Predicting the severity of the grass pollen season and the effect of climate change in Northwest Europe

Current and Future Effects of Climate Change on Airborne Allergens

PURPOSE OF REVIEW

Delineation of the impact of elevated carbon dioxide and concomitant global warming on airborne allergens is performed.

RECENT FINDINGS

European tree pollen trends in general showed earlier start and end dates and increased total pollen release, with some differences both in locale and among species. Earlier flowering was also seen with grasses and weeds. In the case of some boreal trees, flowering was delayed due to a pre-seasonal requirement for necessary accumulated chilling temperature to achieve bud-set. Anthropogenic climate change induced rise in temperature and CO2 levels has resulted in demonstrable increases in aeroallergens. This has been most dramatic in tree pollen annual load, but also seen with grasses and weeds. Collected data is greatest for the Northern Hemisphere, especially the European continent, with supporting data from North America and Australia.

Identifying the Risk Factors of Allergic Rhinitis Based on Zhihu Comment Data Using a Topic-Enhanced Word-Embedding Model: Mixed Method Study and Cluster Analysis

BACKGROUND

Allergic rhinitis (AR) is a chronic disease, and several risk factors predispose individuals to the condition in their daily lives, including exposure to allergens and inhalation irritants. Analyzing the potential risk factors that can trigger AR can provide reference material for individuals to use to reduce its occurrence in their daily lives. Nowadays, social media is a part of daily life, with an increasing number of people using at least 1 platform regularly. Social media enables users to share experiences among large groups of people who share the same interests and experience the same afflictions. Notably, these channels promote the ability to share health information.

OBJECTIVE

This study aims to construct an intelligent method (TopicS-ClusterREV) for identifying the risk factors of AR based on these social media comments. The main questions were as follows: How many comments contained AR risk factor information? How many categories can these risk factors be summarized into? How do these risk factors trigger AR?

METHODS

This study crawled all the data from May 2012 to May 2022 under the topic of allergic rhinitis on Zhihu, obtaining a total of 9628 posts and 33,747 comments. We improved the Skip-gram model to train topic-enhanced word vector representations (TopicS) and then vectorized annotated text items for training the risk factor classifier. Furthermore, cluster analysis enabled a closer look into the opinions expressed in the category, namely gaining insight into how risk factors trigger AR.

RESULTS

Our classifier identified more comments containing risk factors than the other classification models, with an accuracy rate of 96.1% and a recall rate of 96.3%. In general, we clustered texts containing risk factors into 28 categories, with season, region, and mites being the most common risk factors. We gained insight into the risk factors expressed in each category; for example, seasonal changes and increased temperature differences between day and night can disrupt the body's immune system and lead to the development of allergies.

CONCLUSIONS

Our approach can handle the amount of data and extract risk factors effectively. Moreover, the summary of risk factors can serve as a reference for individuals to reduce AR in their daily lives. The experimental data also provide a potential pathway that triggers AR. This finding can guide the development of management plans and interventions for AR.

Association between ambient temperature and common allergenic pollen and fungal spores: A 52-year analysis in central England, United Kingdom

Exposure to pollen and fungal spores can trigger asthma/allergic symptoms and affect health. Rising temperatures from climate change have been associated with earlier seasons and increasing intensity for some pollen, with weaker evidence for fungal spores. It is unclear whether climate change has resulted in changes in the exposure-response function between temperature and pollen/fungal spore concentrations over time. This study examined associations between temperature and pollen/fungal spores in different time periods and assessed potential adaptation using the longest pollen/fungal spore dataset in existence (52 years). Daily concentrations of pollen (birch and grass) and fungal spores (Cladosporium, Alternaria, Sporobolomyces and Tilletiopsis) collected between April and October from Derby (1970-2005) and Leicester (2006-2021), UK, were analysed. Cumulative seasonal concentrations (seasonal integral) and start-of-season were calculated and linked to seasonal mean temperatures (Tmeans) using generalized additive models. Daily concentrations were evaluated against daily Tmean with distributed lagged nonlinear models. Models were adjusted for precipitation, relative humidity, long-term trend and location. Seasonal and daily analyses were respectively stratified into two periods (1970-1995, 1997-2021) and five decades. Warmer seasonal Tmeans were associated with higher seasonal integral for birch, Cladosporium and Alternaria, as well as earlier start-of-season for birch, grass and Cladosporium. There were indications of changing associations with temperature in the recent decades. A warmer January was associated with higher seasonal integral for grass in 1997-2021, but not in 1970-1995. In 2000-2021, daily concentrations of birch pollen tended to remain at higher levels, vs. decrease during 1990s, when Tmean was between 13 and 15 °C. Our study suggests higher temperatures experienced in recent decades are associated with higher overall abundance of some pollen/fungal spores, which may increase future disease burdens of allergies. The changing responses of some pollen to higher temperatures over time may indicate adaptation to increasing temperatures and should be considered in climate change mitigation and adaptation planning.

