Evidence map›Paper›PMID 35709202›Full record

ArticlePloS one2022

Assessment of heavy metals accumulation in agricultural soil, vegetables and associated health risks.

Nehar Ullah, Maqsood Ur Rehman, Bashir Ahmad, Irshad Ali, Muhammad Younas, Muhammad Sagheer Aslam, Atta-Ur Rahman, Ensiyeh Taheri, Ali Fatehizadeh, Mashallah Rezakazemi

Abstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 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

10 authors.

Nehar UllahDepartment of Chemical Engineering, Faculty of Mechanical, Chemical and Industrial Engineering, University of Engineering & Technology, Peshawar, Pakistan.ORCID 0000-0003-2117-0829
Maqsood Ur RehmanDepartment of Chemical Engineering, Faculty of Mechanical, Chemical and Industrial Engineering, University of Engineering & Technology, Peshawar, Pakistan.
Bashir AhmadDepartment of Plant Protection, Agricultural University, Peshawar, Pakistan.
Irshad AliDepartment of Chemical Engineering, Faculty of Mechanical, Chemical and Industrial Engineering, University of Engineering & Technology, Peshawar, Pakistan.
Muhammad YounasDepartment of Chemical Engineering, Faculty of Mechanical, Chemical and Industrial Engineering, University of Engineering & Technology, Peshawar, Pakistan.
Muhammad Sagheer AslamNational Institute of Urban Infrastructure and Planning, University of Engineering & Technology, Peshawar, Pakistan.
Atta-Ur RahmanDepartment of Geography, University of Peshawar, Peshawar, Pakistan.
Ensiyeh TaheriEnvironment Research Center, Research Institute for Primordial Prevention of Non-communicable Disease, Isfahan University of Medical Sciences, Isfahan, Iran.
Ali FatehizadehEnvironment Research Center, Research Institute for Primordial Prevention of Non-communicable Disease, Isfahan University of Medical Sciences, Isfahan, Iran.
Mashallah RezakazemiFaculty of Chemical and Materials Engineering, Shahrood University of Technology, Shahrood, Iran.ORCID 0000-0002-9980-6682

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Industrialization plays a vital role in the development of a country's economy. However, it also adversely affects the environment by discharging various unwanted and harmful substances such as heavy metals into the surface and subsurface aquifers. The current research work investigates the identification, characterization, and evaluation of specific heavy metals in industrial wastewater (IWW) and different composite samples of soil and vegetables (onion, pumpkin, lady finger, and green pepper) collected from selected agricultural fields irrigated with canals fed IWW in Mingora city of Swat (Pakistan). Obtained results were compared with the tube well water irrigated soil and vegetables grown in it. Heavy metals accumulation was tested through wet digestion method and atomic absorption spectrophotometry (AAS). The metal transfer factor (MTF) of heavy metals from soil to vegetables was also determined along with the health index (HI) to assess the potential health risk of the metals towards consumers using Monte Carlo simulation technique. Analysis of water samples showed that the concentration in mg l-1 of heavy metals in IWW follows the trend Fe (6.72) > Cr (0.537) > Pb (0.393) > Co (0.204) > Mn (0.125) > Ni (0.121). Analysis of the soil samples irrigated with IWW followed the order of Fe (47.27) > Pb (2.92) > Cr (2.90) >Ni (1.02) > Mn (0.90) > Co (0.68) and Fe (17.12) > Pb (2.12) > Cr (2.03) >Ni (0.76) > Co (0.49) > Mn (0.23) irrigated with TWW. Heavy metals concentration values found in soil irrigated with IWW were higher than the soil irrigated with TWW. Similar trends were found for agricultural produces grown on soil irrigated with IWW and found higher than the normal allowable WHO limits, indicating higher possibilities of health risks if continuously consumed. MTF values were found higher than 1 for ladyfinger and green pepper for Pb intake and pumpkin for Mn intake. The current study suggests the continuous monitoring of soil, irrigation water and agricultural products to prevent heavy metals concentration beyond allowable limits, in the food chain. Thus, concrete preventive measures must be taken to reduce heavy metal accumulation through wastewater irrigation to protect both human and animal health in the study area of Mingora Swat Pakistan.

Indexed as

Metals, HeavySoil PollutantsAgricultural IrrigationAnimalsEnvironmental MonitoringFood ContaminationHumansLeadRisk AssessmentSoilVegetablesWastewaterWaterLeadMetals, HeavySoilSoil PollutantsWastewaterWater

Identifiers

PMID35709202
PMCPMC9202934

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LicenceCC BY
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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.