RESUMEN
This study aims to investigate the meteorological variables determining Cupressaceae pollen grain disruption in the environment. A parallel sampling of pollen grains and disrupted Cupressaceae pollen grains was performed in six cities using two Spanish aerobiological networks. The pollen concentrations, disrupted pollen concentrations, percentage of disrupted pollen and number of days when the percentage of disrupted pollen was above or equal to 50â¯% were quantified during two pollen seasons. The concentrations were determined following the standardised method EN 16868. Results show that the concentrations of pollen grains and disrupted pollen grains were not determined by geographical features and rarely by bioclimatic variables or indexes but by the ornamental use of the specimens in the vicinity of the pollen sampler, highlighting the possibility of using management practices to reduce exposure to allergens in the cities. African dust outbreaks coincided with higher concentrations of pollen grains and disrupted pollen grains, but the reduced percentage of disrupted pollen grains pointed to a non-causal relationship with long-distance transport. The effect of wind and maximum gusts remained negligible. The triggering factor for pollen disruption was the amount of water in the atmosphere, mainly reported as relative humidity. Rainfall increased the effect of disruption due to pollen grain swelling caused by its wash-out effect. The higher the relative humidity, the higher the disrupted pollen concentrations. This aligns with the mechanism of Cupressaceae reproduction since the family needs a water medium in the form of pollination droplets for the pollination tube to develop and the pollen grain to perform its biological function. Therefore, people that develop allergic symptoms to Cupresaceae pollen should avoid exposure during days with high relative humidity in the main pollen season.
RESUMEN
Missing data is a common problem in scientific research. The availability of extensive environmental time series is usually laborious and difficult, and sometimes unexpected failures are not detected until samples are processed. Consequently, environmental databases frequently have some gaps with missing data in it. Applying an interpolation method before starting the data analysis can be a good solution in order to complete this missing information. Nevertheless, there are several different approaches whose accuracy should be considered and compared. In this study, data from 6 aerobiological sampling stations were used as an example of environmental data series to assess the accuracy of different interpolation methods. For that, observed daily pollen/spore concentration data series were randomly removed, interpolated by using different methods and then, compared with the observed data to measure the errors produced. Different periods, gap sizes, interpolation methods and bioaerosols were considered in order to check their influence in the interpolation accuracy. The moving mean interpolation method obtained the highest success rate as average. By using this method, a success rate of the 70% was obtained when the risk classes used in the alert systems of the pollen information platforms were taken into account. In general, errors were mostly greater when there were high oscillations in the concentrations of biotic particles during consecutive days. That is the reason why the pre-peak and peak periods showed the highest interpolation errors. The errors were also higher when gaps longer than 5 days were considered. So, for completing long periods of missing data, it would be advisable to test other methodological approaches. A new Variation Index based on the behaviour of the pollen/spore season (measurement of the variability of the concentrations every 2 consecutive days) was elaborated, which allows to estimate the potential error before the interpolation is applied.