Evidence map›Paper›PMID 41012389›Full record

ReviewToxics2025

Integrated Approaches of Arsenic Remediation from Wastewater: A Comprehensive Review of Microbial, Bio-Based, and Advanced Technologies.

Aminur Rahman

Abstract readReview
In one paragraph

Review in Toxics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
  5. 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

1 author.

Aminur RahmanDepartment of Biomedical Sciences, College of Clinical Pharmacy, King Faisal University, Al-Ahsa 31982, Saudi Arabia.ORCID 0000-0001-8326-026X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Arsenic-containing wastewater and soil systems are a serious hazard to public health and the environment, particularly in areas where agriculture and drinking water depend on groundwater. Therefore, the removal of arsenic contamination from soil, water, and the environment is of great importance for human welfare. Most of the conventional methods are inefficient and have very high operational costs, especially for metals at low concentrations or in large solution volumes. This review delivers a comprehensive approach to arsenic remediation, including microbiological processes, phytoremediation, biochar technologies, bio-based adsorbents, and nanomaterial-assisted techniques. All of these methods are thoroughly examined in terms of removal competence, their mechanisms, environmental impact, cost-effectiveness, and scalability. Phytoremediation and microbial remediation techniques are self-regenerating and eco-friendly, whereas fruit-waste-derived materials and biochar provide abundant adsorbents, and are therefore low-cost. On the other hand, nanotechnology-based approaches show remarkable effectiveness but raise concerns regarding economic feasibility and environmental safety. Additionally, this review represents a comparative analysis and discusses synergistic and hybrid systems that combine multiple technologies for enhancing the remediation performance. Future research directions are emphasized along with challenges such as material stability, regeneration, and policy integration. This review aims to guide decision-makers, research scholars, and industry stakeholders toward affordable, sustainable, and high-performance arsenic remediation techniques for practical use.

Indexed as

arsenic remediationbio-based adsorbentsbiocharcost-effectivenessfruit peelsmicrobial detoxificationnanotechnologyphytoremediationsustainable remediationwastewater treatment

Identifiers

PMID41012389
PMCPMC12473819

What Socratic 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 Socratic graph.