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Environ Monit Assess ; 191(3): 156, 2019 Feb 12.
Artículo en Inglés | MEDLINE | ID: mdl-30747380

RESUMEN

Traffic-related metal emissions have become a global concern due to their deposition in roadside soils and potential hazardous effects. This study evaluates metal levels in soils adjoining four highways of Rio de Janeiro (Linha Vermelha, Via Dutra, BR-465, and Avenida Brasil), chosen for their diverse traffic volumes, age, and urban/rural settings. In addition to soil physicochemical properties, 11 elements (Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, Sr, V, and Zn) were assessed on samples collected at different distances from the road (1, 3, 5, 10, 15 m) and soil depths (0-15 and 15-30 cm). Moreover, the geoaccumulation index was also computed to infer the soil contamination extent. The results indicate that soil metal levels at each highway are highly dependent on factors like traffic volume, distance to road, other anthropogenic sources of pollution, and their rural or urban location. The highways with greater traffic volume, Linha Vermelha and Avenida Brasil (154,000 and 126,000 vehicles day-1, respectively), clearly presented the highest soil metal concentrations. Still, as stressed by the principal component analysis, traffic volume alone fails to explain the distribution of metals in soils neighboring these highways. Thus, factors like their urban setting and larger exposure to anthropogenic activities may play a pivotal role. On the other hand, soils from Via Dutra and BR-465, both on a rural backdrop, were mostly influenced by traffic as their metal levels decreased with increasing distances from the road. Comparison with reference and preventive values for Brazilian soils and the assessment of the geoaccumulation index have shown that concentrations of Pb and V have reached concerning thresholds at Linha Vermelha and Avenida Brasil.


Asunto(s)
Monitoreo del Ambiente/métodos , Metales Pesados/análisis , Contaminantes del Suelo/análisis , Brasil , Contaminación Ambiental/análisis , Suelo/química , Transportes/estadística & datos numéricos , Urbanización , Emisiones de Vehículos/análisis
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