Indoor air contamination with mould spores currently experiences an increasing interest with respect to their relevance to health. To assess adverse health effects, epidemiological studies combine the health outcome of individuals with their concomitant exposure to airborne spores, which is observed, for example, during the current month. While the latter is representative for the studied period, health effects might also be the result of long term-exposure or emerge in consequence of a peak of pollution throughout the year. To consider such questions, additional information about the spatiotemporal distribution of airborne spores is necessary.
This paper aims at elucidating the spatial and temporal variation of spore concentrations in Leipzig, Germany. The analysis is based on 1165 matched pairs of indoor and outdoor measurements taken in the period 1998–2002. All data were collected in the frame of previous epidemiological studies and refer to apartments. The analysis comprised spore concentrations (as CFU m−3 in air) of the most important genera, such as Penicillium, Aspergillus, Alternaria, Mucorales, Cladosporium, and also for yeasts.
We found two groups of fungi differing in their spatiotemporal distribution. As this behaviour can be explained by the predominant origin and growing conditions, we call them indoor-relevant and outdoor-relevant genera. Penicillium species are a representative of the former group, while the latter is well represented by Cladosporium. In the studied period we did not observe a clear trend in the spore concentration. Outdoors there is a year-to-year variation of Cladosporium spore concentrations, which follow the prevalent climatic conditions.
For the spore concentration of the outdoor-relevant group a significant annual cycle was observed. Highest concentrations occurred during the summer months and were about 100× the winter burden. That means, for a direct comparison of measurements of spore concentrations taken during different months the season has to be considered. We summarise the findings in a seasonal model, which is fitted to our measurements. Based on the model we developed a procedure for seasonal adjustment, which enabled us to estimate the annual peak spore concentration utilising one monthly observation.