Evidence map›Paper›PMID 34832121›Full record

ArticleMembranes2021

Reduction of Cost and Environmental Impact in the Treatment of Textile Wastewater Using a Combined MBBR-MBR System.

Xuefei Yang, Víctor López-Grimau

Open access · goldAbstract read
In one paragraph

Article in Membranes, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.6field-weighted citation impact, top 38% 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

4 citing papers in PubMed, 25 citations in OpenAlex.

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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

2 authors at 1 institution in 1 country.

Xuefei YangInstitute of Textile Research and Industrial Cooperation of Terrassa (INTEXTER), Universitat Politècnica de Catalunya, Carrer de Colom 15, 08222 Terrasa, Spain.ORCID 0000-0001-9695-0323
Víctor López-GrimauDepartment of Project and Construction Engineering, Universitat Politècnica de Catalunya, Carrer de Colom 11, 08222 Terrassa, Spain.ORCID 0000-0001-9008-4188
Universitat Politècnica de Catalunya · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A hybrid Moving Bed Biofilm Reactor-Membrane Bioreactor (MBBR-MBR) was developed for the treatment of wastewater from a Spanish textile company. Compared with conventional activated sludge (CAS) treatment, the feasibility of this hybrid system to reduce economic and environmental impact on an industrial scale was conducted. The results showed that, technically, the removal efficiency of COD, TSS and color reached 93%, 99% and 85%, respectively. The newly dyed fabrics performed with the treated wastewater were qualified under the standards of the textile industry. Economically, the values of Capital Expenditure (CAPEX) calculated for the hybrid MBBR-MBR system are profitable because of the reduction in Operational Expenditure (OPEX) when compared with CAS treatment, due to the lower effluent discharge tax thanks to the higher quality of the effluent and the decolorizing agent saved. The result of Net Present Value (NPV) and the Internal Rate of Return (IRR) of 18% suggested that MBBR-MBR is financially applicable for implantation into the industrial scale. The MBBR-MBR treatment also showed lower environmental impacts than the CAS process in the life cycle assessment (LCA) study, especially in the category of climate change, thanks to the avoidance of using extra decolorizing agent, a synthetic product based on a triamine.

Indexed as

decolorizing agenteconomic feasibilitylife cycle assessmentmembrane bioreactormoving bed biofilm reactortextile wastewaterwater reuse

Identifiers

PMID34832121
PMCPMC8625884
OpenAlexW3217147638

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.