Prediction Model for Annual Variation in Total Pollen by Allergenic Trees in Korean Cities

PURPOSE

Pollen forecasting systems can provide information for coping with respiratory allergies. They estimate daily pollen production, dispersal, deposition, and removal based on daily weather conditions to predict daily pollen concentrations and provide allergy warnings. As of 2023, the Korea Meteorological Administration (KMA) provides 2-day forecast of allergenic pollens. However, unlike these models, long-term analysis of annual observations of tree pollen reveal annual variations. Therefore, in this study, we aimed to develop annual prediction models for allergenic tree pollens based on long-term multi-site pollen and meteorological data.

METHODS

Daily pollen concentrations were observed using Hirst-type volumetric spore traps at nine sites in Korea from 1998 to 2021, and daily weather data from the closest KMA stations were utilized. Models were developed to predict the seasonal pollen integral of seven tree species based on monthly mean temperature, wind speed, and total precipitation using three variable selection methods: 1) the t-test based key variable screening followed by linear regression with stepwise procedure (TM), 2) direct linear regression with stepwise procedure from the full variable model (FM), and 3) LASSO regression from the full variable model (LM).

RESULTS

Data obtained during 1998-2017 and 2018=2021 were utilized for model development and validation, respectively. The root mean squared error, mean absolute error, mean error, and coefficient of determination (R²) revealed that the TM models were best suited for actual forecasting, even though R² in the TM model was lower than those of the FM and LM models.

CONCLUSIONS

The annual variation model in this study can be integrated with the daily pollen forecast model by controlling the annual pollen potential, and the accuracy of the daily forecast can be improved accordingly.

Co-exposure to highly allergenic airborne pollen and fungal spores in Europe

The study is aimed at determining the potential spatiotemporal risk of the co-occurrence of airborne pollen and fungal spores high concentrations in different bio-climatic zones in Europe. Birch, grass, mugwort, ragweed, olive pollen and Alternaria and Cladosporium fungal spores were investigated at 16 sites in Europe, in 2005-2019. In Central and northern Europe, pollen and fungal spore seasons mainly overlap in June and July, while in South Europe, the highest pollen concentrations occur frequently outside of the spore seasons. In the coldest climate, no allergy thresholds were exceeded simultaneously by two spore or pollen taxa, while in the warmest climate most of the days with at least two pollen taxa exceeding threshold values were observed. The annual air temperature amplitude seems to be the main bioclimatic factor influencing the accumulation of days in which Alternaria and Cladosporium spores simultaneously exceed allergy thresholds. The phenomenon of co-occurrence of airborne allergen concentrations gets increasingly common in Europe and is proposed to be present on other continents, especially in temperate climate.

Plants, pollinators and their interactions under global ecological change: The role of pollen DNA metabarcoding

Anthropogenic activities are triggering global changes in the environment, causing entire communities of plants, pollinators and their interactions to restructure, and ultimately leading to species declines. To understand the mechanisms behind community shifts and declines, as well as monitoring and managing impacts, a global effort must be made to characterize plant-pollinator communities in detail, across different habitat types, latitudes, elevations, and levels and types of disturbances. Generating data of this scale will only be feasible with rapid, high-throughput methods. Pollen DNA metabarcoding provides advantages in throughput, efficiency and taxonomic resolution over traditional methods, such as microscopic pollen identification and visual observation of plant-pollinator interactions. This makes it ideal for understanding complex ecological networks and their responses to change. Pollen DNA metabarcoding is currently being applied to assess plant-pollinator interactions, survey ecosystem change and model the spatiotemporal distribution of allergenic pollen. Where samples are available from past collections, pollen DNA metabarcoding has been used to compare contemporary and past ecosystems. New avenues of research are possible with the expansion of pollen DNA metabarcoding to intraspecific identification, analysis of DNA in ancient pollen samples, and increased use of museum and herbarium specimens. Ongoing developments in sequencing technologies can accelerate progress towards these goals. Global ecological change is happening rapidly, and we anticipate that high-throughput methods such as pollen DNA metabarcoding are critical for understanding the evolutionary and ecological processes that support biodiversity, and predicting and responding to the impacts of change.

