Using dispersion and mesoscale meteorological models to forecast pollen concentrations

Pasken, Robert W.; Pietrowicz, Joseph A.

doi:10.1016/j.atmosenv.2005.04.043

Cited by 52 publications

(30 citation statements)

References 11 publications

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“…As will be discussed later, significant progress has been made recently in laboratory measurements of ice nucleation rates of various IN. Combined with increasing model capability of simulating the emission and transport of atmospheric IN species (e.g., Lighthart, 1997;Uno et al, 2003;Chen et al, 2004;Kishcha et al, 2005;Pasken and Pietrowicz, 2005), the next generation meteorological models may be able to adequately examine the roles that major IN play in precipitation formation. Such work would be important to the understanding of interactions between land surface (including the ecosystem) and the atmospheric hydrologic cycle (Barth et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

Parameterizing ice nucleation rates using contact angle and activation energy derived from laboratory data

2008

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Abstract. The rate of ice nucleation in clouds is not easily determined and large discrepancies exist between model predictions and actual ice crystal concentration measured in clouds. In an effort to improve the parameterization of ice nucleating in cloud models, we investigate the rate of heterogeneous ice nucleation under specific ambient conditions by knowing the sizes as well as two thermodynamic parameters of the ice nuclei -contact angle and activation energy. Laboratory data of freezing and deposition nucleation modes were analyzed to derive inversely the two thermodynamic parameters for a variety of ice nuclei, including mineral dusts, bacteria, pollens, and soot particles. The analysis considered the Zeldovich factor for the adjustment of ice germ formation, as well as the solute and curvature effects on surface tension; the latter effects have strong influence on the contact angle. Contact angle turns out to be a more important factor than the activation energy in discriminating the nucleation capabilities of various ice nuclei species. By extracting these thermodynamic parameters, laboratory results can be converted into a formulation that follows classical nucleation theory, which then has the flexibility of incorporating factors such as the solute effect and curvature effect that were not considered in the experiments.

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Section: Introductionmentioning

confidence: 99%

Parameterizing ice nucleation rates using contact angle and activation energy derived from laboratory data

2008

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“…The spatial patterns of the pollen sources are based on vegetation distribution maps, which are subject to large uncertainties (Sofiev et al, , 2013Skjøth et al, 2010;Pauling et al, 2011). For pollen transport modeling, the pollen dispersion is either modeled by Lagrangian trajectory models such as PAPPUS (Tackenberg et al, 2003), SMOP-2D (Jarosz et al, 2004), CALPUFF (Pfender et al, 2006), and HYSPLIT (Pasken and Pietrowicz, 2005;Verinakaite et al, 2010), or by Gaussian advection-diffusion models such as ADMS (Hunt et al, 2001), DRAIS/MADEsoot (Helbig et al, 2004), Aquilon (Dupont et al, 2006), andMETRAS (Schuler andSchlünzen, 2006). Some key physical modules, such as dry deposition due to gravity, washout by precipitation, and resuspension by updrafts, can be parameterized explicitly into a model (Helbig et al, 2004;Kuparinen, 2006;Siljamo et al, 2012).…”

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confidence: 99%

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

et al. 2014

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Abstract. 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 coupled Weather Research and Forecasting Community Multiscale Air Quality (WRF/CMAQ) 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 (USA) 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 O 3 , PM 2.5 , and pollen count, as well as measurements of exhaled nitric oxide in study participants. Two nesting domains with horizontal resolutions of 12 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.

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“…Moreover, these models can take into account the dynamical effect of topography, inhomogeneous canopy distribution, and obstacles that cannot be incorporated into the two models mentioned above. Recently, regional models were used to predict alder or oak pollen dispersal within a range of a few hundred kilometers; these models showed advantages in producing realistic pollen dispersion by using a realistic predicted wind field (Helbig et al, 2004;Pasken and Pietrowicz, 2005;Schueler and Schlünzen, 2006). Dupont et al (2006) predicted field-scale maize pollen dispersal by using a three-dimensional (3-D) atmospheric model and a diffusion transport model; field experimental data were reproduced as well.…”

Section: Introductionmentioning

confidence: 88%

Three-dimensional prediction of maize pollen dispersal and cross-pollination, and the effects of windbreaks

Ushiyama

Inoue

et al. 2009

Environ. Biosafety Res.

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With the extensive adoption of transgenic crops, an understanding of transgene flow is essential to manage gene flow to non-GM crops. Thus, a flexible and accurate numerical model is required to assess gene flow through pollen dispersal. A three-dimensional atmospheric model combined with a diffusion transport model would be a useful tool for predicting pollen dispersal since it would be flexible enough to incorporate the effects of factors such as the spatial arrangement of crop combinations, land use, topography, windbreaks, and buildings. We applied such a model to field measurements of gene flow between two adjacent maize (Zea mays) cultivars, with suppression effects due to windbreaks, in an experimental cornfield in Japan. This combined model reproduced the measured cross-pollination distribution quite well in the case of maize plots with plant windbreaks slightly taller than the maize and without windbreaks, but the model underestimated the effect of a 6-m-tall windbreak net beyond 25 m from the donor pollen source on cross-pollination. The underestimation was most probably due to the problem of assimilated wind data. The model showed that the 6-m-tall windbreak and the plant wind break suppressed average cross-pollination rate by about 60% and 30%, respectively. Halftall and coarser mesh windbreak net suppressed cross-pollination rates by 40% by reducing the swirl of donor pollen by reduced wind speed.

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Using dispersion and mesoscale meteorological models to forecast pollen concentrations

Cited by 52 publications

References 11 publications

Parameterizing ice nucleation rates using contact angle and activation energy derived from laboratory data

Parameterizing ice nucleation rates using contact angle and activation energy derived from laboratory data

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

Three-dimensional prediction of maize pollen dispersal and cross-pollination, and the effects of windbreaks

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