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Heavy metal (Cu, Zn, Cd and Pb) contamination of vegetables in urban India: A case study in Varanasi

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Sharma, Rajesh Kumar, Agrawal, Madhoolika, Marshall, Fiona M.·2008·Environmental Pollution

Abstract

The contributions of heavy metals in selected vegetables through atmospheric deposition were quantified in an urban area of India. Deposition rate of Zn was recorded maximum followed by Cu, Cd and Pb. The concentrations of Zn and Cu were highest in Brassica oleracea, Cd in Abelmoschus esculentus and B. oleracea, while Pb was highest in Beta vulgaris. Heavy metal pollution index showed that B. oleracea was maximally contaminated with heavy metals followed by A. esculentus and then B. vulgaris. The results of washing showed that atmospheric deposition has contributed to the increased levels of heavy metals in vegetables. Both Cu and Cd posed health risk to local population via test vegetables consumption, whereas Pb posed the same only through B. oleracea. The study concludes that atmospheric depositions can elevate the levels of heavy metals in vegetables during marketing having potential health hazards to consumers.

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Metadata

Authors
Sharma, R. K., Agrawal, M., & Marshall, F. M.
Venue
Environmental Pollution
Publisher
Elsevier BV
Published
2008-07
Volume
154
Issue
2
Pages
254-263
ISSN
0269-7491 (ISSN-L)
OpenAlex
W2009521094
Cited by
354
References
0
FWCI
6.12
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Heavy metal (Cu, Zn, Cd and Pb) contamination of vegetables in urban India: A case study in Varanasi. https://app.cochat.ai/papers/10.1016/j.envpol.2007.10.010
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Sharma, R. K., Agrawal, M., & Marshall, F. M. (2008). Heavy metal (Cu, Zn, Cd and Pb) contamination of vegetables in urban India: A case study in Varanasi. Environmental Pollution. https://doi.org/10.1016/j.envpol.2007.10.010

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.