Bayesian Analysis of Climate Change Effects on Observed and Projected Airborne Levels of Birch Pollen

Projected climate-driven changes in pollen emission season length and magnitude over the continental United States

Atmospheric conditions affect the release of anemophilous pollen, and the timing and magnitude will be altered by climate change. As simulated with a pollen emission model and future climate data, warmer end-of-century temperatures (4-6 K) shift the start of spring emissions 10-40 days earlier and summer/fall weeds and grasses 5-15 days later and lengthen the season duration. Phenological shifts depend on the temperature response of individual taxa, with convergence in some regions and divergence in others. Temperature and precipitation alter daily pollen emission maxima by -35 to 40% and increase the annual total pollen emission by 16-40% due to changes in phenology and temperature-driven pollen production. Increasing atmospheric CO2 may increase pollen production, and doubling production in conjunction with climate increases end-of-century emissions up to 200%. Land cover change modifies the distribution of pollen emitters, yet the effects are relatively small (<10%) compared to climate or CO2. These simulations indicate that increasing pollen and longer seasons will increase the likelihood of seasonal allergies.

Exposure to green space and pollen allergy symptom severity: A case-crossover study in Belgium

BACKGROUND

The prevalence of pollen allergy has increased due to urbanization, climate change and air pollution. The effects of green space and air pollution on respiratory health of pollen allergy patients are complex and best studied in spatio-temporal detail.

METHODS

We tracked 144 adults sensitized to Betulaceae pollen during the tree pollen season (January-May) of 2017 and 2018 and assessed their spatio-temporal exposure to green space, allergenic trees, air pollutants and birch pollen. Participants reported daily symptom severity scores. We extracted 404 case days with high symptom severity scores and matched these to 404 control days. The data were analyzed using conditional logistic regression with a 1:1 case-crossover design.

RESULTS

Case days were associated with exposure to birch pollen concentration (100 grains/m³) [adjusted odds ratio 1.045 and 95% confidence interval (1.014-1.078)], O₃ concentration (10 μg/m³) [1.504 (1.281-1.766)] and PM₁₀ concentration (10 μg/m³) [1.255 (1.007-1.565)] on the day of the severe allergy event and with the cumulative exposure of one and two days before. Exposure to grass cover (10% area fraction) [0.655 (0.446-0.960)], forest cover (10% area fraction) [0.543 (0.303-0.973)] and density of Alnus (10%) [0.622 (0.411-0.942)] were protective for severe allergy, but only on the day of the severe allergy event. Increased densities of Betula trees (10%) were a risk factor [unadjusted OR: 2.014 (1.162-3.490)].

CONCLUSION

Exposure to green space may mitigate tree pollen allergy symptom severity but only when the density of allergenic trees is low. Air pollutants contribute to more severe allergy symptoms. Spatio-temporal tracking allows for a more realistic exposure assessment.

Satellite Monitoring for Air Quality and Health

Data from satellite instruments provide estimates of gas and particle levels relevant to human health, even pollutants invisible to the human eye. However, the successful interpretation of satellite data requires an understanding of how satellites relate to other data sources, as well as factors affecting their application to health challenges. Drawing from the expertise and experience of the 2016-2020 NASA HAQAST (Health and Air Quality Applied Sciences Team), we present a review of satellite data for air quality and health applications. We include a discussion of satellite data for epidemiological studies and health impact assessments, as well as the use of satellite data to evaluate air quality trends, support air quality regulation, characterize smoke from wildfires, and quantify emission sources. The primary advantage of satellite data compared to in situ measurements, e.g., from air quality monitoring stations, is their spatial coverage. Satellite data can reveal where pollution levels are highest around the world, how levels have changed over daily to decadal periods, and where pollutants are transported from urban to global scales. To date, air quality and health applications have primarily utilized satellite observations and satellite-derived products relevant to near-surface particulate matter <2.5 μm in diameter (PM_2.5) and nitrogen dioxide (NO₂). Health and air quality communities have grown increasingly engaged in the use of satellite data, and this trend is expected to continue. From health researchers to air quality managers, and from global applications to community impacts, satellite data are transforming the way air pollution exposure is evaluated.

