Impact of Mobile Sources on Near-Roadway Exposures and Respiratory Effects for Childhood Asthmatics

ALAN VETTE (1), Stuart Batterman (2), Michael Breen (1), Vlad Isakov (1), Steven Perry (1), David Heist (1), Gary Norris (1), Toby Lewis (3), Thomas Robins (2), Francois Dion (4), Bhramar Mukherjee (2), and the Community Action Against Asthma Steering Committee (5)

(1) U.S. EPA, National Exposure Research Laboratory, RTP, NC; (2) University of Michigan, School of Public Health, Ann Arbor, MI, (3) University of Michigan, Medical School, Ann Arbor, MI, (4) University of Michigan, Transportation Research Institute, Ann Arbor, MI; and (5) Detroit, MI

     Abstract Number: 243
     Last modified: November 9, 2009

Abstract
This paper describes a planned study to examine the relationship between near-roadway exposures to air pollutants and respiratory health in a cohort of asthmatic children who live close to major roadways in Detroit, MI. The study will investigate the effects of traffic-associated exposures on exaggerated airway responses, biomolecular responses of inflammatory and oxidative stress, and how these exposures affect the frequency and severity of adverse respiratory outcomes. The study will also examine different near-road exposure assessment metrics, including monitoring and modeling techniques.
The study cohort will involve up to 105 children, ages 6 to 13 years, with persistent asthma who are recruited based on their residential proximity to different types of roadways. Participant groups will be drawn from homes located: (1) within 150m of high traffic/high truck volume roads; (2) within 150m of high traffic/low truck volume roads; or (3) more than 300m from moderate-to-high traffic roads. The study will evaluate three respiratory health effect domains potentially associated with exposures to near-road air pollutants: asthma aggravation (lung function and symptoms); inflammation and oxidative stress responses (exhaled nitric oxide and nasal cytokines); and respiratory viral infections (frequency, severity and type). Seasonal health assessments will be performed in each season from March 2010 through May 2011 to collect health measures and biomarkers relevant to pulmonary function, medication and health care use, diary reports of upper respiratory infection symptoms, fraction of exhaled nitric oxide and nasal lavage.
Exposure metrics of varying complexity will be developed to determine their utility in examining associations with observed health effects. The tiered exposure assessment approach combines observational data of key exposure determinants along with predictive models to estimate near-road outdoor air pollution and exposures. Concentrations of traffic-related air pollutants (e.g. black carbon, nitrogen oxides, carbon monoxide and particle counts) will be measured and modeled indoors and outdoors of the children’s homes. Measurements will be made in a subset of homes each during fall 2010 and early spring 2011; both are peak seasons for asthma and viral infections in Detroit. High-time resolution measurements will be made of the chemical composition of traffic-related pollutants in the gas and particle phases adjacent to a roadway. These data will be used to quantify the impact of traffic on the observed air quality data. Air pollutant dispersion and exposure models will be used in combination with measured data to estimate indoor/outdoor concentrations and personal exposures. Near-road spatial concentration patterns will be estimated at the children’s residences and schools across the study domain using dispersion modeling. These data will be used as input for an individual-level exposure model to estimate personal exposures from meteorology and questionnaire data on indoor sources, residential characteristics and operation, and time-location-activity patterns.
The combination of monitoring and modeling data will provide several tiers of exposure information to correlate with observed respiratory outcomes. These approaches will be used to examine the relative importance of exposure metrics with varying amounts of complexity and spatiotemporal resolution.