Assessment of environmental risk areas based on airborne pollen patterns as a response to land use and land cover distribution.

Allergic respiratory diseases are considered to be among the most important public health concerns, and pollen is the main cause of allergic respiratory diseases worldwide. However, the biological component of air quality is largely underestimated, and there is an important gap in the legislation in this area. The aims of this study were to characterise the occurrence and incidence of pollen exposure in relation to potential pollen sources and to delineate the main areas of aerobiological risk in the Madrid Autonomous Region based on homogeneous patterns of pollen exposure. This study uses the historical aerobiological database of the Madrid Region Palynological Network (central Spain) from ten pollen stations from 1994 to 2022, and the land-use information from the Corine Land Cover. Multiple clustering approaches were followed to group the sampling stations and subsequently all the 1 × 1km pixels for the Madrid Autonomous Region. The clustering dendrogram for land-use distribution was compared to the dendrogram for historical airborne pollen data. The two dendrograms showed a good alignment with a very high correlation (0.95) and very low entanglement (0.15), which indicates a close correspondence between the distribution of the potential pollen sources and the airborne pollen dynamics. Based on this knowledge, the Madrid Autonomous Region was divided into six aerobiological risk areas following a clear anthropogenic gradient in terms of the potential pollen sources that determine pollen exposure in the Madrid Region. Spatial regionalisation is a common practice in environmental risk assessment to improve the application of management plans and optimise the air quality monitoring networks. The risk areas proposed by scientific criteria in the Madrid Autonomous Region can be adjusted to other operational criteria following a framework equivalent to other air quality networks.

Characterisation of the airborne pollen spectrum in Guadalajara (central Spain) and estimation of the potential allergy risk.

Aerobiological research into airborne pollen diversity and seasonal variations in pollen counts has become increasingly important over recent decades due to the growing incidence of asthma, rhinitis and other pollen-related allergic conditions. Airborne pollen in Guadalajara (Castilla-La Mancha, Spain) was studied over a 6-year period (2008-2013) using a Hirst-type volumetric spore trap. The highest pollen concentrations were recorded from February to June, coinciding with the pollen season of the pollen types that most contribute to the local airborne pollen spectrum: Cupressaceae (32.2%), Quercus (15.1%), Platanus (13.2%), Olea (8.3%), Populus (7.8%) and Poaceae (7.2%). These are therefore critical months for allergy sufferers. The pollen calendar was typically Mediterranean and comprised 25 pollen types. Between January and March, Cupressaceae pollen concentrations exceeded allergy risk thresholds on 38 days. Other woody species such as Olea and Platanus have a shorter pollen season, and airborne concentrations exceeded allergy risk thresholds on around 13 days in each case. Poaceae pollen concentrations attained allergy risk levels on 26 days between May and July. Other highly allergenic pollen types included Urticaceae and Chenopodiaceae-Amaranthaceae, though these are less abundant than other pollen types in Guadalajara and did not exceed risk thresholds on more than 3 and 5 days, respectively.

Models for forecasting airborne Cupressaceae pollen levels in central Spain.

The influence of meteorological variables on airborne Cupressaceae pollen levels in central Spain was analyzed, and prediction models based on polynomial and multiple regressions were used to predict pollen counts throughout the pollen season. The Cupressaceae pollen type was selected in view of both its abundance in the atmosphere of the central Iberian Peninsula (particularly from January to March) and its allergenic importance. Sampling was performed uninterruptedly over a 5-year period, using a Hirst volumetric sampler and the sampling method established by the Spanish Aerobiology Network. Temperature displayed the strongest (positive) correlation with Cupressaceae pollen counts. Polynomial and multiple regression analysis showed that maximum temperature was the most influential variable included in prediction models. The prediction equations obtained for the study period were reasonably satisfactory, accounting for 48% and 59% of the variation in airborne pollen levels.