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Contributions of Aircraft Activity, Local Sources and Meteorology to Ultrafine Particle Counts Near a Large Airport

Adamkiewicz, Gary1; Hsu, Hsiao-Hsien1; Melly, Steven1; Zarubiak, Darcy2; Spengler, John1; Levy, Jon1

doi: 10.1097/01.ede.0000392347.07581.a5
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 2Jacobs Consultancy, Dallas, TX.

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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Airport activities can potentially contribute to pollutant levels in nearby communities, but it is challenging to isolate the contributions of aircraft emissions from other sources near airports. As part of the Air Quality and Source Apportionment Study (AQSAS), ambient air pollutant and meteorological data were collected for 42 days during July and August of 2008 at fixed sites surrounding Los Angeles International Airport (LAX). In this analysis, we present the results of regression modeling that examines the association between one-minute average size-binned ultrafine particle concentrations and runway-specific Landing and Take-off (LTO) operations data and meteorology.

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In our regression models, wind speed and direction were included as a nonparametric smooth spatial term, using thin-plate splines applied to wind velocity vectors and fitted using linear mixed models. To better pinpoint the timing in the LTO cycle most contributing to elevated concentrations, we used distributed lag models for flight activity, ranging from 5 minutes before to 5 minutes after take-off or landing. Given the short-term measurements, we account for temporal autocorrelation by computing standard errors using a moving-block bootstrap.

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Generalized additive models for wind speed and direction suggest that ultrafine particle levels are associated with airport activities and local traffic sources, with a significant effect of wind direction only given high wind speeds. Model predictors varied significantly by size fraction, with smaller particle sizes demonstrating a greater signal from airport sources and larger particle sizes demonstrating a greater signal from local traffic. Distributed lag modeling suggests that departures contribute more significantly to ultrafine particle concentrations than arrivals, with the time patterns of contributions varying across monitors in a manner consistent with taxiways and flight paths.

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Our analytical approach allows for an enhanced understanding of ultrafine particle contributions from both aircraft and other sources proximate to large airports.

© 2011 Lippincott Williams & Wilkins, Inc.