Microscale pollen release and dispersal patterns in flowering grass populations

Characterizing pollen release and dispersion processes is fundamental for knowledge advancement in ecological, agricultural and public health disciplines. Understanding pollen dispersion from grass communities is especially relevant due to their high species-specific allergenicity and heterogeneously distributed source areas. Here, we aimed to address questions concerning fine level heterogeneity in grass pollen release and dispersion processes, with a focus on characterizing the taxonomic composition of airborne grass pollen over the grass flowering season using eDNA and molecular ecology methods. High resolution grass pollen concentrations were compared between three microscale sites (<300 m apart) in a rural area in Worcestershire, UK. The grass pollen was modelled with local meteorology in a MANOVA (Multivariate ANOVA) approach to investigate factors relevant to pollen release and dispersion. Simultaneously, airborne pollen was sequenced using Illumina MySeq for metabarcoding, analysed against a reference database with all UK grasses using the R packages DADA2 and phyloseq to calculate Shannon's Diversity Index (α-diversity). The flowering phenology of a local Festuca rubra population was observed. We found that grass pollen concentrations varied on a microscale level, likely attributed to local topography and the dispersion distance of pollen from flowering grasses in local source areas. Six genera (Agrostis, Alopecurus, Arrhenatherum, Holcus, Lolium and Poa) dominated the pollen season, comprising on average 77 % of the relative abundance of grass species reads. Temperature, solar radiation, relative humidity, turbulence and wind speeds were found to be relevant for grass pollen release and dispersion processes. An isolated flowering Festuca rubra population contributed almost 40 % of the relative pollen abundance adjacent to the nearby sampler, but only contributed 1 % to samplers situated 300 m away. This suggests that most emitted grass pollen has limited dispersion distance and our results show substantial variation in airborne grass species composition over short geographical scales.

Isolating the species element in grass pollen allergy: A review

Grass pollen is a leading cause of allergy in many countries, particularly Europe. Although many elements of grass pollen production and dispersal are quite well researched, gaps still remain around the grass species that are predominant in the air and which of those are most likely to trigger allergy. In this comprehensive review we isolate the species aspect in grass pollen allergy by exploring the interdisciplinary interdependencies between plant ecology, public health, aerobiology, reproductive phenology and molecular ecology. We further identify current research gaps and provide open ended questions and recommendations for future research in an effort to focus the research community to develop novel strategies to combat grass pollen allergy. We emphasise the role of separating temperate and subtropical grasses, identified through divergence in evolutionary history, climate adaptations and flowering times. However, allergen cross-reactivity and the degree of IgE connectivity in sufferers between the two groups remains an area of active research. The importance of future research to identify allergen homology through biomolecular similarity and the connection to species taxonomy and practical implications of this to allergenicity is further emphasised. We also discuss the relevance of eDNA and molecular ecological techniques (DNA metabarcoding, qPCR and ELISA) as important tools in quantifying the connection between the biosphere with the atmosphere. By gaining more understanding of the connection between species-specific atmospheric eDNA and flowering phenology we will further elucidate the importance of species in releasing grass pollen and allergens to the atmosphere and their individual role in grass pollen allergy.

Extraordinary microcarriers derived from spores and pollens

Spores and pollens refer to the reproductive cells of seed plants and asexually reproducing sporophytes, exhibiting a natural core-shell structure and exquisite surface morphology. They possess extraordinary dimensional homogeneity, porosity, amphiphilicity and adhesion. Their sporopollenin exine layer endows them with chemically stable, UV resistant, and biocompatible properties, which can also be facilely functionalized due to sufficient groups on the surface. The unique characteristics of spores and pollens have facilitated a wide range of applications in drug carriers, biological imaging, food science, microrobotics, environmental purification, flexible electronics, cell scaffolds, 3D printing materials and biological detection. This review showcases the common structural composition and physicochemical properties of spores and pollens, describes the extraction and processing methods, and summarizes the recent research on their applications in various fields. Following these sections, this review analyzes the existing challenges in spores and pollen research and provides a future outlook.

