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    Int J Health Geogr. 2012 Jan 12;11:3.

    U.S. census unit population exposures to ambient air pollutants.

    Source

    National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, Georgia, USA. yhao@cdc.gov

    Abstract

    BACKGROUND:

    Progress has been made recently in estimating ambient PM(2.5) (particulate matter with aerodynamic diameter < 2.5 μm) and ozone concentrations using various data sources and advanced modeling techniques, which resulted in gridded surfaces. However, epidemiologic and health impact studies often require population exposures to ambient air pollutants to be presented at an appropriate census geographic unit (CGU), where health data are usually available to maintain confidentiality of individual health data. We aim to generate estimates of population exposures to ambient PM(2.5) and ozone for U.S. CGUs.

    METHODS:

    We converted 2001-2006 gridded data, generated by the U.S. Environmental Protection Agency (EPA) for CDC's (Centers for Disease Control and Prevention) Environmental Public Health Tracking Network (EPHTN), to census block group (BG) based on spatial proximities between BG and its four nearest grids. We used a bottom-up (fine to coarse) strategy to generate population exposure estimates for larger CGUs by aggregating BG estimates weighted by population distribution.

    RESULTS:

    The BG daily estimates were comparable to monitoring data. On average, the estimates deviated by 2 μg/m(3) (for PM(2.5)) and 3 ppb (for ozone) from their corresponding observed values. Population exposures to ambient PM(2.5) and ozone varied greatly across the U.S. In 2006, estimates for daily potential population exposure to ambient PM(2.5) in west coast states, the northwest and a few areas in the east and estimates for daily potential population exposure to ambient ozone in most of California and a few areas in the east/southeast exceeded the National Ambient Air Quality Standards (NAAQS) for at least 7 days.

    CONCLUSIONS:

    These estimates may be useful in assessing health impacts through linkage studies and in communicating with the public and policy makers for potential intervention.

    PMID:
    22239864
    [PubMed - in process]
    PMCID:
    PMC3274475
    Free PMC Article

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