The Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS): Study design and methods

Abstract

The Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS) was designed to examine the relationship between near-roadway exposures to air pollutants and respiratory outcomes in a cohort of asthmatic children who live close to major roadways in Detroit, Michigan USA. From September 2010 to December 2012 a total of 139 children with asthma, ages 6–14, were enrolled in the study on the basis of the proximity of their home to major roadways that carried different amounts of diesel traffic. The goal of the study was to investigate the effects of traffic-associated exposures on adverse respiratory outcomes, biomolecular markers of inflammatory and oxidative stress, and how these exposures affect the frequency and severity of respiratory viral infections in a cohort of children with asthma. An integrated measurement and modeling approach was used to quantitatively estimate the contribution of traffic sources to near-roadway air pollution and evaluate predictive models for assessing the impact of near-roadway pollution on children’s exposures. Two intensive field campaigns were conducted in Fall 2010 and Spring 2011 to measure a suite of air pollutants including PM2.5 mass and composition, oxides of nitrogen (NO and NO2), carbon monoxide, and black carbon indoors and outdoors of 25 participants’ homes, at two area schools, and along a spatial transect adjacent to I-96, a major highway in Detroit. These data were used to evaluate and refine models to estimate air quality and exposures for each child on a daily basis for the health analyses. The study design and methods are described, and selected measurement results from the Fall 2010 field intensive are presented to illustrate the design and successful implementation of the study. These data provide evidence of roadway impacts and exposure variability between study participants that will be further explored for associations with the health measures.

A modeling framework for characterizing near-road air pollutant concentration at community scales

“…The STOK technique is implemented with BMElib (Bayesian Maximization Entropy library) (Serre, 1999). A detailed description of the STOK algorithm, which was developed and applied for the Near-road Exposures to Urban Air Pollutants Study (NEXUS) (Vette et al, 2013) in Detroit, MI, can be found in Arunachalam et al (2014). We applied this algorithm from Arunachalam et al (2014) to estimate hourly background concentrations at all receptors in each of the study domains.…”

“…Accurate characterization of exposure to air pollution from traffic is also important for environmental epidemiologic studies (Lobdell et al, 2011;Vette et al, 2013). However, estimating near-road exposure is challenging because of dynamic traffic conditions, multiple pollutants, the need to separate near-road and regional pollution, and the spatial and temporal resolution needed to document pollutants.…”

GPS-based microenvironment tracker (MicroTrac) model to estimate time–location of individuals for air pollution exposure assessments: Model evaluation in central North Carolina

“…2,3 To reduce exposure misclassification, we are developing an air pollution exposure model for individuals (EMI) in health studies. 4-6 The EMI predicts personal exposures based on outdoor concentrations, meteorology, questionnaire information (e.g., building characteristics, occupant behavior related to building operation and indoor sources), and time-location information. This study describes a critical aspect of EMI: the development and evaluation of a classification model, called MicroTrac, that estimates time of day and duration spent by individuals in eight ME (indoors and outdoors at home, work, school; inside vehicles; other locations) based on global positioning system (GPS) data and geocoded (geographic coordinates expressed as latitude and longitude) boundaries of buildings.…”

“…11 For individual exposure assessments, diaries from the study participants can be used. 4,12,13 However, diaries have limitations, including burden on participants, inaccuracies due to recall and reporting errors, and missing data.…”

Use of an exposure model to explore the impact of residential proximity to a highway on exposures to air pollutants of an ambient origin

“…The challenges associated with including commute-time exposure and indoor resident-specific sources are widely acknowledged and improvements are ongoing (Dias and Tchepel 2014;Vette et al 2013). Exposure while commuting is currently best handled by in-traffic exposure models (Dons et al 2014a) or LUR models that include traffic volumes/road source intensity.…”