Alternaria Spores in the Air Across Europe: Abundance, Seasonality and Relationships with Climate, Meteorology and Local Environment

We explored the temporal and spatial variations in airborne Alternaria spore quantitative and phenological features in Europe using 23 sites with annual time series between 3 and 15 years. The study covers seven countries and four of the main biogeographical regions in Europe. The observations were obtained with Hirst-type spore traps providing time series with daily records. Site locations extend from Spain in the south to Denmark in the north and from England in the West to Poland in the East. The study is therefore the largest assessment ever carried out for Europe concerning Alternaria. Aerobiological data were investigated for temporal and spatial patterns in their start and peak season dates and their spore indices. Moreover, the effects of climate were checked using meteorological data for the same period, using a crop growth model. We found that local climate, vegetation patterns and management of landscape are governing parameters for the overall spore concentration, while the annual variations caused by weather are of secondary importance but should not be neglected. The start of the Alternaria spore season varies by several months in Europe, but the peak of the season is more synchronised in central northern Europe in the middle of the summer, while many southern sites have peak dates either earlier or later than northern Europe. The use of a crop growth model to explain the start and peak of season suggests that such methods could be useful to describe Alternaria seasonality in areas with no available observations

Changes to Airborne Pollen Counts across Europe

A progressive global increase in the burden of allergic diseases has affected the industrialized world over the last half century and has been reported in the literature. The clinical evidence reveals a general increase in both incidence and prevalence of respiratory diseases, such as allergic rhinitis (common hay fever) and asthma. Such phenomena may be related not only to air pollution and changes in lifestyle, but also to an actual increase in airborne quantities of allergenic pollen. Experimental enhancements of carbon dioxide (CO2) have demonstrated changes in pollen amount and allergenicity, but this has rarely been shown in the wider environment. The present analysis of a continental-scale pollen data set reveals an increasing trend in the yearly amount of airborne pollen for many taxa in Europe, which is more pronounced in urban than semi-rural/rural areas. Climate change may contribute to these changes, however increased temperatures do not appear to be a major influencing factor. Instead, we suggest the anthropogenic rise of atmospheric CO2 levels may be influentia

Perceptions of change in the environment caused by the COVID-19 pandemic: implications for environmental policy

COVID-19 lockdown measures have impacted the environment with both positive and negative effects. However, how human populations have perceived such changes in the natural environment and how they may have changed their daily habits have not been yet thoroughly evaluated. The objectives of this work were to investigate (1) the social perception of the environmental changes produced by the COVID-19 pandemic lockdown and the derived change in habits in relation to i) waste management, energy saving, and sustainable consumption, ii) mobility, iii) social inequalities, iv) generation of noise, v) utilization of natural spaces, and, vi) human population perception towards the future, and (2) the associations of these potential new habits with various socio-demographic variables. First, a SWOT analysis identified strengths (S), weaknesses (W), opportunities (O), and threats (T) generated by the pandemic lockdown measures. Second, a survey based on the aspects of the SWOT was administered among 2370 adults from 37 countries during the period from February to September 2021. We found that the short-term positive impacts on the natural environment were generally well recognized. In contrast, longer-term negative effects arise, but they were often not reported by the survey participants, such as greater production of plastic waste derived from health safety measures, and the increase in e-commerce use, which can displace small storefront businesses. We were able to capture a mismatch between perceptions and the reported data related to visits to natural areas, and generation of waste. We found that age and country of residence were major contributors in shaping the survey participants ´answers, which highlights the importance of government management strategies to address current and future environmental problems. Enhanced positive perceptions of the environment and ecosystems, combined with the understanding that livelihood sustainability, needs to be prioritized and would reinforce environmental protection policies to create greener cities. Moreover, new sustainable jobs in combination with more sustainable human habits represent an opportunity to reinforce environmental policy

Building an Automatic Pollen Monitoring Network (ePIN): Selection of Optimal Sites by Clustering Pollen Stations

