Literature DB >> 21516207

A mechanistic modeling system for estimating large scale emissions and transport of pollen and co-allergens.

Christos Efstathiou1, Sastry Isukapalli, Panos Georgopoulos.   

Abstract

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, CMAQ-pollen, 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 studies (MENTOR) for multiple, co-occurring contaminants that include aeroallergens and irritants.

Entities:  

Year:  2011        PMID: 21516207      PMCID: PMC3079563          DOI: 10.1016/j.atmosenv.2010.12.008

Source DB:  PubMed          Journal:  Atmos Environ (1994)        ISSN: 1352-2310            Impact factor:   4.798


  19 in total

Review 1.  Comparing pollen and spore counts collected with the Rotorod Sampler and Burkard spore trap.

Authors:  D A Frenz
Journal:  Ann Allergy Asthma Immunol       Date:  1999-11       Impact factor: 6.347

2.  Correlation of ambient inhalable bioaerosols with particulate matter and ozone: a two-year study.

Authors:  Atin Adhikari; Tiina Reponen; Sergey A Grinshpun; Dainius Martuzevicius; Grace LeMasters
Journal:  Environ Pollut       Date:  2005-09-23       Impact factor: 8.071

3.  Towards numerical forecasting of long-range air transport of birch pollen: theoretical considerations and a feasibility study.

Authors:  M Sofiev; P Siljamo; H Ranta; A Rantio-Lehtimäki
Journal:  Int J Biometeorol       Date:  2006-04-05       Impact factor: 3.787

4.  Aeroallergen prevalence in the northern New Jersey-New York City metropolitan area: a 15-year summary.

Authors:  Ava Port; John Hein; Alan Wolff; Leonard Bielory
Journal:  Ann Allergy Asthma Immunol       Date:  2006-05       Impact factor: 6.347

Review 5.  Mechanistic models for wind dispersal.

Authors:  Anna Kuparinen
Journal:  Trends Plant Sci       Date:  2006-05-11       Impact factor: 18.313

6.  Rethinking the assessment of photochemical modelin systems in air quality planning applications.

Authors:  Christian Hogrefe; Kevin L Civerolo; Winston Hao; Jia-Yeong Ku; Eric E Zalewsky; Gopal Sistla
Journal:  J Air Waste Manag Assoc       Date:  2008-08       Impact factor: 2.235

7.  Experimental prediction of daily ragweed concentration.

Authors:  G S Raynor; J V Hayes
Journal:  Ann Allergy       Date:  1970-12

8.  Ragweed pollen distribution in the U.S.A.: utilization of graphic maps.

Authors:  L S Girsh
Journal:  Ann Allergy       Date:  1982-07

9.  Economic impact of workplace productivity losses due to allergic rhinitis compared with select medical conditions in the United States from an employer perspective.

Authors:  Charles E Lamb; Paul H Ratner; Clarion E Johnson; Ambarish J Ambegaonkar; Ashish V Joshi; David Day; Najah Sampson; Benjamin Eng
Journal:  Curr Med Res Opin       Date:  2006-06       Impact factor: 2.580

Review 10.  Economic impact and quality-of-life burden of allergic rhinitis.

Authors:  William F Schoenwetter; Leon Dupclay; Sireesh Appajosyula; Marc F Botteman; Chris L Pashos
Journal:  Curr Med Res Opin       Date:  2004-03       Impact factor: 2.580

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  11 in total

1.  Aerobiology in the International Journal of Biometeorology, 1957-2017.

Authors:  Paul J Beggs; Branko Šikoparija; Matt Smith
Journal:  Int J Biometeorol       Date:  2017-06-12       Impact factor: 3.787

2.  Exploring the spatio-temporal relationship between two key aeroallergens and meteorological variables in the United Kingdom.

Authors:  Nabaz Khwarahm; Jadunandan Dash; Peter M Atkinson; R M Newnham; C A Skjøth; B Adams-Groom; Eric Caulton; K Head
Journal:  Int J Biometeorol       Date:  2014-01-31       Impact factor: 3.787

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

Authors:  Yong Zhang; Leonard Bielory; Panos G Georgopoulos
Journal:  Int J Biometeorol       Date:  2013-06-21       Impact factor: 3.787

4.  Development of a semi-mechanistic allergenic pollen emission model.

Authors:  Ting Cai; Yong Zhang; Xiang Ren; Leonard Bielory; Zhongyuan Mi; Christopher G Nolte; Yang Gao; L Ruby Leung; Panos G Georgopoulos
Journal:  Sci Total Environ       Date:  2018-10-18       Impact factor: 7.963

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

Authors:  M Sofiev; P Siljamo; H Ranta; T Linkosalo; S Jaeger; A Rasmussen; A Rantio-Lehtimaki; E Severova; J Kukkonen
Journal:  Int J Biometeorol       Date:  2012-03-13       Impact factor: 3.787

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

Authors:  Yong Zhang; Sastry Isukapalli; Leonard Bielory; Panos Georgopoulos
Journal:  Atmos Environ (1994)       Date:  2012-11-12       Impact factor: 4.798

7.  Ambrosia pollen source inventory for Italy: a multi-purpose tool to assess the impact of the ragweed leaf beetle (Ophraella communa LeSage) on populations of its host plant.

Authors:  M Bonini; Branko Šikoparija; C A Skjøth; G Cislaghi; P Colombo; C Testoni; M Smith
Journal:  Int J Biometeorol       Date:  2017-11-21       Impact factor: 3.787

8.  Development of a regional-scale pollen emission and transport modeling framework for investigating the impact of climate change on allergic airway disease.

Authors:  Rui Zhang; Tiffany Duhl; Muhammad T Salam; James M House; Richard C Flagan; Edward L Avol; Frank D Gilliland; Alex Guenther; Serena H Chung; Brian K Lamb; Timothy M VanReken
Journal:  Biogeosciences       Date:  2013-03-01       Impact factor: 4.295

Review 9.  Airborne Microalgae: Insights, Opportunities, and Challenges.

Authors:  Sylvie V M Tesson; Carsten Ambelas Skjøth; Tina Šantl-Temkiv; Jakob Löndahl
Journal:  Appl Environ Microbiol       Date:  2016-01-22       Impact factor: 4.792

10.  Numerical ragweed pollen forecasts using different source maps: a comparison for France.

Authors:  Katrin Zink; Pirmin Kaufmann; Blaise Petitpierre; Olivier Broennimann; Antoine Guisan; Eros Gentilini; Mathias W Rotach
Journal:  Int J Biometeorol       Date:  2016-06-18       Impact factor: 3.787

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