TY - JOUR
T1 - Development of a semi-mechanistic allergenic pollen emission model
AU - Cai, Ting
AU - Zhang, Yong
AU - Ren, Xiang
AU - Bielory, Leonard
AU - Mi, Zhongyuan
AU - Nolte, Christopher G.
AU - Gao, Yang
AU - Leung, L. Ruby
AU - Georgopoulos, Panos G.
N1 - Funding Information:
This research was funded in part by the U.S. Environmental Protection Agency (EPA) under STAR Grant EPA-RD-83454701-0 to Rutgers University, by the NIEHS sponsored Center for Environmental Exposures and Disease at EOHSI ( P30ES005022 ), and by the Ozone Research Center which is funded by the State of New Jersey Department of Environmental Protection . Drs. Gao and Leung are supported by the U.S. Department of Energy Office of Science Regional and Global Climate Modeling program. Pacific Northwest National Laboratory is operated for DOE by Battelle Memorial Institute under contract DE-AC05-76RL01830. We thank NAB for providing airborne pollen data, and Ms. Linda Everett and Mr. George M. Grindlinger (Rutgers) for editorial and technical assistance. The views expressed in this article are those of the authors and do not necessarily represent the views or policies of the U.S. EPA.
Funding Information:
This research was funded in part by the U.S. Environmental Protection Agency (EPA) under STAR Grant EPA-RD-83454701-0 to Rutgers University, by the NIEHS sponsored Center for Environmental Exposures and Disease at EOHSI (P30ES005022), and by the Ozone Research Center which is funded by the State of New Jersey Department of Environmental Protection. Drs. Gao and Leung are supported by the U.S. Department of Energy Office of Science Regional and Global Climate Modeling program. Pacific Northwest National Laboratory is operated for DOE by Battelle Memorial Institute under contract DE-AC05-76RL01830. We thank NAB for providing airborne pollen data, and Ms. Linda Everett and Mr. George M. Grindlinger (Rutgers) for editorial and technical assistance. The views expressed in this article are those of the authors and do not necessarily represent the views or policies of the U.S. EPA.
Publisher Copyright:
© 2018
PY - 2019/2/25
Y1 - 2019/2/25
N2 - Modeling pollen emission processes is crucial for studying the spatiotemporal distributions of airborne allergenic pollen. A semi-mechanistic emission model was developed based on mass balance of pollen grain fluxes in the surroundings of allergenic plants. The emission model considers direct emission and resuspension and accounts for influences of temperature, wind velocity, and relative humidity. Modules of this emission model have been developed and parameterized with multiple years of pollen count observations to provide pollen season onset and duration, hourly flowering likelihood, and vegetation coverage for oak and ragweed, as two examples. The simulated spatiotemporal pattern of pollen emissions generally follows the corresponding pattern of area coverage of allergenic plants and diurnal pattern of hourly flowering likelihood. It is found that oak pollen emissions start from the Southern part of the Contiguous United States (CONUS) in March and then shift gradually toward the Northern CONUS, with a maximum emission flux of 5.8 × 10 6 pollen/(m 2 h). On the other hand, ragweed pollen emissions start from the Northern CONUS in August and then shift gradually toward the Southern CONUS. The mean ragweed emission flux during August to September can increase up to 2.4 × 10 6 pollen/(m 2 h). This emission model is robust with respect to the input parameters for oak and ragweed. Qualitative evaluations of the model performance indicated that the simulated pollen emission is strongly correlated with the plant coverages and observed pollen counts. This model could also be applied to other pollen species given the relevant parameters.
AB - Modeling pollen emission processes is crucial for studying the spatiotemporal distributions of airborne allergenic pollen. A semi-mechanistic emission model was developed based on mass balance of pollen grain fluxes in the surroundings of allergenic plants. The emission model considers direct emission and resuspension and accounts for influences of temperature, wind velocity, and relative humidity. Modules of this emission model have been developed and parameterized with multiple years of pollen count observations to provide pollen season onset and duration, hourly flowering likelihood, and vegetation coverage for oak and ragweed, as two examples. The simulated spatiotemporal pattern of pollen emissions generally follows the corresponding pattern of area coverage of allergenic plants and diurnal pattern of hourly flowering likelihood. It is found that oak pollen emissions start from the Southern part of the Contiguous United States (CONUS) in March and then shift gradually toward the Northern CONUS, with a maximum emission flux of 5.8 × 10 6 pollen/(m 2 h). On the other hand, ragweed pollen emissions start from the Northern CONUS in August and then shift gradually toward the Southern CONUS. The mean ragweed emission flux during August to September can increase up to 2.4 × 10 6 pollen/(m 2 h). This emission model is robust with respect to the input parameters for oak and ragweed. Qualitative evaluations of the model performance indicated that the simulated pollen emission is strongly correlated with the plant coverages and observed pollen counts. This model could also be applied to other pollen species given the relevant parameters.
KW - Allergy
KW - Distribution
KW - Emission
KW - Model
KW - Pollen
KW - Sensitivity analysis
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UR - http://www.scopus.com/inward/citedby.url?scp=85056166000&partnerID=8YFLogxK
U2 - 10.1016/j.scitotenv.2018.10.243
DO - 10.1016/j.scitotenv.2018.10.243
M3 - Article
C2 - 30759620
AN - SCOPUS:85056166000
SN - 0048-9697
VL - 653
SP - 947
EP - 957
JO - Science of the Total Environment
JF - Science of the Total Environment
ER -