Development of a Simple to use Regression Model for Estimating the Energy Value of Municipal Solid Waste

Aibangbe, O, Ehiorobo, J.O, Ilaboya, I.R, Ihimekpen, N.I

Abstract


In Nigeria and many other African countries, the volume of solid waste generated continues to increase coupled with lack of infrastructure for adequate waste treatment. Nigeria with a population growth rate of about 2.8% per annum and an urban growth rate of about 5.5 % per annum generates about 0.58 kg solid waste per person per day. The focus of this study is to develop a simple regression model for estimating the energy value of municipal solid waste components.The study took a comprehensive evaluation of the solid waste composition in seven major communities in Benin City; Edo State Nigeria. The communities include; Evbuotubu, Ekenwan, Ikpoba- Hill, Ogbebuya, New Benin Oko-Central and Ugbowo. Solid waste survey/ collection using the stratified random sampling approach was done on a daily bases for a period of eight (8) weeks in order to generate enough data for specific analysis. In addition to the stratified random sampling approach 400 survey questionnaires were administered to 400 households (400) per community in order to acquire information about residents’ attitudes towards waste, socio-economic characterization including waste management behaviour etc. To determine the economic value of the waste, analytical method for energy value estimation was employed while the least square regression approach was used to develop the mathematical model for predicting the energy value of solid waste. To validate the reliability of the regression model, selected goodness of fit statistics, namely; coefficient of determination (R2), correlation coefficient (r), Adjusted Coefficient of Determination (Adj. R2) and error sum of square (SSE) were employed.From the energy value estimation, it was observed that 99,693.86KJ/kg of energy was obtain for waste collected from Evbuotubu, 65,599.30 KJ/kg for waste collected from Ekenwan, 68,638.31 KJ/kg for waste collected from Ikpoba Hill, 110,904.98 KJ/kg for waste collected from New Benin, 90,301.96 KJ/kg for waste collected from Ogbebuya, 89,513.86 KJ/kg for waste collected from Oko Central and 79,861.51 KJ/kg for waste collected from Ugbowo. With a coefficient of determination (R2) value of 0.992832 and Adjusted R-Squared value of 0.990784, it was concluded that the regression model developed for predicting the energy value is valid.

Keywords: Waste characterization, Energy value, Least square regression, Dependent variables, Independent variables and Sustainable Waste Management

DOI: 10.7176/CER/14-5-04

Publication date:August 31st 2022


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ISSN (Paper)2224-5790 ISSN (Online)2225-0514

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