Literature DB >> 24327824

ESTIMATING DAILY NITROGEN DIOXIDE LEVEL: EXPLORING TRAFFIC EFFECTS.

Lixun Zhang1, Yongtao Guan, Brian P Leaderer, Theodore R Holford.   

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) at a geographic location. Monthly NO2 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. Finally, the Connecticut Department of Transportation provides data on traffic density on major roadways, a primary contributor to NO2 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 over a region.

Entities:  

Keywords:  Bayesian model; EPA; air pollution; longitudinal model; nitrogen dioxide

Year:  2013        PMID: 24327824      PMCID: PMC3856232          DOI: 10.1214/13-AOAS642

Source DB:  PubMed          Journal:  Ann Appl Stat        ISSN: 1932-6157            Impact factor:   2.083


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