Forecasting and Planning for Solid Waste Generation in the Kumasi Metropolitan Area of Ghana: An ARIMA Time Series Approach
Author(s): Ebenezer Owusu-Sekyere, Emmanuel Harris, Ebenezer Bonyah
One major challenge facing the Kumasi Metropolitan Area (KMA) is the inability of city authorities to manage solid waste due to lack of proper planning and the inability of the authorities to forecast and predict the quantity of solid waste that will be generated in the coming years, based on current trends. This research, which is a predictive study, uses the Autoregressive Integrated Moving Average (ARIMA) time series model to explore the dynamics of solid waste generation and also forecast monthly solid waste generation in the KMA. This study used monthly solid waste generation data from 2005 to 2010 that was obtained from the solid waste department of the Kumasi Metropolitan Assembly. The data was analyzed by applying ARIMA time series model. The results showed that in general, the trend of solid waste generation peaked in December 2008. The analysis indicated that ARIMA (1, 1, 1) was the best model for forecasting solid waste generation in the KMA. The forecast revealed that for the next couple of years, the generation of solid waste will continue to increase as a result of the high rate of urbanization in the metropolis. The research is therefore of the view that sustainable solid management programmes should be put in place to rescue the current situation and also plan for the anticipated solid waste predicted by the research.
Solid waste, Autoregressive (AR), Moving Average (MA) and ARIMA
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International Journal of Sciences is Open Access Journal.
This article is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) License.
Author(s) retain the copyrights of this article, though, publication rights are with Alkhaer Publications.
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