Overview of indoor air pollution measurements in elementary schools in Denmark and impacts of air-purification devices: a case study

Air pollution is the leading Global Burden of Disease risk factor [1]. People spend most of the time indoors and especially children are estimated to spend 90% of their day in indoor environments [2] where they are exposed to indoor air pollution. Children are particularly susceptible to the effects of air pollution, as their faster breathing rate and immature bodies make them more prone to accumulating higher concentrations of pollutants in their bodies [3]. As part of the Horizon Europe project LEARN, we measured indoor air pollution in four elementary schools in Denmark. Our measurements comprised several air-quality parameters such as particulate matter (PM) mass focusing on PM_2.5, particle number (PN), and black carbon (BC). The study followed a single blinded crossover design with measurements carried out in two classrooms in parallel. One classroom had an air-purification device with particulate filter in operation (intervention) and the other had an air-purification device without a filter installed (sham) in a randomized manner. The researchers were aware of the presence/absence of the intervention, while children and teachers were blinded. Each measurement campaign lasted five to six weeks including a baseline, intervention, wash-out period, and sham. Fig. 1 shows diurnal variation in PM_2.5 levels in two different classrooms with and without intervention. Interestingly, between 8:00-14:00 on weekdays when the classrooms were occupied, measurements showed an increase in PM_2.5 indicating high exposure during their school hours. The effects of air-purification device are clearly visible as PM_2.5 levels are lower at times when classrooms had the intervention. The absolute mass concentrations are not final as no sensor calibration factors have yet been applied to data shown here. During the next step of the study, we will investigate the factors leading to high PM_2.5 concentrations indoors during the classroom hours and suggest mitigation strategies for air pollutants improving indoor air quality in schools. We will also investigate the effects of PM_2.5 on children’s cognitive functions during school hours. First results on the efficiency of air purification systems within our studies suggest that such set-ups can improve air quality in classrooms to a significant extent. However, more detailed analysis needs to be conducted before final assessment of this effect can be made.

Fig. 1: Comparison of diurnal variation in PM_2.5 for individual classes i.e., a.) classroom 1 and b.) classroom 2 with intervention periods and sham intervention periods.

References:

1. Murray, C. J. L. et al. Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet 396, 1223–1249 (2020).

2. de Gennaro, G. et al. Indoor air quality in schools. Environ. Chem. Lett. 12, 467–482 (2014).

3. Bennett, W. D., Zeman, K. L. & Jarabek, A. M. Nasal Contribution to Breathing and Fine Particle Deposition in Children Versus Adults. J. Toxicol. Environ. Health A 71, 227–237 (2008).