2011 Progress Report: [Climate Change and Allergic Airway Disease] Observational,Laboratory, and Modeling Studies of the Impacts of Climate Change onAllergic Airway Disease

EPA Grant Number: R834547
Title: [Climate Change and Allergic Airway Disease] Observational,Laboratory, and Modeling Studies of the Impacts of Climate Change onAllergic Airway Disease
Investigators: Bielory, Leonard , Georgopoulos, Panos G. , Hom, John , Isukapalli, Sastry S. , Mayer, Henry , Robock, Alan , Ziska, Lewis
Current Investigators: Bielory, Leonard , Bonos, Stacy , Georgopoulos, Panos G. , Hom, John , Isukapalli, Sastry S. , Lankow, Richard , Mayer, Henry , Robock, Alan , Velliyagounder, Kabilan , Ziska, Lewis
Institution: Rutgers, The State University of New Jersey
EPA Project Officer: Ilacqua, Vito
Project Period: April 1, 2010 through March 31, 2012 (Extended to March 31, 2016)
Project Period Covered by this Report: April 1, 2011 through March 31,2012
Project Amount: $900,000
RFA: Climate Change and Allergic Airway Disease (2008) RFA Text |  Recipients Lists
Research Category: Global Climate Change , Health , Climate Change


  • To develop a regional atmospheric dynamic model of pollen production, distribution and dispersion.
  • To develop a population exposure and dose model for estimating pollen exposures.
  • To generate pollen phenology from the existing 25 years database from the existing certified 74 U.S. pollen counting stations.
  • To use the regional model to determine how climate change over the next 50 years will change pollen production, distribution, dispersion, and subsequently exposures.
  • To determine the impact of climate change on pollen allergenicity of various species of plants using plant chamber and transects with in vitro and in vivo techniques.

Progress Summary:

  • Analysis of observed airborne 1994-2011 pollen data from American Academy of Allergy Asthma and Immunology (AAAAI) monitoring stations:  annual cumulative airborne pollen count, maximum daily pollen count, mean daily count during the pollen season, start date, season length, and the date of maximum daily pollen count were derived for birch, oak, ragweed, mugwort and grass based on the observed airborne daily count in 86 AAAAI stations across the contiguous United States. Five representative stations in the United States were chosen to further study the relationship between start date and season length, and observed hourly temperature using a Growing Degree Hours (GDH) model. The resultant optimum threshold GDH, initial date, and base temperature were utilized to parameterize the start date and pollen season length in an emission model.
  • Bayesian analysis was carried out to study the relationship between multiple pollen indices and multiple climatic factors using historical pollen and climate data in three representative stations in Europe, and five stations in the United States. The relationships that were established were used to relate future pollen indices (such as annual total) to the future temperature and CO2 levels projected by the Intergovernmental Panel on Climate Change (IPCC). The output of the Bayesian analysis provided future annual total emission fluxes for the emission model.
  • SMOKE-Pollen, a pollen-specific emission model based on the Sparse Matrix Operator Kernel Emissions (SMOKE) Modeling System has been developed incorporating physical processes such as direct emission and re-suspension of pollen particles, and accounting for meteorological parameters such as surface temperature trends, friction velocity, humidity, precipitation, etc., and information on land use/land cover. The model also incorporates results of historical analysis for estimating effects of climate change on annual pollen emission flux. A GDH model was used to generate the start date and length of pollen season based on historical and future meteorology. Area coverage of birch, oak and grass was obtained from the Biogenic Emissions Land Use Database, version 3 (BELD3). Daily and hourly flowering likelihood were parameterized based on published data.
  • WRF-SMOKE-CMAQ-Pollen, a mechanistic modeling system, coupling Weather and Research Forecasting (WRF) with SMOKE-Pollen and the Community Multiscale Air Quality system (CMAQ), has been developed to simulate spatiotemporal profiles of pollen emissions and transport over large domains (e.g., the contiguous United States) under a climate change scenario within the framework of the Modeling Environment for Total Risk studies (MENTOR). Results from a version of the WRF model were utilized and downscaled to derive historical and future meteorology data. Historical meteorology simulations were conducted using the National Center for Environmental Prediction/Department of Energy (NCEP/DOE) Reanalysis 2 for boundary conditions; future meteorology simulations were performed using output from the Community Climate System Model (CCSM) to define boundary conditions. The CMAQ model was adapted to simulate pollen transport including the following physico-chemical processes: cloud dynamics, aerosol chemistry, wet and dry deposition, horizontal and vertical advection and dispersion. Verification was conducted by comparing the output of the combined WRF-SMOKE-CMAQ-Pollen modeling system with the observed pollen count at ~ 86 monitoring stations in the United States and Canada. Statistical analysis is being conducted to obtain metrics such as mean square errors, quantile-quantiles plots, skill scores, etc., to evaluate simulation results from the model.
  • An exposure modeling system is being adapted to generate population exposure estimates for multiple aero-allergenic pollens, under different climate change scenarios.
  • Background spatio-temporal concentrations of pollen are being derived from simulation results of the combined WRF-SMOKE-CMAQ-Pollen modeling system.
  • Human activity patterns will be obtained from the Consolidated Human Activity Database (CHAD) using region-specific demographic information. Inhalation rates used in the exposure model are estimated with U.S. EPA’s Exposure Factors Handbook.

