Evidence map›Paper›PMID 32209498›Full record

ArticleEnvironmental research2020

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

Jennifer L Moutinho, Donghai Liang, Rachel Golan, Stefanie T Ebelt, Rodney Weber, Jeremy A Sarnat, Armistead G Russell

Abstract read
In one paragraph

Article in Environmental research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Association of PMNeurology · 2024
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Jennifer L MoutinhoSchool of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, USA.
Donghai LiangDepartment of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, USA. Electronic address: donghai.liang@emory.edu.
Rachel GolanDepartment of Public Health, Ben-Gurion University of the Negev, Beer Sheva, Israel.
Stefanie T EbeltDepartment of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, USA.
Rodney WeberSchool of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, USA.
Jeremy A SarnatDepartment of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, USA.
Armistead G RussellSchool of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, USA.

Funding

Pilot Project ProgramP30ES019776 · NIEHS · EMORY UNIVERSITY · PI Carmen Joseph Marsit · 2013 to 2026
$22.6M
NIEHS NIH HHS P30 ES019776
6 · The paper itself

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.

Indexed as

Air PollutantsAir PollutionTraffic-Related PollutionEcosystemEnvironmental MonitoringHumansVehicle EmissionsAir PollutantsVehicle EmissionsExposure assessmentIntegrated mobile source indicatorMultipollutant exposure metricNear-road environmentTraffic-related air pollution

Identifiers

PMID32209498
PMCPMC7202092

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.