Window pane condensation and high indoor vapour contribution − markers of an unhealthy indoor climate?

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Abstract
The aim of this study was to investigate whether window pane condensation and indoor vapour contribution ≥ 3 g/m3 could be used as indicators of defective air change rate, high indoor humidity and high mite allergen concentration in mattress dust. Actual ventilation rate, indoor temperature, air humidity (AIH/RH) and concentrations of mite allergen were measured in 59 houses and compared with received outdoor temperatures and air humidity. Indoor vapour contribution defined as the difference between the indoor and the outdoor vapour concentration was calculated. Sensitivity, specificity, predictive values and accuracy were calculated for window pane condensation and high vapour contribution (≥ 3 g/m3), as indicators of defective ventilation (< 0.5 ACH), high indoor humidity (≥ 7 g/kg and ≥ 45% RH) and high mite allergen concentration in mattress dust (≥ 2 μg/g). All houses with high humidity and high mite allergen concentrations were positive for the two indicators (high sensitivity), but with a specificity of only 50% so that half of the houses with reported condensation and high vapour contribution turned out to be low pollution houses with adequate high ventilation levels. Both indicators had high negative predictive values and absence of the two indicators almost certainly (97–100%) excluded high indoor pollution with high humidity and high mite concentrations. Overall more than 70% of the dwellings were correctly classified by the two indicators. Absence of window pane condensation on double-glazed windows and low indoor vapour contribution (< 3 g/m3) during the winter are true markers of a dwelling without high indoor air humidity and without high mite allergen concentrations in mattress dust in houses in a cold temperate climate with subzero outdoor temperatures. The presence of the two indicators is associated with a 18–45% risk of high humidity and mite allergen concentrations so in this latter group further measurements are needed for correct classification.