Forecasting of solid waste quantity and composition: a multilinear regression and system dynamics approach
In the present study, a multiple linear regression model and system dynamics model have been proposed for forecasting municipal solid waste quantity and composition respectively. The system dynamics model is based on the comparison of results obtained using logistics, sigmoidal and growth kinetics functions. These models were applied for the case study of Delhi, the capital of India. From the results of the study, it was estimated that the daily solid waste generation rate, in Delhi, is likely to increase by more than 95% between 2011 and 2024. Further, it is estimated that there would also be a significant rise in paper and decrease in food, metals and others during the period. The contribution from the plastic and glass waste streams is expected to remain nearly constant. The changing waste characteristics shall be significantly influencing the choice of waste treatment and disposal technologies.
Keywords: solid waste management, municipal solid waste, MSW, forecasting, multiple linear regression modelling, system dynamics, long–term planning, solid waste quantity, solid waste composition, India, waste treatment, waste disposal, treatment technology, disposal technology
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