Evidence map›Paper›PMID 39362974›Full record

ArticleScientific reports2024

C/N ratio effect on oily wastewater treatment using column type SBR: machine learning prediction and metagenomics study.

Nadeem A Khan, Abhradeep Majumder, Simranjeet Singh, Praveen C Ramamurthy, Sandra Kathott Prakash, I H Farooqi, Nastaran Mozaffari, Dahiru U Lawal, Isam H Aljundi

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2024. 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. 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

9 authors.

Nadeem A KhanInterdisciplinary Research Center for Membranes and Water Security (IRC-MWS), King Fahd University of Petroleum and Minerals, 31261, Dhahran, Saudi Arabia. nadeem.khan@mecw.ac.in.
Abhradeep MajumderDepartment of Civil Engineering, Birla Institute of Technology and Science, Pilani Hyderabad Campus, Hyderabad, 500078, India.
Simranjeet SinghInterdisciplinary Centre for Water Research (ICWaR), Indian Institute of Science, Bangalore, 560012, India.
Praveen C RamamurthyInterdisciplinary Centre for Water Research (ICWaR), Indian Institute of Science, Bangalore, 560012, India.
Sandra Kathott PrakashDepartment of Biosciences and Bioengineering, Indian Institute of Technology, Roorkee, Uttarakhand, India.
I H FarooqiCivil Engineering Department, Zakir Hussain College of Engineering and Technology, Aligarh Muslim University, Aligarh, India.
Nastaran MozaffariChemical Engineering Department, Laval University, Quebec, QC, Canada.
Dahiru U LawalInterdisciplinary Research Center for Membranes and Water Security (IRC-MWS), King Fahd University of Petroleum and Minerals, 31261, Dhahran, Saudi Arabia.
Isam H AljundiInterdisciplinary Research Center for Membranes and Water Security (IRC-MWS), King Fahd University of Petroleum and Minerals, 31261, Dhahran, Saudi Arabia. aljundi@kfupm.edu.sa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The sequencing batch reactor has emerged as a promising technology in treating wastewater; however, its application in the treatment of generated water still needs to be explored. This research gap led to the investigation of various carbon-to-nitrogen (C/N) ratios in a column-type sequencing batch reactor (cSBR). The resulting data and model demonstrated that augmenting the SND process with an external carbon source is effective until the C/N ratio reaches 15, ultimately eliminating nitrogen in the produced water. Conversely, a reduced C/N ratio can limit the ability of polyphosphate-accumulating organisms to incorporate carbon into polyphosphate synthesis, thereby decreasing phosphorus removal efficiency within the cSBR. When the C/N ratio ranged from 6 to 8, and the mixed liquor suspended solids concentration was high, the average phosphate removal was approximately 55%, compared to only around 25% when the C/N ratio was less than 6.

Indexed as

CarbonMachine LearningMetagenomicsNitrogenWastewaterBioreactorsPhosphorusWaste Disposal, FluidWater PurificationCarbonNitrogenPhosphorusWastewaterArtificial neural networkCircular economyCoastal wastewaterInteractive effectSequencing batch reactorStress intensity

Identifiers

PMID39362974
PMCPMC11450006

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.