Modeling Bioremediation Of A Petroleum Contaminated Soil Enhanced With Npk Fertilizer And Animal/Plant Derived Organic Manure

ABSTRACT

In this study, the potential effects of animal derived organic manure (cow dung, poultry droppings), saw dust and NPK fertilizer on the bioremediation of petroleum hydrocarbon contaminated soil was investigated. The rate of biodegradation was studied for the period of 10 weeks under laboratory conditions. The biodegradation data were fitted to eight models, four of which are based on microbial growth rate and the other four based on order of reaction. Results obtained show that bioremediation with NPK fertilizer and poultry manure followed the logistic growth curve with a constant yield i.e (the ratio of microbial population increase per unit substrate consumed being constant). While treatment with blend of poultry+cow+saw dust occurred with the logistic growth curve with varying yield. It was observed that at optimum addition of NPK fertilizer and poultry manure, the process obeyed same trend as observed when a combination of poultry+cow+sawdust was applied. The result obtained showed a significant correlation coefficients well as higher degradation rate constant. It also revealed bioremediation as basically a first order process at low and moderate addition of biostimulants. NPK fertilizer and poultry manure obeyed first order rate model with ultimate contaminant greater than zero. It was also observed that application of NPK fertilizer and animal manure at an increased quantity without combinations offer similar effect with poultry+cow+saw dust i.e both followed second order rate model in which ultimate contaminant zero. Consequently, the result of the percentage degradation of hydrocarbon for the soil sample studied revealed that the rate of hydrocarbon biodegradation was in the following order (83.5%) > (72.6%) > (68.31%) for biotreatment with blend of poultry+cow+sawdust, poultry manure and NPK fertilizer respectively. The observations from the mathematical model, graphical and numerical fits results show that the proposed models employed in this work rather than the usual first order rate model were effective in predicting the bioremediation process.