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Applying mathematical modeling for predicting urban road traffic noise levels in Port Harcourt Metropolis, Nigeria

George Daye Mandy C. and Okeke Peter Ndu

An attempt was made to assess the noise levels of 10 locations in Port Harcourt metropolis, Nigeria, during four periods of the day using noise dosimeter and prediction model. On subjecting the data generated by both methods of measurement, using pearson’ product moment correlation (r), the result revealed that there was strong relationship between the actual and predicted equivalent noise levels (Leqs). To further confirm the applicability, the data was subjected to single factor anova and the result showed that there was no statistically significant difference (P>0.05). Comparison of predicted equivalent noise level with that of actual measured data demonstrated that the model used for the prediction has the ability to calibrate urban traffic noise and yielded reliable results close to that by direct measurement. After comparison of results it was observed that Calixto model could be satisfactorily applied for the Nigerian conditions as they give acceptable results with good “r” value

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