Evidence map›Paper›PMID 39738644›Full record

ArticleScientific reports2024

Exploring heavy metal dynamics and risks from dust and soil in urban cities of Jharkhand, India.

Arpita Roy, Tanushree Bhattacharya, Mala Kumari, Abhishek Kumar

Abstract read
In one paragraph

Article in Scientific reports, 2024. 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

4 authors.

Arpita RoyDepartment of Civil and Environmental Engineering, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, 835215, India.
Tanushree BhattacharyaDepartment of Civil and Environmental Engineering, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, 835215, India. tbhattacharya@bitmesra.ac.in.
Mala KumariDepartment of Civil and Environmental Engineering, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, 835215, India.
Abhishek KumarDepartment of Civil and Environmental Engineering, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, 835215, India.

Funding

Science and Engineering Research Board, Department of Science and Technology, Government of India ECR/2017/000695
6 · The paper itself

Abstract

Jharkhand is a minerally prosperous state with geogenic and industrial origins of metals. This study assesses the seasonal variation of pseudo-total metal contents (Cr, Ni, Pb, Zn, Mn, Cu, Fe, Mg, Al) and related contamination and risks in indoor dust, street dust, and soils of four major cities of Jharkhand. Across cities and seasons, Zn, Cu, and Pb were the most common pollutants. Indoor dust showed higher metal concentrations than street dust and soil, suggesting their indoor origins. Geo-accumulation indices indicated significant Cu contamination, followed by Pb and Zn. Street dust exhibited notable enrichment in Zn and Pb in all cities except Dhanbad, where Cu contamination was substantial. Ecological risk indices peaked during summer in street dusts of Ranchi and Bokaro (for Pb) and during monsoons in soils of Jamshedpur and Dhanbad (for Cu). Based on chemical sequential extractions, the mobilities of Mg, Mn, Zn, and Cu were high, while Pb had moderate mobility. The probable sources of immediate concern were vehicles and paints, wire, electroplating, metal casting, and steel manufacturing industries. The findings emphasize the urgent need for implementing stringent regulations to mitigate metal emissions and ensure compliance with environmental standards.

Indexed as

BioavailabilityEcological risksEnrichment factorIndoor dustMetalsMobilitySoilStreet dust

Identifiers

PMID39738644
PMCPMC11685825

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.