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Atmospheric pollutants and their association with olive and grass aeroallergen concentrations in Córdoba (Spain).

Maria Del Pilar PlazaPurificación AlcázarJosé OterosCarmen Galán
Published in: Environmental science and pollution research international (2020)
Cumulative data indicate that pollen grains and air pollution reciprocally interact. Climate changes seem also to influence pollen allergenicity. Depending on the plant species and on the pollutant type and concentration, this interaction may modify the features and metabolism of the pollen grain. Previous results revealed a significant positive correlation between pollen and aeroallergen, even using two different samplers. However, some discrepancy days have been also detected with low pollen but high aeroallergen concentrations. The main aim of the present paper is to find how the environmental factors, and specially pollutants, could affect the amount of allergens from olive and grass airborne pollen. Pollen grains were collected by a Hirst-type volumetric spore trap. Aeroallergen was simultaneously sampled by a low-volume Cyclone Burkard sampler. Phl p 5 and Ole e 1 aeroallergen were quantified by double-sandwich ELISA test. The data related to air pollutants, pollen grains, and aeroallergens were analyzed with descriptive statistic. Spearman's correlation test was used to identify potential correlations between these variables. There is a significant positive correlation between aeroallergens and airborne pollen concentrations, in both studied pollen types, so allergen concentrations could be explained with the pollen concentration. The days with unlinked events coincide between olive and grass allergens. Nevertheless, concerning to our results, pollutants do not affect the amount of allergens per pollen. Even if diverse pollutants show an unclear relationship with the allergen concentration, this association seems to be a casual effect of the leading role of some meteorological parameters.
Keyphrases
  • air pollution
  • particulate matter
  • chronic obstructive pulmonary disease
  • artificial intelligence
  • cross sectional
  • drug induced