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.

Environmental drivers of the seasonal exposure to airborne Alternaria spores in Spain.

Alternaria conidia have high allergenic potential and they can trigger important respiratory diseases. Due to that and to their extensive detection period, airborne Alternaria spores are considered as a relevant airborne allergenic particle. Several studies have been developed in order to predict the human exposure to this aeroallergen and to prevent their negative effects on sensitive population. These studies revealed that some sampling locations usually have just one single Alternaria spore season while other locations generally have two seasons within the same year. However, the reasons of these two different seasonal patterns remain unclear. To understand them better, the present study was carried out in order to determine if there are any weather conditions that influence these different behaviours at different sampling locations. With this purpose, the airborne Alternaria spore concentrations of 18 sampling locations in a wide range of latitudinal, altitudinal and climate ranges of Spain were studied. The aerobiological samples were obtained by means of Hirst-Type volumetric pollen traps, and the seasonality of the airborne Alternaria spores were analysed. The optimal weather conditions for spore production were studied, and the main weather factor affecting Alternaria spore seasonality were analysed by means of random forests and regression trees. The results showed that the temperature was the most relevant variable for the Alternaria spore dispersion and it influenced both the spore integrals and their seasonality. The water availability was also a very significant variable. Warmer sampling locations generally have a longer period of Alternaria spore detection. However, the spore production declines during the summer when the temperatures are extremely warm, what splits the favourable period for Alternaria spore production and dispersion into two separate ones, detected as two Alternaria spore seasons within the same year.

Causes of increased pollen exposure during Saharan-Sahel dust intrusions.

Airborne particulate matter such as mineral dust comes mainly from natural sources, and the African regions of Sahara and Sahel originate large amounts of the aerosols dispersed worldwide. There is little knowledge about the influence of dust episodes on airborne pollen concentrations, and although the centre and southeast of the Iberian Peninsula are frequently affected by dust intrusions, until now, no specific works have analysed the effect of these episodes on airborne pollen concentrations in these areas. The aims of this study were to analyse the simultaneous occurrence of airborne pollen peaks and Saharan-Sahel dust intrusions in the central and south-eastern Iberian Peninsula, and to study the weather conditions - air mass pathways and conditions of air temperature, relative humidity and atmospheric pressure - that influence the airborne pollen concentrations during dust episodes. The results showed that the rise in airborne pollen concentrations during dust episodes is apparent in inland Iberian areas, although not in coastal areas in the southeast where pollen concentrations are even observed to decrease, coinciding with prevailing easterly winds from the sea. Total pollen concentrations and specific pollen types such as Olea, Poaceae and Quercus showed an increase in the central Iberian Peninsula during dust episodes when two meteorological phenomena concur: 1) prevailing winds from extensive areas of major wind-pollinated pollen sources over a medium or short distance (mainly from western and southwestern areas); and 2) optimal meteorological conditions that favour pollen release and dispersal into the atmosphere (mainly high temperatures and subsequently low humidity in central areas). Both conditions often occur during the Saharan-Sahel dust intrusions in the centre. Maximum pollen peaks are therefore most likely to occur during dust episodes in the central Iberian Peninsula, thus dramatically increasing the risk of outbreaks of pollinosis and other respiratory diseases in the population.

Standardised index for measuring atmospheric grass-pollen emission.

Grass pollen is the main cause of pollen allergy in Europe, and-given its marked allergenic potential and elevated airborne concentrations-constitutes a major public health risk. This study sought to identify the grass species triggering allergies during the highest-risk periods, and to measure the contribution of each species to airborne grass pollen concentrations. This type of research is particularly useful with a view to optimising the prevention and diagnosis of pollen allergies and developing the most effective immunological treatments. To that end, a total of 28 species potentially responsible for allergies were analysed. In order to assess the potential contribution of these species to overall airborne pollen concentrations, an index was designed (Pollen Contribution Index) based on the following parameters for each species: flowering phenology, pollen grain size (polar and equatorial axes), abundance of the species in the area and pollen production. The species contributing most to airborne pollen concentrations were, in order: Dactylis glomerata subsp. hispanica, Lolium rigidum, Trisetum paniceum and Arrhenatherum album. These species all shared certain features: small grain size (and thus greater buoyancy in air), high pollen production and considerable abundance. This Index was applied to a case study in a Mediterranean-climate area of the central Iberian Peninsula, but could equally be applied to other areas and other allergenic pollens. Findings showed that a small number of species were responsible for most airborne grass pollen.

Modeling pollen time series using seasonal-trend decomposition procedure based on LOESS smoothing.

Analysis of airborne pollen concentrations provides valuable information on plant phenology and is thus a useful tool in agriculture-for predicting harvests in crops such as the olive and for deciding when to apply phytosanitary treatments-as well as in medicine and the environmental sciences. Variations in airborne pollen concentrations, moreover, are indicators of changing plant life cycles. By modeling pollen time series, we can not only identify the variables influencing pollen levels but also predict future pollen concentrations. In this study, airborne pollen time series were modeled using a seasonal-trend decomposition procedure based on LOcally wEighted Scatterplot Smoothing (LOESS) smoothing (STL). The data series-daily Poaceae pollen concentrations over the period 2006-2014-was broken up into seasonal and residual (stochastic) components. The seasonal component was compared with data on Poaceae flowering phenology obtained by field sampling. Residuals were fitted to a model generated from daily temperature and rainfall values, and daily pollen concentrations, using partial least squares regression (PLSR). This method was then applied to predict daily pollen concentrations for 2014 (independent validation data) using results for the seasonal component of the time series and estimates of the residual component for the period 2006-2013. Correlation between predicted and observed values was r = 0.79 (correlation coefficient) for the pre-peak period (i.e., the period prior to the peak pollen concentration) and r = 0.63 for the post-peak period. Separate analysis of each of the components of the pollen data series enables the sources of variability to be identified more accurately than by analysis of the original non-decomposed data series, and for this reason, this procedure has proved to be a suitable technique for analyzing the main environmental factors influencing airborne pollen concentrations.