Predictions of airborne infection risk can be made based on the fraction of rebreathed air inferred from point measurements of carbon dioxide (CO⁣2
). We investigate the extent to which environmental factors, particularly spatial variations due to the ventilation provision, affect the uncertainty in these predictions. Spatial variations are expected to be especially problematic in naturally ventilated spaces, which include the majority of classrooms in the UK. An idealized classroom, broadly representative of the physics of (buoyancy-driven) displacement ventilation, is examined using computational fluid dynamics, with different ventilation configurations. Passive tracers are used to model both the CO⁣2
generated by all 32 occupants and the breath of a single infectious individual (located in nine different regions). The distribution of infected breath is shown to depend strongly on the distance from the release location but is also affected by the pattern of the ventilating flow, including the presence of stagnating regions. However, far-field exposure predictions based on single point measurements of CO⁣2
within the breathing zone are shown to rarely differ from the actual exposure to infected breath by more than a factor of two—we argue this uncertainty is small compared with other uncertainties inherent in modelling airborne infection risk.