ABSTRACT

 The increasing contamination of soil by spent oil is very common and of great concern to our society because of the possible harm that it can cause the environment. Remediation of contaminated soil is the application ofsuitable techniques in the removal of contaminants present in soil. Contaminants like heavy metals and aromatic hydrocarbons are found in spent oil as a result of reactions in engines occurring during use of various lubricants. The study was set up to evaluates the selected heavy metals (Pb, Fe, Cd) in spent oil contaminated soil using mariscus alternifolius augumented with pig dung. Pig dung was added to soil contaminated by spent oil. After forty eight (48) hours, the concentration of heavy metals ( Cd, Pb, and Fe) and Polyaromatic Hydrocarbons (PAHs) in the soil residue were determined. A control experiment was carried out for a soil sample with no spent oil added to it. The control experiment indicated that PAHs were not present in the soil before introduction ofspent oil. Pig dung was found to be effective in remediation of soils contaminated by low concentrations of spent oil. Phytoremediation is an emerging technology that employs the use of higher plants for the cleanup of contaminated environments. Fundamental and applied research have unequivocally demonstrated that selected plant species possess the genetic potential to remove, degrade, metabolize, or immobilize a wide range of contaminants. Thus, an understanding of the basic plant mechanisms, and the effect of agronomic practices on plant/soil/contaminant interaction would allow practitioners to optimize phytoremediation by customizing the process to site specific conditions. Unlike organic contaminants, metals cannot be degraded. Commonly, decontamination of metal-contaminated soils requires the removal of toxic metals. Recently, phytoextraction, the use ofplants to extract toxic metals from contaminated soils, has emerged as a cost-effective, environment friendly cleanup alternative. Data obtained from the study were statistical treated by analysis of variance using IBM SPSS (statistical package for social science), version 22.0 and graphically represented using tables and charts. Samples where significant at (P<0.05). Multiple comparism ofmean was done using Duncan significant test level.