Publications by authors named "Darpa Saurav Jyethi"

Urban agriculture is common in fertile river floodplains of many developing countries. However, there is a risk of contamination in highly polluted regions. This study quantifies health risks associated with the consumption of vegetables grown in the floodplain of the urban river 'Yamuna' in the highly polluted yet data-scarce megacity Delhi, India.

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The study attempts to look into the morphological characteristics, elemental composition, contamination, source contributions, and associated health risks in household dust of Napaam, a rural region in the Brahmaputra flood plain in North East India. Morphological evidence suggests that most of the house dust particles were sourced from vehicle abrasion and soil. Three contamination indices-enrichment factor (EF), index of geo-accumulation (I), and pollution load index (PLI) indicated that Cl and four trace elements (Cu, Zn, As, and Pb) are significantly enriched in house dust with extreme pollution load.

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The study investigated the levels of organochlorine pesticides (OCPs) in different types of vegetables grown in periurban area of National Capital Region (NCR), India. Vegetable sampling was carried out in winter and summer season of 2012. A total of 20 different OCPs were determined using gas chromatography (GC) assembled with electron capture detector (ECD).

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Polycyclic aromatic hydrocarbons (PAHs) associated with the inhalable fraction of particulate matter were determined for 1 year (2009-2010) at a school site located in proximity of industrial and heavy traffic roads in Delhi, India. PM10 (aerodynamic diameter ≤10 μm) levels were ∼11.6 times the World Health Organization standard.

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Six different vegetables grown in the vicinity of three thermal power plants and a background site in Delhi, India were analyzed for 16 priority polycyclic aromatic hydrocarbons (PAHs) and 7 heavy metals (Cd, Cu, Cr, Ni, Zn, Fe and Mn). Annual mean concentrations of PAHs and all metals were found to be significantly higher (ANOVA, p<0.001) at power plant sites as compared to the background site.

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