Abstract
Current methodologies for estimating the number of waste sorts require prior information on statistics (mean and standard deviation) for specific waste categories. The methods often require an iterative procedure or computer software to estimate the number of sorts required and the required statistics may change both spatially and temporally. To overcome the need for prior statistical information and avoid the need for iterative effort, a real-time methodology is developed to determine the required number of waste sorts for a waste category while sampling in the field for solid waste characterization. The information on required numbers of waste sorts is field-based and evolves during the sampling by utilizing real-time data to characterize the means and standard deviations. The proposed approach does not require prior information. The application of proposed methodology is demonstrated using the data from the Greater Vancouver Regional District (GVRD) for the primary categories of paper, glass, and secondary category glass-beverage.
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