Abstract
Children spend a large part of their waking lives in school buildings. There is substantial evidence that poor indoor air quality (IAQ) and thermal discomfort can have detrimental impacts on the performance, wellbeing and health of schoolchildren and staff. Maintaining good IAQ while avoiding overheating in classrooms is challenging due to the unique occupancy patterns and heat properties of schools. Building stock modelling has been extensively used in recent years to quantify and evaluate performance of large numbers of buildings at various scales. This paper builds on an archetype stock modelling approach which represents the diversity of the school stock in England through an analysis of The Property Data Survey Programme (PDSP) and the Display Energy Certificates (DEC) databases. The model was used for simulating Indoor-to-Outdoor pollution ratios to estimate indoor air pollution levels (NO2, PM2.5 and CO2) and thermal comfort (overheating) in two climate areas in England: London and the West Pennines. analysis highlighted variations in classrooms’ indoor CO2 levels in different seasons and explored the risk of overheating in relation to a classroom’s orientation.
Highlights
Children spend a significant amount of their daily lives in schools’ premises, 70% inside classrooms [1], subject to unique and dynamic usage patterns [2]
Exposure to air pollution is a major contributor to mortality in the UK [3] with high concentrations of Particulate Matter (PM) and Nitrogen dioxide (NO2) believed to be a significant component in increased death rates in England [3], related to illnesses such as Asthma and decreased nasal patency [4]
Stock Data analysis (PDSP / DEC) & Archetype model development The archetypes in this study were developed following a statistical analysis of two databases: Property Data Survey Programme (PDSP) [17] and Display Energy Certificates (DEC) [18] databases
Summary
Children spend a significant amount (around 30%) of their daily lives in schools’ premises, 70% inside classrooms [1], subject to unique and dynamic usage patterns [2]. Avoiding compromises in Indoor Environmental Quality (IEQ) due to changes in occupancy patterns, seasonal or outdoor conditions can be a challenging task, even more so in the context of climate change. The indoor environment is often evaluated using deterministic models, in which exposure to pollution is modelled as a function of a set of building characteristics (e.g., outdoor concentrations, indoor emissions and indoor use patterns [6], [7]). School buildings in the UK were originally designed to deal with heating demand. As such they largely rely on natural ventilation [11].
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