Evidence map›Paper›PMID 34554459›Full record

ReviewBiologia futura2020

Biological treatment of coke plant effluents: from a microbiological perspective.

Tamás Felföldi, Zsuzsanna Nagymáté, Anna J Székely, Laura Jurecska, Károly Márialigeti

Abstract readReview
PubMed Publisher
In one paragraph

Review in Biologia futura, 2020. 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.

Tamás FelföldiDepartment of Microbiology, ELTE Eötvös Loránd University, Pázmány Péter stny. 1/c., Budapest, 1117, Hungary. tamas.felfoldi@ttk.elte.hu.ORCID http://orcid.org/0000-0003-2009-2478
Zsuzsanna NagymátéDepartment of Microbiology, ELTE Eötvös Loránd University, Pázmány Péter stny. 1/c., Budapest, 1117, Hungary.
Anna J SzékelyDepartment of Ecology and Genetics/Limnology, Uppsala University, Norbyvägen 18 D, 75236, Uppsala, Sweden.
Laura JurecskaDepartment of Microbiology, ELTE Eötvös Loránd University, Pázmány Péter stny. 1/c., Budapest, 1117, Hungary.
Károly MárialigetiDepartment of Microbiology, ELTE Eötvös Loránd University, Pázmány Péter stny. 1/c., Budapest, 1117, Hungary.

Funding

János Bolyai Research Scholarship of the Hungarian Academy of Sciences BO/00837/20/8
6 · The paper itself

Abstract

During coke production, large volume of effluent is generated, which has a very complex chemical composition and contains several toxic and carcinogenic substances, mainly aromatic compounds, cyanide, thiocyanate and ammonium. The composition of these high-strength effluents is very diverse and depends on the quality of coals used and the operating and technological parameters of coke ovens. In general, after initial physicochemical treatment, biological purification steps are applied in activated sludge bioreactors. This review summarizes the current knowledge on the anaerobic and aerobic transformation processes and describes key microorganisms, such as phenol- and thiocyanate-degrading, floc-forming, nitrifying and denitrifying bacteria, which contribute to the removal of pollutants from coke plant effluents. Providing the theoretical basis for technical issues (in this case the microbiology of coke plant effluent treatment) aids the optimization of existing technologies and the design of new management techniques.

Indexed as

CokeHumansIndustrial WasteMetallurgySewageWaste Disposal, FluidWater QualityCokeIndustrial WasteSewageActivated sludgeBioreactorPhenolsThiocyanateToxic compounds

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.