Airborne pollen is a recognized biological indicator and its monitoring has multiple uses such as providing a tool for allergy diagnosis and prevention. There is a knowledge gap related to the distribution of pollen traps needed to achieve representative biomonitoring in a region. The aim of this manuscript is to suggest a method for setting up a pollen network (monitoring method, monitoring conditions, number and location of samplers etc.). As a case study, we describe the distribution of pollen across Bavaria and the design of the Bavarian pollen monitoring network (ePIN), the first operational automatic pollen network worldwide. We established and ran a dense pollen monitoring network of 27 manual Hirst-type pollen traps across Bavaria, Germany, during 2015. Hierarchical cluster analysis of the data was then performed to select the locations for the sites of the final pollen monitoring network. According to our method, Bavaria can be clustered into three large pollen regions with eight zones. Within each zone, pollen diversity and distribution among different locations does not vary significantly. Based on the pollen zones, we opted to place one automatic monitoring station per zone resulting in the ePIN network, serving 13 million inhabitants. The described method defines stations representative for a homogeneous aeropalynologically region, which reduces redundancy within the network and subsequent costs (in the study case from 27 to 8 locations). Following this method, resources in pollen monitoring networks can be optimized and allergic citizens can then be informed in a timely and effective way, even in larger geographical areas

Airborne Alternaria and Cladosporium Fungal Spores in Europe: Forecasting Possibilities and Relationships with Meteorological Parameters

Airborne fungal spores are prevalent components of bioaerosols with a large impact on ecology, economy and health. Their major socioeconomic effects could be reduced by accurate and timely prediction of airborne spore concentrations. The main aim of this study was to create and evaluate models of Alternaria and Cladosporium spore concentrations based on data on a continental scale. Additional goals included assessment of the level of generalization of the models in space and description of the main meteorological factors influencing fungal spore concentrations. Aerobiological monitoring was carried out at 18 sites in six countries across Europe over 3 to 21 years depending on site. Quantile random forest modelling was used to predict spore concentrations values. Generalization of the Alternaria and Cladosporium models was tested using (i) one model for all the sites, (ii) models for groups of sites, and (iii) models for individual sites. The study revealed the possibility of reliable prediction of fungal spore levels using gridded meteorological data. The classification models also showed the capacity for providing larger scale predictions of fungal spore concentrations. Regression models were distinctly less accurate than classification models due to several factors, including measurement errors and distinct day-to-day changes of concentrations. Temperature and vapour pressure proved to be the most important variables in the regression and classification models of Alternaria and Cladosporium spore concentrations. Accurate and operational daily-scale predictive models of bioaerosol abundances contribute to the assessment and evaluation of relevant exposure and consequently more timely and efficient management of phytopathogenic and of human allergic diseases

Airborne Alternaria and Cladosporium Fungal Spores in Europe: Forecasting Possibilities and Relationships with Meteorological Parameters

Airborne fungal spores are prevalent components of bioaerosols with a large impact on ecology, economy and health. Their major socioeconomic effects could be reduced by accurate and timely prediction of airborne spore concentrations. The main aim of this study was to create and evaluate models of Alternaria and Cladosporium spore concentrations based on data on a continental scale. Additional goals included assessment of the level of generalization of the models in space and description of the main meteorological factors influencing fungal spore concentrations. Aerobiological monitoring was carried out at 18 sites in six countries across Europe over 3 to 21 years depending on site. Quantile random forest modelling was used to predict spore concentrations values. Generalization of the Alternaria and Cladosporium models was tested using (i) one model for all the sites, (ii) models for groups of sites, and (iii) models for individual sites. The study revealed the possibility of reliable prediction of fungal spore levels using gridded meteorological data. The classification models also showed the capacity for providing larger scale predictions of fungal spore concentrations. Regression models were distinctly less accurate than classification models due to several factors, including measurement errors and distinct day-to-day changes of concentrations. Temperature and vapour pressure proved to be the most important variables in the regression and classification models of Alternaria and Cladosporium spore concentrations. Accurate and operational daily-scale predictive models of bioaerosol abundances contribute to the assessment and evaluation of relevant exposure and consequently more timely and efficient management of phytopathogenic and of human allergic diseases

Higher airborne pollen concentrations correlated with increased SARS-CoV-2 infection rates, as evidenced from 31 countries across the globe