Future Activities:

  • The environmental growth climate chambers were received at the USDA location in Maryland. They required simulations for past and present climates prior to initiation of specific allergenic plant growths. The first run is being completed at elevated CO2 and temperature. Two runs have been completed at elevated CO2 alone, and a second run will be started after switching chambers for the elevated CO2 and temperature treatment, by September 1, 2012. Pollen collection is under way and ~200 mg/plantain plant have been collected; mugwort may reach 1 g of pollen per plant (presently collecting 200 mg per mugwort plant sampled). The plan is to purchase a special vacuum to collect the pollen and increase the yield. Ragweed will reach a gram of pollen per plant.
  • Baseline electron and routine microscopy samples have been generated for grass pollen (phleum pretense) and common mugwort. Additional baseline allergenic plants to be studied include ragweed and English plantain. Baseline measurements of control samples utilizing a digital program have been initiated.
  • The combined WRF-SMOKE-CMAQ-Pollen modeling system will be run to generate emissions and ambient distributions of ragweed, mugwort, and grass from 2004, 2040 and 2050.
  • The existing MENTOR system will be adapted to generate population exposures of multiple aero-allergic pollens under different climate change scenarios.
  • Longitudinal transects in North America will be selected to study the changes of start date and season length of pollen along with the latitude. Latitudinal effects of climate change on pollen timing, and therefore exposure times, can be identified by doing transect analysis.
  • An average pollen index for five species calculated using historical data from 1994 to 2000 in all U.S. stations will be compared with those from 2001 to 2010. These analyses will be used to find the pollen timing shift and quantity variation across the contiguous United States due to climate change. Variograms for the spatial variation of pollen indices in the above mentioned two periods will be calculated to check the spatial correlation of pollen timing and quantity. Contours of pollen indices in two periods will be calculated to determine variation patterns of pollen release timing and quantity. 

Journal Articles on this Report : 4 Displayed | Download in RIS Format

Other project views: All 63 publications 16 publications in selected types All 14 journal articles
Type Citation Project Document Sources
Journal Article Blando J, Bielory L, Nguyen V, Diaz R, Jeng HA. Anthropogenic climate change and allergic diseases. Atmosphere 2012;3(1):200-212. R834547 (2011)
R834547 (Final)
  • Full-text: Atmosphere-Full Text PDF
  • Abstract: Atmosphere-Abstract
  • Journal Article Dapul-Hidalgo G, Bielory L. Climate change and allergic diseases. Annals of Allergy, Asthma & Immunology 2012;109(3):166-172. R834547 (2011)
    R834547 (2012)
    R834547 (Final)
  • Full-text: ResearchGate-Introduction & Full Text-PDF
  • Abstract: AAA&I-Abstract
  • Journal Article Zhang Y, Isukapalli SS, Bielory L, Georgopoulos PG. Bayesian analysis of climate change effects on observed and projected airborne levels of birch pollen. Atmospheric Environment 2013;68:64-73. R834547 (2011)
    R834547 (2012)
    R834547 (2014)
    R834547 (Final)
  • Full-text from PubMed
  • Abstract from PubMed
  • Associated PubMed link
  • Full-text: ScienceDirect-Full Text-HTML
  • Abstract: ScienceDirect-Abstract
  • Other: ScienceDirect-Full Text-PDF
  • Journal Article Zhang Y, Bielory L, Georgopoulos PG. Climate change effect on Betula (birch) and Quercus (oak) pollen seasons in the United States. International Journal of Biometeorology 2014;58(5):909-919. R834547 (2011)
    R834547 (2012)
    R834547 (2013)
    R834547 (2014)
    R834547 (Final)
  • Full-text from PubMed
  • Abstract from PubMed
  • Associated PubMed link
  • Full-text: ResearchGate-Abstract & Full-text-PDF
  • Abstract: Springer-Abstract & Full-text HTML
  • Supplemental Keywords:

    allergens, exposure, climate change, health effects, dose-response;, RFA, Health, Scientific Discipline, Air, Health Risk Assessment, climate change, Risk Assessments, Environmental Monitoring, Ecological Risk Assessment, air quality modeling, ecosystem models, climatic influence, climate related morbidity, emissions impact, modeling, climate models, demographics, human exposure, regional climate model, ambient air pollution, Global Climate Change

    Relevant Websites:

    http://envsci.rutgers.edu Exit EPA Disclaimer
    http://ccl.rutgers.edu Exit EPA Disclaimer

    Progress and Final Reports:

    Original Abstract
  • 2010 Progress Report
  • 2012 Progress Report
  • 2013 Progress Report
  • 2014 Progress Report
  • Final Report