1 Department of Environmental Science - Atmospheric modeling, Department of Environmental Science, Science and Technology, Aarhus University2 Department of Environmental Science - Atmospheric chemistry and physics (Atmospheric proceses) (ATPRO), Department of Environmental Science, Science and Technology, Aarhus University3 University of Worcester4 Medical University of Vienna5 Department of Environmental Science - Atmospheric chemistry and physics (Atmospheric proceses) (ATPRO), Department of Environmental Science, Science and Technology, Aarhus University
Objectives: Exposure to pollen is typically assessed using data collected at fixed roof-top monitoring stations, which give a general picture of airborne pollen concentrations over a wide region. Actual exposure levels can be obtained through personal exposure monitoring. This is typically done using a suction sampler worn on the chest or lapel that measures breathing zone concentration; a more useful exposure parameter for pollen allergy sufferers is the amount of pollen inhaled, i.e. the dose. The objective of this study was to investigate how well monitoring station data reflect actual exposure, something that is currently not well understood. Methods: Exposure samples were collected during the 2011 grass pollen season in an area of abundant unmaintained grass coverage close to the centre of Aarhus, Denmark. Sampling was performed at two-hourly intervals between 12:00 and 20:00 on 14 separate days whilst walking a set route. Journey times were in the region of 28 minutes. Nasal Air Samplers (small impaction devices worn inside the nostrils that capture inhaled particles) were used. The number of inhaled grass pollen grains was counted under a light microscope and compared with concurrent concentrations recorded at a nearby roof level pollen monitoring station. The relationship between these two data sets was also compared with local meteorological variables (wind direction, wind speed, temperature, relative humidity and solar radiation). Results: The number of grass pollen grains inhaled during individual exposure episode ranged from 6 -127 (median 34), and inhalation rates were between 0.23 - 4.83 (median 1.20) grains min-1. Corresponding concentrations recorded at the monitoring station lay within the range 0 - 311 (median 56) grains m-3. The Spearman's correlation coefficient between the exposure and monitoring station data was 0.65 (p<0.001). Exposure was disproportionately high relative to monitoring station data in 15% of the dataset, with these occurring close to midday (12:00-14:00). On no occasion was exposure disproportionately low. Correlation coefficients for the ‘early’ (12:00-14:00) and ‘late’ (18:00-20:00) periods differ considerably (rs=0.51 and rs=0.82 respectively). The mean profile of monitoring station concentrations shows a persistent increase from 12:00-20:00 whilst for the exposure data the opposite is true. No relationship was observed between the standardised ratio of exposure to monitored data and any of the available weather data. Conclusions: Whilst the monitoring station data is a reasonable proxy for exposure, the quality of the relationship depends upon the time of day. Within the study area the risk of exposure decreases between noon and mid-evening, likely reflecting diurnal variation in the emission of grass pollen. This trend is contrary to what the monitoring station predicts, and this has implications where allergen avoidance is being advocated as a method for controlling symptoms. An exposure model for grass pollen is currently being developed for Aarhus. Model performance will be tested against the empirical exposure data described here, the ultimate aim being to build upon this study by using the model to assess the importance of source proximity to exposure.