Seasonal and Spatial Variations of Heavy Metal concentrations in soil and plants along North Badia AlMafraq Highway using Geographic Information System (GIS) technique
Some heavy metals (Zn, Cu, Pb and Fe) were identified by using geographic information system (GIS) technology along the North Badia - Mafrak Expressway, and the vegetation and soil samples were analyzed. A reference plant and soil samples were obtained at 500 meters from the street in the study area...
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Veröffentlicht in: | NeuroQuantology 2022-01, Vol.20 (10), p.9528 |
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Sprache: | eng |
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Zusammenfassung: | Some heavy metals (Zn, Cu, Pb and Fe) were identified by using geographic information system (GIS) technology along the North Badia - Mafrak Expressway, and the vegetation and soil samples were analyzed. A reference plant and soil samples were obtained at 500 meters from the street in the study area, and soil and plant samples were congregated in two separate months: July and November. The primary aim of the study was to evaluate the impact of the increase in the concentrations of heavy metals due to various human activities on plant, soil, human health and its impact on animals in the area. For that purpose, twenty (20) soil samples and 80 plant samples of two plant species (Peganumharmala L. and Anabasis articulata) were collected from the study area. To indicate the change in the concentration of heavy metals in each section, all plant samples were separated into two portions (branches and roots). After the collection process, samples were digested using acid digestion, and heavy metals were analyzed using ICP techniques, and the analysis outcomes were compared with WHO figures.The study indicated that seasonal variations were noticed as the lowest concentration were assigned for July samples, and the highest concentrations were paired with November samples. As per the spatial variations for the metal concentrations, the results showed a higher concentration distribution for both July and November at 5 meters than at 10 meters. Finally, the outcomes inferred a higher concentration distribution risk for November samples than for July samples |
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ISSN: | 1303-5150 |
DOI: | 10.14704/nq.2022.20.10.NQ55930 |