Exposure to allergenic tree pollen is a risk factor for multiple allergic disease outcomes. Little is known about how tree pollen levels vary within cities and whether such variation affects the development or exacerbation of allergic disease. Accordingly, we collected integrated pollen samples at uniform height at 45 sites across New York City during the 2013 pollen season. We used these monitoring results in combination with adjacent land use data to develop a land use regression model for tree pollen. We evaluated four types of land use variables for inclusion in the model: tree canopy, distributed building height (a measure of building volume density), elevation, and distance to water. When included alone in the model, percent tree canopy cover within a 0.5 km radial buffer explained 39% of the variance in tree pollen (1.9% increase in tree pollen per one-percentage point increase in tree canopy cover, P<0.0001). The inclusion of additional variables did not improve model fit. We conclude that intra-urban variation in tree canopy is an important driver of tree pollen exposure. Land use regression models can be used to incorporate spatial variation in tree pollen exposure in studies of allergic disease outcomes.
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We thank Lisa Campbell and the New York Botanical Garden for providing lab space, as well as Michael Ivkov, Isabel Paul, and Alexis Fitts for their assistance in the installation of the pollen monitoring network. We also thank Sarah Johnson for providing advice on the development of the land use regression and kriging models. This project was supported by NIEHS grant #P30ES009089. Dr. Weinberger was supported by NIEHS training grants #T32ES007322 and #T32ES023770.
The authors declare no conflict of interest.
Supplementary Information accompanies the paper on the Journal of Exposure Science and Environmental Epidemiology website
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Weinberger, K., Kinney, P., Robinson, G. et al. Levels and determinants of tree pollen in New York City. J Expo Sci Environ Epidemiol 28, 119–124 (2018). https://doi.org/10.1038/jes.2016.72
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