Forecasting Solid Waste Generation Rates
Design of efficient solid waste management (SWM) systems requires accurate estimates of waste generation rates. Waste generation rates can be measured by direct sampling and several methods like database mining and sample surveys have been used in differe
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Abstract Design of efficient solid waste management (SWM) systems requires accurate estimates of waste generation rates. Waste generation rates can be measured by direct sampling and several methods like database mining and sample surveys have been used in different locations. Another approach is to use different types of models to predict or forecast waste generation rates based on knowledge of impacting factors. These models include statistical models like multiple linear regression, econometric models, system dynamics methods, time-series analysis, factor analysis and Geographical Information Systems (GIS)-based methods. More non-conventional methods like artificial neural networks (ANN), fuzzy logic (FL) and support vector machine (SVM) methods are becoming popular. A brief literature review of these methods used by researchers for forecasting solid waste generation rates is provided in this chapter.
Keywords Statistical Econometric Regression Sampling Soft computing Solid waste generation models Economic solid waste management
Introduction The objective of Solid Waste Management (SWM) is to control the functions of generation, collection, separation, transfer and transport, treatment and disposal of SW so that there are no adverse effects on either public health or the environment. Thus, efficient management of municipal solid waste (MSW) has become a major concern for urban local bodies (ULBs) throughout the world, especially the developing world. Several factors need to be accounted for in MSW management such as economic, technical, environmental, legislative, and political. Successful B. Bardhan T. Hazra Civil Engineering Department, Jadavpur University, Kolkata, India S. Goel (&) V.P. Ranjan Civil Engineering Department, IIT Kharagpur, Kharagpur, India e-mail: [email protected]; [email protected] © Springer Science+Business Media Singapore 2017 D. Sengupta and S. Agrahari (eds.), Modelling Trends in Solid and Hazardous Waste Management, DOI 10.1007/978-981-10-2410-8_3
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design of treatment facilities and implementation of SWM policies depends on reliable statistics regarding solid waste generation rates, composition, and characteristics. In general, data regarding MSW generation or collection are collected on a regular basis in middle- and high-income countries while data are extremely difficult to obtain in developing countries like India since routine monitoring and data collection are rarely done. In such cases, SW collection data are used to estimate generation rates. Since knowledge of SW generation rates is the basis of all SWM strategies, there has been growing interest and research activity in this area in the last few decades. A brief literature review about factors affecting solid waste (SW) generation rates, and models developed and used for forecasting SW generation rates is presented in this chapter.
Factors Affecting Solid Waste Generation Rates SW generation rates have been increasing all over the world mainly due to increase in
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