Simulation Palynologists for Pollinosis Prevention: A Progressive Learning of Pollen Localization and Classification for Whole Slide Images

Existing API approaches usually independently leverage detection or classification models to distinguish allergic pollens from Whole Slide Images (WSIs). However, palynologists tend to identify pollen grains in a progressive learning manner instead of the above one-stage straightforward way. They generally focus on two pivotal problems during pollen identification. (1) Localization: where are the pollen grains located? (2) Classification: which categories do these pollen grains belong to? To perfectly mimic the manual observation process of the palynologists, we propose a progressive method integrating pollen localization and classification to achieve allergic pollen identification from WSIs. Specifically, data preprocessing is first used to cut WSIs into specific patches and filter out blank background patches. Subsequently, we present the multi-scale detection model to locate coarse-grained pollen regions (targeting at "pollen localization problem") and the multi-classifiers combination to determine the fine-grained category of allergic pollens (targeting at "pollen classification problem"). Extensive experimental results have demonstrated the feasibility and effectiveness of our proposed method.

25-year retrospective longitudinal study on seasonal allergic rhinitis associations with air temperature in general practice

Due to climate change, air temperature in the Netherlands has gradually increased. Higher temperatures lead to longer pollen seasons. Possible relations between air temperature and increased impact of seasonal allergic rhinitis (SAR) in general practice have not been investigated yet. We explored trends in timing of frequent seasonal allergic rhinitis presentation to general practitioners (GPs) over 25 years and explored associations with air temperature. We performed a retrospective exploratory longitudinal study with data from our Family Medicine Network (1995-2019), including all SAR patients and their GP-encounters per week. We determined patients' GP-consultation frequency. Every year we identified seasonal periods with substantial increase in SAR related encounters: peak-periods. We determined start date and duration of the peak-period and assessed associations with air temperature in the beginning and throughout the year, respectively. The peak-period duration increased by a mean of 1.3 days (95% CI 0.23-2.45, P = 0.02) per year throughout the study period. Air temperature between February and July showed a statistically significant association with peak-period duration. We could not observe direct effects of warmer years on the start of peak-periods within distinct years (P = 0.06). SAR patients' contact frequency slightly increased by 0.01 contacts per year (95% CI 0.002-0.017, P = 0.015). These longitudinal findings may help to facilitate further research on the impact of climate change, and raise awareness of the tangible impact of climate change in general practice.

Evaluation of climate change adaptation measures for childhood asthma: A systematic review of epidemiological evidence

Global climate change (GCC) is widely accepted as the biggest threat to human health of the 21st century. Children are particularly vulnerable to GCC due to developing organ systems, psychological immaturity, nature of daily activities, and higher level of per-body-unit exposure. There is a rising trend in the disease burden of childhood asthma and allergies in many parts of the world. The associations of CC, air pollution and other environmental exposures with childhood asthma are attracting more research attention, but relatively few studies have focused on CC adaptation measures and childhood asthma. This study aimed to bridge this knowledge gap and conducted the first systematic review on CC adaptation measures and childhood asthma. We searched electronic databases including PubMed, Embase, and Web of Science using a set of MeSH terms and related synonyms, and identified 20 eligible studies included for review. We found that there were a number of adaptation measures proposed for childhood asthma in response to GCC, including vulnerability assessment, improving ventilation and heating, enhancing community education, and developing forecast models and early warning systems. Several randomized controlled trials show that improving ventilation and installing heating in the homes appear to be an effective way to relieve childhood asthma symptoms, especially in winter. However, the effectiveness of most adaptation measures, except for improving ventilation and heating, have not been explored and quantified. Given more extreme weather events (e.g., cold spells and heatwaves) may occur as climate change progresses, this finding may have important implications. Evidently, further research is urgently warranted to evaluate the impacts of CC adaptation measures on childhood asthma. These adaptation measures, if proven to be effective, should be integrated in childhood asthma control and prevention programs as GCC continues.

