green systems by considering the thermal comfort and energy consumption," Applied Energy, Elsevier, vol. 169(C), pages 682-695.
    17. Ochoa, Carlos E. & Aries, Myriam B.C. & van Loenen, Evert J. & Hensen, Jan L.M., 2012. "Considerations on design optimization criteria for windows providing low energy consumption and high visual comfort," Applied Energy, Elsevier, vol. 95(C), pages 238-245.
    18. Djongyang, Noël & Tchinda, René & Njomo, Donatien, 2010. "Thermal comfort: A review paper," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(9), pages 2626-2640, December.
    19. Michael, A. & Gregoriou, S. & Kalogirou, S.A., 2018. "Environmental assessment of an integrated adaptive system for the improvement of indoor visual comfort of existing buildings," Renewable Energy, Elsevier, vol. 115(C), pages 620-633.
    20. Korkas, Christos D. & Baldi, Simone & Michailidis, Iakovos & Kosmatopoulos, Elias B., 2016. "Occupancy-based demand response and thermal comfort optimization in microgrids with renewable energy sources and energy storage," Applied Energy, Elsevier, vol. 163(C), pages 93-104.
    21. Yang, Shiyu & Wan, Man Pun & Chen, Wanyu & Ng, Bing Feng & Dubey, Swapnil, 2020. "Model predictive control with adaptive machine-learning-based model for building energy efficiency and comfort optimization," Applied Energy, Elsevier, vol. 271(C).
    22. Chen, Xiao & Wang, Qian & Srebric, Jelena, 2016. "Occupant feedback based model predictive control for thermal comfort and energy optimization: A chamber experimental evaluation," Applied Energy, Elsevier, vol. 164(C), pages 341-351.
    23. Mukhtar, A. & Ng, K.C. & Yusoff, M.Z., 2018. "Design optimization for ventilation shafts of naturally-ventilated underground shelters for improvement of ventilation rate and thermal comfort," Renewable Energy, Elsevier, vol. 115(C), pages 183-198.
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