Evidence map›Paper›PMID 34328919›Full record

ArticleThe Science of the total environment2021

Predicting wildfire particulate matter and hypothetical re-emission of radiological Cs-137 contamination incidents.

Kirk R Baker, Sang Don Lee, Paul Lemieux, Scott Hudson, Benjamin N Murphy, Jesse O Bash, Shannon N Koplitz, Thien Khoi V Nguyen, Wei Min Hao, Stephen Baker and 1 more

Abstract read
In one paragraph

Article in The Science of the total environment, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Youth Suicidality in the Context of Disasters.Current psychiatry reports · 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

11 authors.

Kirk R BakerU.S. Environmental Protection Agency, Research Triangle Park, NC, USA. Electronic address: baker.kirk@epa.gov.
Sang Don LeeU.S. Environmental Protection Agency, Research Triangle Park, NC, USA.
Paul LemieuxU.S. Environmental Protection Agency, Research Triangle Park, NC, USA.
Scott HudsonU.S. Environmental Protection Agency, Cincinnati, OH, USA.
Benjamin N MurphyU.S. Environmental Protection Agency, Research Triangle Park, NC, USA.
Jesse O BashU.S. Environmental Protection Agency, Research Triangle Park, NC, USA.
Shannon N KoplitzU.S. Environmental Protection Agency, Research Triangle Park, NC, USA.
Thien Khoi V NguyenU.S. Environmental Protection Agency, San Francisco, CA, USA.
Wei Min HaoMissoula Fire Sciences Laboratory, Rocky Mountain Research Station, US Forest Service, Missoula, MT, USA.
Stephen BakerMissoula Fire Sciences Laboratory, Rocky Mountain Research Station, US Forest Service, Missoula, MT, USA.
Emily LincolnMissoula Fire Sciences Laboratory, Rocky Mountain Research Station, US Forest Service, Missoula, MT, USA.

Funding

Intramural EPA EPA999999
6 · The paper itself

Abstract

Radiological release incidents can potentially contaminate widespread areas with radioactive materials and decontamination efforts are typically focused on populated areas, which means radionuclides may be left in forested areas for long periods of time. Large wildfires in contaminated forested areas have the potential to reintroduce these radionuclides into the atmosphere and cause exposure to first responders and downwind communities. One important radionuclide contaminant released from radiological incidents is radiocesium (

Indexed as

Air PollutantsWildfiresCesium RadioisotopesEnvironmental MonitoringParticulate MatterSmokeAir PollutantsCesium-137Cesium RadioisotopesParticulate MatterSmokeCesiumCMAQPM2.5Wildfire

Identifiers

PMID34328919
PMCPMC9019821

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.