Analysis of the annual pollen integral in Albuquerque, New Mexico, shows a negative trend with temperatures for Juniper, Cottonwood, Elm, and Mulberry

The goal of this study is to determine if the annual pollen integral (APIn) for the top tree allergens in the City of Albuquerque is correlated with meteorological variables. This analysis would be the first of its kind for this area. We used 17 consecutive years from 2004 to 2020 and data collected by the city of Albuquerque using a Spore Trap (Burkard) volumetric air sampler in a location designed to represent a typical desert environment. The pollen studied include Juniper, Elm, Ash, Cottonwood, and Mulberry. We found a negative linear correlation with early summer temperatures of the previous year and APIn for Elm, Cottonwood, and Mulberry, and early fall temperatures for Juniper. Linear regression models developed for Elm, Cottonwood, and Mulberry used the monthly mean maximum temperature for the month of June of the prior year as the independent variable to yield a R squared statistic (R ²) of 0.88, 0.91 and 0.78, respectively. For Juniper, the average monthly mean minimum temperature for the previous September and October served as the independent variable and yielded the R ² value of 0.80. We also observed a positive trend for the annual maximum temperature over time and a negative trend for the total APIn. Summers in New Mexico are hot and dry, and they may be getting hotter and drier because of climate change. Our analysis predicts that climate change in this area may lead to reduced allergies if temperatures continue to increase and if precipitation patterns remain the same.

Phenotypic variation from waterlogging in multiple perennial ryegrass varieties under climate change conditions

Identifying how various components of climate change will influence ecosystems and vegetation subsistence will be fundamental to mitigate negative effects. Climate change-induced waterlogging is understudied in comparison to temperature and CO2. Grasslands are especially vulnerable through the connection with global food security, with perennial ryegrass dominating many flood-prone pasturelands in North-western Europe. We investigated the effect of long-term waterlogging on phenotypic responses of perennial ryegrass using four common varieties (one diploid and three tetraploid) grown in atmospherically controlled growth chambers during two months of peak growth. The climate treatments compare ambient climatological conditions in North-western Europe to the RCP8.5 climate change scenario in 2050 (+2°C and 550 ppm CO2). At the end of each month multiple phenotypic plant measurements were made, the plants were harvested and then allowed to grow back. Using image analysis and principal component analysis (PCA) methodologies, we assessed how multiple predictors (phenotypic, environmental, genotypic, and temporal) influenced overall plant performance, productivity and phenotypic responses. Long-term waterlogging was found to reduce leaf-color intensity, with younger plants having purple hues indicative of anthocyanins. Plant performance and yield was lower in waterlogged plants, with tetraploid varieties coping better than the diploid one. The climate change treatment was found to reduce color intensities further. Flooding was found to reduce plant productivity via reductions in color pigments and root proliferation. These effects will have negative consequences for global food security brought on by increased frequency of extreme weather events and flooding. Our imaging analysis approach to estimate effects of waterlogging can be incorporated into plant health diagnostics tools via remote sensing and drone-technology.

Pollen season trends as markers of climate change impact: Betula, Quercus and Poaceae

The incidences of respiratory allergies are at an all-time high. Pollen aeroallergens can reflect changing climate, with recent studies in Europe showing some, but not all, pollen types are increasing in severity, season duration and experiencing an earlier onset. This study aimed to identify pollen trends in the UK over the last twenty-six years for a range of pollen sites, with a focus on the key pollen types of Poaceae (grass), Betula (birch) and Quercus (oak) and to examine the relationship of these trends with meteorological factors. Betula pollen seasons show no significant trends for onset, first high day or duration but increasing pollen production in the Midlands region of the UK is being driven by warmer temperatures in the previous June and July. Quercus pollen seasons are starting earlier, due to increasing temperature and sunshine totals in April, but are not becoming more severe. The seasons are lasting longer, although no significant climate drivers for this were identified. The first high day of the Poaceae pollen season is occurring earlier in central UK regions due to an increasing trend for all temperature variables in the previous December, January, April, May and June. Severity and duration of the season show no significant trends and are spatially and temporally variable. Important changes are occurring in the UK pollen seasons that will impact on the health of respiratory allergy sufferers, with more severe Betula pollen seasons and longer Quercus pollen seasons. Most of the changes identified were caused by climate drivers of increasing temperature and sunshine total. However, Poaceae pollen seasons are neither becoming more severe nor longer. The reasons for this included a lack of change in some monthly meteorological variables, or land-use change, such as grassland being replaced by urban areas or woodland.

