Evidence map›Paper›PMID 35909454›Full record

ArticleSustainability2022

A Real-Time Comparison of Four Particulate Matter Size Fractions in the Personal Breathing Zone of Paris Subway Workers: A Six-Week Prospective Study.

Rémy Pétremand, Guillaume Suárez, Sophie Besançon, J Hugo Dil, Irina Guseva Canu

Abstract read
In one paragraph

Article in Sustainability, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

5 authors.

Rémy PétremandDepartment of Occupational and Environmental Health, Center of Primary Care and Public Health (Unisanté), University of Lausanne, Epalinges, 1066 Lausanne, Switzerland; remy.petremand@chuv.ch (R.P.); guillaume.suarez@unisante.ch (G.S.).ORCID https://orcid.org/0000-0002-7629-7336
Guillaume SuárezDepartment of Occupational and Environmental Health, Center of Primary Care and Public Health (Unisanté), University of Lausanne, Epalinges, 1066 Lausanne, Switzerland; remy.petremand@chuv.ch (R.P.); guillaume.suarez@unisante.ch (G.S.).
Sophie BesançonRégie Automne de Transport Parisien (RATP), 75012 Paris, France; sophie.besancon@ratp.fr.
J Hugo DilInstitute of Physics, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland; hugo.dil@epfl.ch.ORCID https://orcid.org/0000-0002-6016-6120
Irina Guseva CanuDepartment of Occupational and Environmental Health, Center of Primary Care and Public Health (Unisanté), University of Lausanne, Epalinges, 1066 Lausanne, Switzerland; remy.petremand@chuv.ch (R.P.); guillaume.suarez@unisante.ch (G.S.).ORCID https://orcid.org/0000-0001-7059-8421

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We developed a Bayesian spline model for real-time mass concentrations of particulate matter (PM10, PM2.5, PM1, and PM0.3) measured simultaneously in the personal breathing zone of Parisian subway workers. The measurements were performed by GRIMM, a gravimetric method, and DiSCmini during the workers' work shifts over two consecutive weeks. The measured PM concentrations were analyzed with respect to the working environment, the underground station, and any specific events that occurred during the work shift. Overall, PM0.3 concentrations were more than an order of magnitude lower compared to the other PM concentrations and showed the highest temporal variation. The PM2.5 levels raised the highest exposure concern: 15 stations out of 37 had higher mass concentrations compared to the reference. Station PM levels were not correlated with the annual number of passengers entering the station, the year of station opening or renovation, or the number of platforms and tracks. The correlation with the number of station entrances was consistently negative for all PM sizes, whereas the number of correspondence concourses was negatively correlated with PM0.3 and PM10 levels and positively correlated with PM1 and PM2.5 levels. The highest PM10 exposure was observed for the station platform, followed by the subway cabin and train, while ticket counters had the highest PM0.3, PM1, and PM2.5 mass concentrations. We further found that compared to gravimetric and DiSCmini measurements, GRIMM results showed some discrepancies, with an underestimation of exposure levels. Therefore, we suggest using GRIMM, calibrated by gravimetric methods, for PM sizes above 1μm, and DiSCmini for sizes below 700 nm.

Indexed as

Bayesian spline modelinhalationoccupational exposureparticulate matterpublic transporttime-series

Identifiers

PMID35909454
PMCPMC9170000

What OpenQuestion holds

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LicenceCC BY
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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.