Evidence map›Paper›PMID 38933980›Full record

ArticleHeliyon2024

Separation processes for the treatment of industrial flue gases - Effective methods for global industrial air pollution control.

Francis B Elehinafe, Ephraim A Aondoakaa, Akinnike F Akinyemi, Oluranti Agboola, Oyetunji B Okedere

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

5 authors.

Francis B ElehinafeDepartment of Chemical Engineering, College of Engineering, Covenant University, Ota, Ogun State, Nigeria.
Ephraim A AondoakaaDepartment of Chemical Engineering, College of Engineering, Covenant University, Ota, Ogun State, Nigeria.
Akinnike F AkinyemiDepartment of Chemical Engineering, College of Engineering, Covenant University, Ota, Ogun State, Nigeria.
Oluranti AgboolaDepartment of Chemical Engineering, College of Engineering, Covenant University, Ota, Ogun State, Nigeria.
Oyetunji B OkedereDepartment of Chemical Engineering, Faculty of Engineering, Osun State University, Osogbo, Ogun State, Nigeria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The treatment of flue gases has become a crucial area of interest with the increasing air emissions into the atmosphere from industries involved in combustion of fossil fuels in their operations. In essence, there is a critical need for effective methods of treatment more than ever. Treatment and separation are now a demand for the overall industrial operations to control the rate of flue gas emissions. The major culprit in this wise is power generating industry. The major associated air pollutants are carbon dioxide, sulfur oxides, trace metals, volatile organic compounds, particulate matters, and nitrogen oxides. However, the choice of technologies to be utilized requires more than just knowledge of the separation process, but also a good understanding of the properties of the pollutants. This review explored and evaluated the various separation processes and technologies for the treatment of industrial flue gases for the control of the associated air pollutants. It also analyzed the performance with references to cost and efficiency, the advantages and disadvantages, principles for selection, research direction, and/or potential opportunities in existing separation processes and technologies.

Indexed as

Air pollutionControlFlue gasesSeparation processesTreatment

Identifiers

PMID38933980
PMCPMC11200353

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.