Describing variability of MSW composition data with the log-logistic distribution |
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Authors: | Mark W Milke Vincent Wong Edward A McBean |
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Affiliation: | Department of Civil Engineering, University of Canterbury, Christchurch, New Zealand. mark.milke@canterbury.ac.nz |
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Abstract: | Variations in solid waste composition data are necessary as inputs to solid waste planning, yet uncertainty exists regarding which probability distributions might be generally valuable to describe the variability. Twenty-two detailed analyses of solid waste from British Columbia, Canada, were fitted to distributions using the BestFit software. Alternative distributions were ranked based on three goodness-of-fit parameters and twelve waste fractions. The log-logistic distribution was found to be the most able to fit over the wide range of composition types considered. The results were demonstrated to be insensitive to the number of waste components or to the choice of a two- or three-parameter distribution. Although other distributions were able to better match the waste composition for individual waste types, the log-logistic distribution was demonstrated to fit, overall, a wide variety of waste composition types. |
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