Evidence map›Paper›PMID 28696043›Full record

ArticleMicrobial biotechnology2018

The bioelectric well: a novel approach for in situ treatment of hydrocarbon-contaminated groundwater.

Enza Palma, Matteo Daghio, Andrea Franzetti, Marco Petrangeli Papini, Federico Aulenta

Abstract read
In one paragraph

Article in Microbial biotechnology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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  9. Simulation tests ofHeliyon · 2019
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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

5 authors.

Enza PalmaDepartment of Chemistry - Sapienza University of Rome, P.le Aldo Moro 5, Rome, 00185, Italy.
Matteo DaghioDepartment of Earth and Environmental Sciences - University of Milano-Bicocca, Piazza della Scienza 1, Milan, 20126, Italy.
Andrea FranzettiDepartment of Earth and Environmental Sciences - University of Milano-Bicocca, Piazza della Scienza 1, Milan, 20126, Italy.
Marco Petrangeli PapiniDepartment of Chemistry - Sapienza University of Rome, P.le Aldo Moro 5, Rome, 00185, Italy.
Federico AulentaWater Research Institute (IRSA) - National Research Council (CNR), Via Salaria km 29, 300, Monterotondo (RM), 00015, Italy.ORCID 0000-0001-6819-7944

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Groundwater contamination by petroleum hydrocarbons (PHs) is a widespread problem which poses serious environmental and health concerns. Recently, microbial electrochemical technologies (MET) have attracted considerable attention for remediation applications, having the potential to overcome some of the limiting factors of conventional in situ bioremediation systems. So far, field-scale application of MET has been largely hindered by the limited availability of scalable system configurations. Here, we describe the 'bioelectric well' a bioelectrochemical reactor configuration, which can be installed directly within groundwater wells and can be applied for in situ treatment of organic contaminants, such as PHs. A laboratory-scale prototype of the bioelectric well has been set up and operated in continuous-flow regime with phenol as the model contaminant. The best performance was obtained when the system was inoculated with refinery sludge and the anode potentiostatically controlled at +0.2 V versus SHE. Under this condition, the influent phenol (25 mg l

Indexed as

Biodegradation, EnvironmentalBioreactorsBiotransformationElectrochemical TechniquesElectrodesGroundwaterHydrocarbonsSewageWater Pollutants, ChemicalWater PurificationHydrocarbonsSewageWater Pollutants, Chemical

Identifiers

PMID28696043
PMCPMC5743819

What OpenQuestion holds

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LicenceCC BY
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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.