Evidence map›Paper›PMID 39314825›Full record

ArticleWater research X2024

Isotope analysis of nitrogen removal pathways and N

Mengjia Zhan, Wei Zeng, Xiaojing Hao, Haohao Miao, Yao Lu, Wenzhuo Jiang, Qingan Meng, Qingteng Gong

Abstract read
In one paragraph

Article in Water research X, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Mengjia ZhanNational Engineering Laboratory for Advanced Municipal Wastewater Treatment and Reuse Technology, Beijing University of Technology, Beijing 100124, China.
Wei ZengNational Engineering Laboratory for Advanced Municipal Wastewater Treatment and Reuse Technology, Beijing University of Technology, Beijing 100124, China.
Xiaojing HaoNational Engineering Laboratory for Advanced Municipal Wastewater Treatment and Reuse Technology, Beijing University of Technology, Beijing 100124, China.
Haohao MiaoNational Engineering Laboratory for Advanced Municipal Wastewater Treatment and Reuse Technology, Beijing University of Technology, Beijing 100124, China.
Yao LuNational Engineering Laboratory for Advanced Municipal Wastewater Treatment and Reuse Technology, Beijing University of Technology, Beijing 100124, China.
Wenzhuo JiangNational Engineering Laboratory for Advanced Municipal Wastewater Treatment and Reuse Technology, Beijing University of Technology, Beijing 100124, China.
Qingan MengNational Engineering Laboratory for Advanced Municipal Wastewater Treatment and Reuse Technology, Beijing University of Technology, Beijing 100124, China.
Qingteng GongNational Engineering Laboratory for Advanced Municipal Wastewater Treatment and Reuse Technology, Beijing University of Technology, Beijing 100124, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study explored the impact of varying nitrate to sulfide (N/S) ratios on nitrogen removal efficiency (NRE) in the sulfide-driven autotrophic denitrification and anammox (SDAD-anammox) system. Optimal nitrogen removal was observed at N/S ratios between 1.5 and 2.0. Isotope tracing results showed that the contribution of anammox to nitrogen removal was enhanced with increasing N/S ratios, reaching up to 37 % at the N/S ratio of 2.5. Additionally, complex nitrogen pathways were identified, including dissimilatory nitrate reduction to ammonium (DNRA). Furthermore, isotope tracing was innovatively applied to investigate N

Indexed as

AnammoxDenitrification desulfurization systemFunctional geneIsotope effectNitrous oxide

Identifiers

PMID39314825
PMCPMC11419794

What OpenQuestion holds

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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.