English

Estimating daily nitrogen dioxide level: Exploring traffic effects

Applications 2013-12-02 v1

Abstract

Data used to assess acute health effects from air pollution typically have good temporal but poor spatial resolution or the opposite. A modified longitudinal model was developed that sought to improve resolution in both domains by bringing together data from three sources to estimate daily levels of nitrogen dioxide (NO2\mathrm {NO}_2) at a geographic location. Monthly NO2\mathrm {NO}_2 measurements at 316 sites were made available by the Study of Traffic, Air quality and Respiratory health (STAR). Four US Environmental Protection Agency monitoring stations have hourly measurements of NO2\mathrm {NO}_2. Finally, the Connecticut Department of Transportation provides data on traffic density on major roadways, a primary contributor to NO2\mathrm {NO}_2 pollution. Inclusion of a traffic variable improved performance of the model, and it provides a method for estimating exposure at points that do not have direct measurements of the outcome. This approach can be used to estimate daily variation in levels of NO2\mathrm {NO}_2 over a region.

Keywords

Cite

@article{arxiv.1311.7478,
  title  = {Estimating daily nitrogen dioxide level: Exploring traffic effects},
  author = {Lixun Zhang and Yongtao Guan and Brian P. Leaderer and Theodore R. Holford},
  journal= {arXiv preprint arXiv:1311.7478},
  year   = {2013}
}

Comments

Published in at http://dx.doi.org/10.1214/13-AOAS642 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org)

R2 v1 2026-06-22T02:17:20.525Z