An evaluation of municipal solid waste composition bias sources

    Authors

    H. Sfeir; D. R. Reinhart;P. R. McCauley-Bell

    Comments

    Authors: contact us about adding a copy of your work at STARS@ucf.edu

    Abbreviated Journal Title

    J. Air Waste Manage. Assoc.

    Keywords

    Engineering, Environmental; Environmental Sciences; Meteorology &; Atmospheric Sciences

    Abstract

    The University of Central Florida (UCF) was contracted by the Florida Center for Solid and Hazardous Waste Management (FCSHWM) to develop a well-defined methodology for conducting municipal solid waste composition studies. This methodology must account for the statistical variations in waste composition, be economical and practical in implementation and build on a consensus of waste management professionals. This paper identifies possible sources of bias in waste composition study results and provides guidance for future planning of local waste stream composition analysis. To accomplish this objective, a composition study was designed and implemented for Marion County, FL, in fall 1996. The potential sources of concern investigated in detail were sample weight and contamination. The methodology developed by UCF is statistically valid and if widely implemented would provide a better representation of the waste stream. Lack of contamination adjustment is a major contributor to error in the waste stream analysis and should be accounted for in the methodology. For sample sorts using a large number of categories, sample size may be a contributor to bias. This likelihood for bias can be reduced by increasing the sample weight to at least 200 kg, particularly when sorting commercial loads or reducing the number of categories.

    Journal Title

    Journal of the Air & Waste Management Association

    Volume

    49

    Issue/Number

    9

    Publication Date

    1-1-1999

    Document Type

    Article

    Language

    English

    First Page

    1096

    Last Page

    1102

    WOS Identifier

    WOS:000082832900010

    ISSN

    1047-3289

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