A Review of the Respiratory Health Burden Attributable to Short-Term Exposure to Pollen

Respiratory diseases such as asthma, allergic rhinitis (AR) and chronic obstructive pulmonary disease (COPD) affect millions worldwide and pose a significant global public health burden. Over the years, changes in land use and climate have increased pollen quantity, allergenicity and duration of the pollen season, thus increasing its impact on respiratory disease. Many studies have investigated the associations between short-term ambient pollen (i.e., within days or weeks of exposure) and respiratory outcomes. Here, we reviewed the current evidence on the association between short-term outdoor pollen exposure and thunderstorm asthma (TA), asthma and COPD hospital presentations, general practice (GP) consultations, self-reported respiratory symptoms, lung function changes and their potential effect modifiers. The literature suggests strong evidence of an association between ambient pollen concentrations and almost all respiratory outcomes mentioned above, especially in people with pre-existing respiratory diseases. However, the evidence on sub-clinical lung function changes, COPD, and effect modifiers other than asthma, hay fever and pollen sensitisation are still scarce and requires further exploration. Better understanding of the implications of pollen on respiratory health can aid healthcare professionals to implement appropriate management strategies.

Data mining assessment of Poaceae pollen influencing factors and its environmental implications

Poaceae pollen is highly allergenic, with a marked contribution to the pollen worldwide allergy prevalence. Pollen counts are defined by the species present in the considered area, although year-to-year oscillations may be triggered by different parameters, among which are weather conditions. Due to the predominant role of Poaceae pollen in the allergenicity in urban green areas, the aim of this study was the analysis of pollen trends and the influence of meteorology to forecast relevant variations in airborne pollen levels. The study was carried out during the 1993-2020 period in Ourense, in NW Iberian Peninsula. We used a volumetric Lanzoni VPPS 2000 trap for recording Poaceae airborne pollen grains, and meteorological daily data were obtained from the Galician Institute for Meteorology and Oceanography. The main indexes of the pollen season and their trends were calculated. A correlation analysis and 'C5.0 Decision Trees and Rule-Based Models' data mining algorithm were applied to determine the influence of meteorological conditions on pollen levels. We detected atmospheric Poaceae pollen during 139 days on average, mainly from April to August. The mean pollen grains amount recorded during the pollen season was 4608 pollen grains, with the pollen maximum peak of 276 pollen/m³ on 27 June. We found no statistically significant trends and slight slopes for the seasonal indexes, similarly to previous Poaceae studies in the same region. The calculated C5.0 model offered defined results, indicating that the combination of mean temperature above 17.46 °C and sunlight exposure higher than 12.7 h is conductive to significantly high pollen levels. The obtained results make possible the identification of risk moments during the pollen season for the activation of protective measures for sensitized population to grass pollen.

Atmospheric transport reveals grass pollen dispersion distances

Identifying the origin of bioaerosols is of central importance in many biological disciplines, such as human health, agriculture, forestry, aerobiology and conservation. Modelling sources, transportation pathways and sinks can reveal how bioaerosols vary in the atmosphere and their environmental impact. Grass pollen are particularly important due to their widely distributed source areas, relatively high abundance in the atmosphere and high allergenicity. Currently, studies are uncertain regarding sampler representability between distance and sources for grass pollen. Using generalized linear modelling, this study aimed to analyse this relationship further by answering the question of distance-to-source area contribution. Grass pollen concentrations were compared between urban and rural locations, located 6.4 km apart, during two years in Worcestershire, UK. We isolated and refined vegetation areas at 100 m × 100 m using the 2017 CEH Crop Map and conducted atmospheric modelling using HYSPLIT to identify which source areas could contribute pollen. Pollen concentrations were then modelled with source areas and meteorology using generalized linear mixed-models with three temporal variables as random variation. We found that the Seasonal Pollen Integral for grass pollen varied between both years and location, with the urban location having higher levels. Day of year showed higher temporal variation than the diurnal or annual variables. For the urban location, grass source areas within 30 km had positive significant effects in predicting grass pollen concentrations, while source areas within 2-10 km were important for the rural one. The source area differential was likely influenced by an urban-rural gradient that caused differences in the source area contribution. Temperature had positive highly significant effects on both locations while precipitation affected only the rural location. Combining atmospheric modelling, vegetation source maps and generalized linear modelling was found to be a highly accurate tool to identify transportation pathways of bioaerosols in landscape environments.

