Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/25817
Title: Correlation model to evaluate climate effect on indoor air quality and thermal comfort in houses
Authors: May, Z
Kolokotroni, M
Keywords: climate correlation;indoor air quality;adaptive thermal comfort;indoor condition prediction;residential building
Issue Date: 5-Sep-2022
Publisher: Ecohouse Initative Ltd.
Citation: May, Z. and Kolokotroni, M. (2022) 'Correlation model to evaluate climate effect on indoor air quality and thermal comfort in houses', Proceedings of the 3rd International Conference on: Comfort at the Extremes: Covid, Climate Change and Ventilation [CATE 2022], Edinburgh, UK, 5-6 September, pp. 1 - 15. Available at: http://mosser.scot/CATE2022/CATE2022%20Proceedings%20(web_220930).pdf.
Abstract: This study presents the development of a climate correlation model encompassing the impacts of diverse climatic parameters for the indoor conditions prediction concerning thermal comfort and indoor air quality (IAQ). We investigated the relationship between outdoor and indoor conditions in free-standing small houses, and compared the results of two contrasting European climates - Nordic and Mediterranean. The impacts of ventilation modes on the IAQ - infiltration and natural ventilation through window openings - were compared using a black-box model generated in the CONTAM and EnergyPlus simulation engines. The effects of ventilation and heating schedules, model size, and orientation for prevailing wind were tested considering factors that could statistically change correlation equations. The correlations between dry bulb temperature, operative temperature, temperature differences between indoor and outdoor, and airflow were analysed to identify significant patterns or trends between variables without controlling or manipulating any of them. The results were evaluated using adaptive thermal comfort equations and equations to estimate space-specific indoor CO2 concentrations. The study informed the importance of user-driven decision-making processes for predicting the indoor conditions from outdoor climatic parameters which could encourage behavioural change for building operation to improve building thermal comfort and IAQ through natural ventilation strategies.
URI: https://bura.brunel.ac.uk/handle/2438/25817
ISBN: 978-1-9161876-4-1
Other Identifiers: ORCID iD: Maria Kolokotroni https://orcid.org/0000-0003-4478-1868
Appears in Collections:Dept of Mechanical and Aerospace Engineering Research Papers

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