Evidence map›Paper›PMID 27848134›Full record

ArticleEnvironmental science and pollution research international2017

Fine and ultrafine particle doses in the respiratory tract from digital printing operations.

Aristeidis Voliotis, Irene Karali, Athanasios Kouras, Constantini Samara

Abstract read
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In one paragraph

Article in Environmental science and pollution research international, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. TMT-Based Quantitative Proteomics Analysis Reveals Airborne PMInternational journal of environmental research and public health · 2018
    Article
  5. Article
  6. 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

4 authors.

Aristeidis VoliotisEnvironmental Pollution Control Laboratory, Department of Chemistry, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece. voliotis@chem.auth.gr.
Irene KaraliEnvironmental Pollution Control Laboratory, Department of Chemistry, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece.
Athanasios KourasEnvironmental Pollution Control Laboratory, Department of Chemistry, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece.
Constantini SamaraEnvironmental Pollution Control Laboratory, Department of Chemistry, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, we report for the first time particle number doses in different parts of the human respiratory tract and real-time deposition rates for particles in the 10 nm to 10 μm size range emitted by digital printing operations. Particle number concentrations (PNCs) and size distribution were measured in a typical small-sized printing house using a NanoScan scanning mobility particle sizer and an optical particle sizer. Particle doses in human lung were estimated applying a multiple-path particle dosimetry model under two different breathing scenarios. PNC was dominated by the ultrafine particle fractions (UFPs, i.e., particles smaller than 100 nm) exhibiting almost nine times higher levels in comparison to the background values. The average deposition rate fοr each scenario in the whole lung was estimated at 2.0 and 2.9 × 10

Indexed as

PrintingAir PollutantsAir Pollution, IndoorHumansInhalation ExposureLungModels, TheoreticalParticle SizeParticulate MatterAir PollutantsParticulate MatterDigital printingIndoor airLung depositionOccupational exposureUltrafine particles

Identifiers

What OpenQuestion holds

Textmetadata
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.