International Journal of Science and Technology

International Journal of Science and Technology>> Volume 7, Number 6, June 2017

International Journal of Science and Technology

Multiple Linear Regression Model for the Estimation of Sulphur Dioxide in Aba Urban, Nigeria

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Author Agbanyim Akuagwu N., Kalu A. U., Ejike E.N.
Volume No. 5
Issue No. 9
Issue Date September 01, 2015
Publishing Date September 01, 2015
Keywords Multiple Linear Regression Model; Atmospheric pollution, Analysis of variance, Correlation coefficient, Coefficient of determination.


Atmospheric pollution has continued to increase exponentially with increase in domestic and industrial activities in major urban and sub-urban cities of the world. Sulphur dioxide and other oxides of Sulphur are component of atmospheric pollution. It has continued to be a global problem due to its adverse effect on both the environment and on human health. Aba being a growing commercial and industrializing urban city in Nigeria is very much at risk of the negative effect of atmospheric pollution. There is therefore a need to constantly monitor the level of Sulphur dioxide in the Atmosphere to prevent it from reaching a level that will be dangerous for human existence in Aba and its environs. The relationship between Sulphur dioxide and four meteorological variables - Wind Speed, Temperature, Relative Humility and Light Intensity, were investigated in Aba urban, using the multiple linear regression technique. The model was found to be: SO_2=-670.87-10.52WS+10.84TP+6.72RM-0.02LI The analysis of variance (ANOVA) conducted on the model shows that it was statistically significant and so a good model for the estimation of Sulphur Dioxide in the Atmosphere in that area. All the assumptions of the model were checked but none of them, including the assumptions of Normality, Linearity, Homoscedasticity and Independence of residuals were violated.

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