Evidence map›Paper›PMID 31251121›Full record

ArticleJournal of occupational and environmental hygiene2019

Sources of error and variability in particulate matter sensor network measurements.

Christopher Zuidema, Larissa V Stebounova, Sinan Sousan, Geb Thomas, Kirsten Koehler, Thomas M Peters

Open access · greenAbstract read
In one paragraph

Article in Journal of occupational and environmental hygiene, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 22% of its field
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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. 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

6 authors at 3 institutions in 1 country.

Christopher Zuidemaa Department of Environmental and Occupational Health Sciences , University of Washington , Seattle , Washington.ORCID 0000-0002-2233-2706
Larissa V Stebounovab Department of Occupational and Environmental Health , University of Iowa , Iowa City , Iowa.
Sinan Sousanb Department of Occupational and Environmental Health , University of Iowa , Iowa City , Iowa.
Geb Thomasd Department of Industrial and Systems Engineering , University of Iowa , Iowa City , Iowa.ORCID 0000-0001-5032-4001
Kirsten Koehlere Department of Environmental Health and Engineering , Johns Hopkins Bloomberg School of Public Health , Baltimore , Maryland.
Thomas M Petersb Department of Occupational and Environmental Health , University of Iowa , Iowa City , Iowa.ORCID 0000-0002-1698-8856
University of Iowa · USJohns Hopkins University · USUniversity of Washington · US

Funding

Pulmonary Toxicology Facility CoreP30ES005605 · NIEHS · UNIVERSITY OF IOWA · PI Brandi Janssen · 1990 to 2026
$40.5M
Targeted Research Training CoreT42OH008428 · OH · JOHNS HOPKINS UNIVERSITY · PI RAMACHANDRAN, GURUMURTHY · 2005 to 2025
$31.1M
Biostatistics, Epidemiologic & Bioinformatic Training in Environmental HealthT32ES015459 · NIEHS · UNIVERSITY OF WASHINGTON · PI June T. Spector · 2009 to 2026
$10.6M
An Inexpensive Monitoring Network to Assess Workplace Aerosol ExposuresR01OH010533 · OH · JOHNS HOPKINS UNIVERSITY · PI KOEHLER, KIRSTEN ANNE, PETERS, THOMAS MICHAEL · 2014 to 2017
$1.9M
NIEHS NIH HHS P30 ES005605NIEHS NIH HHS T32 ES015459NIOSH CDC HHS R01 OH010533NIOSH CDC HHS T42 OH008428
6 · The paper itself

Abstract

The quality of mass concentration estimates from increasingly popular networks of low-cost particulate matter sensors depends on accurate conversion of sensor output (e.g., voltage) into gravimetric-equivalent mass concentration, typically using a calibration procedure. This study evaluates two important sources of variability that lead to error in estimating gravimetric-equivalent mass concentration: the temporal changes in sensor calibration and the spatial and temporal variability in gravimetric correction factors. A 40-node sensor network was deployed in a heavy vehicle manufacturing facility for 8 months. At a central location in the facility, particulate matter was continuously measured with three sensors of the network and a traditional, higher-cost photometer, determining the calibration slope and intercept needed to translate sensor output to photometric-equivalent mass concentration. Throughout the facility, during three intensive sampling campaigns, respirable mass concentrations were measured with gravimetric samplers and photometers to determine correction factors needed to adjust photometric-equivalent to gravimetric-equivalent mass concentration. Both field-determined sensor calibration slopes and intercepts were statistically different than those estimated in the laboratory (α = 0.05), emphasizing the importance of aerosol properties when converting voltage to photometric-equivalent mass concentration and the need for field calibration to determine slope. Evidence suggested the sensors' weekly field calibration slope decreased and intercept increased, indicating the sensors were deteriorating over time. The mean correction factor in the cutting and shot blasting area (2.9) was substantially and statistically lower than that in the machining and welding area (4.6; p = 0.01). Therefore, different correction factors should be determined near different occupational processes to accurately estimate particle mass concentrations.

Indexed as

Air PollutantsCalibrationEnvironmental MonitoringManufacturing and Industrial FacilitiesMotor VehiclesOccupational ExposureParticulate MatterAir PollutantsParticulate MatterCorrection factorfield calibrationlow-cost sensorsparticle compositionparticulate matter concentration photometer

Identifiers

PMID31251121
PMCPMC6954050
OpenAlexW2955620993

What OpenQuestion holds

Textmetadata
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Read underepoch 390

Registered trials

None linked

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.