Evidence map›Paper›PMID 31098950›Full record

ArticleEnvironmental geochemistry and health2019

Characterization, concentration and risk assessment of airborne particles using car engine air filter (case study: Tehran metropolis).

Fatemeh Ahmadipour, Abbas Esmaeili Sari, Nader Bahramifar

Abstract read
PubMed Publisher
In one paragraph

Article in Environmental geochemistry and health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Comparative review of ambient air PMJournal of environmental health science & engineering · 2023
    Review
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

3 authors.

Fatemeh AhmadipourDepartment of Environmental Sciences, Faculty of Natural Resources and Marine Sciences, Tarbiat Modares University, Noor, Mazandaran, Iran. fahmadipour@gmail.com.
Abbas Esmaeili SariDepartment of Environmental Sciences, Faculty of Natural Resources and Marine Sciences, Tarbiat Modares University, Noor, Mazandaran, Iran.
Nader BahramifarDepartment of Environmental Sciences, Faculty of Natural Resources and Marine Sciences, Tarbiat Modares University, Noor, Mazandaran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Atmospheric elements released into the atmosphere can enter the human body through inhalation, ingestion and dermal contact and are then deposited in the body. Trace elements have potential risks to human health. For this purpose, the particulate matter accumulated by car air filters (CAFs) was studied. The morphology and distribution of particle size were examined using scanning electron microscopy and energy-dispersive X-ray spectroscopy. The concentration of elements in CAFs and CAF-estimated air for 30 elements in Tehran, Iran, was analyzed in winter and summer, from February to July 2017. Samples were determined by inductively coupled mass plasma spectrometry. The most abundantly detected elements in both CAFs and air in both seasons were Ca, Mg, Na and Fe. The shape of the particles was mostly irregular and spherical. Most of the particles were between 0.5 and 1.0 µm. The carcinogenic risks of inhalation exposure to Cr and Co in winter and summer were higher than the acceptable level (< 1 × 10

Indexed as

AdultAir FiltersAir PollutantsAutomobilesCarcinogensChildEnvironmental MonitoringHumansInhalation ExposureIranMetalsMicroscopy, Electron, ScanningParticle SizeParticulate MatterRisk AssessmentSeasonsAir PollutantsCarcinogensMetalsParticulate MatterCar engine air filterElementsHealth risk assessmentIranTehran

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.