Increased duration of pollen and mold exposure are linked to climate change

Pollen and molds are environmental allergens that are affected by climate change. As pollen and molds exhibit geographical variations, we sought to understand the impact of climate change (temperature, carbon dioxide (CO₂), precipitation, smoke exposure) on common pollen and molds in the San Francisco Bay Area, one of the largest urban areas in the United States. When using time-series regression models between 2002 and 2019, the annual average number of weeks with pollen concentrations higher than zero increased over time. For tree pollens, the average increase in this duration was 0.47 weeks and 0.51 weeks for mold spores. Associations between mold, pollen and meteorological data (e.g., precipitation, temperature, atmospheric CO₂, and area covered by wildfire smoke) were analyzed using the autoregressive integrated moving average model. We found that peak concentrations of weed and tree pollens were positively associated with temperature (p < 0.05 at lag 0–1, 0–4, and 0–12 weeks) and precipitation (p < 0.05 at lag 0–4, 0–12, and 0–24 weeks) changes, respectively. We did not find clear associations between pollen concentrations and CO₂ levels or wildfire smoke exposure. This study’s findings suggest that spore and pollen activities are related to changes in observed climate change variables.

Allergenic Pollen Season Variations in the Past Two Decades Under Changing Climate in the United States

Prevalence of allergic diseases has been increasing due to multiple factors, among which climate change has had the most impact. Climate factors increase production of pollen, which also exhibits increased allergenicity. Also, as a result of climate change, there has been a shift in flowering phenology and pollen initiation causing prolonged pollen exposure. Various numerical models have been developed to understand the effect of climate change on pollen emission and transport and the impact on allergic airway diseases.

An Overview of Rising CO₂ and Climatic Change on Aeroallergens and Allergic Diseases

There are a number of implications of climate change in regard to human health. Among these, the role of rising carbon dioxide (CO₂) and temperature in aeroallergen exposure and associated changes in the start, duration and intensity of the pollen season, and associated consequences in aeroallergens and allergic disease are a primary concern. This review is intended to provide a synopsis of CO₂ and climate factors associated with likely changes in aeroallergen biology (indoor and outdoor), including changes in the demography of flowering plants, pollen seasonality, aeroallergen production, and potential biotic and abiotic interactions. These factors, in turn, are compared to clinical trials that have linked aeroallergens to allergic disease and associated health impacts. Finally, suggestions to address unmet needs and critical knowledge gaps are offered. Such recommendations are not meant to be inclusive, but to serve as a spur for the additional research and resources that will be necessary to acquire a better understanding of climate change, CO₂, aeroallergens and associated allergic diseases. Such resources will be critical to derive time-relevant scientific and policy solutions that will minimize public health consequences in a changing climate.

Forecasting the seasonal pollen index by using a hidden Markov model combining meteorological and biological factors

The seasonal pollen index (SPI) is a continuing concern within the fields of aerobiology, ecology, botany, and epidemiology. The SPI of anemophilous trees, which varies substantially from year to year, reflects the flowering intensity. This intensity is regulated by two factors: weather conditions during flower formation and the inner resource for assimilation. A deterministic approach has to date been employed for predicting SPI, in which the forecast is made entirely by parameters. However, given the complexity of the masting mechanism (which has intrinsic stochastic properties), few attempts have been made to apply a stochastic model that considers the inter-annual SPI variation as a stochastic process. We propose a hidden Markov model that can integrate the stochastic process of mast flowering and the meteorological conditions influencing flower formation to predict the annual birch pollen concentration. In experiments conducted, the model was trained and validated by using data in Hokkaido, Japan covering 22 years. In the model, the hidden Markov sequence was assigned to represent the recurrence of mast years via a transition matrix, and the observation sequences were designated as meteorological conditions in the previous summer, which are governed by hidden states with emission distribution. The proposed model achieved accuracies of 83.3% in the training period and 75.0% in the test period. Thus, the proposed model can provide an alternative perspective toward the SPI forecast and probabilistic information of pollen levels as a useful reference for allergy stakeholders.

