Modeling past and future spatiotemporal distributions of airborne allergenic pollen across the contiguous United States (original) (raw)
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Biogeosciences, 2014
Exposure to bioaerosol allergens such as pollen can cause exacerbations of allergenic airway disease (AAD) in sensitive populations, and thus cause serious public health problems. Assessing these health impacts by linking the airborne pollen levels, concentrations of respirable allergenic material, and human allergenic response under current and future climate conditions is a key step toward developing preventive and adaptive actions. To that end, a regional-scale pollen emission and transport modeling framework was developed that treats allergenic pollens as non-reactive tracers within the WRF/CMAQ air-quality modeling system. The Simulator of the Timing and Magnitude of Pollen Season (STaMPS) model was used to generate a daily pollen pool that can then be emitted into the atmosphere by wind. The STaMPS is driven by species-specific meteorological (temperature and/or precipitation) threshold conditions and is designed to be flexible with respect to its representation of vegetation species and plant functional types (PFTs). The hourly pollen emission flux was parameterized by considering the pollen pool, friction velocity, and wind threshold values. The dry deposition velocity of each species of pollen was estimated based on pollen grain size and density. An evaluation of the pollen modeling framework was conducted for southern California for the period from March to June 2010. This period coincided with observations by the University of Southern California's Children's Health Study (CHS), which included O3, PM2.5, and pollen count, as well as measurements of exhaled nitric oxide in study participants. Two nesting domains with horizontal resolutions of 12 km and 4 km were constructed, and six representative allergenic pollen genera were included: birch tree, walnut tree, mulberry tree, olive tree, oak tree, and brome grasses. Under the current parameterization scheme, the modeling framework tends to underestimate walnut and peak oak pollen concentrations, and tends to overestimate grass pollen concentrations. The model shows reasonable agreement with observed birch, olive, and mulberry tree pollen concentrations. Sensitivity studies suggest that the estimation of the pollen pool is a major source of uncertainty for simulated pollen concentrations. Achieving agreement between emission modeling and observed pattern of pollen releases is the key for successful pollen concentration simulations.
Atmospheric Environment, 2011
Allergic airway diseases represent a complex health problem which can be exacerbated by the synergistic action of pollen particles and air pollutants such as ozone. Understanding human exposures to aeroallergens requires accurate estimates of the spatial distribution of airborne pollen levels as well as of various air pollutants at different times. However, currently there are no established methods for estimating allergenic pollen emissions and concentrations over large geographic areas such as the United States. A mechanistic modeling system for describing pollen emissions and transport over extensive domains has been developed by adapting components of existing regional scale air quality models and vegetation databases. First, components of the Biogenic Emissions Inventory System (BEIS) were adapted to predict pollen emission patterns. Subsequently, the transport module of the Community Multiscale Air Quality (CMAQ) modeling system was modified to incorporate description of pollen transport. The combined model, CMAQpollen, allows for simultaneous prediction of multiple air pollutants and pollen levels in a single model simulation, and uses consistent assumptions related to the transport of multiple chemicals and pollen species. Application case studies for evaluating the combined modeling system included the simulation of birch and ragweed pollen levels for the year 2002, during their corresponding peak pollination periods (April for birch and September for ragweed). The model simulations were driven by previously evaluated meteorological model outputs and emissions inventories for the eastern United States for the simulation period. A semi-quantitative evaluation of CMAQ-pollen was performed using tree and ragweed pollen counts in Newark, NJ for the same time periods. The peak birch pollen concentrations were predicted to occur within two days of the peak measurements, while the temporal patterns closely followed the measured profiles of overall tree pollen. For the case of ragweed pollen, the model was able to capture the patterns observed during September 2002, but did not predict an early peak; this can be associated with a wider species pollination window and inadequate spatial information in current land cover databases. An additional sensitivity simulation was performed to comparatively evaluate the dispersion patterns predicted by CMAQ-pollen with those predicted by the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model, which is used extensively in aerobiological studies. The CMAQ estimated concentration plumes matched the equivalent pollen scenario modeled with HYSPLIT. The novel pollen modeling approach presented here allows simultaneous estimation of multiple airborne allergens and other air pollutants, and is being developed as a central component of an integrated population exposure modeling system, the Modeling Environment for Total Risk
Geosci. Model Dev. Discuss., 2013
A pollen model that simulates the timing and production of wind-dispersed allergenic pollen by terrestrial, temperate vegetation has been developed to quantify how pollen occurrence may be affected by climate change and to investigate how pollen can interact with anthropogenic pollutants to affect human health. The Simulator of the Timing and Nevada. Differences in the simulated timing and magnitude of pollen season for the selected allergenic species under current and future climate scenarios are presented. The results suggest that across all of the simulated species, pollen season starts an average of 5-6 days earlier under predicted future climatic conditions with an associated average annual domain-wide temperature increase of about 1 • C compared to 5 simulated current conditions. Differences in the amount of pollen produced under the two scenarios vary by species and are affected by the selected simulation period (1 March-30 June). Uncertainties associated with the STaMPS model and future model development plans are also discussed.
