Personal Exposure to Grass Pollen: Relating Inhaled Dose to Background Concentration

Background Very few studies on human exposure to allergenic pollen have been conducted using direct methods, with background concentrations measured at city center monitoring stations typically taken as a proxy for exposure despite the inhomogeneous nature of atmospheric pollen concentrations. A 2003 World Health Organization report highlighted the need for an improved understanding of the relation between monitoring station data and actual exposure. Objective To investigate the relation between grass pollen dose and background concentrations measured at a monitoring station, to assess the fidelity of monitoring station data as a qualitative proxy for dose, and to evaluate the ratio of dose rate to background concentration. Methods Grass pollen dose data were collected in Aarhus, Denmark, in an area where grass pollen sources were prevalent, using Nasal Air Samplers. Sample collection lasted for approximately 25 to 30 minutes and was performed at 2-hour intervals from noon to midevening under moderate exercise by 2 individuals. Results A median ratio of dose rate to background concentration of 0.018 was recorded, with higher ratio values frequently occurring at 12 to 2 pm, the time of day when grass species likely to be present in the area are expected to flower. From 4 to 8 pm, dose rate and background concentration data were found to be strongly and significantly correlated (rs = 0.81). Averaged dose rate and background concentration data showed opposing temporal trends. Conclusion Where local emissions are not a factor, background concentration data constitute a good quantitative proxy for inhaled dose. The present ratio of dose rate to background concentration may aid the study of dose–response relations.

Seasonal Variation in Diurnal Atmospheric Grass Pollen Concentration Profiles

In this study, the diurnal atmospheric grass pollen concentration profile within the Danish city of Aarhus was shown to change in a systematic manner as the pollen season progressed. Although diurnal grass pollen profiles can differ greatly from day-to-day, it is common practice to establish the time of day when peak concentrations are most likely to occur using seasonally averaged diurnal profiles. Atmospheric pollen loads are highly dependent upon emissions, and different species of grass are known to flower and emit pollen at different times of the day and during different periods of the pollen season. Pollen concentrations are also influenced by meteorological factors – directly through those parameters that govern pollen dispersion and transport, and indirectly through the weather-driven flowering process. We found that three different profiles dominated the grass pollen season in Aarhus – a twin peak profile during the early season, a single evening profile during the middle of the season, and a single midday peak during the late season. Whilst this variation could not be explained by meteorological factors, no inconsistencies were found with the theory that it was driven by a succession of different grass species with different diurnal flowering patterns dominating atmospheric pollen loads as the season progressed. The potential for exposure was found to be significantly greater during the late-season period than during either the early- or mid-season periods.

Application of WRF-Chem to Forecasting PM10 Concentration over Poland

The meteorological and chemical transport model WRF-Chem was implemented to forecast PM10 concentrations over Poland. WRF-Chem version 3.5 was configured with three one way nested domains using the GFS meteorological data and the TNO MACC II emissions. Forecasts, with 48h lead time, were run for a winter and summer period 2014. WRF-Chem in general captures the variability in observed PM10 concentrations, but underestimates some peak concentrations during winter-time. The peaks coincide with either stable atmospheric condition during nighttime in the lower part of the planetary boundary layer or on days with very low surface temperatures. Such episodes lead to increased combustion in residential heating, where hard coal is the main fuel in Poland. This suggests that a key to improvement in the model performance for the peak concentrations is to focus on the simulation of PBL processes and the distribution of emissions with high resolution in WRF-Chem.

Forecasting Methodologies for Ganoderma Spore Concentration Using Combined Statistical Approaches and Model Evaluations

High concentration levels of Ganoderma spp. spores were observed in Worcester, UK, during 2006–2010.These basidiospores are known to cause sensitization due to the allergen content and their small dimensions. This enables them to penetrate the lower part of the respiratory tract in humans. Establishment of a link between occurring symptoms of sensitization to Ganoderma spp. and other basidiospores is challenging due to lack of information regarding spore concentration in the air. Hence, aerobiological monitoring should be conducted, and if possible extended with the construction of forecast models. Daily mean concentration of allergenic Ganoderma spp. spores in the atmosphere of Worcester was measured using 7-day volumetric spore sampler through five consecutive years. The relationships between the presence of spores in the air and the weather parameters were examined. Forecast models were constructed for Ganoderma spp. spores using advanced statistical techniques, i.e. multivariate regression trees and artificial neural networks. Dew point temperature along with maximumtemperature was the most important factor influencing the presence of spores in the air of Worcester. Based on these two major factors and several others of lesser importance, thresholds for certain levels of fungal spore concentration, i.e. low (0–49 s m−3), moderate(50–99 s m−3), high (100–149 s m−3) and very high (150