Pollen exposure weakens the immunity against certain seasonal respiratory viruses by diminishing the antiviral interferon response. Here we investigate whether the same applies to the pandemic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is sensitive to antiviral interferons, if infection waves coincide with high airborne pollen concentrations. Our original hypothesis was that more airborne pollen would lead to increases in infection rates. To examine this, we performed a cross-sectional and longitudinal data analysis on SARS-CoV-2 infection, airborne pollen, and meteorological factors. Our dataset is the most comprehensive, largest possible worldwide from 130 stations, across 31 countries and five continents. To explicitly investigate the effects of social contact, we additionally considered population density of each study area, as well as lockdown effects, in all possible combinations: without any lockdown, with mixed lockdown−no lockdown regime, and under complete lockdown. We found that airborne pollen, sometimes in synergy with humidity and temperature, explained, on average, 44% of the infection rate variability. Infection rates increased after higher pollen concentrations most frequently during the four previous days. Without lockdown, an increase of pollen abundance by 100 pollen/m3 resulted in a 4% average increase of infection rates. Lockdown halved infection rates under similar pollen concentrations. As there can be no preventive measures against airborne pollen exposure, we suggest wide dissemination of pollen−virus coexposure dire effect information to encourage high-risk individuals to wear particle filter masks during high springtime pollen concentrations

Temperature-related changes in airborne allergenic pollen abundance and seasonality across the northern hemisphere: a retrospective data analysis

Background: Ongoing climate change might, through rising temperatures, alter allergenic pollen biology across the northern hemisphere. We aimed to analyse trends in pollen seasonality and pollen load and to establish whether there are specific climate-related links to any observed changes.Methods: For this retrospective data analysis, we did an extensive search for global datasets with 20 years or more of airborne pollen data that consistently recorded pollen season indices (eg, duration and intensity). 17 locations across three continents with long-term (approximately 26 years on average) quantitative records of seasonal concentrations of multiple pollen (aeroallergen) taxa met the selection criteria. These datasets were analysed in the context of recent annual changes in maximum temperature (Tmax) and minimum temperature (Tmin) associated with anthropogenic climate change. Seasonal regressions (slopes) of variation in pollen load and pollen season duration over time were compared to Tmax, cumulative degree day Tmax, Tmin, cumulative degree day Tmin, and frost-free days among all 17 locations to ascertain significant correlations.Findings: 12 (71%) of the 17 locations showed significant increases in seasonal cumulative pollen or annual pollen load. Similarly, 11 (65%) of the 17 locations showed a significant increase in pollen season duration over time, increasing, on average, 0·9 days per year. Across the northern hemisphere locations analysed, annual cumulative increases in Tmax over time were significantly associated with percentage increases in seasonal pollen load (r=0·52, p=0·034) as were annual cumulative increases in Tmin (r=0·61, p=0·010). Similar results were observed for pollen season duration, but only for cumulative degree days (higher than the freezing point [0°C or 32°F]) for Tmax (r=0·53, p=0·030) and Tmin (r=0·48, p=0·05). Additionally, temporal increases in frost-free days per year were significantly correlated with increases in both pollen load (r=0·62, p=0·008) and pollen season duration (r=0·68, p=0·003) when averaged for all 17 locations.Interpretation: Our findings reveal that the ongoing increase in temperature extremes (Tmin and Tmax) might already be contributing to extended seasonal duration and increased pollen load for multiple aeroallergenic pollen taxa in diverse locations across the northern hemisphere. This study, done across multiple continents, highlights an important link between ongoing global warming and public health—one that could be exacerbated as temperatures continue to increase.</p

A numerical model of birch pollen emission and dispersion in the atmosphere. Description of the emission module

A birch pollen emission model is described and its main features are discussed. The development of the model is based on a double-threshold temperature sum model that describes the propagation of the flowering season and naturally links to the thermal time models to predict the onset and duration of flowering. For the flowering season, the emission model considers ambient humidity and precipitation rate, both of which suppress the pollen release, as well as wind speed and turbulence intensity, which promote it. These dependencies are qualitatively evaluated using the aerobiological observations. Reflecting the probabilistic character of the flowering of an individual tree in a population, the model introduces relaxation functions at the start and end of the season. The physical basis of the suggested birch pollen emission model is compared with another comprehensive emission module reported in literature. The emission model has been implemented in the SILAM dispersion modelling system, the results of which are evaluated in a companion paper