Evaluation and forecasting of atmospheric concentrations of allergenic pollen in Europe
Diseases in the respiratory system due to aeroallergens, such as rhinitis and asthma, are major causes of a demand for increased healthcare, loss of productivity and an increased rate of morbidity. Pollenosis accounts for 12 -45 % of overall allergy cases. The sensitisation to pollen allergens is increasing in most European regions. The adverse health effects of allergens can be reduced by preemptive medical measures. However, their planning requires reliable forecasts of high atmospheric pollen concentrations , .
Global change biology, 2015
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% ...
Aerobiologia, 2016
The incidence of allergic diseases has been increasing in recent decades, in part due to increased exposure to aeroallergens, particularly pollen. Allergic diseases have a major burden on the health care system, with annual costs in the USA alone exceeding $30 billion. There is evidence that the production of aeroallergens, including pollen, is increasing in response to environmental and climatic change, which has important implications for the treatment of allergy sufferers. In this study, pollen data from a Rotorod sampler in Raleigh, North Carolina, was used to characterize and examine trends in the atmospheric pollen seasons for trees, grasses, and weeds over the period 1999-2012. The influence of mean monthly antecedent and concurrent temperature and precipitation on the timing, duration, and severity of the pollen seasons was assessed using Pearson's product-moment correlation coefficients and multiple linear regression models. An increasing trend was noted in seasonal tree pollen concentrations, while seasonal and peak weed pollen concentrations declined over time. The atmospheric pollen seasons for grasses and weeds trended toward earlier start dates and longer durations, while the tree pollen season trended toward an earlier end date. Peak daily tree pollen concentrations were strongly associated with antecedent temperature and precipitation, while peak daily grass pollen concentrations were strongly associated with concurrent precipitation. The strongest relationships between climate and weed pollen were associated with the timing and duration of the pollen season, with drier antecedent and warmer concurrent conditions tied to longer weed pollen seasons.
Incorporation of pollen data in source maps is vital for pollen dispersion models
Atmospheric Chemistry and Physics Discussions, 2019
Information about distribution of pollen sources, i.e. their presence and abundance in a specific region, is important especially when atmospheric transport models are applied to forecast pollen concentrations. The goal of this study is to evaluate three pollen source maps using an atmospheric transport model and study the effect on the model results by combining these source maps with pollen data. Here we evaluate three maps for the birch taxon: (1) a map derived by combining land cover data and forest inventory; (2) a map obtained from land cover data and calibrated using model simulations and pollen observations; (3) a statistical map resulting from analysis of forest inventory and forest plot data. The maps were introduced to the Enviro-HIRLAM (Environment-High Resolution Limited Area Model) as input data to simulate birch pollen concentrations over Europe for the birch pollen season 2006. 18 model runs were performed using each of the selected maps in turn with and without calibration with observed pollen data from 2006. The model results were compared with the pollen observation data at 12 measurement sites located in Finland, Denmark and Russia. We show that calibration of the maps using pollen observations significantly improved the model performance for all three maps. The findings also indicate the large sensitivity of the model results to the source maps and agree well with other studies on birch showing that pollen or hybrid-based source maps provide the best model performance. This study highlights the importance of including pollen data in the production of source maps for pollen dispersion modelling and for exposure studies. 1 Introduction Aeroallergens are a specific type of atmospheric aerosols causing allergic reactions among people suffering from allergic rhinitis and it is often connected with asthma (Bachert et al., 2004). The amount of allergic patients sensitive to pollen is assessed 1
Using dispersion and mesoscale meteorological models to forecast pollen concentrations
Atmospheric Environment, 2005
This work describes the results of research into a source-oriented pollen concentration forecasting technique. Tests were conducted using the National Center for Atmospheric Research/ Penn State Fifth Generation Mesoscale Model (MM5), the National Oceanographic and Atmospheric Administration (NOAA) Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT_4) Model combined with the locations of oak trees and their aerial coverage from biogenic emissions land cover database version 3.1 (BELD3). Daily forecasts of pollen concentrations via MM5 and HYSPLIT_4 were made with 30-min increments and tested against 30-min oak pollen data collected by the St. Louis County Department of Health in Clayton, Missouri, for the month of April 2000.
