Evidence map›Paper›PMID 29971744›Full record

ArticleEnvironmental science and pollution research international2018

Assessment of arsenic removal efficiency by an iron oxide-coated sand filter process.

Arianna Callegari, Navarro Ferronato, Elena Cristina Rada, Andrea G Capodaglio, Vincenzo Torretta

Abstract readEvaluation Study
PubMed Publisher
In one paragraph

Article in Environmental science and pollution research international, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Arianna CallegariDepartment of Civil Engineering and Architecture, University of Pavia, Via Ferrata 3, 27100, Pavia, Italy.
Navarro FerronatoDepartment of Theoretical and Applied Sciences, University of Insubria, Via G.B. Vico 46, 21100, Varese, Italy.
Elena Cristina RadaDepartment of Theoretical and Applied Sciences, University of Insubria, Via G.B. Vico 46, 21100, Varese, Italy.
Andrea G CapodaglioDepartment of Civil Engineering and Architecture, University of Pavia, Via Ferrata 3, 27100, Pavia, Italy.
Vincenzo TorrettaDepartment of Theoretical and Applied Sciences, University of Insubria, Via G.B. Vico 46, 21100, Varese, Italy. vincenzo.torretta@uninsubria.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Arsenic is among the most dangerous contaminants which can limit groundwater use for drinking water consumption. Among the most diffused As-removal technologies around the world, adsorptive media systems are usually favored for relatively low cost and simplicity of operation. This study examines the performance of a laboratory-scale iron oxide-coated sand (IOCS) column filter, to remove arsenic (arsenate (As[V]) and arsenite (As[III])) from groundwater. This technology could be adopted in small communities, as it showed consistent removal rates of 99% with an easy-to-operate process. Some considerations about the possible introduction of such technology in developing countries are provided, highlighting the general impacts to human health related to high arsenic concentrations in groundwater. This, among other adsorption processes, could be recommended as a sustainable mean of ensuring good drinking water quality in developing regions, reducing human health impacts.

Indexed as

FiltrationWater PurificationAdsorptionArsenicFerric CompoundsGroundwaterSilicon DioxideWater Pollutants, ChemicalArsenicFerric Compoundsferric oxideSilicon DioxideWater Pollutants, ChemicalArsenic removalDeveloping countriesDrinking waterIron oxide-coated sand (IOCS)Risk assessment

Identifiers

What OpenQuestion holds

Textmetadata
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.