Numerical Prediction of Ammoniacal Nitrogen Concentrations Profile in Soil within the Vicinity of Soluos Dumpsite in Lagos State, Nigeria

L. Salami *

Environmental Engineering Research Unit, Department of Chemical and Polymer Engineering, Lagos State University, Epe, Lagos State, Nigeria.

A. A. Susu

Department of Chemical Engineering, University of Lagos, Akoka, Yaba, Lagos State, Nigeria.

O. Koleola

Department of Energy and Environmental Engineering, Edinburgh Napier University, Edinburgh, Scotland, United Kingdom.

*Author to whom correspondence should be addressed.


Abstract

The presence of pollutants in soil is a threat not only to human life but also to surface and groundwater integrity as well as the vegetations in the area. This work was carried out to predict the ammonia nitrogen concentrations in soil within the vicinity of Soluos dumpsite in Lagos state of Nigeria. A one – dimensional transport model of David and Peter was used in this work. The model was solved using explicit finite difference method implemented in Matlab 7.9 with the aid of model parameters obtained through screening method of sensitivity analysis of model parameters of Bhamnani and Singh. The predicted results revealed a regular trend of decreasing ammonia nitrogen concentrations as the depth increases downward in the soil which was in line with the experimental data used for the validation of the predicted results. The experimental data validated the predicted results to a 99 percent confidence level. This indicated that the model parameters used in this work are suitable for Soluos dumpsite and the one – dimensional transport model employed is useful in the prediction of ammonia nitrogen concentrations in the soil. 

Keywords: Numerical prediction, organic pollutant, concentration, profile, soil and dumpsite


How to Cite

Salami, L., A. A. Susu, and O. Koleola. 2017. “Numerical Prediction of Ammoniacal Nitrogen Concentrations Profile in Soil Within the Vicinity of Soluos Dumpsite in Lagos State, Nigeria”. Current Journal of Applied Science and Technology 22 (1):1-7. https://doi.org/10.9734/CJAST/2017/33034.

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