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dc.contributor.authorAdamkiewicz, Garyen_US
dc.contributor.authorHsu, Hsiao-Hsienen_US
dc.contributor.authorVallarino, Joseen_US
dc.contributor.authorMelly, Steven Jen_US
dc.contributor.authorSpengler, John Den_US
dc.contributor.authorLevy, Jonathan Ien_US
dc.date.accessioned2011-12-29T22:49:48Z
dc.date.available2011-12-29T22:49:48Z
dc.date.copyright2010en_US
dc.date.issued2010-11-17en_US
dc.identifier.citationAdamkiewicz, Gary, Hsiao-Hsien Hsu, Jose Vallarino, Steven J Melly, John D Spengler, Jonathan I Levy. "Nitrogen dioxide concentrations in neighborhoods adjacent to a commercial airport: a land use regression modeling study" Environmental Health 9:73. (2010)en_US
dc.identifier.issn1476-069Xen_US
dc.identifier.urihttp://hdl.handle.net/2144/2619
dc.description.abstractBACKGROUND: There is growing concern in communities surrounding airports regarding the contribution of various emission sources (such as aircraft and ground support equipment) to nearby ambient concentrations. We used extensive monitoring of nitrogen dioxide (NO2) in neighborhoods surrounding T.F. Green Airport in Warwick, RI, and land-use regression (LUR) modeling techniques to determine the impact of proximity to the airport and local traffic on these concentrations. METHODS: Palmes diffusion tube samplers were deployed along the airport's fence line and within surrounding neighborhoods for one to two weeks. In total, 644 measurements were collected over three sampling campaigns (October 2007, March 2008 and June 2008) and each sampling location was geocoded. GIS-based variables were created as proxies for local traffic and airport activity. A forward stepwise regression methodology was employed to create general linear models (GLMs) of NO2 variability near the airport. The effect of local meteorology on associations with GIS-based variables was also explored. RESULTS: Higher concentrations of NO2 were seen near the airport terminal, entrance roads to the terminal, and near major roads, with qualitatively consistent spatial patterns between seasons. In our final multivariate model (R2 = 0.32), the local influences of highways and arterial/collector roads were statistically significant, as were local traffic density and distance to the airport terminal (all p < 0.001). Local meteorology did not significantly affect associations with principal GIS variables, and the regression model structure was robust to various model-building approaches. CONCLUSION: Our study has shown that there are clear local variations in NO2 in the neighborhoods that surround an urban airport, which are spatially consistent across seasons. LUR modeling demonstrated a strong influence of local traffic, except the smallest roads that predominate in residential areas, as well as proximity to the airport terminal.en_US
dc.description.sponsorshipFederal Aviation Administration through AiR Transportation Noise and Emissions Reduction (07-C-NE-HU)en_US
dc.language.isoenen_US
dc.publisherBioMed Centralen_US
dc.rightsCopyright 2010 Adamkiewicz et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.en_US
dc.rights.urihttp://creativecommons.org/licenses/by/2.0en_US
dc.titleNitrogen Dioxide Concentrations in Neighborhoods Adjacent to a Commercial Airport: A Land Use Regression Modeling Studyen_US
dc.typearticleen_US
dc.identifier.doi10.1186/1476-069X-9-73en_US
dc.identifier.pubmedid21083910en_US
dc.identifier.pmcid2996366en_US


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Copyright 2010 Adamkiewicz et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Except where otherwise noted, this item's license is described as Copyright 2010 Adamkiewicz et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.