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Development of an Indoor Environmental Quality Assessment Tool for the Rating of Offices in Real Working Conditions

Author

Listed:
  • Anna Devitofrancesco

    (Construction Technologies Institute of the National Research Council of Italy (ITC–CNR), via Lombardia 49, San Giuliano Milanese, 20098 Milan, Italy)

  • Lorenzo Belussi

    (Construction Technologies Institute of the National Research Council of Italy (ITC–CNR), via Lombardia 49, San Giuliano Milanese, 20098 Milan, Italy)

  • Italo Meroni

    (Construction Technologies Institute of the National Research Council of Italy (ITC–CNR), via Lombardia 49, San Giuliano Milanese, 20098 Milan, Italy)

  • Fabio Scamoni

    (Construction Technologies Institute of the National Research Council of Italy (ITC–CNR), via Lombardia 49, San Giuliano Milanese, 20098 Milan, Italy)

Abstract

The Indoor Environmental Quality (IEQ) refers to the quality of indoor spaces in relation to the health and well-being of users. IEQ is a holistic concept considering various components of the overall indoor comfort: thermo-hygrometric, lighting, air quality and acoustics. Each component is described through specific performance indicators and benchmarks. The quality of the built environment is assessed at different stages from design to operational phase. The scientific literature reports several case studies related to the assessment of the individual components of the IEQ Tools aimed at the evaluation of the overall IEQ. The paper proposes an assessment tool based on the SB Method (Sustainable Building Method) and the Multi Criteria Analysis for the evaluation of IEQ during the operational phase of a building. Each component of IEQ is analysed through objective indicators and calculation methods. The tool provides two main outcomes: a global score expressing the overall performance of the building from the IEQ perspective; quantitative evaluations of all indoor comfort components through monitoring and measurement of the environmental variables. The above contributes to select intervention areas to optimize indoor design and to identify technologies aimed at ensuring the best IEQ levels for users at the operational stage. The system was applied to an open-plan working space of an office building. Monitoring activities and measurements are carried out to detect the indoor and outdoor variables affecting the IEQ. All aspects of IEQ were analysed and quantified so to evaluate the overall performance of the building and provide data to improve the working conditions.

Suggested Citation

  • Anna Devitofrancesco & Lorenzo Belussi & Italo Meroni & Fabio Scamoni, 2019. "Development of an Indoor Environmental Quality Assessment Tool for the Rating of Offices in Real Working Conditions," Sustainability, MDPI, vol. 11(6), pages 1-17, March.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:6:p:1645-:d:215096
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    References listed on IDEAS

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    1. Baird, George & Field, Carmeny, 2013. "Thermal comfort conditions in sustainable buildings – Results of a worldwide survey of users’ perceptions," Renewable Energy, Elsevier, vol. 49(C), pages 44-47.
    2. Michał Piasecki & Mateusz Kozicki & Szymon Firląg & Anna Goljan & Krystyna Kostyrko, 2018. "The Approach of Including TVOCs Concentration in the Indoor Environmental Quality Model (IEQ)—Case Studies of BREEAM Certified Office Buildings," Sustainability, MDPI, vol. 10(11), pages 1-22, October.
    3. Carmen María Calama-González & Rafael Suárez & Ángel Luis León-Rodríguez & Simone Ferrari, 2019. "Assessment of Indoor Environmental Quality for Retrofitting Classrooms with An Egg-Crate Shading Device in A Hot Climate," Sustainability, MDPI, vol. 11(4), pages 1-21, February.
    4. World Commission on Environment and Development,, 1987. "Our Common Future," OUP Catalogue, Oxford University Press, number 9780192820808.
    5. Oriol Pons & Albert De la Fuente & Antonio Aguado, 2016. "The Use of MIVES as a Sustainability Assessment MCDM Method for Architecture and Civil Engineering Applications," Sustainability, MDPI, vol. 8(5), pages 1-15, May.
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    1. Bibars Amangeldy & Nurdaulet Tasmurzayev & Timur Imankulov & Baglan Imanbek & Waldemar Wójcik & Yedil Nurakhov, 2025. "A Hybrid Machine Learning Approach for High-Accuracy Energy Consumption Prediction Using Indoor Environmental Quality Sensors," Energies, MDPI, vol. 18(15), pages 1-31, August.
    2. Zhifeng Shen & Xirui Yang & Chunlu Liu & Junjie Li, 2021. "Assessment of Indoor Environmental Quality in Budget Hotels Using Text-Mining Method: Case Study of Top Five Brands in China," Sustainability, MDPI, vol. 13(8), pages 1-24, April.

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