Air change rates and infection risk in school environments: Monitoring naturally ventilated classrooms in a northern Italian urban context

Abstract

The importance of building ventilation in avoiding long-distance airborne transmission has been highlighted with the advent of the COVID-19 pandemics. Among others, school environments, in particular classrooms, present criticalities in the implementation of ventilation strategies and their impact on indoor air quality and risk of contagion. In this work, three naturally ventilated school buildings located in northern Italy have undergone monitoring at the end of the heating season. Environmental parameters, such as CO₂ concentration and indoor/outdoor air temperature, have been recorded together with the window opening configurations to develop a two-fold analysis: i) the estimation of real air change rates through the transient mass balance equation method, and ii) the individual infection risk via the Wells-Riley equation. A strong statistical correlation has been found between the air change rates and the windows opening configuration by means of a window-to-volume ratio between the total opening area and the volume of the classroom, which has been used to estimate the individual infection risk. Results show that the European Standard recommendation for air renewal could be achieved by a window opening area of at least 1.5 m², in the most prevailing Italian classrooms. Furthermore, scenarios in which the infector agent is a teacher show higher individual infection risk than those in which the infector is a student. In addition, the outcomes serve school staff as a reference to ensure adequate ventilation in classrooms and keep the risk of infection under control based on the number of the students and the volume of the classroom.

Keywords: Air change rates; Infection risk; Natural ventilation; School building; Transient mass-balance equation; Well-Riley equation.

Fig. 1

Location of the case-study school buildings in the city of Milan.

Fig. 2

Installation scheme of the indoor dataloggers.

Fig. 3

Indoor placement of the internal dataloggers: on the wall opposite the blackboard (a), on the blackboard wall (b) (pictures referred to classroom B4A).

Fig. 4

Shape and typology of the windows found in classroom A1C. Type A: tilt-and-turn windows with two casements.

Fig. 5

Shape and typology of the windows found in classrooms B4A and B5C. Type B: Sliding windows.

Fig. 6

Shape and typology of the windows found in classroom C3D. Type C: Tilt-and-turn windows with one casement.

Fig. 7

Shape and typology of the windows found in classroom 3CB. Type D: Vertical pivot windows.

Fig. 8

Example of CO₂ concentration and indoor air temperature measurements in two points of a classroom (B4A).

Fig. 9

Absolute differences on CO₂ concentration (A) and indoor air temperature (B) between the dataloggers in each classroom.

Fig. 10

Trend of indoor CO₂ concentration (CO2), indoor air temperature (Tin), outdoor air temperature (Tout), and window opening ratios (Aw/Vc) during the occupied period in School A classrooms A1C (A) and A4B (B).

Fig. 11

Trend of indoor CO₂ concentration (CO2), indoor air temperature (Tin), outdoor air temperature (Tout), and window opening ratios (Aw/Vc) during the occupied period in School B classrooms B4A (A) and B5C (B).

Fig. 12

Trend of indoor CO₂ concentration (CO2), indoor air temperature (Tin), outdoor air temperature (Tout), and window opening ratios (Aw/Vc) during the occupied period in School C classrooms C3B (A) and C3D (B).

Fig. 13

Impact of window opening ratio (Aw/Vc) on air change per hour.

Fig. 14

Comparison of individual infection probability (%) of Sars-CoV-2 for Scenario 1 (i.e., with an infected student) and Scenario 2 (i.e., with an infected teacher).

Fig. 15

Individual infection probability (%) as a function of the window opening ratio (Aw/Vc) and different classroom dimensions. Dashed lines represent Scenario 1 (i.e., with an infected student), while continuous lines represent Scenario 2 (i.e., with an infected teacher).