Evidence map›Paper›PMID 37323133›Full record

ArticleWater, air, and soil pollution2023

Efficient Removal of Analgesic and Anti-Inflammatory Drugs from Sewage Treatment Plant Effluents Using Magnetite Nanoparticles Synthesized Red Mud.

Senar Aydın, Arzu Ulvi, Fatma Bedük, Mehmet Emin Aydın

Abstract read
In one paragraph

Article in Water, air, and soil pollution, 2023. 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. 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

4 authors.

Senar AydınDepartment of Environmental Engineering, Necmettin Erbakan University, Konya, Türkiye.ORCID 0000-0002-0960-480X
Arzu UlviDepartment of Environmental Engineering, Necmettin Erbakan University, Konya, Türkiye.
Fatma BedükDepartment of Environmental Engineering, Necmettin Erbakan University, Konya, Türkiye.
Mehmet Emin AydınDepartment of Civil Engineering, Necmettin Erbakan University, Konya, Türkiye.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Due to the COVID-19 epidemic, the consumption of pharmaceuticals, especially paracetamol, has sharply increased on a global scale. The increasing concentration of analgesic and anti-inflammatory drugs (AAIDs) in the aquatic medium is a global problem for human and aquatic life. Therefore, simple and effective treatment options for removing AAIDs from wastewater after the COVID-19 pandemic are needed. The removal of AAIDs (acetaminophen, acetylsalicylic acid, codeine, diclofenac, ibuprofen, indomethacin, ketoprofen, mefenamic acid, naproxen, and phenylbutazone) from sewage treatment plant (STP) effluents by the prepared magnetite nanoparticles synthesized from red mud (mNPs-RM) is presented for the first time in this study. The removal efficiencies of AAIDs onto mNPs-RM were determined to be between 90% (diclofenac) and 100% (naproxen, codeine, and indomethacin). Acetaminophen (paracetamol) was used as a model compound in kinetic and isotherm model studies. The adsorption of acetaminophen was matched well with the pseudo second order kinetic model. Film diffusion governed its rate mechanism. The Freundlich isotherm model preferably fitted the adsorption data with an adsorption capacity of 370 mg/g at 120 min contact time at pH 7.0 at 25 °C. Furthermore, the regenerated mNPs-RM were used four times without affecting the adsorption capacity and the magnetic separability. mNPs-RM can be used as a simple, inexpensive and effective adsorbent for removing AAIDs from STP effluents. Also, low cost adsorbent obtained from industrial waste could be employed to replace the high cost activated carbons for the adsorption of other micro pollutants in STP effluents. Supplementary Information: The online version contains supplementary material available at 10.1007/s11270-023-06404-7.

Indexed as

Anti-inflammatory/analgesic pharmaceuticalsEffluent, magnetic nanoparticlesRed mudSewage treatment plant

Identifiers

PMID37323133
PMCPMC10249540

What OpenQuestion holds

Textmetadata
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Registered trials

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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.