Energy retrofit and passive cooling: overheating and air quality in primary schools

While building stock modelling has been used previously to investigate the space heating demand implications of national energy efficiency retrofitting, there are also implications for indoor overheating and air quality, particularly in schools, with highly intermittent occupancy patterns. This paper assesses indoor overheating risk and air quality within an English classroom stock model containing 111 archetypes, based on the analysis of the nationwide Property Data Survey Programme (PDSP) containing 9629 primary school buildings in England. Metrics for indoor temperatures, heating demand and concentrations of three contaminants (CO₂, NO₂, PM_2.5) were estimated in naturally ventilated classrooms, while exploring future climate projections, retrofit and overheating mitigation scenarios to analyse school stock resilience. Classrooms with a south-east orientation experience around four to six times the overheating-hours compared with those with a northern orientation. Post-1976 archetypes are most susceptible to overheating, indicative of the conflict between better insulated and airtight classrooms and overheating prevention. A range of retrofit and passive cooling measures can mitigate against overheating alone, although mechanically driven cooling and filtration may be required towards the 2080s. While no single measure predicted universally positive effects for building performance, night ventilation and overhangs were found to be particularly effective passive overheating mitigation methods across the school stock.

Policy relevance

With around 30% of their waking hours spent in classrooms, English schoolchildren experience greater vulnerability to higher indoor temperatures and air pollutants than adults due to limited thermoregulation and immunity, with additional impacts on cognitive performance. An increased risk of overheating (due to a warming climate) necessitates the development of future overheating mitigation policies and strategies, which could directly impact separate retrofit strategies required for energy demand reduction. Airflow network modelling has demonstrated how such measures could contribute to school sector carbon emissions. While the granularity of national datasets represents a hurdle to predictive modelling, the orientations, geographical regions and construction eras most vulnerable to overheating risk have been identified. Building stock-level modelling could thus be used to identify sectors of the stock most vulnerable to overheating and poor air quality, leading to strategies with more targeted solutions, including the use of alternative cooling strategies to air-conditioning.