Optimizing Solid Waste Management in Ajmer: Forecasting Waste Generation and Financial Requirements Using Statistical Models

Environmental Engineering

Abstract Effective solid waste management (SWM) is essential for achieving sustainable urban development, especially in rapidly urbanizing cities such as Ajmer, Rajasthan. This study addresses two primary objectives: (1) forecasting solid waste generation (SWG) rates using the Double Exponential Smoothing (DES) model, and (2) estimating financial requirements for SWM using both DES and Double Moving Average (DMA) statistical models. Historical data from 2007 to 2011, obtained from the Ajmer Municipal Corporation (AMC), were utilized to forecast SWG rates and financial needs for the period 2012–2016 across six administrative zones. Results reveal significantly higher SWG rates in central urban zones, attributable to increased population density and rapid urban expansion. Among the two methods, DES demonstrated greater accuracy for financial forecasting, as evidenced by lower mean square error values. The findings offer practical insights for developing strategic, zone-specific waste management plans and sustainable financial allocation frameworks. Future research is recommended to explore optimization of waste transportation logistics and the integration of smart technologies aimed at waste minimization and system efficiency.

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