Evidence map›Paper›PMID 33855229›Full record

ArticleHeliyon2021

Sources and level of heavy metal contamination in the water of Awetu watershed streams, southwestern Ethiopia.

Higemengist Astatkie, Argaw Ambelu, Embialle Mengistie Beyene

Abstract read
In one paragraph

Article in Heliyon, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

3 authors.

Higemengist AstatkieDepartment of Environmental Health Sciences and Technology, Jimma University, Jimma, Ethiopia.
Argaw AmbeluDepartment of Environmental Health Sciences and Technology, Jimma University, Jimma, Ethiopia.
Embialle Mengistie BeyeneDepartment of Environmental Health, Faculty of Public Health, Hawassa University, Hawassa, Ethiopia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The present study aimed to investigate the contamination source, level, and spatial distribution of globally alarming trace metals from Awetu watershed streams, southwestern Ethiopia. Surface water samples were collected from 20 sampling sites in December 2019. Water samples were collected in 500 ml polyethylene bottles previously washed with deionized water and rinsed with the sample to be collected from different stretches and acidified with 5 ml concentrated nitric acid. The samples were digested with open acid digestion and the contents of the metal were analysed using inductively coupled plasma optical emission spectrometry (ICP-OES) ranged from 18 - 351 μg/L for As, 5-19 μg/L for Cd, 232-421 μg/L for Cr, 314-920 μg/L for Pb and 10-16 μg/L for Hg. The highest concentrations of As were detected at K3, Cd at K2, Pb and Cr at D4, and Hg at D5. Analysis of variance results revealed that the Cd concentrations were statistically significant among all the streams except for Boye. Streams found at the center of Jimma city with effluents emanated from Jimma University, garage maintenances, car-wash and agricultural areas had higher values than the streams in the periphery. This study concluded that a higher concentration of trace elements is associated with the type of waste entering the streams. Trace elements concentration in the watershed is to the level that can pose a risk to downstream users. Public awareness creation to establish waste management systems and river quality monitoring should be implemented to minimize the public health risk and deterioration of the aquatic ecosystem.

Indexed as

Heavy metalsPollution distributionSurface water pollutionWatershed streams

Identifiers

PMID33855229
PMCPMC8027692

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.