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Spatiotemporal Patterns of Ultrafine Particle Counts and Fine Particle Mass in Neighborhoods Surrounding an Airport

Hsu, Hsiao-Hsien1; Adamkiewicz, Gary1; Houseman, Andres1; Vallarino, Jose1; Melly, Steven1; Wayson, Roger2; Spengler, John1; Levy, Jonathan1

doi: 10.1097/01.ede.0000392322.95904.39
Abstracts: ISEE 22nd Annual Conference, Seoul, Korea, 28 August–1 September 2010: Air Pollution - Exposure Characterization and Health Effects

1Harvard School of Public Health, Boston, MA; and 2Volpe National Transportation Systems Center, Cambridge, MA.

Abstracts published in Epidemiology have been reviewed by the societies at whose meetings the abstracts have been accepted for presentation. These abstracts have not undergone review by the Editorial Board of Epidemiology.


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Previous studies have demonstrated significant contributions from aircraft to ultrafine particle counts near airports, but studies to date have not characterized spatial patterns in residential settings near airports and have not formally isolated the contribution of aircraft from other local sources. In this study, our objective was to determine the contribution of landing and takeoff (LTO) activity to concentrations of ultrafine particles as well as fine particulate matter (PM2.5) near TF Green Airport in Warwick, RI.

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A mobile monitoring protocol was implemented in 2 one-week campaigns in the spring and summer of 2008. Field teams were outfitted with backpacks containing water-based condensation particle counters to measure ultrafine particle levels, continuous monitors for PM2.5, and a GPS. Mobile sampling routes captured neighborhoods in all compass directions and were implemented to ensure sufficient spatiotemporal coverage. Regression models included as predictors of concentrations meteorological characteristics, source terms, and distance variables. To better pinpoint the timing in the LTO cycle most contributing to elevated concentrations, and to capture variability across aircraft and the spatiotemporal complexity of our data, we used distributed lag models for flight activity and incorporated emissions proxies for all individual aircraft.

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Results suggest significant positive associations between ultrafine particle concentrations and both departures and arrivals, with departures having larger effects and the distributed lag modeling indicating the strongest association with predeparture taxing and the take-off process. Causal linkages with the LTO cycle were further enhanced by generalized additive models for wind speed and direction, which demonstrate an enhanced signal from LTO activities at higher wind speeds with a greater indication of local traffic contributions at low wind speeds.

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Our analysis allows for quantification of the marginal contribution of airport sources and characterization of spatiotemporal concentration patterns, providing insight for urban communities regarding the impact of airport activities on local air quality.

© 2011 Lippincott Williams & Wilkins, Inc.