The impact of data assimilation into the meteorological WRF model on birch pollen modelling

We analyse the impact of ground-based data assimilation to the Weather Research and Forecasting (WRF) meteorological model on parameters relevant for birch pollen emission calculations. Then, we use two different emission databases (BASE - no data assimilation, OBSNUD - data assimilation for the meteorological model) in the chemical transport model and evaluate birch pollen concentrations. Finally, we apply a scaling factor for the emissions (BASE and OBSNUD), based on the ratio between simulated and observed seasonal pollen integral (SPIn) to analyse its impact on birch concentrations over Central Europe. Assimilation of observational data significantly reduces model overestimation of air temperature, which is the main parameter responsible for the start of pollen emission and amount of released pollen. The results also show that a relatively small bias in air temperature from the model can lead to significant differences in heating degree days (HDD) value. This may cause the HDD threshold to be attained several days earlier/later than indicated from observational data which has further impact on the start of pollen emission. Even though the bias for air temperature was reduced for OBSNUD, the model indicates a start for the birch pollen season that is too early compared to observations. The start date of the season was improved at two of the 11 stations in Poland. Data assimilation does not have a significant impact on the season's end or SPIn value. The application of the SPIn factor for the emissions results in a much closer birch pollen concentration level to observations even though the factor does not improve the start or end of the pollen season. The post-processing of modelled meteorological fields, such as the application of bias correction, can be considered as a way to further improve the pollen emission modelling.

Developing climate-resilient crops: improving plant tolerance to stress combination

Global warming and climate change are driving an alarming increase in the frequency and intensity of different abiotic stresses, such as droughts, heat waves, cold snaps, and flooding, negatively affecting crop yields and causing food shortages. Climate change is also altering the composition and behavior of different insect and pathogen populations adding to yield losses worldwide. Additional constraints to agriculture are caused by the increasing amounts of human-generated pollutants, as well as the negative impact of climate change on soil microbiomes. Although in the laboratory, we are trained to study the impact of individual stress conditions on plants, in the field many stresses, pollutants, and pests could simultaneously or sequentially affect plants, causing conditions of stress combination. Because climate change is expected to increase the frequency and intensity of such stress combination events (e.g., heat waves combined with drought, flooding, or other abiotic stresses, pollutants, and/or pathogens), a concentrated effort is needed to study how stress combination is affecting crops. This need is particularly critical, as many studies have shown that the response of plants to stress combination is unique and cannot be predicted from simply studying each of the different stresses that are part of the stress combination. Strategies to enhance crop tolerance to a particular stress may therefore fail to enhance tolerance to this specific stress, when combined with other factors. Here we review recent studies of stress combinations in different plants and propose new approaches and avenues for the development of stress combination- and climate change-resilient crops.

Development of MIF/IL-1β biosensors for discovery of critical quality attributes and potential allergic rhinitis targets from clinical real-world data by intelligent algorithm coupled with in vitro and vivo mechanism validation

There are still huge challenges from clinical real-world data to accurate targets and critical quality attributes (CQAs) for effective treatment of allergic rhinitis (AR). Here, we present a novel integrated strategy that biosensors and intelligent algorithms were used to angle AR targets and CQAs from clinical real world. Firstly, bagging and boosting partial least squares discrimination analysis (PLS-DA) and Monte-Carlo sampling were proposed to screen accurate AR targets. Macrophage migration inhibitory factor (MIF) and Interleukin-1beta (IL-1β) potential targets were obtained based on large-scale analysis of one thousand proteins and in-depth precise screening of seventy proteins. Furthermore, high electron mobility transistor (HEMT) biosensors were fabricated and successfully modified by MIF and IL-1β potential targets with a low detection concentration as 1 pM and quantitative range from 1 pM to 10 nM. Surprisingly, through MIF/IL-1β biosensors, we angled 5-O-methylvisammioside, amygdalin, and cimicifugoside three CQAs. The strong interaction was discovered among three CQAs and MIF/IL-1β biosensors with almost all K_D up to 10^-11 M. Finally, interaction among three CQAs and MIF/IL-1β biosensors were evaluated by in vitro and vivo experiments. In this paper, two critical potential targets and three effective CQAs for AR treatment were discovered and validated by biosensor and advanced algorithms. It provides a superior integrated idea for angling critical targets and CQAs from clinical real-world data by biosensors and informatics.

