Evidence map›Paper›PMID 36003366›Full record

ArticleAgricultural and forest meteorology2022

Real-time automatic detection of starch particles in ambient air.

Branko Šikoparija, Predrag Matavulj, Gordan Mimić, Matt Smith, Łukasz Grewling, Zorica Podraščanin

Open access · hybridAbstract read
In one paragraph

Article in Agricultural and forest meteorology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.7field-weighted citation impact, top 17% 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, 16 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. 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

6 authors at 3 institutions in 3 countries.

Branko ŠikoparijaBioSensе Institute-Research Institute for Information Technologies in Biosystems, University of Novi Sad, Dr Zorana Djindjica 1, Novi Sad 21000, Serbia.
Predrag MatavuljBioSensе Institute-Research Institute for Information Technologies in Biosystems, University of Novi Sad, Dr Zorana Djindjica 1, Novi Sad 21000, Serbia.
Gordan MimićBioSensе Institute-Research Institute for Information Technologies in Biosystems, University of Novi Sad, Dr Zorana Djindjica 1, Novi Sad 21000, Serbia.
Matt SmithSchool of Science and the Environment, University of Worcester, UK.
Łukasz GrewlingLaboratory of Aerobiology, Department of Systematic and Environmental Botany, Adam Mickiewicz University, Poznań, Poland.
Zorica PodraščaninDepartment of Physics, Faculty of Sciences, University of Novi Sad, Novi Sad, Serbia.
University of Novi Sad · RSAdam Mickiewicz University in Poznań · PLUniversity of Worcester · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Considerable amounts of starch granules can be present in the atmosphere from both natural and anthropogenic sources. The aim of this study is to investigate the variability and potential origin of starch granules in ambient air recorded at six cities situated in a region with dominantly agricultural land use. This is achieved by using a combination of laser spectroscopy bioaerosol measurements with 1 min temporal resolution, traditional volumetric Hirst type bioaerosol sampling and atmospheric modelling. The analysis of wind roses identified potential sources of airborne starch (i.e., cereal grain storage facilities) in the vicinity of all aerobiological stations analysed in this study. The analysis of the CALPUFF dispersion model confirmed that emission of dust from the location of storage towers situated about 2.5 km north of the aerobiological station in Novi Sad is a plausible source of high airborne concentrations of starch granules. This study is important for environmental health since it contributes body of knowledge about sources, emission, and dispersion of airborne starch, known to be involved in phenomena such as thunderstorm-triggered asthma. The presented approach integrates monitoring and modelling, and provides a roadmap for examining a variety of bioaerosols previously considered to be outside the scope of traditional aerobiological measurements.

Indexed as

AerobiologyAirborne starchAutomatic monitoringDispersion modellingEmission sources

Identifiers

PMID36003366
PMCPMC9391928
OpenAlexW4281672658

What OpenQuestion holds

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LicenceCC BY
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.