4.1 Article

Urban-scale variation in pollen concentrations: a single station is insufficient to characterize daily exposure

Journal

AEROBIOLOGIA
Volume 36, Issue 3, Pages 417-431

Publisher

SPRINGER
DOI: 10.1007/s10453-020-09641-z

Keywords

Aeroallergens; Allergenic pollen; Allergic rhinitis; Exposure misclassification; Exposure measurement error

Funding

  1. National Institute of Environmental Health Sciences through a NRSA postdoctoral fellowship [F32 ES026477]
  2. Michigan Institute for Clinical Health Research through the Postdoctoral Translational Scholars Program [UL1 TR002240]
  3. National Institute of Environmental Health Sciences, National Institutes of Health [P30ES017885]

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Epidemiological analyses of airborne allergenic pollen often use concentration measurements from a single station to represent exposure across a city, but this approach does not account for the spatial variation of concentrations within the city. Because there are few descriptions of urban-scale variation, the resulting exposure measurement error is unknown but potentially important for epidemiological studies. This study examines urban-scale variation in pollen concentrations by measuring pollen concentrations of 13 taxa over 24-h periods twice weekly at 25 sites in two seasons in Detroit, Michigan. Spatiotemporal variation is described using cumulative distribution functions and regression models. Daily pollen concentrations across the 25 stations varied considerably, and the average quartile coefficient of dispersion was 0.63. Measurements at a single site explained 3-85% of the variation at other sites, depending on the taxon, and 95% prediction intervals of pollen concentrations generally spanned one to two orders of magnitude. These results demonstrate considerable heterogeneity of pollen levels at the urban scale and suggest that the use of a single monitoring site will not reflect pollen exposure over an urban area and can lead to sizable measurement error in epidemiological studies, particularly when a daily time step is used. These errors might be reduced by using predictive daily pollen levels in models that combine vegetation maps, pollen production estimates, phenology models, and dispersion processes, or by using coarser time steps in the epidemiological analysis.

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