Evidence map›Paper›PMID 41149989›Full record

ArticleMembranes2025

Practical Algal Control in Lower Yangtze Reservoirs Using Composite Microfiltration Physical Enclosure.

Bin Xu, Fangzhou Liu, Qi Zhang, Congcong Ni, Jianan Gao, Xin Huang

Abstract read
In one paragraph

Article in Membranes, 2025. 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. Review
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

6 authors.

Bin XuSchool of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China.
Fangzhou LiuShandong Institute for Product Quality Inspection, Jinan 250102, China.
Qi ZhangSchool of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China.
Congcong NiSchool of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China.
Jianan GaoDepartment of Civil Engineering, The University of Hong Kong, Hong Kong 999077, China.ORCID 0000-0003-1255-1240
Xin HuangSchool of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China.

Funding

National Natural Science Foundation of China No. 52300100, No. 51678351Science and Technology Innovation Plan of Shanghai Science and Technology Commission No. 22YF1412900
6 · The paper itself

Abstract

Source water reservoirs in the lower reaches of the Yangtze River are increasingly threatened by algal contamination, driven by fluctuations in upstream water quality. To ensure stable reservoir operation and protect downstream drinking water sources, physical enclosures are widely used. However, most algal pollution in reservoirs consists of microalgae (diameters < 100 μm), and conventional algae barriers are effective primarily against visible algal blooms but perform poorly against microscopic algal clusters. To address this limitation, we developed a composite microfiltration physical enclosure system by integrating a microfiltration membrane, supported by a mechanical layer, onto physical enclosures. The algal removal performance of this system was evaluated from lab-scale tests to field-scale applications. Results demonstrated that the composite membrane exhibited excellent interception efficiency against algal aggregates, with algae density in the filtered water reduced by over 80%. The composite enclosure effectively filters multiple algae species, significantly reducing the risk of algae entering downstream water treatment plants, thereby alleviating the burden of traditional processes and reducing operating costs.

Indexed as

algal controlcomposite enclosurereservoir

Identifiers

PMID41149989
PMCPMC12566066

What OpenQuestion holds

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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.