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Ambient Air Quality Monitoring Procedure via Estimation of Cadmium and Lead Content in Atmospheric Dust Using Vegetable Leaves
Abstract
Dust emitted into the air through human activities reduces air quality because it comes along with its deleterious constituents. This study aims to monitor the ambient air quality via the estimation of cadmium and lead concentration in the dust-polluted atmospheric environment using vegetable leaves. Leaves of pumpkin (Telfairia Occidentalis) and green (Amaranthus hybridus) vegetables obtained from Oba, Ekiosa, New Benin, and Ikpoba-Hill markets in Edo State, Nigeria, were washed with de-ionized water, spread, and exposed on tables placed at ten different points, 10 meters apart near the roadside outside and inside each market from 8:00 am to 6:00 pm every day (Monday - Friday) for three months (from November to March). The cadmium and lead pollutants in the dust deposit were analyzed using atomic absorption spectrophotometer after wet digestion of the different collectors. The study revealed that there was no cadmium content in the dust deposited on the vegetable leaves exposed inside each market. Atmospheric dust deposited on the vegetable leaves outside each market had cadmium content up to the tune of ≤0.01mg/kg. The study also revealed that the atmospheric dust inside and outside each market contained lead content. The lead content in the dust deposit obtained from outside each market ranged from 0.03-1.04 mg/kg, and the lead content in the atmospheric dust deposit obtained from inside each market ranged from 0.02-0.69 mg/kg. The air quality index (AQI) prediction for cadmium inside and outside the market atmosphere was very good (very clean). However, for the lead contaminant, the AQI rating outside and inside the market ranged from moderate (fairly clean) to very poor (severely polluted). Ekiosa market was very poor (severely polluted) and the Ikpoba-Hill market was moderate (fairly clean) due to lead contaminants in dust deposited due to human activities and heavy vehicular traffic.