Evidence map›Paper›PMID 35038018›Full record

ArticleEnvironmental monitoring and assessment2022

Ecological and human health risks from pseudo-total and bio-accessible metals in street dusts.

Arpita Roy, Tanushree Bhattacharya

Abstract read
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Article in Environmental monitoring and assessment, 2022. 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
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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

2 authors.

Arpita RoyDepartment of Civil & Environmental Engineering, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India, 835215.
Tanushree BhattacharyaDepartment of Civil & Environmental Engineering, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India, 835215. tbhattacharya@bitmesra.ac.in.ORCID http://orcid.org/0000-0003-3547-2529

Funding

Science and Engineering Research Board ECR/2017/000695
6 · The paper itself

Abstract

Street dust samples were collected from industrial and commercial cities (Jamshedpur and Ranchi during monsoon and post-monsoon seasons) for detecting the levels of Cr, Cd, Cu, Ni, Pb, Zn, As, Co, Al, and Mn. The industrial city recorded higher metal concentrations compared to commercial. Similar trend of pseudo-total metal concentrations was observed in both the seasons at industrial city (Al > Mn > Zn > Cr > Pb > Cu > Ni > Cd) and only monsoon season at commercial city (Al > Mn > Zn > Cu > Cr > Pb > Ni > Cd). Zn > Cd was the most bioaccessible metal throughout the cities (monsoon and post-monsoon). The geochemical parameters (Igeo, EF, CF) were highest for Cd and lowest for Ni (both cities for the two seasons). Pollution Load Indices (PLI zone) were highest during the post-monsoon season in the industrial city. The highest carcinogenic risk was posed by Cr ranging from 1.87E-05 to 4.80E-05, in both the cities through ingestion and inhalation pathways. Children were found at higher risks, while the bioaccessible fractions posed neither carcinogenic nor non-carcinogenic threats to the population. Principal component analysis and correlation analysis indicated the influence of vehicular and industrial emissions, especially steel industry and coal-based thermal power plants as the major source of metals in street-dust. The outcomes of this work will be useful in providing baseline information of pollution along with their consequent environmental and human health risks of Jharkhand state.

Indexed as

DustMetals, HeavyChildChinaCitiesEnvironmental MonitoringEnvironmental PollutionHumansRisk AssessmentDustMetals, HeavyCarcinogenic risksEcological risksGeoaccumulation indexHazard quotientNon-carcinogenic risksPollution Load Index

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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.