Evidence map›Paper›PMID 36769935›Full record

ArticleMaterials (Basel, Switzerland)2023

Geochemical Modeling of Heavy Metal Removal from Acid Mine Drainage in an Ethanol-Supplemented Sulfate-Reducing Column Test.

Keishi Oyama, Kentaro Hayashi, Yusei Masaki, Takaya Hamai, Shigeshi Fuchida, Yutaro Takaya, Chiharu Tokoro

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2023. 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

7 authors.

Keishi OyamaFaculty of Science and Engineering, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan.
Kentaro HayashiJapan Organization for Metals and Energy Security (JOGMEC), 2-10-1 Toranomon, Minato-ku, Tokyo 105-0001, Japan.
Yusei MasakiJapan Organization for Metals and Energy Security (JOGMEC), 2-10-1 Toranomon, Minato-ku, Tokyo 105-0001, Japan.
Takaya HamaiJapan Organization for Metals and Energy Security (JOGMEC), 2-10-1 Toranomon, Minato-ku, Tokyo 105-0001, Japan.ORCID 0000-0002-4156-4043
Shigeshi FuchidaFaculty of Science and Engineering, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan.
Yutaro TakayaFaculty of Science and Engineering, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan.
Chiharu TokoroFaculty of Science and Engineering, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan.ORCID 0000-0001-6214-0402

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A passive treatment process using sulfate-reducing bacteria (SRB) is known to be effective in removing heavy metals from acid mine drainage (AMD), though there has been little discussion of the mechanism involved to date. In this work, a sulfate-reducing column test was carried out using supplementary ethanol as an electron donor for microorganisms, and the reaction mechanism was examined using geochemical modeling and X-ray absorption fine structure (XAFS) analysis. The results showed that Cu was readily removed from the AMD on the top surface of the column (0-0.2 m), while Zn and Cd depletion was initiated in the middle of the column (0.2-0.4 m), where sulfide formation by SRB became noticeable. Calculations by a developed geochemical model suggested that ethanol decomposition by aerobic microbes contributed to the reduction of Cu, while sulfide produced by SRB was the major cause of Zn and Cd removal. XAFS analysis of column residue detected ZnS, ZnSO

Indexed as

acid mine drainage (AMD)geochemical modelingheavy metal removalpassive treatment (PT)sulfate-reducing bacteria (SRB)

Identifiers

PMID36769935
PMCPMC9917845

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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.