A statistical model for predicting the inter-annual variability of birch pollen abundance in Northern and North-Eastern Europe

The paper suggests a methodology for predicting next-year seasonal pollen index (SPI, a sum of daily-mean pollen concentrations) over large regions and demonstrates its performance for birch in Northern and North-Eastern Europe. A statistical model is constructed using meteorological, geophysical and biological characteristics of the previous year). A cluster analysis of multi-annual data of European Aeroallergen Network (EAN) revealed several large regions in Europe, where the observed SPI exhibits similar patterns of the multi-annual variability. We built the model for the northern cluster of stations, which covers Finland, Sweden, Baltic States, part of Belarus, and, probably, Russia and Norway, where the lack of data did not allow for conclusive analysis. The constructed model was capable of predicting the SPI with correlation coefficient reaching up to 0.9 for some stations, odds ratio is infinitely high for 50% of sites inside the region and the fraction of prediction falling within factor of 2 from observations, stays within 40-70%. In particular, model successfully reproduced both the bi-annual cycle of the SPI and years when this cycle breaks down.

Pollen Season Trends (1973-2013) in Stockholm Area, Sweden

In the present study, the phenological and quantitative changes in the pollen seasons between 1973 and 2013 in the Stockholm region of Sweden were studied for nine types of pollen (hazel, alder, elm, birch, oak, grass, mugwort, willow and pine). Linear regression models were used to estimate the long term trends in duration, start- and end-dates, peak-values and the yearly accumulated pollen sums of the pollen seasons. The pollen seasons of several arboreal plant species (e.g. birch, oak and pine) were found to start significantly earlier today compared to 41 years earlier, and have an earlier peak-date, while the season of other species seemed largely unaffected. However, the long term trends in the end-dates of pollen seasons differed between arboreal and herbaceous species. For herbaceous species (grass and mugwort), a significant change towards later end-dates was observed and the duration of season was found to have increased. A significant trend towards an earlier end-date was found in the majority of the arboreal plant species (i.e. elm, oak, pine and birch), but the length of the season seemed unaffected. A trend towards an increase in yearly concentrations of pollen was observed for several species; however the reasons for this phenomenon cannot be explained unambiguously by the present study design. The trend of increasing yearly mean air temperatures in the Stockholm area may be the reason to changed phenological patterns of pollen seasons.

Regional forecast model for the Olea pollen season in Extremadura (SW Spain)

The olive tree (Olea europaea) is a predominantly Mediterranean anemophilous species. The pollen allergens from this tree are an important cause of allergic problems. Olea pollen may be relevant in relation to climate change, due to the fact that its flowering phenology is related to meteorological parameters. This study aims to investigate airborne Olea pollen data from a city on the SW Iberian Peninsula, to analyse the trends in these data and their relationships with meteorological parameters using time series analysis. Aerobiological sampling was conducted from 1994 to 2013 in Badajoz (SW Spain) using a 7-day Hirst-type volumetric sampler. The main Olea pollen season lasted an average of 34 days, from May 4th to June 7th. The model proposed to forecast airborne pollen concentrations, described by one equation. This expression is composed of two terms: the first term represents the resilience of the pollen concentration trend in the air according to the average concentration of the previous 10 days; the second term was obtained from considering the actual pollen concentration value, which is calculated based on the most representative meteorological variables multiplied by a fitting coefficient. Due to the allergenic characteristics of this pollen type, it should be necessary to forecast its short-term prevalence using a long record of data in a city with a Mediterranean climate. The model obtained provides a suitable level of confidence to forecast Olea airborne pollen concentration.

Asthma, oculonasal symptoms, and skin test sensitivity across National Health and Nutrition Examination Surveys

BACKGROUND

The increasing prevalence of allergies and asthma has been reported. However, the progression of the prevalence of allergy (the "allergic diathesis progression") has not been examined over time from skin test positivity to oculonasal symptoms to the development of asthma.

OBJECTIVE

To investigate the change in the prevalences and associations of positive skin test reactions, oculonasal symptoms, and asthma during the Second and Third National Health and Nutrition Examination Surveys (NHANES II and NHANES III, respectively).

METHODS

Data collected during NHANES II and III were used. The prevalence and associations of positive skin test reactions, oculonasal symptoms, and asthma and the linear trend of oculonasal symptoms and asthma prevalence across different cumulative positive skin test reactions were calculated for each NHANES period.

