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Browsing Question Papers by Subject "Heavy metals"

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    Modeling lateral distribution of heavy metal and bio-accumulation in earthworm in the varying acidic surface horizon of waste-polluted soil
    (U. P., 2013) Atulegwu, Patrick Uzoije; Uzoigwe, Luke; Otuonye, Erick; Kamalu, Clifford O.; Onunkwo-Akunne, Austine
    Heavy metal concentrations and its distributions in the soil have been a source of concern to soil usage, particularly to agriculture as concentration and distribution of heavy metal determine to a large extent, the soil quality and consequently that of the crops. The ability to quantify the amount of heavy metal in the soil is of immense importance to soil management. The use of accurate model is essential to estimate the actual soil heavy metal values and its distribution for efficient management. In this study, soil and earthworm samples of the battery-waste-polluted site and that of the background site were collected from five different locations(A,B,C,D and E) along the gradient of decreasing pollution. With five replicates each form one sampling location, twenty–five soil and fifty earthworms samples (two earthworms from each replicate) were collected using stratified random sampling technique. Lead(pb), Cadmium(Cd), Chromium(Cr), Nickel(Ni), Manganese(Mn), Arsenic(As), pH and Mercury(Hg) were analyzed using standard methods. The same process was replicated for the background site. Values of the heavy metals in soil and earthworms were natural and typical of Ameki-Nanka-soil formation. The average range of heavy metals concentrations in soil and earthworm samples from the polluted site were; pb(1025-695 mg/kg), Cd(11.34-6.3 mg/kg), Mn(290-81 mg/kg), pH(2.3-6.9mg/kg),Cr(185-3.7 mg/kg), Ni(12.87-1.7 mg/kg), As(72-4.5 mg/kg), Hg(1.7-0.002mg/kg) and pb(193-37.98 mg/kg), Cd(14.04-0.01 mg/kg), Mn(17.34-1.10mg/kg), pH(6.9-2.3mg/kg), Cr(8.45-0.01 mg/kg), Ni(1.41-0.03 mg/kg), As(0.75-0.01 mg/kg), Hg(0.4-0.009mg/kg) respectively. Concentrations of heavy metals for soil and earthworm samples decreased along the gradient of decreasing pollution of the polluted site. Three models(Linear , Logarithmic and quadratic models) were developed to test their suitability to the data in which Ph was correlated with heavy metals. Inverse correlation was observed with coefficient R2 of between 0.77-0.95 and lowest percentage deviation of the field from the predicted values.
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    ItemOpen Access
    Soil quality modeling of a highly acidic eutric - tropofluvent soil
    (IDOSI Publications, 2010) Uzoije Atulegwu Patrick
    Waste from garri processing centre of Umuagwo, Ohaji L.G.A of Imo state has impacted enormous pollution on the soil ecosystem of the centre. Huge resources and quality man hour have been spent on determining the level of such pollution in similar circumstances using laboratory techniques. In view of the aforementioned, the study developed several regression models, establishing the relationship between Ph and other selected soil physiochemical properties, to predict the values of the these selected properties in the polluted soils. The study took place in three sampling pedons A, B and C using the technique of stratified random sapling for sample collection. Pedon A is the background or the control unit, pedon B or the discharge point is the cassava mill effluent (CME) receiving unit and pedon C is the down stream, 500m away from pedon B. the result showed high values of soil physiochemical properties(mainly the heavy metals) at pedon B and the trend reduced away from pedon B and lowest in pedon A. In terms of pedons the heavy metal concentrations took this trend; pedon B>pedon C>pedonA. pH relationship with heavy metals in pedons A and B showed positive linear relationships with their coefficient of linearity(R2) ranging between 0.70-0.92 while other soil physiochemical properties obeyed polynomial relationships at reasonably high coefficient of fitness. Polynomial models fitted the pH relationships virtually in all the selected physiochemical properties of pedon C. The models have provided quick assessment of these physiochemical materials by mere determining the pH value and substituting the pH values into the models to predicting other properties.