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Analyses of school commuting data for exposure modeling purposes

Journal of Exposure Science & Environmental Epidemiology volume 20, pages 69–78 (2010)Cite this article

Abstract

Human exposure models often make the simplifying assumption that school children attend school in the same census tract where they live. This paper analyzes that assumption and provides information on the temporal and spatial distributions associated with school commuting. The data were obtained using Oak Ridge National Laboratory's LandScan USA population distribution model applied to Philadelphia, PA. It is a high-resolution model used to allocate individual school-aged children to both a home and school location, and to devise a minimum-time home-to-school commuting path (called a trace) between the two locations. LandScan relies heavily on Geographic Information System (GIS) data. With respect to school children attending school in their home census tract, the vast majority does not in Philadelphia. Our analyses found that: (1) about 32% of the students walk across two or more census tracts going to school and 40% of them walk across four or more census blocks; and (2) 60% drive across four or more census tracts going to school and 50% drive across 10 or more census blocks. We also find that: (3) using a 5-min commuting time interval — as opposed to the modeled “trace” — results in misclassifying the “actual” path taken in 90% of the census blocks, 70% of the block groups, and 50% of the tracts; (4) a 1-min time interval is needed to reasonably resolve time spent in the various census unit designations; and (5) approximately 50% of both the homes and schools of Philadelphia school children are located within 160 m of highly traveled roads, and 64% of the schools are located within 200 m. These findings are very important when modeling school children's exposures, especially, when ascertaining the impacts of near-roadway concentrations on their total daily body burden. As many school children also travel along these streets and roadways to get to school, a majority of children in Philadelphia are in mobile source-dominated locations most of the day. We hypothesize that exposures of school children in Philadelphia to benzene and particulate matter will be much higher than if home and school locations and commuting paths at a 1-min time resolution are not explicitly modeled in an exposure assessment. Undertaking such an assessment will be the topic of a future paper.

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Acknowledgements

The LandScan work was done under contract to Oak Ridge National Laboratory through Interagency Agreement #DW89921830 funded by the US Environmental Protection Agency (EPA). Oak Ridge staffs who played an important role in the project include Eddie Bright and Marie Minner. We acknowledge their fine work on obtaining and organizing land use and GIS data in Philadelphia. We greatly acknowledge the fast work by Will Stevens of the Delaware Valley Regional Planning Commission to provide us with link-specific ADT data in Philadelphia. We also acknowledge the input provided by Dr. Lisa Baxter as part of EPA's internal review process; she sharpened up the focus of our paper. The two anonymous reviewer comments also made us clarify our wording in a number of places, and we appreciate their input. This paper has been subject to Agency review and approved for publication, but does not necessarily constitute an endorsement of our findings. Mention of trade names, commercial products, and organizations does not constitute endorsement or recommendation for use.

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Authors and Affiliations

  1. Division National Exposure Research Laboratory US Environmental Protection Agency, Human Exposure and Atmospheric Sciences, Research Triangle Park, North Carolina, USA

    Jianping Xue, Thomas McCurdy & Janet Burke

  2. Division Oak Ridge National Laboratory US Department of Energy, Computational Sciences & Engineering, Oak Ridge, Tennessee, USA

    Budhendra Bhaduri, Cheng Liu, James Nutaro & Lauren Patterson

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  1. Jianping Xue
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Correspondence to Thomas McCurdy.

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Xue, J., McCurdy, T., Burke, J. et al. Analyses of school commuting data for exposure modeling purposes. J Expo Sci Environ Epidemiol 20, 69–78 (2010). https://doi.org/10.1038/jes.2009.3

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