RESULTS

From NHANES II to NHANES III, the prevalence of asthma doubled (2 times) and increased for positive skin test reactions (2.2 times), oculonasal symptoms (3.3 times), and concurrence of asthma, oculonasal symptoms, and positive skin test reactions (5.3 times). People were sensitive to an increasing number of allergens. Positive skin test reactions increased from 0.2% (NHANES II) to 2.7% (NHANES III) for people allergic to all 6 allergens.

CONCLUSION

Despite some methodologic differences in skin tests across NHANES II and III, this study demonstrated significant increases in allergen sensitivities (prevalence and number of allergens), oculonasal symptoms, and asthma over a 20-year course, indicating that increased sensitivity led to increased allergic symptoms and asthma during the 20 years from NHANES II to NHANES III.

Temporal modelling and forecasting of the airborne pollen of Cupressaceae on the southwestern Iberian Peninsula

Cupressaceae includes species cultivated as ornamentals in the urban environment. This study aims to investigate airborne pollen data for Cupressaceae on the southwestern Iberian Peninsula over a 21-year period and to analyse the trends in these data and their relationship with meteorological parameters using time series analysis. Aerobiological sampling was conducted from 1993 to 2013 in Badajoz (SW Spain). The main pollen season for Cupressaceae lasted, on average, 58 days, ranging from 55 to 112 days, from 24 January to 22 March. Furthermore, a short-term forecasting model has been developed for daily pollen concentrations. The model proposed to forecast the airborne pollen concentration is described by one equation. This expression is composed of two terms: the first term represents the pollen concentration trend in the air according to the average concentration of the previous 10 days; the second term is obtained from considering the actual pollen concentration value, which is calculated based on the most representative meteorological parameters multiplied by a fitting coefficient. Temperature was the main meteorological factor by its influence over daily pollen forecast, being the rain the second most important factor. This model represents a good approach to a continuous balance model of Cupressaceae pollen concentration and is supported by a close agreement between the observed and predicted mean concentrations. The novelty of the proposed model is the analysis of meteorological parameters that are not frequently used in Aerobiology.

Disentangling the effects of feedback structure and climate on Poaceae annual airborne pollen fluctuations and the possible consequences of climate change

Pollen allergies are the most common form of respiratory allergic disease in Europe. Most studies have emphasized the role of environmental processes, as the drivers of airborne pollen fluctuations, implicitly considering pollen production as a random walk. This work shows that internal self-regulating processes of the plants (negative feedback) should be included in pollen dynamic systems in order to give a better explanation of the observed pollen temporal patterns. This article proposes a novel methodological approach based on dynamic systems to investigate the interaction between feedback structure of plant populations and climate in shaping long-term airborne Poaceae pollen fluctuations and to quantify the effects of climate change on future airborne pollen concentrations. Long-term historical airborne Poaceae pollen data (30 years) from Cordoba city (Southern Spain) were analyzed. A set of models, combining feedback structure, temperature and actual evapotranspiration effects on airborne Poaceae pollen were built and compared, using a model selection approach. Our results highlight the importance of first-order negative feedback and mean annual maximum temperature in driving airborne Poaceae pollen dynamics. The best model was used to predict the effects of climate change under two standardized scenarios representing contrasting temporal patterns of economic development and CO2 emissions. Our results predict an increase in pollen levels in southern Spain by 2070 ranging from 28.5% to 44.3%. The findings from this study provide a greater understanding of airborne pollen dynamics and how climate change might impact the future evolution of airborne Poaceae pollen concentrations and thus the future evolution of related pollen allergies.

