Forecasting of municipal solid waste quantity and quality in a developing region using regression predictive models

Updated waste composition information relation using economic, socio-demographic and management data will identify possible factors that will help in selecting the crucial design options and the setting of an adequate framework to improve the sustainable planning, management and operation of solid waste facilities. To this direction this paper presents the results of a study performed in Nablus and Jenin Districts, West Bank, which involves application of efficient mathematical models to predict the future generation rates and components of municipal solid waste generation in the given area. Monthly quantities of solid waste in the two aforementioned governorates were compiled for the years of 2011-2013 while simultaneously data was collected to identify waste composition. The mean value of the daily generated solid waste is found to be 0.95 kg/cap/day. Seven multiple- variable regression equations and models are derived for estimating the monthly generated total solid waste and its components. The results were crosschecked with the introduction of appropriate indicators which established the models high reliability and significance in predicting the components of SW. The developed models' results aim to assist the decision-makers to better organise and plan the SWM in the areas of interest as well as step in the design and plan of the SWM facilities to ensure their sustainable operation in the future. © 2019 Widener University School of Civil Engineering. All rights reserved.