Forecasting airborne pollen concentrations: Development of local models
Aerobiologia, 2003
People's sensitivity to allergies may representone of the most important health factors of thenext century to which attention must be paid inorder to reduce the incidence of social costsand improve the quality of life.Taking into consideration the earnest requestsof the medical-scientific communityEmilia-Romagna ARPA (Regional Agency for thePrevention of the Environment) moved theattention from the monitoring to a short andmedium term prediction of the concentration ofallergenic pollens in the air in order toachieve a more effective therapeutic action.Our main objectives are to improve seasonalforecasts and to interpret anomalous years.A neural network model for grass pollenforecasting has been implemented. Inputvariables were meteorological situations, i.e.,daily temperature (max., min. and average) andrainfall, in addition to combinations ofindividual variables and their thresholds. Theoutput was daily pollen concentration.The model was able to understand and predictanomalous years. We demonstrate that therelationships between pollen concentrations andmeteorological situations are independent fromsite. This means that such models canunderstand the differences in differentareas.
Using Mesoscale Meteorological Models as a Tool to Forecast Pollen Concentrations
Introduction Many people experience a seasonal disorder that causes sneezing, itching, runny nose and nasal congestion. Seasonal allergic rhinitis, also known as "hay fever", affects approximately 35.9 million people in the United States (Nathan et al.; 1997). Although treatment is possible, the American Academy of Allergy, Asthma and Immunology (AAAAI) recommends the complete avoidance of the allergens. By altering their daily routine to avoid the times and places where the allergens are present, hay fever sufferers can reduce the need for treatment and allow medical personnel to create a more effective treatment plan. In order to accomplish this, the spatial and temporal distribution during the day of the allergens needs to be known. Currently the only information concerning the pollen and mold concentrations in the Saint Louis area comes from the Saint Louis County Department of Health. This County Department samples pollens and molds at a single site in Clayton, Missouri and provides the pollen and mold concentrations for the previous 24-hours during business days. Thus the only information available to the public are the mold and pollen counts for the previous 24 hours. Forecasting of pollen counts is a very difficult task. Most techniques fall into one of two categories; one method, known as the receptor-oriented technique, predicts the concentration without prior knowledge of the emission strengths, duration or diffusion by the atmosphere. This technique is the most commonly used forecast technique. A second method, known as the sourceoriented technique, requires knowledge of the source locations, emission rates, and duration and the structure of the meteorological boundary layer. The source oriented tecnique is not in common use because of the complexities of modeling the atmospheric boundary layer (ABL) on scales small enough to accurately reproduce the temporal and spatial variations of the pollen and mold sources. Developments in mesoscale and pollution modeling allow experiments with the sourceoriented technique to be conducted. The MM5 mesoscale model (Dudhia et al.; 2001) is now capable of making accurate forecasts with resolutions as fine as 1 km 2 and allows experimentation with various boundary layer prediction schemes. The Air Resources Laboratory's (ARL's) HYSPLIT_4 (Draxler and Hess; 1998) readily accepts as input the meteorological data from mesoscale models to compute the dispersion rate from the vertical diffusivity profile, wind shear and the horizontal deformation of the wind field. Combined with an understanding of the biology of the plants releasing the pollen, the sources of the allergens can be mapped both spatially and temporally. The use of high resolution mesoscale