Allergenic pollen season variations in the past two decades under changing climate in the United States

Many diseases are linked with climate trends and variations. In particular, climate change is expected to alter the spatiotemporal dynamics of allergenic airborne pollen and potentially increase occurrence of allergic airway disease. Understanding the spatiotemporal patterns of changes in pollen season timing and levels is thus important in assessing climate impacts on aerobiology and allergy caused by allergenic airborne pollen. Here, we describe the spatiotemporal patterns of changes in the seasonal timing and levels of allergenic airborne pollen for multiple taxa in different climate regions at a continental scale. The allergenic pollen seasons of representative trees, weeds and grass during the past decade (2001-2010) across the contiguous United States have been observed to start 3.0 [95% Confidence Interval (CI), 1.1-4.9] days earlier on average than in the 1990s (1994-2000). The average peak value and annual total of daily counted airborne pollen have increased by 42.4% (95% CI, 21.9-62.9%) and 46.0% (95% CI, 21.5-70.5%), respectively. Changes of pollen season timing and airborne levels depend on latitude, and are associated with changes of growing degree days, frost free days, and precipitation. These changes are likely due to recent climate change and particularly the enhanced warming and precipitation at higher latitudes in the contiguous United States.

Predicting Onset and Duration of Airborne Allergenic Pollen Season in the United States

Allergenic pollen is one of the main triggers of Allergic Airway Disease (AAD) affecting 5% to 30% of the population in industrialized countries. A modeling framework has been developed using correlation and collinearity analyses, simulated annealing, and stepwise regression based on nationwide observations of airborne pollen counts and climatic factors to predict the onsets and durations of allergenic pollen seasons of representative trees, weeds and grass in the contiguous United States. Main factors considered are monthly, seasonal and annual mean temperatures and accumulative precipitations, latitude, elevation, Growing Degree Day (GDD), Frost Free Day (FFD), Start Date (SD) and Season Length (SL) in the previous year. The estimated mean SD and SL for birch (Betula), oak (Quercus), ragweed (Ambrosia), mugwort (Artemisia) and grass (Poaceae) pollen season in 1994-2010 are mostly within 0 to 6 days of the corresponding observations for the majority of the National Allergy Bureau (NAB) monitoring stations across the contiguous US. The simulated spatially resolved maps for onset and duration of allergenic pollen season in the contiguous US are consistent with the long term observations.

Climate change effect on Betula (birch) and Quercus (oak) pollen seasons in the United States

Climatic change is expected to affect the spatiotemporal patterns of airborne allergenic pollen, which has been found to act synergistically with common air pollutants, such as ozone, to cause allergic airway disease (AAD). Observed airborne pollen data from six stations from 1994 to 2011 at Fargo (North Dakota), College Station (Texas), Omaha (Nebraska), Pleasanton (California), Cherry Hill and Newark (New Jersey) in the US were studied to examine climate change effects on trends of annual mean and peak value of daily concentrations, annual production, season start, and season length of Betula (birch) and Quercus (oak) pollen. The growing degree hour (GDH) model was used to establish a relationship between start/end dates and differential temperature sums using observed hourly temperatures from surrounding meteorology stations. Optimum GDH models were then combined with meteorological information from the Weather Research and Forecasting (WRF) model, and land use land coverage data from the Biogenic Emissions Land use Database, version 3.1 (BELD3.1), to simulate start dates and season lengths of birch and oak pollen for both past and future years across the contiguous US (CONUS). For most of the studied stations, comparison of mean pollen indices between the periods of 1994-2000 and 2001-2011 showed that birch and oak trees were observed to flower 1-2 weeks earlier; annual mean and peak value of daily pollen concentrations tended to increase by 13.6%-248%. The observed pollen season lengths varied for birch and for oak across the different monitoring stations. Optimum initial date, base temperature, and threshold GDH for start date was found to be 1 March, 8 °C, and 1,879 h, respectively, for birch; 1 March, 5 °C, and 4,760 h, respectively, for oak. Simulation results indicated that responses of birch and oak pollen seasons to climate change are expected to vary for different regions.

Climate change and allergic disease

Allergies are prevalent throughout the United States and impose a substantial quality of life and economic burden. The potential effect of climate change has an impact on allergic disorders through variability of aeroallergens, food allergens and insect-based allergic venoms. Data suggest allergies (ocular and nasal allergies, allergic asthma and sinusitis) have increased in the United States and that there are changes in allergies to stinging insect populations (vespids, apids and fire ants). The cause of this upward trend is unknown, but any climate change may induce augmentation of this trend; the subspecialty of allergy and immunology needs to be keenly aware of potential issues that are projected for the near and not so distant future.