Climate Change and Global Issues in Allergy and Immunology

The steady increase in global temperatures, resulting from the combustion of fossil fuels and the accumulation of greenhouse gases (GHG), continues to destabilize all ecosystems worldwide. Although annual emissions must halve by 2030 and reach net-zero by 2050 to limit some of the most catastrophic impacts associated with a warming planet, the world's efforts to curb GHG emissions fall short of the commitments made in the 2015 Paris Agreement (1). To this effect, July 2021 was recently declared the hottest month ever recorded in 142 years (2). The ramifications of these changes on global temperatures are complex and further promote outdoor air pollution, pollen exposure, and extreme weather events. Besides worsening respiratory health, air pollution, promotes atopy and susceptibility to infections. The GHG effects on pollen affect the frequency and severity of asthma and allergic rhinitis. Changes in temperature, air pollution, and extreme weather events exert adverse multisystemic health effects and disproportionally affect disadvantaged and vulnerable populations. This article is an update for allergists and immunologists about the health impacts of climate change, already evident in our daily practices. It is also a call to action and advocacy, including integrating climate change-related mitigation, education, and adaptation measures to protect our patients and avert further injury to our planet.

Analysis of changes in Betula pollen season start including the cycle of pollen concentration in atmospheric air

Birch belongs to the most important allergenic taxa in Europe, therefore information on the start dates of the pollen season is very important for allergists and their patients as well as for climatologists. The study examined changes in the start of the birch pollen season as well as determined the trend of these changes. Pollen monitoring was performed in Lublin (eastern Poland) in the period 2001-2019 using the volumetric method. The Makra-test was used to detect periods with significantly higher or lower average of the onset than the average for the whole dataset. Two significant falls in the average of the pollen season start were found in 2007 and 2014. Besides, taking into account the 2-3-year rhythm of high and low concentrations of birch pollen in the atmospheric air, linear trends were fitted for the subsets of high and low abundance seasons. Significant changes in Betula pollen season start dates were only determined for the highly abundance seasons, while the results for seasons with a low concentration did not allow rejecting the hypothesis about the lack of a linear trend in the changes in the studied parameter. Moreover, a significant polynomial relationship was found between the beginning of a pollen season and the average values of monthly temperatures preceded a season. These analyses show that the start dates of the Betula pollen season are getting significantly earlier. The dynamics of changes differ between seasons with high and low concentrations of pollen.

The Role of Environmental Risk Factors on the Development of Childhood Allergic Rhinitis

Environmental factors play an important role in the development and exacerbation of allergic rhinitis (AR) in childhood. Indoor air pollution, such as house dust mites and secondhand smoke, can significantly increase the onset of AR, while pet dander may affect the exacerbation of AR symptoms in children. Furthermore, traffic related air pollution and pollen are outdoor air pollutants that can affect immune competency and airway responsiveness, increasing the risk of AR in children. Climate change has increased AR in children, as growth patterns of allergenic species have changed, resulting in longer pollen seasons. More extreme and frequent weather events also contribute to the deterioration of indoor air quality due to climate change. Additionally, viruses provoke respiratory tract infections, worsening the symptoms of AR, while viral infections alter the immune system. Although viruses and pollution influence development and exacerbation of AR, a variety of treatment and prevention options are available for AR patients. The protective influence of vegetation (greenness) is heavily associated with air pollution mitigation, relieving AR exacerbations, while the use of air filters can reduce allergic triggers. Oral antihistamines and intranasal corticosteroids are common pharmacotherapy for AR symptoms. In this review, we discuss the environmental risk factors for AR and summarize treatment strategies for preventing and managing AR in children.