Nitrogen Dioxide Concentrations in Neighborhoods Adjacent to a Commercial Airport: A Land Use Regression Modeling Study

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dc.contributor.author Adamkiewicz, Gary en_US
dc.contributor.author Hsu, Hsiao-Hsien en_US
dc.contributor.author Vallarino, Jose en_US
dc.contributor.author Melly, Steven J en_US
dc.contributor.author Spengler, John D en_US
dc.contributor.author Levy, Jonathan I en_US
dc.date.accessioned 2011-12-29T22:49:48Z
dc.date.available 2011-12-29T22:49:48Z
dc.date.copyright 2010 en_US
dc.date.issued 2010-11-17 en_US
dc.identifier.citation Adamkiewicz, 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.issn 1476-069X en_US
dc.identifier.uri http://hdl.handle.net/2144/2619
dc.description.abstract BACKGROUND: 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.sponsorship Federal Aviation Administration through AiR Transportation Noise and Emissions Reduction (07-C-NE-HU) en_US
dc.language.iso en en_US
dc.publisher BioMed Central en_US
dc.rights 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. en_US
dc.rights.uri http://creativecommons.org/licenses/by/2.0 en_US
dc.title Nitrogen Dioxide Concentrations in Neighborhoods Adjacent to a Commercial Airport: A Land Use Regression Modeling Study en_US
dc.type article en_US
dc.identifier.doi 10.1186/1476-069X-9-73 en_US
dc.identifier.pubmedid 21083910 en_US
dc.identifier.pmcid 2996366 en_US

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