Evidence map›Paper›PMID 31934794›Full record

ArticleEnvironmental health perspectives2020

Moving beyond Fine Particle Mass: High-Spatial Resolution Exposure to Source-Resolved Atmospheric Particle Number and Chemical Mixing State.

Qing Ye, Hugh Z Li, Peishi Gu, Ellis S Robinson, Joshua S Apte, Ryan C Sullivan, Allen L Robinson, Neil M Donahue, Albert A Presto

Abstract read
In one paragraph

Article in Environmental health perspectives, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Long-Term PMAnnals of the American Thoracic Society · 2025
    Pooled it
  2. Article
  3. Article
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

9 authors.

Qing YeCenter for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.
Hugh Z LiCenter for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.
Peishi GuCenter for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.
Ellis S RobinsonCenter for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.
Joshua S ApteDepartment of Civil, Architectural, and Environmental Engineering, University of Texas at Austin, Austin, Texas, USA.
Ryan C SullivanCenter for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.
Allen L RobinsonCenter for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.
Neil M DonahueCenter for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.
Albert A PrestoCenter for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMost epidemiological studies address health effects of atmospheric particulate matter (PM) using mass-based measurements as exposure surrogates. However, this approach ignores many critical physiochemical properties of individual atmospheric particles. These properties control the deposition of particles in the human lung and likely their toxicity; in addition, they likely have larger spatial variability than PM mass.

objectivesThis study was designed to quantify the spatial variability in number, size, source, and chemical mixing state of individual particles in a populous urban area. We quantified the population exposure to these detailed particle properties and compared them to mass-based exposures.

methodsWe performed mobile sampling using an advanced single-particle mass spectrometer to measure the spatial variability of number concentration of source-resolved

resultsParticle number concentration had a much larger spatial variability than mass concentration within the city. Freshly emitted particles from traffic and cooking drive the variability in particle number, but mass concentrations are dominated by aged background particles composed of secondary materials. In addition, people exposed to elevated number concentrations of atmospheric particles are also exposed to more externally mixed particles.

conclusionsOur advanced measurement technique provides a new exposure picture that resolves the large intra-city spatial heterogeneity in traffic and cooking particle number concentrations in the populous urban area. Our results provide a complementary and more detailed perspective compared with bulk measurements of composition. In addition, given the influence of particle mixing state on properties such as particle deposition in the lung, the large spatial gradients of chemical mixing state may significantly influence the health effects of fine PM. https://doi.org/10.1289/EHP5311.

Indexed as

Particulate MatterAir PollutantsAir PollutionEnvironmental ExposureEnvironmental MonitoringVehicle EmissionsAir PollutantsParticulate MatterVehicle Emissions

Identifiers

PMID31934794
PMCPMC7015569

What OpenQuestion holds

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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.