Evidence map›Paper›PMID 32570720›Full record

ArticleMicroorganisms2020

Energy-Efficient Single-Stage Nitrite Shunt Denitrification with Saline Sewage through Concise Dissolved Oxygen (DO) Supply: Process Performance and Microbial Communities.

Huichuan Zhuang, Zhuoying Wu, Linji Xu, Shao-Yuan Leu, Po-Heng Lee

Open access · goldAbstract read
In one paragraph

Article in Microorganisms, 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
0.5field-weighted citation impact, top 43% 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

3 citing papers in PubMed, 17 citations in OpenAlex.

  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 at 3 institutions in 3 countries.

Huichuan ZhuangDepartment of Civil and Environmental Engineering, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China.ORCID 0000-0003-1570-9269
Zhuoying WuDepartment of Civil and Environmental Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.
Linji XuEnvironmental Engineering Technology Research Center, Chongqing Academy of Ecology and Environmental Sciences, Chongqing 401147, China.
Shao-Yuan LeuDepartment of Civil and Environmental Engineering, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China.
Po-Heng LeeDepartment of Civil and Environmental Engineering, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China.
Hong Kong Polytechnic University · HKChongqing Academy of Environmental Science · CNImperial College London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-stage nitrite shunt denitrification (through nitrite rather than nitrate) with low dissolved oxygen (DO) supply is a better alternative in terms of energy-efficiency, short-footprint, and low C/N-ratio requirement. This study investigates the optimal DO level with temperature effect, with saline sewage at the fixed hydraulic and solids retention times of 8 h and 8 d, respectively. Moreover, 16S rRNA gene sequencing analysis corresponding with total nitrogen (TN) and chemical oxygen demand (COD) removals in each operating condition were performed. Results showed that DO of 0.3 mg/L at 20 °C achieved over 60.7% and over 97.9% of TN and COD removal, respectively, suggesting that such condition achieved effective nitrite-oxidizing bacteria inhibition and efficient denitrification. An unexpected finding was that sulfur-reducing

Indexed as

16S rRNA sequencingdissolve oxygennitrite shunt denitrificationtotal nitrogen removal

Identifiers

PMID32570720
PMCPMC7356877
OpenAlexW3036908800

What OpenQuestion holds

Textmetadata
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.