Evidence map›Paper›PMID 36279024›Full record

ArticleEnvironmental monitoring and assessment2022

Potentially toxic elements (PTEs) in Gomti-Ganga Alluvial Plain, associated human health risks assessment and potential remediation using novel-nanomaterials.

Ramsha Khan, Abhishek Saxena

Abstract read
In one paragraph

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. 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

2 authors.

Ramsha KhanFaculty of Civil Engineering, Institute of Technology, Shri Ramswaroop Memorial University, Barabanki, India. ramshaokhan@gmail.com.ORCID http://orcid.org/0000-0002-0280-6601
Abhishek SaxenaFaculty of Civil Engineering, Institute of Technology, Shri Ramswaroop Memorial University, Barabanki, India. abhisheksaxena79@gmail.com.ORCID http://orcid.org/0000-0003-0595-2118

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The health risks associated with consumption of water from river Gomti polluted with potentially toxic elements (PTEs), including As, Fe, Pb, Cd, Mn, Cr, Ni, and Hg were investigated at the initiation of unlocking of COVID-19 lockdown and compared with pre-COVID-19 lockdown status. In the current investigation, the total hazard index (THI) values exceeded the acceptable limit of "unity" at all sampling stations. The use of river water for drinking and domestic purposes by millions of people with high THI values has emerged as a matter of huge concern. The individual hazard quotients associated with Cd and Pb were found to be most severe (> 1). A vivid difference between the THI values during the two study phases indicated the positive impact of COVID-19 lockdown signifying the prominent impact of anthropogenic activities on the PTE concentrations. The closure of local manufacturing units (textile, battery, etc.) emerged as a potential reason for decreased health risks associated with PTE levels. The higher susceptibility of children to health risks in comparison with adults through the values of THI and HQs was interpreted across the study area. Potential remedial measures for PTE contamination have also been suggested in the study.

Indexed as

COVID-19MercuryMetals, HeavyNanostructuresSoil PollutantsAdultCadmiumChildCommunicable Disease ControlEnvironmental MonitoringHumansLeadRisk AssessmentWaterCadmiumLeadMercuryMetals, HeavySoil PollutantsWaterCOVID-19Hazard quotientLockdownLucknow cityRiver Gomti

Identifiers

PMID36279024
PMCPMC9589610

What OpenQuestion holds

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Read underepoch 390

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.