Evaluating a multipollutant metric for use in characterizing traffic-related air pollution exposures within near-road environments

• Type of Material: Article
• Authors: Jennifer L. Moutinho, Georgia Institute of Technology; Donghai Liang, Emory University; Rachel Golan, Ben Gurion University of the Negev; Stefanie Ebelt, Emory University; Rodney Weber, Georgia Institute of Technology; Jeremy Sarnat, Emory University; Armistead G. Russell, Georgia Institute of Technology
• Language: English
• Date: 2020-05-01
• Publisher: Academic Press Inc. Elsevier Science
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2020 Elsevier Inc. All rights reserved.
• License: Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1016/j.envres.2020.109389
• Title of Journal or Parent Work: Environmental Research
• Volume: 184
• Start Page: 109389
• End Page: 109389
• Grant/Funding Information: Dr. A Russell made use of funds provided by a generous gift from Howard T. Tellepson.; Support for this project were provided through a contract with the Health Effects Institute (RFA #4942-RFA13–1/14–3).; Dr. J Moutinho acknowledges that this material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. (NSF DGE-1650044).; This publication was also supported by the HERCULES Center P30ES019776 and the Emory Rollins School of Public Health Dean’s Pilot and Innovation Grant.; R Golan gratefully acknowledges support by a post-doctoral fellowship from the Environment and Health Fund, Jerusalem, Israel.
• Keywords: Quality; Science & Technology; Multipollutant exposure metric; Trends; Near-road environment; Integrated mobile source indicator; Environmental Sciences & Ecology; Public, Environmental & Occupational Health; Traffic-related air pollution; Characterization research; Exposure assessment; Vegetation; Environmental Sciences; Indicators; Emissions; Life Sciences & Biomedicine; Health; Single pollutant; Mortality
• Research Categories: Health Sciences, Public Health; Engineering, Environmental; Environmental Sciences

Abstract

Accurately characterizing human exposures to traffic-related air pollutants (TRAPs) is critical to public health protection. However, quantifying exposure to this single source is challenging, given its extremely heterogeneous chemical composition. Efforts using single-species tracers of TRAP are, thus, lacking in their ability to accurately reflect exposures to this complex mixture. There have been recent discussions centered on adopting a multipollutant perspective for sources with many emitted pollutants to maximize the benefits of control expenditures as well as to minimize population and ecosystem exposure. As part of a larger study aimed to assess a complete emission-to-exposure pathway of primary traffic pollution and understand exposure of individuals in the near-road environment, an intensive field campaign measured TRAPs and related data (e.g., meteorology, traffic counts, and regional air pollutant levels) in Atlanta along one of the busiest highway corridors in the US. Given the dynamic nature of the near-road environment, a multipollutant exposure metric, the Integrated Mobile Source Indicator (IMSI), which was generated based on emissions-based ratios, was calculated and compared to traditional single-species methods for assessing exposure to mobile source emissions. The current analysis examined how both traditional and non-traditional metrics vary spatially and temporally in the near-road environment, how they compare with each other, and whether they have the potential to offer more accurate means of assigning exposures to primary traffic emissions. The results indicate that compared to the traditional single pollutant specie, the multipollutant IMSI metric provided a more spatially stable method for assessing exposure, though variations occurred based on location with varying results among the six sites within a kilometer of the highway.