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

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.

Figure 1

Schematic flowchart depicting the modeling methodology for bioaerosols (e.g. aeroallergens, pollen particles, spores) developed in this work for use within the CMAQ-MM5 modeling framework for air quality studies.

Figure 2

Intersection of “ragweed-positive” and “8-hour ozone exceedance-positive” areas in the United States. The nested MM5 and CMAQ grid setup which was used for meteorological and pollen emission and dispersion simulations is also depicted. (Adapted from a map published by NRDC, the Natural Resources Defense Council, www.nrdc.org (Knowlton et al., 2007)).

Figure 3

Mapped components of the BELD3 database used to classify different zones of birch and ragweed pollen sources within the OTC domain: (a) Birch tree areal coverage used for the spring simulations, and (b) Dominant land use-land cover from the USGS component used for the fall ragweed simulations.

Figure 4

Evaluation of different approaches for estimating the leaf area index (LAI) parameter used in the birch and ragweed pollen simulations: (a) BEIS calculated LAI used for the birch pollen simulations, and (b) 8-day composite LAI remote sensing dataset from the MODIS satellite used for the ragweed simulations.

Figure 5

Daily total tree and ragweed pollen counts measured in Newark, NJ during the years 1990–2003 (Data courtesy of Dr. L. Bielory).

Figure 6

Observed pollen counts of (a) total tree species and (b) ragweed, plotted with the average temperature for the months of April and September 2002, respectively. Pollen counts were obtained from the Newark UMDNJ location (Data courtesy of Dr. L. Bielory), local meteorology from the Newark Interational Airport meteorological station.

Figure 7

Weighted potential source contribution function (PSCF) calculated with the TrajStat software ((Wang et al., 2009)) based on daily HYSPLIT modeled backward trajectories corresponding to the pollen counts measured at the Newark UMDNJ location, NJ during the month of April 2002. Meteorological fields were obtained from the MM5 model, while the number at the end of each trajectory represents the day that the air parcel arrives at the UMDNJ location (noon local time).

Figure 8

Wind-rose plots of the local winds from the Newark Interational Airport meteorological station during the tree and ragweed simulation periods of April and September 2002.

Figure 9

Gridded hourly birch pollen emission fluxes (noon - 12 pm) calculated with the pollen model using a spatiotemporal flowering map developed for April 2002 over the Northeast Ozone Transport Commission (OTC) domain.

Figure 10

Hourly birch pollen levels calculated with the CMAQ-pollen model during April 16^th, 2002 over the Northeast Ozone Transport Commission (OTC) domain. All emissions were allocated to the first layer in the vertical dimension and results are provided for every 4 hours.

Figure 11

Hourly ragweed pollen levels calculated with the CMAQ-pollen model during September 16^th, 2002 over the Northeast Ozone Transport Commission (OTC) domain. All emissions were allocated to the first layer in the vertical dimension and results are provided for every 4 hours.

Figure 12

Comparison plot showing CMAQ-pollen model estimates and observed pollen levels in Newark, NJ for the months of April and September, 2002. The top panel shows estimates using alternative assumptions for pollen emissions: in the CMAQ-pollen-A simulation, all birch pollen emissions were allocated to the first layer in the vertical dimension (from ground to 20 m), while in the CMAQ-pollen-B simulation, 80% of emissions were allocated to the first layer, and 20% were allocated to the second layer (20 to 50 m). In the ragweed simulation case (bottom panel), all emissions were allocated to the first layer.

Figure 13

Comparison of CMAQ and HYSPLIT-modeled dispersal of birch pollen, released from a single cell (12×12 km) forested area of Northern New Jersey at 8 am and 8pm of April 16^th of 2002. Height of release was 20 m (surface CMAQ layer) and 15 m (HYSPLIT), respectively.